Glucosinolates are amino acid derived secondary metabolites found in the order Capparales. It is an important class of phytochemicals involved in plant-microbe, plant-insect, plant-animal and plant-human interactions. It is, therefore, important to understand genetic mechanism of glucosinolate biosynthesis in Brassica for efficient manipulation. In this study, QTL mapping of leaf and seed glucosinolates was performed in B. rapa using two RIL populations, SR-RILs and BU-RILs. QTL mapping was performed using SR-RILs developed from a cross of Chinese cabbage and turnip rapeseed and a genetic map in B.rapa. Genetic map was developed using a total 1,579 molecular markers including 9 markers specific to glucosinolate genes, GSL-ELONG, GSL-PRO, GSL-FMOOX1, and GSL-AOP/ALK. Several QTL for progoitrin, gluconapin, glucoalyssin, glucobrassicanapin, 2-methylpropyl and 4-hydoxyglucobrassicin glucosinolates were identified with phenotype variance between 6 and 54%. Interestingly, a major QTL for 5C aliphatic glucosinolates was co-localized with a candidate Br-GSL-ELONG locus on linkage group A3, displayed co-segregation with co-dominant SCAR marker BrMAM1-1. The Br-GSL-ELONG locus was identified to regulate 20 µmole/g seed 5C glucosinolate biosynthesis. BU-RILs derived from a cross of yellow sarson and USU9 was segregated for glucoerucin, gluconapin and progoitrin 4C aliphatic glucosinolates with 4-hydoxyglucobrassicin. Phenotyping was performed in controlled and field environments for seed glucosinolates and controlled environments for leaf glucosinolates. Genetic map was developed using SRAP markers and glucosinolate gene, GSL-ELONG and GSL-PRO specific 4 loci were integrated on map. Four and three QTL were identified for seed glucoerucin and gluconapin, respectively in both environments with phenotypic variance up to 49%. Additionally, genetic manipulation of glucosinolates was performed by backcross with MAS in B. rapa. Resynthesized B. napus line was backcrossed with B. rapa genotypes, RI16, BAR6 and USU9 for replacement or introgression of glucosinolate genes, GSL-ELONG- and GSL-PRO+. In RI16 genotype, 15 to 25 µmole/g seed 5C glucosinolates reduced in 15 BC3F2 lines those were positive with GSL-ELONG- marker and negative with the A-genome and gene specific marker BrMAM1-1. This suggests that the functional allele has replaced by non-functional from B. oleracea. GSL-PRO+ positive backcross lines in RI16 genotype displayed sinigrin 3C aliphatic glucosinolate in B. rapa. This suggests introgression of GSL-PRO+ in B. rapa.

A genetic linkage map of mustard (Brassica juncea) was developed using two double haploid populations produced from crosses between a low erucic cultivar “ZEM1” and two moderate erucic acid lines “Vniimk351” and “Vniimk405” with the use of SSR and SRAP markers. The linkage map of the ZEM1xVniimk351 population included 13 linkage groups with an overall length of 791 cM with an average marker interval of 5.7 cM. The linkage map of the ZEM1xVniimk405 population also contained 13 linkage groups with a distance of 623 cM and an average marker interval of 4.6 cM. Using the linkage maps for the two populations, QTLs were detected for seed oil, protein and fatty acids. QTL analysis for fatty acids indentified QTLs on LG1, 7 and 12 for the ZEM1xVniimk351 population and LG1, 3 and 4 for the ZEM1xVniimk405 population. Analysis for the seed oil and protein content in the ZEM1xVniimk351 population identified 2 QTLs on LG1 and LG4 and 1 QTL on LG1 respectively. The QTL analysis ZEM1xVniimk405 of oil and protein content identified 1 QTL for oil and protein on LG1. The variation of fatty acids was shown to be the result of monogenic inheritance of the FAE1 gene in both populations.

No description available.

Many important traits in plants, animals and humans are quantitative, and most such traits are generally believed to be affected by multiple genetic loci. Standard computational tools for mapping of quantitative traits (i.e. for finding Quantitative Trait Loci, QTL, in the genome) use linear regression models for relating the observed phenotypes to the genetic composition of individuals in an experimental population. Using these tools to simultaneously search for multiple QTL is computationally demanding. The main reason for this is the complex optimization landscape for the multidimensional global optimization problems that must be solved. This thesis describes parallel algorithms, implementations and tools for simultaneous mapping of several QTL. These new computational tools enable genetic analysis exploiting new classes of multidimensional statistical models, potentially resulting in interesting results in genetics. We first describe how the standard, brute-force algorithm for global optimization in QTL analysis is parallelized and implemented on a grid system. Then, we also present a parallelized version of the more elaborate global optimization algorithm DIRECT and show how this can be efficiently deployed and used on grid systems and other loosely-coupled architectures. The parallel DIRECT scheme is further developed to exploit both coarse-grained parallelism in grid systems or clusters as well as fine-grained, tightly-coupled parallelism in multi-core nodes. The results show that excellent speedup and performance can be archived on grid systems and clusters, even when using a tightly-coupled algorithm such as DIRECT. Finally, we provide two distinctly different front-ends for our code. One is a grid portal providing a graphical front-end suitable for novice users and standard forms of QTL analysis. The other is a prototype of an R-based grid-enabled problem solving environment. Both of these front-ends can, after some further refinement, be utilized by geneticists for performing multidimensional genetic analysis of quantitative traits on a regular basis. / eSSENCE

Zugl.: Giessen, Universiẗat, Diss., 2008.

Zugl.: Giessen, Universiẗat, Diss., 2008.

University, Diss., 2004--Bonn.

No description available.

Doctor of Philosophy / Department of Agronomy / Guihua Bai / Allan K. Fritz / Wheat leaf rust, caused by Puccinia triticina, is an important fungal disease worldwide. Growing resistant cultivars is an effective practice to reduce the losses caused by the disease, and using slow-rusting resistance genes can improve the durability of rust resistance in the cultivars. CI13227 is a winter wheat line that shows a high level of slow-rusting resistance to leaf rust and has been studied extensively. In this research, two recombinant inbreed line (RIL) populations derived from CI13227 x Suwon (104 RILs) and CI13227 x Everest (184 RILs) and one doubled haploid (DH) population derived from CI13227 x Lakin with 181 lines were used to identify quantitative trait loci (QTLs) for slow leaf rusting resistance. Each population and its parents were evaluated for slow-rusting traits in two greenhouse experiments. A selected set of 384 simple sequence repeat markers (SSRs), single nucleotide polymorphism markers (SNPs) derived from genotyping-by-sequencing (GBS-SNPs) or 90K-SNP chip (90K-SNPs) were analyzed in the three populations. Six QTLs for slow-rusting resistance, QLr.hwwgru-2DS, QLr.hwwgru-7BL, QLr.hwwgru-7AL, QLr.hwwgru-3B_1, QLr.hwwgru-3B_2, and QLr.hwwgru-1D were detected in the three populations with three stable QTLs, QLr.hwwgru-2DS, QLr.hwwgru-7BL and QLr.hwwgru-7AL. These were detected and validated by Kompetitive Allele-Specific PCR (KASP) markers converted from GBS-SNPs and 90K-SNPs in at least two populations. Another three QTLs were detected only in a single population, and either showed a minor effect or came from the susceptible parents. The KASP markers tightly linked to QLr.hwwgru-2DS (IWB34642, IWB8545 and GBS_snpj2228), QLr.hwwgru-7BL (GBS_snp1637 and IWB24039) and QLr.hwwgru-7AL (IWB73053 and IWB42182) are ready to be used in marker-assisted selection (MAS) to transfer these QTLs into wheat varieties to improve slow-rusting resistance in wheat.

Master of Science / Department of Plant Pathology / William Bockus / Robert Bowden / Stem rust, caused by the fungus Puccinia graminis f. sp. tritici, has historically been one of the most important diseases of wheat. Although losses have been much reduced in the last fifty years, new highly virulent races of the pathogen have recently emerged in East Africa. These new races are virulent on nearly all of the currently deployed resistance genes and therefore pose a serious threat to global wheat production. The spring wheat variety ‘Kingbird’ is thought to contain multiple quantitative trait loci (QTLs) that provide durable, adult-plant resistance against wheat stem rust. Stem rust-susceptible Kansas winter wheat line ‘KS05HW14’ was backcrossed to Kingbird and 379 recombinant lines were advanced to BC₁F₅ and then increased for testing. The lines were screened for stem rust resistance in the greenhouse and field in Kansas and in the field in Kenya over multiple years. We identified 16,237 single nucleotide polymorphisms (SNPs) with the Wheat 90K iSelect SNP Chip assay. After filtering for marker quality, linkage maps were constructed for each wheat chromosome. Composite interval mapping and multiple-QTL mapping identified seven QTLs on chromosome arms 2BL, 2DS, 3BS, 3BSc, 5DL, 7BL, and 7DS. Six QTLs were inherited from Kingbird and one QTL on 7BL was inherited from KS05HW14. The location of the QTL on 2BL is approximately at locus Sr9, 3BS is at Sr2, 3BSc is at Sr12, and 7DS is at Lr34/Yr18/Sr57. Although no QTL was found on 1BL, the presence of resistance gene Lr46/Yr29/Sr58 on 1BL in both parents was indicated by the gene-specific marker csLV46. QTLs on 2DS and 5DL may be related to photoperiod or vernalization genes. Pairwise interactions were only observed with race QFCSC, most notably occurring with QTLs 2BL and 3BSc. These results confirm that there are multiple QTLs present in Kingbird. Ultimately, the identification of the QTLs that make Kingbird resistant will aid in the understanding of durable, non-race-specific resistance to stem rust of wheat.