Suppr超能文献

利用转录组数据的系统发育基因组学

Phylogenomics Using Transcriptome Data.

作者信息

Cannon Johanna Taylor, Kocot Kevin Michael

机构信息

Department of Zoology, Naturhistoriska Riksmuseet, 50007, SE-104 05, Stockholm, Sweden.

Department of Biological Sciences and Alabama Museum of Natural History, The University of Alabama, 307 Mary Harmon Bryant Hall, Tuscaloosa, AL, 35487, USA.

出版信息

Methods Mol Biol. 2016;1452:65-80. doi: 10.1007/978-1-4939-3774-5_4.

Abstract

This chapter presents a generalized protocol for conducting phylogenetic analyses using large-scale molecular datasets, specifically using transcriptome data from the Illumina sequencing platform. The general molecular lab bench protocol consists of RNA extraction, cDNA synthesis, and sequencing, in this case via Illumina. After sequences have been obtained, bioinformatics methods are used to assemble raw reads, identify coding regions, and categorize sequences from different species into groups of orthologous genes (OGs). The specific OGs to be used for phylogenetic inference are selected using a custom shell script. Finally, the selected orthologous groups are concatenated into a supermatrix. Generalized methods for phylogenomic inference using maximum likelihood and Bayesian inference software are presented.

摘要

本章介绍了一种使用大规模分子数据集进行系统发育分析的通用方案,具体是使用来自Illumina测序平台的转录组数据。一般的分子实验室操作方案包括RNA提取、cDNA合成和测序,在这种情况下是通过Illumina进行测序。获得序列后,使用生物信息学方法组装原始读数、识别编码区域,并将来自不同物种的序列分类为直系同源基因(OG)组。使用自定义的Shell脚本选择用于系统发育推断的特定OG。最后,将选定的直系同源组连接成一个超级矩阵。还介绍了使用最大似然法和贝叶斯推断软件进行系统发育基因组推断的通用方法。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验