De novo identification, differential analysis and functional annotation of SNPs from RNA-seq data in non-model species

• DOI: 10.1101/035238
• Publication Date: 2015-12-25T06:12:18Z
• Authors: Hélène Lopez Maestre; Lilia Brinza; Camille Marchet; Janice Kielbassa; Sylvère Bastien; Mathilde Boutigny; David Monnin; Adil El Filali; Claudia Marcia Ca...; Cristina Vieira; Franck Picard; Natacha Kremer; Fabrice Vavre; Marie-France Sagot; Vincent Lacroix
• Keywords: RNA-Seq; Identification

Abstract SNPs (Single Nucleotide Polymorphisms) are genetic markers whose precise identification is a prerequisite for association studies. Methods to identify them currently well developed model species, but rely on the availability of (good) reference genome, and therefore cannot be applied non-model species. They also mostly tailored whole genome (re-)sequencing experiments, whereas in many cases, transcriptome sequencing can used as cheaper alternative which already enables located transcribed regions. In this paper, we propose method that identifies, quantifies annotates without any using RNA-seq data only. Individuals pooled prior sequencing, if not enough material available from one individual. Using human data, first compared performance our with G atk , established requires genome. We showed both methods predict similar accuracy. then validated experimentally predictions two The species annotate their impact proteins. further enable test identified phenotype interest.