Reference Genome Anchoring of High-Density Markers for Association Mapping and Genomic Prediction in European Winter Wheat

Genomic wide association study and selective sweep analysis identify genes associated with improved yield under drought in Turkish winter wheat germplasm

A panel comprising of 84 Turkish winter wheat landraces (LR) and 73 modern varieties (MV) was analyzed with genome wide association study (GWAS) to identify genes/genomic regions associated with increased yield under favorable and drought conditions. In addition, selective sweep analysis was conducted to detect signatures of selection in the winter wheat genome driving the differentiation between LR and MV, to gather an understanding of genomic regions linked to adaptation and yield improvement. The panel was genotyped with 25 K wheat SNP array and phenotyped for agronomic traits for two growing seasons (2018 and 2019) in Konya, Turkey. Year 2018 was treated as drought environment due to very low precipitation prior to heading whereas year 2019 was considered as a favorable season. GWAS conducted with SNPs and haplotype blocks using mixed linear model identified 18 genomic regions in the vicinities of known genes i.e., TaERF3-3A, TaERF3-3B, DEP1-5A, FRIZZY PANICLE-2D, TaSnRK23-1A, TaAGL6-A, TaARF12-2A, TaARF12-2B, WAPO1, TaSPL16-7D, TaTGW6-A1, KAT-2B, TaOGT1, TaSPL21-6B, TaSBEIb, trs1/WFZP-A, TaCwi-A1-2A and TaPIN1-7A associated with grain yield (GY) and yield related traits. Haplotype-based GWAS identified five haplotype blocks (H1A-42, H2A-71, H4A-48, H7B-123 and H7B-124), with the favorable haplotypes showing a yield increase of > 700 kg/ha in the drought season. SNP-based GWAS, detected only one larger effect genomic region on chromosome 7B, in common with haplotype-based GWAS. On an average, the percentage variation (PV) explained by haplotypes was 8.0% higher than PV explained by SNPs for all the investigated traits. Selective sweep analysis detected 39 signatures of selection between LR and MV of which 15 were within proximity of known functional genes controlling flowering (PRR-A1, PPR-D1, TaHd1-6B), GY and GY components (TaSus2-2B, TaGS2-B1, AG1-1A/WAG1-1A, DUO-A1, DUO-B1, AG2-3A/WAG2-3A, TaLAX1, TaSnRK210-4A, FBP, TaLAX1, TaPIL1 and AP3-1-7A/WPA3-7A) and 10 regions underlying various transcription factors and regulatory genes. The study outcomes contribute to utilization of LR in breeding winter wheat.

GWAS and genomic prediction for pre-harvest sprouting tolerance involving sprouting score and two other related traits in spring wheat

In wheat, a genome-wide association study (GWAS) and genomic prediction (GP) analysis were conducted for pre-harvest sprouting (PHS) tolerance and two of its related traits. For this purpose, an association panel of 190 accessions was phenotyped for PHS (using sprouting score), falling number, and grain color over two years and genotyped with 9904 DArTseq based SNP markers. GWAS for main-effect quantitative trait nucleotides (M-QTNs) using three different models (CMLM, SUPER, and FarmCPU) and epistatic QTNs (E-QTNs) using PLINK were performed. A total of 171 M-QTNs (CMLM, 47; SUPER, 70; FarmCPU, 54) for all three traits, and 15 E-QTNs involved in 20 first-order epistatic interactions were identified. Some of the above QTNs overlapped the previously reported QTLs, MTAs, and cloned genes, allowing delineating 26 PHS-responsive genomic regions that spread over 16 wheat chromosomes. As many as 20 definitive and stable QTNs were considered important for use in marker-assisted recurrent selection (MARS). The gene, TaPHS1, for PHS tolerance (PHST) associated with one of the QTNs was also validated using the KASP assay. Some of the M-QTNs were shown to have a key role in the abscisic acid pathway involved in PHST. Genomic prediction accuracies (based on the cross-validation approach) using three different models ranged from 0.41 to 0.55, which are comparable to the results of previous studies. In summary, the results of the present study improved our understanding of the genetic architecture of PHST and its related traits in wheat and provided novel genomic resources for wheat breeding based on MARS and GP.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01357-5.

Wheat Omics: Advancements and Opportunities

Plant omics, which includes genomics, transcriptomics, metabolomics and proteomics, has played a remarkable role in the discovery of new genes and biomolecules that can be deployed for crop improvement. In wheat, great insights have been gleaned from the utilization of diverse omics approaches for both qualitative and quantitative traits. Especially, a combination of omics approaches has led to significant advances in gene discovery and pathway investigations and in deciphering the essential components of stress responses and yields. Recently, a Wheat Omics database has been developed for wheat which could be used by scientists for further accelerating functional genomics studies. In this review, we have discussed various omics technologies and platforms that have been used in wheat to enhance the understanding of the stress biology of the crop and the molecular mechanisms underlying stress tolerance.

Analysis of historical selection in winter wheat

KEY MESSAGE

Modeling of the distribution of allele frequency over year of variety release identifies major loci involved in historical breeding of winter wheat. Winter wheat is a major crop with a rich selection history in the modern era of crop breeding. Genetic gains across economically important traits like yield have been well characterized and are the major force driving its production. Winter wheat is also an excellent model for analyzing historical genetic selection. As a proof of concept, we analyze two major collections of winter wheat varieties that were bred in Western Europe from 1916 to 2010, namely the Triticeae Genome (TG) and WAGTAIL panels, which include 333 and 403 varieties, respectively. We develop and apply a selection mapping approach, Regression of Alleles on Years (RALLY), in these panels, as well as in simulated populations. RALLY maps loci under sustained historical selection by using a simple logistic model to regress allele counts on years of variety release. To control for drift-induced allele frequency change, we develop a hybrid approach of genomic control and delta control. Within the TG panel, we identify 22 significant RALLY quantitative selection loci (QSLs) and estimate the local heritabilities for 12 traits across these QSLs. By correlating predicted marker effects with RALLY regression estimates, we show that alleles whose frequencies have increased over time are heavily biased toward conferring positive yield effect, but negative effects in flowering time, lodging, plant height and grain protein content. Altogether, our results (1) demonstrate the use of RALLY to identify selected genomic regions while controlling for drift, and (2) reveal key patterns in the historical selection in winter wheat and guide its future breeding.

Genotyping-by-Sequencing Based Molecular Genetic Diversity of Pakistani Bread Wheat (Triticum aestivum L.) Accessions

Spring wheat (Triticum aestivum L.) is one of the most imperative staple food crops, with an annual production of 765 million tons globally to feed ∼40% world population. Genetic diversity in available germplasm is crucial for sustainable wheat improvement to ensure global food security. A diversity panel of 184 Pakistani wheat accessions was genotyped using 123,596 high-quality single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing with 42% of the SNPs mapped on B, 36% on A, and 22% on D sub-genomes of wheat. Chromosome 2B contains the most SNPs (9,126), whereas 4D has the least (2,660) markers. The mean polymorphic information content, genetic diversity, and major allele frequency of the population were 0.157, 0.1844, and 0.87, respectively. Analysis of molecular variance revealed a higher genetic diversity (80%) within the sub-population than among the sub-populations (20%). The genome-wide linkage disequilibrium was 0.34 Mbp for the whole wheat genome. Among the three subgenomes, A has the highest LD decay value (0.29 Mbp), followed by B (0.2 Mbp) and D (0.07 Mbp) genomes, respectively. The results of population structure, principal coordinate analysis, phylogenetic tree, and kinship analysis also divided the whole population into three clusters comprising 31, 33, and 120 accessions in group 1, group 2, and group 3, respectively. All groups were dominated by the local wheat accessions. Estimation of genetic diversity will be a baseline for the selection of breeding parents for mutations and the genome-wide association and marker-assisted selection studies.

Trends of genetic changes uncovered by Env- and Eigen-GWAS in wheat and barley

Variety age and population structure detect novel QTL for yield and adaptation in wheat and barley without the need to phenotype. The process of crop breeding over the last century has delivered new varieties with increased genetic gains, resulting in higher crop performance and yield. However, in many cases, the alleles and genomic regions underpinning this success remain unknown. This is partly due to the difficulty of generating sufficient phenotypic data on large numbers of historical varieties to enable such analyses. Here we demonstrate the ability to circumvent such bottlenecks by identifying genomic regions selected over 100 years of crop breeding using age of a variety as a surrogate for yield. Rather than collecting phenotype data, we deployed 'environmental genome-wide association scans' (EnvGWAS) based on variety age in two of the world's most important crops, wheat and barley, and detected strong signals of selection across both genomes. EnvGWAS identified 16 genomic regions in barley and 10 in wheat with contrasting patterns between spring and winter types of the two crops. To further examine changes in genome structure, we used the genomic relationship matrix of the genotypic data to derive eigenvectors for analysis in EigenGWAS. This detected seven major chromosomal introgressions that contributed to adaptation in wheat. EigenGWAS and EnvGWAS based on variety age avoid costly phenotyping and facilitate the identification of genomic tracts that have been under selection during breeding. Our results demonstrate the potential of using historical cultivar collections coupled with genomic data to identify chromosomal regions under selection and may help guide future plant breeding strategies to maximise the rate of genetic gain and adaptation.

Resistance of the Wheat Cultivar ‘Renan’ to Septoria Leaf Blotch Explained by a Combination of Strain Specific and Strain Non-Specific QTL Mapped on an Ultra-Dense Genetic Map

Quantitative resistance is considered more durable than qualitative resistance as it does not involve major resistance genes that can be easily overcome by pathogen populations, but rather a combination of genes with a lower individual effect. This durability means that quantitative resistance could be an interesting tool for breeding crops that would not systematically require phytosanitary products. Quantitative resistance has yet to reveal all of its intricacies. Here, we delve into the case of the wheat/Septoria tritici blotch (STB) pathosystem. Using a population resulting from a cross between French cultivar Renan, generally resistant to STB, and Chinese Spring, a cultivar susceptible to the disease, we built an ultra-dense genetic map that carries 148,820 single nucleotide polymorphism (SNP) markers. Phenotyping the interaction was done with two different Zymoseptoria tritici strains with contrasted pathogenicities on Renan. A linkage analysis led to the detection of three quantitative trait loci (QTL) related to resistance in Renan. These QTL, on chromosomes 7B, 1D, and 5D, present with an interesting diversity as that on 7B was detected with both fungal strains, while those on 1D and 5D were strain-specific. The resistance on 7B was located in the region of Stb8 and the resistance on 1D colocalized with Stb19. However, the resistance on 5D was new, so further designated Stb20q. Several wall-associated kinases (WAK), nucleotide-binding and leucine-rich repeats (NB-LRR) type, and kinase domain carrying genes were present in the QTL regions, and some of them were expressed during the infection. These results advocate for a role of Stb genes in quantitative resistance and for resistance in the wheat/STB pathosystem being as a whole quantitative and polygenic.

Exploring the legacy of Central European historical winter wheat landraces

Historical wheat landraces are rich sources of genetic diversity offering untapped reservoirs for broadening the genetic base of modern varieties. Using a 20K SNP array, we investigated the accessible genetic diversity in a Central European bread wheat landrace collection with great drought, heat stress tolerance and higher tillering capacity. We discovered distinct differences in the number of average polymorphisms between landraces and modern wheat cultivars, and identified a set of novel rare alleles present at low frequencies in the landrace collection. The detected polymorphisms were unevenly distributed along the wheat genome, and polymorphic markers co-localized with genes of great agronomic importance. The geographical distribution of the inferred Bayesian clustering revealed six genetically homogenous ancestral groups among the collection, where the Central European core bared an admixed background originating from four ancestral groups. We evaluated the effective population sizes (Ne) of the Central European collection and assessed changes in diversity over time, which revealed a dramatic ~ 97% genetic erosion between 1955 and 2015.

A Genome-Wide Association Study Pinpoints Quantitative Trait Genes for Plant Height, Heading Date, Grain Quality, and Yield in Rye (Secale cereale L.)

Rye is the only cross-pollinating Triticeae crop species. Knowledge of rye genes controlling complex-inherited traits is scarce, which, currently, largely disables the genomics assisted introgression of untapped genetic variation from self-incompatible germplasm collections in elite inbred lines for hybrid breeding. We report on the first genome-wide association study (GWAS) in rye based on the phenotypic evaluation of 526 experimental hybrids for plant height, heading date, grain quality, and yield in 2 years and up to 19 environments. We established a cross-validated NIRS calibration model as a fast, effective, and robust analytical method to determine grain quality parameters. We observed phenotypic plasticity in plant height and tiller number as a resource use strategy of rye under drought and identified increased grain arabinoxylan content as a striking phenotype in osmotically stressed rye. We used DArTseq™ as a genotyping-by-sequencing technology to reduce the complexity of the rye genome. We established a novel high-density genetic linkage map that describes the position of almost 19k markers and that allowed us to estimate a low genome-wide LD based on the assessed genetic diversity in elite germplasm. We analyzed the relationship between plant height, heading date, agronomic, as well as grain quality traits, and genotype based on 20k novel single-nucleotide polymorphism markers. In addition, we integrated the DArTseq™ markers in the recently established 'Lo7' reference genome assembly. We identified cross-validated SNPs in 'Lo7' protein-coding genes associated with all traits studied. These include associations of the WUSCHEL-related homeobox transcription factor DWT1 and grain yield, the DELLA protein gene SLR1 and heading date, the Ethylene overproducer 1-like protein gene ETOL1 and thousand-grain weight, protein and starch content, as well as the Lectin receptor kinase SIT2 and plant height. A Leucine-rich repeat receptor protein kinase and a Xyloglucan alpha-1,6-xylosyltransferase count among the cross-validated genes associated with water-extractable arabinoxylan content. This study demonstrates the power of GWAS, hybrid breeding, and the reference genome sequence in rye genetics research to dissect and identify the function of genes shaping genetic diversity in agronomic and grain quality traits of rye. The described links between genetic causes and phenotypic variation will accelerate genomics-enabled rye improvement.

Characterization and Mapping of Spot Blotch in Triticum durum-Aegilops speltoides Introgression Lines Using SNP Markers

Spot blotch (SB) of wheat is emerging as a major threat to successful wheat production in warm and humid areas of the world. SB, also called leaf blight, is caused by Bipolaris sorokiniana, and is responsible for high yield losses in Eastern Gangetic Plains Zone in India. More recently, SB is extending gradually toward cooler, traditional wheat-growing North-Western part of the country which is a major contributor to the national cereal basket. Deployment of resistant cultivars is considered as the most economical and ecologically sound measure to avoid losses due to this disease. In the present study, 89 backcross introgression lines (DSBILs) derived from Triticum durum (cv. PDW274-susceptible) × Aegilops speltoides (resistant) were evaluated against SB for four consecutive years, 2016-2020. Phenotypic evaluation of these lines showed a continuous variation in disease severity indicating that the resistance to SB is certainly quantitative in nature. Phenotypic data of DSBILs were further used for mapping QTLs using SNPs obtained by genotyping by sequencing. To identify QTLs stable across the environments, Best Linear Unbiased Estimates (BLUEs) and Predictions (BLUPs) were used for mapping QTLs based on stepwise regression-based Likelihood Ratio Test (RSTEP-LRT) for additive effect of markers and single marker analysis (SMA). Five QTLs, Q.Sb.pau-2A, Q.Sb.pau-2B, Q.Sb.pau-3B, Q.Sb.pau-5B, and Q.Sb.pau-6A, linked to SB resistance were mapped across chromosomes 2A, 2B, 3B, 5B, and 6A. Genes found adjacent to the SNP markers linked to these QTLs were literature mined to identify possible candidate genes by studying their role in plant pathogenesis. Further, highly resistant DSBIL (DSBIL-13) was selected to cross with a susceptible hexaploidy cultivar (HD3086) generating BC₂F₁ population. The QTL Q.Sb.pau-5B, linked to SNP S5B_703858864, was validated on this BC₂F₁ population and thus, may prove to be a potential diagnostic marker for SB resistance.

Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat

We untangled key regions of the genetic architecture of grain yield (GY) in CIMMYT spring bread wheat by conducting a haplotype-based, genome-wide association study (GWAS), together with an investigation of epistatic interactions using seven large sets of elite yield trials (EYTs) consisting of a total of 6,461 advanced breeding lines. These lines were phenotyped under irrigated and stress environments in seven growing seasons (2011-2018) and genotyped with genotyping-by-sequencing markers. Genome-wide 519 haplotype blocks were constructed, using a linkage disequilibrium-based approach covering 14,036 Mb in the wheat genome. Haplotype-based GWAS identified 7, 4, 10, and 15 stable (significant in three or more EYTs) associations in irrigated (I), mild drought (MD), severe drought (SD), and heat stress (HS) testing environments, respectively. Considering all EYTs and the four testing environments together, 30 stable associations were deciphered with seven hotspots identified on chromosomes 1A, 1B, 2B, 4A, 5B, 6B, and 7B, where multiple haplotype blocks were associated with GY. Epistatic interactions contributed significantly to the genetic architecture of GY, explaining variation of 3.5-21.1%, 3.7-14.7%, 3.5-20.6%, and 4.4- 23.1% in I, MD, SD, and HS environments, respectively. Our results revealed the intricate genetic architecture of GY, controlled by both main and epistatic effects. The importance of these results for practical applications in the CIMMYT breeding program is discussed.