Author : Gitanshu Munjal
Release : 2017
Genre :
Kind : eBook
Book Rating : 505/5 ( reviews)
Book Synopsis Genomic Investigations of Autumn Dormancy in Alfalfa (Medicago Sativa) by : Gitanshu Munjal
Download or read book Genomic Investigations of Autumn Dormancy in Alfalfa (Medicago Sativa) written by Gitanshu Munjal. This book was released on 2017. Available in PDF, EPUB and Kindle. Book excerpt: The primary goal of the research presented in the following chapters was to assess the genomic basis of the adaptive trait of autumn dormancy in alfalfa using high resolution genetic mapping approaches in diverse germplasm. Previous work in the field has developed protocols to generate vast amounts of sequence based marker data for this species using GBS. However, opportunity remains to extract more information from such data than had been previously possible. In chapter 1, we review some concepts relevant to the rest of this work including basic biology and improvement of alfalfa, the trait of autumn dormancy, and opportunities for molecular markers in alfalfa research. In chapter 2, we employ a recent SNP calling methodology and develop a framework for estimating allele frequencies from pooled sequencing. We use that framework to screen the non-dormant cultivar CUF 101 and populations developed by three cycles of selection for taller and shorter plants in autumn. We validated the robustness of our GBS-derived, population-specific allele frequency estimates using an analytic approach. In chapter 3, we analyze pre- and post-selection populations from an additional five backgrounds together with CUF 101 to seek evidence for loci under selection in germplasm expressing a range of dormancy levels. In chapter 4, we build on recent scientific reports to propose a method for conducting genome-wide association scans from low-coverage autotetraploid sequencing data that is able to account for uncertainty regarding genotypes. We apply this method to a panel of semi-dormant individuals from a commercial breeding program. Using simulations, we show this method to be more powerful than an existing method.
