HyLiTE: accurate and flexible analysis of gene expression in hybrid and allopolyploid species. Issue 1 (December 2015)

• Record Type: Journal Article
• Authors: Duchemin, Wandrille; Dupont, Pierre-Yves; Campbell, Matthew; Ganley, Austen; Cox, Murray
• Is Part Of: BMC bioinformatics. Volume 16:Issue 1(2015)
• Page Start: 1
• Page End: 4
• Publication Date: 2015-12
• Subjects: Hybrid -- Allopolyploid -- Homeolog -- RNA-seq -- Read assignment; Bioinformatics -- Periodicals; Computational biology -- Periodicals; 570.285
• DOI: 10.1186/s12859-014-0433-8
• Languages: English
• ISSNs: 1471-2105

Abstract

Abstract 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.