期刊文献+

昆虫RNA-Seq数据的分析流程 被引量:1

Insect RNA-Seq data analysis pipeline
原文传递
导出
摘要 随着高通量RNA测序(RNA-Seq)技术的发展和测序成本迅速下降,RNA-Seq技术已经成为生物学研究的重要工具,为生物学家全面地了解和研究转录组提供了机遇。高通量测序具有读长短、存在一定比例的测序错误、数据量大等特点,因此RNA-Seq数据分析与基因组分析和传统的EST数据分析有所不同。本文通过介绍不同的测序平台、原始数据产生和低质量数据过滤的计算流程,对短序列比对、转录组拼接、功能注释、以及差异表达分析进行了研究和分析,最后对RNA-Seq在昆虫学研究中的应用进行了综述,并对RNA-Seq技术进行了总结和展望。 With the rapid development of highthroughput RNA sequencing (RNASeq) technology and the rapidly decreasing cost of this method, RNASeq is becoming an important tool for biological research, especially investigating gene function at the transcriptome level. RNASeq typically reads sequences rapidly with a certain percentage of sequence errors and bias producing a huge amount of data. RNASeq data analysis faces lots of challenges. Here, we describe different RNA sequencing platforms, raw data generation processes and data filtering and introduce short sequence alignment, transcriptome assembly, functional annotation and gene expression analysis. Finally, we briefly review the application of RNASeq in insects. The prospects of RNASeq techniques and their application are also discussed.
出处 《应用昆虫学报》 CAS CSCD 北大核心 2013年第5期1458-1468,共11页 Chinese Journal of Applied Entomology
基金 国家自然科学基金(31171843) 国家高技术研究发展计划("863"计划)(2012AA101505)
关键词 高通量RNA测序 段序列比对 转录组拼接 基因功能注释 基因表达定量 基因差异表达 high-throughput RNA sequencing, short sequence alignment, transcriptome reconstruction, gene function annotation, gene expression quantification, gene differential expression
  • 相关文献

参考文献81

  • 1Ahschul SF, Gish W, Miller W, Myers EW, Lipman D J, 1990. Basic local alignment search tool. J. Mol. Biol. , 215(3) :403 -410. 被引量:1
  • 2Anders S, Huber W, 2010. Differential expression analysis for sequence count data. Genome Res. , 11 (10) :R106. 被引量:1
  • 3Au KF, Jiang H, Lin L, Xing Y, Wong WH, 2010. Detection of splice junctions from paired-end RNA-seq data by SpliceMap. Nucleic Acids Res. , 38(14):4570-4578. 被引量:1
  • 4Beissbarth T, Speed TP, 2004. GOstat: find statistically overrepresented Gene Ontologies within a group of genes. Bioinformatics, 20 ( 9 ) : 1464 - 1465. 被引量:1
  • 5Berger MF, Levin JZ, Vijayendran K, Sivaehenko A, Adiconis X, Maguire J, Johnson LA, Robinson J, Verhaak RG, Sougnez C, Onofrio RC, Ziaugra L, Cibulskis K, Laine E, Barretina J, Winckler W, Fisher DE, Getz G, Meyerson M, Jaffe DB, Gabriel SB, Lander ES, Dummer R, Gnirke A, Nusbaum C, Garraway LA, 2010. Integrative analysis of the melanoma transcriptome. Genome Res. , 20(4) :413 -427. 被引量:1
  • 6Black DL, 2003. Mechanisms of alternative pre-messenger RNA splicing. Annu. Rev. Biochem., 72:291-336. 被引量:1
  • 7Bonizzoni M, Dunn WA, Campbell CL, Olson KE, Dimon MT, Marinotti O, James AA, 2011. RNA-seq analyses of blood-induced changes in gene expression in the mosquito vector species, Aedes aegypti. BMC Genomics, 12:82. 被引量:1
  • 8Bullard JH, Purdom E, Hansen KD, Dudoit S, 2010. Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinformatics, 11:94. 被引量:1
  • 9Chen S, Yang P, Jiang F, Wei Y, Ma Z, Kang L, 2010. De novo analysis of transcriptome dynamics in the migratory locust during the development of phase traits. PLoS ONE, 5 (12) :e15633. 被引量:1
  • 10Cloonan N, Xu Q, Faulkner GJ, Taylor DF, Tang DT, KolleG, Grimmond SM, 2009. RNA-MATE :a recursive mapping strategy for high-throughput RNA-sequencing data. Bioinformatics, 25 (19) :2615 - 2616. 被引量:1

同被引文献4

引证文献1

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部