HyLiTE: accurate and flexible analysis of gene expression in hybrid and allopolyploid species.
HyLiTE: accurate and flexible analysis of gene expression in hybrid and allopolyploid species.
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DOI：
10.1186/s12859-014-0433-8
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发表时间：
2015-01-16
影响因子：
3
通讯作者：
Cox MP
中科院分区：
文献类型：
--
作者：
Duchemin W;Dupont PY;Campbell MA;Ganley AR;Cox MP
通过合并两个或更多不同的亲本物种来形成一个新物种越来越被视为许多生物系统进化中的一个关键现象。然而，关于双亲基因拷贝(同源基因)在基因组合并后的表达如何反应，人们知之甚少。高通量RNA测序现在使这种分析在技术上是可行的，但确定同源基因表达的工具仍处于初级阶段。在这里，我们提出了HyLiTE-一种单步分析，直接从原始的mRNA序列文件中获得杂交或异源多倍体及其亲本物种的同源基因表达表。通过实现诊断亲本多态的即时检测，HyLiTE可以同时执行SNP调用和读取分类，从而允许HyLiTE作为并行代码运行。HyLiTE支持任意数量的亲本物种、多个数据源(包括基因组DNA读取以改进SNP检测)，并实施了针对低到中等表达的基因进行优化的统计框架。HyLiTE是一个灵活且易于使用的程序，专为普通生物学家设计，用于探索基因组合并后的基因表达模式。与人工方法和现有程序相比，HyLiTE提供了实用的优势，旨在适应广泛的基因组合并系统，可以识别基因组合并后出现的SNP，并在非模式生物上提供准确的性能。本文的在线版本(doi：10.1186/s12859-0140433-8)包含补充材料，授权用户可以使用。
Forming a new species through the merger of two or more divergent parent species is increasingly seen as a key phenomenon in the evolution of many biological systems. However, little is known about how expression of parental gene copies (homeologs) responds following genome merger. High throughput RNA sequencing now makes this analysis technically feasible, but tools to determine homeolog expression are still in their infancy. Here we present HyLiTE – a single-step analysis to obtain tables of homeolog expression in a hybrid or allopolyploid and its parent species directly from raw mRNA sequence files. By implementing on-the-fly detection of diagnostic parental polymorphisms, HyLiTE can perform SNP calling and read classification simultaneously, thus allowing HyLiTE to be run as parallelized code. HyLiTE accommodates any number of parent species, multiple data sources (including genomic DNA reads to improve SNP detection), and implements a statistical framework optimized for genes with low to moderate expression. HyLiTE is a flexible and easy-to-use program designed for bench biologists to explore patterns of gene expression following genome merger. HyLiTE offers practical advantages over manual methods and existing programs, has been designed to accommodate a wide range of genome merger systems, can identify SNPs that arose following genome merger, and offers accurate performance on non-model organisms. The online version of this article (doi:10.1186/s12859-014-0433-8) contains supplementary material, which is available to authorized users.
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DOI：
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