Debbie Wong

Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array

High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.

Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars

Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessions of hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact of crop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneck and extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzing genetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected to selection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology. An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-based analysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targets or multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selected alleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variation in the targets of directional selection during breeding probably associated with changing agricultural practices or environmental conditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supporting future population genomic and genome-wide association studies in wheat.

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

BackgroundBread 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.ResultsA 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.ConclusionsEvidence 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 of robust molecular markers for marker-assisted selection of leaf rust resistance gene Lr23 in common and durum wheat breeding programs

Leaf rust, caused by Puccinia triticina (Pt), is one of the most important fungal diseases of wheat worldwide. The common wheat genotype BT-Schomburgk selection (BTSS) and the durum wheat cultivar Tamaroi carry Lr23, which is effective against predominant Pt pathotypes in Australia. BTSS and Tamaroi were crossed with the seedling susceptible genotypes W195 and Bansi, respectively, and recombinant inbred line (RIL) F5:7 populations W195/BTSS (88 RILs) and Tamaroi/Bansi (85 RILs) were developed. These populations were screened against Pt pathotype 104-1,(2),3,(6),(7),11,13 at the seedling stage and monogenic segregation at the Lr23 locus was observed. A combination of DNA marker technologies and genomic resources were used to fine map the chromosome 2B region carrying Lr23 in both RIL populations to develop closely linked markers for its marker-assisted selection in common and durum wheat breeding. Three single-marker SNP assays (sunKASP_16, sunKASP_47, and sunKASP_48) were developed and validated for selecting Lr23 in common wheat and one single-marker SNP assay (KASP_69462) was validated for durum wheat. None of the SNP markers worked across both common wheat and durum wheat backgrounds. The SSR marker sun471 showed close linkage with Lr23 across both ploidy levels. Overall, robust markers linked with Lr23 for use across different socio-economic geographic regions of the world were developed.

Detection and validation of genomic regions associated with resistance to rust diseases in a worldwide hexaploid wheat landrace collection using BayesR and mixed linear model approaches

Key messageBayesR and MLM association mapping approaches in common wheat landraces were used to identify genomic regions conferring resistance to Yr, Lr, and Sr diseases.AbstractDeployment of rust resistant cultivars is the most economically effective and environmentally friendly strategy to control rust diseases in wheat. However, the highly evolving nature of wheat rust pathogens demands continued identification, characterization, and transfer of new resistance alleles into new varieties to achieve durable rust control. In this study, we undertook genome-wide association studies (GWAS) using a mixed linear model (MLM) and the Bayesian multilocus method (BayesR) to identify QTL contributing to leaf rust (Lr), stem rust (Sr), and stripe rust (Yr) resistance. Our study included 676 pre-Green Revolution common wheat landrace accessions collected in the 1920–1930s by A.E. Watkins. We show that both methods produce similar results, although BayesR had reduced background signals, enabling clearer definition of QTL positions. For the three rust diseases, we found 5 (Lr), 14 (Yr), and 11 (Sr) SNPs significant in both methods above stringent false-discovery rate thresholds. Validation of marker–trait associations with known rust QTL from the literature and additional genotypic and phenotypic characterisation of biparental populations showed that the landraces harbour both previously mapped and potentially new genes for resistance to rust diseases. Our results demonstrate that pre-Green Revolution landraces provide a rich source of genes to increase genetic diversity for rust resistance to facilitate the development of wheat varieties with more durable rust resistance.

Accelerating wheat breeding for end-use quality with multi-trait genomic predictions incorporating near infrared and nuclear magnetic resonance-derived phenotypes

Key messageUsing NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection to accelerate improvement in grain end-use quality traits of wheat.AbstractGrain end-use quality traits are among the most important in wheat breeding. These traits are difficult to breed for, as their assays require flour quantities only obtainable late in the breeding cycle, and are expensive. These traits are therefore an ideal target for genomic selection. However, large reference populations are required for accurate genomic predictions, which are challenging to assemble for these traits for the same reasons they are challenging to breed for. Here, we use predictions of end-use quality derived from near infrared (NIR) or nuclear magnetic resonance (NMR), that require very small amounts of flour, as well as end-use quality measured by industry standard assay in a subset of accessions, in a multi-trait approach for genomic prediction. The NIR and NMR predictions were derived for 19 end-use quality traits in 398 accessions, and were then assayed in 2420 diverse wheat accessions. The accessions were grown out in multiple locations and multiple years, and were genotyped for 51208 SNP. Incorporating NIR and NMR phenotypes in the multi-trait approach increased the accuracy of genomic prediction for most quality traits. The accuracy ranged from 0 to 0.47 before the addition of the NIR/NMR data, while after these data were added, it ranged from 0 to 0.69. Genomic predictions were reasonably robust across locations and years for most traits. Using NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection for grain end-use quality traits in wheat breeding.

Exome sequence genotype imputation in globally diverse hexaploid wheat accessions

Key messageImputing genotypes from the 90K SNP chip to exome sequence in wheat was moderately accurate. We investigated the factors that affect imputation and propose several strategies to improve accuracy.AbstractImputing genetic marker genotypes from low to high density has been proposed as a cost-effective strategy to increase the power of downstream analyses (e.g. genome-wide association studies and genomic prediction) for a given budget. However, imputation is often imperfect and its accuracy depends on several factors. Here, we investigate the effects of reference population selection algorithms, marker density and imputation algorithms (Beagle4 and FImpute) on the accuracy of imputation from low SNP density (9K array) to the Infinium 90K single-nucleotide polymorphism (SNP) array for a collection of 837 hexaploid wheat Watkins landrace accessions. Based on these results, we then used the best performing reference selection and imputation algorithms to investigate imputation from 90K to exome sequence for a collection of 246 globally diverse wheat accessions. Accession-to-nearest-entry and genomic relationship-based methods were the best performing selection algorithms, and FImpute resulted in higher accuracy and was more efficient than Beagle4. The accuracy of imputing exome capture SNPs was comparable to imputing from 9 to 90K at approximately 0.71. This relatively low imputation accuracy is in part due to inconsistency between 90K and exome sequence formats. We also found the accuracy of imputation could be substantially improved to 0.82 when choosing an equivalent number of exome SNP, instead of 90K SNPs on the existing array, as the lower density set. We present a number of recommendations to increase the accuracy of exome imputation.

Development of co-dominant KASP markers co-segregating with Ug99 effective stem rust resistance gene Sr26 in wheat

Stem rust of wheat, caused by Puccinia graminis f. sp. tritici (Pgt), is a threat to global food security due to its ability to cause total crop failures. The Pgt race TTKSK (Ug99) and its derivatives detected in East Africa carry virulence for many resistance genes present in modern cultivars. However, stem rust resistance gene Sr26 remains effective to all races of Pgt worldwide. Sr26 is carried on the Agropyron elongatum (syn. Thinopyrum ponticum) segment 6Ae#1L translocated to chromosome 6AL of wheat. In this study, a recombinant inbred line (RIL) population derived from a cross between the landrace Aus27969 and Avocet S, which carries Sr26, was used to develop co-dominant kompetitive allele-specific polymerase chain reaction (KASP) markers that co-segregate with Sr26. Four KASP markers (sunKASP_216, sunKASP_218, sunKASP_224 and sunKASP_225) were also shown to co-segregate with Sr26 in four additional RIL populations. When tested on Australian cultivars and breeding lines, these markers amplified alleles alternate to that linked with Sr26 in all cultivars known to lack this gene and Sr26-linked alleles in cultivars and genotypes known to carry Sr26. Genotypes WA-1 and WA-1/3*Yitpi carrying the shortest Sr26 translocation segment were positive only for markers sunKASP_224 and sunKASP_225. Our results suggest the four KASP markers are located on the original translocation and sunKASP_224 and sunKASP_225 are located on the shortened version. Therefore, sunKASP_224 and sunKASP_225 can be used for marker-assisted pyramiding of Sr26 with other stem rust resistance genes to achieve durable resistance in wheat.

Zinc finger nuclease-mediated precision genome editing of an endogenous gene in hexaploid bread wheat (Triticum aestivum) using a DNA repair template

Summary Sequence‐specific nucleases have been used to engineer targeted genome modifications in various plants. While targeted gene knockouts resulting in loss of function have been reported with relatively high rates of success, targeted gene editing using an exogenously supplied DNA repair template and site‐specific transgene integration has been more challenging. Here, we report the first application of zinc finger nuclease (ZFN)‐mediated, nonhomologous end‐joining (NHEJ)‐directed editing of a native gene in allohexaploid bread wheat to introduce, via a supplied DNA repair template, a specific single amino acid change into the coding sequence of acetohydroxyacid synthase (AHAS) to confer resistance to imidazolinone herbicides. We recovered edited wheat plants having the targeted amino acid modification in one or more AHAS homoalleles via direct selection for resistance to imazamox, an AHAS‐inhibiting imidazolinone herbicide. Using a cotransformation strategy based on chemical selection for an exogenous marker, we achieved a 1.2% recovery rate of edited plants having the desired amino acid change and a 2.9% recovery of plants with targeted mutations at the AHAS locus resulting in a loss‐of‐function gene knockout. The latter results demonstrate a broadly applicable approach to introduce targeted modifications into native genes for nonselectable traits. All ZFN‐mediated changes were faithfully transmitted to the next generation.

Genetic Relationship of Stripe Rust Resistance Genes Yr34 and Yr48 in Wheat and Identification of Linked KASP Markers

The Australian continent was free from wheat stripe rust caused by Puccinia striiformis f. sp. tritici until exotic incursions occurred in 1979 and 2002. The 2002 incursion enabled the identification of a new stripe rust resistance gene (Yr34) in the advanced breeding line WAWHT2046. In this study, we developed and validated markers closely linked with Yr34, which is located in the distal region in the long arm of chromosome 5A. Four kompetitive allele-specific polymerase chain reaction (KASP) and three sequence-tagged site (STS) markers derived from the International Wheat Genome Sequencing Consortium RefSeq v1.0 scaffold-77836 cosegregated with Yr34. Markers sun711, sun712, sun725, sunKASP_109, and sunKASP_112 were shown to be suitable for marker-assisted selection in a validation panel of 71 Australian spring wheat genotypes, with the exception of cultivar Orion that carried the Yr34-linked alleles for sunKASP_109 and sunKASP_112. Markers previously reported to be linked with adult plant stripe rust resistance gene Yr48 also cosegregated with Yr34. Wheat genotypes carrying Yr34 and Yr48 produced identical haplotypes for the Yr34-linked markers identified in this study and those previously reported to be linked with Yr48. Phenotypic testing of genotypes carrying Yr34 and Yr48 showed that both genes conferred similar seedling responses to pre-2002 and post-2002 P. striiformis f. sp. tritici pathotypes. Further testing of 600 F2 plants from a cross between WAWHT2046 and RIL143 (Yr48) with P. striiformis f. sp. tritici pathotype 134 E16A+Yr17+Yr27+ failed to reveal any susceptible segregants. Our results strongly suggest that Yr34 and Yr48 are the same gene, and that Yr48 should be considered a synonym of Yr34.