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MicroRNAs (miRNAs) can group together along the human genome to form stable secondary structures made of several hairpins hosting miRNAs in their stems. The few known examples of such structures are all involved in cancer development. A large scale computational analysis of human chromosomes crossing sequence analysis and deep sequencing data revealed the presence of >400 structural clusters of miRNAs in the human genome. An a posteriori analysis validates predictions as bona fide miRNAs. A functional analysis of structural clusters position along the chromosomes co-localizes them with genes involved in several key cellular processes like immune systems, sensory systems, signal transduction and development. Immune systems diseases, infectious diseases and neurodegenerative diseases are characterized by genes that are especially well organized around structural clusters of miRNAs. Target genes functional analysis strongly supports a regulatory role of most predicted miRNAs and, notably, a strong involvement of predicted miRNAs in the regulation of cancer pathways. This analysis provides new fundamental insights on the genomic organization of miRNAs in human chromosomes.

Availability: The program, called MIReStruC (standing for ‘miRNA Structural Cluster’), has been implemented in bash, C, Awk and Python. It is available at the address http://www.ihes.fr/∼carbone/data9/.

• Mathelier A, Carbone A. (2013) Large scale chromosomal mapping of human microRNA structural clusters. Nucleic Acids Res [Epub ahead of print]. [article]

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Biogenesis and molecular function are two key subjects in the field of microRNA (miRNA) research. Deep sequencing has become the principal technique in cataloging of miRNA repertoire and generating expression profiles in an unbiased manner.

A team led by researchers at Ewha Womans University, Korea have updated miRGator to version v3.0. miRGator compiles the deep sequencing miRNA data available in public and the team has implemented several novel tools to facilitate exploration of massive data. The miR-seq browser supports users to examine short read alignment with the secondary structure and read count information available in concurrent windows. Features such as sequence editing, sorting, ordering, import and export of user data would be of great utility for studying iso-miRs, miRNA editing and modifications. miRNA-target relation is essential for understanding miRNA function. Coexpression analysis of miRNA and target mRNAs, based on miRNA-Seq and RNA-Seq data from the same sample, is visualized in the heat-map and network views where users can investigate the inverse correlation of gene expression and target relations, compiled from various databases of predicted and validated targets. By keeping datasets and analytic tools up-to-date, miRGator should continue to serve as an integrated resource for biogenesis and functional investigation of miRNAs.

Availability – miRGator v3.0 update is available at: http://mirgator.kobic.re.kr

Cho S, Jang I, Jun Y, Yoon S, Ko M, Kwon Y, Choi I, Jang H, Ryu D, Lee B, Kim VN, Kim W, Lee S. (2012) miRGator v3.0: a microRNA portal for deep sequencing, expression profiling and mRNA targeting. Nucleic Acids Res [Epub ahead of print]. [article]

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MicroRNAs (miRNAs) are small molecules that post-transcriptionally regulate the expression of a large number of protein-coding genes in metazoans, and are suggested to play important roles in fine-tuning immune mechanisms and disease responses. Polymorphisms in either miRNAs or their gene targets may have a significant impact on gene expression by abolishing, weakening or creating miRNA target sites, possibly leading to phenotypic variation.

A multi-national team led by researchers at INRA, Jouy-en-Josas, France has now explored the impact of variants in the 3′-UTR miRNA target sites of genes. They used combined predictions by TargetScan, PACMIT and TargetSpy, based on different biological parameters, for the identification of miRNA target sites and the discovery of polymorphic miRNA target sites (poly-miRTSs).

Predictions for three SLA genes (important determinants of immune, infectious disease and vaccine response in pigs) characterized by a different range of sequence variation provided proof of principle for the analysis of poly-miRTSs from a total of 144 M RNA-Seq reads collected from different porcine tissues….An inverse correlation in expression levels was demonstrated between miRNAs and co-expressed SLA targets by exploiting a published dataset (RNA-Seq and small RNA-Seq) of three porcine tissues. These results support the resource value of RNA-Seq collections to identify SNPs that may lead to altered miRNA regulation patterns.

• Endale Ahanda ML, Fritz ER, Estellé J, Hu ZL, Madsen O, Groenen MA, Beraldi D, Kapetanovic R, Hume DA, Rowland RR, Lunney JK, Rogel-Gaillard C, Reecy JM, Giuffra E. (2012) Prediction of Altered 3′- UTR miRNA-Binding Sites from RNA-Seq Data: The Swine Leukocyte Antigen Complex (SLA) as a Model Region. PLoS One 7(11), e48607. [article]

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from the Houston Chronicle

Hangzhou, China (PRWEB) May 29, 2012 – In a new study published online in Nature Communications, researchers from Sichuan Agricultural University and LC Sciences report the miRNAome in porcine adipose and muscle tissues. The report provides a valuable epigenomic source for obesity prediction and prevention and furthers the development of pig as a model organism for human obesity research.

Scientists now know that the genetic code alone isn’t responsible for adult phenotype or even the offspring of these adults. Epigenetics refers to changes in gene expression affecting phenotype that don’t involve changes to the DNA nucleotide sequence itself, and yet are heritable. DNA methylation, histone modification and microRNA (miRNA) expression are examples of epigenetic mechanisms that have recently been identified as important regulators of gene expression in many biological systems.

Obesity is a huge problem worldwide. Recently, the World Health Organization reported that obesity levels doubled in every region of the world between 1980 and 2008, spurring rates of non-communicable diseases such as diabetes and cancer that now account for almost two out of three deaths globally. It has become evident that epigenetic factors, such as DNA methylation and miRNA expression, have essential roles in obesity development. (read more…)

• Li, M. et al. (2012)An atlas of DNA methylomes in porcine adipose and muscle tissues. Nat Commun[Epub ahead of print]. [abstract]

 

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miRFANs, an online database for Arabidopsis thaliana miRNA function annotations. The creators integrated various type of datasets, including miRNA-target interactions, transcription factor (TF) and their targets, expression profiles, genomic annotations and pathways, into a comprehensive database, and developed various statistical and mining tools.

miRFANs consists of:

1. Comprehensive collection of miRNA targets for Arabidopsis thaliana provides valuable information about the functions of plant miRNAs.
2. Highly informative miRNA-mediated genetic regulatory network is extracted from our integrative database.
3. Set of statistical and mining tools is equipped for analyzing and mining the database.
4. User-friendly web interface is developed to facilitate the browsing and analysis of the collected data.

miRFANs is freely available at: http://www.cassava-genome.cn/mirfans

• Liu H, Jin T, Liao R, Wan L, Xu B, Zhou S, Guan J. (2012) miRFANs: an integrated database for Arabidopsis thaliana microRNA function annotations. BMC Plant Biology [Epub ahead of print]. [abstract]

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A Team of researchers from Taiwan & Denmark have performed a comprehensive profiling of the RNA editome of a male Han Chinese individual based on analysis of ~767 million sequencing reads from poly(A)⁺, poly(A)⁻ and small RNA samples.

• Developed a computational pipeline that carefully controls for false positives while calling RNA editing events from genome and whole-transcriptome data of the same individual.

• Identified 22,688 RNA editing events in noncoding genes and introns, untranslated regions and coding sequences of protein-coding genes. Most changes (~93%) converted A to I(G), consistent with known editing mechanisms based on adenosine deaminase acting on RNA (ADAR).

• Found evidence of other types of nucleotide changes; however, these were validated at lower rates.

• Found 44 editing sites in microRNAs (miRNAs), suggesting a potential link between RNA editing and miRNA-mediated regulation.

This approach facilitates large-scale studies to profile and compare editomes across a wide range of samples.

• Peng Z, Cheng Y, Tan BC, Kang L, Tian Z, Zhu Y, Zhang W, Liang Y, Hu X, Tan X, Guo J, Dong Z, Liang Y, Bao L,Wang J. (2012) Comprehensive analysis of RNA-Seq data reveals extensive RNA editing in a human transcriptome. Nature Biotech [Epub ahead of print]. [abstract]

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Despite accumulating data on animal and plant microRNAs and their functions, existing public miRNA resources usually collect miRNAs from a very limited number of species. A lot of microRNAs, including those from model organisms, remain undiscovered. As a result there is a continuous need to search for new microRNAs.

Izabela Makałowska’s Laboratory of Evolutionary Genomics at The Adam Mickiewicz University in Poznan just published miRNEST, a comprehensive database of animal, plant and virus microRNAs. The core part of the database is built from the author’s miRNA predictions conducted on Expressed Sequence Tags of 225 animal and 202 plant species. The miRNA search was performed based on sequence similarity and as many as 10 004 miRNA candidates in 221 animal and 199 plant species were discovered. Out of them only 299 have already been deposited in miRBase. Additionally, miRNEST has been integrated with external miRNA data from literature and 13 databases, which includes miRNA sequences, small RNA sequencing data, expression, polymorphisms and targets data as well as links to external miRNA resources, whenever applicable. All this makes miRNEST a considerable miRNA resource in a sense of number of species (544) that integrates a scattered miRNA data into a uniform format with a user-friendly web interface.

miRNEST: http://mirnest.amu.edu.pl

Szczesniak MW, Deorowicz S, Gapski J, Kaczynski L, Makalowska I. (2011) miRNEST database: an integrative approach in microRNA search and annotation. Nucleic Acids Res [Epub ahead of print]. [article]

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RNA-Seq reveals plant microRNAs regulating expression in mammals

from The Scientist

Chen-Yu Zhang, a molecular biologist at Nanjing University in China, hypothesized that exogenous microRNAs, such as those ingested through the consumption of milk, could also be found circulating in the serum of mammals. To test this idea, Zhang and his team of researchers sequenced the blood microRNAs of 31 healthy human subjects and searched for the presence of plant microRNAs. Because plant microRNAs are structurally different from those of mammals, they react differently to oxidizing agents, and the researchers were able to differentiate the two by treating them with sodium periodate, which oxidizes mammal but not plant microRNAs.

To their surprise, they found about 40 types of plant microRNAs circulating in the subjects’ blood—some of which were found in concentrations that were comparable to major endogenous human microRNAs—and that these exogenous plant microRNAs are primarily acquired orally, through food intake.

(Read more…)

L. Zhang, et. al. (2011) Exogenous plant MIR168a specifically targets mammalian LDLRAP1: evidence of cross-kingdom regulation by microRNA. Cell Research [Epub ahead of print]. [abstract]

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MicroRNAs (miRNAs), small non-coding RNAs of 19 to 25 nt, play important roles in gene regulation in both animals and plants.

Expression profiling by microarray is one high-throughput and robust method for detecting miRNA expression, however, the approach is restricted to detecting the expression of known miRNAs. RNA-Seq is a promising new method with high sensitivity and specificity and can be used not only to measure the abundance of small-RNA sequences in a sample but also to discover novel miRNAs.

miRExpress is a stand-alone software package is implemented for generating miRNA expression profiles from high-throughput sequencing of RNA without the need for sequenced genomes. The software is also a database-supported, efficient and flexible tool for investigating miRNA regulation.

The software is freely available at: http://mirexpress.mbc.nctu.edu.tw/Download.php

• Wang, W.C., et al., (2009) miRExpress: Analyzing high-throughput sequencing data for profiling microRNA expression. BMC Bioinformatics 10(1), 328. [article]

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The capacity of highly parallel sequencing technologies to detect small RNAs at unprecedented depth suggests their value in systematically identifying microRNAs (miRNAs). However, the identification of miRNAs from the large pool of sequenced transcripts from a single deep sequencing run remains a major challenge.

Here, the authors present an algorithm, miRDeep, which uses a probabilistic model of miRNA biogenesis to score compatibility of the position and frequency of sequenced RNA with the secondary structure of the miRNA precursor.

The miRDeep package was developed to discover active known or novel miRNAs from deep sequencing data (Solexa/Illumina, 454, …). The package consists of everything you need to analyze your own deep sequencing data after removal of ligation adapters: a number of scripts to preprocess the mapped data, and the core miRDeep algorithm that will analyze and score these data.

They demonstrate its accuracy and robustness using published Caenorhabditis elegans data and data they generated by deep sequencing human and dog RNAs. miRDeep reports altogether approximately 230 previously unannotated miRNAs, of which four novel C. elegans miRNAs are validated by northern blot analysis.

miRDeep is freely available at: http://www.mdc-berlin.de/en/research/research_teams/systems_biology_of_gene_regulatory_elements/projects/miRDeep/index.html

Friedländer MR, Chen W, Adamidi C, Maaskola J, Einspanier R, Knespel S, Rajewsky N. (2008) Discovering microRNAs from deep sequencing data using miRDeep. Nat Biotechnol 26(4), 407-15. [abstract]

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Small non-coding RNAs (ncRNAs) such as microRNAs, snoRNAs and tRNAs are a diverse collection of molecules with several important biological functions. Current methods for high-throughput sequencing for the first time offer the opportunity to investigate the entire ncRNAome in an essentially unbiased way. However, there is a substantial need for methods that allow a convenient analysis of these overwhelmingly large data sets.

Exploring small RNA biology or characterizing differential expression profiles by sequencing and comparing small RNA transcriptomes is also an exciting possibility to get more and deeper information about the world of non-coding RNAs (ncRNAs).

DARIO is a free web service that allows to study short read data from small RNA-seq experiments. It provides a wide range of analysis features, including quality control, read normalization, ncRNA quantification and prediction of putative ncRNA candidates.

The DARIO web site can be accessed at http://dario.bioinf.uni-leipzig.de/.

Fasold M, Langenberger D, Binder H, Stadler PF, Hoffmann S. (2011) DARIO: a ncRNA detection and analysis tool for next-generation sequencing experiments. Nucleic Acids Res [Epub ahead of print]. [article]

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Computational prediction of microRNA targets remains a challenging problem. The existing rule-based, data-driven and expression profiling approaches to target prediction are mostly approached from the gene-level. The advent of next-generation sequencing technologies provides new opportunities to profile transcriptomes and microRNA targetomes at base-wise resolution and provides a new perspective for microRNA target prediction on the isoform-level.  We hypothesize that the splicing isoform is the ultimate effector in microRNA targeting and that with the use of gene-structure information derived from the RNA-seq data to assess isoform specific microRNA regulation it is possible to predict non-dominant isoform targets as well as their targeting regions that are otherwise invisible to many existing approaches.

Deng N, Puetter A, Zhang K, Johnson K, Zhao Z, Taylor C, Flemington EK, Zhu D. (2011) Isoform-level microRNA-155 target prediction using RNA-seq. Nucleic Acids Res {Epub ahead of print]. [article]

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MicroRNAs (miRNAs) are key regulators of gene expression and contribute to a variety of biological processes including cell growth, differentiation, and development. Abnormal microRNA expression has been reported in various diseases including various cancers, cardiovascular disease, and neurological disorders. Therefore microRNAs are considered to be promising diagnostic and therapeutic candidates for the treatment of human disease.

The miRBase sequence database, is the public repository for all known microRNAs. Newly discovered microRNAs are routinely added and it has grown rapidly with approximately >10,000 entries to date. Despite this rapid growth, many miRNAs have not yet been validated, and many believe there are numerous microRNAs yet to be identified. A lack of a full complement of miRNAs has imposed limitations on recognizing their important roles in development and disease.

Now researchers are using the latest in deep sequencing technology along with advanced bioinformatics packages to identify novel microRNAs in various tissue types and species.

• Ryu S, Joshi N, McDonnell K, Woo J, Choi H, et al. (2011) Discovery of Novel Human Breast Cancer MicroRNAs from Deep Sequencing Data by Analysis of Pri-MicroRNA Secondary Structures. PLoS ONE 6(2), e16403. [article]
• Xie SS, Li XY, Liu T, Cao JH, Zhong Q, Zhao SH. (2011) Discovery of Porcine microRNAs in Multiple Tissues by a Solexa Deep Sequencing Approach. PLoS One 6(1), e16235. [article]
• Creighton CJ, Benham AL, Zhu H, Khan MF, Reid JG, Nagaraja AK, Fountain MD, Dziadek O, Han D, Ma L, Kim J, Hawkins SM, Anderson ML, Matzuk MM, Gunaratne PH. (2010) Discovery of novel microRNAs in female reproductive tract using next generation sequencing. PLoS One 5(3), e9637. [article]
• Huang QX, Cheng XY, Mao ZC, Wang YS, Zhao LL, Yan X, Ferris VR, Xu RM, Xie BY. (2010) MicroRNA discovery and analysis of pinewood nematode (Bursaphelenchus xylophilus) by deep sequencing. PLoS One 5(10), e13271. [article]
• Song C, Wang C, Zhang C, Korir NK, Yu H, Ma Z, Fang J. (2010) Deep sequencing discovery of novel and conserved microRNAs in trifoliate orange (Citrus trifoliata). BMC Genomics 11, 431. [article]
• Zhao CZ, Xia H, Frazier TP, Yao YY, Bi YP, Li AQ, Li MJ, Li CS, Zhang BH, Wang XJ. (2010) Deep sequencing identifies novel and conserved microRNAs in peanuts (Arachis hypogaea L.). BMC Plant Biol 10, 3. [article]

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