Mathematics
Te Tari Pāngarau me te Tatauranga
Department of Mathematics & Statistics
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Jie Kang

Studying for Doctor of Philosophy

Area of study:
Multi Allelic Genotyping-By-Sequencing (MA-GBS) to improve genomic selection models in forage

Supervisor: Phillip Wilcox


Email: kanji709@student.otago.ac.nz  


Thesis

Title: Multi Allelic Genotyping-By-Sequencing (MA-GBS) to improve genomic selection models in forage

Supervisors: Phillip Wilcox, Ken Dodds (AgResearch), Dan Milbourne (Teagasc) and Mik Black

Previous Degrees:

  • BSc(Hons) Statistics (Otago)

Past studies demonstrated promising potential of selective breeding in livestock and plants, for instance, marker-assisted selection (MAS) is often employed to accelerate the genetic gain. More recently, Hayes et al. (2001) introduced genomic selection (GS) methods, which use genetic markers covering the whole genome to achieve that all quantitative trait locus (QTL) are in linkage disequilibrium (LD) with one or more makers. Compared with traditional marker-assisted selection, GS generally overcame the drawback where the QTLs can be in linkage equilibrium with the markers used in MAS (Goddard and Hayes, 2007; Bernardo, 2008). Due to latest advances in genetic markers, the cost of genotyping assays have greatly reduced through methods such as Genotyping-by-Sequencing (Schaeffer, 2006; Jannink et al., 2010). Genotyping-by-Sequencing (GBS), first proposed by Elshire et al. (2011), is especially practicable and cost-effective for those species with high genetic diversity, e.g. perennial ryegrass (Lolium perenne L.). As one of the most important pasture and forage plant species in Ireland and New Zealand, perennial ryegrass plays a crucial role in the development of the agricultural sector. From the statistical prospective, improving the prediction accuracy of GS with the application in perennial ryegrass is also a challenging and constructive area.