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The development of a cost-efficient eQTL scanning strategy to unravel the broad transcriptional response of a generalist pest to novel hosts. (3G006720)

Finding genetic variants that explain transcriptional variation underlying phenotypes of interest is of major relevance for the biological sciences However, state-of-the-art methods to comprehensively scan for such expression - quantitative trait loci (eQTLs) throughout the genome are prohibitively expensive for common applications Here, we propose to develop a novel strategy that is based on statistically modelling allele-specific RNA-seq data for eQTLs, which leads to more power and less artefacts compared to the state-of-the-art methods, ensuring superior cost-efficiency To demonstrate the benefits, we will apply the novel methodology on RNA-seq data of the spider mite Tetranychus urticae T urticae is a common crop pest species notorious for rapidly developing resistance to pesticides as well as adapting to new hosts, yet the mechanism explaining its fast transcriptional response and adaptation towards new toxins/hosts remains elusive By (i) scanning for eQTLs in progeny of randomly mixed field populations of different hosts, and (ii) associating the eQTL genotypes with the progeny's phenotypic response to transfer to a complex host, we aim at identifying those eQTLs explaining the successful transcriptional response to new hosts If successful, this research will contribute to the potential use of genetic eQTL testing of T urticae and, by extent, other generalist pests, in the field

Date:1 Jan 2020  →  Today
Keywords:statistical transcriptomics, expression-quantitative trait loci (eQTL), Applied genetics
Disciplines:Agricultural plant protection, Transcriptomics, Development of bioinformatics software, tools and databases