Literature DB >> 19406225

In silico detection and characteristics of novel microRNA genes in the Equus caballus genome using an integrated ab initio and comparative genomic approach.

Meng Zhou1, Qianghu Wang, Jie Sun, Xia Li, Liangde Xu, Haixiu Yang, Hongbo Shi, Shangwei Ning, Li Chen, Yan Li, Taotao He, Yan Zheng.   

Abstract

The importance of microRNAs at the post-transcriptional regulation level has recently been recognized in both animals and plants. We used the simple but effective sequential method of first Blasting known animal miRNAs against the horse genome and then using the located candidates to search for novel miRNAs by RNA folding method in the vicinity (+ -500 bp) of the candidates. Here, a total of 407 novel horse miRNA genes including 354 mature miRNAs were identified, of these, 75 miRNAs were grouped into 32 families based on seed sequence identity. MiRNA genes tend to be present as clusters in some chromosomes, and 146 miRNA genes accounted for 36% of the total were observed as part of polycistronic transcripts. Detailed analysis of sequence characteristics in novel horse and all previous known animal miRNAs were carried out. Our study will provide a reference point for further study on miRNAs identification in animals and improve the understanding of genome in horse.

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Year:  2009        PMID: 19406225     DOI: 10.1016/j.ygeno.2009.04.006

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  18 in total

1.  Systematic analysis of genomic organization and heterogeneities of miRNA cluster in vertebrates.

Authors:  Jie Sun; Hai-Ping Liu; Jia-En Deng; Meng Zhou
Journal:  Mol Biol Rep       Date:  2011-12-11       Impact factor: 2.316

2.  An integrative bioinformatics pipeline for the genomewide identification of novel porcine microRNA genes.

Authors:  Wei Fang; Na Zhou; Dengyun Li; Zhigang Chen; Pengfei Jiang; Deli Zhang
Journal:  J Genet       Date:  2013-12       Impact factor: 1.166

3.  Cloning and characterization of Bubaline mammary miRNAs: An in silico approach.

Authors:  Krishnadeo Ankush Khade; Manjit Panigrahi; Sheikh Firdous Ahmad; Anuj Chauhan; Pushpendra Kumar; Bharat Bhushan
Journal:  Mol Biol Rep       Date:  2019-02-20       Impact factor: 2.316

4.  Computational identification and characterization of novel microRNA in the mammary gland of dairy goat (Capra hircus).

Authors:  Bo Qu; Youwen Qiu; Zhen Zhen; Feng Zhao; Chunmei Wang; Yingjun Cui; Qizhang Li; Li Zhang
Journal:  J Genet       Date:  2016-09       Impact factor: 1.166

Review 5.  RNA sequencing as a powerful tool in searching for genes influencing health and performance traits of horses.

Authors:  Monika Stefaniuk; Katarzyna Ropka-Molik
Journal:  J Appl Genet       Date:  2015-10-07       Impact factor: 3.240

6.  A genome-wide SNP-association study confirms a sequence variant (g.66493737C>T) in the equine myostatin (MSTN) gene as the most powerful predictor of optimum racing distance for Thoroughbred racehorses.

Authors:  Emmeline W Hill; Beatrice A McGivney; Jingjing Gu; Ronan Whiston; David E Machugh
Journal:  BMC Genomics       Date:  2010-10-11       Impact factor: 3.969

7.  Origin and evolution of a placental-specific microRNA family in the human genome.

Authors:  Zhidong Yuan; Xiao Sun; Dongke Jiang; Yan Ding; Zhiyuan Lu; Lejun Gong; Hongde Liu; Jianming Xie
Journal:  BMC Evol Biol       Date:  2010-11-10       Impact factor: 3.260

8.  Stallion sperm transcriptome comprises functionally coherent coding and regulatory RNAs as revealed by microarray analysis and RNA-seq.

Authors:  Pranab J Das; Fiona McCarthy; Monika Vishnoi; Nandina Paria; Cathy Gresham; Gang Li; Priyanka Kachroo; A Kendrick Sudderth; Sheila Teague; Charles C Love; Dickson D Varner; Bhanu P Chowdhary; Terje Raudsepp
Journal:  PLoS One       Date:  2013-02-11       Impact factor: 3.240

9.  Identification and characterization of microRNAs in normal equine tissues by Next Generation Sequencing.

Authors:  Myung-Chul Kim; Seung-Woo Lee; Doug-Young Ryu; Feng-Ji Cui; Jong Bhak; Yongbaek Kim
Journal:  PLoS One       Date:  2014-04-02       Impact factor: 3.240

10.  Identification of novel microRNAs in primates by using the synteny information and small RNA deep sequencing data.

Authors:  Zhidong Yuan; Hongde Liu; Yumin Nie; Suping Ding; Mingli Yan; Shuhua Tan; Yuanchang Jin; Xiao Sun
Journal:  Int J Mol Sci       Date:  2013-10-16       Impact factor: 5.923

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