Automatic Workflow for the Identification of Constitutively-Expressed Genes Based on Mapped NGS Reads

Abstract

Expression analyses such as quantitative and/or real-time PCR require the use of reference genes for normalization in order to obtain reliable assessments. The expression levels of these reference genes must remain constant in all different experimental conditions and/or tissues under study. Traditionally, housekeeping genes have been used for this purpose, but most of them have been reported to vary their expression levels under some experimental conditions. Consequently, the election of the best reference genes should be tested and validated in every experimental scenario. Microarray data are not always available for the search of appropriate reference genes, but NGS experiments are increasingly common. For this reason, an automatic workflow based on mapped NGS reads is presented with the aim of obtaining putative reference genes for a giving species in the experimental conditions of interest. The calculation of the coefficient of variation (CV) and a simple, normalized expression value such as RPKM per transcript allows for filtering and selecting those transcripts expressed homogeneously and consistently in all analyzed conditions. This workflow has been tested with Roche/454 reads obtained from olive (Olea europaea L.) pollen and pistil at different developmental stages, as well as with Illumina paired-end reads from two different accessions of Arabidopsis thaliana. Some of the putative candidate reference genes have been experimentally validated.