Genome wide association study (GWAS) and genomic selection are important tools for detection of causal genes and genetic improvement in livestock. An efficient approach to increase power of GWAS and accuracy of genomic selection is to use the data combining different populations. In such situation, G by E interaction should be taken into consideration. The objectives of Xiujin’s PhD project were to perform GWAS and genomic prediction in multiple populations, and to investigate interaction between genotypes and production environments in different countries. The results lead to the following conclusions. 1) Prediction reliabilities for Brazilian Holsteins can be increased by adding Nordic and French genotyped bulls into the data, and there exists a large interaction between genotypes and environments of Brazilian and Nordic (or Nordic and French) populations. 2) Combining data from Chinese and Danish Holstein populations increases the power of GWAS, detects some new QTL regions for milk fatty acid traits, compared with analysis based on a single population alone, and 56 SNP show significantly different effects between the two populations. 3) The novel multi-trait Bayesian model efficiently estimates region-specific genomic variances, covariances and correlations between Chinese and Nordic Holstein populations. Although overall correlation between the two populations are highly positive,  some genome regions shows highly negative genomic correlations for milk yield and fat yield, which are helpful for understanding interaction of genotypes and environments in the two populations.

The PhD degree was completed at the Department of Animal science and Technology, China Agriculture University, and Center for Genetics and Genomics, Department of Molecular Biology and Genetic, Aarhus University.

This résumé is prepared by the PhD student.

Time: Monday, 30 November 2015 at 10:00
Place: Conference room 4, Department of Animal science and Technology, China Agriculture University
Title of dissertation: Methods to improve genomic prediction and GWAS using combined Holstein populations
Contact information: Xiujin Li, e-mail: xiujin.li@mbg.au.dk, tel.: +86 15801564659
Members of the assessment committee:
Professor Georg Thaller, InstitutfürTierzucht und Tierhaltung, Christian-Albrechts-University Kiel, Germany
Professor Ning Yang, Department of Animal science and Technology, China Agriculture University, China
Professor Yan Fu, College of Animal Science, University of Zhejiang, China
Professor Yuchun Pan, School of Agriculture and Biology, Shanghai Jiao Tong University, China
Professor Just Jensen (chair), Department of Molecular Biology and Genetics, Aarhus University
Main supervisor:
Professor Qin Zhang, Department of Animal Science and Technology, China Agriculture University
Senior researcher Guosheng Su, Department of Molecular Biology and Genetics, Aarhus University
Co-supervisor:
Professor Mogens Sandø Lund, Department of Molecular Biology and Genetics, Aarhus University
Associate professor Xiangdong Ding, Department of Animal Science and Technology, China Agriculture University
Language: The PhD dissertation will be defended in English.