MicroRNA sequencing

MicroRNAs (miRNAs) are a family of small ribonucleic acids, 21-25 nucleotides in length, that modulate protein expression through transcript degradation, inhibition of translation, or sequestering transcripts.{{cite journal|last1=Kim|first1=V. Narry |author-link1= V. Narry Kim |last2=Han|first2=Jinju|last3=Siomi|first3=Mikiko C.|title=Biogenesis of small RNAs in animals|journal=Nature Reviews Molecular Cell Biology|volume=10|issue=2|year=2009|pages=126–139|issn=1471-0072|doi=10.1038/nrm2632|pmid=19165215|s2cid=8360619 }}{{cite journal|last1=Bartel|first1=D|title=MicroRNAsGenomics, Biogenesis, Mechanism, and Function|journal=Cell|volume=116|issue=2|year=2004|pages=281–297|issn=0092-8674|doi=10.1016/S0092-8674(04)00045-5|pmid=14744438|s2cid=2669459|doi-access=free}}{{cite journal|last1=He|first1=Lin|last2=Hannon|first2=Gregory J.|title=MicroRNAs: small RNAs with a big role in gene regulation|journal=Nature Reviews Genetics|volume=5|issue=7|year=2004|pages=522–531|issn=1471-0056|doi=10.1038/nrg1379|pmid=15211354|s2cid=86602746}} The first miRNA to be discovered, lin-4, was found in a genetic mutagenesis screen to identify molecular elements controlling post-embryonic development of the nematode Caenorhabditis elegans.{{cite journal|last1=Ambros|first1=Victor|title=A hierarchy of regulatory genes controls a larva-to-adult developmental switch in C. elegans|journal=Cell|volume=57|issue=1|year=1989|pages=49–57|issn=0092-8674|doi=10.1016/0092-8674(89)90171-2|pmid=2702689|s2cid=13103224}} The lin-4 gene encoded a 22 nucleotide RNA with conserved complementary binding sites in the 3’-untranslated region of the lin-14 mRNA transcript{{cite journal|last1=Lee|first1=Rosalind C.|last2=Feinbaum|first2=Rhonda L.|last3=Ambros|first3=Victor|title=The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14|journal=Cell|volume=75|issue=5|year=1993|pages=843–854|issn=0092-8674|doi=10.1016/0092-8674(93)90529-Y|pmid=8252621|doi-access=free}} and downregulated LIN-14 protein expression.{{cite journal|last1=Wightman|first1=Bruce|last2=Ha|first2=Ilho|last3=Ruvkun|first3=Gary|title=Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans|journal=Cell|volume=75|issue=5|year=1993|pages=855–862|issn=0092-8674|doi=10.1016/0092-8674(93)90530-4|pmid=8252622|doi-access=free}} miRNAs are now thought to be involved in the regulation of many developmental and biological processes, including haematopoiesis (miR-181 in Mus musculus{{cite journal|last1=Chen|first1=C.-Z.|title=MicroRNAs Modulate Hematopoietic Lineage Differentiation|journal=Science|volume=303|issue=5654|year=2004|pages=83–86|issn=0036-8075|doi=10.1126/science.1091903|pmid=14657504|bibcode=2004Sci...303...83C|hdl=1721.1/7483|s2cid=7044929|url=https://dspace.mit.edu/bitstream/1721.1/7483/1/MEBCS012.pdf|hdl-access=free}}), lipid metabolism (miR-14 in Drosophila melanogaster{{cite journal|last1=Xu|first1=Peizhang|last2=Vernooy|first2=Stephanie Y.|last3=Guo|first3=Ming|last4=Hay|first4=Bruce A.|title=The Drosophila MicroRNA Mir-14 Suppresses Cell Death and Is Required for Normal Fat Metabolism|journal=Current Biology|volume=13|issue=9|year=2003|pages=790–795|issn=0960-9822|doi=10.1016/S0960-9822(03)00250-1|pmid=12725740|s2cid=6391484|url=https://authors.library.caltech.edu/102829/2/1-s2.0-S0960982203002501-mmc1.pdf|doi-access=free}}) and neuronal development (lsy-6 in Caenorhabditis elegans{{cite journal|last1=Johnston|first1=Robert J.|last2=Hobert|first2=Oliver|title=A microRNA controlling left/right neuronal asymmetry in Caenorhabditis elegans|journal=Nature|volume=426|issue=6968|year=2003|pages=845–849|issn=0028-0836|doi=10.1038/nature02255|pmid=14685240|bibcode=2003Natur.426..845J|s2cid=4410288}}). These discoveries necessitated development of techniques able to identify and characterize miRNAs, such as miRNA-seq.

MicroRNA sequencing (miRNA-seq) was developed to take advantage of next-generation sequencing or massively parallel high-throughput sequencing technologies in order to find novel miRNAs and their expression profiles in a given sample. miRNA sequencing in and of itself is not a new idea, initial methods of sequencing utilized Sanger sequencing methods. Sequencing preparation involved creating libraries by cloning of DNA reverse transcribed from endogenous small RNAs of 21–25 bp size selected by column and gel electrophoresis.{{cite journal|last1=Lee|first1=R. C.|title=An Extensive Class of Small RNAs in Caenorhabditis elegans|journal=Science|volume=294|issue=5543|year=2001|pages=862–864|issn=0036-8075|doi=10.1126/science.1065329|pmid=11679672|bibcode=2001Sci...294..862L|s2cid=33480585}} However, this method is exhaustive in terms of time and resources, as each clone has to be individually amplified and prepared for sequencing. This method also inadvertently favors miRNAs that are highly expressed. Next-generation sequencing eliminates the need for sequence specific hybridization probes required in DNA microarray analysis as well as laborious cloning methods required in the Sanger sequencing method. Additionally, next-generation sequencing platforms in the miRNA-SEQ method facilitate the sequencing of large pools of small RNAs in a single sequencing run.{{cite book|last1=Aldridge|first1=Sarah|last2=Hadfield|first2=James|chapter=Introduction to miRNA Profiling Technologies and Cross-Platform Comparison |volume=822|year=2012|pages=19–31|issn=1064-3745|doi=10.1007/978-1-61779-427-8_2|title=Next-Generation MicroRNA Expression Profiling Technology|publisher=Next-Generation MicroRNA Expression Profiling Technology|series=Methods in Molecular Biology|pmid=22144189|isbn=978-1-61779-426-1}}

miRNA-seq can be performed using a variety of sequencing platforms. The first analysis of small RNAs using miRNA-seq methods examined approximately 1.4 million small RNAs from the model plant Arabidopsis thaliana using Lynx Therapeutics' Massively Parallel Signature Sequencing (MPSS) sequencing platform. This study demonstrated the potential of novel, high-throughput sequencing technologies for the study of small RNAs, and it showed that genomes generate large numbers of small RNAs with plants as particularly rich sources of small RNAs.{{cite journal|last=Lu|first=C|author2=Tej, SS |author3=Luo, S |author4=Haudenschild, CD |author5=Meyers, BC |author6= Green, PJ |title=Elucidation of the small RNA component of the transcriptome.|journal=Science|date=Sep 2, 2005|volume=309|issue=5740|pages=1567–9|pmid=16141074|doi=10.1126/science.1114112|bibcode=2005Sci...309.1567L|s2cid=1651848}} Later studies used other sequencing technologies, such as a study in C. elegans which identified 18 novel miRNA genes as well as a new class of nematode small RNAs termed 21U-RNAs.{{cite journal|last1=Ruby|first1=J. Graham|last2=Jan|first2=Calvin|last3=Player|first3=Christopher|last4=Axtell|first4=Michael J.|last5=Lee|first5=William|last6=Nusbaum|first6=Chad|last7=Ge|first7=Hui|last8=Bartel|first8=David P.|title=Large-Scale Sequencing Reveals 21U-RNAs and Additional MicroRNAs and Endogenous siRNAs in C. elegans|journal=Cell|volume=127|issue=6|year=2006|pages=1193–1207|issn=0092-8674|doi=10.1016/j.cell.2006.10.040|pmid=17174894|s2cid=16838469|doi-access=free}} Another study comparing small RNA profiles of human cervical tumours and normal tissue, utilized the Illumina (company) Genome Analyzer to identify 64 novel human miRNA genes as well as 67 differentially expressed miRNAs.{{cite journal|last1=Witten|first1=Daniela|last2=Tibshirani|first2=Robert|last3=Gu|first3=Sam|last4=Fire|first4=Andrew|last5=Lui|first5=Weng-Onn|title=Ultra-high throughput sequencing-based small RNA discovery and discrete statistical biomarker analysis in a collection of cervical tumours and matched controls|journal=BMC Biology|volume=8|issue=1|year=2010|pages=58|issn=1741-7007|doi=10.1186/1741-7007-8-58|pmc=2880020|pmid=20459774 |doi-access=free }} Applied Biosystems SOLiD sequencing platform has also been used to examine the prognostic value of miRNAs in detecting human breast cancer.{{cite journal|last1=Wu|first1=Qian|last2=Lu|first2=Zuhong|last3=Li|first3=Hailing|last4=Lu|first4=Jiafeng|last5=Guo|first5=Li|last6=Ge|first6=Qinyu|title=Next-Generation Sequencing of MicroRNAs for Breast Cancer Detection|journal=Journal of Biomedicine and Biotechnology|volume=2011|year=2011|pages=1–7|issn=1110-7243|doi=10.1155/2011/597145|pmc=3118289|pmid=21716661|doi-access=free}}

File:Miran-seq-library-prep.pdf

{{See also|RNA extraction|Phenol–chloroform extraction|Gel Electrophoresis|DNA ligase|Reverse transcriptase|Polymerase chain reaction}}

Sequence library construction can be performed using a variety of different kits depending on the high-throughput sequencing platform being employed. However, there are several common steps for small RNA sequencing preparation.{{cite journal|last=Lu|first=C|author2=Meyers, BC |author3=Green, PJ |title=Construction of small RNA cDNA libraries for deep sequencing.|journal=Methods |date=October 2007|volume=43|issue=2|pages=110–7|pmid=17889797|doi=10.1016/j.ymeth.2007.05.002}}{{cite journal|last1=Hafner|first1=Markus|last2=Landgraf|first2=Pablo|last3=Ludwig|first3=Janos|last4=Rice|first4=Amanda|last5=Ojo|first5=Tolulope|last6=Lin|first6=Carolina|last7=Holoch|first7=Daniel|last8=Lim|first8=Cindy|last9=Tuschl|first9=Thomas|title=Identification of microRNAs and other small regulatory RNAs using cDNA library sequencing|journal=Methods|volume=44|issue=1|year=2008|pages=3–12|issn=1046-2023|doi=10.1016/j.ymeth.2007.09.009|pmid=18158127|pmc=2847350}}

Total RNA Isolation

In a given sample all the RNA is extracted and isolated using an isothiocyanate/phenol/chloroform (GITC/phenol) method or a commercial product such as Trizol (Invitrogen) reagent. A starting quantity of 50-100 μg total RNA, 1 g of tissue typically yields 1 mg of total RNA, is usually required for gel purification and size selection. Quality control of the RNA is also measured, for example running an RNA chip on Caliper LabChipGX (Caliper Life Sciences).

Size Fractionation of small RNAs by Gel Electrophoresis

Isolated RNA is run on a denaturing polyacrylamide gel. An imaging method such as radioactive 5’-32P-labeled oligonucleotides along with a size ladder is used to identify a section of the gel containing RNA of the appropriate size, reducing the amount of material ultimately sequenced. This step does not have to be necessarily carried out before the ligation and reverse transcription steps outlined below.

Ligation

The ligation step adds DNA adaptors to both ends of the small RNAs, which act as primer binding sites during reverse transcription and PCR amplification. An adenylated single strand DNA 3’adaptor followed by a 5’adaptor is ligated to the small RNAs using a ligating enzyme such as T4 RNA ligase2. The adaptors are also designed to capture small RNAs with a 5’ phosphate group, characteristic microRNAs, rather than RNA degradation products with a 5’ hydroxyl group.

Reverse Transcription and PCR Amplification

This step converts the small adaptor ligated RNAs into cDNA clones used in the sequencing reaction. There are many commercial kits available that will carry out this step using some form of reverse transcriptase. PCR is then carried out to amplify the pool of cDNA sequences. Primers designed with unique nucleotide tags can also be used in this step to create ID tags in pooled library multiplex sequencing.

{{See also|DNA sequencing}}

The actual RNA sequencing varies significantly depending on the platform used. Three common next-generation sequencing{{cite journal|last1=Shendure|first1=Jay|last2=Ji|first2=Hanlee|title=Next-generation DNA sequencing|journal=Nature Biotechnology|volume=26|issue=10|year=2008|pages=1135–1145|issn=1087-0156|doi=10.1038/nbt1486|pmid=18846087|s2cid=6384349}} platforms are Pyrosequencing on the 454 Life Sciences platform,{{cite web |url=http://www.454.com/applications/transcriptome-sequencing.asp |title=Applications - Transcriptome Sequencing : 454 Life Sciences, a Roche Company |access-date=2012-03-01 |url-status=dead|archive-url=https://web.archive.org/web/20110526125609/http://www.454.com/applications/transcriptome-sequencing.asp |archive-date=2011-05-26 }} polymerase-based sequence-by-synthesis on the Illumina (company) platform,{{Cite web|url=http://www.illumina.com/pages.ilmn?ID=204|title = Illumina DesignStudio}} or sequencing by ligation on the ABI Solid Sequencing platform.{{cite web |url=http://solid.appliedbiosystems.com/ |title=Archived copy |access-date=2008-05-16 |url-status=dead|archive-url=https://web.archive.org/web/20080516181322/http://solid.appliedbiosystems.com/ |archive-date=2008-05-16 }}

Central to miRNA-seq data analysis is the ability to 1) obtain miRNA abundance levels from sequence reads, 2) discover novel miRNAs and then be able to 3) determine the differentially expressed miRNA and their 4) associated mRNA gene targets.

File:Mirna seq data analysis.pdf

miRNAs may be preferentially expressed in certain cell types, tissues, stages of development, or in particular disease states such as cancer. Since deep sequencing (miRNA-seq) generates millions of reads from a given sample, it allows us to profile miRNAs; whether it may be by quantifying their absolute abundance, to discover their variants (known as isomirs{{cite journal|last1=Morin|first1=R. D.|last2=O'Connor|first2=M. D.|last3=Griffith|first3=M.|last4=Kuchenbauer|first4=F.|last5=Delaney|first5=A.|last6=Prabhu|first6=A.-L.|last7=Zhao|first7=Y.|last8=McDonald|first8=H.|last9=Zeng|first9=T.|last10=Hirst|first10=M.|last11=Eaves|first11=C. J.|last12=Marra|first12=M. A.|title=Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells|journal=Genome Research|volume=18|issue=4|year=2008|pages=610–621|issn=1088-9051|doi=10.1101/gr.7179508|pmid=18285502|pmc=2279248}}) Note that given that the average length of sequence reads are longer than the average miRNA (17-25 nt), the 3’ and 5’ ends of the miRNA should be found on the same read.

There are several miRNA abundance quantification algorithms.{{cite journal|last1=Berninger|first1=Philipp|last2=Gaidatzis|first2=Dimos|last3=van Nimwegen|first3=Erik|last4=Zavolan|first4=Mihaela|title=Computational analysis of small RNA cloning data|journal=Methods|volume=44|issue=1|year=2008|pages=13–21|issn=1046-2023|doi=10.1016/j.ymeth.2007.10.002|pmid=18158128}} Their general steps are as follows:{{cite journal|last1=Creighton|first1=C. J.|last2=Reid|first2=J. G.|last3=Gunaratne|first3=P. H.|title=Expression profiling of microRNAs by deep sequencing|journal=Briefings in Bioinformatics|volume=10|issue=5|year=2009|pages=490–497|issn=1467-5463|doi=10.1093/bib/bbp019|pmid=19332473|pmc=2733187}}

1. After sequencing, the raw sequence reads are filtered based on quality. The adaptor sequences are also trimmed off the raw sequence reads.
2. The resulting reads are then formatted into a fasta file where the copy number and sequence is recorded for each unique tag.
3. Sequences that may represent E. Coli contamination are identified by a BLAST search against an E. Coli database and are removed from analysis.
4. Each of the remaining sequences are aligned against a miRNA sequence database (such as miRBase{{cite journal|last1=Kozomara|first1=A.|last2=Griffiths-Jones|first2=S.|title=miRBase: integrating microRNA annotation and deep-sequencing data|journal=Nucleic Acids Research|volume=39|issue=Database|year=2010|pages=D152–D157|issn=0305-1048|doi=10.1093/nar/gkq1027|pmid=21037258|pmc=3013655}}) In order to account for imperfect DICER processing, a 6nt overhang on the 3’ end, and 3nt on the 5’ end are allowed.
5. The reads that do not align to the miRNA database are then loosely aligned to miRNA precursors to detect miRNAs that might carry mutations or those that have gone through RNA editing.
6. The read counts for each miRNA are then normalized to the total number of mapped miRNAs to report the abundance of each miRNA.

Another advantage of miRNA-seq is that it allows the discovery of novel miRNAs that may have eluded traditional screening and profiling methods. There are several novel miRNA discovery algorithms. Their general steps are as follows:

1. Obtain reads that did not align to known miRNA sequences, and map them to the genome.
2. RNA Folding Method
3. For the miRNA sequences were an exact match is found, obtain the genomic sequence including ~100bp of flanking sequence on either side, and run the RNA through RNA folding software such as the Vienna package.{{cite journal|last1=Hofacker|first1=I. L.|last2=Fontana|first2=W.|last3=Stadler|first3=P. F.|last4=Bonhoeffer|first4=L. S.|last5=Tacker|first5=M.|last6=Schuster|first6=P.|title=Fast folding and comparison of RNA secondary structures|journal=Monatshefte für Chemie|volume=125|issue=2|year=1994|pages=167–188|issn=0026-9247|doi=10.1007/BF00818163|s2cid=19344304}}
4. Folded sequences that lie on one arm of the miRNA hairpin and have a minimum free energy of less than ~25kcal/mol are shortlisted as putative miRNA.
5. The shortlisted sequences are trimmed down to include only the possible precursor sequence and are then refolded to ensure that the precursor was not artificially stabilized by neighbouring sequences.
6. The resulting folded sequences are considered novel miRNAs if the miRNA sequence falls within one arm of the hairpin, and are highly conserved between species.
7. Star Strand Expression Method (miRdeep{{cite journal|last1=Yang|first1=X.|last2=Li|first2=L.|title=miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants|journal=Bioinformatics|year=2011|issn=1367-4803|doi=10.1093/bioinformatics/btr430|pmid=21775303|volume=27|issue=18|pages=2614–5|doi-access=free}})
8. Novel miRNA sequences are identified based on the characteristic expression pattern that they display due to DICER processing: higher expression of the mature miRNA over the star strand and loop sequences.

After the abundances of miRNAs are quantified for each sample, their expression levels can be compared between samples. One would then be able to identify miRNA that are preferentially expressed that particular time points, or in particular tissues or disease states. After normalizing for the number of mapped reads between samples, one can use a host of statistical tests (like those used in gene expression profiling) to determine differential expression

Identifying a miRNA's mRNA targets will provide an understanding of the genes or networks of genes whose expression they regulate.{{cite journal|last1=Cloonan|first1=Nicole|last2=Wani|first2=Shivangi|last3=Xu|first3=Qinying|last4=Gu|first4=Jian|last5=Lea|first5=Kristi|last6=Heater|first6=Sheila|last7=Barbacioru|first7=Catalin|last8=Steptoe|first8=Anita L|last9=Martin|first9=Hilary C|last10=Nourbakhsh|first10=Ehsan|last11=Krishnan|first11=Keerthana|last12=Gardiner|first12=Brooke|last13=Wang|first13=Xiaohui|last14=Nones|first14=Katia|last15=Steen|first15=Jason A|last16=Matigan|first16=Nick|last17=Wood|first17=David L|last18=Kassahn|first18=Karin S|last19=Waddell|first19=Nic|last20=Shepherd|first20=Jill|last21=Lee|first21=Clarence|last22=Ichikawa|first22=Jeff|last23=McKernan|first23=Kevin|last24=Bramlett|first24=Kelli|last25=Kuersten|first25=Scott|last26=Grimmond|first26=Sean M|title=MicroRNAs and their isomiRs function cooperatively to target common biological pathways|journal=Genome Biology|volume=12|issue=12|year=2011|pages=R126|issn=1465-6906|doi=10.1186/gb-2011-12-12-r126|pmid=22208850|pmc=3334621 |doi-access=free }} Public databases provide predictions of miRNA targets. But to better distinguish true positive predictions from false positive predictions, miRNA-seq data can be integrated to mRNA-seq data to observe for miRNA:mRNA functional pairs. RNA22,{{cite journal |vauthors=Miranda KC, Huynh T, Tay Y, Ang YS, Tam WL, Thomson AM, Lim B, Rigoutsos I |title=A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes. |journal=Cell |volume=126 |issue=6 |pages=1203–17 |year=2006 |pmid=16990141 |doi=10.1016/j.cell.2006.07.031|s2cid=12749133 |doi-access=free }} TargetScan,{{cite journal|last=Lewis|first=BP|author2=Burge CB |author3=Bartel DP |title=Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets|journal=Cell|date=Jan 14, 2005|volume=120|issue=1|pages=15–20|pmid=15652477|doi=10.1016/j.cell.2004.12.035|s2cid=17316349|doi-access=free}}{{cite journal|last=Grimson|first=A|author2=Farh, KK |author3=Johnston, WK |author4=Garrett-Engele, P |author5=Lim, LP |author6= Bartel, DP |title=MicroRNA targeting specificity in mammals: determinants beyond seed pairing.|journal=Molecular Cell|date=Jul 6, 2007|volume=27|issue=1|pages=91–105|pmid=17612493|doi=10.1016/j.molcel.2007.06.017 |pmc=3800283}}{{cite journal|last=Friedman|first=RC|author2=Farh, KK |author3=Burge, CB |author4= Bartel, DP |title=Most mammalian mRNAs are conserved targets of microRNAs.|journal=Genome Research|date=January 2009|volume=19|issue=1|pages=92–105|doi=10.1101/gr.082701.108|pmid=18955434|pmc=2612969}}{{cite journal|last=Garcia|first=DM|author2=Baek, D |author3=Shin, C |author4=Bell, GW |author5=Grimson, A |author6= Bartel, DP |title=Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other microRNAs.|journal=Nature Structural & Molecular Biology|date=Sep 11, 2011|volume=18|issue=10|pages=1139–46|pmid=21909094|doi=10.1038/nsmb.2115|pmc=3190056}}{{Cite journal|title=Predicting effective microRNA target sites in mammalian mRNAs |journal=eLife |date=2015-08-12 |issn=2050-084X |pmc=4532895 |pmid=26267216 |pages=e05005 |volume=4 |doi=10.7554/eLife.05005 |first1=Vikram |last1=Agarwal |first2=George W. |last2=Bell |first3=Jin-Wu |last3=Nam |first4=David P. |last4=Bartel |doi-access=free }}{{cite journal |last1=Agarwal |first1=V |last2=Subtelny |first2=AO |last3=Thiru |first3=P |last4=Ulitsky |first4=I |last5=Bartel |first5=DP |title=Predicting microRNA targeting efficacy in Drosophila. |journal=Genome Biology |date=4 October 2018 |volume=19 |issue=1 |pages=152 |doi=10.1186/s13059-018-1504-3 |pmid=30286781 |pmc=6172730 |doi-access=free }} miRanda,{{cite journal|last1=Maziere|first1=P|last2=Enright|first2=A|title=Prediction of microRNA targets|journal=Drug Discovery Today|volume=12|issue=11–12|year=2007|pages=452–458|issn=1359-6446|doi=10.1016/j.drudis.2007.04.002|pmid=17532529}} and PicTarKrek, A. Identification of microRNA targets. DAI-B 70/07, (2010). are software designed for this purpose. A list of prediction software is given here.

The general steps are:

1. Determine miRNA:mRNA binding pairs, complementarity between the miRNA sequences at the 3’-UTR of the mRNA sequence is identified.
2. Determine the degree of conservation of miRNA:mRNA binding pairs across species. Typically, more highly binding pairs are less likely to be false positives of prediction.
3. Observe for evidence of miRNA targeting in mRNA-seq or protein expression data: where the miRNA expression is high, the gene and protein expression of its target gene should be low.

Many miRNAs function to direct cleavage of their mRNA targets; this is particularly true in plants, and thus high-throughput sequencing methods have been developed to take advantage of this property of miRNAs by sequencing the uncapped 3' ends of cleaved or degraded mRNAs. These methods are known as Degradome sequencing or PARE.{{cite journal |vauthors=German MA, Pillay M, Jeong DH, Hetawal A, Luo S, Janardhanan P, Kannan V, Rymarquis LA, Nobuta K, German R, De Paoli E, Lu C, Schroth G, Meyers BC, Green PJ |title=Global identification of microRNA-target RNA pairs by parallel analysis of RNA ends. |journal=Nat. Biotechnol. |volume=26 |issue=8 |pages=941–946 |year=2008 |pmid=18542052 |doi=10.1038/nbt1417|s2cid=13187064 }}{{cite journal |vauthors=Addo-Quaye C, Eshoo TW, Bartel DP, Axtell MJ |title=Endogenous siRNA and miRNA targets identified by sequencing of the Arabidopsis degradome. |journal=Curr. Biol. |volume=18 |issue=10 |pages=758–762 |year=2008 |pmid=18472421 |doi=10.1016/j.cub.2008.04.042 |pmc=2583427}} Validation of target cleavage in specific mRNAs is typically performed using a modified version of 5' Rapid Amplification of cDNA Ends with a gene-specific primer.

miRNA-seq has revealed novel miRNAs that were previously eluded in traditional miRNA profiling methods. Examples of such findings are in embryonic stem cells, chicken embryos,{{cite journal|last1=Buermans|first1=Henk PJ|last2=Ariyurek|first2=Yavuz|last3=van Ommen|first3=Gertjan|last4=den Dunnen|first4=Johan T|last5='t Hoen|first5=Peter AC|title=New methods for next generation sequencing based microRNA expression profiling|journal=BMC Genomics|volume=11|issue=1|year=2010|pages=716|issn=1471-2164|doi=10.1186/1471-2164-11-716|pmid=21171994|pmc=3022920 |doi-access=free }} acute lymphoblastic leukaemia,{{cite journal|last1=Zhang|first1=Baohong|last2=Zhang|first2=Hua|last3=Yang|first3=Jian-Hua|last4=Zheng|first4=Yu-Sheng|last5=Zhang|first5=Peng|last6=Chen|first6=Xiao|last7=Wu|first7=Jun|last8=Xu|first8=Ling|last9=Luo|first9=Xue-Qun|last10=Ke|first10=Zhi-Yong|last11=Zhou|first11=Hui|last12=Qu|first12=Liang-Hu|last13=Chen|first13=Yue-Qin|title=Genome-Wide Analysis of Small RNA and Novel MicroRNA Discovery in Human Acute Lymphoblastic Leukemia Based on Extensive Sequencing Approach|journal=PLOS ONE|volume=4|issue=9|year=2009|pages=e6849|issn=1932-6203|doi=10.1371/journal.pone.0006849|pmid=19724645|pmc=2731166|bibcode=2009PLoSO...4.6849Z|doi-access=free}} diffuse large b-cell lymphoma and b-cells,{{cite journal|last1=Jima|first1=D. D.|last2=Zhang|first2=J.|last3=Jacobs|first3=C.|last4=Richards|first4=K. L.|last5=Dunphy|first5=C. H.|last6=Choi|first6=W. W. L.|last7=Yan Au|first7=W.|last8=Srivastava|first8=G.|last9=Czader|first9=M. B.|last10=Rizzieri|first10=D. A.|last11=Lagoo|first11=A. S.|last12=Lugar|first12=P. L.|last13=Mann|first13=K. P.|last14=Flowers|first14=C. R.|last15=Bernal-Mizrachi|first15=L.|last16=Naresh|first16=K. N.|last17=Evens|first17=A. M.|last18=Gordon|first18=L. I.|last19=Luftig|first19=M.|last20=Friedman|first20=D. R.|last21=Weinberg|first21=J. B.|last22=Thompson|first22=M. A.|last23=Gill|first23=J. I.|last24=Liu|first24=Q.|last25=How|first25=T.|last26=Grubor|first26=V.|last27=Gao|first27=Y.|last28=Patel|first28=A.|last29=Wu|first29=H.|last30=Zhu|first30=J.|last31=Blobe|first31=G. C.|last32=Lipsky|first32=P. E.|last33=Chadburn|first33=A.|last34=Dave|first34=S. S.|title=Deep sequencing of the small RNA transcriptome of normal and malignant human B cells identifies hundreds of novel microRNAs|journal=Blood|volume=116|issue=23|year=2010|pages=e118–e127|issn=0006-4971|doi=10.1182/blood-2010-05-285403|pmid=20733160|pmc=3012600}} acute myeloid leukemia,{{cite journal|last1=Starczynowski|first1=D. T.|last2=Morin|first2=R.|last3=McPherson|first3=A.|last4=Lam|first4=J.|last5=Chari|first5=R.|last6=Wegrzyn|first6=J.|last7=Kuchenbauer|first7=F.|last8=Hirst|first8=M.|last9=Tohyama|first9=K.|last10=Humphries|first10=R. K.|last11=Lam|first11=W. L.|last12=Marra|first12=M.|last13=Karsan|first13=A.|title=Genome-wide identification of human microRNAs located in leukemia-associated genomic alterations|journal=Blood|volume=117|issue=2|year=2010|pages=595–607|issn=0006-4971|doi=10.1182/blood-2010-03-277012|pmid=20962326|doi-access=free}} and lung cancer.{{cite journal|last1=Keller|first1=Andreas|last2=Backes|first2=Christina|last3=Leidinger|first3=Petra|last4=Kefer|first4=Nathalie|last5=Boisguerin|first5=Valesca|last6=Barbacioru|first6=Catalin|last7=Vogel|first7=Britta|last8=Matzas|first8=Mark|last9=Huwer|first9=Hanno|last10=Katus|first10=Hugo A.|last11=Stähler|first11=Cord|last12=Meder|first12=Benjamin|last13=Meese|first13=Eckart|title=Next-generation sequencing identifies novel microRNAs in peripheral blood of lung cancer patients|journal=Molecular BioSystems|volume=7|issue=12|year=2011|pages=3187–99|issn=1742-206X|doi=10.1039/c1mb05353a|pmid=22027949}}

Micro RNAs are important regulators of almost all cellular processes such as survival, proliferation, and differentiation. Consequently, it is not unexpected that miRNAs are involved in various aspects of cancer through the regulation of onco- and tumor suppressor gene expression. In combination with the development of high-throughput profiling methods, miRNAs have been identified as biomarkers for cancer classification, response to therapy, and prognosis.{{cite journal|last1=Chan|first1=Elcie|last2=Prado|first2=Daniel Estévez|last3=Weidhaas|first3=Joanne Barnes|title=Cancer microRNAs: From subtype profiling to predictors of response to therapy|journal=Trends in Molecular Medicine|volume=17|issue=5|year=2011|pages=235–243|issn=1471-4914|doi=10.1016/j.molmed.2011.01.008|pmid=21354374|pmc=3092835}} Additionally, because miRNAs regulate gene expression they can also reveal perturbations in important regulatory networks that may be driving a particular disorder. Several applications of miRNAs as biomarkers and predictors of disease are given below.

^αThis is not a comprehensive list of miRNAs involved with these malignancies.

The disadvantages of using miRNA-seq over other methods of miRNA profiling are that it is more expensive, generally requires a larger amount of total RNA, involves extensive amplification, and is more time-consuming than microarray and qPCR methods.{{cite journal|last1=Baker|first1=Monya|title=MicroRNA profiling: separating signal from noise|journal=Nature Methods|volume=7|issue=9|year=2010|pages=687–692|issn=1548-7091|doi=10.1038/nmeth0910-687|pmid=20805796|s2cid=6853222|doi-access=free}} As well, miRNA-seq library preparation methods seem to have systematic preferential representation of the miRNA complement, and this prevents accurate determination of miRNA abundance.{{cite journal|last1=Linsen|first1=Sam E V|last2=de Wit|first2=Elzo|last3=Janssens|first3=Georges|last4=Heater|first4=Sheila|last5=Chapman|first5=Laura|last6=Parkin|first6=Rachael K|last7=Fritz|first7=Brian|last8=Wyman|first8=Stacia K|last9=de Bruijn|first9=Ewart|last10=Voest|first10=Emile E|last11=Kuersten|first11=Scott|last12=Tewari|first12=Muneesh|last13=Cuppen|first13=Edwin|title=Limitations and possibilities of small RNA digital gene expression profiling|journal=Nature Methods|volume=6|issue=7|year=2009|pages=474–476|issn=1548-7091|doi=10.1038/nmeth0709-474|pmid=19564845|s2cid=7953265}} At the same time, the approach is hybridization independent and therefore does not require a priori sequence information. Because of this, one can obtain sequences of novel miRNAs and miRNA isoforms (isoMirs), distinguish sequentially similar miRNAs, and identify point mutations.{{cite journal|last1=Git|first1=A.|last2=Dvinge|first2=H.|last3=Salmon-Divon|first3=M.|last4=Osborne|first4=M.|last5=Kutter|first5=C.|last6=Hadfield|first6=J.|last7=Bertone|first7=P.|last8=Caldas|first8=C.|title=Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression|journal=RNA|volume=16|issue=5|year=2010|pages=991–1006|issn=1355-8382|doi=10.1261/rna.1947110|pmid=20360395|pmc=2856892}}

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Category:DNA sequencing