Fusarium head blight (FHB), which is mainly caused by Fusarium graminearum, is a destructive wheat disease that threatens global wheat production. Fhb1, a quantitative trait locus discovered in ...Chinese germplasm, provides the most stable and the largest effect on FHB resistance in wheat. Here we show that TaHRC, a gene that encodes a putative histidine-rich calcium-binding protein, is the key determinant of Fhb1-mediated resistance to FHB. We demonstrate that TaHRC encodes a nuclear protein conferring FHB susceptibility and that a deletion spanning the start codon of this gene results in FHB resistance. Identical sequences of the TaHRC-R allele in diverse accessions indicate that Fhb1 had a single origin, and phylogenetic and haplotype analyses suggest that the TaHRC-R allele most likely originated from a line carrying the Dahongpao haplotype. This discovery opens a new avenue to improve FHB resistance in wheat, and possibly in other cereal crops, by manipulating TaHRC sequence through bioengineering approaches.
Fusarium head blight (FHB) is a destructive disease that reduces wheat grain yield and quality. To date, the quantitative trait locus on 3BS (Fhb1) from Sumai 3 has shown the largest effect on FHB ...resistance. Single nucleotide polymorphism (SNP) is the most common form of genetic variation and is suitable for high-throughput marker-assisted selection (MAS). We analyzed SNPs derived from 23 wheat expressed sequence tags (ESTs) that previously mapped near Fhb1 on chromosome 3BS. Using 71 Ning 7840/Clark BC7F7 recombinant inbred lines and the single-base extension method, we mapped seven SNP markers between Xgwm533 and Xgwm493, flanking markers for Fhb1. Five of the SNPs explained 45–54% of the phenotypic variation for FHB resistance. Haplotype analysis of 63 wheat accessions from eight countries based on SNPs in EST sequences, simple sequence repeats, and sequence tagged sites in the Fhb1 region identified four major groups: (1) US-Clark, (2) Asian, (3) US-Ernie, and (4) Chinese Spring. The Asian group consisted of Chinese and Japanese accessions that carry Fhb1 and could be differentiated from other groups by marker Xsnp3BS-11. All Sumai 3-related accessions formed a subgroup within the Asian group and could be sorted out by Xsnp3BS-8. The SNP markers identified in this study should be useful for MAS of Fhb1 and fine mapping to facilitate cloning of the Fhb1 resistance gene.
With the advent of next generation sequencing (NGS) technologies, single nucleotide polymorphisms (SNPs) have become the major type of marker for genotyping in many crops. However, the availability ...of SNP markers for important traits of bread wheat (Triticum aestivum L.) that can be effectively used in marker-assisted selection (MAS) is still limited and SNP assays for MAS are usually uniplex. A shift from uniplex to multiplex assays will allow the simultaneous analysis of multiple markers and increase MAS efficiency. We designed 33 locus-specific markers from SNP or indel-based marker sequences that linked to 20 different quantitative trait loci (QTL) or genes of agronomic importance in wheat and analyzed the amplicon sequences using an Ion Torrent Proton Sequencer and a custom allele detection pipeline to determine the genotypes of 24 selected germplasm accessions. Among the 33 markers, 27 were successfully multiplexed and 23 had 100% SNP call rates. Results from analysis of "kompetitive allele-specific PCR" (KASP) and sequence tagged site (STS) markers developed from the same loci fully verified the genotype calls of 23 markers. The NGS-based multiplexed assay developed in this study is suitable for rapid and high-throughput screening of SNPs and some indel-based markers in wheat.
Genetic improvement of pearl millet is lagging behind most of the major crops. Development of genomic resources is expected to expedite breeding for improved agronomic traits, stress tolerance, ...yield, and nutritional quality. Genotyping a breeding population with high throughput markers enables exploration of genetic diversity, population structure, and linkage disequilibrium (LD) which are important preludes for marker-trait association studies and application of genomic-assisted breeding.
Genotyping-by-sequencing (GBS) libraries of 309 inbred lines derived from landraces and improved varieties from Africa and India generated 54,770 high quality single nucleotide polymorphism (SNP) markers. On average one SNP per 29 Kb was mapped in the reference genome, with the telomeric regions more densely mapped than the pericentromeric regions of the chromosomes. Population structure analysis using 30,208 SNPs evenly distributed in the genome divided 309 accessions into five subpopulations with different levels of admixture. Pairwise genetic distance (GD) between accessions varied from 0.09 to 0.33 with the average distance of 0.28. Rapid LD decay implied low tendency of markers inherited together. Genetic differentiation estimates were the highest between subgroups 4 and 5, and the lowest between subgroups 1 and 2.
Population genomic analysis of pearl millet inbred lines derived from diverse geographic and agroecological features identified five subgroups mostly following pedigree differences with different levels of admixture. It also revealed the prevalence of high genetic diversity in pearl millet, which is very useful in defining heterotic groups for hybrid breeding, trait mapping, and holds promise for improving pearl millet for yield and nutritional quality. The short LD decay observed suggests an absence of persistent haplotype blocks in pearl millet. The diverse genetic background of these lines and their low LD make this set of germplasm useful for traits mapping.
Genomic prediction is a promising approach for accelerating the genetic gain of complex traits in wheat breeding. However, increasing the prediction accuracy (PA) of genomic prediction (GP) models ...remains a challenge in the successful implementation of this approach. Multivariate models have shown promise when evaluated using diverse panels of unrelated accessions; however, limited information is available on their performance in advanced breeding trials. Here, we used multivariate GP models to predict multiple agronomic traits using 314 advanced and elite breeding lines of winter wheat evaluated in 10 site-year environments. We evaluated a multi-trait (MT) model with two cross-validation schemes representing different breeding scenarios (CV1, prediction of completely unphenotyped lines; and CV2, prediction of partially phenotyped lines for correlated traits). Moreover, extensive data from multi-environment trials (METs) were used to cross-validate a Bayesian multi-trait multi-environment (MTME) model that integrates the analysis of multiple-traits, such as G × E interaction. The MT-CV2 model outperformed all the other models for predicting grain yield with significant improvement in PA over the single-trait (ST-CV1) model. The MTME model performed better for all traits, with average improvement over the ST-CV1 reaching up to 19, 71, 17, 48, and 51% for grain yield, grain protein content, test weight, plant height, and days to heading, respectively. Overall, the empirical analyses elucidate the potential of both the MT-CV2 and MTME models when advanced breeding lines are used as a training population to predict related preliminary breeding lines. Further, we evaluated the practical application of the MTME model in the breeding program to reduce phenotyping cost using a sparse testing design. This showed that complementing METs with GP can substantially enhance resource efficiency. Our results demonstrate that multivariate GS models have a great potential in implementing GS in breeding programs.
Integrating high-throughput phenotyping (HTP) based traits into phenomic and genomic selection (GS) can accelerate the breeding of high-yielding and climate-resilient wheat cultivars. In this study, ...we explored the applicability of Unmanned Aerial Vehicles (UAV)-assisted HTP combined with deep learning (DL) for the phenomic or multi-trait (MT) genomic prediction of grain yield (GY), test weight (TW), and grain protein content (GPC) in winter wheat. Significant correlations were observed between agronomic traits and HTP-based traits across different growth stages of winter wheat. Using a deep neural network (DNN) model, HTP-based phenomic predictions showed robust prediction accuracies for GY, TW, and GPC for a single location with R 2 of 0.71, 0.62, and 0.49, respectively. Further prediction accuracies increased (R 2 of 0.76, 0.64, and 0.75) for GY, TW, and GPC, respectively when advanced breeding lines from multi-locations were used in the DNN model. Prediction accuracies for GY varied across growth stages, with the highest accuracy at the Feekes 11 (Milky ripe) stage. Furthermore, forward prediction of GY in preliminary breeding lines using DNN trained on multi-location data from advanced breeding lines improved the prediction accuracy by 32% compared to single-location data. Next, we evaluated the potential of incorporating HTP-based traits in multi-trait genomic selection (MT-GS) models in the prediction of GY, TW, and GPC. MT-GS, models including UAV data-based anthocyanin reflectance index (ARI), green chlorophyll index (GCI), and ratio vegetation index 2 (RVI_2) as covariates demonstrated higher predictive ability (0.40, 0.40, and 0.37, respectively) as compared to single-trait model (0.23) for GY. Overall, this study demonstrates the potential of integrating HTP traits into DL-based phenomic or MT-GS models for enhancing breeding efficiency.
Rye (Secale cereale L.) is known for its wide adaptation due to its ability to tolerate harsh environments in semiarid areas. To assess the diversity in rye we genotyped a panel of 178 geographically ...diverse accessions of four Secale sp. from U.S. National Small Grains Collection using 4,037 high-quality SNPs (single nucleotide polymorphisms) developed by genotyping-by-sequencing (GBS). PCA and STRUCTURE analysis revealed three major clusters that separate S. cereale L. from S. strictum and S. sylvestre, however, genetic clusters did not correlate with geographic origins and growth habit (spring/winter). The panel was evaluated for response to Pyrenophora tritici-repentis race 5 (PTR race 5) and nearly 59% accessions showed resistance or moderate resistance. Genome-wide association study (GWAS) was performed on S. cereale subsp. cereale using the 4,037 high-quality SNPs. Two QTLs (QTs.sdsu-5R and QTs.sdsu-2R) on chromosomes 5R and 2R were identified conferring resistance to PTR race 5 (p < 0.001) that explained 13.1% and 11.6% of the phenotypic variation, respectively. Comparative analysis showed a high degree of synteny between rye and wheat with known rearrangements as expected. QTs.sdsu-2R was mapped in the genomic region corresponding to wheat chromosome group 2 and QTs.sdsu-5R was mapped to a small terminal region on chromosome 4BL. Based on the genetic diversity, a set of 32 accessions was identified to represents more than 99% of the allelic diversity with polymorphic information content (PIC) of 0.25. This set can be utilized for genetic characterization of useful traits and genetic improvement of rye, triticale, and wheat.
Fusarium head blight (FHB), caused by the fungus
Fusarium graminearum
Schwabe is an important disease of wheat that causes severe yield losses along with serious quality concerns. Incorporating the ...host resistance from either wild relatives, landraces, or exotic materials remains challenging and has shown limited success. Therefore, a better understanding of the genetic basis of native FHB resistance in hard winter wheat (HWW) and combining it with major quantitative trait loci (QTLs) can facilitate the development of FHB-resistant cultivars. In this study, we evaluated a set of 257 breeding lines from the South Dakota State University (SDSU) breeding program to uncover the genetic basis of native FHB resistance in the US hard winter wheat. We conducted a multi-locus genome-wide association study (ML-GWAS) with 9,321 high-quality single-nucleotide polymorphisms (SNPs). A total of six distinct marker-trait associations (MTAs) were identified for the FHB disease index (DIS) on five different chromosomes including 2A, 2B, 3B, 4B, and 7A. Further, eight MTAs were identified for Fusarium-damaged kernels (FDK) on six chromosomes including 3B, 5A, 6B, 6D, 7A, and 7B. Out of the 14 significant MTAs, 10 were found in the proximity of previously reported regions for FHB resistance in different wheat classes and were validated in HWW, while four MTAs represent likely novel loci for FHB resistance. Accumulation of favorable alleles of reported MTAs resulted in significantly lower mean DIS and FDK score, demonstrating the additive effect of FHB resistance alleles. Candidate gene analysis for two important MTAs identified several genes with putative proteins of interest; however, further investigation of these regions is needed to identify genes conferring FHB resistance. The current study sheds light on the genetic basis of native FHB resistance in the US HWW germplasm and the resistant lines and MTAs identified in this study will be useful resources for FHB resistance breeding
via
marker-assisted selection.
Moderate heat stress accompanied by short episodes of extreme heat during the post-anthesis stage is common in most US wheat growing areas and causes substantial yield losses. Sink strength (grain ...number) is a key yield limiting factor in modern wheat varieties. Increasing spike fertility (SF) and improving the partitioning of assimilates can optimize sink strength which is essential to improve wheat yield potential under a hot and humid environment. A genome-wide association study (GWAS) allows identification of novel quantitative trait loci (QTLs) associated with SF and other partitioning traits that can assist in marker assisted breeding. In this study, GWAS was performed on a soft wheat association mapping panel (SWAMP) comprised of 236 elite lines using 27,466 single nucleotide polymorphisms (SNPs). The panel was phenotyped in two heat stress locations over 3 years. GWAS identified 109 significant marker-trait associations (MTAs) (p ≤ 9.99 x 10-5) related to eight phenotypic traits including SF (a major component of grain number) and spike harvest index (SHI, a major component of grain weight). MTAs detected on chromosomes 1B, 3A, 3B, and 5A were associated with multiple traits and are potentially important targets for selection. More than half of the significant MTAs (60 out of 109) were found in genes encoding different types of proteins related to metabolism, disease, and abiotic stress including heat stress. These MTAs could be potential targets for further validation study and may be used in marker-assisted breeding for improving wheat grain yield under post-anthesis heat stress conditions. This is the first study to identify novel QTLs associated with SF and SHI which represent the major components of grain number and grain weight, respectively, in wheat.
Increasing attention is paid to providing new tools to breeders for targeted breeding for specific root traits that are beneficial in low-fertility, drying soils; however, such information is not ...available for barley (
Hordeum vulgare
L.). A panel of 191 barley accessions (originating from Australia, Europe, and Africa) was phenotyped for 26 root and shoot traits using the semi-hydroponic system and genotyped using 21 062 high-quality single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS). The population structure analysis of the barley panel identified six distinct groups. We detected 1199 significant (
P<
0.001) marker-trait associations (MTAs) with r
2
values up to 0.41. The strongest MTAs were found for root diameter in the top 20 cm and the longest root length. Based on the physical locations of these MTAs in the barley reference genome, we identified 37 putative QTLs for the root traits, and three QTLs for shoot traits, with nine QTLs located in the same physical regions. The genomic region 640-653 Mb on chromosome 7H was significant for five root length-related traits, where 440 annotated genes were located. The putative QTLs for various root traits identified in this study may be useful for genetic improvement regarding the adaptation of new barley cultivars to suboptimal environments and abiotic stresses.
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