Degree Type

Dissertation

Date of Award

2012

Degree Name

Doctor of Philosophy

Department

Agronomy

First Advisor

William D Beavis

Second Advisor

Paul Scott

Abstract

This dissertation explored genomewide association study (GWAS) and conducted actual breeding program in oat using different selection methods to identify molecular markers and improve beta-glucan content- a trait with positive health benefits. Results from GWAS suggested that beta-glucan content in elite oat is controlled by many QTL with small effects. Some of the important markers in our study co-localized with QTL in previous linkage studies. For the selection study, results demonstrated that after two cycles of selection the population means from marker-assisted selection and genomic selection methods were higher than BLUP phenotypic selection. The study also showed that the top performing lines came from marker-based methods indicating superiority of these methods in terms of cultivar development. The top lines in this study were also submitted to National Small Grains Collection for germplasm preservation and distribution purposes. We also found that the genetic variance for beta-glucan is mainly controlled by additive genetic component. However, the genetic variance decreased after two cycles of selection but the magnitude of decrease was different between selection methods. Particularly, the greatest reduction in genetic variance was detected for populations undergoing BLUP phenotypic selection. This could be attributed to higher chance of co-selection of sibs. On the other hand, populations under genomic selection had the lowest reduction in genetic variance which could be attributed to ability of markers to detect segregation in the estimation of breeding values. Among the three methods, only genomic selection can be conducted atleast twice a year which can result to doubling of genetic gain. Our experiments also demonstrated empirically that the accuracy of genomic selection can be increased by larger training population size, higher marker density and if selection candidates are genetically related to the training population.

DOI

https://doi.org/10.31274/etd-180810-1832

Copyright Owner

Franco Garcia Asoro

Language

en

Date Available

2012-10-31

File Format

application/pdf

File Size

164 pages

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