HyLiTE: accurate and flexible analysis of gene expression in hybrid and allopolyploid species

BMC Bioinformatics

Murray P Cox²  Austen RD Ganley³  Matthew A Campbell²  Pierre-Yves Dupont²  Wandrille Duchemin¹ 

[1]Present address: Laboratoire de Biométrie et Biologie Évolutive, UMR CNRS 5558, Université Lyon I, Villeurbanne F-69622, France

[2]Statistics and Bioinformatics Group, Institute of Fundamental Sciences, Massey University, Palmerston North, New Zealand

[3]Institute of Mathematical and Natural Sciences, Massey University, Auckland, New Zealand

关键词: Read assignment;    RNA-seq;    Homeolog;    Allopolyploid;    Hybrid;   

Others  :  1089016
DOI  :  10.1186/s12859-014-0433-8

 received in 2014-06-27, accepted in 2014-12-16,  发布年份 2015

【 摘 要 】

Background

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.

Results

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.

Conclusions

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.

【 授权许可】

   
2015 Duchemin et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

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