Micro-Variations from RNA-seq Experiments for Non-model Organisms.

RNA-based high-throughput sequencing technologies provide a huge amount of reads from transcripts. In addition to expression analyses, transcriptome reconstruction, or isoform detection, they could be useful for detection of gene variations, in particular micro-variations (single nucleotide polymorphisms [SNPs] and indels). Gene variations are usually based on homogenous (one single individual) DNA-seq data, but this study aims the usage of heterogeneous (several individuals) RNA-seq data to obtain clues about gene variability of a population. Therefore, new algorithms or workflows are required to fill this gap, usually disregarded. Here it is presented an automated workflow based on existing software to predict micro-variations from RNA-seq data using a genome or a transcriptome as reference. It can deal with organism whose genome sequence is known and well-annotated, as well as non-model organism where only draft genomes or transcriptomes are available. Mapping is based on STAR in both cases. Micro-variation detection relies on GATK (combining Mutect2 and HaplotypeCaller) and VarScan since they are able to provide reliable results from RNA-seq reads. The workflow has been tested with reads from normal and diseased lung from patients having small-cell lung carcinoma. Human genome, as well as human transcriptome, were used as reference and then compared: from the initial 120 000 micro-variations, only 267 were predicted by at least two algorithm in the exome of patients. The workflow was tested in non-model organisms such as Senegalese sole, using its transcriptome as reference, to determine micro-variations in sole larvae exposed to different salinities. Therefore, the workflow seems to produce robust and reliable micro-variations in coding genes based on RNA-seq, irrespective of the nature of the reference sequence. We think that this paves the way to correlate micro-variations and differentially expressed genes in non-model organisms with the aim of foster breeding plans.