U.S. patent application number 15/926861 was filed with the patent office on 2018-07-26 for methods, compositions, and devices utilizing microrna to determine physiological conditions.
The applicant listed for this patent is Battelle Memorial Institute, Institute for Systems Biology, The Ohio State University Research Foundation. Invention is credited to David Galas, Richard Evan Gelinas, Clay Braden Marsh, Melissa Garnet Piper, Kai Wang, Shile Zhang.
Application Number | 20180208997 15/926861 |
Document ID | / |
Family ID | 41720584 |
Filed Date | 2018-07-26 |
United States Patent
Application |
20180208997 |
Kind Code |
A1 |
Galas; David ; et
al. |
July 26, 2018 |
METHODS, COMPOSITIONS, AND DEVICES UTILIZING MicroRNA TO DETERMINE
PHYSIOLOGICAL CONDITIONS
Abstract
Methods, compositions, and devices are disclosed which use
microRNA to detect, predict, treat, and monitor physiological
conditions such as disease or injury. microRNA are isolated and
their differential expression is measured to provide diagnostic
information. This information may then be utilized for evaluation
and/or treatment purposes.
Inventors: |
Galas; David; (Seattle,
WA) ; Gelinas; Richard Evan; (Seattle, WA) ;
Marsh; Clay Braden; (Columbus, OH) ; Piper; Melissa
Garnet; (Powell, OH) ; Wang; Kai; (Bellevue,
WA) ; Zhang; Shile; (Seattle, WA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Battelle Memorial Institute
Institute for Systems Biology
The Ohio State University Research Foundation |
Columbus
Seattle
Columbus |
OH
WA
OH |
US
US
US |
|
|
Family ID: |
41720584 |
Appl. No.: |
15/926861 |
Filed: |
March 20, 2018 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
14300071 |
Jun 9, 2014 |
|
|
|
15926861 |
|
|
|
|
12615969 |
Nov 10, 2009 |
8748101 |
|
|
14300071 |
|
|
|
|
61112985 |
Nov 10, 2008 |
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
C12Q 2600/178 20130101;
C12Q 2600/158 20130101; C12Q 1/6883 20130101; C12Q 1/6827 20130101;
C12Q 1/6886 20130101; C12Q 2600/142 20130101 |
International
Class: |
C12Q 1/6886 20060101
C12Q001/6886; C12Q 1/6827 20060101 C12Q001/6827; C12Q 1/6883
20060101 C12Q001/6883 |
Claims
1. A method of detecting or predicting a neurological condition,
comprising: generating a first microRNA profile from a biological
sample, wherein the first microRNA profile comprises the amount of
at least one specific microRNA sequence, by: receiving the
biological sample, the sample being a tissue, serum, or plasma; and
isolating microRNA from the biological sample by extracting the
microRNA with an organic solvent and obtaining an aqueous phase
containing the microRNA, then purifying the aqueous phase through a
silica membrane to isolate the microRNA; using hybridization to
identify the microRNA sequences; and measuring the amount of at
least one specific microRNA sequence; and comparing the amount of
the at least one specific microRNA sequence to a reference to
provide information for detecting or predicting the neurological
condition.
2. The method of claim 1, wherein the at least one specific
microRNA sequence is selected from the group consisting of let-7g,
miR-298, miR-1, miR-101a*, miR-101b, miR-1224, miR-126-5p, miR-127,
miR-128, miR-129-3p, miR-133b, miR-136, miR-138, miR-138*,
miR-139-3p, miR-140, miR-140*, miR-142-3p, miR-143, miR-146a,
miR-146b, miR-148b, miR-150, miR-15a*, miR-15b, miR-181b, miR-181d,
miR-183, miR-185, miR-186, miR-191*, miR-194, miR-19a, miR-200a,
miR-200b, miR-200b*, miR-202-3p, miR-206, miR-208a, miR-21,
miR-211, miR-221, miR-222, miR-223, miR-27a, miR-27b*, miR-28*,
miR-290-5p, miR-291a-5p, miR-297a, miR-299, miR-29b, miR-29c*,
miR-301b, miR-302c*, miR-30c, miR-31, miR-322, miR-323-3p,
miR-324-3p, miR-324-5p, miR-326, miR-328, miR-331-5p, miR-341,
miR-34b-5p, miR-34c*, miR-369-3p, miR-374, miR-376b, miR-379,
miR-380-3p, miR-382, miR-384-5p, miR-409-5p, miR-411, miR-411*,
miR-423-5p, miR-425, miR-429, miR-434-5p, miR-450b-3p, miR-451,
miR-455, miR-465c-3p, miR-466d-5p, miR-467e*, miR-484, miR-486,
miR-487b, miR-497, miR-505, miR-511, miR-539, miR-540-3p, miR-551b,
miR-568, miR-654-5p, miR-669a, miR-686, miR-688, miR-699, miR-701,
miR-706, miR-708, miR-720, miR-721, miR-744*, miR-760, miR-770-5p,
miR-7a, miR-7b, miR-881*, miR-93, miR-96, mghv-miR-M1-6,
mghv-miR-M1-9, and human orthologs thereof.
3. The method of claim 2, wherein the biological sample is serum or
plasma; and further comprising generating a second microRNA profile
from cerebrospinal fluid, wherein the second microRNA profile
comprises the amount of at least one specific microRNA sequence
selected from the group consisting of miR-134, miR-151-5p,
miR-223*, miR-302d, miR-325, miR-335*, miR-377*, miR-483-5p,
miR-505, miR-509-5p, miR-515-3p, miR-518e, miR-556-3p, miR-589,
miR-616*, miR-652, miR-767-3p, miR-873, miR-892a, miR-923, and
human orthologs thereof.
4. The method of claim 3, wherein at least two differentially
expressed microRNA sequences are identified in the first microRNA
profile and at least two differentially expressed microRNA
sequences are identified in the second microRNA profile.
5. The method of claim 4, wherein the at least two differentially
expressed microRNA sequences in the first microRNA profile are
different from the at least two differentially expressed microRNA
sequences in the second microRNA profile.
6. The method of claim 1, wherein the at least one specific
microRNA sequence is selected from the group consisting of miR-122,
miR-124, miR-124a, miR-124b, miR-128a, miR-128b, miR-129, miR-132,
miR-134, miR-137, miR-138, miR-149, miR-153, miR-154*, miR-181a,
miR-181b, miR-181bN, miR-181c, miR-181d, miR-184, miR-204, miR-213,
miR-219, miR-323, miR-324-5p, miR-328, miR-330, miR-338, miR-340,
miR-342, miR-348, miR-370, miR-379, miR-383, miR-432, miR-433,
miR-485-3p, miR-485-5p, miR-491, miR-9, miR-9*, and human orthologs
thereof.
7. The method of claim 1, wherein the at least one specific
microRNA sequence is selected from the group consisting of miR-134,
miR-151-5p, miR-223*, miR-302d, miR-325, miR-335*, miR-377*,
miR-483-5p, miR-505, miR-509-5p, miR-515-3p, miR-518e, miR-556-3p,
miR-589, miR-616*, miR-652, miR-767-3p, miR-873, miR-892a, miR-923,
and human orthologs thereof.
8. The method of claim 1, wherein the at least one specific
microRNA sequence is selected from the group consisting of let-7g,
miR-298, miR-1, miR-101a*, miR-101b, miR-1224, miR-126-5p, miR-127,
miR-128, miR-129-3p, miR-133b, miR-136, miR-138, miR-138*,
miR-139-3p, miR-140, miR-140*, miR-142-3p, miR-143, miR-146a,
miR-146b, miR-148b, miR-150, miR-15a*, miR-15b, miR-181b, miR-181d,
miR-183, miR-185, miR-186, miR-191*, miR-194, miR-19a, miR-200a,
miR-200b, miR-200b*, miR-202-3p, miR-206, miR-208a, miR-21,
miR-211, miR-221, miR-222, miR-223, miR-27a, miR-27b*, miR-28*,
miR-290-5p, miR-291a-5p, miR-297a, miR-299, miR-29b, miR-29c*,
miR-301b, miR-302c*, miR-30c, miR-31, miR-322, miR-323-3p,
miR-324-3p, miR-324-5p, miR-326, miR-328, miR-331-5p, miR-341,
miR-34b-5p, miR-34c*, miR-369-3p, miR-374, miR-376b, miR-379,
miR-380-3p, miR-382, miR-384-5p, miR-409-5p, miR-411, miR-411*,
miR-423-5p, miR-425, miR-429, miR-434-5p, miR-450b-3p, miR-451,
miR-455, miR-465c-3p, miR-466d-5p, miR-467e*, miR-484, miR-486,
miR-487b, miR-497, miR-505, miR-511, miR-539, miR-540-3p, miR-551b,
miR-568, miR-654-5p, miR-669a, miR-686, miR-688, miR-699, miR-701,
miR-706, miR-708, miR-720, miR-721, miR-744*, miR-760, miR-770-5p,
miR-7a, miR-7b, miR-881*, miR-93, miR-96, mghv-miR-M1-6,
mghv-miR-M1-9; miR-122, miR-124, miR-124a, miR-124b, miR-128a,
miR-128b, miR-129, miR-132, miR-134, miR-137, miR-138, miR-149,
miR-153, miR-154*, miR-181a, miR-181b, miR-181bN, miR-181c,
miR-181d, miR-184, miR-204, miR-213, miR-219, miR-323, miR-324-5p,
miR-328, miR-330, miR-338, miR-340, miR-342, miR-348, miR-370,
miR-379, miR-383, miR-432, miR-433, miR-485-3p, miR-485-5p,
miR-491, miR-9, miR-9*; miR-134, miR-151-5p, miR-223*, miR-302d,
miR-325, miR-335*, miR-377*, miR-483-5p, miR-505, miR-509-5p,
miR-515-3p, miR-518e, miR-556-3p, miR-589, miR-616*, miR-652,
miR-767-3p, miR-873, miR-892a, miR-923; and human orthologs
thereof.
9. The method of claim 1, wherein the at least one specific
microRNA sequence is a plurality of microRNA sequences.
10. The method of claim 1, wherein the at least one specific
microRNA sequence is selected from the group consisting of let-7g,
miR-298, miR-1, miR-101a*, miR-101b, miR-1224, miR-126-5p, miR-127,
miR-128, miR-129-3p, miR-133b, miR-136, miR-138, miR-138*,
miR-139-3p, miR-140, miR-140*, miR-142-3p, miR-143, miR-146a,
miR-146b, miR-148b, miR-150, miR-15a*, miR-15b, miR-181b, miR-181d,
miR-183, miR-185, miR-186, miR-191*, miR-194, miR-19a, miR-200a,
miR-200b, miR-200b*, miR-202-3p, miR-206, miR-208a, miR-21,
miR-211, miR-221, miR-222, miR-223, miR-27a, miR-27b*, miR-28*,
miR-290-5p, miR-291a-5p, miR-297a, miR-299, miR-29b, miR-29c*,
miR-301b, miR-302c*, miR-30c, miR-31, miR-322, miR-323-3p,
miR-324-3p, miR-324-5p, miR-326, miR-328, miR-331-5p, miR-341,
miR-34b-5p, miR-34c*, miR-369-3p, miR-374, miR-376b, miR-379,
miR-380-3p, miR-382, miR-384-5p, miR-409-5p, miR-411, miR-411*,
miR-423-5p, miR-425, miR-429, miR-434-5p, miR-450b-3p, miR-451,
miR-455, miR-465c-3p, miR-466d-5p, miR-467e*, miR-484, miR-486,
miR-487b, miR-497, miR-505, miR-511, miR-539, miR-540-3p, miR-551b,
miR-568, miR-654-5p, miR-669a, miR-686, miR-688, miR-699, miR-701,
miR-706, miR-708, miR-720, miR-721, miR-744*, miR-760, miR-770-5p,
miR-7a, miR-7b, miR-881*, miR-93, miR-96, mghv-miR-M1-6,
mghv-miR-M1-9, and human orthologs thereof.
11. The method of claim 1, wherein the at least one specific
microRNA sequence is selected from the group consisting of let-7g,
miR-298, miR-101a*, miR-101b, miR-1224, miR-126-5p, miR-128,
miR-129-3p, miR-133b, miR-138*, miR-139-3p, miR-140*, miR-146a,
miR-148b, miR-15a*, miR-15b, miR-181b, miR-181d, miR-185, miR-186,
miR-191*, miR-19a, miR-200b*, miR-202-3p, miR-208a, miR-211,
miR-27b*, miR-28*, miR-290-5p, miR-291a-5p, miR-297a, miR-299,
miR-29c*, miR-301b, miR-302c*, miR-322, miR-323-3p, miR-324-3p,
miR-324-5p, miR-326, miR-328, miR-331-5p, miR-341, miR-34b-5p,
miR-34c*, miR-369-3p, miR-374, miR-376b, miR-379, miR-380-3p,
miR-382, miR-384-5p, miR-409-5p, miR-411, miR-411*, miR-423-5p,
miR-425, miR-429, miR-434-5p, miR-450b-3p, miR-465c-3p,
miR-466d-5p, miR-467e*, miR-505, miR-511, miR-539, miR-540-3p,
miR-551b, miR-568, miR-654-5p, miR-669a, miR-686, miR-688, miR-699,
miR-701, miR-706, miR-720, miR-721, miR-744*, miR-760, miR-770-5p,
miR-7a, miR-7b, miR-881*, miR-96, mghv-miR-M1-6, mghv-miR-M1-9, and
human orthologs thereof.
12. A method of using microRNA to monitor a neurological condition,
comprising: generating a first microRNA profile from a first
biological sample of a patient; administering a treatment to the
patient; generating a second microRNA profile from a second
biological sample of the patient; comparing the second microRNA
profile with the first microRNA profile to identify differentially
expressed microRNA sequences; and identifying a change in the
neurological condition based on the identity or the amounts of the
differentially expressed microRNA sequences.
Description
[0001] This application is a divisional of U.S. patent application
Ser. No. 14/300,071, filed Jun. 9, 2014, which is a continuation of
U.S. patent application Ser. No. 12/615,969, now U.S. Pat. No.
8,748,101, which claims priority to U.S. Provisional Patent
Application Ser. No. 61/112,985, filed Nov. 10, 2008. The contents
of these applications are hereby fully incorporated by reference in
its entirety.
BACKGROUND
[0002] Disclosed herein are various methods, compositions, and
devices utilizing microRNA, such as microRNA-based markers, to
detect, predict, treat, or monitor various physiological or
pathological conditions.
[0003] The ideal diagnostic marker has to fulfill certain key
requirements including being specific, sensitive, robust, and
non-invasive. Current disease diagnoses are primarily based on two
different but complementary approaches--physical imaging and
biomolecular profiling. Both approaches currently suffer from a
lack of specificity and early detection capability. Tissue-specific
blood biomarkers can increase the specificity to selected organs.
However, the levels of these tissue-specific biomarkers are usually
low in blood. In addition, the difficulty of developing suitable
capture agents for proteins makes the identification and
development of new molecular diagnostic markers difficult.
[0004] It would be desirable to provide new methods, compositions,
and devices for diagnosing physiological and pathological
conditions.
BRIEF DESCRIPTION
[0005] The present disclosure relates, in different embodiments, to
the use of the levels of microRNA sequences (miRNA) in body fluids
to establish correlations with the body's pathophysiological
conditions. Exemplary body fluids include, but are not limited to,
serum, plasma, saliva, urine, tears, amniotic fluid, sweat,
cerebrospinal fluid, seminal fluid (semen), lung mucus (e.g. from
bronchial lavage), pleural fluid, peritoneal fluid, colostrums, and
breast milk. These levels can then provide diagnostic and/or
predictive information with regard to important issues of health
and disease.
[0006] Disclosed are methods of using microRNA sequences to detect
a physiological condition. The methods comprise: isolating microRNA
sequences from a biological sample; generating a microRNA profile
from the isolated microRNA sequences, the profile including the
levels of expressed microRNA sequences in the biological sample;
comparing the microRNA profile with a reference to identify
differentially expressed microRNA sequences; and detecting the
physiological condition based on the identity or the levels of the
differentially expressed microRNA sequences.
[0007] The biological sample may be a biopsy material, tissue, or
body fluid. In embodiments, the biological sample comprises a body
fluid selected from the group consisting of serum, plasma, lymph,
saliva, urine, tears, sweat, semen, synovial fluid, cervical mucus,
amniotic fluid, cerebrospinal fluid, and breast milk.
[0008] The microRNA sequences may be isolated by extracting the
biological sample with an organic solvent to obtain an aqueous
phase containing the microRNA sequences; and purifying the aqueous
phase through a silica membrane to isolate the microRNA
sequences.
[0009] The microRNA profile can be generated using hybridization to
identify a microRNA sequences; or by using a quantitative
polymerase chain reaction to identify the level of a microRNA
sequences.
[0010] The reference can be a table of the levels of expressed
microRNA sequences in a normal person, or a reference sample.
[0011] The biological sample may be from a microbe, such as a
virus, bacterium, fungus, protozoan, or parasite.
[0012] The isolated microRNA sequences may be specific to a
biological pathway, a cell type, or a tissue.
[0013] The physiological condition may be a disease, injury, or
infection.
[0014] Also disclosed are methods of using microRNA sequences to
detect or predict a physiological condition. These methods also
comprise: generating a microRNA profile from a biological sample,
the profile including the levels of expressed microRNA sequences in
the biological sample; and comparing the microRNA profile with a
reference to identify differentially expressed microRNA sequences.
The physiological condition could then be detected or predicted
based on the identity or the levels of the differentially expressed
microRNA sequences. Alternatively, the physiological condition can
be identified, and a treatment can then be administered based on
the identity of the physiological condition.
[0015] Further disclosed are methods of using microRNA sequences to
monitor a physiological condition, comprising: generating a first
microRNA profile from a first biological sample of a patient;
administering a treatment to the patient; generating a second
microRNA profile from a second biological sample of the patient;
comparing the second microRNA profile with the first microRNA
profile to identify differentially expressed microRNA sequences;
and identifying a change in the physiological condition based on
the identity or the amounts of the differentially expressed
microRNA sequences.
[0016] Additionally disclosed are methods of using microRNA
sequences to treat a physiological condition. The methods comprise:
identifying at least one microRNA sequence based on the
physiological condition; and manipulating the level of the at least
one microRNA sequence to treat the physiological condition.
Manipulating the level of the at least one microRNA sequence may
comprise: constructing a specific DNA or RNA sequence related to
the at least one microRNA sequence; and delivering the specific DNA
or RNA sequence to a targeted cell, tissue, or organ.
[0017] Also disclosed are methods of using microRNA sequences to
detect, predict, or treat a physiological condition. The methods
comprise: generating a microRNA profile from a biological sample;
identifying at least one differentially expressed microRNA sequence
by comparing the microRNA profile to a reference; and detecting,
predicting, or treating the physiological condition based on the
identity or the levels of the at least one differentially expressed
microRNA sequence. In alternative embodiments, at least two
differentially expressed microRNA sequences are identified.
[0018] Other methods of detecting or predicting a physiological
condition comprise generating a microRNA profile from a biological
sample, wherein the microRNA profile comprises at least one
specific microRNA sequence; and comparing the microRNA profile to a
reference to provide information useful for detecting or predicting
the physiological condition. In alternative embodiments, the
microRNA profile comprises at least two specific microRNA
sequences.
[0019] A differentially expressed microRNA sequence can be
identified by comparing the amount of a particular microRNA
sequence in the microRNA profile with the amount of that particular
microRNA sequence in the reference. A differentially expressed
microRNA sequence is identified when the ratio of the amount in the
microRNA profile to the amount in the reference is at least 1.5, or
at least 3.
[0020] When the physiological condition is related to liver disease
or liver injury, in some embodiments, the microRNA profile or the
specific microRNA sequence(s) may comprise at least one microRNA
sequence selected from the group consisting of mmu-miR-122,
mmu-miR-486, mmu-miR-125b-5p, mmu-let-7d*, mmu-miR-101a,
mmu-miR-101b, mmu-miR-1224, mmu-miR-124, mmu-miR-125a-3p,
mmu-miR-125a-5p, mmu-miR-127, mmu-miR-130a, mmu-miR-133a,
mmu-miR-133b, mmu-miR-135a*, mmu-miR-141, mmu-miR-193,
mmu-miR-193b, mmu-miR-199a-5p, mmu-miR-199b*, mmu-miR-200c,
mmu-miR-202-3p, mmu-miR-205, mmu-miR-22, mmu-miR-23b, mmu-miR-26a,
mmu-miR-27b, mmu-miR-291a-5p, mmu-miR-294*, mmu-miR-29b,
mmu-miR-30a, mmu-miR-30c-1*, mmu-miR-30e, mmu-miR-320, mmu-miR-327,
mmu-miR-339-3p, mmu-miR-342-3p, mmu-miR-370, mmu-miR-375,
mmu-miR-451, mmu-miR-466f-3p, mmu-miR-483, mmu-miR-494,
mmu-miR-574-5p, mmu-miR-652, mmu-miR-671-5p, mmu-miR-685,
mmu-miR-710, mmu-miR-711, mmu-miR-712, mmu-miR-714, mmu-miR-720,
mmu-miR-721, mmu-miR-877, mmu-miR-877*, mmu-miR-882, mmu-miR-93,
mmu-miR-99a, and human orthologs thereof.
[0021] In other embodiments where the physiological condition is
related to liver disease or liver injury, the microRNA profile or
the specific microRNA sequence may comprise at least one microRNA
sequence selected from the group consisting of mmu-miR-122,
mmu-miR-486, mmu-miR-125b-5p, mmu-let-7d*, mmu-miR-101a,
mmu-miR-101b, mmu-miR-1224, mmu-miR-124, mmu-miR-125a-3p,
mmu-miR-125a-5p, mmu-miR-133a, mmu-miR-133b, mmu-miR-135a*,
mmu-miR-193, mmu-miR-193b, mmu-miR-199a-5p, mmu-miR-199b*,
mmu-miR-202-3p, mmu-miR-291a-5p, mmu-miR-294*, mmu-miR-30c-1*,
mmu-miR-30e, mmu-miR-327, mmu-miR-339-3p, mmu-miR-342-3p,
mmu-miR-375, mmu-miR-466f-3p, mmu-miR-483, mmu-miR-574-5p,
mmu-miR-652, mmu-miR-671-5p, mmu-miR-685, mmu-miR-710, mmu-miR-711,
mmu-miR-712, mmu-miR-714, mmu-miR-720, mmu-miR-721, mmu-miR-877,
mmu-miR-877*, mmu-miR-882, and human orthologs thereof.
[0022] In particular embodiments, the at least one differentially
expressed microRNA sequence or the at least one specific sequence
comprises hsa-miR-122. In more specific embodiments, they comprise
hsa-miR-122 and either hsa-miR-486-3p or hsa-miR-486-5p (i.e. the
human orthologs to mmu-miR-486). The ratio of the amount of miR-122
to the amount of miR-486 may be greater than 4.0, including greater
than 6.0.
[0023] When the physiological condition is neurological disease or
neurological injury, in some embodiments, the microRNA profile or
the specific microRNA sequence may comprise at least one microRNA
sequence selected from the group consisting of mmu-let-7g,
mmu-miR-298, mmu-miR-1, mmu-miR-101a*, mmu-miR-101b, mmu-miR-1224,
mmu-miR-126-5p, mmu-miR-127, mmu-miR-128, mmu-miR-129-3p,
mmu-miR-133b, mmu-miR-136, mmu-miR-138, mmu-miR-138*,
mmu-miR-139-3p, mmu-miR-140, mmu-miR-140*, mmu-miR-142-3p,
mmu-miR-143, mmu-miR-146a, mmu-miR-146b, mmu-miR-148b, mmu-miR-150,
mmu-miR-15a*, mmu-miR-15b, mmu-miR-181b, mmu-miR-181d, mmu-miR-183,
mmu-miR-185, mmu-miR-186, mmu-miR-191*, mmu-miR-194, mmu-miR-19a,
mmu-miR-200a, mmu-miR-200b, mmu-miR-200b*, mmu-miR-202-3p,
mmu-miR-206, mmu-miR-208a, mmu-miR-21, mmu-miR-211, mmu-miR-221,
mmu-miR-222, mmu-miR-223, mmu-miR-27a, mmu-miR-27b*, mmu-miR-28*,
mmu-miR-290-5p, mmu-miR-291a-5p, mmu-miR-297a, mmu-miR-299,
mmu-miR-29b, mmu-miR-29c*, mmu-miR-301b, mmu-miR-302c*,
mmu-miR-30c, mmu-miR-31, mmu-miR-322, mmu-miR-323-3p,
mmu-miR-324-3p, mmu-miR-324-5p, mmu-miR-326, mmu-miR-328,
mmu-miR-331-5p, mmu-miR-341, mmu-miR-34b-5p, mmu-miR-34c*,
mmu-miR-369-3p, mmu-miR-374, mmu-miR-376b, mmu-miR-379,
mmu-miR-380-3p, mmu-miR-382, mmu-miR-384-5p, mmu-miR-409-5p,
mmu-miR-411, mmu-miR-411*, mmu-miR-423-5p, mmu-miR-425,
mmu-miR-429, mmu-miR-434-5p, mmu-miR-450b-3p, mmu-miR-451,
mmu-miR-455, mmu-miR-465c-3p, mmu-miR-466d-5p, mmu-miR-467e*,
mmu-miR-484, mmu-miR-486, mmu-miR-487b, mmu-miR-497, mmu-miR-505,
mmu-miR-511, mmu-miR-539, mmu-miR-540-3p, mmu-miR-551b,
mmu-miR-568, mmu-miR-654-5p, mmu-miR-669a, mmu-miR-686,
mmu-miR-688, mmu-miR-699, mmu-miR-701, mmu-miR-706, mmu-miR-708,
mmu-miR-720, mmu-miR-721, mmu-miR-744*, mmu-miR-760,
mmu-miR-770-5p, mmu-miR-7a, mmu-miR-7b, mmu-miR-881*, mmu-miR-93,
mmu-miR-96, mghv-miR-M1-6, mghv-miR-M1-9, and human orthologs
thereof.
[0024] In other embodiments where the physiological condition is
neurological disease or neurological injury, the microRNA profile
or the specific microRNA sequence may comprise at least one
microRNA sequence selected from the group consisting of mmu-let-7g,
mmu-miR-298, mmu-miR-101a*, mmu-miR-101b, mmu-miR-1224,
mmu-miR-126-5p, mmu-miR-128, mmu-miR-129-3p, mmu-miR-133b,
mmu-miR-138*, mmu-miR-139-3p, mmu-miR-140*, mmu-miR-146a,
mmu-miR-148b, mmu-miR-15a*, mmu-miR-15b, mmu-miR-181b,
mmu-miR-181d, mmu-miR-185, mmu-miR-186, mmu-miR-191*, mmu-miR-19a,
mmu-miR-200b*, mmu-miR-202-3p, mmu-miR-208a, mmu-miR-211,
mmu-miR-27b*, mmu-miR-28*, mmu-miR-290-5p, mmu-miR-291a-5p,
mmu-miR-297a, mmu-miR-299, mmu-miR-29c*, mmu-miR-301b,
mmu-miR-302c*, mmu-miR-322, mmu-miR-323-3p, mmu-miR-324-3p,
mmu-miR-324-5p, mmu-miR-326, mmu-miR-328, mmu-miR-331-5p,
mmu-miR-341, mmu-miR-34b-5p, mmu-miR-34c*, mmu-miR-369-3p,
mmu-miR-374, mmu-miR-376b, mmu-miR-379, mmu-miR-380-3p,
mmu-miR-382, mmu-miR-384-5p, mmu-miR-409-5p, mmu-miR-411,
mmu-miR-411*, mmu-miR-423-5p, mmu-miR-425, mmu-miR-429,
mmu-miR-434-5p, mmu-miR-450b-3p, mmu-miR-465c-3p, mmu-miR-466d-5p,
mmu-miR-467e*, mmu-miR-505, mmu-miR-511, mmu-miR-539,
mmu-miR-540-3p, mmu-miR-551b, mmu-miR-568, mmu-miR-654-5p,
mmu-miR-669a, mmu-miR-686, mmu-miR-688, mmu-miR-699, mmu-miR-701,
mmu-miR-706, mmu-miR-720, mmu-miR-721, mmu-miR-744*, mmu-miR-760,
mmu-miR-770-5p, mmu-miR-7a, mmu-miR-7b, mmu-miR-881*, mmu-miR-96,
mghv-miR-M1-6, mghv-miR-M1-9, and human orthologs thereof.
[0025] When the physiological condition is related to lung disease
or lung injury, in some embodiments, the microRNA profile or the
specific microRNA sequence may comprise at least one microRNA
sequence selected from the group consisting of hsa-miR-135a*,
hsa-miR-10b, hsa-miR-1224-3p, hsa-miR-1224-5p, hsa-miR-1225-3p,
hsa-miR-1225-5p, hsa-miR-1226*, hsa-miR-1227, hsa-miR-1228,
hsa-miR-1229, hsa-miR-1234, hsa-miR-1237, hsa-miR-1238,
hsa-miR-124, hsa-miR-129*, hsa-miR-129-3p, hsa-miR-136*,
hsa-miR-187*, hsa-miR-188-5p, hsa-miR-190b, hsa-miR-198,
hsa-miR-22, hsa-miR-220b, hsa-miR-300, hsa-miR-301b, hsa-miR-30e,
hsa-miR-338-3p, hsa-miR-33a*, hsa-miR-33b, hsa-miR-33b*,
hsa-miR-34c-3p, hsa-miR-34c-5p, hsa-miR-363*, hsa-miR-371-3p,
hsa-miR-371-5p, hsa-miR-375, hsa-miR-377*, hsa-miR-423-5p,
hsa-miR-424, hsa-miR-424*, hsa-miR-429, hsa-miR-448, hsa-miR-449a,
hsa-miR-449b, hsa-miR-450b-3p, hsa-miR-452, hsa-miR-454*,
hsa-miR-455-3p, hsa-miR-483-3p, hsa-miR-483-5p, hsa-miR-491-3p,
hsa-miR-491-5p, hsa-miR-493, hsa-miR-493*, hsa-miR-494,
hsa-miR-497, hsa-miR-498, hsa-miR-500, hsa-miR-503, hsa-miR-505,
hsa-miR-507, hsa-miR-513a-3p, hsa-miR-513a-5p, hsa-miR-513b,
hsa-miR-513c, hsa-miR-515-5p, hsa-miR-518b, hsa-miR-518c*,
hsa-miR-518d-3p, hsa-miR-518d-5p, hsa-miR-518e*, hsa-miR-520d-5p,
hsa-miR-520h, hsa-miR-541, hsa-miR-545*, hsa-miR-548d-3p,
hsa-miR-548d-5p, hsa-miR-551a, hsa-miR-551b, hsa-miR-552,
hsa-miR-554, hsa-miR-556-5p, hsa-miR-557, hsa-miR-559, hsa-miR-561,
hsa-miR-564, hsa-miR-572, hsa-miR-575, hsa-miR-576-3p, hsa-miR-578,
hsa-miR-583, hsa-miR-586, hsa-miR-589, hsa-miR-589*, hsa-miR-591,
hsa-miR-595, hsa-miR-601, hsa-miR-602, hsa-miR-609, hsa-miR-610,
hsa-miR-612, hsa-miR-613, hsa-miR-614, hsa-miR-615-3p, hsa-miR-616,
hsa-miR-619, hsa-miR-622, hsa-miR-623, hsa-miR-624*, hsa-miR-627,
hsa-miR-633, hsa-miR-634, hsa-miR-638, hsa-miR-639, hsa-miR-640,
hsa-miR-642, hsa-miR-644, hsa-miR-647, hsa-miR-648, hsa-miR-652,
hsa-miR-654-5p, hsa-miR-658, hsa-miR-659, hsa-miR-662, hsa-miR-663,
hsa-miR-665, hsa-miR-671-5p, hsa-miR-675, hsa-miR-708,
hsa-miR-708*, hsa-miR-744*, hsa-miR-760, hsa-miR-765, hsa-miR-766,
hsa-miR-767-3p, hsa-miR-802, hsa-miR-874, hsa-miR-876-3p,
hsa-miR-876-5p, hsa-miR-877, hsa-miR-877*, hsa-miR-885-3p,
hsa-miR-885-5p, hsa-miR-886-3p, hsa-miR-890, hsa-miR-891b,
hsa-miR-892b, hsa-miR-920, hsa-miR-922, hsa-miR-923, hsa-miR-92b,
hsa-miR-92b*, hsa-miR-933, hsa-miR-934, hsa-miR-935, hsa-miR-936,
hsa-miR-937, hsa-miR-939, hsa-miR-940, hsv1-miR-H1, hsv1-miR-LAT,
kshv-miR-K12-12, kshv-miR-K12-3, kshv-miR-K12-3*,
kshv-miR-K12-4-5p, kshv-miR-K12-6-5p, kshv-miR-K12-8,
kshv-miR-K12-9, kshv-miR-K12-9*, ebv-miR-BART10*, ebv-miR-BART12,
ebv-miR-BART13, ebv-miR-BART13*, ebv-miR-BART15, ebv-miR-BART1-5p,
ebv-miR-BART16, ebv-miR-BART18-5p, ebv-miR-BART19-3p,
ebv-miR-BART19-5p, ebv-miR-BART20-5p, ebv-miR-BART2-5p,
ebv-miR-BART3*, ebv-miR-BART5, ebv-miR-BART6-5p, ebv-miR-BART7,
ebv-miR-BART7*, ebv-miR-BHRF1-1, ebv-miR-BHRF1-3, hcmv-miR-UL148D,
hcmv-miR-UL22A, hcmv-miR-UL22A*, hcmv-miR-UL70-3p,
hcmv-miR-UL70-5p, hcmv-miR-US25-1, hcmv-miR-US25-2-3p,
hcmv-miR-US25-2-5p, hcmv-miR-US4, hiv1-miR-H1, hiv1-miR-N367, and
human orthologs thereof.
[0026] In other embodiments where the physiological condition is
related to lung disease or lung injury, the microRNA profile or the
specific microRNA sequence may comprise at least one microRNA
sequence selected from the group consisting of hsa-miR-135a*,
hsa-miR-1224-3p, hsa-miR-1224-5p, hsa-miR-1225-3p, hsa-miR-1225-5p,
hsa-miR-1226*, hsa-miR-1227, hsa-miR-1228, hsa-miR-1229,
hsa-miR-1234, hsa-miR-1237, hsa-miR-1238, hsa-miR-124,
hsa-miR-129*, hsa-miR-129-3p, hsa-miR-136*, hsa-miR-187*,
hsa-miR-188-5p, hsa-miR-190b, hsa-miR-220b, hsa-miR-300,
hsa-miR-301b, hsa-miR-30e, hsa-miR-338-3p, hsa-miR-33a*,
hsa-miR-33b, hsa-miR-33b*, hsa-miR-34c-3p, hsa-miR-34c-5p,
hsa-miR-363*, hsa-miR-371-3p, hsa-miR-371-5p, hsa-miR-375,
hsa-miR-377*, hsa-miR-423-5p, hsa-miR-424*, hsa-miR-429,
hsa-miR-448, hsa-miR-449a, hsa-miR-449b, hsa-miR-450b-3p,
hsa-miR-452, hsa-miR-454*, hsa-miR-455-3p, hsa-miR-483-3p,
hsa-miR-483-5p, hsa-miR-491-3p, hsa-miR-491-5p, hsa-miR-493,
hsa-miR-493*, hsa-miR-500, hsa-miR-505, hsa-miR-507,
hsa-miR-513a-3p, hsa-miR-513a-5p, hsa-miR-513b, hsa-miR-513c,
hsa-miR-515-5p, hsa-miR-518c*, hsa-miR-518d-3p, hsa-miR-518d-5p,
hsa-miR-518e*, hsa-miR-520d-5p, hsa-miR-541, hsa-miR-545*,
hsa-miR-548d-3p, hsa-miR-548d-5p, hsa-miR-551b, hsa-miR-552,
hsa-miR-554, hsa-miR-556-5p, hsa-miR-557, hsa-miR-559, hsa-miR-561,
hsa-miR-564, hsa-miR-575, hsa-miR-576-3p, hsa-miR-578, hsa-miR-583,
hsa-miR-586, hsa-miR-589, hsa-miR-589*, hsa-miR-591, hsa-miR-595,
hsa-miR-602, hsa-miR-609, hsa-miR-610, hsa-miR-612, hsa-miR-613,
hsa-miR-614, hsa-miR-615-3p, hsa-miR-616, hsa-miR-619, hsa-miR-623,
hsa-miR-624*, hsa-miR-633, hsa-miR-638, hsa-miR-639, hsa-miR-640,
hsa-miR-642, hsa-miR-644, hsa-miR-647, hsa-miR-652, hsa-miR-654-5p,
hsa-miR-658, hsa-miR-659, hsa-miR-665, hsa-miR-671-5p, hsa-miR-675,
hsa-miR-708*, hsa-miR-744*, hsa-miR-760, hsa-miR-765, hsa-miR-766,
hsa-miR-767-3p, hsa-miR-768-3p, hsa-miR-768-5p, hsa-miR-801,
hsa-miR-802, hsa-miR-874, hsa-miR-876-3p, hsa-miR-876-5p,
hsa-miR-877, hsa-miR-877*, hsa-miR-885-3p, hsa-miR-885-5p,
hsa-miR-886-3p, hsa-miR-890, hsa-miR-891b, hsa-miR-892b,
hsa-miR-920, hsa-miR-922, hsa-miR-923, hsa-miR-92b*, hsv1-miR-H1,
hsv1-miR-LAT, kshv-miR-K12-12, kshv-miR-K12-3, kshv-miR-K12-3*,
kshv-miR-K12-4-5p, kshv-miR-K12-6-5p, kshv-miR-K12-8,
kshv-miR-K12-9, kshv-miR-K12-9*, ebv-miR-BART10*, ebv-miR-BART12,
ebv-miR-BART13, ebv-miR-BART13*, ebv-miR-BART15, ebv-miR-BART1-5p,
ebv-miR-BART16, ebv-miR-BART18-5p, ebv-miR-BART19-3p,
ebv-miR-BART19-5p, ebv-miR-BART20-5p, ebv-miR-BART2-5p,
ebv-miR-BART3*, ebv-miR-BART5, ebv-miR-BART6-5p, ebv-miR-BART7,
ebv-miR-BART7*, ebv-miR-BHRF1-1, ebv-miR-BHRF1-3, hcmv-miR-UL148D,
hcmv-miR-UL22A, hcmv-miR-UL22A*, hcmv-miR-UL70-3p,
hcmv-miR-UL70-5p, hcmv-miR-US25-1, hcmv-miR-US25-2-3p,
hcmv-miR-US25-2-5p, hcmv-miR-US4, hiv1-miR-H1, hiv1-miR-N367, and
human orthologs thereof.
[0027] The physiological condition may also be a lung disease or
lung injury, such as chronic obstructive pulmonary disease (COPD)
and idiopathic pulmonary fibrosis (IPF), also known as interstitial
lung disease (ILD).
[0028] In embodiments, the at least one differentially expressed
microRNA sequence or at least one specific microRNA sequence is
selected from the group consisting of hsa-miR-630, hsa-miR-134,
hsa-miR-1225-5p, hsa-miR-135a*, hsa-miR-150*, hsa-miR-22,
hsa-miR-223, hsa-miR-448, hsa-miR-451, hsa-miR-483-5p, hsa-miR-575,
hsa-miR-638, hsa-miR-923, hsa-miR-92a-2*, hsa-miR-939, hsa-miR-940,
hsv1-miR-H1, kshv-miR-K12-3, hsv1-miR-LAT, hcmv-miR-UL70-3p,
hsv1-miR-H1, hsv1-miR-LAT, kshv-miR-K12-3, hcmv-miR-UL70-3p, and
human orthologs thereof.
[0029] In other embodiments, the biological sample is plasma and
the at least one differentially expressed microRNA sequence or at
least one specific microRNA sequence is selected from the group
consisting of hsa-miR-630, hsa-miR-134, hsa-miR-1225-5p,
hsa-miR-135a*, hsa-miR-150*, hsa-miR-22, hsa-miR-223,
hsa-miR-483-5p, hsa-miR-575, hsa-miR-638, hsa-miR-923, hsa-miR-939,
hsa-miR-940, hsv1-miR-H1, hsv1-miR-LAT, kshv-miR-K12-3,
hcmv-miR-UL70-3p, and human orthologs thereof. In some particular
embodiments, the microRNA profile consists of only a selection of
at least two of these microRNA sequences, i.e. the microRNA profile
does not look at other microRNA sequences.
[0030] In yet other embodiments, the biological sample is plasma
and the at least one differentially expressed microRNA sequence or
at least one specific microRNA sequence is selected from the group
consisting of hsa-miR-630, hsa-miR-134, hcmv-miR-UL70-3p,
hsa-miR-1225-5p, hsa-miR-135a*, hsa-miR-150*, hsa-miR-483-5p,
hsa-miR-575, hsa-miR-638, hsv1-miR-H1, hsv1-miR-LAT, and human
orthologs thereof. In some particular embodiments, the microRNA
profile consists of only a selection of at least two of these
microRNA sequences, i.e. the microRNA profile does not look at
other microRNA sequences.
[0031] In some alternate embodiments, the biological sample is
plasma and at least two differentially expressed microRNA sequences
or specific microRNA sequences are identified. At least one of the
at least two differentially expressed microRNA sequences or
specific microRNA sequences is selected from the group consisting
of hsa-miR-630, hcmv-miR-UL70-3p, hsa-miR-1225-5p, hsa-miR-134,
hsa-miR-135a*, hsa-miR-150*, hsa-miR-483-5p, hsa-miR-575,
hsa-miR-638, hsv1-miR-H1, hsv1-miR-LAT, and human orthologs
thereof. The other one of the at least two differentially expressed
microRNA sequences or specific microRNA sequences is selected from
the group consisting of hsa-miR-451, hsa-miR-448, hsa-miR-92a-2*,
and human orthologs thereof. In some particular embodiments, the
microRNA profile consists of only a selection of these microRNA
sequences, i.e. the microRNA profile does not look at other
microRNA sequences.
[0032] In yet other embodiments, the biological sample is lung
tissue and the at least one differentially expressed microRNA
sequence is selected from the group consisting of hsa-miR-451,
hsa-miR-923, hsa-miR-1225-5p, hsa-miR-22, hsa-miR-223, hsa-miR-638,
kshv-miR-K12-3, and human orthologs thereof. In some particular
embodiments, the microRNA profile consists of only a selection of
these microRNA sequences.
[0033] In still other embodiments, the biological sample is plasma
and the at least one differentially expressed microRNA sequence is
selected from the group consisting of hsa-miR-940, hsa-miR-134,
hsa-miR-135a*, hsa-miR-150*, hsa-miR-483-5p, hsa-miR-575,
hsa-miR-939, hsv1-miR-H1, kshv-miR-K12-3, hsv1-miR-LAT,
hcmv-miR-UL70-3p, and human orthologs thereof. In some particular
embodiments, the microRNA profile consists of only a selection of
these microRNA sequences, i.e. the microRNA profile does not look
at other microRNA sequences.
[0034] Also disclosed are methods of using microRNA sequences to
detect a lung condition, comprising: generating a microRNA profile
from a biological sample; and detecting the lung condition based on
the levels of at least one overexpressed microRNA sequence and at
least one underexpressed microRNA sequence. The at least one
overexpressed microRNA sequence is selected from the group
consisting of hsa-miR-630, hcmv-miR-UL70-3p, hsa-miR-1225-5p,
hsa-miR-134, hsa-miR-135a*, hsa-miR-150*, hsa-miR-483-5p,
hsa-miR-575, hsa-miR-638, hsv1-miR-H1, hsv1-miR-LAT, and human
orthologs thereof. The at least one underexpressed microRNA
sequence is selected from the group consisting of hsa-miR-451,
hsa-miR-448, and hsa-miR-92a-2*, and human orthologs thereof. In
some particular embodiments, the microRNA profile examines only a
selection of these listed microRNA sequences.
[0035] Also disclosed are methods of detecting or predicting
certain physiological conditions in a patient. Those methods
comprise generating a microRNA profile from a biological sample
provided by the patient; identifying at least one differentially
expressed microRNA sequence by comparing the microRNA profile to a
reference; and detecting or predicting the physiological condition
based on the identity or the amounts of the at least one
differentially expressed microRNA sequence. The biological sample
comprises (i) serum or plasma; and (ii) an additional body fluid
specific to a particular location of the body that is relevant to
the particular physiological condition. In a first embodiment, the
biological sample further comprises amniotic fluid and the
physiological condition is the health status of a fetus being
carried by the patient. In a second embodiment, the biological
sample further comprises urine and the physiological condition is
the health status of a bladder or a kidney of the patient. In a
third embodiment, the biological sample further comprises breast
milk and the physiological condition is the health status of a
breast of the patient. In a fourth embodiment, the biological
sample further comprises saliva and the physiological condition is
the health status of the head and neck region of the patient. In a
fifth embodiment, the biological sample further comprises tears and
the physiological condition is the health status of an eye of the
patient. In a sixth embodiment, the biological sample further
comprises semen and the physiological condition is the health
status of a prostate or male reproductive organ of the patient. In
a seventh embodiment, the biological sample further comprises
synovial fluid and the physiological condition is the health status
of a joint of the patient. In an eighth embodiment, the biological
sample further comprises sweat and the physiological condition is
the health status of the skin of the patient. In a ninth
embodiment, the biological sample further comprises cerebrospinal
fluid and the physiological condition is the health status of the
central nerve system of the patient.
[0036] Also disclosed are methods of diagnosing a physiological
condition. The methods comprise taking a sample of a body fluid and
a sample of a body tissue from a patient. A first microRNA profile
is generated from the body fluid sample, and a second microRNA
profile is generated from the body tissue sample. At least two
differentially expressed microRNA sequences are identified in the
first microRNA profile by comparing the first microRNA profile to a
first reference. At least two differentially expressed microRNA
sequences are identified in the second microRNA profile by
comparing the second microRNA profile to a second reference. The
physiological condition is then diagnosed based on the
differentially expressed microRNA sequences identified. In
particular, the differentially expressed microRNA sequences in the
first microRNA profile are different from the differentially
expressed microRNA sequences in the second microRNA profile. This
difference in the differentially expressed microRNA sequences
between the body fluid and the body tissue increases the
probability of a correct diagnosis.
[0037] Also included are assays for detecting the identity and/or
levels of the various combinations of microRNA sequences described
above.
[0038] These and other non-limiting aspects and/or objects of the
disclosure are more particularly described below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0039] The following is a brief description of the drawings, which
are presented for the purposes of illustrating the disclosure set
forth herein and not for the purposes of limiting the same.
[0040] FIGS. 1A-1B are electropherograms of RNA.
[0041] FIG. 2 is a microRNA profile showing changes in specific
microRNA expression levels over time in the liver after exposing
the animal to a high dose of acetaminophen.
[0042] For reference, the text on the right-hand side of FIG. 2
reads, in order from top to bottom: mmu-miR-720, mmu-miR-1224,
mmu-miR-122, mmu-miR-494, mmu-miR-609, mmu-miR-21, mmu-miR-22,
mmu-miR-451, mmu-miR-466f-3p, mmu-miR-574-5p, mmu-let-7a,
mmu-let-7f, mmu-miR-192, mmu-miR-194, mmu-miR-212, mmu-let-7g,
mmu-miR-29b, mmu-miR-26a, mmu-miR-30c, mmu-miR-29a, mmu-miR-188-5p,
mmu-miR-709, mmu-miR-466g, mmu-miR-574-3p, mmu-miR-125a-3p,
mmu-miR-125b-5p, mmu-miR-29c, mmu-miR-483, mmu-miR-600,
mmu-miR-705, mmu-miR-721, mmu-miR-376b, mmu-miR-706, mmu-miR-710,
mmu-miR-711, mmu-let-7c-2*, mmu-miR-376a, mmu-miR-891, mmu-miR-452,
mmu-miR-467a*, mmu-miR-718, mmu-miR-500, mmu-miR-669c, mmu-miR-714,
mmu-miR-290-5p, mmu-miR-134, mmu-miR-27b, mmu-miR-671-5p,
mmu-miR-135a*, and mmu-miR-877*.
[0043] FIG. 3 is a microRNA profile showing differences in specific
microRNA levels between plasma samples from a treated group and a
control group.
[0044] For reference, the text on the right-hand side of FIG. 3
reads, in order from top to bottom: mmu-miR-21, mmu-miR-122,
mmu-miR-22, mmu-miR-192, mmu-miR-29a, mmu-miR-30a, mmu-miR-130a,
mmu-miR-29c, mmu-miR-30a, mmu-miR-148a, mmu-miR-19b, mmu-miR-101b,
mmu-miR-15a, mmu-miR-685, mmu-let-7g, mmu-miR-27b, mmu-miR-574-5p,
mmu-miR-671-5p, mmu-miR-107, mmu-let-7d*, mmu-miR-29b, mmu-miR-193,
mmu-miR-194, mmu-miR-101a, mmu-miR-185, mmu-miR-221, mmu-miR-294*,
mmu-miR-877, mmu-miR-291a-5p, mmu-miR-877*, mmu-miR-339-3p,
mmu-miR-466f-3p, mmu-miR-30c-1*, mmu-miR-199b, mmu-miR-199a-5p,
mmu-miR-193b, mmu-miR-370, mmu-miR-882, mmu-miR-327, mmu-miR-127,
mmu-miR-714, mmu-miR-150, mmu-miR-125a-5p, mmu-miR-141,
mmu-miR-23b, mmu-miR-145, mmu-miR-320, mmu-miR-342-3p,
mmu-miR-200c, mmu-miR-223, mmu-miR-99a, mmu-miR-202-3p,
mmu-miR-494, mmu-miR-652, mmu-miR-375, mmu-miR-125a-3p,
mmu-miR-124, mmu-miR-721, mmu-miR-93, mmu-miR-483, mmu-miR-205,
mmu-miR-712, mmu-miR-26a, mmu-miR-710, mmu-miR-23a, mmu-miR-135a*,
mmu-miR-711, mmu-miR-720, mmu-miR-125b-5p, mmu-miR-133a,
mmu-miR-133b, mmu-miR-451, mmu-miR-486, and mmu-miR-1224.
[0045] FIG. 4 is a graph of intensities for two selected microRNA
sequences, mir-122 and mir-486 in plasma after exposing the animal
to different doses of acetaminophen.
[0046] FIG. 5 is a graph of the ratio between mir-122 and mir-486
(either median or average intensities) for the same data as FIG.
4.
[0047] FIG. 6 is a microRNA profile showing differences in microRNA
expression levels between normal brain tissue and diseased brain
tissue.
[0048] FIG. 7 is a microRNA profile showing differences in microRNA
expression levels as a disease progressed in lung tissue.
[0049] FIG. 8 is a microRNA profile showing differences in microRNA
expression levels between serum and urine samples.
[0050] FIG. 9 is a graph comparing miRNA expression levels in
control plasma samples with ILD plasma samples.
[0051] FIGS. 10A-10B are graphs showing the signal strength in the
ILD and control plasma samples of FIG. 9.
[0052] FIG. 11 is a graph showing the signal strength for all
oligonucleotide probes used to target certain microRNA
sequences.
[0053] FIG. 12 is a graph showing the difference in the signal
strength for certain microRNA sequences in the ILD and control
plasma samples of FIG. 9.
[0054] FIG. 13 is a graph showing the degree of overexpression in
certain microRNA sequences in the ILD and control plasma samples of
FIG. 9.
[0055] FIG. 14 is a graph comparing miRNA expression levels in ILD
tissue samples with ILD plasma samples.
[0056] FIG. 15 is a graph comparing miRNA expression levels in
control lung tissue samples with ILD lung tissue samples.
[0057] FIG. 16 is a graph showing the effect of normalization on
data in a data analysis method.
[0058] FIGS. 17A-17B are graphs showing the effect of normalization
on the quality of data.
[0059] FIG. 18 is a graph clustering normalized miRNA data.
[0060] FIG. 19 is a graph showing the p-value distribution of all
miRNA in a sample.
[0061] FIG. 20 is a collection of charts showing the selection of
panels that separates data.
DETAILED DESCRIPTION
[0062] A more complete understanding of the processes and
apparatuses disclosed herein can be obtained by reference to the
accompanying drawings. These figures are merely schematic
representations based on convenience and the ease of demonstrating
the existing art and/or the present development, and are,
therefore, not intended to indicate relative size and dimensions of
the assemblies or components thereof.
[0063] Although specific terms are used in the following
description for the sake of clarity, these terms are intended to
refer only to the particular structure of the embodiments selected
for illustration in the drawings, and are not intended to define or
limit the scope of the disclosure. In the drawings and the
following description below, it is to be understood that like
numeric designations refer to components of like function.
[0064] MicroRNAs (also known as miRNA) are small but potent
regulatory non-coding ribonucleic acid (RNA) sequences first
identified in C. elegans in 1993. miRNA may be about 21 to about 23
nucleotides in length. Through sequence complementation, microRNA
interacts with messenger RNA (mRNA) and affects the stability of
mRNA and/or the initiation and progression of protein translation.
It has been estimated that over 30% of the mRNAs are regulated by
microRNA. Like mRNA, some of the microRNAs also display restricted
tissue distribution. The biological function of microRNA is yet to
be fully understood; however, it has been shown that microRNA
sequences are involved in various physiological and pathological
conditions, including differentiation, development, cancer, and
neurological disorders. Unlike mRNA and proteins, microRNA is
reasonably well conserved across different species. Thus, a
specific microRNA sequences which is shown to correlate to a
particular condition, such as disease or injury, in one species,
should also correlate to that particular condition in other
species, particularly humans (i.e. Homo sapiens). This correlation
provides useful diagnostic content.
[0065] MicroRNAs can also be manipulated with commonly used
molecular biology techniques including complementary DNA (cDNA)
synthesis, polymerase chain reactions, Northern blotting, and array
based hybridization. This makes it possible to easily investigate
the function(s) of a given microRNA sequences of interest.
[0066] A microRNA is encoded by a gene. When the DNA of the gene is
transcribed into RNA, the RNA is not subsequently translated into
protein. Instead each primary transcript (a pri-mir) is processed
into a short stem-loop structure (a pre-mir) and finally into a
mature sequence, designated miR. The primary transcript can form
local hairpin structures, which ordinarily are processed such that
a single microRNA sequence accumulates from one arm of a hairpin
precursor molecule. Sometimes the primary transcript contains
multiple hairpins, and different hairpins give rise to different
microRNA sequences.
[0067] The microRNA sequences discussed herein are named according
the miRBase database available at http://microrna.sanger.ac.uk/ and
maintained by the Wellcome Trust Sanger Institute (now redirected
to http://www.miRBase.org/). Generally speaking, microRNA sequences
are assigned sequential numerical identifiers, with the numerical
identifier based on sequence similarity. A 3- or 4-letter prefix
designates the species from which the microRNA sequence came. For
example, the hsa in hsa-miR-101 refers to homo sapiens.
[0068] Orthologous sequences, or orthologs, refer to microRNA
sequences that are in different species but are similar (i.e.
homologous) because they originated from a common ancestor.
Generally speaking, orthologs have the same numerical identifier
and are believed to serve a similar function. For example,
mmu-miR-101 and hsa-miR-101 are in mouse and human, respectively,
and are orthologs to each other. In this disclosure, microRNA
sequences are referred to without the prefix designating the
species, and should be construed as preferentially referring to the
human microRNA sequence and the murine sequence. For example,
miR-101 should be construed as referring to hsa-miR-101 and
mmu-miR-101.
[0069] Paralogous sequences, or paralogs, are microRNA sequences
that differ from each other in only a few positions. Paralogs occur
within a species. Paralogs are designated with letter suffixes. For
example, mmu-miR-133a and mmu-miR-133b are paralogs.
[0070] Identical microRNA sequences that originate from separate
genomic loci are given numerical suffixes, such as hsa-miR-26a-1
and hsa-miR-26a-2.
[0071] Sometimes, two different mature microRNA sequences are
excised from opposite arms of the same hairpin precursor. The two
microRNA sequences can be designated in at least two ways. First,
when it is possible to determine which arm gives rise to the
predominantly expressed miRNA sequence, an asterisk has been used
to denote the less predominant form, such as hsa-let-7b and
hsa-let-7b*. Alternatively, they are named to designate whether
they come from the 5' or 3' arm, such as hsa-miR-125a-3p and
hsa-miR-125a-5p.
[0072] Specific microRNA sequences have been identified in the
blood that are associated with liver injuries. Thus, the levels of
selected microRNA sequences can be used to detect, predict, or
diagnose diseases, predict and monitor therapeutic responses,
and/or predict disease outcomes.
[0073] MicroRNA-based blood markers offer superior properties over
existing markers. Such markers are sensitive, in part because
microRNA signals can be amplified using standard polymerase chain
reactions (PCR) while protein-based markers cannot be easily
amplified. Because the sequence and expression profile of microRNAs
are largely conserved across species, discoveries made in animal
models can be easily translated to and adapted for use in humans.
MicroRNA assays can be quickly performed and developed with
standard PCR or array based systems; therefore, beside PCR primers,
there is no need to develop special detection agents. Finally,
since microRNA can be easily accessed in various body fluids,
obtaining such diagnostic information can be done
non-invasively.
[0074] The level of specific microRNA sequences(s) in a cell,
tissue, or body fluid(s) can be used to monitor the
physiopathological conditions of the body.
[0075] Sets of microRNA sequences in the tissue and the serum have
been identified that are associated with liver injuries, lung
injuries, and lung diseases. The combination of information from
multiple microRNA expression level changes can further enhance the
sensitivity and specificity of disease/injury detection, including
using the ratio of paired microRNA sequences.
[0076] MicroRNA profiles, for example a microRNA profile of
tissue-specific microRNA sequences, could be used to monitor the
health status of that tissue. Those microRNA sequences could also
be used as therapeutic targets for diseases associated with the
tissue.
[0077] MicroRNA sequences from microbes or infectious agents, such
as bacteria and viruses, could be used as an indication of
infection. Host responses could be monitored by using the
combination of microRNA sequences from infectious agents and the
host as measured from the host's body fluids.
[0078] Biological processes occurring in a number of cell types or
tissues could be monitored by the use of microRNA profiles specific
to a process or network. These specific microRNA sequences could
also be used as therapeutic targets for diseases associated with
the biological processes.
[0079] The methods of the present disclosure could be used to
detect, predict, monitor, or treat a physiological condition such
as a disease, injury, or infection. Generally, the methods include:
(a) isolating microRNA sequences from a biological sample; (b)
generating a microRNA profile from the isolated microRNA sequences,
the profile including the levels of expressed microRNA sequences in
the biological sample; and (c) comparing the microRNA profile with
a reference to identify differentially expressed microRNA
sequences. Based on the identity or the levels of the
differentially expressed microRNA sequences, the physiological
condition could be detected, predicted, or monitored; or a
treatment could be indicated, administered, or monitored
accordingly.
[0080] The biological sample is generally non-invasive, and may be,
for example, a biopsy material, tissue, or body fluid. Exemplary
body fluids include serum, plasma, lymph, saliva, urine, tears,
sweat, semen, synovial fluid, cervical mucus, amniotic fluid,
cerebrospinal fluid, and breast milk.
[0081] Combinations of different biological samples are also
contemplated for providing more specific diagnoses. For example,
plasma and serum would provide some general indicators of health,
while a specific body fluid could be included for specific
information. For example, if one wanted to assess the health status
of a fetus being carried by the mother, one might test the amniotic
fluid along with the mother's plasma or serum. As another example,
one might test the urine to assess the health status of a bladder
or a kidney. Testing the breast milk would help assess the health
status of a breast of the patient providing the biological sample.
Testing the saliva would help assess the health status of the head
and neck region. Testing the tears would help assess the health
status of an eye of the patient providing the biological sample.
Testing semen would help assess the health status of a prostate or
male reproductive organ. Testing the synovial fluid would help
assess the health status of a joint of the patient providing the
biological sample. Testing the sweat would help assess the health
status of the skin. Testing the cerebrospinal fluid would help
assess the health status of the central nerve system. The term
"health status" refers only to the physiological condition of the
given body part, and has no specific meaning otherwise.
[0082] Isolating microRNA can be done by various methods. For
example, the biological sample may be extracted with an organic
solvent to obtain an aqueous phase containing the microRNA
sequences. The aqueous phase is then purified through a silica
membrane to isolate the microRNA sequences.
[0083] A microRNA profile can then be generated from the isolated
microRNA sequences. Generally speaking, the microRNA profile
provides the identity of specific microRNA sequences and/or the
expression level (i.e. amount) of each specific microRNA sequence.
An exemplary microRNA profile is seen in FIG. 2, which shows the
expression levels for several microRNA sequences from several
different liver samples that have been exposed to a high dose of
acetaminophen. The microRNA profile of FIG. 2 has six columns, but
a microRNA profile may be simply one column (along with the
identifying microRNA). The expression level can be displayed either
as a sliding color scale or simply as numerical values. The
microRNA profile can be generated by using hybridization to
identify the microRNA sequences and/or using quantitative PCR
(qPCR) to identify the levels of one or more particular microRNA
sequences. It should be noted that the diagnostic information may
be in the identity of the microRNA sequences themselves, or in the
absolute or relative levels of the microRNA sequence, either
between two microRNA sequences in a given sample or between two
samples for a given microRNA sequence. A reference table could be
provided, for example from a reference sample taken from the
patient or from a table of levels of expressed microRNA sequences
in a normal (healthy) person or a table compiled from the expressed
microRNA sequences over a large sample of people. Differentially
expressed microRNA sequences can then be identified by comparing
the microRNA profile of the biological sample with the reference
sample or table to obtain diagnostic information. The term
"differentially expressed" refers only to the fact that the amount
or expression level has changed. The direction of change (i.e.
upwards or downwards, overexpressed or underexpressed) is not
significant, except as otherwise stated.
[0084] In particular embodiments, it is contemplated that
identifying at least one specific microRNA sequence as being
differentially expressed would be sufficient to identify a
particular physiological condition as occurring. In other
embodiments, at least two differentially expressed microRNA
sequences are identified. This provides for an additional degree of
confirmation in the identity of the physiological condition.
[0085] In using the terms "generating" and "identifying," it is
contemplated that these actions may be performed directly or
indirectly. For example, a laboratory technician may perform the
actions that directly "generate" a microRNA profile. The physician
who ordered the microRNA profile that was directly "generated" by
the laboratory technician may be considered to have indirectly
"generated" the microRNA profile.
[0086] Because microRNA sequences and expression levels are
generally conserved across species, it is contemplated that
sequences and levels from other species would contain useful
diagnostic information. For example, the biological sample may be
from a microbe, such as a virus, bacterium, fungus, protozoan, or
parasite.
[0087] It has been found that microRNA sequences and their
expression levels can differ depending on their location in the
body. In other words, they can be specific to a biological pathway,
cell type, or tissue. This fact can provide powerful diagnostic
information as well.
[0088] Table 1 lists some microRNA sequences which have been found
to be specific to certain tissues in the human body.
TABLE-US-00001 TABLE 1 Human tissue Human tissue Tissue specific
miRNA Tissue specific miRNA Adipose hsa-miR-452 Placenta
hsa-miR-527 Adipose hsa-miR-196a Placenta hsa-miR-377 Adipose
hsa-miR-224 Placenta hsa-miR-526c Adipose hsa-miR-335 Placenta
hsa-miR-524* Adipose hsa-miR-452* Placenta hsa-miR-517* Adipose
hsa-miR-432* Placenta hsa-miR-450 Adrenal hsa-miR-409-5p Placenta
hsa-miR-503 Adrenal hsa-miR-494 Placenta hsa-miR-526b* Adrenal
hsa-miR-485-5p Placenta hsa-miR-371 Adrenal hsa-miR-360-5p Placenta
hsa-miR-519b Adrenal hsa-miR-154 Placenta hsa-miR-516-3p Adrenal
hsa-miR-370 Placenta hsa-miR-526a Adrenal hsa-miR-381 Placenta
hsa-miR-523 Adrenal hsa-miR-369 Placenta hsa-miR-518a-2* Adrenal
hsa-miR-485-3p Placenta hsa-miR-518c* Adrenal hsa-miR-134 Placenta
hsa-miR-520b Adrenal hsa-miR-323 Placenta hsa-miR-518d Adrenal
hsa-miR-7N Placenta hsa-miR-524 Adrenal hsa-miR-382 Placenta
hsa-miR-519a Adrenal hsa-miR-7 Placenta hsa-miR-520a Adrenal
hsa-miR-405 Placenta hsa-miR-521 Adrenal hsa-miR-127 Placenta
hsa-miR-522 Adrenal hsa-miR-493 Placenta hsa-miR-520d Adrenal
hsa-miR-379 Placenta hsa-miR-525 Adrenal hsa-miR-432 Placenta
hsa-miR-512-5p Adrenal hsa-miR-299 Placenta hsa-miR-520a* Adrenal
hsa-miR-433 Placenta hsa-miR-519a* Adrenal hsa-miR-376a Placenta
hsa-miR-517a Adrenal hsa-miR-202* Placenta hsa-miR-517b Adrenal
hsa-miR-137 Placenta hsa-miR-515-5p Adrenal hsa-miR-501 Placenta
hsa-miR-525* Adrenal hsa-miR-202 Placenta hsa-miR-518 Adrenal
hsa-miR-491 Placenta hsa-miR-512-3p Bladder hsa-miR-451 Placenta
hsa-miR-517c Brain hsa-miR-330 Placenta hsa-miR-518a Brain
hsa-miR-219 Placenta hsa-miR-519d Brain hsa-miR-124 Placenta
hsa-miR-518c Brain hsa-miR-9 Placenta hsa-miR-518e Brain hsa-miR-9*
Placenta hsa-miR-520g Brain hsa-miR-124a Placenta hsa-miR-519c
Brain hsa-miR-129 Placenta hsa-miR-515-3p Brain hsa-miR-124b
Placenta hsa-miR-520b Brain hsa-miR-137 Placenta hsa-miR-372 Brain
hsa-miR-383 Placenta hsa-miR-520a Brain hsa-miR-433 Placenta
hsa-miR-520c Brain hsa-miR-348 Placenta hsa-miR-373 Brain
hsa-miR-323 Placenta hsa-miR-520b Brain hsa-miR-153 Placenta
hsa-miR-154* Brain hsa-miR-128b Placenta hsa-miR-520c Brain
hsa-miR-128a Placenta hsa-miR-493 Brain hsa-miR-485-5p Placenta
hsa-miR-381 Brain hsa-miR-370 Placenta hsa-miR-151 Brain
hsa-miR-485-3p Placenta hsa-miR-495 Brain hsa-miR-181b Placenta
hsa-miR-474 Brain hsa-miR-338 Placenta hsa-miR-369-5p Brain
hsa-miR-154* Placenta hsa-miR-184 Brain hsa-miR-149 Placenta
hsa-miR-489 Brain hsa-miR-213 Placenta hsa-miR-376a Brain
hsa-miR-340 Placenta hsa-miR-500 Brain hsa-miR-181bN Placenta
hsa-miR-369 Brain hsa-miR-181d Placenta hsa-miR-135b Brain
hsa-miR-491 Placenta hsa-miR-432 Brain hsa-miR-184 Placenta
hsa-miR-27aN Brain hsa-miR-138 Placenta hsa-miR-198 Brain
hsa-miR-132 Placenta hsa-miR-224 Brain hsa-miR-181c Placenta
hsa-miR-452* Brain hsa-miR-204 Placenta hsa-miR-433 Brain
hsa-miR-328 Placenta hsa-miR-193b Brain hsa-miR-181a Placenta
hsa-miR-494 Brain hsa-miR-432 Placenta hsa-miR-502 Brain
hsa-miR-379 Placenta hsa-miR-335 Brain hsa-miR-324-5p Placenta
hsa-miR-299 Brain hsa-miR-122 Placenta hsa-miR-149 Brain
hsa-miR-134 Placenta hsa-miR-213 Brain hsa-miR-342 Placenta
hsa-miR-30d Breast hsa-miR-452 Placenta hsa-miR-141 Breast
hsa-miR-205 Placenta hsa-miR-301 Breast hsa-miR-489 Placenta
hsa-miR-485-3p Colon hsa-miR-490 Placenta hsa-miR-141N Colon
hsa-miR-363 Placenta hsa-miR-379 Colon hsa-miR-338 Placenta
hsa-miR-130a Colon hsa-miR-31 Placenta hsa-miR-382 Colon
hsa-miR-215 Placenta hsa-miR-99b Colon hsa-miR-200a* Placenta
hsa-miR-370 Colon hsa-miR-200a Placenta hsa-miR-130b Colon
hsa-miR-196b Placenta hsa-miR-27a Colon hsa-miR-196a Placenta
hsa-miR-200cN Colon hsa-miR-194 Placenta hsa-miR-24 Colon
hsa-miR-192 Placenta hsa-miR-30a-5p Colon hsa-miR-141N Placenta
hsa-miR-30bN Colon hsa-miR-141 Placenta hsa-miR-221 Small
hsa-miR-490 Placenta hsa-miR-200c Intestine Small hsa-miR-451
Placenta hsa-miR-320 Intestine Small hsa-miR-429 Placenta
hsa-miR-127 Intestine Small hsa-miR-31 Placenta hsa-miR-485-5p
Intestine Small hsa-miR-215 Placenta hsa-miR-30b Intestine Small
hsa-miR-200bN Placenta hsa-miR-90a-3p Intestine Small hsa-miR-200b
Placenta hsa-miR-181a Intestine Small hsa-miR-200a* Placenta
hsa-miR-222 Intestine Small hsa-miR-198 Placenta hsa-miR-362
Intestine Small hsa-miR-194 Placenta hsa-miR-125a Intestine Small
hsa-miR-192 Placenta hsa-miR-323 Intestine Small hsa-miR-138
Placenta hsa-miR-451 Intestine Cervix hsa-miR-196b Placenta
hsa-miR-409-5p Cervix hsa-miR-99a Placenta hsa-miR-452 Heart
hsa-miR-1 Placenta hsa-miR-518b Heart hsa-miR-107 Placenta
hsa-miR-515-5p Heart hsa-miR-133a Placenta hsa-miR-130aN Heart
hsa-miR-189 Skeletal hsa-miR-206 Muscle Heart hsa-miR-221 Skeletal
hsa-miR-95 Muscle Heart hsa-miR-23bN Skeletal hsa-miR-133b Muscle
Heart hsa-miR-302a Skeletal hsa-miR-133a Muscle Heart hsa-miR-302b
Skeletal hsa-miR-128b Muscle Heart hsa-miR-302c Skeletal hsa-miR-1
Muscle Heart hsa-miR-302d Skeletal hsa-miR-489 Muscle Heart
hsa-miR-300-3p Skeletal hsa-miR-378 Muscle Heart hsa-miR-367
Skeletal hsa-miR-422a Muscle Heart hsa-miR-378 Skeletal
hsa-miR-128a Muscle Heart hsa-miR-422a Skeletal hsa-miR-196a Muscle
Heart hsa-miR-422b Skeletal hsa-miR-502 Muscle Heart hsa-miR-452
Spleen hsa-miR-223 Heart hsa-miR-490 Spleen hsa-miR-139 Heart
hsa-miR-491 Lymph Node hsa-miR-150 Heart hsa-miR-409 Lymph Node
hsa-miR-142-3p Heart hsa-miR-7a Lymph Node hsa-miR-146b Pericardium
hsa-miR-188 Lymph Node hsa-miR-146 Pericardium hsa-miR-369 Lymph
Node hsa-miR-155 Pericardium hsa-miR-305 Lymph Node hsa-miR-363
Pericardium hsa-miR-452 PBMC hsa-miR-128a Pericardium hsa-miR-224
PBMC hsa-miR-124b Pericardium hsa-miR-511 PBMC hsa-miR-124a
Pericardium hsa-miR-199b PBMC hsa-miR-137 Kidney hsa-miR-500 PBMC
hsa-miR-431 Kidney hsa-miR-204 PBMC hsa-miR-129 Kidney hsa-miR-480
PBMC hsa-miR-128b Kidney hsa-miR-190 PBMC hsa-miR-138 Kidney
hsa-miR-501 Thymus hsa-miR-183 Kidney hsa-miR-196a Thymus
hsa-miR-96 Kidney hsa-miR-211 Thymus hsa-miR-128b Kidney
hsa-miR-363 Thymus hsa-miR-213 Kidney hsa-miR-502 Thymus
hsa-miR-205 Kidney hsa-miR-184 Thymus hsa-miR-128a Liver
hsa-miR-122a Thymus hsa-miR-181bN Liver hsa-miR-30a-3p Thymus
hsa-miR-182 Lung hsa-miR-223 Thymus hsa-miR-181b Esophagus
hsa-miR-203 Thymus hsa-miR-181d Esophagus hsa-miR-205 Thymus
hsa-miR-181a Esophagus hsa-miR-145 Thymus hsa-miR-181c Esophagus
hsa-miR-210N Thymus hsa-miR-20b Esophagus hsa-miR-143 Thymus
hsa-miR-383 Esophagus hsa-miR-31 Thymus hsa-miR-17-5p Esophagus
hsa-miR-187 Thymus hsa-miR-142-3p Trachea hsa-miR-34b Stomach
hsa-miR-211 Trachea hsa-miR-205 Stomach hsa-miR-188 Trachea
hsa-miR-34cN Stomach hsa-miR-346 Trachea hsa-miR-34c Stomach
hsa-miR-200a* Prostate hsa-miR-363 Stomach hsa-miR-375 Prostate
hsa-miR-205 Stomach hsa-miR-148a Prostate hsa-miR-196b Stomach
hsa-miR-200a Ovary hsa-miR-502 Stomach hsa-miR-200b Ovary
hsa-miR-383 Stomach hsa-miR-200c Fallopian hsa-miR-34bN Stomach
hsa-miR-200bN Tube Fallopian hsa-miR-34b Stomach hsa-miR-212 Tube
Fallopian hsa-mi-34cN Stomach hsa-miR-31 Tube Fallopian hsa-miR-449
Stomach hsa-miR-7 Tube Fallopian hsa-miR-34c Stomach hsa-miR-153
Tube Fallopian hsa-miR-135a Stomach hsa-miR-429 Tube Pancreas
hsa-miR-217 Stomach hsa-miR-107 Pancreas hsa-miR-216 Stomach
hsa-miR-200cN Pancreas hsa-miR-375 Stomach hsa-miR-502 Pancreas
hsa-miR-98 Stomach hsa-miR-203 Pancreas hsa-miR-163 Testicle
hsa-miR-202 Pancreas hsa-miR-141N Testicle hsa-miR-506 Pancreas
hsa-miR-148a Testicle hsa-miR-507 Pancreas hsa-miR-141 Testicle
hsa-miR-510 Pancreas hsa-miR-7N Testicle hsa-miR-514 Pancreas
hsa-miR-494 Testicle hsa-miR-513 Pancreas hsa-miR-130b Testicle
hsa-miR-508 Pancreas hsa-miR-200cN Testicle hsa-miR-509 Pancreas
hsa-miR-148b Testicle hsa-miR-202* Pancreas hsa-miR-182 Testicle
hsa-miR-449 Pancreas hsa-miR-200a Testicle hsa-miR-34c Thyroid
hsa-miR-138 Testicle hsa-miR-432* Thyroid hsa-miR-135a Testicle
hsa-miR-184 Thyroid hsa-miR-206 Testicle hsa-miR-520c Thyroid
hsa-miR-95 Testicle hsa-miR-520l Thyroid hsa-miR-1 Testicle
hsa-miR-34cN Thyroid hsa-miR-7 Testicle hsa-miR-34b Uterus
hsa-miR-10b Testicle hsa-miR-520b Uterus hsa-miR-196b Testicle
hsa-miR-135b Uterus hsa-miR-502 Testicle hsa-miR-383 Testicle
hsa-miR-204 Testicle hsa-miR-34bN
[0089] It has been found that microRNA sequences and their
expression levels can differ depending on their location in
different types of body fluid samples. In other words, they can be
specific to a biological pathway, cell type, or tissue. This fact
can provide powerful diagnostic information as well.
[0090] Table 2 lists some microRNA sequences which have been found
to be highly abundant in different body fluids. The sequences in
bold font are unique to the listed body fluid.
TABLE-US-00002 TABLE 2 Tears Urine Breast Milk Seminal Fluid Saliva
Amniotic Fluid miR-518e miR-515-3p miR-518e miR-518e miR-335*
miR-518e miR-335* miR-335* miR-26a-2* miR-590-3p miR-515-3p
miR-335* miR-137 miR-892a miR-335* miR-588 miR-545* miR-302c
miR-515-3p miR-509-5p miR-490-5p miR-873 miR-492 miR-515-3p
miR-509-5p miR-223* miR-181d miR-590-5p miR-892a miR-452 miR-873
miR-302d miR-26a-1* miR-137 miR-518e miR-892a miR-223* miR-873
miR-137 miR-197 miR-27a miR-671-5p miR-892a miR-923 miR-524-5p
miR-515-5p miR-923 miR-515-5p miR-590-3p miR-616* miR-509-5p
miR-515-3p miR-509-5p miR-590-3p miR-302d miR-483-5p miR-513c
miR-218 miR-873 miR-593* miR-616* miR-134 miR-595 miR-20b
miR-483-5p miR-873 miR-590-5p miR-589 miR-515-3p miR-410 miR-616*
miR-137 miR-101* miR-556-3p miR-515-5p miR-335* miR-580 miR-410
miR-130a miR-101* miR-598 miR-617 miR-609 miR-548d-5p miR-410
miR-138 miR-130a miR-671-5p miR-302d miR-223* miR-195 miR-652
miR-181b miR-524-5p miR-25* miR-590-5p miR-675 miR-325 miR-671-5p
miR-892a miR-134 miR-616* miR-325 let-7i miR-892a miR-181d miR-92b
miR-302d miR-134 miR-377* miR-578 miR-545* miR-598 miR-509-5p
miR-29b miR-545* miR-580 miR-1 let-7a miR-210 Bronchial Lavage CSF
Pleural Fluid Peritoneal Fluid Colostrum Plasma miR-515-3p
miR-515-3p miR-515-3p miR-892a miR-509-5p miR-335* miR-335*
miR-335* miR-892a miR-518e miR-181d miR-325 miR-509-5p miR-892a
miR-509-5p miR-515-3p miR-335* miR-377* miR-483-5p miR-223* miR-134
miR-134 miR-518e miR-586 miR-892a miR-873 miR-590-5p miR-509-5p
miR-515-5p miR-518e miR-223* miR-509-5p miR-515-5p miR-223*
miR-223* let-7i miR-873 miR-302d miR-873 miR-515-5p miR-671-5p
miR-539 miR-1225-3p miR-616* miR-335* miR-616* miR-873 miR-616*
miR-302d miR-134 miR-920 miR-137 miR-483-5p miR-302d miR-545*
miR-483-5p miR-616* miR-873 miR-186 miR-589 miR-324-3p miR-325
miR-302d miR-483-5p miR-515-3p miR-556-3p miR-616* miR-151-5p
miR-518e miR-518c miR-616* miR-151-3p miR-92b miR-589 miR-923
miR-92b miR-134 miR-548b-3p miR-25* miR-377* miR-589 miR-923
miR-892a miR-192 miR-539 miR-923 miR-377* miR-302d miR-590-5p
miR-151-5p miR-923 miR-652 miR-410 miR-374a miR-590-3p miR-598
miR-192 miR-518e miR-137 miR-598 miR-425 miR-187 miR-134 miR-556-3p
miR-671-5p miR-937 miR-454 miR-873 miR-371-3p miR-767-3p miR-151-5p
miR-335* miR-101* miR-218 miR-580 miR-505 miR-223* miR-885-5p
miR-132 miR-923
[0091] With the diagnostic information obtained, a physiological
condition could be detected, identified, predicted, treated, and/or
monitored. For example, a treatment could be administered based on
the identity of the physiological condition. A particular treatment
could be monitored by taking a first sample, administering the
treatment, taking a second sample, and comparing the microRNA
profiles of the two samples to identify and/or track changes
resulting from the treatment. Those changes could include the
amounts of a particular microRNA sequence, or the identity of the
differentially expressed microRNA sequences that have changed
between the two samples.
[0092] It is also contemplated that manipulating the levels of
microRNA sequences might itself be a treatment for a physiological
condition. The microRNA level could be altered by constructing a
specific DNA or RNA sequence related to the microRNA sequences,
then delivering that DNA or RNA sequence to a targeted cell,
tissue, or organ expressing the targeted microRNA sequences.
[0093] As discussed below, specific microRNA sequences are
identified that may be useful in diagnosing and/or treating liver
disease or injury, lung disease or injury, and neurological disease
or injury. Such conditions include chronic obstructive pulmonary
disease (COPD) and idiopathic pulmonary fibrosis (IPF) (also known
as interstitial lung disease (ILD)).
[0094] Other methods embodied herein include generating a microRNA
profile from a biological sample. The microRNA profile comprises
the amounts of specific microRNA sequences. The amounts of those
specific microRNA sequences are then compared to a reference to
provide information for detecting or predicting the lung condition.
In this regard, the microRNA profile may include those specific
microRNA sequences identified below in the examples, or a subset
thereof. Such microRNA profiles would be smaller, faster, and
provide the same diagnostic information as larger test kits.
[0095] The following examples are provided to illustrate the
devices and methods of the present disclosure. The examples are
merely illustrative and are not intended to limit the disclosure to
the materials, conditions, or process parameters set forth
therein.
EXAMPLES
Isolation of microRNA
[0096] microRNA can be isolated using glass filter based methods to
selectively bind RNA in a high salt buffer. The unwanted
biomolecules can then be washed off by using high salt buffers
containing at least 50% alcohol. The bound pure RNA can then eluted
off the glass membrane with low salt buffer or RNAse-free
water.
[0097] 1). Isolating microRNA from Solid Tissues
[0098] Briefly, total RNA, including microRNA, was isolated using
commercial kits such as miRNeasy mini kit (Qiagen Inc. Valencia,
Calif.). Approximately 5 mg to 50 mg tissue samples were excised
from flash-frozen tissue. After placing the tissue sample into a
Dounce tissue grinder, 700 microliter (.mu.l) QIAzol lysis reagent
was added to the grinder and the tissue was homogenized
immediately. For every 700 .mu.l QIAzol lysis reagent used, 140
.mu.l chloroform was added to the tissue lysate to extract the
water soluble content. After mixing for 15 seconds, the lysate was
placed in a centrifuge and spun at 12000.times.g for 15 minutes at
room temperature. The upper aqueous phase (containing the RNA) was
then transferred to a new collection tube, and 1.5 volumes of
ethanol was added. The sample was then transferred to a cartridge
containing a glass filter (i.e. silica membrane) so that RNA could
attach to the glass filter. The contaminants were washed off the
silica membrane by applying different high salt washing buffers
included in the miRNeasy kit. The bound pure RNA was then eluted
off the membrane with water or low salt buffer.
[0099] 2). Isolating microRNA from Liquid Samples
[0100] Approximately, 800 .mu.l of QIAzol lysis reagent was added
to 200 .mu.l liquid sample. The sample was mixed in a tube followed
by adding 200 .mu.l of chloroform. After mixing rigorously for 15
seconds, the sample was then centrifuged at 12,000.times.g for 15
minutes. The upper aqueous phase was carefully transferred to a new
collection tube, and 1.5 total volumes of ethanol was added. The
sample was then applied directly to a glass membrane containing
column and the RNA was bound and purified by three contiguous
washing to remove unwanted contamination. The immobilized RNA was
then collected from the membrane with a low salt elution
buffer.
[0101] The yield of microRNA from different amount of liquid
samples used in these protocols was tested. The best ratio was
found to be 4 volumes of lysis buffer with 1 volume of liquid
sample.
[0102] The quality and quantity of RNA isolated was evaluated by
RNA by NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific
Inc. Waltham, Mass.) and the Agilent 2100 Bioanalyzer (Agilent Inc.
Santa Clara, Calif.).
[0103] FIG. 1A shows an electropherogram of RNA isolated from solid
tissue, while FIG. 1B shows an electropherogram of RNA isolated
from a liquid sample. The 18S and 28S peaks are clearly visible and
marked. The microRNA are located on the left of both
electropherograms. This region also contains all degraded RNA.
Array Hybridization and Quantitative PCR
[0104] Agilent's human and mouse microRNA microarray kits (Agilent
Inc. Santa Clara, Calif.) were used as the array platform; however,
arrays from different companies including Affymetrix and Exiqon
have also been used. The human microRNA microarray contained probes
for 723 human and 76 human viral microRNAs from the Sanger database
v 10.1. The mouse microRNA microarray contained probes for 567
mouse and 10 mouse herpes virus microRNA sequences from the Sanger
database v 10.1. Cyanine 3-pCp labeled RNA (i.e. RNA labeled with
Cyanine 3-Cytidine bisphosphate) for array hybridization was
generated by 100 nanograms (ng) of total RNA using Agilent's
microRNA complete labeling and hybridization kit. All the steps,
including labeling, hybridization, washing, scanning and feature
extraction were performed in accordance with the manufacturer's
instructions.
[0105] In brief, 100 ng of total RNA was dephosphorylated with calf
intestinal alkaline phosphatase, then heat and DMSO treated to
yield denatured RNA. Cyanine 3-Cytidine bisphosphate was joined to
the microRNA by T4 RNA ligase. MicroBioSpin 6 columns were used to
desalt the samples and remove any unincorporated fluorophores. The
samples were hybridized to 8.times.15K Agilent Human microRNA (V2)
or Mouse microRNA microarrays in a rotating hybridization oven for
20 hours at 55.degree. C. and 10 rpm. The arrays were washed for 5
minutes in Agilent GE Wash Buffer 1 with Triton X-102 and then for
another 5 minutes in Agilent GE Wash Buffer 2 with Triton
X-102.
[0106] After washing, all slides were immediately scanned using a
PerkinElmer ScanArray Express at 5 micron resolution. The resulting
images were quantified using Agilent's Feature Extraction software.
The differentially expressed microRNA sequences were then
identified using a standard protocol developed for gene array data
processing. The sample or gene clustering and array hybridization
heatmap were generated using MeV4 software package from The
Institute for Genomic Research (TIGR) (available at
http://www.tigr.org/tdb/microarray/).
[0107] Quantitative PCR (QPCR) with microRNA specific primer sets
were used to confirm the results from array hybridization. In
brief, a SYBR Green based method, miScript real-time PCR (Qiagen
Inc. Valencia, Calif., USA), or TaqMan primer set from Apply
Biosystems, was used with 50 ng of total RNA from each sample. The
first strand cDNA was generated according to the manufacturer's
instruction. Approximately 2.5 ng of cDNA was used in the PCR
reaction. The yield of 18 to 20 base pair fragments (based on SYBR
Green intensity) corresponding to the specific microRNA species was
monitored with the 7900HT fast real-time PCR system from Applied
Biosystems (Applied Biosystems, Foster City, Calif.). QPCR results
were analyzed by SDS 2.2.2, with a manual CT threshold value of
0.2.
Example 1
[0108] This example showed that microRNA sequences could be used as
a marker to detect liver injury. Mice were used as the experimental
model.
[0109] 6-month-old male C57/B6 mice were grouped into control and
treatment groups with 4 animals in each group. The mice then fasted
for 24 hours prior to a single intraperitoneal injection of either
(a) 300 mg/kg of acetaminophen in phosphate buffer saline (PBS)
(treatment group); (b) or PBS (control group). Mice were sacrificed
at different time points post-exposure (12 hr, 24 hr, 48 hr, 72 hr,
and 120 hr) and plasma and liver samples were collected. Part of
the liver samples were sectioned and examined by a pathologist and
the serum alanine transaminase (ALT) levels were also determined to
confirm as well as assess the severity of liver injury.
[0110] Total RNA was isolated from collected samples to conduct
comprehensive microRNA analyses. To assess the level of microRNA in
liver tissues, a microRNA array from Agilent was used. The RNA
samples were labeled and processed according to the manufacturer's
recommended protocols. The data from each array were extracted,
normalized and compared following a standard gene expression
microarray method.
[0111] The expression levels of various microRNA sequences in the
liver tissues were used to generate a microRNA profile and used to
assess tissue injury. Differentially expressed microRNA sequences
were clustered using the Hierarchical clustering method and the
result is shown in FIG. 2. The different time points are indicated
on the top, while the identity of individual microRNA sequences is
listed on the right. (The identifying labels correspond to those in
the miRNA Registry maintained at the Sanger Institute.) The
hybridization intensity of individual microRNA sequences is
represented in different colors as indicated on top of the figure
(yellow representing the highest expression and blue representing
the lowest expression signal). The microRNA profile clearly
indicates that the levels of some microRNA sequences were changed
by the exposure to acetaminophen.
Example 2
[0112] This example showed that the levels of specific microRNA
sequences in the serum or plasma could be used to assess
drug-induced liver injury.
[0113] The male C57/B6 mice were randomly grouped into two groups,
a treatment group (3 animals) and control group (4 animals). They
fasted for 24 hours prior to a single intraperitoneal injection of
either (a) 300 mg/kg of acetaminophen in PBS (treatment group); or
(b) PBS (control group). Mice were sacrificed at 24 hours post
exposure, the plasma samples were collected and RNA was
isolated.
[0114] The expression levels of microRNA sequences in the serum
were used to make a microRNA profile. The differentially expressed
microRNA sequences between the treatment group and the control
group were clustered with the Hierarchical clustering method and is
shown in FIG. 3. The result clearly indicated that the levels of
certain microRNA sequences in the serum could be used as an
indication of the acetaminophen toxicity.
Example 3
[0115] This example showed that the levels of specific microRNA
sequences in the serum or plasma could be used as an early
indication of drug-induced liver injury.
[0116] The male C57/B6 mice were randomly grouped into nine
different groups with 4 animals in each group. They fasted for 24
hours prior to a single intraperitoneal injection with either (a)
75 mg/Kg of acetaminophen in PBS (treatment 1); (b) 150 mg/Kg of
acetaminophen in PBS (treatment 2); (c) 300 mg/Kg of acetaminophen
in PBS (treatment 3); or (d) PBS (control group). Mice were
sacrificed and plasma samples were collected at 1, 3 and 24 hours
post-exposure. The nine groups were: 1) 1 hour control; 2) 1 hour
treatment 1; 3) 1 hour treatment 2; 4) 1 hour treatment 3; 5) 3
hour control; 6) 3 hour treatment 1; 7) 3 hour treatment 2; 8) 3
hour treatment 3; and 9) 24 hour treatment 3. The group at 24 hr
post-exposure received only the highest dose (300 mg/kg) to serve
as a positive control. The expression levels of two different
microRNA sequences, mir-486 and mir-122, in the serum were profiled
by quantitative polymerase chain reactions (Q-PCR).
[0117] The median intensities (Z-axes) from each group (X-axis) at
PCR cycle number 19 were plotted. This graph is shown in FIG. 4.
Both mir-486 (red bars) and mir-122 (green bars) intensities showed
dose-dependent changes at 3 hr post-exposure. The intensity of
mir-122 at 300 mg/kg was almost the same between 3 hr and 24 hr
post-exposure. Clear changes were observed in the samples obtained
at one hour post-acetaminophen injection. The results clearly
indicated that the levels of selected microRNA sequences, such as
mir-122 and mir-486, in the serum could be used as an early
indication of tissue injury.
[0118] Next, the ratios of the median intensities (green bars) and
average intensities (blue bars) from each group at PCR cycle number
19 were plotted. This graph is shown as FIG. 5. As expected, the
ratios of both median and average intensities showed dose-dependent
changes at 3 hr post-exposure. The ratio also clearly indicated the
difference between 3 hr and 24 hr post-exposure. This result
clearly indicated the ratio of selected microRNA sequences, such as
mir-122 and mir-486, in the serum could be used as an early
indication of tissue injury.
Example 4
[0119] This example showed that microRNA could be used in assessing
neurological disorders. The microRNA expression patterns in brain
tissues obtained from normal and prion infected animals were
profiled as described above. The results are shown in FIG. 6. The
result clearly indicated differences between normal and diseased
samples.
Example 5
[0120] This example showed that microRNA could be used in assessing
the health status of lungs. The microRNA expression patterns in
lung tissues obtained from normal and diseased animals were
profiled as described above. The results are shown in FIG. 7. The
result clearly indicated there were differences on microRNA
expression as the disease progressed (from 1 to 6 where 6 has the
most serious disease condition) and a number of microRNA sequences
are different between normal and disease samples. Thus, specific
microRNA sequences or a panel of microRNA sequences could be used
as a tool to assess the health status of lungs.
Example 6
[0121] This example showed that different biological pathways or
compartments had very different microRNA profiles. The microRNA
profiles in serum and urine samples obtained from a normal mouse
were profiled as described above, then compared. The result is
shown in FIG. 8. The result clearly revealed a significant
difference in the microRNA composition in different body fluids.
This would allow the development of different biomarkers to be used
in different body fluids to assess the health status of tissues. In
addition, microRNA sequences in a specific body fluid can be used
as a reliable tool to assess the health status of tissues
intimately associated with that body fluid, e.g. bladder and kidney
tissues to the urine.
Example 7
[0122] miRNA profiles from lung tissue and plasma from ILD patients
and COPD patients were compared to a control set of miRNA profiles
from uninvolved lung tissue obtained from lung cancer resections
(controls) and a control set of miRNA profiles from plasma samples
obtained from clinically normal donors (collected by the Marsh
lab). The miRNA profiles were compared in various pairwise
combinations to determine which miRNA sequences were overexpressed
and thus useful for diagnostic purposes. The miRNA profiles were
obtained using a microarray kit available from Agilent, which
generally detected a given miRNA with usually two independent
oligonucleotide (oligo) targets and four or more in some cases.
[0123] FIG. 9 shows the graph comparing miRNA expression levels in
control plasma with ILD plasma. Note the log scale. MiRNA with
expression values that differ substantially between the two samples
reside away from the diagonal line (i.e. y=x) that would represent
equivalent expression in the two samples. This graph indicated that
many miRNAs in ILD plasma are expressed at substantially higher
levels than in the control plasma. There also appear to be a few
miRNAs in the control profile that were expressed at relatively
lower levels than in the ILD profile.
[0124] Next, in order to reduce the complexity of the data, the
similarity of the signals returned by the different oligos that
were present on the Agilent array and designed to detect a given
miRNA were examined. For example, miRNA 1225-5p (i.e. mir-1225-5p)
was about 3-fold over expressed in ILD plasma. For mir-1225-5p,
four probe oligos were used in the Agilent array. FIG. 10A shows
the signal in the ILD plasma samples (n=24). FIG. 10B shows the
signal in the control plasma samples (n=6). As seen, all four probe
oligos gave signals in the ILD and control plasma samples. In
addition, the signal strengths were within a factor of about two to
each other, even though these oligos differ slightly in
sequence.
[0125] 17 miRNA sequences were identified that appeared to be
overexpressed in the ILD plasma samples. FIG. 11 shows the signal
strength for all of the oligos that targeted these 17 sequences.
The ILD plasma signals are shown as blue diamonds and the control
plasma signals are shown as pink squares. As seen, the signal
strengths for all of the independent oligo probes were reasonably
close (i.e. within a factor of 2.5).
[0126] Since the signals from the independent probes were close,
the data from all probes was combined. Then, the mean expression
level for each miRNA was calculated and miRNA sequences which were
relatively overexpressed in the ILD plasma samples were identified.
(An alternative analysis path could have been to choose the data
from one or two of the independent probes and identify
overexpressed miRNA sequences based on that data.)
[0127] FIG. 12 shows the resulting graph with the mean and one
standard deviation identified. Again, the ILD plasma signals are
shown as blue diamonds and the control plasma signals are shown as
pink squares. The expression of the displayed microRNAs was at
least two-fold higher in the ILD plasma samples than in the control
plasma samples (2.times. was an arbitrary value). Table 3 lists the
specific data of FIG. 12.
TABLE-US-00003 TABLE 3 mean mean mean ILD/ microRNA level St. Dev.
level St. Dev. mean sequence (ILD) (ILD) (control) (control)
control hsv1-miR-H1 371 100 207 13.9 1.8 hsa-miR-223 688 317 338
105 2.0 hsa-miR-575 416 17 198 21.4 2.1 hsa-miR-483-5p 589 179 259
70.1 2.3 hsa-miR-150* 659 142 267 35.6 2.5 hsa-miR-22 958 589 376
91 2.5 hsa-miR-1225-5p 3361 873 1201 324.4 2.8 hsa-miR-939 644 463
224 36.5 2.9 hsa-miR-135a* 499 127 172 33.2 2.9 hsa-miR-940 1316
906 341 45.6 3.9 hsa-miR-134 830 9 201 50 4.1 hcmv-miR-UL70-3p 721
129 166 25.2 4.3 hsa-miR-630 3349 65 683 100.3 4.9 hsv1-miR-LAT
1250 490 223 64.2 5.6 kshv-miR-K12-3 3542 2912 588 422.3 6.0
hsa-miR-638 18055 11123 1670 716.2 10.8 hsa-miR-923 42215 40796 310
9883.1 136.2
[0128] Based on the standard deviations, the 17 miRNAs that met
this criterion can be divided into three groups. 11 miRNAs
(UL70-3p, 1225-5p, 134, 135a*, 150*, 483-5p, 575, 630, 638, H1, and
LAT) were likely to be differentially expressed between ILD and
control with high confidence. There was intermediate confidence for
4 miRNAs (mir-22, 223, 939, and 940); and lower confidence for
miRNAs 923 and K12-3.
[0129] The degree of over expression displayed by these miRNAs
varied over 100-fold, as shown in FIG. 13. Note the log scale.
[0130] Next, the miRNA that were expressed at a higher level in
control plasma than ILD plasma were investigated. An arbitrary
expression level of 250 or greater and 3.0 fold or greater relative
overexpression as used to screen out marginal miRNA candidates.
Three miRNA sequences passed this screen as shown in Table 4.
TABLE-US-00004 TABLE 4 mean mean mean control/ microRNA level St.
Dev. level St. Dev. mean sequence (ILD) (ILD) (control) (control)
ILD hsa-miR-451 729 1695.917 5274 5362.923 7 oligo 1 hsa-miR-451;
487 1096.762 3527.167 3421.076 7 oligo 2 hsa-miR-451; 390 375 5274
13.5 oligo 1 w/o outlier hsa-miR-451; 268 243 3527 13.1 oligo 2 w/o
outlier hsa-miR-448 64 38.3 253 93 4 hsa-miR-92a-2* 78 46.94568
253.6667 109.7154 3
[0131] hsa-miR-448 and hiss-miR-92-a-2* were just over the
threshold for inclusion and showed low absolute expression. The
standard deviation for hsa-miR-451 was rather large when all
samples (n=24) were used. However, when one outlier was removed
(n=23), the standard deviations improved, as did the ratios.
hsa-miR-451 was expressed ten times higher in control plasma
relative to ILD plasma.
[0132] One of the miRNAs that is overexpressed in control serum
relative to ILD serum, in combination with a miRNA that is
overexpressed in ILD serum relative to control serum, could be used
in a simple "top scoring pair" test for ILD.
Example 8
[0133] Using the same data as in Example 7, the expression of miRNA
in both ILD plasma and ILD tissue was examined. That graph is shown
in FIG. 14. While many miRNAs that were expressed in ILD plasma had
little or no expression in ILD tissue, most of those that were
expressed in tissue had at least some expression in plasma. Those
miRNA sequences that had signal strength of at least 1000 in both
tissue and plasma (an arbitrarily chosen value) are listed in Table
5. The ratio of the expression for the miRNA sequence was also
compared to the average expression of all the miRNAs in the sample
and is labeled as "overexpression ratio."
TABLE-US-00005 TABLE 5 mean mean microRNA level overexpression
level overexpression sequence (plasma) ratio (tissue) ratio
hsa-miR-1225-5p 4043 9.8 1189.0 3.1 hsa-miR-21 455 1.1 9938.7 26.0
hsa-miR-22 1374 3.3 5555.8 14.5 hsa-miR-223 835 2.0 1303.4 3.4
hsa-miR-451 729 1.8 6564.4 17.2 hsa-miR-638 25920 62.6 1084.6 2.8
hsa-miR-923 71062 171.7 6114.7 16.0 kshv-miR-K12-3 5602 13.5 498.0
1.3
[0134] hsa-miR-21 was present here, but not in Tables 3 or 4, while
the other seven were also listed in either Table 3 or 4.
Example 9
[0135] Using the same data as in Example 7, the expression of miRNA
in both ILD lung tissue and control lung tissue was examined. That
graph is shown in FIG. 15. The expression levels for certain miRNA
sequences, as well as those overexpressed in ILD lung tissue, are
listed below in Table 6.
TABLE-US-00006 TABLE 6 microRNA mean level mean level mean ILD/
sequence (ILD) (control) mean control hsa-miR-923 6114.7 22421.33
0.3 hsa-miR-22 5555.8 4771.83 1.2 hsa-miR-29a 4881.6 2183.67 2.2
hsa-miR-145 3759.9 1449.50 2.6 hsa-miR-26a 3187.3 1123.33 2.8
hsa-let-7c 4405.5 1336.33 3.3 hsa-miR-23a 4396.1 1144.83 3.8
hsa-miR-21 9938.7 2450.83 4.1 hsa-miR-125b 3843.2 939.17 4.1
hsa-miR-27a 3090.2 720.50 4.3 hsa-let-7a 5709.2 1039.33 5.5
hsa-let-7f 3352.5 504.83 6.6 hsa-miR-451 6564.4 383.33 17.1
[0136] miRNA hsa-miR-923 was over 130-fold over-expressed in ILD
plasma relative to control plasma (Table 3), but it is
under-expressed in ILD lung tissue relative to control lung tissue
(Table 6). This suggests the tissue or cell of origin for this
miRNA may be within the blood itself, or at least not the ILD lung.
Similarly, miRNA hsa-miR-22 is expressed three times higher in ILD
plasma compared to control plasma (Table 3), but is expressed at
nearly the same level in ILD lung and control lung tissue (Table
6). Other miRNAs that are characteristic of ILD, such as miRNA-451,
were elevated in ILD lung tissue (17.times. in Table 6) but not in
ILD plasma (see Table 4).
[0137] In total 17 miRNA sequences were identified as containing
diagnostic information related to ILD. Those 17 sequences are
listed in Table 3.
Example 10
[0138] The plasma sample data (control, COPD, and ILD) was
separately analyzed using the Panorama suite of tools and consisted
of the following steps: (A) Normalization; (B) Quality Control; (C)
Cluster Analysis; (D) Panel Selection; and (E) Comparison. Each
step is explained in more detail below.
[0139] In Normalization, the following steps occurred. First,
missing values were left unchanged instead of imputing a value.
Second, each sample was normalized independently of other samples.
Third, the natural log was applied to the values for each sample;
then the values were adjusted by the median and standard deviation.
FIG. 16 shows the results of normalization.
[0140] In Quality Control, the quality of the data was assessed
before and after normalization. FIG. 17A shows the Pearson
correlation distribution before normalization. This figure
correlated the score for each miRNA across the samples to the total
miRNA expression level across the samples. This figure showed that
the vast majority of miRNA sequences had the same expression
profile across the samples, and furthermore, this expression
profile is the total miRNA level per sample--this is the dominant
feature of the dataset. FIG. 17B shows the Pearson correlation
distribution after normalization. Normalization improved the
quality of the dataset. The distribution in FIG. 17B was much less
skewed than that of FIG. 17A.
[0141] In Cluster Analysis, the normalized miRNA data was clustered
using multi-dimensional scaling (MDS); the results are presented in
FIG. 18. This was an unsupervised analysis without samples being
identified by group or miRNA selected that differentiated the
groups. There were several notable features of this plot. First,
the samples within each group clustered together showing uniformity
in miRNA expression. The exception was IPF tissue where a few
outliers occurred, likely due to sample handling. Second, the
tissue groups cluster away from the plasma groups. Third, within
the plasma groups, the COPD and ILD plasma samples overlapped and
were clustered away from the plasma control samples.
[0142] Performing a T-test at significance level 0.01, 194 miRNA
were found to separate the plasma control samples from the ILD
plasma samples. Performing 50 permutation tests revealed that the
expected number of miRNA, by chance alone, was 21.5, yielding a
false discovery rate of 11%. The p-value distribution of all miRNA
is shown in FIG. 19. There was a uniform distribution over most
p-values, except an increase below 0.05. This was consistent with
the hypothesis that there are miRNA that segregate the two sample
groups.
[0143] In Panel Selection, panels that segregated the control
plasma samples from the ILD plasma samples were selected using Area
Under the Curve (AOC). AOC is a measure of diagnostic segregation.
It ranges from 0 to 1 where 1 indicates perfect segregation. The
AUC of individual miRNA can be determined independently of each
other allowing for straightforward selection of the best
segregating miRNA. In addition, the combined AUC of panels of miRNA
can be calculated to assess how well groups of miRNA work together
to segregate control plasma samples from ILD plasma samples.
[0144] To calculate the combined AUC, a combination rule must be
established. The combination rule used here was majority consensus:
if the strict majority of miRNA classified a sample as diseased
(i.e. ILD or IPF) then the sample was classified diseased,
otherwise, the sample was classified as normal.
[0145] FIG. 20 is three charts showing the distribution of
directional bias (upper left), the AUC distribution (upper right),
and the standard deviation for the ILD group (lower left). The
number of miRNA higher in the control samples than the ILD samples
was essentially the same as the opposite direction. The
distribution of AUC scores for all miRNA was centered about 0.6
which is expected. A small rise around 0.95 indicated the presence
of miRNA that distinguish the control and ILD samples. The
distribution of miRNA expression standard deviations showed that
overall, variability was similar across miRNA (note that
normalization is done by sample, not by miRNA).
[0146] In Comparison, the data was analyzed. Using an AUC threshold
of 0.95, 57 out of 2421 (2.4%) miRNA probes were selected. Table 7
contains the oligo probe used for the miRNA, the corresponding
miRNA, p-value, AUC, and number of panels of 3 miRNA above combined
AUC 0.99 that each miRNA participated in. If the miRNA was
expressed higher in the control sample than the ILD sample, the
column "Control>ILD" was marked with a Y.
TABLE-US-00007 TABLE 7 Probe miRNA Control > ILD P-value AUC St.
Dev. # Panels A_25_P00010804 hsa-miR-518d-3p Y 9.96E-06 1.00 0.42
945 A_25_P00013406 hsa-miR-135a* N 1.56E-09 1.00 0.55 681
A_25_P00013825 hiv1-miR-H1 N 4.98E-06 1.00 0.66 656 A_25_P00011724
hcmv-miR-UL70-3p N 1.23E-13 1.00 0.62 621 A_25_P00013407
hsa-miR-135a* N 1.41E-12 1.00 0.62 615 A_25_P00013090 hsa-miR-940 N
8.13E-09 1.00 0.88 581 A_25_P00012074 hsa-miR-139-3p N 3.27E-07
1.00 0.63 572 A_25_P00013689 kshv-miR-K12-3 N 1.09E-11 1.00 0.60
572 A_25_P00012231 hsa-miR-134 N 9.11E-11 1.00 0.64 548
A_25_P00012230 hsa-miR-134 N 6.22E-13 1.00 0.65 539 A_25_P00010345
hsa-miR-557 N 2.47E-06 1.00 0.55 534 A_25_P00013829 hsv1-miR-LAT N
1.52E-11 1.00 0.77 500 A_25_P00011725 hcmv-miR-UL70-3p N 6.62E-13
1.00 0.65 463 A_25_P00013830 hsv1-miR-LAT N 1.42E-12 1.00 0.65 449
A_25_P00013831 hsv1-miR-LAT N 2.62E-09 1.00 0.84 449 A_25_P00013087
hsa-miR-939 N 3.19E-13 1.00 0.53 362 A_25_P00013453 hsa-miR-150* N
1.67E-08 1.00 0.58 362 A_25_P00014907 hsa-miR-1224-5p N 6.43E-07
1.00 0.47 344 A_25_P00013326 hsa-miR-187* N 1.24E-06 1.00 0.70 324
A_25_P00013828 hsv1-miR-LAT N 1.33E-12 1.00 0.80 299 A_25_P00011853
ebv-miR-BART13 N 4.09E-08 0.99 0.47 435 A_25_P00015004
hsa-miR-1226* N 2.14E-06 0.99 0.66 362 A_25_P00010687 hsa-miR-498 N
7.82E-08 0.99 0.46 498 A_25_P00011096 hsa-miR-572 N 3.25E-08 0.99
0.81 420 A_25_P00010808 hsa-miR-575 N 2.42E-07 0.99 0.85 415
A_25_P00014908 hsa-miR-1224-5p N 4.81E-07 0.99 0.60 344
A_25_P00014896 hsa-miR-575 N 4.23E-07 0.99 0.82 316 A_25_P00010641
hsa-miR-601 N 2.63E-08 0.99 0.49 218 A_25_P00013086 hsa-miR-939 N
1.09E-07 0.99 0.49 179 A_25_P00013450 hsa-miR-150* N 2.91E-08 0.99
0.67 178 A_25_P00010344 hsa-miR-557 N 5.45E-06 0.98 0.65 684
A_25_P00013327 hsa-miR-187* N 1.06E-05 0.98 0.65 347 A_25_P00015003
hsa-miR-1226* N 2.15E-06 0.98 0.61 179 A_25_P00013451 hsa-miR-150*
N 1.39E-06 0.98 0.67 178 A_25_P00014906 hsa-miR-1224-5p N 2.03E-07
0.97 0.55 330 A_25_P00012059 hsa-miR-198 N 1.13E-05 0.97 0.67 296
A_25_P00011799 hsv1-miR-H1 N 6.61E-07 0.97 0.98 268 A_25_P00011097
hsa-miR-572 N 6E-05 0.97 0.60 203 A_25_P00013452 hsa-miR-150* N
8.41E-07 0.97 0.62 179 A_25_P00010669 hsa-miR-326 N 7.84E-05 0.97
0.83 177 A_25_P00014892 hsa-miR-539 N 0.000543 0.97 0.59 722
A_25_P00010444 hsa-miR-448 N 6.72E-05 0.97 0.58 581 A_25_P00012030
hsa-miR-92a N 1.18E-05 0.97 0.86 343 A_25_P00013448 hsa-miR-149* N
1.95E-05 0.97 0.58 260 A_25_P00014861 hsa-miR-483-5p N 2.9E-07 0.97
0.62 144 A_25_P00010228 hsa-miR-623 N 5.7E-05 0.96 0.79 356
A_25_P00012419 hsa-miR-423-5p N 0.000569 0.96 0.87 336
A_25_P00011796 hsv1-miR-H1 N 2.96E-06 0.96 0.69 268 A_25_P00011854
ebv-miR-BART13 N 0.000141 0.96 0.73 268 A_25_P00011719
ebv-miR-BART7 N 7.87E-05 0.96 0.57 224 A_25_P00012459
hsa-miR-483-5p N 2.03E-07 0.96 0.66 178 A_25_P00013449 hsa-miR-149*
N 1.55E-06 0.96 0.66 164 A_25_P00012262 hsa-miR-320 N 5.41E-05 0.96
0.73 84 A_25_P00011342 hsa-miR-765 N 5.08E-06 0.96 0.38 57
A_25_P00013324 hsa-miR-187* N 5.29E-05 0.95 0.68 477 A_25_P00010227
hsa-miR-623 N 4.89E-05 0.95 0.97 362 A_25_P00012031 hsa-miR-92a N
2.59E-05 0.95 1.07 343
[0147] Interestingly, only 3 of the 57 miRNA were higher in the
control samples than the ILD samples, despite the near equivalence
of miRNA higher in control samples over ILD samples, as compared to
the opposite among all miRNA (see FIG. 20). 20 of the 57 miRNA had
a perfect AUC score of 1.00. Not shown here is the fact that there
were also many panels of three miRNA that had a perfect AUC score
of 1.00.
[0148] There were also unique miRNA among the 57 miRNA probes,
which illustrated a strong redundancy among probes. This redundancy
could be used as a selection criterion.
[0149] 11 of the 17 miRNA sequences listed in Table 3 of Example 7
also appear in Table 7. They are shown in bold text in Table 7.
[0150] The claims refer to identifying "at least one" or "at least
two" differentially expressed microRNA sequences in a microRNA
profile, wherein the differentially expressed microRNA sequences
are selected from a list. This language should be construed as
meaning that the microRNA sequence selected from the list is
identified as a differentially expressed microRNA sequence in the
microRNA profile.
[0151] It is contemplated that assays or microRNA profiles would
test for only specific microRNA sequences, such as those identified
above.
[0152] In some embodiments, an assay or microRNA profile tests for
at least two microRNA sequences selected from the group consisting
of miR-630, miR-134, hcmv-miR-UL70-3p, miR-1225-5p, miR-135a*,
miR-150*, miR-22, miR-223, miR-483-5p, miR-575, miR-638, miR-923,
miR-939, miR-940, hsv1-miR-H1, hsv1-miR-LAT, kshv-miR-K12-3, and
human orthologs thereof. In other embodiments, at least three of
these sequences is tested for. In particular embodiments, all 17 of
these sequences are tested for. Specific pairs of these 17 microRNA
sequences include those listed in Table 8:
TABLE-US-00008 TABLE 8 miR-630, miR-134 miR-630, hcmv-miR-UL70-3p
miR-630, miR-1225-5p miR-630, miR-135a* miR-630, miR-150* miR-630,
miR-22 miR-630, miR-223 miR-630, miR-483-5p miR-630, miR-575
miR-630, miR-638 miR-630, miR-923 miR-630, miR-939 miR-630, miR-940
miR-630, hsv1-miR-H1 miR-630, hsv1-miR-LAT miR-630, kshv-miR-K12-3
miR-134, hcmv-miR-UL70-3p miR-134, miR-1225-5p miR-134, miR-135a*
miR-134, miR-150* miR-134, miR-22 miR-134, miR-223 miR-134,
miR-483-5p miR-134, miR-575 miR-134, miR-638 miR-134, miR-923
miR-134, miR-939 miR-134, miR-940 miR-134, hsv1-miR-H1 miR-134,
hsv1-miR-LAT miR-134, kshv-miR-K12-3 hcmv-miR-UL70-3p, miR-1225-5p
hcmv-miR-UL70-3p, miR-135a* hcmv-miR-UL70-3p, miR-150*
hcmv-miR-UL70-3p, miR-22 hcmv-miR-UL70-3p, miR-223
hcmv-miR-UL70-3p, miR-483-5p hcmv-miR-UL70-3p, miR-575
hcmv-miR-UL70-3p, miR-638 hcmv-miR-UL70-3p, miR-923
hcmv-miR-UL70-3p, miR-939 hcmv-miR-UL70-3p, miR-940
hcmv-miR-UL70-3p, hsv1-miR-H1 hcmv-miR-UL70-3p, hsv1-miR-LAT
hcmv-miR-UL70-3p, kshv-miR- miR-1225-5p, miR-135a* K12-3
miR-1225-5p, miR-150* miR-1225-5p, miR-22 miR-1225-5p, miR-223
miR-1225-5p, miR-483-5p miR-1225-5p, miR-575 miR-1225-5p, miR-638
miR-1225-5p, miR-923 miR-1225-5p, miR-939 miR-1225-5p, miR-940
miR-1225-5p, hsv1-miR-H1 miR-1225-5p, hsv1-miR-LAT miR-1225-5p,
kshv-miR-K12-3 miR-135a*, miR-150* miR-135a*, miR-22 miR-135a*,
miR-223 miR-135a*, miR-483-5p miR-135a*, miR-575 miR-135a*, miR-638
miR-135a*, miR-923 miR-135a*, miR-939 miR-135a*, miR-940 miR-135a*,
hsv1-miR-H1 miR-135a*, hsv1-miR-LAT miR-135a*, kshv-miR-K12-3
miR-150*, miR-22 miR-150*, miR-223 miR-150*, miR-483-5p miR-150*,
miR-575 miR-150*, miR-638 miR-150*, miR-923 miR-150*, miR-939
miR-150*, miR-940 miR-150*, hsv1-miR-H1 miR-150*, hsv1-miR-LAT
miR-150*, kshv-miR-K12-3 miR-22, miR-223 miR-22, miR-483-5p miR-22,
miR-575 miR-22, miR-638 miR-22, miR-923 miR-22, miR-939 miR-22,
miR-940 miR-22, hsv1-miR-H1 miR-22, hsv1-miR-LAT miR-22,
kshv-miR-K12-3 miR-223, miR-483-5p miR-223, miR-575 miR-223,
miR-638 miR-223, miR-923 miR-223, miR-939 miR-223, miR-940 miR-223,
hsv1-miR-H1 miR-223, hsv1-miR-LAT miR-223, kshv-miR-K12-3
miR-483-5p, miR-575 miR-483-5p, miR-638 miR-483-5p, miR-923
miR-483-5p, miR-939 miR-483-5p, miR-940 miR-483-5p, hsv1-miR-H1
miR-483-5p, hsv1-miR-LAT miR-483-5p, kshv-miR-K12-3 miR-575,
miR-638 miR-575, miR-923 miR-575, miR-939 miR-575, miR-940 miR-575,
hsv1-miR-H1 miR-575, hsv1-miR-LAT miR-575, kshv-miR-K12-3 miR-638,
miR-923 miR-638, miR-939 miR-638, miR-940 miR-638, hsv1-miR-H1
miR-638, hsv1-miR-LAT miR-638, kshv-miR-K12-3 miR-923, miR-939
miR-923, miR-940 miR-923, hsv1-miR-H1 miR-923, hsv1-miR-LAT
miR-923, kshv-miR-K12-3 miR-939, miR-940 miR-939, hsv1-miR-H1
miR-939, hsv1-miR-LAT miR-939, kshv-miR-K12-3 miR-940, hsv1-miR-H1
miR-940, hsv1-miR-LAT miR-940, kshv-miR-K12-3 hsv1-miR-H1,
hsv1-miR-LAT hsv1-miR-H1, kshv-miR-K12-3 hsv1-miR-LAT,
kshv-miR-K12-3
[0153] In other embodiments, an assay or microRNA profile tests for
at least two microRNA sequences selected from the group consisting
of miR-630, miR-134, hcmv-miR-UL70-3p, miR-1225-5p, miR-135a*,
miR-150*, miR-483-5p, miR-575, miR-638, hsv1-miR-H1, hsv1-miR-LAT,
and human orthologs thereof. In other embodiments, at least three
of these sequences is tested for. In particular embodiments, all 11
of these sequences are tested for. Specific pairs of these 11
microRNA sequences include those listed in Table 9:
TABLE-US-00009 TABLE 9 miR-630, miR-134 miR-630, hcmv-miR-UL70-3p
miR-630, miR-1225-5p miR-630, miR-135a* miR-630, miR-150* miR-630,
miR-483-5p miR-630, miR-575 miR-630, miR-638 miR-630, hsv1-miR-H1
miR-630, hsv1-miR-LAT miR-134, hcmv-miR-UL70-3p miR-134,
miR-1225-5p miR-134, miR-135a* miR-134, miR-150* miR-134,
miR-483-5p miR-134, miR-575 miR-134, miR-638 miR-134, hsv1-miR-H1
miR-134, hsv1-miR-LAT hcmv-miR-UL70-3p, miR-1225-5p
hcmv-miR-UL70-3p, miR-135a* hcmv-miR-UL70-3p, miR-150*
hcmv-miR-UL70-3p, miR-483-5p hcmv-miR-UL70-3p, miR-575
hcmv-miR-UL70-3p, miR-638 hcmv-miR-UL70-3p, hsv1-miR-H1
hcmv-miR-UL70-3p, hsv1-miR-LAT miR-1225-5p, miR-135a* miR-1225-5p,
miR-150* miR-1225-5p, miR-483-5p miR-1225-5p, miR-575 miR-1225-5p,
miR-638 miR-1225-5p, hsv1-miR-H1 miR-1225-5p, hsv1-miR-LAT
miR-135a*, miR-150* miR-135a*, miR-483-5p miR-135a*, miR-575
miR-135a*, miR-638 miR-135a*, hsv1-miR-H1 miR-135a*, hsv1-miR-LAT
miR-150*, miR-483-5p miR-150*, miR-575 miR-150*, miR-638 miR-150*,
hsv1-miR-H1 miR-150*, hsv1-miR-LAT miR-483-5p, miR-575 miR-483-5p,
miR-638 miR-483-5p, hsv1-miR-H1 miR-483-5p, hsv1-miR-LAT miR-575,
miR-638 miR-575, hsv1-miR-H1 miR-575, hsv1-miR-LAT miR-638,
hsv1-miR-H1 miR-638, hsv1-miR-LAT hsv1-miR-H1, hsv1-miR-LAT
[0154] In some embodiments, an assay or microRNA profile tests for
two or more microRNA sequences. At least one of the microRNA
sequences tested for is selected from the group consisting of
miR-630, hcmv-miR-UL70-3p, miR-1225-5p, miR-134, miR-135a*,
miR-150*, miR-483-5p, miR-575, miR-638, hsv1-miR-H1, hsv1-miR-LAT,
and human orthologs thereof. At least one of the microRNA sequences
tested for is selected from the group consisting of miR-451,
miR-448, and miR-92a-2*. In particular embodiments, miR-451 is one
of the microRNA sequences tested for. Specific pairs of these
microRNA sequences include those listed in Table 10:
TABLE-US-00010 TABLE 10 miR-630, miR-451 miR-630, miR-448 miR-630,
miR-92a-2* hcmv-miR-UL70-3p, miR-451 hcmv-miR-UL70-3p, miR-448
hcmv-miR-UL70-3p, miR-92a-2* miR-1225-5p, miR-451 miR-1225-5p,
miR-448 miR-1225-5p, miR-92a-2* miR-134, miR-451 miR-134, miR-448
miR-134, miR-92a-2* miR-135a*, miR-451 miR-135a*, miR-448
miR-135a*, miR-92a-2* miR-150*, miR-451 miR-150*, miR-448 miR-150*,
miR-92a-2* miR-483-5p, miR-451 miR-483-5p, miR-448 miR-483-5p,
miR-92a-2* miR-575, miR-451 miR-575, miR-448 miR-575, miR-92a-2*
miR-638, miR-451 miR-638, miR-448 miR-638, miR-92a-2* hsv1-miR-H1,
miR-451 hsv1-miR-H1, miR-448 hsv1-miR-H1, miR-92a-2* hsv1-miR-LAT,
miR-451 hsv1-miR-LAT, miR-448 hsv1-miR-LAT, miR-92a-2*
[0155] In some embodiments, an assay or microRNA profile tests for
at least two microRNA sequences selected from the group consisting
of miR-451, miR-923, miR-1225-5p, miR-22, miR-223, miR-638,
kshv-miR-K12-3, and human orthologs thereof. In other embodiments,
at least three of these sequences is tested for. In particular
embodiments, all seven of these sequences are tested for. Specific
pairs of these seven microRNA sequences include those listed in
Table 11:
TABLE-US-00011 TABLE 11 miR-451, miR-923 miR-451, miR-1225-5p
miR-451, miR-22 miR-451, miR-223 miR-451, miR-638 miR-451,
kshv-miR-K12-3 miR-923, miR-1225-5p miR-923, miR-22 miR-923,
miR-223 miR-923, miR-638 miR-923, kshv-miR-K12-3 miR-1225-5p,
miR-22 miR-1225-5p, miR-223 miR-1225-5p, miR-638 miR-1225-5p,
kshv-miR-K12-3 miR-22, miR-223 miR-22, miR-638 miR-22,
kshv-miR-K12-3 miR-223, miR-638 miR-223, kshv-miR-K12-3 miR-638,
kshv-miR-K12-3
[0156] In some embodiments, an assay or microRNA profile tests for
at least two microRNA sequences selected from the group consisting
of miR-940, miR-134, miR-135a*, miR-150*, miR-483-5p, miR-575,
miR-939, hsv1-miR-H1, kshv-miR-K12-3, hsv1-miR-LAT,
hcmv-miR-UL70-3p, and human orthologs thereof. In other
embodiments, at least three of these sequences is tested for. In
particular embodiments, all 11 of these sequences are tested for.
Specific pairs of these 11 microRNA sequences include those listed
in Table 12:
TABLE-US-00012 TABLE 12 miR-940, miR-134 miR-940, miR-135a*
miR-940, miR-150* miR-940, miR-483-5p miR-940, miR-575 miR-940,
miR-939 miR-940, hsv1-miR-H1 miR-940, kshv-miR-K12-3 miR-940,
hsv1-miR-LAT miR-940, hcmv-miR-UL70-3p miR-134, miR-135a* miR-134,
miR-150* miR-134, miR-483-5p miR-134, miR-575 miR-134, miR-939
miR-134, hsv1-miR-H1 miR-134, kshv-miR-K12-3 miR-134, hsv1-miR-LAT
miR-134, hcmv-miR-UL70-3p miR-135a*, miR-150* miR-135a*, miR-483-5p
miR-135a*, miR-575 miR-135a*, miR-939 miR-135a*, hsv1-miR-H1
miR-135a*, kshv-miR-K12-3 miR-135a*, hsv1-miR-LAT miR-135a*,
hcmv-miR-UL70-3p miR-150*, miR-483-5p miR-150*, miR-575 miR-150*,
miR-939 miR-150*, hsv1-miR-H1 miR-150*, kshv-miR-K12-3 miR-150*,
hsv1-miR-LAT miR-150*, hcmv-miR-UL70-3p miR-483-5p, miR-575
miR-483-5p, miR-939 miR-483-5p, hsv1-miR-H1 miR-483-5p,
kshv-miR-K12-3 miR-483-5p, hsv1-miR-LAT miR-483-5p,
hcmv-miR-UL70-3p miR-575, miR-939 miR-575, hsv1-miR-H1 miR-575,
kshv-miR-K12-3 miR-575, hsv1-miR-LAT miR-575, hcmv-miR-UL70-3p
miR-939, hsv1-miR-H1 miR-939, kshv-miR-K12-3 miR-939, hsv1-miR-LAT
miR-939, hcmv-miR-UL70-3p hsv1-miR-H1, kshv-miR-K12-3 hsv1-miR-H1,
hsv1-miR-LAT hsv1-miR-H1, hcmv-miR-UL70-3p kshv-miR-K12-3,
hsv1-miR-LAT kshv-miR-K12-3, hcmv-miR-UL70-3p hsv1-miR-LAT,
hcmv-miR-UL70-3p
[0157] Appendix A provides a listing of the RNA sequences for all
of the microRNA discussed herein, including human orthologs
thereof.
TABLE-US-00013 APPENDIX A Accession SEQ ID miRNA name Number RNA
Sequence No: ebv-miR-BART10* MIMAT0004817 gccaccucuuugguucuguaca 1
ebv-miR-BART12 MIMAT0003423 uccugugguguuuggugugguu 2 ebv-miR-BART13
MIMAT0003424 uguaacuugccagggacggcuga 3 ebv-miR-BART13* MIMAT0004818
aaccggcucguggcucguacag 4 ebv-miR-BART15 MIMAT0003713
gucagugguuuuguuuccuuga 5 ebv-miR-BART1-5p MIMAT0000999
ucuuaguggaagugacgugcugug 6 ebv-miR-BART16 MIMAT0003714
uuagauagagugggugugugcucu 7 ebv-miR-BART18- MIMAT0003717
ucaaguucgcacuuccuauaca 8 5p ebv-miR-BART19- MIMAT0003718
uuuuguuugcuugggaaugcu 9 3p ebv-miR-BART19- MIMAT0004836
acauuccccgcaaacaugacaug 10 5p ebv-miR-BART20- MIMAT0003719
uagcaggcaugucuucauucc 11 5p ebv-miR-BART2-5p MIMAT0001000
uauuuucugcauucgcccuugc 12 ebv-miR-BART3* MIMAT0003410
accuaguguuaguguugugcu 13 ebv-miR-BART5 MIMAT0003413
caaggugaauauagcugcccaucg 14 ebv-miR-BART6-5p MIMAT0003414
uaagguugguccaauccauagg 15 ebv-miR-BART7 MIMAT0003416
caucauaguccaguguccaggg 16 ebv-miR-BART7* MIMAT0004815
ccuggaccuugacuaugaaaca 17 ebv-miR-BHRF1-1 MIMAT0000995
uaaccugaucagccccggaguu 18 ebv-miR-BHRF1-3 MIMAT0000998
uaacgggaaguguguaagcaca 19 hcmv-miR-UL148D MIMAT0001578
ucguccuccccuucuucaccg 20 hcmv-miR-UL22A MIMAT0001574
uaacuagccuucccgugaga 21 hcmv-miR-UL22A* MIMAT0001575
ucaccagaaugcuaguuuguag 22 hcmv-miR-UL70-3p MIMAT0003343
ggggaugggcuggcgcgcgg 23 hcmv-miR-UL70-5p MIMAT0003342
ugcgucucggccucguccaga 24 hcmv-miR-US25-1 MIMAT0001581
aaccgcucaguggcucggacc 25 hcmv-miR-US25-2- MIMAT0001583
auccacuuggagagcucccgcgg 26 3p hcmv-miR-US25-2- MIMAT0001582
agcggucuguucagguggauga 27 5p hcmv-miR-US4 MIMAT0003341
cgacauggacgugcagggggau 28 hiv1-miR-H1 MIMAT0004480
ccagggaggcgugccugggc 29 hiv1-miR-N367 MIMAT0004478
acugaccuuuggauggugcuucaa 30 hsa-miR-1 MIMAT0000416
ggaauguaaagaaguauguau 31 hsa-miR-10b MIMAT0000254
uacccuguagaaccgaauuugug 32 hsa-miR-122 MIMAT0000421
uggagugugacaaugguguuug 33 hsa-miR-1224-3p MIMAT0005459
ccccaccuccucucuccucag 34 hsa-miR-1224-5p MIMAT0005458
gugaggacucgggaggugg 35 hsa-miR-1225-3p MIMAT0005573
ugagccccugugccgcccccag 36 hsa-miR-1225-5p MIMAT0005572
guggguacggcccagugggggg 37 hsa-miR-1226* MIMAT0005576
gugagggcaugcaggccuggaugggg 38 hsa-miR-1227 MIMAT0005580
cgugccacccuuuuccccag 39 hsa-miR-1228 MIMAT0005583
ucacaccugccucgcccccc 40 hsa-miR-1229 MIMAT0005584
cucucaccacugcccucccacag 41 hsa-miR-1234 MIMAT0005589
ucggccugaccacccaccccac 42 hsa-miR-1237 MIMAT0005592
uccuucugcuccgucccccag 43 hsa-miR-1238 MIMAT0005593
cuuccucgucugucugcccc 44 hsa-miR-124 MIMAT0000422
uaaggcacgcggugaaugcc 45 hsa-miR-125a-3p MIMAT0004602
acaggugagguucuugggagcc 46 hsa-miR-125a-5p MIMAT0000443
ucccugagacccuuuaaccuguga 47 hsa-miR-127-3p MIMAT0000446
ucggauccgucugagcuuggcu 48 hsa-miR-127-5p MIMAT0004604
cugaagcucagagggcucugau 49 hsa-miR-128 MIMAT0000424
ucacagugaaccggucucuuu 50 hsa-miR-129* MIMAT0004548
aagcccuuaccccaaaaaguau 51 hsa-miR-129-3p MIMAT0004605
aagcccuuaccccaaaaagcau 52 hsa-miR-130a MIMAT0000425
cagugcaauguuaaaagggcau 53 hsa-miR-133a MIMAT0000427
uuugguccccuucaaccagcug 54 hsa-miR-133b MIMAT0000770
uuugguccccuucaaccagcua 55 hsa-miR-134 MIMAT0000447
ugugacugguugaccagagggg 56 hsa-miR-135a* MIMAT0004595
uauagggauuggagccguggcg 57 hsa-miR-136 MIMAT0000448
acuccauuuguuuugaugaugga 58 hsa-miR-136* MIMAT0004606
caucaucgucucaaaugagucu 59 hsa-miR-138 MIMAT0000430
agcugguguugugaaucaggccg 60 hsa-miR-139-3p MIMAT0004552
ggagacgcggcccuguuggagu 61 hsa-miR-140-3p MIMAT0004597
uaccacaggguagaaccacgg 62 hsa-miR-140-5p MIMAT0000431
cagugguuuuacccuaugguag 63 hsa-miR-141 MIMAT0000432
uaacacugucugguaaagaugg 64 hsa-miR-142-3p MIMAT0000434
uguaguguuuccuacuuuaugga 65 hsa-miR-143 MIMAT0000435
ugagaugaagcacuguagcuc 66 hsa-miR-146a MIMAT0000449
ugagaacugaauuccauggguu 67 hsa-miR-146b-3p MIMAT0004766
ugcccuguggacucaguucugg 68 hsa-miR-146b-5p MIMAT0002809
ugagaacugaauuccauaggcu 69 hsa-miR-148b MIMAT0000759
ucagugcaucacagaacuuugu 70 hsa-miR-150 MIMAT0000451
ucucccaacccuuguaccagug 71 hsa-miR-150* MIMAT0004610
cugguacaggccugggggacag 72 hsa-miR-15a* MIMAT0004488
caggccauauugugcugccuca 73 hsa-miR-15b MIMAT0000417
uagcagcacaucaugguuuaca 74 hsa-miR-181b MIMAT0000257
aacauucauugcugucggugggu 75 hsa-miR-181d MIMAT0002821
aacauucauuguugucggugggu 76 hsa-miR-183 MIMAT0000261
uauggcacugguagaauucacu 77 hsa-miR-185 MIMAT0000455
uggagagaaaggcaguuccuga 78 hsa-miR-186 MIMAT0000456
caaagaauucuccuuuugggcu 79 hsa-miR-187* MIMAT0004561
ggcuacaacacaggacccgggc 80 hsa-miR-188-5p MIMAT0000457
caucccuugcaugguggaggg 81 hsa-miR-190b MIMAT0004929
ugauauguuugauauuggguu 82 hsa-miR-191* MIMAT0001618
gcugcgcuuggauuucgucccc 83 hsa-miR-193b MIMAT0002819
aacuggcccucaaagucccgcu 84 hsa-miR-194 MIMAT0000460
uguaacagcaacuccaugugga 85 hsa-miR-198 MIMAT0000228
gguccagaggggagauagguuc 86 hsa-miR-199a-5p MIMAT0000231
cccaguguucagacuaccuguuc 87 hsa-miR-19a MIMAT0000073
ugugcaaaucuaugcaaaacuga 88 hsa-miR-200a MIMAT0000682
uaacacugucugguaacgaugu 89 hsa-miR-200b MIMAT0000318
uaauacugccugguaaugauga 90 hsa-miR-200b* MIMAT0004571
caucuuacugggcagcauugga 91 hsa-miR-200c MIMAT0000617
uaauacugccggguaaugaugga 92 hsa-miR-205 MIMAT0000266
uccuucauuccaccggagucug 93 hsa-miR-206 MIMAT0000462
uggaauguaaggaagugugugg 94 hsa-miR-208a MIMAT0000241
auaagacgagcaaaaagcuugu 95 hsa-miR-21 MIMAT0000076
uagcuuaucagacugauguuga 96 hsa-miR-211 MIMAT0000268
uucccuuugucauccuucgccu 97 hsa-miR-22 MIMAT0000077
aagcugccaguugaagaacugu 98 hsa-miR-220b MIMAT0004908
ccaccaccgugucugacacuu 99 hsa-miR-221 MIMAT0000278
agcuacauugucugcuggguuuc 100 hsa-miR-222 MIMAT0000279
agcuacaucuggcuacugggu 101 hsa-miR-223 MIMAT0000280
ugucaguuugucaaauacccca 102 hsa-miR-23b MIMAT0000418
aucacauugccagggauuacc 103 hsa-miR-26a MIMAT0000082
uucaaguaauccaggauaggcu 104 hsa-miR-27a MIMAT0000084
uucacaguggcuaaguuccgc 105 hsa-miR-27b MIMAT0000419
uucacaguggcuaaguucugc 106 hsa-miR-27b* MIMAT0004588
agagcuuagcugauuggugaac 107 hsa-miR-299-3p MIMAT0000687
uaugugggaugguaaaccgcuu 108 hsa-miR-299-5p MIMAT0002890
ugguuuaccgucccacauacau 109 hsa-miR-29b MIMAT0000100
uagcaccauuugaaaucaguguu 110 hsa-miR-29c* MIMAT0004673
ugaccgauuucuccugguguuc 111 hsa-miR-300 MIMAT0004903
uauacaagggcagacucucucu 112 hsa-miR-301b MIMAT0004958
cagugcaaugauauugucaaagc 113 hsa-miR-302c* MIMAT0000716
uuuaacauggggguaccugcug 114 hsa-miR-30a MIMAT0000087
uguaaacauccucgacuggaag 115 hsa-miR-30c MIMAT0000244
uguaaacauccuacacucucagc 116 hsa-miR-30c-1* MIMAT0004674
cugggagaggguuguuuacucc 117 hsa-miR-30e MIMAT0000692
uguaaacauccuugacuggaag 118 hsa-miR-31 MIMAT0000089
aggcaagaugcuggcauagcu 119
hsa-miR-323-3p MIMAT0000755 cacauuacacggucgaccucu 120
hsa-miR-324-3p MIMAT0000762 acugccccaggugcugcugg 121 hsa-miR-324-5p
MIMAT0000761 cgcauccccuagggcauuggugu 122 hsa-miR-326 MIMAT0000756
ccucugggcccuuccuccag 123 hsa-miR-328 MIMAT0000752
cuggcccucucugcccuuccgu 124 hsa-miR-331-5p MIMAT0004700
cuagguauggucccagggaucc 125 hsa-miR-338-3p MIMAT0000763
uccagcaucagugauuuuguug 126 hsa-miR-339-3p MIMAT0004702
ugagcgccucgacgacagagccg 127 hsa-miR-33a* MIMAT0004506
caauguuuccacagugcaucac 128 hsa-miR-33b MIMAT0003301
gugcauugcuguugcauugc 129 hsa-miR-33b* MIMAT0004811
cagugccucggcagugcagccc 130 hsa-miR-342-3p MIMAT0000753
ucucacacagaaaucgcacccgu 131 hsa-miR-34c-3p MIMAT0004677
aaucacuaaccacacggccagg 132 hsa-miR-34c-5p MIMAT0000686
aggcaguguaguuagcugauugc 133 hsa-miR-363* MIMAT0003385
cggguggaucacgaugcaauuu 134 hsa-miR-369-3p MIMAT0000721
aauaauacaugguugaucuuu 135 hsa-miR-370 MIMAT0000722
gccugcugggguggaaccuggu 136 hsa-miR-371-3p MIMAT0000723
aagugccgccaucuuuugagugu 137 hsa-miR-371-5p MIMAT0004687
acucaaacugugggggcacu 138 hsa-miR-375 MIMAT0000728
uuuguucguucggcucgcguga 139 hsa-miR-376b MIMAT0002172
aucauagaggaaaauccauguu 140 hsa-miR-377* MIMAT0000730
aucacacaaaggcaacuuuugu 141 hsa-miR-379 MIMAT0000733
ugguagacuauggaacguagg 142 hsa-miR-382 MIMAT0000737
gaaguuguucgugguggauucg 143 hsa-miR-409-5p MIMAT0001638
agguuacccgagcaacuuugcau 144 hsa-miR-411 MIMAT0003329
uaguagaccguauagcguacg 145 hsa-miR-411* MIMAT0004813
uauguaacacgguccacuaacc 146 hsa-miR-423-5p MIMAT0004748
ugaggggcagagagcgagacuuu 147 hsa-miR-424 MIMAT0001341
cagcagcaauucauguuuugaa 148 hsa-miR-424* MIMAT0004749
caaaacgugaggcgcugcuau 149 hsa-miR-425 MIMAT0003393
aaugacacgaucacucccguuga 150 hsa-miR-429 MIMAT0001536
uaauacugucugguaaaaccgu 151 hsa-miR-448 MIMAT0001532
uugcauauguaggaugucccau 152 hsa-miR-449a MIMAT0001541
uggcaguguauuguuagcuggu 153 hsa-miR-449b MIMAT0003327
aggcaguguauuguuagcuggc 154 hsa-miR-450b-3p MIMAT0004910
uugggaucauuuugcauccaua 155 hsa-miR-451 MIMAT0001631
aaaccguuaccauuacugaguu 156 hsa-miR-452 MIMAT0001635
aacuguuugcagaggaaacuga 157 hsa-miR-454* MIMAT0003884
acccuaucaauauugucucugc 158 hsa-miR-455-3p MIMAT0004784
gcaguccaugggcauauacac 159 hsa-miR-455-5p MIMAT0003150
uaugugccuuuggacuacaucg 160 hsa-miR-483-3p MIMAT0002173
ucacuccucuccucccgucuu 161 hsa-miR-483-5p MIMAT0004761
aagacgggaggaaagaagggag 162 hsa-miR-484 MIMAT0002174
ucaggcucaguccccucccgau 163 hsa-miR-486-3p MIMAT0004762
cggggcagcucaguacaggau 164 hsa-miR-486-5p MIMAT0002177
uccuguacugagcugccccgag 165 hsa-miR-487b MIMAT0003180
aaucguacagggucauccacuu 166 hsa-miR-491-3p MIMAT0004765
cuuaugcaagauucccuucuac 167 hsa-miR-491-5p MIMAT0002807
aguggggaacccuuccaugagg 168 hsa-miR-493 MIMAT0003161
ugaaggucuacugugugccagg 169 hsa-miR-493* MIMAT0002813
uuguacaugguaggcuuucauu 170 hsa-miR-494 MIMAT0002816
ugaaacauacacgggaaaccuc 171 hsa-miR-497 MIMAT0002820
cagcagcacacugugguuugu 172 hsa-miR-498 MIMAT0002824
uuucaagccagggggcguuuuuc 173 hsa-miR-500 MIMAT0004773
uaauccuugcuaccugggugaga 174 hsa-miR-503 MIMAT0002874
uagcagcgggaacaguucugcag 175 hsa-miR-505 MIMAT0002876
cgucaacacuugcugguuuccu 176 hsa-miR-507 MIMAT0002879
uuuugcaccuuuuggagugaa 177 hsa-miR-511 MIMAT0002808
gugucuuuugcucugcaguca 178 hsa-miR-513a-3p MIMAT0004777
uaaauuucaccuuucugagaagg 179 hsa-miR-513a-5p MIMAT0002877
uucacagggaggugucau 180 hsa-miR-513b MIMAT0005788
uucacaaggaggugucauuuau 181 hsa-miR-513c MIMAT0005789
uucucaaggaggugucguuuau 182 hsa-miR-515-5p MIMAT0002826
uucuccaaaagaaagcacuuucug 183 hsa-miR-518b MIMAT0002844
caaagcgcuccccuuuagaggu 184 hsa-miR-518c* MIMAT0002847
ucucuggagggaagcacuuucug 185 hsa-miR-518d-3p MIMAT0002864
caaagcgcuucccuuuggagc 186 hsa-miR-518d-5p MIMAT0005456
cucuagagggaagcacuuucug 187 hsa-miR-518e* MIMAT0005450
cucuagagggaagcgcuuucug 188 hsa-miR-520d-5p MIMAT0002855
cuacaaagggaagcccuuuc 189 hsa-miR-520h MIMAT0002867
acaaagugcuucccuuuagagu 190 hsa-miR-539 MIMAT0003163
ggagaaauuauccuuggugugu 191 hsa-miR-541 MIMAT0004920
uggugggcacagaaucuggacu 192 hsa-miR-545* MIMAT0004785
ucaguaaauguuuauuagauga 193 hsa-miR-548d-3p MIMAT0003323
caaaaaccacaguuucuuuugc 194 hsa-miR-548d-5p MIMAT0004812
aaaaguaauugugguuuuugcc 195 hsa-miR-551a MIMAT0003214
gcgacccacucuugguuucca 196 hsa-miR-551b MIMAT0003233
gcgacccauacuugguuucag 197 hsa-miR-552 MIMAT0003215
aacaggugacugguuagacaa 198 hsa-miR-554 MIMAT0003217
gcuaguccugacucagccagu 199 hsa-miR-556-5p MIMAT0003220
gaugagcucauuguaauaugag 200 hsa-miR-557 MIMAT0003221
guuugcacgggugggccuugucu 201 hsa-miR-559 MIMAT0003223
uaaaguaaauaugcaccaaaa 202 hsa-miR-561 MIMAT0003225
caaaguuuaagauccuugaagu 203 hsa-miR-564 MIMAT0003228
aggcacggugucagcaggc 204 hsa-miR-568 MIMAT0003232
auguauaaauguauacacac 205 hsa-miR-572 MIMAT0003237
guccgcucggcgguggccca 206 hsa-miR-574-5p MIMAT0004795
ugagugugugugugugagugugu 207 hsa-miR-575 MIMAT0003240
gagccaguuggacaggagc 208 hsa-miR-576-3p MIMAT0004796
aagauguggaaaaauuggaauc 209 hsa-miR-578 MIMAT0003243
cuucuugugcucuaggauugu 210 hsa-miR-583 MIMAT0003248
caaagaggaaggucccauuac 211 hsa-miR-586 MIMAT0003252
uaugcauuguauuuuuaggucc 212 hsa-miR-589 MIMAT0004799
ugagaaccacgucugcucugag 213 hsa-miR-589* MIMAT0003256
ucagaacaaaugccgguucccaga 214 hsa-miR-591 MIMAT0003259
agaccauggguucucauugu 215 hsa-miR-595 MIMAT0003263
gaagugugccguggugugucu 216 hsa-miR-601 MIMAT0003269
uggucuaggauuguuggaggag 217 hsa-miR-602 MIMAT0003270
gacacgggcgacagcugcggccc 218 hsa-miR-609 MIMAT0003277
aggguguuucucucaucucu 219 hsa-miR-610 MIMAT0003278
ugagcuaaaugugugcuggga 220 hsa-miR-612 MIMAT0003280
gcugggcagggcuucugagcuccuu 221 hsa-miR-613 MIMAT0003281
aggaauguuccuucuuugcc 222 hsa-miR-614 MIMAT0003282
gaacgccuguucuugccaggugg 223 hsa-miR-615-3p MIMAT0003283
uccgagccugggucucccucuu 224 hsa-miR-616 MIMAT0004805
agucauuggaggguuugagcag 225 hsa-miR-619 MIMAT0003288
gaccuggacauguuugugcccagu 226 hsa-miR-622 MIMAT0003291
acagucugcugagguuggagc 227 hsa-miR-623 MIMAT0003292
aucccuugcaggggcuguugggu 228 hsa-miR-624* MIMAT0003293
uaguaccaguaccuuguguuca 229 hsa-miR-627 MIMAT0003296
gugagucucuaagaaaagagga 230 hsa-miR-630 MIMAT0003299
aguauucuguaccagggaaggu 231 hsa-miR-633 MIMAT0003303
cuaauaguaucuaccacaauaaa 232 hsa-miR-634 MIMAT0003304
aaccagcaccccaacuuuggac 233 hsa-miR-638 MIMAT0003308
agggaucgcgggcggguggcggccu 234 hsa-miR-639 MIMAT0003309
aucgcugcgguugcgagcgcugu 235 hsa-miR-640 MIMAT0003310
augauccaggaaccugccucu 236 hsa-miR-642 MIMAT0003312
gucccucuccaaaugugucuug 237 hsa-miR-644 MIMAT0003314
aguguggcuuucuuagagc 238 hsa-miR-647 MIMAT0003317
guggcugcacucacuuccuuc 239 hsa-miR-648 MIMAT0003318
aagugugcagggcacuggu 240 hsa-miR-652 MIMAT0003322
aauggcgccacuaggguugug 241 hsa-miR-654-5p MIMAT0003330
uggugggccgcagaacaugugc 242 hsa-miR-658 MIMAT0003336
ggcggagggaaguagguccguuggu 243 hsa-miR-659 MIMAT0003337
cuugguucagggagggucccca 244 hsa-miR-662 MIMAT0003325
ucccacguuguggcccagcag 245
hsa-miR-663 MIMAT0003326 aggcggggcgccgcgggaccgc 246 hsa-miR-665
MIMAT0004952 accaggaggcugaggccccu 247 hsa-miR-671-5p MIMAT0003880
aggaagcccuggaggggcuggag 248 hsa-miR-675 MIMAT0004284
uggugcggagagggcccacagug 249 hsa-miR-708 MIMAT0004926
aaggagcuuacaaucuagcuggg 250 hsa-miR-708* MIMAT0004927
caacuagacugugagcuucuag 251 hsa-miR-711 MIMAT0012734
gggacccagggagagacguaag 252 hsa-miR-720 MIMAT0005954
ucucgcuggggccucca 253 hsa-miR-744* MIMAT0004946
cuguugccacuaaccucaaccu 254 hsa-miR-760 MIMAT0004957
cggcucugggucugugggga 255 hsa-miR-765 MIMAT0003945
uggaggagaaggaaggugaug 256 hsa-miR-766 MIMAT0003888
acuccagccccacagccucagc 257 hsa-miR-767-3p MIMAT0003883
ucugcucauaccccaugguuucu 258 hsa-miR-770-5p MIMAT0003948
uccaguaccacgugucagggcca 259 hsa-miR-802 MIMAT0004185
caguaacaaagauucauccuugu 260 hsa-miR-874 MIMAT0004911
cugcccuggcccgagggaccga 261 hsa-miR-876-3p MIMAT0004925
uggugguuuacaaaguaauuca 262 hsa-miR-876-5p MIMAT0004924
uggauuucuuugugaaucacca 263 hsa-miR-877 MIMAT0004949
guagaggagauggcgcaggg 264 hsa-miR-877* MIMAT0004950
uccucuucucccuccucccag 265 hsa-miR-885-3p MIMAT0004948
aggcagcgggguguaguggaua 266 hsa-miR-885-5p MIMAT0004947
uccauuacacuacccugccucu 267 hsa-miR-886-3p MIMAT0004906
cgcgggugcuuacugacccuu 268 hsa-miR-890 MIMAT0004912
uacuuggaaaggcaucaguug 269 hsa-miR-891b MIMAT0004913
ugcaacuuaccugagucauuga 270 hsa-miR-892b MIMAT0004918
cacuggcuccuuucuggguaga 271 hsa-miR-920 MIMAT0004970
ggggagcuguggaagcagua 272 hsa-miR-922 MIMAT0004972
gcagcagagaauaggacuacguc 273 hsa-miR-923 none GUCAGCGGAGGAAAAGAAA
274 CU hsa-miR-92a-2* MIMAT0004508 ggguggggauuuguugcauuac 275
hsa-miR-92b MIMAT0003218 uauugcacucgucccggccucc 276 hsa-miR-92b*
MIMAT0004792 agggacgggacgcggugcagug 277 hsa-miR-93 MIMAT0000093
caaagugcuguucgugcagguag 278 hsa-miR-933 MIMAT0004976
ugugcgcagggagaccucuccc 279 hsa-miR-934 MIMAT0004977
ugucuacuacuggagacacugg 280 hsa-miR-935 MIMAT0004978
ccaguuaccgcuuccgcuaccgc 281 hsa-miR-936 MIMAT0004979
acaguagagggaggaaucgcag 282 hsa-miR-937 MIMAT0004980
auccgcgcucugacucucugcc 283 hsa-miR-939 MIMAT0004982
uggggagcugaggcucugggggug 284 hsa-miR-940 MIMAT0004983
aaggcagggcccccgcucccc 285 hsa-miR-96 MIMAT0000095
uuuggcacuagcacauuuuugcu 286 hsa-miR-99a MIMAT0000097
aacccguagauccgaucuugug 287 hsv1-miR-H1 MIMAT0003744
uggaaggacgggaaguggaag 288 hsv1-miR-LAT none uggcggcccggcccggggcc
289 kshv-miR-K12-12 IMAT0003712 accaggccaccauuccucuccg 290
kshv-miR-K12-3 MIMAT0002193 ucacauucugaggacggcagcga 291
kshv-miR-K12-3* MIMAT0002194 ucgcggucacagaaugugaca 292
kshv-miR-K12-4-5p MIMAT0002191 agcuaaaccgcaguacucuagg 293
kshv-miR-K12-6-5p MIMAT0002188 ccagcagcaccuaauccaucgg 294
kshv-miR-K12-8 MIMAT0002186 uaggcgcgacugagagagcacg 295
kshv-miR-K12-9 MIMAT0002185 cuggguauacgcagcugcguaa 296
kshv-miR-K12-9* MIMAT0002184 acccagcugcguaaaccccgcu 297
mghv-miR-M1-6 MIMAT0001569 ugaaacugugugaggugguuuu 298 mghv-miR-M1-9
MIMAT0001573 ucacauuugccuggaccuuuuu 299 mmu-let-7d* MIMAT0000384
cuauacgaccugcugccuuucu 300 mmu-let-7g MIMAT0000121
ugagguaguaguuuguacaguu 301 mmu-miR-298 MIMAT0000376
ggcagaggagggcuguucuuccc 302 mmu-miR-1 MIMAT0000123
uggaauguaaagaaguauguau 303 mmu-miR-101a MIMAT0000133
uacaguacugugauaacugaa 304 mmu-miR-101a* MIMAT0004526
ucaguuaucacagugcugaugc 305 mmu-miR-101b MIMAT0000616
uacaguacugugauagcugaa 306 mmu-miR-122 MIMAT0000246
uggagugugacaaugguguuug 307 mmu-miR-1224 MIMAT0005460
gugaggacuggggagguggag 308 mmu-miR-124 MIMAT0000134
uaaggcacgcggugaaugcc 309 mmu-miR-125a-3p MIMAT0004528
acaggugagguucuugggagcc 310 mmu-miR-125a-5p MIMAT0000135
ucccugagacccuuuaaccuguga 311 mmu-miR-125b-5p MIMAT0000136
ucccugagacccuaacuuguga 312 mmu-miR-126-5p MIMAT0000137
auuauuacuuuugguacgcg 313 mmu-miR-127 MIMAT0000139
ucggauccgucugagcuuggcu 314 mmu-miR-128 MIMAT0000140
ucacagugaaccggucucuuu 315 mmu-miR-129-3p MIMAT0000544
aagcccuuaccccaaaaagcau 316 mmu-miR-130a MIMAT0000141
cagugcaauguuaaaagggcau 317 mmu-miR-133a MIMAT0000145
uuugguccccuucaaccagcug 318 mmu-miR-133b MIMAT0000769
uuugguccccuucaaccagcua 319 mmu-miR-135a* MIMAT0004531
uauagggauuggagccguggcg 320 mmu-miR-136 MIMAT0000148
acuccauuuguuuugaugaugg 321 mmu-miR-138 MIMAT0000150
agcugguguugugaaucaggccg 322 mmu-miR-138* MIMAT0004668
ggcuacuucacaacaccaggg 323 mmu-miR-139-3p MIMAT0004662
uggagacgcggcccuguuggag 324 mmu-miR-140 MIMAT0000151
cagugguuuuacccuaugguag 325 mmu-miR-140* MIMAT0000152
uaccacaggguagaaccacgg 326 mmu-miR-141 MIMAT0000153
uaacacugucugguaaagaugg 327 mmu-miR-142-3p MIMAT0000155
uguaguguuuccuacuuuaugga 328 mmu-miR-143 MIMAT0000247
ugagaugaagcacuguagcuc 329 mmu-miR-146a MIMAT0000158
ugagaacugaauuccauggguu 330 mmu-miR-146b MIMAT0003475
ugagaacugaauuccauaggcu 331 mmu-miR-148b MIMAT0000580
ucagugcaucacagaacuuugu 332 mmu-miR-150 MIMAT0000160
ucucccaacccuuguaccagug 333 mmu-miR-15a* MIMAT0004624
caggccauacugugcugccuca 334 mmu-miR-15b MIMAT0000124
uagcagcacaucaugguuuaca 335 mmu-miR-181b MIMAT0000673
aacauucauugcugucggugggu 336 mmu-miR-181d MIMAT0004324
aacauucauuguugucggugggu 337 mmu-miR-183 MIMAT0000212
uauggcacugguagaauucacu 338 mmu-miR-185 MIMAT0000214
uggagagaaaggcaguuccuga 339 mmu-miR-186 MIMAT0000215
caaagaauucuccuuuugggcu 340 mmu-miR-191* MIMAT0004542
gcugcacuuggauuucguuccc 341 mmu-miR-193 MIMAT0000223
aacuggccuacaaagucccagu 342 mmu-miR-193b MIMAT0004859
aacuggcccacaaagucccgcu 343 mmu-miR-194 MIMAT0000224
uguaacagcaacuccaugugga 344 mmu-miR-199a-5p MIMAT0000229
cccaguguucagacuaccuguuc 345 mmu-miR-199b* MIMAT0000672
cccaguguuuagacuaccuguuc 346 mmu-miR-19a MIMAT0000651
ugugcaaaucuaugcaaaacuga 347 mmu-miR-200a MIMAT0000519
uaacacugucugguaacgaugu 348 mmu-miR-200b MIMAT0000233
uaauacugccugguaaugauga 349 mmu-miR-200b* MIMAT0004545
caucuuacugggcagcauugga 350 mmu-miR-200c MIMAT0000657
uaauacugccggguaaugaugga 351 mmu-miR-202-3p MIMAT0000235
agagguauagcgcaugggaaga 352 mmu-miR-205 MIMAT0000238
uccuucauuccaccggagucug 353 mmu-miR-206 MIMAT0000239
uggaauguaaggaagugugugg 354 mmu-miR-208a MIMAT0000520
auaagacgagcaaaaagcuugu 355 mmu-miR-21 MIMAT0000530
uagcuuaucagacugauguuga 356 mmu-miR-211 MIMAT0000668
uucccuuugucauccuuugccu 357 mmu-miR-22 MIMAT0000531
aagcugccaguugaagaacugu 358 mmu-miR-221 MIMAT0000669
agcuacauugucugcuggguuuc 359 mmu-miR-222 MIMAT0000670
agcuacaucuggcuacugggu 360 mmu-miR-223 MIMAT0000665
ugucaguuugucaaauacccca 361 mmu-miR-23b MIMAT0000125
aucacauugccagggauuacc 362 mmu-miR-26a MIMAT0000533
uucaaguaauccaggauaggcu 363 mmu-miR-27a MIMAT0000537
uucacaguggcuaaguuccgc 364 mmu-miR-27b MIMAT0000126
uucacaguggcuaaguucugc 365 mmu-miR-27b* MIMAT0004522
agagcuuagcugauuggugaac 366 mmu-miR-28* MIMAT0004661
cacuagauugugagcugcugga 367 mmu-miR-290-5p MIMAT0000366
acucaaacuaugggggcacuuu 368 mmu-miR-291a-5p MIMAT0000367
caucaaaguggaggcccucucu 369 mmu-miR-294* MIMAT0004574
acucaaaauggaggcccuaucu 370
mmu-miR-297a MIMAT0000375 auguaugugugcaugugcaugu 371 mmu-miR-299
MIMAT0004577 uaugugggacgguaaaccgcuu 372 mmu-miR-29b MIMAT0000127
uagcaccauuugaaaucaguguu 373 mmu-miR-29c* MIMAT0004632
ugaccgauuucuccugguguuc 374 mmu-miR-301b MIMAT0004186
cagugcaaugguauugucaaagc 375 mmu-miR-302c* MIMAT0003375
gcuuuaacaugggguuaccugc 376 mmu-miR-30a MIMAT0000128
uguaaacauccucgacuggaag 377 mmu-miR-30c MIMAT0000514
uguaaacauccuacacucucagc 378 mmu-miR-30c-1* MIMAT0004616
cugggagaggguuguuuacucc 379 mmu-miR-30e MIMAT0000248
uguaaacauccuugacuggaag 380 mmu-miR-31 MIMAT0000538
aggcaagaugcuggcauagcug 381 mmu-miR-320 MIMAT0000666
aaaagcuggguugagagggcga 382 mmu-miR-322 MIMAT0000548
cagcagcaauucauguuuugga 383 mmu-miR-323-3p MIMAT0000551
cacauuacacggucgaccucu 384 mmu-miR-324-3p MIMAT0000556
ccacugccccaggugcugcu 385 mmu-miR-324-5p MIMAT0000555
cgcauccccuagggcauuggugu 386 mmu-miR-326 MIMAT0000559
ccucugggcccuuccuccagu 387 mmu-miR-327 MIMAT0004867
acuugaggggcaugaggau 388 mmu-miR-328 MIMAT0000565
cuggcccucucugcccuuccgu 389 mmu-miR-331-5p MIMAT0004643
cuagguauggucccagggaucc 390 mmu-miR-339-3p MIMAT0004649
ugagcgccucggcgacagagccg 391 mmu-miR-341 MIMAT0000588
ucggucgaucggucggucggu 392 mmu-miR-342-3p MIMAT0000590
ucucacacagaaaucgcacccgu 393 mmu-miR-34b-5p MIMAT0000382
aggcaguguaauuagcugauugu 394 mmu-miR-34c* MIMAT0004580
aaucacuaaccacacagccagg 395 mmu-miR-369-3p MIMAT0003186
aauaauacaugguugaucuuu 396 mmu-miR-370 MIMAT0001095
gccugcugggguggaaccuggu 397 mmu-miR-374 MIMAT0003727
auauaauacaaccugcuaagug 398 mmu-miR-375 MIMAT0000739
uuuguucguucggcucgcguga 399 mmu-miR-376b MIMAT0001092
aucauagaggaacauccacuu 400 mmu-miR-379 MIMAT0000743
ugguagacuauggaacguagg 401 mmu-miR-380-3p MIMAT0000745
uauguaguaugguccacaucuu 402 mmu-miR-382 MIMAT0000747
gaaguuguucgugguggauucg 403 mmu-miR-384-5p MIMAT0004745
uguaaacaauuccuaggcaaugu 404 mmu-miR-409-5p MIMAT0004746
agguuacccgagcaacuuugcau 405 mmu-miR-411 MIMAT0004747
uaguagaccguauagcguacg 406 mmu-miR-411* MIMAT0001093
uauguaacacgguccacuaacc 407 mmu-miR-423-5p MIMAT0004825
ugaggggcagagagcgagacuuu 408 mmu-miR-425 MIMAT0004750
aaugacacgaucacucccguuga 409 mmu-miR-429 MIMAT0001537
uaauacugucugguaaugccgu 410 mmu-miR-434-5p MIMAT0001421
gcucgacucaugguuugaacca 411 mmu-miR-450b-3p MIMAT0003512
auugggaacauuuugcaugcau 412 mmu-miR-451 MIMAT0001632
aaaccguuaccauuacugaguu 413 mmu-miR-455 MIMAT0003742
gcaguccacgggcauauacac 414 mmu-miR-465c-3p MIMAT0004874
gaucagggccuuucuaaguaga 415 mmu-miR-466d-5p MIMAT0004930
ugugugugcguacauguacaug 416 mmu-miR-466f-3p MIMAT0004882
cauacacacacacauacacac 417 mmu-miR-467e* MIMAT0005294
auauacauacacacaccuauau 418 mmu-miR-483 MIMAT0004782
aagacgggagaagagaagggag 419 mmu-miR-484 MIMAT0003127
ucaggcucaguccccucccgau 420 mmu-miR-486 MIMAT0003130
uccuguacugagcugccccgag 421 mmu-miR-487b MIMAT0003184
aaucguacagggucauccacuu 422 mmu-miR-494 MIMAT0003182
ugaaacauacacgggaaaccuc 423 mmu-miR-497 MIMAT0003453
cagcagcacacugugguuugua 424 mmu-miR-505 IMAT0003513
cgucaacacuugcugguuuucu 425 mmu-miR-511 MIMAT0004940
augccuuuugcucugcacuca 426 mmu-miR-539 MIMAT0003169
ggagaaauuauccuuggugugu 427 mmu-miR-540-3p MIMAT0004786
caagggucacccucugacucugu 428 mmu-miR-551b MIMAT0003890
gcgacccauacuugguuucag 429 mmu-miR-568 MIMAT0004892
auguauaaauguauacacac 430 mmu-miR-574-5p MIMAT0004893
ugagugugugugugugagugugu 431 mmu-miR-652 MIMAT0003711
aauggcgccacuaggguugug 432 mmu-miR-654-5p MIMAT0004897
ugguaagcugcagaacaugugu 433 mmu-miR-669a MIMAT0003477
aguugugugugcauguucaugu 434 mmu-miR-671-5p MIMAT0003731
aggaagcccuggaggggcuggag 435 mmu-miR-685 MIMAT0003463
ucaauggcugaggugaggcac 436 mmu-miR-686 MIMAT0003464
auugcuucccagacggugaaga 437 mmu-miR-688 MIMAT0003467
ucgcaggcgacuacuuauuc 438 mmu-miR-701 MIMAT0003491
uuagccgcugaaauagaugga 439 mmu-miR-706 MIMAT0003496
agagaaacccugucucaaaaaa 440 mmu-miR-708 MIMAT0004828
aaggagcuuacaaucuagcuggg 441 mmu-miR-710 MIMAT0003500
ccaagucuuggggagaguugag 442 mmu-miR-711 MIMAT0003501
gggacccggggagagauguaag 443 mmu-miR-712 MIMAT0003502
cuccuucacccgggcgguacc 444 mmu-miR-714 MIMAT0003505
cgacgagggccggucggucgc 445 mmu-miR-720 MIMAT0003484
aucucgcuggggccucca 446 mmu-miR-721 MIMAT0003515
cagugcaauuaaaagggggaa 447 mmu-miR-744* MIMAT0004820
cuguugccacuaaccucaaccu 448 mmu-miR-760 MIMAT0003898
cggcucugggucugugggga 449 mmu-miR-770-5p MIMAT0004822
agcaccacgugucugggccacg 450 mmu-miR-7a MIMAT0000677
uggaagacuagugauuuuguugu 451 mmu-miR-7b MIMAT0000678
uggaagacuugugauuuuguugu 452 mmu-miR-877 MIMAT0004861
guagaggagauggcgcaggg 453 mmu-miR-877* MIMAT0004862
uguccucuucucccuccuccca 454 mmu-miR-881* MIMAT0004845
cagagagauaacagucacaucu 455 mmu-miR-882 MIMAT0004847
aggagagaguuagcgcauuagu 456 mmu-miR-93 MIMAT0000540
caaagugcuguucgugcagguag 457 mmu-miR-96 MIMAT0000541
uuuggcacuagcacauuuuugcu 458 mmu-miR-99a MIMAT0000131
aacccguagauccgaucuugug 459
[0158] The devices and methods of the present disclosure have been
described with reference to exemplary embodiments. Obviously,
modifications and alterations will occur to others upon reading and
understanding the preceding detailed description. It is intended
that the exemplary embodiments be construed as including all such
modifications and alterations insofar as they come within the scope
of the appended claims or the equivalents thereof.
Sequence CWU 1
1
459122RNAEpstein Barr Virus 1gccaccucuu ugguucugua ca
22222RNAEpstein Barr Virus 2uccuguggug uuuggugugg uu
22323RNAEpstein Barr Virus 3uguaacuugc cagggacggc uga
23422RNAEpstein Barr Virus 4aaccggcucg uggcucguac ag
22522RNAEpstein Barr Virus 5gucagugguu uuguuuccuu ga
22624RNAEpstein Barr Virus 6ucuuagugga agugacgugc ugug
24724RNAEpstein Barr Virus 7uuagauagag ugggugugug cucu
24822RNAEpstein Barr Virus 8ucaaguucgc acuuccuaua ca
22921RNAEpstein Barr Virus 9uuuuguuugc uugggaaugc u
211023RNAEpstein Barr Virus 10acauuccccg caaacaugac aug
231121RNAEpstein Barr Virus 11uagcaggcau gucuucauuc c
211222RNAEpstein Barr Virus 12uauuuucugc auucgcccuu gc
221321RNAEpstein Barr Virus 13accuaguguu aguguugugc u
211424RNAEpstein Barr Virus 14caaggugaau auagcugccc aucg
241522RNAEpstein Barr Virus 15uaagguuggu ccaauccaua gg
221622RNAEpstein Barr Virus 16caucauaguc caguguccag gg
221722RNAEpstein Barr Virus 17ccuggaccuu gacuaugaaa ca
221822RNAEpstein Barr Virus 18uaaccugauc agccccggag uu
221922RNAEpstein Barr Virus 19uaacgggaag uguguaagca ca
222021RNAHuman cytomegalovirus 20ucguccuccc cuucuucacc g
212120RNAHuman cytomegalovirus 21uaacuagccu ucccgugaga
202222RNAHuman cytomegalovirus 22ucaccagaau gcuaguuugu ag
222320RNAHuman cytomegalovirus 23ggggaugggc uggcgcgcgg
202421RNAHuman cytomegalovirus 24ugcgucucgg ccucguccag a
212521RNAHuman cytomegalovirus 25aaccgcucag uggcucggac c
212623RNAHuman cytomegalovirus 26auccacuugg agagcucccg cgg
232722RNAHuman cytomegalovirus 27agcggucugu ucagguggau ga
222822RNAHuman cytomegalovirus 28cgacauggac gugcaggggg au
222920RNAHuman immunodeficiency virus type 1 29ccagggaggc
gugccugggc 203024RNAHuman immunodeficiency virus type 1
30acugaccuuu ggauggugcu ucaa 243121RNAHomo sapiens 31ggaauguaaa
gaaguaugua u 213223RNAHomo sapiens 32uacccuguag aaccgaauuu gug
233322RNAHomo sapiens 33uggaguguga caaugguguu ug 223421RNAHomo
sapiens 34ccccaccucc ucucuccuca g 213519RNAHomo sapiens
35gugaggacuc gggaggugg 193622RNAHomo sapiens 36ugagccccug
ugccgccccc ag 223722RNAHomo sapiens 37guggguacgg cccagugggg gg
223826RNAHomo sapiens 38gugagggcau gcaggccugg augggg 263920RNAHomo
sapiens 39cgugccaccc uuuuccccag 204020RNAHomo sapiens 40ucacaccugc
cucgcccccc 204123RNAHomo sapiens 41cucucaccac ugcccuccca cag
234222RNAHomo sapiens 42ucggccugac cacccacccc ac 224321RNAHomo
sapiens 43uccuucugcu ccguccccca g 214420RNAHomo sapiens
44cuuccucguc ugucugcccc 204520RNAHomo sapiens 45uaaggcacgc
ggugaaugcc 204622RNAHomo sapiens 46acaggugagg uucuugggag cc
224724RNAHomo sapiens 47ucccugagac ccuuuaaccu guga 244822RNAHomo
sapiens 48ucggauccgu cugagcuugg cu 224922RNAHomo sapiens
49cugaagcuca gagggcucug au 225021RNAHomo sapiens 50ucacagugaa
ccggucucuu u 215122RNAHomo sapiens 51aagcccuuac cccaaaaagu au
225222RNAHomo sapiens 52aagcccuuac cccaaaaagc au 225322RNAHomo
sapiens 53cagugcaaug uuaaaagggc au 225422RNAHomo sapiens
54uuuggucccc uucaaccagc ug 225522RNAHomo sapiens 55uuuggucccc
uucaaccagc ua 225622RNAHomo sapiens 56ugugacuggu ugaccagagg gg
225722RNAHomo sapiens 57uauagggauu ggagccgugg cg 225823RNAHomo
sapiens 58acuccauuug uuuugaugau gga 235922RNAHomo sapiens
59caucaucguc ucaaaugagu cu 226023RNAHomo sapiens 60agcugguguu
gugaaucagg ccg 236122RNAHomo sapiens 61ggagacgcgg cccuguugga gu
226221RNAHomo sapiens 62uaccacaggg uagaaccacg g 216322RNAHomo
sapiens 63cagugguuuu acccuauggu ag 226422RNAHomo sapiens
64uaacacuguc ugguaaagau gg 226523RNAHomo sapiens 65uguaguguuu
ccuacuuuau gga 236621RNAHomo sapiens 66ugagaugaag cacuguagcu c
216722RNAHomo sapiens 67ugagaacuga auuccauggg uu 226822RNAHomo
sapiens 68ugcccugugg acucaguucu gg 226922RNAHomo sapiens
69ugagaacuga auuccauagg cu 227022RNAHomo sapiens 70ucagugcauc
acagaacuuu gu 227122RNAHomo sapiens 71ucucccaacc cuuguaccag ug
227222RNAHomo sapiens 72cugguacagg ccugggggac ag 227322RNAHomo
sapiens 73caggccauau ugugcugccu ca 227422RNAHomo sapiens
74uagcagcaca ucaugguuua ca 227523RNAHomo sapiens 75aacauucauu
gcugucggug ggu 237623RNAHomo sapiens 76aacauucauu guugucggug ggu
237722RNAHomo sapiens 77uauggcacug guagaauuca cu 227822RNAHomo
sapiens 78uggagagaaa ggcaguuccu ga 227922RNAHomo sapiens
79caaagaauuc uccuuuuggg cu 228022RNAHomo sapiens 80ggcuacaaca
caggacccgg gc 228121RNAHomo sapiens 81caucccuugc augguggagg g
218221RNAHomo sapiens 82ugauauguuu gauauugggu u 218322RNAHomo
sapiens 83gcugcgcuug gauuucgucc cc 228422RNAHomo sapiens
84aacuggcccu caaagucccg cu 228522RNAHomo sapiens 85uguaacagca
acuccaugug ga 228622RNAHomo sapiens 86gguccagagg ggagauaggu uc
228723RNAHomo sapiens 87cccaguguuc agacuaccug uuc 238823RNAHomo
sapiens 88ugugcaaauc uaugcaaaac uga 238922RNAHomo sapiens
89uaacacuguc ugguaacgau gu 229022RNAHomo sapiens 90uaauacugcc
ugguaaugau ga 229122RNAHomo sapiens 91caucuuacug ggcagcauug ga
229223RNAHomo sapiens 92uaauacugcc ggguaaugau gga 239322RNAHomo
sapiens 93uccuucauuc caccggaguc ug 229422RNAHomo sapiens
94uggaauguaa ggaagugugu gg 229522RNAHomo sapiens 95auaagacgag
caaaaagcuu gu 229622RNAHomo sapiens 96uagcuuauca gacugauguu ga
229722RNAHomo sapiens 97uucccuuugu cauccuucgc cu 229822RNAHomo
sapiens 98aagcugccag uugaagaacu gu 229921RNAHomo sapiens
99ccaccaccgu gucugacacu u 2110023RNAHomo sapiens 100agcuacauug
ucugcugggu uuc 2310121RNAHomo sapiens 101agcuacaucu ggcuacuggg u
2110222RNAHomo sapiens 102ugucaguuug ucaaauaccc ca 2210321RNAHomo
sapiens 103aucacauugc cagggauuac c 2110422RNAHomo sapiens
104uucaaguaau ccaggauagg cu 2210521RNAHomo sapiens 105uucacagugg
cuaaguuccg c 2110621RNAHomo sapiens 106uucacagugg cuaaguucug c
2110722RNAHomo sapiens 107agagcuuagc ugauugguga ac 2210822RNAHomo
sapiens 108uaugugggau gguaaaccgc uu 2210922RNAHomo sapiens
109ugguuuaccg ucccacauac au 2211023RNAHomo sapiens 110uagcaccauu
ugaaaucagu guu 2311122RNAHomo sapiens 111ugaccgauuu cuccuggugu uc
2211222RNAHomo sapiens 112uauacaaggg cagacucucu cu 2211323RNAHomo
sapiens 113cagugcaaug auauugucaa agc 2311422RNAHomo sapiens
114uuuaacaugg ggguaccugc ug 2211522RNAHomo sapiens 115uguaaacauc
cucgacugga ag 2211623RNAHomo sapiens 116uguaaacauc cuacacucuc agc
2311722RNAHomo sapiens 117cugggagagg guuguuuacu cc 2211822RNAHomo
sapiens 118uguaaacauc cuugacugga ag 2211921RNAHomo sapiens
119aggcaagaug cuggcauagc u 2112021RNAHomo sapiens 120cacauuacac
ggucgaccuc u 2112120RNAHomo sapiens 121acugccccag gugcugcugg
2012223RNAHomo sapiens 122cgcauccccu agggcauugg ugu 2312320RNAHomo
sapiens 123ccucugggcc cuuccuccag 2012422RNAHomo sapiens
124cuggcccucu cugcccuucc gu 2212522RNAHomo sapiens 125cuagguaugg
ucccagggau cc 2212622RNAHomo sapiens 126uccagcauca gugauuuugu ug
2212723RNAHomo sapiens 127ugagcgccuc gacgacagag ccg 2312822RNAHomo
sapiens 128caauguuucc acagugcauc ac 2212920RNAHomo sapiens
129gugcauugcu guugcauugc 2013022RNAHomo sapiens 130cagugccucg
gcagugcagc cc 2213123RNAHomo sapiens 131ucucacacag aaaucgcacc cgu
2313222RNAHomo sapiens 132aaucacuaac cacacggcca gg 2213323RNAHomo
sapiens 133aggcagugua guuagcugau ugc 2313422RNAHomo sapiens
134cggguggauc acgaugcaau uu 2213521RNAHomo sapiens 135aauaauacau
gguugaucuu u 2113622RNAHomo sapiens 136gccugcuggg guggaaccug gu
2213723RNAHomo sapiens 137aagugccgcc aucuuuugag ugu 2313820RNAHomo
sapiens 138acucaaacug ugggggcacu 2013922RNAHomo sapiens
139uuuguucguu cggcucgcgu ga 2214022RNAHomo sapiens 140aucauagagg
aaaauccaug uu 2214122RNAHomo sapiens 141aucacacaaa ggcaacuuuu gu
2214221RNAHomo sapiens 142ugguagacua uggaacguag g 2114322RNAHomo
sapiens 143gaaguuguuc gugguggauu cg 2214423RNAHomo sapiens
144agguuacccg agcaacuuug cau 2314521RNAHomo sapiens 145uaguagaccg
uauagcguac g 2114622RNAHomo sapiens 146uauguaacac gguccacuaa cc
2214723RNAHomo sapiens 147ugaggggcag agagcgagac uuu 2314822RNAHomo
sapiens 148cagcagcaau ucauguuuug aa 2214921RNAHomo sapiens
149caaaacguga ggcgcugcua u 2115023RNAHomo sapiens 150aaugacacga
ucacucccgu uga 2315122RNAHomo sapiens 151uaauacuguc ugguaaaacc gu
2215222RNAHomo sapiens 152uugcauaugu aggauguccc au 2215322RNAHomo
sapiens 153uggcagugua uuguuagcug gu 2215422RNAHomo sapiens
154aggcagugua uuguuagcug gc 2215522RNAHomo sapiens 155uugggaucau
uuugcaucca ua 2215622RNAHomo sapiens 156aaaccguuac cauuacugag uu
2215722RNAHomo sapiens 157aacuguuugc agaggaaacu ga 2215822RNAHomo
sapiens 158acccuaucaa uauugucucu gc 2215921RNAHomo sapiens
159gcaguccaug ggcauauaca c 2116022RNAHomo sapiens 160uaugugccuu
uggacuacau cg 2216121RNAHomo sapiens 161ucacuccucu ccucccgucu u
2116222RNAHomo sapiens 162aagacgggag gaaagaaggg ag 2216322RNAHomo
sapiens 163ucaggcucag uccccucccg au 2216421RNAHomo sapiens
164cggggcagcu caguacagga u 2116522RNAHomo sapiens 165uccuguacug
agcugccccg ag 2216622RNAHomo sapiens 166aaucguacag ggucauccac uu
2216722RNAHomo sapiens 167cuuaugcaag auucccuucu ac 2216822RNAHomo
sapiens 168aguggggaac ccuuccauga gg 2216922RNAHomo sapiens
169ugaaggucua cugugugcca gg 2217022RNAHomo sapiens 170uuguacaugg
uaggcuuuca uu 2217122RNAHomo sapiens 171ugaaacauac acgggaaacc uc
2217221RNAHomo sapiens 172cagcagcaca cugugguuug u 2117323RNAHomo
sapiens 173uuucaagcca gggggcguuu uuc 2317423RNAHomo sapiens
174uaauccuugc uaccugggug aga 2317523RNAHomo sapiens 175uagcagcggg
aacaguucug cag 2317622RNAHomo sapiens 176cgucaacacu ugcugguuuc cu
2217721RNAHomo sapiens 177uuuugcaccu uuuggaguga a 2117821RNAHomo
sapiens 178gugucuuuug cucugcaguc a 2117923RNAHomo sapiens
179uaaauuucac cuuucugaga agg 2318018RNAHomo sapiens 180uucacaggga
ggugucau 1818122RNAHomo sapiens 181uucacaagga ggugucauuu au
2218222RNAHomo sapiens 182uucucaagga ggugucguuu au 2218324RNAHomo
sapiens 183uucuccaaaa gaaagcacuu ucug 2418422RNAHomo sapiens
184caaagcgcuc cccuuuagag gu 2218523RNAHomo sapiens 185ucucuggagg
gaagcacuuu cug 2318621RNAHomo sapiens 186caaagcgcuu cccuuuggag
c
2118722RNAHomo sapiens 187cucuagaggg aagcacuuuc ug 2218822RNAHomo
sapiens 188cucuagaggg aagcgcuuuc ug 2218920RNAHomo sapiens
189cuacaaaggg aagcccuuuc 2019022RNAHomo sapiens 190acaaagugcu
ucccuuuaga gu 2219122RNAHomo sapiens 191ggagaaauua uccuuggugu gu
2219222RNAHomo sapiens 192uggugggcac agaaucugga cu 2219322RNAHomo
sapiens 193ucaguaaaug uuuauuagau ga 2219422RNAHomo sapiens
194caaaaaccac aguuucuuuu gc 2219522RNAHomo sapiens 195aaaaguaauu
gugguuuuug cc 2219621RNAHomo sapiens 196gcgacccacu cuugguuucc a
2119721RNAHomo sapiens 197gcgacccaua cuugguuuca g 2119821RNAHomo
sapiens 198aacaggugac ugguuagaca a 2119921RNAHomo sapiens
199gcuaguccug acucagccag u 2120022RNAHomo sapiens 200gaugagcuca
uuguaauaug ag 2220123RNAHomo sapiens 201guuugcacgg gugggccuug ucu
2320221RNAHomo sapiens 202uaaaguaaau augcaccaaa a 2120322RNAHomo
sapiens 203caaaguuuaa gauccuugaa gu 2220419RNAHomo sapiens
204aggcacggug ucagcaggc 1920520RNAHomo sapiens 205auguauaaau
guauacacac 2020620RNAHomo sapiens 206guccgcucgg cgguggccca
2020723RNAHomo sapiens 207ugagugugug ugugugagug ugu 2320819RNAHomo
sapiens 208gagccaguug gacaggagc 1920922RNAHomo sapiens
209aagaugugga aaaauuggaa uc 2221021RNAHomo sapiens 210cuucuugugc
ucuaggauug u 2121121RNAHomo sapiens 211caaagaggaa ggucccauua c
2121222RNAHomo sapiens 212uaugcauugu auuuuuaggu cc 2221322RNAHomo
sapiens 213ugagaaccac gucugcucug ag 2221424RNAHomo sapiens
214ucagaacaaa ugccgguucc caga 2421520RNAHomo sapiens 215agaccauggg
uucucauugu 2021621RNAHomo sapiens 216gaagugugcc gugguguguc u
2121722RNAHomo sapiens 217uggucuagga uuguuggagg ag 2221823RNAHomo
sapiens 218gacacgggcg acagcugcgg ccc 2321920RNAHomo sapiens
219aggguguuuc ucucaucucu 2022021RNAHomo sapiens 220ugagcuaaau
gugugcuggg a 2122125RNAHomo sapiens 221gcugggcagg gcuucugagc uccuu
2522220RNAHomo sapiens 222aggaauguuc cuucuuugcc 2022323RNAHomo
sapiens 223gaacgccugu ucuugccagg ugg 2322422RNAHomo sapiens
224uccgagccug ggucucccuc uu 2222522RNAHomo sapiens 225agucauugga
ggguuugagc ag 2222624RNAHomo sapiens 226gaccuggaca uguuugugcc cagu
2422721RNAHomo sapiens 227acagucugcu gagguuggag c 2122823RNAHomo
sapiens 228aucccuugca ggggcuguug ggu 2322922RNAHomo sapiens
229uaguaccagu accuuguguu ca 2223022RNAHomo sapiens 230gugagucucu
aagaaaagag ga 2223122RNAHomo sapiens 231aguauucugu accagggaag gu
2223223RNAHomo sapiens 232cuaauaguau cuaccacaau aaa 2323322RNAHomo
sapiens 233aaccagcacc ccaacuuugg ac 2223425RNAHomo sapiens
234agggaucgcg ggcggguggc ggccu 2523523RNAHomo sapiens 235aucgcugcgg
uugcgagcgc ugu 2323621RNAHomo sapiens 236augauccagg aaccugccuc u
2123722RNAHomo sapiens 237gucccucucc aaaugugucu ug 2223819RNAHomo
sapiens 238aguguggcuu ucuuagagc 1923921RNAHomo sapiens
239guggcugcac ucacuuccuu c 2124019RNAHomo sapiens 240aagugugcag
ggcacuggu 1924121RNAHomo sapiens 241aauggcgcca cuaggguugu g
2124222RNAHomo sapiens 242uggugggccg cagaacaugu gc 2224325RNAHomo
sapiens 243ggcggaggga aguagguccg uuggu 2524422RNAHomo sapiens
244cuugguucag ggaggguccc ca 2224521RNAHomo sapiens 245ucccacguug
uggcccagca g 2124622RNAHomo sapiens 246aggcggggcg ccgcgggacc gc
2224720RNAHomo sapiens 247accaggaggc ugaggccccu 2024823RNAHomo
sapiens 248aggaagcccu ggaggggcug gag 2324923RNAHomo sapiens
249uggugcggag agggcccaca gug 2325023RNAHomo sapiens 250aaggagcuua
caaucuagcu ggg 2325122RNAHomo sapiens 251caacuagacu gugagcuucu ag
2225222RNAHomo sapiens 252gggacccagg gagagacgua ag 2225317RNAHomo
sapiens 253ucucgcuggg gccucca 1725422RNAHomo sapiens 254cuguugccac
uaaccucaac cu 2225520RNAHomo sapiens 255cggcucuggg ucugugggga
2025621RNAHomo sapiens 256uggaggagaa ggaaggugau g 2125722RNAHomo
sapiens 257acuccagccc cacagccuca gc 2225823RNAHomo sapiens
258ucugcucaua ccccaugguu ucu 2325923RNAHomo sapiens 259uccaguacca
cgugucaggg cca 2326023RNAHomo sapiens 260caguaacaaa gauucauccu ugu
2326122RNAHomo sapiens 261cugcccuggc ccgagggacc ga 2226222RNAHomo
sapiens 262uggugguuua caaaguaauu ca 2226322RNAHomo sapiens
263uggauuucuu ugugaaucac ca 2226420RNAHomo sapiens 264guagaggaga
uggcgcaggg 2026521RNAHomo sapiens 265uccucuucuc ccuccuccca g
2126622RNAHomo sapiens 266aggcagcggg guguagugga ua 2226722RNAHomo
sapiens 267uccauuacac uacccugccu cu 2226821RNAHomo sapiens
268cgcgggugcu uacugacccu u 2126921RNAHomo sapiens 269uacuuggaaa
ggcaucaguu g 2127022RNAHomo sapiens 270ugcaacuuac cugagucauu ga
2227122RNAHomo sapiens 271cacuggcucc uuucugggua ga 2227220RNAHomo
sapiens 272ggggagcugu ggaagcagua 2027323RNAHomo sapiens
273gcagcagaga auaggacuac guc 2327421RNAHomo sapiens 274gucagcggag
gaaaagaaac u 2127522RNAHomo sapiens 275ggguggggau uuguugcauu ac
2227622RNAHomo sapiens 276uauugcacuc gucccggccu cc 2227722RNAHomo
sapiens 277agggacggga cgcggugcag ug 2227823RNAHomo sapiens
278caaagugcug uucgugcagg uag 2327922RNAHomo sapiens 279ugugcgcagg
gagaccucuc cc 2228022RNAHomo sapiens 280ugucuacuac uggagacacu gg
2228123RNAHomo sapiens 281ccaguuaccg cuuccgcuac cgc 2328222RNAHomo
sapiens 282acaguagagg gaggaaucgc ag 2228322RNAHomo sapiens
283auccgcgcuc ugacucucug cc 2228424RNAHomo sapiens 284uggggagcug
aggcucuggg ggug 2428521RNAHomo sapiens 285aaggcagggc ccccgcuccc c
2128623RNAHomo sapiens 286uuuggcacua gcacauuuuu gcu 2328722RNAHomo
sapiens 287aacccguaga uccgaucuug ug 2228821RNAHerpes Simplex Virus
1 288uggaaggacg ggaaguggaa g 2128920RNAHerpes Simplex Virus 1
289uggcggcccg gcccggggcc 2029022RNAKaposi's sarcoma-associated
herpesvirus 290accaggccac cauuccucuc cg 2229123RNAKaposi's
sarcoma-associated herpesvirus 291ucacauucug aggacggcag cga
2329221RNAKaposi's sarcoma-associated herpesvirus 292ucgcggucac
agaaugugac a 2129322RNAKaposi's sarcoma-associated herpesvirus
293agcuaaaccg caguacucua gg 2229422RNAKaposi's sarcoma-associated
herpesvirus 294ccagcagcac cuaauccauc gg 2229522RNAKaposi's
sarcoma-associated herpesvirus 295uaggcgcgac ugagagagca cg
2229622RNAKaposi's sarcoma-associated herpesvirus 296cuggguauac
gcagcugcgu aa 2229722RNAKaposi's sarcoma-associated herpesvirus
297acccagcugc guaaaccccg cu 2229822RNAMouse Gammaherpes Virus
298ugaaacugug ugaggugguu uu 2229922RNAMouse Gammaherpes Virus
299ucacauuugc cuggaccuuu uu 2230022RNAMus musculus 300cuauacgacc
ugcugccuuu cu 2230122RNAMus musculus 301ugagguagua guuuguacag uu
2230223RNAMus musculus 302ggcagaggag ggcuguucuu ccc 2330322RNAMus
musculus 303uggaauguaa agaaguaugu au 2230421RNAMus musculus
304uacaguacug ugauaacuga a 2130522RNAMus musculus 305ucaguuauca
cagugcugau gc 2230621RNAMus musculus 306uacaguacug ugauagcuga a
2130722RNAMus musculus 307uggaguguga caaugguguu ug 2230821RNAMus
musculus 308gugaggacug gggaggugga g 2130920RNAMus musculus
309uaaggcacgc ggugaaugcc 2031022RNAMus musculus 310acaggugagg
uucuugggag cc 2231124RNAMus musculus 311ucccugagac ccuuuaaccu guga
2431222RNAMus musculus 312ucccugagac ccuaacuugu ga 2231320RNAMus
musculus 313auuauuacuu uugguacgcg 2031422RNAMus musculus
314ucggauccgu cugagcuugg cu 2231521RNAMus musculus 315ucacagugaa
ccggucucuu u 2131622RNAMus musculus 316aagcccuuac cccaaaaagc au
2231722RNAMus musculus 317cagugcaaug uuaaaagggc au 2231822RNAMus
musculus 318uuuggucccc uucaaccagc ug 2231922RNAMus musculus
319uuuggucccc uucaaccagc ua 2232022RNAMus musculus 320uauagggauu
ggagccgugg cg 2232122RNAMus musculus 321acuccauuug uuuugaugau gg
2232223RNAMus musculus 322agcugguguu gugaaucagg ccg 2332321RNAMus
musculus 323ggcuacuuca caacaccagg g 2132422RNAMus musculus
324uggagacgcg gcccuguugg ag 2232522RNAMus musculus 325cagugguuuu
acccuauggu ag 2232621RNAMus musculus 326uaccacaggg uagaaccacg g
2132722RNAMus musculus 327uaacacuguc ugguaaagau gg 2232823RNAMus
musculus 328uguaguguuu ccuacuuuau gga 2332921RNAMus musculus
329ugagaugaag cacuguagcu c 2133022RNAMus musculus 330ugagaacuga
auuccauggg uu 2233122RNAMus musculus 331ugagaacuga auuccauagg cu
2233222RNAMus musculus 332ucagugcauc acagaacuuu gu 2233322RNAMus
musculus 333ucucccaacc cuuguaccag ug 2233422RNAMus musculus
334caggccauac ugugcugccu ca 2233522RNAMus musculus 335uagcagcaca
ucaugguuua ca 2233623RNAMus musculus 336aacauucauu gcugucggug ggu
2333723RNAMus musculus 337aacauucauu guugucggug ggu 2333822RNAMus
musculus 338uauggcacug guagaauuca cu 2233922RNAMus musculus
339uggagagaaa ggcaguuccu ga 2234022RNAMus musculus 340caaagaauuc
uccuuuuggg cu 2234122RNAMus musculus 341gcugcacuug gauuucguuc cc
2234222RNAMus musculus 342aacuggccua caaaguccca gu 2234322RNAMus
musculus 343aacuggccca caaagucccg cu 2234422RNAMus musculus
344uguaacagca acuccaugug ga 2234523RNAMus musculus 345cccaguguuc
agacuaccug uuc 2334623RNAMus musculus 346cccaguguuu agacuaccug uuc
2334723RNAMus musculus 347ugugcaaauc uaugcaaaac uga 2334822RNAMus
musculus 348uaacacuguc ugguaacgau gu 2234922RNAMus musculus
349uaauacugcc ugguaaugau ga 2235022RNAMus musculus 350caucuuacug
ggcagcauug ga 2235123RNAMus musculus 351uaauacugcc ggguaaugau gga
2335222RNAMus musculus 352agagguauag cgcaugggaa ga 2235322RNAMus
musculus 353uccuucauuc caccggaguc ug 2235422RNAMus musculus
354uggaauguaa ggaagugugu gg 2235522RNAMus musculus 355auaagacgag
caaaaagcuu gu 2235622RNAMus musculus 356uagcuuauca gacugauguu ga
2235722RNAMus musculus 357uucccuuugu cauccuuugc cu 2235822RNAMus
musculus 358aagcugccag uugaagaacu gu 2235923RNAMus musculus
359agcuacauug ucugcugggu uuc 2336021RNAMus musculus 360agcuacaucu
ggcuacuggg u 2136122RNAMus musculus 361ugucaguuug ucaaauaccc ca
2236221RNAMus musculus 362aucacauugc cagggauuac c 2136322RNAMus
musculus 363uucaaguaau ccaggauagg cu 2236421RNAMus musculus
364uucacagugg cuaaguuccg c 2136521RNAMus musculus 365uucacagugg
cuaaguucug c 2136622RNAMus musculus 366agagcuuagc ugauugguga ac
2236722RNAMus musculus 367cacuagauug ugagcugcug ga 2236822RNAMus
musculus 368acucaaacua ugggggcacu uu 2236922RNAMus musculus
369caucaaagug gaggcccucu cu 2237022RNAMus musculus 370acucaaaaug
gaggcccuau cu
2237122RNAMus musculus 371auguaugugu gcaugugcau gu 2237222RNAMus
musculus 372uaugugggac gguaaaccgc uu 2237323RNAMus musculus
373uagcaccauu ugaaaucagu guu 2337422RNAMus musculus 374ugaccgauuu
cuccuggugu uc 2237523RNAMus musculus 375cagugcaaug guauugucaa agc
2337622RNAMus musculus 376gcuuuaacau gggguuaccu gc 2237722RNAMus
musculus 377uguaaacauc cucgacugga ag 2237823RNAMus musculus
378uguaaacauc cuacacucuc agc 2337922RNAMus musculus 379cugggagagg
guuguuuacu cc 2238022RNAMus musculus 380uguaaacauc cuugacugga ag
2238122RNAMus musculus 381aggcaagaug cuggcauagc ug 2238222RNAMus
musculus 382aaaagcuggg uugagagggc ga 2238322RNAMus musculus
383cagcagcaau ucauguuuug ga 2238421RNAMus musculus 384cacauuacac
ggucgaccuc u 2138520RNAMus musculus 385ccacugcccc aggugcugcu
2038623RNAMus musculus 386cgcauccccu agggcauugg ugu 2338721RNAMus
musculus 387ccucugggcc cuuccuccag u 2138819RNAMus musculus
388acuugagggg caugaggau 1938922RNAMus musculus 389cuggcccucu
cugcccuucc gu 2239022RNAMus musculus 390cuagguaugg ucccagggau cc
2239123RNAMus musculus 391ugagcgccuc ggcgacagag ccg 2339221RNAMus
musculus 392ucggucgauc ggucggucgg u 2139323RNAMus musculus
393ucucacacag aaaucgcacc cgu 2339423RNAMus musculus 394aggcagugua
auuagcugau ugu 2339522RNAMus musculus 395aaucacuaac cacacagcca gg
2239621RNAMus musculus 396aauaauacau gguugaucuu u 2139722RNAMus
musculus 397gccugcuggg guggaaccug gu 2239822RNAMus musculus
398auauaauaca accugcuaag ug 2239922RNAMus musculus 399uuuguucguu
cggcucgcgu ga 2240021RNAMus musculus 400aucauagagg aacauccacu u
2140121RNAMus musculus 401ugguagacua uggaacguag g 2140222RNAMus
musculus 402uauguaguau gguccacauc uu 2240322RNAMus musculus
403gaaguuguuc gugguggauu cg 2240423RNAMus musculus 404uguaaacaau
uccuaggcaa ugu 2340523RNAMus musculus 405agguuacccg agcaacuuug cau
2340621RNAMus musculus 406uaguagaccg uauagcguac g 2140722RNAMus
musculus 407uauguaacac gguccacuaa cc 2240823RNAMus musculus
408ugaggggcag agagcgagac uuu 2340923RNAMus musculus 409aaugacacga
ucacucccgu uga 2341022RNAMus musculus 410uaauacuguc ugguaaugcc gu
2241122RNAMus musculus 411gcucgacuca ugguuugaac ca 2241222RNAMus
musculus 412auugggaaca uuuugcaugc au 2241322RNAMus musculus
413aaaccguuac cauuacugag uu 2241421RNAMus musculus 414gcaguccacg
ggcauauaca c 2141522RNAMus musculus 415gaucagggcc uuucuaagua ga
2241622RNAMus musculus 416ugugugugcg uacauguaca ug 2241721RNAMus
musculus 417cauacacaca cacauacaca c 2141822RNAMus musculus
418auauacauac acacaccuau au 2241922RNAMus musculus 419aagacgggag
aagagaaggg ag 2242022RNAMus musculus 420ucaggcucag uccccucccg au
2242122RNAMus musculus 421uccuguacug agcugccccg ag 2242222RNAMus
musculus 422aaucguacag ggucauccac uu 2242322RNAMus musculus
423ugaaacauac acgggaaacc uc 2242422RNAMus musculus 424cagcagcaca
cugugguuug ua 2242522RNAMus musculus 425cgucaacacu ugcugguuuu cu
2242621RNAMus musculus 426augccuuuug cucugcacuc a 2142722RNAMus
musculus 427ggagaaauua uccuuggugu gu 2242823RNAMus musculus
428caagggucac ccucugacuc ugu 2342921RNAMus musculus 429gcgacccaua
cuugguuuca g 2143020RNAMus musculus 430auguauaaau guauacacac
2043123RNAMus musculus 431ugagugugug ugugugagug ugu 2343221RNAMus
musculus 432aauggcgcca cuaggguugu g 2143322RNAMus musculus
433ugguaagcug cagaacaugu gu 2243422RNAMus musculus 434aguugugugu
gcauguucau gu 2243523RNAMus musculus 435aggaagcccu ggaggggcug gag
2343621RNAMus musculus 436ucaauggcug aggugaggca c 2143722RNAMus
musculus 437auugcuuccc agacggugaa ga 2243820RNAMus musculus
438ucgcaggcga cuacuuauuc 2043921RNAMus musculus 439uuagccgcug
aaauagaugg a 2144022RNAMus musculus 440agagaaaccc ugucucaaaa aa
2244123RNAMus musculus 441aaggagcuua caaucuagcu ggg 2344222RNAMus
musculus 442ccaagucuug gggagaguug ag 2244322RNAMus musculus
443gggacccggg gagagaugua ag 2244421RNAMus musculus 444cuccuucacc
cgggcgguac c 2144521RNAMus musculus 445cgacgagggc cggucggucg c
2144618RNAMus musculus 446aucucgcugg ggccucca 1844721RNAMus
musculus 447cagugcaauu aaaaggggga a 2144822RNAMus musculus
448cuguugccac uaaccucaac cu 2244920RNAMus musculus 449cggcucuggg
ucugugggga 2045022RNAMus musculus 450agcaccacgu gucugggcca cg
2245123RNAMus musculus 451uggaagacua gugauuuugu ugu 2345223RNAMus
musculus 452uggaagacuu gugauuuugu ugu 2345320RNAMus musculus
453guagaggaga uggcgcaggg 2045422RNAMus musculus 454uguccucuuc
ucccuccucc ca 2245522RNAMus musculus 455cagagagaua acagucacau cu
2245622RNAMus musculus 456aggagagagu uagcgcauua gu 2245723RNAMus
musculus 457caaagugcug uucgugcagg uag 2345823RNAMus musculus
458uuuggcacua gcacauuuuu gcu 2345922RNAMus musculus 459aacccguaga
uccgaucuug ug 22
* * * * *
References