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基于转录组测序的长吻鮠转录组分析

Transcriptome Analysis of Chinese Longsnout Catfish Leiocassis Longirostris Based on Transcriptome Sequencing

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【作者】 徐慧敏巨丹丹龚兵肖明松

【Author】 XU Huimin;JU Dandan;GONG Bing;XIAO Mingsong;College of Animal Science, Anhui Science and Technology University;

【通讯作者】 肖明松;

【机构】 安徽科技学院动物科学学院

【摘要】 目的:长吻鮠是我国特有的淡水名贵经济鱼类,通过转录组测序技术发掘其功能基因,提高其优良性状。方法:采用Illumina测序平台对长吻鮠肌肉组织进行转录组测序。结果:利用Trinity软件对所得clean data进行从头组装,共得到44 153条unigene,序列长度为201~44 153 bp,平均长度为1 394 bp。Unigene功能注释显示,NR注释率为53.75%,Pfam注释率为34.46%,KEGG注释率为28.59%,String注释率为27.98%,Swiss-Prot注释率为37.82%,其中有23 731条序列在NR数据库中得到注释。将获得的12 939条Unigene与GO数据库进行分析,可划分为细胞组分、分子功能和生物学过程3个大类;在KEGG数据库中则注释到5大类34小类中,有机过程中的功能预测的较多,有4 562条。结论:本研究成果丰富了长吻鮠的基因遗传资源,可为长吻鮠生物学研究提供基础数据。

【Abstract】 Objective: Chinese longsnout catfish Leiocassis Longirostris has become an important economic freshwater fishes with great market demand and high price in China. To improve its excellent characters, the functional genes of L. Longirostris were explored. Methods: The transcriptome of six L. Longirostris muscles were sequenced using Illumina sequencing platform. Results: After de novo assembly of the obtained clean data by Trinity software, 44 153 unigene were assembled, with a sequence length of 201-44 153 bp and an average length of 1 394 bp. Unigene functional annotation showed that NR annotation rate was 53.75%, PFAM annotation rate was 34.46%, KEGG annotation rate was 28.59%, STRING annotation rate was 27.98%, and Swiss-Prot annotation rate was 37.82%. Among them, 23 731 sequences were annotated in NR database. Based on the analysis of 12 939 unigene and GO database, which can be divided into three categories: cell components, molecular functions and biological processes. In KEGG database, it is annotated into 5 categories and 34 sub categories, of which 4 562 functions are predicted in organic process. Conclusion: The results of this study enrich the genetic resources of L. Longirostris and provide basic data for the biological research of L. Longirostris.

【基金】 安徽省高校自然科学研究重大项目(KJ2019ZD59);安徽省重点研究与开发计划项目(1804a07020119);安徽省水产产业技术体系(2021)
  • 【文献出处】 安徽科技学院学报 ,Journal of Anhui Science and Technology University , 编辑部邮箱 ,2022年05期
  • 【分类号】S917.4
  • 【下载频次】40
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