MicroRNAs (miRNAs) are emerging as important, albeit poorly characterized, regulators of biological processes. Key to further elucidation of their roles is the generation of more complete lists of their numbers and expression changes in different cell states. Here, we report a new method for surveying the expression of small RNAs, including microRNAs, using Illumina sequencing technology. We also present a set of methods for annotating sequences deriving from known miRNAs, identifying variability in mature miRNA sequences, and identifying sequences belonging to previously unidentified miRNA genes. Application of this approach to RNA from human embryonic stem cells obtained before and after their differentiation into embryoid bodies revealed the sequences and expression levels of 334 known plus 104 novel miRNA genes. One hundred seventy-one known and 23 novel microRNA sequences exhibited significant expression differences between these two developmental states. Owing to the increased number of sequence reads, these libraries represent the deepest miRNA sampling to date, spanning nearly six orders of magnitude of expression. The predicted targets of those miRNAs enriched in either sample shared common features. Included among the high-ranked predicted gene targets are those implicated in differentiation, cell cycle control, programmed cell death, and transcriptional regulation.

/pdf/application-of-massively-parallel-sequencing-to-microrna-2p4fm1ocma.pdf

Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells.

https://bi.snu.ac.kr/Publications/Journals/International/TRENDS_GENET_JWNam.pdf

Genomics of microRNA

Plant microRNA: a small regulatory molecule with big impact.

MicroRNAs (miRNAs) are important genetic regulators of development, differentiation, growth, and metabolism. The mammalian genome encodes ≈500 known miRNA genes. Approximately 50% are expressed from non-protein-coding transcripts, whereas the rest are located mostly in the introns of coding genes. Intronic miRNAs are generally transcribed coincidentally with their host genes. However, the nature of the primary transcript of intergenic miRNAs is largely unknown. We have performed a large-scale analysis of transcription start sites, polyadenylation signals, CpG islands, EST data, transcription factor-binding sites, and expression ditag data surrounding intergenic miRNAs in the human genome to improve our understanding of the structure of their primary transcripts. We show that a significant fraction of primary transcripts of intergenic miRNAs are 3–4 kb in length, with clearly defined 5′ and 3′ boundaries. We provide strong evidence for the complete transcript structure of a small number of human miRNAs.

https://www.pnas.org/content/pnas/104/45/17719.full.pdf

Genomic analysis of human microRNA transcripts

microRNAs (miRNAs) are an abundant class of newly identified endogenous non-protein-coding small RNAs. They exist in animals, plants, and viruses, and play an important role in gene silencing. Translational repression, mRNA cleavage, and mRNA decay initiated by miRNA-directed deadenylation of targeted mRNAs are three mechanisms of miRNA-guided gene regulation at the post-transcriptional levels. Many miRNAs are highly conserved in animals and plants, suggesting that they play an essential function in plants and animals. Lots of investigations indicate that miRNAs are involved in multiple biological processes, including stem cell differentiation, organ development, phase change, signaling, disease, cancer, and response to biotic and abiotic environmental stresses. This review provides a general background and current advance on the discovery, history, biogenesis, genomics, mechanisms, and functions of miRNAs.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcp.20869

MicroRNAs and their regulatory roles in animals and plants

Background: MicroRNAs (miRNAs) are a group of short (similar to 22 nt) non-coding RNAs that play important regulatory roles. MiRNA precursors (pre-miRNAs) are characterized by their hairpin structures. However, a large amount of similar hairpins can be folded in many genomes. Almost all current methods for computational prediction of miRNAs use comparative genomic approaches to identify putative pre-miRNAs from candidate hairpins. Ab initio method for distinguishing pre-miRNAs from sequence segments with pre-miRNA-like hairpin structures is lacking. Being able to classify real vs. pseudo pre-miRNAs is important both for understanding of the nature of miRNAs and for developing ab initio prediction methods that can discovery new miRNAs without known homology.

/pdf/classification-of-real-and-pseudo-microrna-precursors-using-2319w8u8lk.pdf

Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine

Motivation: MicroRNAs (miRNA) are ∼22 nt long non-coding RNAs that are derived from larger hairpin RNA precursors and play important regulatory roles in both animals and plants. The short length of the miRNA sequences and relatively low conservation of pre-miRNA sequences restrict the conventional sequence-alignment-based methods to finding only relatively close homologs. On the other hand, it has been reported that miRNA genes are more conserved in the secondary structure rather than in primary sequences. Therefore, secondary structural features should be more fully exploited in the homologue search for new miRNA genes.

Results: In this paper, we present a novel genome-wide computational approach to detect miRNAs in animals based on both sequence and structure alignment. Experiments show this approach has higher sensitivity and comparable specificity than other reported homologue searching methods. We applied this method on Anopheles gambiae and detected 59 new miRNA genes.

Availability: This program is available at http://bioinfo.au.tsinghua.edu.cn/miralign

Contact: daulyd@tsinghua.edu.cn

Supplementary information: Supplementary information is available at http://bioinfo.au.tsinghua.edu.cn/miralign/supplementary.htm

MicroRNA identification based on sequence and structure alignment

MicroRNAs (miRNAs) are a class of approximately 22-nt small RNAs that regulate posttranscriptional gene expression. Thousands of expressed sequence tags (ESTs) have been identified by using upstream 2500-nt and downstream 4000-nt flanking sequences to BLAST in the dbEST database. The cotranscription of the miRNAs and their flanking sequences covered by the matched ESTs is verified by RT-PCR. It directly reveals that a large portion of mammalian intergenic miRNAs are first transcribed as long primary transcripts (pri-miRNAs). Also, the transcripts' ranges of tens of pri-miRNAs are predicted by the EST-extension method. We then extracted the tissue-specific expression information from the annotations of the matched ESTs and established the expression profile of the studied miRNAs for tens of tissues. This provided a new way to establish the expression profiles of miRNAs. Results show that the human brain, lung, liver, and eye and the mouse brain, eye, and mammary gland are tissues in which enriched numbers of miRNAs are expressed.

/pdf/primary-transcripts-and-expressions-of-mammal-intergenic-x5qrmdz616.pdf

Primary transcripts and expressions of mammal intergenic microRNAs detected by mapping ESTs to their flanking sequences

Although a large amount of experimentally derived information about RNA editing sites currently exists, this information has remained scattered in a variety of sources and in diverse data formats. Availability of standard collections for high-quality experimental data will be by of great help for systematic studying of RNA editing, especially for developing computational algorithm to predict RNA editing site. dbRES (http://bioinfo.au.tsinghua.edu.cn/dbRES) is a public database of known RNA editing sites. All sites are manually curated from literature and GenBank annotations. dbRES version 1.1 contains 5437 RNA editing sites of 251 transcripts, covering 96 organisms across plant, metazoan, protozoa, fungi and virus. dbRES provides comprehensive annotations and data summaries, including (but not limited to) transcript sequences, RNA editing types, editing site locations, amino acid changes, organisms, subcellular organelles (if available), cited references, etc. A user-friendly web interface is developed to facilitate both retrieving data and online display of RNA edit site information.

Tao He

Papers

Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine

MicroRNA identification based on sequence and structure alignment

Primary transcripts and expressions of mammal intergenic microRNAs detected by mapping ESTs to their flanking sequences

dbRES: a web-oriented database for annotated RNA editing sites

Independent transcription of miR-281 in the intron of ODA in Drosophila melanogaster.