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Identification of candidate genes and mutations in QTL regions for chicken growth using bioinformatic analysis of NGS and SNP-ChiP data

Ahsan, Muhammad; Li, Xidan; Lundberg, Andreas E; Kierczak, Marcin; Siegel, Paul B.; Carlborg, Örjan; Marklund, Stefan


Quantitative trait loci (QTL) mapping is a first step to identify chromosomal regions harboring genetic polymorphisms that regulate complex traits. Searching causative mutations for observed effects is sometimes a daunting task as even after fine mapping of the QTL, millions of base pairs including many genes will typically need to be explored. There is thus a great need for efficient bioinformatics strategies to trace the causative mutation(s). Here, we searched for gene transcripts along with mutations regulating body weight at 56 days traits in the Virginia chicken lines – an experimental population comprising two lines that have been divergently selected for 56 days body weight for more than 50 generations. Several QTL regions have been mapped in an F2 intercross between the lines, and the regions have subsequently been replicated and fine mapped using an Advanced Intercross Line (AIL). Candidate transcripts and mutations were here sought in the parts of the QTL regions where the highest genetic divergence between the High-Weight selected (HWS) and Low-Weight selected (LWS) lines was observed. Such regions, 47 Mbp or 35% of the actual QTL regions, were identified by comparing the allele frequencies in the genomes of the HWS and LWS lines using both individual 60K SNP chip genotyping of birds and analysis of read proportions with 12X ABI SOLID genome resequencing of DNA pools. Gene transcripts in the target segments, obtained using the Ensembl genome browser 67, were analyzed with DAVID bioinformatic database to investigate their role in any growth-related functions. Single nucleotide polymorphisms (SNPs) in target segments obtained from resequencing data were analyzed with Variant Effect Predictor (VEP) tool to find their location and functional consequences in gene transcripts. Non-synonymous SNPs (nsSNPs) were scored for their effects on protein function with PASE software (Li et al., submitted). Finally, we present most important candidate gene transcripts from each QTL segment for further functional validation. For example, the cysteine rich transmembrane BMP regulator 1 (chordin-like) gene has growth factor binding and cell growth functions. It carries a nsSNP with high allele frequency difference (0.97) between lines, PASE (0.67) and conservation scores (0.63). Another candidate, glucagon is involved in anorexia and appetite regulation carrying a CpG mutation with high allele frequency difference (0.87) between lines.

Published in

Title: Proceedings of the 9th International Symposium on Integrative Bioinformatics 2013

Publisher: Leibniz Institue of Plant Genetics and Crop Plant Research (IPK)