绵羊肌肉转录组的差异基因表达及新转录单元分析
Analysis of differential gene expression and novel transcript units of ovine muscle transcriptomes.
作者信息
Zhang Chunlan, Wang Guizhi, Wang Jianmin, Ji Zhibin, Dong Fei, Chao Tianle
机构信息
Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Taian, China ; College of Biological and Agricultural Engineering, Weifang University, Key Laboratory of Biochemistry and Molecular Biology in Universities of Shandong, Weifang, China.
Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University, Taian, China.
出版信息
PLoS One. 2014 Feb 26;9(2):e89817. doi: 10.1371/journal.pone.0089817. eCollection 2014.
In this study, we characterized differentially expressed genes (DEGs) between the muscle transcriptomes of Small-tailed Han sheep and Dorper sheep and predicted novel transcript units using high-throughput RNA sequencing technology. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that 1,300 DEGs were involved in cellular processes, metabolic pathways, and the actin cytoskeleton pathway. Importantly, we identified 34 DEGs related to muscle cell development and differentiation. Additionally, we were able to optimize the gene structure and predict the untranslated regions (UTRs) for some of the DEGs. Among the 123,678 novel predicted transcript units (TUs), 15,015 units were predicted protein sequences. The reliability of the sequencing data was verified through qRT-PCR analysis of 12 genes. These results will provide useful information for functional genetic research in the future.
在本研究中，我们利用高通量RNA测序技术对小尾寒羊和杜泊绵羊肌肉转录组之间的差异表达基因（DEGs）进行了表征，并预测了新的转录单元。基因本体论（GO）和京都基因与基因组百科全书（KEGG）分析表明，1300个DEGs参与了细胞过程、代谢途径和肌动蛋白细胞骨架途径。重要的是，我们鉴定出了34个与肌肉细胞发育和分化相关的DEGs。此外，我们能够优化某些DEGs的基因结构并预测其非翻译区（UTRs）。在123,678个新预测的转录单元（TUs）中，有15,015个单元预测有蛋白质序列。通过对12个基因的qRT-PCR分析验证了测序数据的可靠性。这些结果将为未来的功能基因研究提供有用信息。
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