Browsing by Subject "QTL Mapping"
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Item Genetic Analysis of Stem Composition Variation in Sorghum Bicolor(2012-10-19) Evans, JosephSorghum (Sorghum bicolor [L.] Moench) is the world's fifth most economically important cereal crop, grown worldwide as a source of food for both humans and livestock. Sorghum is a C4 grass that is well adapted to hot and arid climes and is popular for cultivation on lands of marginal quality. Recent interest in development of biofuels from lignocellulosic biomass has drawn attention to sorghum, which can be cultivated in areas not suitable for more traditional crops, and is capable of generating plant biomass in excess of 40 tons per acre. While the quantity of biomass and low water consumption make sorghum a viable candidate for biofuels growth, the biomass composition is enriched in lignin, which is problematic for enzymatic and chemical conversion techniques. The genetic basis for stem composition was analyzed in sorghum populations using a combination of genetic, genomic, and bioinformatics techniques. Utilizing acetyl bromide extraction, the variation in stem lignin content was quantified across several sorghum cultivars, confirming that lignin content varied considerably among sorghum cultivars. Previous work identifying sorghum reduced-lignin lines has involved the monolignol biosynthetic pathway; all steps in the pathway were putatively identified in the sorghum genome using sequence analysis. A bioinformatics toolkit was constructed to allow for the development of genetic markers in sorghum populations, and a database and web portal were generated to allow users to access previously developed genetic markers. Recombinant inbred lines were analyzed for stem composition using near infrared reflectance spectroscopy (NIR) and genetic maps constructed using restriction site-linked polymorphisms, revealing 34 quantitative trail loci (QTL) for stem composition variation in a BTx642 x RTx7000 population, and six QTL for stem composition variation in an SC56 x RTx7000 population. Sequencing the genome of BTx642 and RTx7000 to a depth of ~11x using Illumina sequencing revealed approximately 1.4 million single nucleotide polymorphisms (SNPs) and 1 million SNPs, respectively. These polymorphisms can be used to identify putative amino acid changes in genes within these genotypes, and can also be used for fine mapping. Plotting the density of these SNPs revealed patterns of genetic inheritance from shared ancestral lines both between the newly sequenced genotypes and relative to the reference genotype BTx623.Item Quantitative trait loci affecting the agronomic performance of a Sorghum bicolor (L.) Moench recombinant inbred restorer line population(Texas A&M University, 2004-09-30) Moran Maradiaga, Jorge LuisLately the rate of genetic gain in most agronomic crop species has been reduced due to several factors that limit breeding efficiency and genetic gain. New genetic tools and more powerful statistical analyses provide an alternative approach to enhance genetic improvements through the identification of molecular markers linked to genomic regions or QTLs controlling quantitative traits. The main objective of this research was to identify genomic regions associated with enhanced agronomic performance in lines per se and hybrid combination in Sorghum bicolor (L.) Moench. A population composed of 187 F5:6 recombinant inbred lines (RIL) was derived from the cross of restorer lines RTx430 and RTx7000. Also, a testcross hybrid population (TCH) was developed by using each RIL as a pollinator onto ATx2752. A linkage map was constructed using 174 marker loci generated from AFLP and SSR primer combinations. These markers were assigned to 12 different linkage groups. The linkage map covers 1573 cM with marker loci spaced at an averaged 9.04 cM. In this study, 89 QTL that control variation in seven different morphological traits were identified in the recombinant inbred line population, while in the testcross hybrid population, 79 QTL were identified. These traits included grain yield, plant height, days to mid-anthesis, panicle number, panicle length, panicle exsertion and panicle weight. These putative QTL explained from 4 to 42% of the phenotypic variation observed for each trait. Many of the QTL were not consistent across populations and across environments. Nevertheless, a few key QTL were identified and the source of the positive additive genetics isolated. RTx7000 was consistently associated with better agronomic performance in RIL, while in testcrosses, RTx430 was. Some genomic regions from RTx7000 may be utilized to improve RTx430 as a line per se. However, it is very unlikely that such regions will have a positive effect on the combining ability of RTx430 since testcross results did not reveal any transgressive segregants from the RIL population.