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| In silico Detection of Novel MicroRNAs Genes in Soybean Genome |
| LIU Yong-xin, CHANG Wei, HAN Ying-peng, ZOU Quan, GUO Mao-zu , LI Wen-bin |
1. Key Laboratory of Soybean Biology, Chinese Ministry of Education/Soybean Research Institute
2. School of Information Science and Technology, Xiamen University
3. Department of Computer Science and Technology, Harbin Institute of Technology |
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摘要 The importance of microRNAs (miRNAs) at the post-transcriptional regulation level has recently been recognized in bothanimals and plants. In this study, the simple and most effective method of comparative genomic approach was used. Firstknown plants miRNAs BLAST against the soybean genome, and then the located candidates were searched for novelmiRNAs by RNA folding method in the vicinity (±400 nt) of the candidates. The results showed that a total of 521 novelsoybean miRNA genes, including 236 mature miRNAs, were identified. All these mature miRNAs were grouped into 58families, of which 21 of them were novel family in soybean. The upstream 2 000 nt of potential pre-miRNAs was used forpromoter prediction, in order to investigate prediction of miRNAs and detect transcript unit and clustering. In this study,miRNA genes less tend to be present as clusters in soybean. Only 9 clusters, containing 21 miRNA genes (accounted for4.0% of the total), were observed as part of polycistronic transcripts. Detailed analysis of sequence characteristics ofnovel miRNAs in soybean and all previous known plants miRNAs, were carried out. These results of this study providea reference point for further study on miRNAs identification in plants, and improve the understanding of genome insoybean.
Abstract The importance of microRNAs (miRNAs) at the post-transcriptional regulation level has recently been recognized in bothanimals and plants. In this study, the simple and most effective method of comparative genomic approach was used. Firstknown plants miRNAs BLAST against the soybean genome, and then the located candidates were searched for novelmiRNAs by RNA folding method in the vicinity (±400 nt) of the candidates. The results showed that a total of 521 novelsoybean miRNA genes, including 236 mature miRNAs, were identified. All these mature miRNAs were grouped into 58families, of which 21 of them were novel family in soybean. The upstream 2 000 nt of potential pre-miRNAs was used forpromoter prediction, in order to investigate prediction of miRNAs and detect transcript unit and clustering. In this study,miRNA genes less tend to be present as clusters in soybean. Only 9 clusters, containing 21 miRNA genes (accounted for4.0% of the total), were observed as part of polycistronic transcripts. Detailed analysis of sequence characteristics ofnovel miRNAs in soybean and all previous known plants miRNAs, were carried out. These results of this study providea reference point for further study on miRNAs identification in plants, and improve the understanding of genome insoybean.
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Received: 25 October 2011
Accepted:
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| Fund: This study was financially supported by the NationalHigh-Tech R&D Program of China (863 Program,2006AA100104-4), the 948 Project, Ministry ofAgriculture, China (2006-G5), the National NaturalScience Foundation of China (30971810, 60932008),the National Basic Research Program of China (973Program, 2009CB118400), the National GeneticallyModified Organisms Breeding Major Projects of China(2009ZX08009-088B), the Postdoctoral Fund inHeilongjiang Province, China (LBH-Z07228), the TechnologyProject of Ministry of Education, HeilongjiangProvince, China (11541025), and the TechnologyProject of Harbin, China (2009RFQXN085). |
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Corresponding Authors:
Correspondence LI Wen-bin, Professor, Tel: +86-451-55190778, Fax: +86-451-55103336, E-mail: wenbinli@neau.edu.cn
E-mail: wenbinli@neau.edu.cn
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| About author: LIU Yong-xin, MSc, E-mail: woodcorpse@163.com |
Cite this article:
LIU Yong-xin, CHANG Wei, HAN Ying-peng, ZOU Quan, GUO Mao-zu , LI Wen-bin.
2011.
In silico Detection of Novel MicroRNAs Genes in Soybean Genome. Journal of Integrative Agriculture, 10(9): 1336-1345.
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