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Download or read book Phenotypic Analysis and Genetic Dissection of Yield Component Traits in Maize (Zea Mays L.) written by Nicholas James Haase and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Maize yield suffers from low heritability, and thus the elucidation of its genetic contributions is difficult to obtain. Maize yield components are correlated to maize yield while having increased heritabilities, making the detection of quantitative trait loci more feasible. The goal of this thesis is to characterize the genetic architecture of yield component traits in maize. First, an image-analysis pipeline was used to extract quantitative shape information on maize ears, cobs, and kernels. Correlations between a hand measured validation set of 275 random plots and image-analysis estimates ranged from 0.708 (kernel width) to 0.995 (ear length). Principal component (PC) analysis was used to develop ear shape descriptors from 1,000 width measurements along the length of an ear. These descriptors explained roughly 90.92 and 85.15 percent of the width variation for ears and cobs, respectively. Additionally, 1,233 individuals from nine biparental families of maize were introduced and genetically characterized. These populations were analyzed using a randomized complete block design (RCBD) with two replications per environment and genotyped using ~956,000 genotype-by-sequencing single nucleotide polymorphism (SNP) markers. In total, 101 quantitative trait loci (QTL) were mapped for kernel traits, 158 for ear traits, and 34 for kernel row number in these families using a linkage mapping approach. These QTL could be condensed into 37 QTL clusters, which moderately (approximately 50 percent) overlapped with known ear and kernel developmental mutants. Additionally, a genomewide association (GWA) analysis was performed using imputed SNP data across these families, identifying 32 genomic regions associated with the fourteen traits previously described. Lastly, 390 diverse maize inbreds were also evaluated in a RCBD with two replications grown in two years. GWA analysis was performed using the approximately 437,000 RNA-seq based markers available for this population which identified four significant associations for kernel depth, kernel area, kernel thickness, and ear PC1. In some cases, candidate genes showed corroborated results compared with associations identified using inbreds derived from two divergently selected subpopulations of maize for seed size. In summary, this work has elucidated genomic regions associated with economically relevant traits and candidate genes contributing to yield in maize.