Differential expression analysis of cold tolerance adaptation in D. buzzatii by RNA-seq de novo approach

HASSON ESTEBAN; MOREYRA NICOLÁS; HURTADO JUAN; MENSCH JULIÁN

Bahia Blanca

Conferencia; VI Argentinian Conference on Bioinformatics and Computational Biology; 2015

CAB2C

BackgroundMany traits and biological processes can be affected by climatic changes and genetic variation has a major role in the ecological adaptation to thermal changes during development steps. Adaptation to these kinds of environments appears to involve a set of traits related to reproduction, stress resistance and metabolic processes. We have performed a RNA-seq analysis in Drosophila buzzatii to investigate profiles of gene expression changes during female reproductive diapause.Materials and methodsThe study was conducted by explosing sets of females to three different conditions of temperatures. Two conditions were controls with little differences between each other (named J25 and C) and the third condition implied the measure of cold tolerance (named D ? diapause state). We run all treatments and replicates simultaneously.We used the Trinity package software to generate a de novo RNA-seq assembly from ~100 paired-end Illumina reads. Next, we mapped reads and Trinity transcripts to a reference genome (obtained from Flybase) guided by the Trinity protocol [3]. To analyze expression levels of the Trinity-reconstructed transcripts, we aligned the RNA-seq reads data against the contigs (Trinity transcripts), and then estimated the number of RNA-seq fragments that had mapped to each contig. Taking into account the skew generated for the different transcripts proportions in each sample, we applied the TMM normalization method to generate the normalized FPKM expression values separately for each sample and therefore to get the differences in RNA composition. Thereby, we extracted transcripts that were at least 6.25-fold differentially expressed at a significance of 0.001(FDR) in any of the sample comparisons. A transcripts cluster dendrogram was created based on expression profiles. From these, we selected only two clusters involving overexpressed and underexpressed genes in diapause relative to other treatments.ResultsWe found 87 transcript differentially expressed into two clusters. All transcripts were blasted against genome assembly, annotated genes and non-redundant databases (Flybase and NCBI). The most relevant transcripts exhibited high identity to chorion protein coding genes of D. melanogaster, Vitelline membrane cysteine-rich domains, Heat Shock Protein (HSP) coding genes and critical respiratory chain genes of the mitochondrial genome (D. mojavensis).ConclusionsAll CDS were consistent with the initial hypothesis and therefore, for the near future, we propose a validation by the Real-Time PCR (qPCR) method. In addition, examine the data set to find overexpressed genes across conditions will allow us to determine which regions of the transcriptome preferentially participate depending on the environmental temperature.