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Doctoral thesis, 2014

Functional prediction of genetic variation within and between two chicken lines selected for body-weight

Li, Xidan

Abstract

Identifying genetic variation influencing complex traits is often a big challenge. Paul Siegel at the Virginia Polytechnic Institute and State University (USA) initiated a breeding experiment in the 1950s, where White Plymouth Rock (WPR) chicken lines were bi-directionally selected for body-weight at 56 days of age. After more than 50 generations of selection, the High Weight Selected (HWS) line is more than 10-fold bigger than the Low Weight Selected (LWS) line. These HWS and LWS lines have become a good model to investigate the genetic mechanisms underlying the body weight changes under long-term selection. Moreover, as a result of the recently rapid development of next generation sequencing technologies, with high throughput, a large number of genetics polymorphisms have been identified and can be used to explore the genetic factors underlying complex traits. In this thesis, we used NGS resequencing data and several leading databases to search for genes and mutations within previously mapped epistasic QTL regions, which could explain the differences in growth-related traits between the HWS and LWS lines. In consequence, a number of genetic factors have been detected and provide a good basis for further experimental investigation in relation to the observed effects on growth and other metabolic traits. Additionally, we also developed three softwares, which can be useful in the process of identifying genes and variations with phenotypic effects. One of these softwares were also applied within genetic studies in this thesis. Our softwares could be widely applied in many species and are likely to benefit many other research projects.

Keywords

NGS; SNP; amino acid substitution; chicken; body weight; protein motif; expression phenotype

Published in

Acta Universitatis Agriculturae Sueciae
2014, number: 2014:24
ISBN: 978-91-576-7996-3, eISBN: 978-91-576-7997-0
Publisher: Department of Clinical Sciences, Swedish University of Agricultural Sciences

Authors' information

Li, Xidan (Li, Xidan)
Swedish University of Agricultural Sciences, Department of Clinical Sciences

UKÄ Subject classification

Bioinformatics and Systems Biology
Clinical Science

URI (permanent link to this page)

https://res.slu.se/id/publ/52442