A haplotype map of allohexaploid wheat reveals distinct patterns of selection on homoeologous genomes

BACKGROUND: Bread wheat is an allopolyploid species with a large, highly repetitive genome. To investigate the impact of selection on variants distributed among homoeologous wheat genomes and to build a foundation for understanding genotype-phenotype relationships, we performed population-scale re-sequencing of a diverse panel of wheat lines. RESULTS: A sample of 62 diverse lines was re-sequenced using the whole exome capture and genotyping-by-sequencing approaches. We describe the allele frequency, functional significance, and chromosomal distribution of 1.57 million single nucleotide polymorphisms and 161,719 small indels. Our results suggest that duplicated homoeologous genes are under purifying selection. We find contrasting patterns of variation and inter-variant associations among wheat genomes; this, in addition to demographic factors, could be explained by differences in the effect of directional selection on duplicated homoeologs. Only a small fraction of the homoeologous regions harboring selected variants overlapped among the wheat genomes in any given wheat line. These selected regions are enriched for loci associated with agronomic traits detected in genome-wide association studies. CONCLUSIONS: Evidence suggests that directional selection in allopolyploids rarely acted on multiple parallel advantageous mutations across homoeologous regions, likely indicating that a fitness benefit could be obtained by a mutation at any one of the homoeologs. Additional advantageous variants in other homoelogs probably either contributed little benefit, or were unavailable in populations subjected to directional selection. We hypothesize that allopolyploidy may have increased the likelihood of beneficial allele recovery by broadening the set of possible selection targets

Development and validation of molecular markers linked with stem rust resistance gene Sr13 in durum wheat

Stem rust resistance gene Sr13, found frequently in tetraploid wheats, was tested effective against Puccinia graminis f. sp. tritici pathotype Ug99 (TTKSK) and its derivatives. It remains a candidate for developing new cultivars with diverse combinations of stem rust resistance genes. To combine Sr13 with other genes that produce a similar phenotype, linked markers would be required. We used the AFLP approach to identify markers linked closely with Sr13. The STS marker AFSr13, derived from an AFLP fragment, mapped at 3.4-6.0 cM proximal to Sr13 across three mapping populations. Marker dupw167, previously reported to be linked with Sr13, mapped 2.3-5.7 cM distal to Sr13 in four F-3 populations. Marker gwm427 mapped proximal to AFSr13 in two populations, and these markers were monomorphic on one population each. The map order dupw167-Sr13-AFSr13-gwm427 was deduced from the recombination data. Markers dupw167 and AFSr13 were validated on 21 durum wheat genotypes. Combination of dupw167 and AFSr13 would facilitate marker-assisted selection of Sr13 in segregating populations. At the hexaploid level, only gwm427 showed polymorphism and differentiated the presence of Sr13 in 10 of the 15 backcross derivatives carrying Sr13 from their Sr13-lacking recurrent parents

Assessment of Genetic Diversity for Stem Rust and Stripe Rust Resistance in an International Wheat Nursery Using Phenotypic and Molecular Technologies

The objective of this study was to assess diversity for stem rust and stripe rust resistance in an international wheat screening nursery under greenhouse conditions using pathotypes with known avirulence/ virulence profiles. A set of 95 entries of an international wheat screening nursery collected from material generated by staff of the International Maize and Wheat Improvement Centre (CIMMYT) was tested against seven Australian Pgt and five Pst pathotypes through artificial inoculation under the greenhouse conditions using standard procedures. Ten all-stage stem rust resistance genes (Sr8a, Sr8b, Sr9b, Sr12, Sr17, Sr23, Sr24, Sr30, Sr31 and Sr38) and seven all-stage stripe rust resistance genes (Yr3, Yr4, Yr6, Yr9, Yr17, Yr27 and Yr34) were postulated either singly or in combinations based on seedling responses of test entries against pathotypes differing in virulence for commonly deployed genes. Sr30 and Sr38 were the most common stem rust resistance genes in this nursery. The Sr38-linked stripe rust resistance gene Yr17 was present in high proportion. The presence of rust resistance genes Sr24, Sr31/Yr9, Sr38/Yr17 and Yr4 were confirmed using the closely linked molecular markers. The adult plant resistance (APR) genes Sr2 and Lr34/Yr18/Sr57 were detected using linked molecular markers csSr2 and csLV34, respectively. Genotypes carrying combinations of stem rust and stripe rust resistance were identified for use as donor sources in breeding programs

Association mapping of rust resistance in pre-green revolution wheat accessions

Association mapping detects correlations between genotypes and phenotypes in a sample of individuals based on the linkage disequilibrium and can be used to uncover new genetic variation among germplasm collections. Two hundred and five landraces collected by the English botanist A. Watkins in the 1920s were screened for rust response variation under field conditions during three crop seasons. An integrated map of 350 polymorphic DArT markers was developed. Association mapping identified the involvement of several genomic regions in controlling resistance to three rust diseases. Seven, eight and nine genomic regions, respectively, appeared to carry yet uncharacterized leaf rust, stripe rust and stem rust resistance. Three dimensional analyses indicated genetic association of leaf rust and stripe rust resistance in some accessions, whereas no such association was observed between stem rust resistance and resistance to either of the other two rust diseases. A new stripe rust resistance locus, Yr47, has been named

Joukhadar2017

Genotype calls for 8194 SNPs in 2026 Australian and worldwide bread wheat accession

Data from: Genetic diversity, population structure and ancestral origin of Australian wheat

Since the introduction of wheat into Australia by the First Fleet settlers, germplasm from different geographical origins has been used to adapt wheat to the Australian climate through selection and breeding. In this paper, we used 482 cultivars, representing the breeding history of bread wheat in Australia since 1840, to characterize their diversity and population structure and to define the geographical ancestral background of Australian wheat germplasm. This was achieved by comparing them to a global wheat collection using in-silico chromosome painting based on SNP genotyping. The global collection involved 2,335 wheat accessions which was divided into 23 different geographical subpopulations. However, the whole set was reduced to 1,544 accessions to increase the differentiation and decrease the admixture among different global subpopulations to increase the power of the painting analysis. Our analysis revealed that the structure of Australian wheat germplasm and its geographic ancestors have changed significantly through time, especially after the Green Revolution. Before 1920, breeders used cultivars from around the world, but mainly Europe and Africa, to select potential cultivars that could tolerate Australian growing conditions. Between 1921 and 1970, a dependence on African wheat germplasm became more prevalent. Since 1970, a heavy reliance on International Maize and Wheat Improvement Center (CIMMYT) germplasm has persisted. Combining the results from linkage disequilibrium, population structure and in-silico painting revealed that the dependence on CIMMYT materials has varied among different Australian Sstates, has shrunken the germplasm effective population size and produced larger linkage disequilibrium blocks. This study documents the evolutionary history of wheat breeding in Australia and provides an understanding for how the wheat genome has been adapted to local growing conditions. This information provides a guide for industry to assist with maintaining genetic diversity for long-term selection gains and to plan future breeding programs

Microsatellite mapping identifies TTKST-effective stem rust resistance gene in wheat cultivars VL404 and Janz

Wheat cultivar VL404 carries seedling resistance to Puccinia graminis f. sp. tritici pathotype TTKST. Monogenic segregation for seedling resistance was observed in a VL404/WL711 recombinant inbred line population and the resistance locus was temporarily designated SrVL. Bulked segregant analysis using Diversity Arrays Technology markers located SrVL on chromosome 2BL. Detailed simple sequence repeat mapping placed SrVL between gwm120 and wmc175, both at genetic distances of 3.3 cM. Based on adult plant responses of Janz and VL404 in India and Kenya, we expected these cultivars to carry the same gene against TTKST. A subset of Diamondbird/Janz doubled haploid (DH) population showed monogenic segregation, when tested against TTKST and the locus was temporarily named SrJNZ. SrVL-linked markers gwm120 and wmc175 flanked SrJNZ at a similar genetic distance, thereby confirming our hypothesis. Chromosome 2BL carries Sr9, Sr16 and Sr28. Sr9 is a multi-allelic locus and all known alleles of Sr9 and Sr16 are ineffective against TTKSK and its derivatives. A recombination value of 16.7 cM between Sr9g-linked stripe rust resistance gene Yr7 and SrJNZ in Diamondbird/Janz DH population suggested that SrJNZ is not an allele at the Sr9 locus. Based on comparison of published genetic distances between Lr13,Sr9, Sr28 and Sr16 with that observed in this study, we concluded SrVL and SrJNZ to be Sr28. This gene was contributed by a common parent Gabo, which also exhibited resistance against TTKST. Sr28-linked markers gwm120 and wmc175 confirmed the presence of this gene in a high proportion of Australian cultivars that showed stem rust resistance in Kenya. These markers can be used for marker-assisted pyramiding of Sr28 with other stem rust resistance genes

Data from: Genetic diversity, population structure and ancestral origin of Australian wheat

Since the introduction of wheat into Australia by the First Fleet settlers, germplasm from different geographical origins has been used to adapt wheat to the Australian climate through selection and breeding. In this paper, we used 482 cultivars, representing the breeding history of bread wheat in Australia since 1840, to characterize their diversity and population structure and to define the geographical ancestral background of Australian wheat germplasm. This was achieved by comparing them to a global wheat collection using in-silico chromosome painting based on SNP genotyping. The global collection involved 2,335 wheat accessions which was divided into 23 different geographical subpopulations. However, the whole set was reduced to 1,544 accessions to increase the differentiation and decrease the admixture among different global subpopulations to increase the power of the painting analysis. Our analysis revealed that the structure of Australian wheat germplasm and its geographic ancestors have changed significantly through time, especially after the Green Revolution. Before 1920, breeders used cultivars from around the world, but mainly Europe and Africa, to select potential cultivars that could tolerate Australian growing conditions. Between 1921 and 1970, a dependence on African wheat germplasm became more prevalent. Since 1970, a heavy reliance on International Maize and Wheat Improvement Center (CIMMYT) germplasm has persisted. Combining the results from linkage disequilibrium, population structure and in-silico painting revealed that the dependence on CIMMYT materials has varied among different Australian Sstates, has shrunken the germplasm effective population size and produced larger linkage disequilibrium blocks. This study documents the evolutionary history of wheat breeding in Australia and provides an understanding for how the wheat genome has been adapted to local growing conditions. This information provides a guide for industry to assist with maintaining genetic diversity for long-term selection gains and to plan future breeding programs

Genomic prediction for rust resistance in diverse wheat landraces

Key message We have demonstrated that genomic selection in diverse wheat landraces for resistance to leaf, stem and strip rust is possible, as genomic breeding values were moderately accurate. Markers with large effects in the Bayesian analysis confirmed many known genes, while also discovering many previously uncharacterised genome regions associated with rust scores. Abstract Genomic selection, where selection decisions are based on genomic estimated breeding values (GEBVs) derived from genome-wide DNA markers, could accelerate genetic progress in plant breeding. In this study, we assessed the accuracy of GEBVs for rust resistance in 206 hexaploid wheat (Triticum aestivum) landraces from the Watkins collection of phenotypically diverse wheat genotypes from 32 countries. The landraces were genotyped for 5,568 SNPs using an Illumina iSelect 9 K bead chip assay and phenotyped for field-based leaf rust (Lr), stem rust (Sr) and stripe rust (Yr) responses across multiple years. Genomic Best Linear Unbiased Prediction (GBLUP) and a Bayesian Regression method (BayesR) were used to predict GEBVs. Based on fivefold cross-validation, the accuracy of genomic prediction averaged across years was 0.35, 0.27 and 0.44 for Lr, Sr and Yr using GBLUP and 0.33, 0.38 and 0.30 for Lr, Sr and Yr using BayesR, respectively. Inclusion of PCR-predicted genotypes for known rust resistance genes increased accuracy more substantially when the marker was diagnostic (Lr34/Sr57/Yr18) for the presence-absence of the gene rather than just linked (Sr2). Investigation of the impact of genetic relatedness between validation and reference lines on accuracy of genomic prediction showed that accuracy will be higher when each validation line had at least one close relationship to the reference lines. Overall, the prediction accuracies achieved in this study are encouraging, and confirm the feasibility of genomic selection in wheat. In several instances, estimated marker effects were confirmed by published literature and results of mapping experiments using Watkins accessions