Genome-Wide Association Analyses Identify QTL Hotspots for Yield and Component Traits in Durum Wheat Grown under Yield Potential, Drought, and Heat Stress Environments

Exploring the Drought Tolerant Quantitative Trait Loci in Spring Wheat

Drought-induced stress poses a significant challenge to wheat throughout its growth, underscoring the importance of identifying drought-stable quantitative trait loci (QTLs) for enhancing grain yield. Here, we evaluated 18 yield-related agronomic and physiological traits, along with their drought tolerance indices, in a recombinant inbred line population derived from the XC7 × XC21 cross. These evaluations were conducted under both non-stress and drought-stress conditions. Drought stress significantly reduced grain weight per spike and grain yield per plot. Genotyping the recombinant inbred line population using the wheat 90K single nucleotide polymorphism array resulted in the identification of 131 QTLs associated with the 18 traits. Drought stress also exerted negative impacts on grain formation and filling, directly leading to reductions in grain weight per spike and grain yield per plot. Among the identified QTLs, 43 were specifically associated with drought tolerance across the 18 traits, with 6 showing direct linkages to drought tolerance in wheat. These results provide valuable insights into the genetic mechanisms governing wheat growth and development, as well as the traits contributing to the drought tolerance index. Moreover, they serve as a theoretical foundation for the development of new wheat cultivars having exceptional drought tolerance and high yield potentials under both drought-prone and drought-free conditions.

Deciphering the genetic landscape of seedling drought stress tolerance in wheat (Triticum aestivum L.) through genome-wide association studies

Wheat is an important cereal crop constrained by several biotic and abiotic stresses including drought stress. Understating the effect of drought stress and the genetic basis of stress tolerance is important to develop drought resilient, high-yielding wheat cultivars. In this study, we investigated the effects of drought stress on seedling characteristics in an association panel consisting of 198 germplasm lines. Our findings revealed that drought stress had a detrimental effect on all the seedling characteristics under investigation with a maximum effect on shoot length (50.94% reduction) and the minimum effect on germination percentage (7.9% reduction). To gain a deeper understanding, we conducted a genome-wide association analysis using 12,511 single nucleotide polymorphisms (SNPs), which led to the identification of 39 marker-trait associations (MTAs). Of these 39 MTAs, 13 were particularly noteworthy as they accounted for >10% of the phenotypic variance with a LOD score >5. These high-confidence MTAs were further utilized to extract 216 candidate gene (CGs) models within 1 Mb regions. Gene annotation and functional characterization identified 83 CGs with functional relevance to drought stress. These genes encoded the WD40 repeat domain, Myb/SANT-like domain, WSD1-like domain, BTB/POZ domain, Protein kinase domain, Cytochrome P450, Leucine-rich repeat domain superfamily, BURP domain, Calmodulin-binding protein60, Ubiquitin-like domain, etc. Findings from this study hold significant promise for wheat breeders as they provide direct assistance in selecting lines harboring favorable alleles for improved drought stress tolerance. Additionally, the identified SNPs and CGs will enable marker-assisted selection of potential genomic regions associated with enhanced drought stress tolerance in wheat.

Genome-wide dissection and haplotype analysis identified candidate loci for nitrogen use efficiency under drought conditions in winter wheat

Climate change causes extreme conditions like prolonged drought, which results in yield reductions due to its effects on nutrient balances such as nitrogen uptake and utilization by plants. Nitrogen (N) is a crucial nutrient element for plant growth and productivity. Understanding the mechanistic basis of nitrogen use efficiency (NUE) under drought conditions is essential to improve wheat (Triticum aestivum L.) yield. Here, we evaluated the genetic variation of NUE-related traits and photosynthesis response in a diversity panel of 200 wheat genotypes under drought and nitrogen stress conditions to uncover the inherent genetic variation and identify quantitative trait loci (QTLs) underlying these traits. The results revealed significant genetic variations among the genotypes in response to drought stress and nitrogen deprivation. Drought impacted plant performance more than N deprivation due to its effect on water and nutrient uptake. GWAS identified a total of 27 QTLs with a significant main effect on the drought-related traits, while 10 QTLs were strongly associated with the NUE traits. Haplotype analysis revealed two different haplotype blocks within the associated region on chromosomes 1B and 5A. The two haplotypes showed contrasting effects on N uptake and use efficiency traits. The in silico and transcript analyses implicated candidate gene coding for cold shock protein. This gene was the most highly expressed gene under several stress conditions, including drought stress. Upon validation, these QTLs on 1B and 5A could be used as a diagnostic marker for NUE and drought tolerance screening in wheat.

Genomic regions of durum wheat involved in water productivity

Durum wheat is a staple food in the Mediterranean Basin, mostly cultivated under rainfed conditions. As such, the crop is often exposed to moisture stress. Therefore, the identification of genetic factors controlling the capacity of genotypes to convert moisture into grain yield (i.e., water productivity) is quintessential to stabilize production despite climatic variations. A global panel of 384 accessions was tested across 18 Mediterranean environments (in Morocco, Lebanon, and Jordan) representing a vast range of moisture levels. The accessions were assigned to water responsiveness classes, with genotypes 'Responsive to Low Moisture' reaching an average +1.5 kg ha-1 mm-1 yield advantage. Genome wide association studies revealed that six loci explained most of this variation. A second validation panel tested under moisture stress confirmed that carrying the positive allele at three loci on chromosomes 1B, 2A, and 7B generated an average water productivity gain of +2.2 kg ha-1 mm-1. These three loci were tagged by kompetitive allele specific PCR (KASP) markers, and these were used to screen a third independent validation panel composed of elites tested across moisture stressed sites. The three KASP combined predicted up to 10% of the variation for grain yield at 60% accuracy. These loci are now ready for molecular pyramiding and transfer across cultivars to improve the moisture conversion of durum wheat.

Molecular Genetic Diversity of Local and Exotic Durum Wheat Genotypes and Their Combining Ability for Agronomic Traits under Water Deficit and Well-Watered Conditions

Water deficit poses significant environmental stress that adversely affects the growth and productivity of durum wheat. Moreover, projections of climate change suggest an increase in the frequency and severity of droughts, particularly in arid regions. Consequently, there is an urgent need to develop drought-tolerant and high-yielding genotypes to ensure sustained production and global food security in response to population growth. This study aimed to explore the genetic diversity among local and exotic durum wheat genotypes using simple sequence repeat (SSR) markers and, additionally, to explore the combining ability and agronomic performance of assessed durum wheat genotypes and their 28 F1 crosses under normal and drought stress conditions. The investigated SSRs highlighted and confirmed the high genetic variation among the evaluated parental durum wheat genotypes. These diverse eight parental genotypes were consequently used to develop 28 F1s through a diallel mating design. The parental durum genotypes and their developed 28 F1s were assessed under normal and drought stress conditions. The evaluated genotypes were analyzed for their general and specific combining abilities as well as heterosis for agronomic traits under both conditions. The local cultivar Bani-Suef-7 (P8) is maintained as an effective combiner for developing shortened genotypes and improving earliness. Moreover, the local cultivars Bani-Suef-5 (P7) and Bani-Suef-7 (P8) along with the exotic line W1520 (P6) demonstrated excellent general combining ability for improving grain yield and its components under drought stress conditions. Furthermore, valuable specific hybrid combinations, W988 × W994 (P1 × P2), W996 × W1518 (P3 × P5), W1011 × W1520 (P4 × P6), and Bani-Suef-5 × Bani-Suef-7 (P7 × P8), were identified for grain yield and its components under drought stress conditions. The assessed 36 genotypes were grouped according to tolerance indices into five clusters varying from highly drought-sensitive genotypes (group E) to highly drought-tolerant (group A). The genotypes in cluster A (two crosses) followed by thirteen crosses in cluster B displayed higher drought tolerance compared to the other crosses and their parental genotypes. Subsequently, these hybrids could be considered valuable candidates in future durum wheat breeding programs to develop desired segregants under water-deficit conditions. Strong positive relationships were observed between grain yield and number of grains per spike, plant height, and 1000-grain weight under water-deficit conditions. These results highlight the significance of these traits for indirect selection under drought stress conditions, particularly in the early stages of breeding, owing to their convenient measurability.

Genomic regions involved in the control of 1,000-kernel weight in wild relative-derived populations of durum wheat

Terminal drought is one of the most common and devastating climatic stress factors affecting durum wheat (Triticum durum Desf.) production worldwide. The wild relatives of this crop are deemed a vast potential source of useful alleles to adapt to this stress. A nested association mapping (NAM) panel was generated using as a recurrent parent the Moroccan variety 'Nachit' derived from Triticum dicoccoides and known for its large grain size. This was recombined to three top-performing lines derived from T. dicoccoides, T. araraticum, and Aegilops speltoides, for a total of 426 inbred progenies. This NAM was evaluated across eight environments (Syria, Lebanon, and Morocco) experiencing different degrees of terminal moisture stress over two crop seasons. Our results showed that drought stress caused on average 41% loss in yield and that 1,000-kernel weight (TKW) was the most important trait for adaptation to it. Genotyping with the 25K TraitGenetics array resulted in a consensus map of 1,678 polymorphic SNPs, spanning 1,723 cM aligned to the reference 'Svevo' genome assembly. Kinship distinguished the progenies in three clades matching the parent of origin. A total of 18 stable quantitative trait loci (QTLs) were identified as controlling various traits but independent from flowering time. The most significant genomic regions were named Q.ICD.NAM-04, Q.ICD.NAM-14, and Q.ICD.NAM-16. Allelic investigation in a second germplasm panel confirmed that carrying the positive allele at all three loci produced an average TKW advantage of 25.6% when field-tested under drought conditions. The underlying SNPs were converted to Kompetitive Allele-Specific PCR (KASP) markers and successfully validated in a third germplasm set, where they explained up to 19% of phenotypic variation for TKW under moisture stress. These findings confirm the identification of critical loci for drought adaptation derived from wild relatives that can now be readily exploited via molecular breeding.

Combined linkage analysis and association mapping identifies genomic regions associated with yield-related and drought-tolerance traits in wheat (Triticum aestivum L.)

KEY MESSAGE

Combined linkage analysis and association mapping identified genomic regions associated with yield and drought tolerance, providing information to assist breeding for high yield and drought tolerance in wheat. Wheat (Triticum aestivum L.) is one of the most widely grown food crops and provides adequate amounts of protein to support human health. Drought stress is the most important abiotic stress constraining yield during the flowering and grain development periods. Precise targeting of genomic regions underlying yield- and drought tolerance-responsive traits would assist in breeding programs. In this study, two water treatments (well-watered, WW, and rain-fed water stress, WS) were applied, and five yield-related agronomic traits (plant height, PH; spike length, SL; spikelet number per spike, SNPS; kernel number per spike, KNPS; thousand kernel weight, TKW) and drought response values (DRVs) were used to characterize the drought sensitivity of each accession. Association mapping was performed on an association panel of 304 accessions, and linkage analysis was applied to a doubled haploid (DH) population of 152 lines. Eleven co-localized genomic regions associated with yield traits and DRV were identified in both populations. Many previously cloned key genes were located in these regions. In particular, a TKW-associated region on chromosome 2D was identified using both association mapping and linkage analysis and a key candidate gene, TraesCS2D02G142500, was detected based on gene annotation and differences in expression levels. Exonic SNPs were analyzed by sequencing the full length of TraesCS2D02G142500 in the association panel, and a rare haplotype, Hap-2, which reduced TKW to a lesser extent than Hap-1 under drought stress, and the Hap-2 varieties presented drought-insensitive. Altogether, this study provides fundamental insights into molecular targets for high yield and drought tolerance in wheat.

Simultaneous improvement of grain yield and grain protein concentration in durum wheat by using association tests and weighted GBLUP

KEY MESSAGE

Simultaneous improvement for GY and GPC by using GWAS and GBLUP suggested a significant application in durum wheat breeding. Despite the importance of grain protein concentration (GPC) in determining wheat quality, its negative correlation with grain yield (GY) is still one of the major challenges for breeders. Here, a durum wheat panel of 200 genotypes was evaluated for GY, GPC, and their derived indices (GPD and GYD), under eight different agronomic conditions. The plant material was genotyped with the Illumina 25 k iSelect array, and a genome-wide association study was performed. Two statistical models revealed dozens of marker-trait associations (MTAs), each explaining up to 30%. phenotypic variance. Two markers on chromosomes 2A and 6B were consistently identified by both models and were found to be significantly associated with GY and GPC. MTAs identified for phenological traits co-mapped to well-known genes (i.e., Ppd-1, Vrn-1). The significance values (p-values) that measure the strength of the association of each single nucleotide polymorphism marker with the target traits were used to perform genomic prediction by using a weighted genomic best linear unbiased prediction model. The trained models were ultimately used to predict the agronomic performances of an independent durum wheat panel, confirming the utility of genomic prediction, although environmental conditions and genetic backgrounds may still be a challenge to overcome. The results generated through our study confirmed the utility of GPD and GYD to mitigate the inverse GY and GPC relationship in wheat, provided novel markers for marker-assisted selection and opened new ways to develop cultivars through genomic prediction approaches.

Data-driven approaches to improve water-use efficiency and drought resistance in crop plants

With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.

Association Analysis of Tiller-Related Traits with EST-SSR Markers in Psathyrostachys juncea

Psathyrostachys juncea is a long-lived perennial Gramineae grass with dense basal tillers and soft leaves. It is used widely in cold and dry areas of Eurasia and North America to establish grazing pasture and is even used as an ideal plant for revegetation and ecological restoration. Plant architecture, especially tillering traits, is critical for bunch grasses in breeding programs, and these traits in plants are mostly quantitative traits. In this study, the genetic diversity, population structure, and linkage disequilibrium of 480 individual lines were analyzed using 127 pairs of the EST-SSR marker, and a significant association between ten plant-architecture-related traits of P. juncea and molecular markers was found. The results of the genetic diversity analysis showed that the number of observed alleles was 1.957, the number of effective alleles was 1.682, Shannon's information index was 0.554, observed heterozygosity was 0.353, expected heterozygosity was 0.379, and the polymorphism information content was 0.300. A total of 480 individual lines were clustered into five groups based on population genetic structure, principal coordinate analysis, and unweighted pair group method with arithmetic mean analysis (UPGMA). The linkage disequilibrium coefficient (r2) was between 0.00 and 0.68, with an average of 0.04, which indicated a relatively low level of linkage disequilibrium among loci. The results of the association analysis revealed 55 significant marker-trait associations (MTA). Moreover, nine SSR markers were associated with multiple traits. This study provides tools with promising applications in the molecular selection and breeding of P. juncea germplasm.

Genome-wide association mapping in elite winter wheat breeding for yield improvement

Increased grain yield (GY) is the primary breeding target of wheat breeders. We performed the genome-wide association study (GWAS) on 168 elite winter wheat lines from an ongoing breeding program to identify the main determinants of grain yield. Sequencing of Diversity Array Technology fragments (DArTseq) resulted in 19,350 single-nucleotide polymorphism (SNP) and presence-absence variation (PAV) markers. We identified 15 main genomic regions located in ten wheat chromosomes (1B, 2B, 2D, 3A, 3D, 5A, 5B, 6A, 6B, and 7B) that explained from 7.9 to 20.3% of the variation in grain yield and 13.3% of the yield stability. Loci identified in the reduced genepool are important for wheat improvement using marker-assisted selection. We found marker-trait associations between three genes involved in starch biosynthesis and grain yield. Two starch synthase genes (TraesCS2B03G1238800 and TraesCS2D03G1048800) and a sucrose synthase gene (TraesCS3D03G0024300) were found in regions of QGy.rut-2B.2, QGy.rut-2D.1, and QGy.rut-3D, respectively. These loci and other significantly associated SNP markers found in this study can be used for pyramiding favorable alleles in high-yielding varieties or to improve the accuracy of prediction in genomic selection.

Genomics for Yield and Yield Components in Durum Wheat

In recent years, many efforts have been conducted to dissect the genetic basis of yield and yield components in durum wheat thanks to linkage mapping and genome-wide association studies. In this review, starting from the analysis of the genetic bases that regulate the expression of yield for developing new durum wheat varieties, we have highlighted how, currently, the reductionist approach, i.e., dissecting the yield into its individual components, does not seem capable of ensuring significant yield increases due to diminishing resources, land loss, and ongoing climate change. However, despite the identification of genes and/or chromosomal regions, controlling the grain yield in durum wheat is still a challenge, mainly due to the polyploidy level of this species. In the review, we underline that the next-generation sequencing (NGS) technologies coupled with improved wheat genome assembly and high-throughput genotyping platforms, as well as genome editing technology, will revolutionize plant breeding by providing a great opportunity to capture genetic variation that can be used in breeding programs. To date, genomic selection provides a valuable tool for modeling optimal allelic combinations across the whole genome that maximize the phenotypic potential of an individual under a given environment.

Optimizing genomic selection of agricultural traits using K-wheat core collection

The agricultural traits that constitute basic plant breeding information are usually quantitative or complex in nature. This quantitative and complex combination of traits complicates the process of selection in breeding. This study examined the potential of genome-wide association studies (GWAS) and genomewide selection (GS) for breeding ten agricultural traits by using genome-wide SNPs. As a first step, a trait-associated candidate marker was identified by GWAS using a genetically diverse 567 Korean (K)-wheat core collection. The accessions were genotyped using an Axiom^® 35K wheat DNA chip, and ten agricultural traits were determined (awn color, awn length, culm color, culm length, ear color, ear length, days to heading, days to maturity, leaf length, and leaf width). It is essential to sustain global wheat production by utilizing accessions in wheat breeding. Among the traits associated with awn color and ear color that showed a high positive correlation, a SNP located on chr1B was significantly associated with both traits. Next, GS evaluated the prediction accuracy using six predictive models (G-BLUP, LASSO, BayseA, reproducing kernel Hilbert space, support vector machine (SVM), and random forest) and various training populations (TPs). With the exception of the SVM, all statistical models demonstrated a prediction accuracy of 0.4 or better. For the optimization of the TP, the number of TPs was randomly selected (10%, 30%, 50% and 70%) or divided into three subgroups (CC-sub 1, CC-sub 2 and CC-sub 3) based on the subpopulation structure. Based on subgroup-based TPs, better prediction accuracy was found for awn color, culm color, culm length, ear color, ear length, and leaf width. A variety of Korean wheat cultivars were used for validation to evaluate the prediction ability of populations. Seven out of ten cultivars showed phenotype-consistent results based on genomics-evaluated breeding values (GEBVs) calculated by the reproducing kernel Hilbert space (RKHS) predictive model. Our research provides a basis for improving complex traits in wheat breeding programs through genomics assisted breeding. The results of our research can be used as a basis for improving wheat breeding programs by using genomics-assisted breeding.

Validation and marker-assisted selection of DArT-genomic regions associated with wheat yield-related traits under normal and drought conditions

Quantitative trait loci (QTL) is one of the most important steps in marker-assisted selection. Few studies have validated quantitative trait loci for marker-assisted selection of yield traits under drought stress conditions in wheat. A set of 138 highly diverse wheat genotypes were tested under normal and drought stress conditions for 2 years. Plant height, heading date, spike length, grain number per spike, grain yield per spike, and 1000-kernel weight were scored. High genetic variation was found among genotypes in all traits scored under both conditions in the 2 years. The same panel was genotyped using a diversity-array technology (DArT) marker, and a genome-wide association study was performed to find alleles associated with yield traits under all conditions. A set of 191 significant DArT markers were identified in this study. The results of the genome-wide association study revealed eight common markers in wheat that were significantly associated with the same traits under both conditions in the 2 years. Out of the eight markers, seven were located on the D genome except one marker. Four validated markers were located on the 3D chromosome and found in complete linkage disequilibrium. Moreover, these four markers were significantly associated with the heading date under both conditions and the grain yield per spike under drought stress condition in the 2 years. This high-linkage disequilibrium genomic region was located within the TraesCS3D02G002400 gene model. Furthermore, of the eight validated markers, seven were previously reported to be associated with yield traits under normal and drought conditions. The results of this study provided very promising DArT markers that can be used for marker-assisted selection to genetically improve yield traits under normal and drought conditions.

Genome-wide association mapping of genomic regions associated with drought stress tolerance at seedling and reproductive stages in bread wheat

Understanding the genetic architecture of drought stress tolerance in bread wheat at seedling and reproductive stages is crucial for developing drought-tolerant varieties. In the present study, 192 diverse wheat genotypes, a subset from the Wheat Associated Mapping Initiative (WAMI) panel, were evaluated at the seedling stage in a hydroponics system for chlorophyll content (CL), shoot length (SLT), shoot weight (SWT), root length (RLT), and root weight (RWT) under both drought and optimum conditions. Following that, a genome-wide association study (GWAS) was carried out using the phenotypic data recorded during the hydroponics experiment as well as data available from previously conducted multi-location field trials under optimal and drought stress conditions. The panel had previously been genotyped using the Infinium iSelect 90K SNP array with 26,814 polymorphic markers. Using single as well as multi-locus models, GWAS identified 94 significant marker-trait associations (MTAs) or SNPs associated with traits recorded at the seedling stage and 451 for traits recorded at the reproductive stage. The significant SNPs included several novel, significant, and promising MTAs for different traits. The average LD decay distance for the whole genome was approximately 0.48 Mbp, ranging from 0.07 Mbp (chromosome 6D) to 4.14 Mbp (chromosome 2A). Furthermore, several promising SNPs revealed significant differences among haplotypes for traits such as RLT, RWT, SLT, SWT, and GY under drought stress. Functional annotation and in silico expression analysis revealed important putative candidate genes underlying the identified stable genomic regions such as protein kinases, O-methyltransferases, GroES-like superfamily proteins, NAD-dependent dehydratases, etc. The findings of the present study may be useful for improving yield potential, and stability under drought stress conditions.

Genome-Wide Association Study for Grain Protein, Thousand Kernel Weight, and Normalized Difference Vegetation Index in Bread Wheat (Triticum aestivum L.)

Genomic regions governing grain protein content (GPC), 1000 kernel weight (TKW), and normalized difference vegetation index (NDVI) were studied in a set of 280 bread wheat genotypes. The genome-wide association (GWAS) panel was genotyped using a 35K Axiom array and phenotyped in three environments. A total of 26 marker-trait associations (MTAs) were detected on 18 chromosomes covering the A, B, and D subgenomes of bread wheat. The GPC showed the maximum MTAs (16), followed by NDVI (6), and TKW (4). A maximum of 10 MTAs was located on the B subgenome, whereas, 8 MTAs each were mapped on the A and D subgenomes. In silico analysis suggest that the SNPs were located on important putative candidate genes such as NAC domain superfamily, zinc finger RING-H2-type, aspartic peptidase domain, folylpolyglutamate synthase, serine/threonine-protein kinase LRK10, pentatricopeptide repeat, protein kinase-like domain superfamily, cytochrome P450, and expansin. These candidate genes were found to have different roles including regulation of stress tolerance, nutrient remobilization, protein accumulation, nitrogen utilization, photosynthesis, grain filling, mitochondrial function, and kernel development. The effects of newly identified MTAs will be validated in different genetic backgrounds for further utilization in marker-aided breeding.

Genome-wide association studies of Striga resistance in extra-early maturing quality protein maize inbred lines

Identification of genes associated with Striga resistance is invaluable for accelerating genetic gains in breeding for Striga resistance in maize. We conducted a genome-wide association study to identify genomic regions associated with grain yield and other agronomic traits under artificial Striga field infestation. One hundred and forty-one extra-early quality protein maize inbred lines were phenotyped for key agronomic traits. The inbred lines were also genotyped using 49,185 DArTseq markers from which 8,143 were retained for population structure analysis and genome wide-association study. Cluster analysis and population structure revealed the presence of 3 well-defined genetic groups. Using the mixed linear model, 22 SNP markers were identified to be significantly associated with grain yield, Striga damage at 10 weeks after planting, number of emerged Striga plants at 8 and 10 weeks after planting and ear aspect. The identified SNP markers would be useful for breeders for marker-assisted selection to accelerate the genetic enhancement of maize for Striga resistance in sub-Saharan Africa after validation.

Association mapping unravels the genetics controlling seedling drought stress tolerance in winter wheat

Drought is a major constraint in wheat (Triticum aestivum L.) grain yield. The present work aimed to identify quantitative trait nucleotides (QTNs)/ candidate genes influencing drought tolerance-related traits at the seedling stage in 261 accessions of a diverse winter wheat panel. Seeds from three consecutive years were exposed to polyethylene glycol 12% (PEG-6000) and a control treatment (distilled water). The Farm-CPU method was used for the association analysis with 17,093 polymorphic SNPs. PEG treatment reduced shoot length (SL) (-36.3%) and root length (RL) (-11.3%) compared with control treatments, while the coleoptile length (CL) was increased by 11% under drought conditions, suggesting that it might be considered as an indicator of stress-tolerance. Interestingly, we revealed 70 stable QTN across 17 chromosomes. Eight QTNs related to more than one trait were detected on chromosomes 1B, 2A (2), 2B, 2D, 4B, 7A, and 7B and located nearby or inside candidate genes within the linkage disequilibrium (LD) interval. For instance, the QTN on chromosome 2D is located inside the gene TraesCS2D02G133900 that controls the variation of CL_S and SL_C. The allelic variation at the candidate genes showed significant influence on the associated traits, demonstrating their role in controlling the natural variation of multi-traits of drought stress tolerance. The gene expression of these candidate genes under different stress conditions validates their biological role in stress tolerance. Our findings offer insight into understanding the genetic factors and diverse mechanisms in response to water shortage conditions that are important for wheat improvement and adaptation at early developmental stages.

Uncovering the genetic basis for quality traits in the Mediterranean old wheat germplasm and phenotypic and genomic prediction assessment by cross-validation test

The release of new wheat varieties is based on two main characteristics, grain yield and quality, to meet the consumer's demand. Identifying the genetic architecture for yield and key quality traits has wide attention for genetic improvement to meet the global requirement. In this sense, the use of landraces represents an impressive source of natural allelic variation. In this study, a genome-wide association analysis (GWAS) with PCA and kinship matrix was performed to detect QTLs in bread wheat for fifteen quality and agronomic traits using 170 diverse landraces from 24 Mediterranean countries in two years of field trials. A total of 53 QTL hotspots containing 165 significant marker-trait associations (MTAs) were located across the genome for quality and agronomical traits except for chromosome 2D. The major specific QTL hotspots for quality traits were QTL_3B.3 (13 MTAs with a mean PVE of 8.2%) and QTL_4A.3 (15 MTAs, mean PVE of 11.0%), and for yield-related traits were QTL_2B.1 (8 MTAs, mean PVE of 7.4%) and QTL_4B.2 (5 MTAs, mean PVE of 10.0%). A search for candidate genes (CG) identified 807 gene models within the QTL hotspots. Ten of these CGs were expressed specifically in grain supporting the role of identified QTLs in Landraces, associated to bread wheat quality traits and grain formation. A cross-validation approach within the collection was performed to calculate the accuracies of genomic prediction for quality and agronomical traits, ranging from -0.03 to 0.64 for quality and 0.46 to 0.65 for agronomic traits. In addition, five prediction equations using the phenotypic data were developed to predict bread loaf volume in landraces. The prediction ability varied from 0.67 to 0.82 depending on the complexity of the traits considered to predict loaf volume.

Genetic approaches to exploit landraces for improvement of Triticum turgidum ssp. durum in the age of climate change

Addressing the challenges of climate change and durum wheat production is becoming an important driver for food and nutrition security in the Mediterranean area, where are located the major producing countries (Italy, Spain, France, Greece, Morocco, Algeria, Tunisia, Turkey, and Syria). One of the emergent strategies, to cope with durum wheat adaptation, is the exploration and exploitation of the existing genetic variability in landrace populations. In this context, this review aims to highlight the important role of durum wheat landraces as a useful genetic resource to improve the sustainability of Mediterranean agroecosystems, with a focus on adaptation to environmental stresses. We described the most recent molecular techniques and statistical approaches suitable for the identification of beneficial genes/alleles related to the most important traits in landraces and the development of molecular markers for marker-assisted selection. Finally, we outline the state of the art about landraces genetic diversity and signature of selection, already identified from these accessions, for adaptability to the environment.

Marker-trait association analyses revealed major novel QTLs for grain yield and related traits in durum wheat

The growing global demand for wheat for food is rising due to the influence of population growth and climate change. The dissection of complex traits by employing a genome-wide association study (GWAS) allows the identification of DNA markers associated with complex traits to improve the productivity of crops. We used GWAS with 10,045 single nucleotide polymorphism (SNP) markers to search for genomic regions associated with grain yield and related traits based on diverse panels of Ethiopian durum wheat. In Ethiopia, multi-environment trials of the genotypes were carried out at five locations. The genotyping was conducted using the 25k Illumina Wheat SNP array to explore population structure, linkage disequilibrium (LD), and marker-trait associations (MTAs). For GWAS, the multi-locus Fixed and Random Model Circulating Probability Unification (FarmCPU) model was applied. Broad-sense heritability estimates were high, ranging from 0.63 (for grain yield) to 0.97 (for thousand-kernel weight). The population structure based on principal component analysis, and model-based cluster analysis revealed two genetically distinct clusters with limited admixtures. The LD among SNPs declined within the range of 2.02-10.04 Mbp with an average of 4.28 Mbp. The GWAS scan based on the mean performance of the genotypes across the environments identified 44 significant MTAs across the chromosomes. Twenty-six of these MTAs are novel, whereas the remaining 18 were previously reported and confirmed in this study. We also identified candidate genes for the novel loci potentially regulating the traits. Hence, this study highlights the significance of the Ethiopian durum wheat gene pool for improving durum wheat globally. Furthermore, a breeding strategy focusing on accumulating favorable alleles at these loci could improve durum wheat production in the East African highlands and elsewhere.

Discovering Loci for Breeding Prospective and Phenology in Wheat Mediterranean Landraces by Environmental and eigenGWAS

Knowledge of the genetic basis of traits controlling phenology, differentiation patterns, and environmental adaptation is essential to develop new cultivars under climate change conditions. Landrace collections are an appropriate platform to study the hidden variation caused by crop breeding. The use of genome-wide association analysis for phenology, climatic data and differentiation among Mediterranean landraces led to the identification of 651 marker-trait associations that could be grouped in 46 QTL hotspots. A candidate gene analysis using the annotation of the genome sequence of the wheat cultivar 'Chinese Spring' detected 1097 gene models within 33 selected QTL hotspots. From all the gene models, 42 were shown to be differentially expressed (upregulated) under abiotic stress conditions, and 9 were selected based on their levels of expression. Different gene families previously reported for their involvement in different stress responses were found (protein kinases, ras-like GTP binding proteins and ethylene-responsive transcription factors). Finally, the synteny analysis in the QTL hotspots regions among the genomes of wheat and other cereal species identified 23, 21 and 7 ortho-QTLs for Brachypodium, rice and maize, respectively, confirming the importance of these loci.

Mapping QTL for Phenological and Grain-Related Traits in a Mapping Population Derived from High-Zinc-Biofortified Wheat

Genomic regions governing days to heading (DH), days to maturity (DM), plant height (PH), thousand-kernel weight (TKW), and test weight (TW) were investigated in a set of 190 RILs derived from a cross between a widely cultivated wheat-variety, Kachu (DPW-621-50), and a high-zinc variety, Zinc-Shakti. The RIL population was genotyped using 909 DArTseq markers and phenotyped in three environments. The constructed genetic map had a total genetic length of 4665 cM, with an average marker density of 5.13 cM. A total of thirty-seven novel quantitative trait loci (QTL), including twelve for PH, six for DH, five for DM, eight for TKW and six for TW were identified. A set of 20 stable QTLs associated with the expression of DH, DM, PH, TKW, and TW were identified in two or more environments. Three novel pleiotropic genomic-regions harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the DArTseq markers were located on important putative candidate genes such as MLO-like protein, Phytochrome, Zinc finger and RING-type, Cytochrome P450 and pentatricopeptide repeat, involved in the regulation of pollen maturity, the photoperiodic modulation of flowering-time, abiotic-stress tolerance, grain-filling duration, thousand-kernel weight, seed morphology, and plant growth and development. The identified novel QTLs, particularly stable and co-localized QTLs, will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).

Genome-wide association mapping for component traits of drought tolerance in dry beans (Phaseolus vulgaris L.)

Understanding the genetic basis of traits of economic importance under drought stressed and well-watered conditions is important in enhancing genetic gains in dry beans (Phaseolus vulgaris L.). This research aims to: (i) identify markers associated with agronomic and physiological traits for drought tolerance and (ii) identify drought-related putative candidate genes within the mapped genomic regions. An andean and middle-american diversity panel (AMDP) comprising of 185 genotypes was screened in the field under drought stressed and well-watered conditions for two successive seasons. Agronomic and physiological traits, viz., days to 50% flowering (DFW), plant height (PH), days to physiological maturity (DPM), grain yield (GYD), 100-seed weight (SW), leaf temperature (LT), leaf chlorophyll content (LCC) and stomatal conductance (SC) were phenotyped. Principal component and association analysis were conducted using the filtered 9370 Diversity Arrays Technology sequencing (DArTseq) markers. The mean PH, GYD, SW, DPM, LCC and SC of the panel was reduced by 12.1, 29.6, 10.3, 12.6, 28.5 and 62.0%, respectively under drought stressed conditions. Population structure analysis revealed two sub-populations, which corresponded to the andean and middle-american gene pools. Markers explained 0.08-0.10, 0.22-0.23, 0.29-0.32, 0.43-0.44, 0.65-0.66 and 0.69-0.70 of the total phenotypic variability (R2) for SC, LT, PH, GYD, SW and DFW, respectively under drought stressed conditions. For well-watered conditions, R2 varied from 0.08 (LT) to 0.70 (DPM). Overall, 68 significant (p < 10-03) marker-trait associations (MTAs) and 22 putative candidate genes were identified across drought stressed and well-watered conditions. Most of the identified genes had known biological functions related to regulating the response to drought stress. The findings provide new insights into the genetic architecture of drought stress tolerance in common bean. The findings also provide potential candidate SNPs and putative genes that can be utilized in gene discovery and marker-assisted breeding for drought tolerance after validation.

Environment-oriented selection criteria to overcome controversies in breeding for drought resistance in wheat

Wheat is one of the most important cereal crops, representing a fundamental source of calories and protein for the global human population. Drought stress (DS) is a widespread phenomenon, already affecting large wheat-growing areas worldwide, and a major threat for cereal productivity, resulting in consistent losses in average grain yield (GY). Climate change is projected to exacerbate DS incidence and severity by increasing temperatures and changing rainfall patterns. Estimating that wheat production has to substantially increase to guarantee food security to a demographically expanding human population, the need for breeding programs focused on improving wheat drought resistance is manifest. Drought occurrence, in terms of time of appearance, duration, frequency, and severity, along the plant's life cycle varies significantly among different environments and different agricultural years, making it difficult to identify reliable phenological, morphological, and functional traits to be used as effective breeding tools. The situation is further complicated by the presence of confounding factors, e.g., other concomitant abiotic stresses, in an open-field context. Consequently, the relationship between morpho-functional traits and GY under water deficit is often contradictory; moreover, controversies have emerged not only on which traits are to be preferred, but also on how one specific trait should be desired. In this review, we attempt to identify the possible causes of these disputes and propose the most suitable selection criteria in different target environments and, thus, the best trait combinations for breeders in different drought contexts. In fact, an environment-oriented approach could be a valuable solution to overcome controversies in identifying the proper selection criteria for improving wheat drought resistance.

Genome-Wide Association Analysis of Senescence-Related Traits in Maize

Senescence is a programmed process that involves the destruction of the photosynthesis apparatus and the relocation of nutrients to the grain. Identifying senescence-associated genes is essential to adapting varieties for the duration of the cultivation cycle. A genome-wide association study (GWAS) was performed using 400 inbred maize lines with 156,164 SNPs to study the genetic architecture of senescence-related traits and their relationship with agronomic traits. We estimated the timing of senescence to be 45 days after anthesis in the whole plant and specifically in the husks. A list of genes identified in a previous RNAseq experiment as involved in senescence (core senescence genes) was used to propose candidate genes in the vicinity of the significant SNPs. Forty-six QTLs of moderate to high effect were found for senescence traits, including specific QTLs for husk senescence. The allele that delayed senescence primarily increased grain yield and moisture. Seven and one significant SNPs were found in the coding and promoter regions of eight core senescence genes, respectively. These genes could be potential candidates for generating a new variation by genome editing for functional analysis and breeding purposes, particularly Zm00001d014796, which could be responsible for a QTL of senescence found in multiple studies.

Pinpointing genomic loci for drought-induced proline and hydrogen peroxide accumulation in bread wheat under field conditions

BACKGROUND

Proline (Pro) and hydrogen peroxide (H₂O₂) play a critical role in plants during drought adaptation. Genetic mapping for drought-induced Pro and H₂O₂ production under field conditions is very limited in crop plants since their phenotyping with large populations is labor-intensive. A genome-wide association study (GWAS) of a diversity panel comprised of 184 bread wheat cultivars grown in natural field (control) and rain-out shelter (drought) environments was performed to identify candidate loci and genes regulating Pro and H₂O₂ accumulation induced by drought.

RESULTS

The GWAS identified top significant marker-trait associations (MTAs) on 1A and 2A chromosomes, respectively for Pro and H₂O₂ in response to drought. Similarly, MTAs for stress tolerance index (STI) of Pro and H₂O₂ were identified on 5B and 1B chromosomes, respectively. Total 143 significant MTAs were identified including 36 and 71 were linked to drought and 2 and 34 were linked to STI for Pro and H₂O_2, respectively. Next, linkage disequilibrium analysis revealed minor alleles of significant single-markers and haplotypes were associated with higher Pro and H₂O₂ accumulation under drought. Several putative candidate genes for Pro and H₂O₂ content encode proteins with kinase, transporter or protein-binding activities.

CONCLUSIONS

The identified genetic factors associated with Pro and H₂O₂ biosynthesis underlying drought adaptation lay a fundamental basis for functional studies and future marker-assisted breeding programs.

Estimation of soybean yield parameters under lodging conditions using RGB information from unmanned aerial vehicles

The estimation of yield parameters based on early data is helpful for agricultural policymakers and food security. Developments in unmanned aerial vehicle (UAV) platforms and sensor technology help to estimate yields efficiency. Previous studies have been based on less cultivars (<10) and ideal experimental environments, it is not available in practical production. Therefore, the objective of this study was to estimate the yield parameters of soybean (Glycine max (L.) Merr.) under lodging conditions using RGB information. In this study, 17 time point data throughout the soybean growing season in Nanchang, Jiangxi Province, China, were collected, and the vegetation index, texture information, canopy cover, and crop height were obtained by UAV-image processing. After that, partial least squares regression (PLSR), logistic regression (Logistic), random forest regression (RFR), support vector machine regression (SVM), and deep learning neural network (DNN) were used to estimate the yield parameters. The results can be summarized as follows: (1) The most suitable time point to estimate the yield was flowering stage (48 days), which was when most of the soybean cultivars flowered. (2) The multiple data fusion improved the accuracy of estimating the yield parameters, and the texture information has a high potential to contribute to the estimation of yields, and (3) The DNN model showed the best accuracy of training (R²=0.66 rRMSE=32.62%) and validation (R²=0.50, rRMSE=43.71%) datasets. In conclusion, these results provide insights into both best estimate period selection and early yield estimation under lodging condition when using remote sensing.

Systematic trait dissection in oilseed rape provides a comprehensive view, further insight, and exact roadmap for yield determination

Background

Yield is the most important and complex trait that is influenced by numerous relevant traits with very complicated interrelations. While there are a large number of studies on the phenotypic relationship and genetic basis of yield traits, systematic studies with further dissection focusing on yield are limited. Therefore, there is still lack of a comprehensive and in-depth understanding of the determination of yield.

Results

In this study, yield was systematically dissected at the phenotypic, genetic to molecular levels in oilseed rape (Brassica napus L.). The analysis of correlation, network, and principal component for 21 traits in BnaZN-RIL population showed that yield was determined by a complex trait network with key contributors. The analysis of the constructed high-density single nucleotide polymorphism (SNP) linkage map revealed the concentrated distribution of distorted and heterozygous markers, likely due to selection on genes controlling the growth period and yield heterosis. A total of 134 consensus quantitative trait loci (QTL) were identified for 21 traits, of which all were incorporated into an interconnecting QTL network with dozens of hub-QTL. Four representative hub-QTL were further dissected to the target or candidate genes that governed the causal relationships between the relevant traits.

Conclusions

The highly consistent results at the phenotypic, genetic, and molecular dissecting demonstrated that yield was determined by a multilayer composite network that involved numerous traits and genes showing complex up/down-stream and positive/negative regulation. This provides a systematic view, further insight, and exact roadmap for yield determination, which represents a significant advance toward the understanding and dissection of complex traits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13068-022-02134-w.

Unlocking the molecular basis of wheat straw composition and morphological traits through multi-locus GWAS

BACKGROUND

Rapid reductions in emissions from fossil fuel burning are needed to curb global climate change. Biofuel production from crop residues can contribute to reducing the energy crisis and environmental deterioration. Wheat is a renewable source for biofuels owing to the low cost and high availability of its residues. Thus, identifying candidate genes controlling these traits is pivotal for efficient biofuel production. Here, six multi-locus genome-wide association (ML-GWAS) models were applied using 185 tetraploid wheat accessions to detect quantitative trait nucleotides (QTNs) for fifteen traits associated with biomass composition.

RESULTS

Among the 470 QTNs, only 72 identified by at least two models were considered as reliable. Among these latter, 16 also showed a significant effect on the corresponding trait (p.value < 0.05). Candidate genes survey carried out within 4 Mb flanking the QTNs, revealed putative biological functions associated with lipid transfer and metabolism, cell wall modifications, cell cycle, and photosynthesis. Four genes encoded as Cellulose Synthase (CeSa), Anaphase promoting complex (APC/C), Glucoronoxylan 4-O Methyltransferase (GXM) and HYPONASTIC LEAVES1 (HYL1) might be responsible for an increase in cellulose, and natural and acid detergent fiber (NDF and ADF) content in tetraploid wheat. In addition, the SNP marker RFL_Contig3228_2154 associated with the variation in stem solidness (Q.Scsb-3B) was validated through two molecular methods (High resolution melting; HRM and RNase H²-dependent PCR; rhAMP).

CONCLUSIONS

The study provides new insights into the genetic basis of biomass composition traits on tetraploid wheat. The application of six ML-GWAS models on a panel of diverse wheat genotypes represents an efficient approach to dissect complex traits with low heritability such as wheat straw composition. The discovery of genes/genomic regions associated with biomass production and straw quality parameters is expected to accelerate the development of high-yielding wheat varieties useful for biofuel production.

New Genomic Regions Identified for Resistance to Spot Blotch and Terminal Heat Stress in an Interspecific Population of Triticum aestivum and T. spelta

Wheat is one of the most widely grown and consumed food crops in the world. Spot blotch and terminal heat stress are the two significant constraints mainly in the Indo-Gangetic plains of South Asia. The study was undertaken using 185 recombinant lines (RILs) derived from the interspecific hybridization of 'Triticum aestivum (HUW234) × T. spelta (H⁺26)' to reveal genomic regions associated with tolerance to combined stress to spot blotch and terminal heat. Different physiological (NDVI, canopy temperature, leaf chlorophyll) and grain traits (TGW, grain size) were observed under stressed (spot blotch, terminal heat) and non-stressed environments. The mean maturity duration of RILs under combined stress was reduced by 12 days, whereas the normalized difference vegetation index (NDVI) was 46.03%. Similarly, the grain size was depleted under combined stress by 32.23% and thousand kernel weight (TKW) by 27.56% due to spot blotch and terminal heat stress, respectively. The genetic analysis using 6734 SNP markers identified 37 significant loci for the area under the disease progress curve (AUDPC) and NDVI. The genome-wide functional annotation of the SNP markers revealed gene functions such as plant chitinases, NB-ARC and NBS-LRR, and the peroxidase superfamily Cytochrome P450 have a positive role in the resistance through a hypersensitive response. Zinc finger domains, cysteine protease coding gene, F-box protein, ubiquitin, and associated proteins, play a substantial role in the combined stress of spot blotch and terminal heat in bread wheat, according to genomic domains ascribed to them. The study also highlights T. speltoides as a source of resistance to spot blotch and terminal heat tolerance.

Heat Stress Tolerance 2 confers basal heat stress tolerance in allohexaploid wheat (Triticum aestivum L.)

Heat stress substantially reduces the yield potential of wheat (Triticum aestivum L.), one of the most widely cultivated staple crops, and greatly threatens global food security in the context of global warming. However, few studies have explored the heat stress tolerance (HST)-related genetic resources in wheat. Here, we identified and fine-mapped a wheat HST locus, TaHST2, which is indispensable for HST in both the vegetative and reproductive stages of the wheat life cycle. The studied pair of near isogenic lines (NILs) exhibited diverse morphologies under heat stress, based on which we mapped TaHST2 to a 485 kb interval on chromosome arm 4DS. Under heat stress, TaHST2 confers a superior conversion rate from soluble sugars to starch in wheat grains, resulting in faster grain filling and a higher yield potential. A further exploration of genetic resources indicated that TaHST2 underwent strong artificial selection during wheat domestication, suggesting it is an essential locus for basal HST in wheat. Our findings provide deeper insights into the genetic basis of wheat HST and might be useful for global efforts to breed heat-stress-tolerant cultivars.

Chromosome 3A harbors several pleiotropic and stable drought-responsive alleles for photosynthetic efficiency selected through wheat breeding

Water deficit is the most severe stress factor in crop production threatening global food security. In this study, we evaluated the genetic variation in photosynthetic traits among 200 wheat cultivars evaluated under drought and rainfed conditions. Significant genotypic, treatments, and their interaction effects were detected for chlorophyll content and chlorophyll fluorescence parameters. Drought stress reduced the effective quantum yield of photosystem II (YII) from the anthesis growth stage on. Leaf chlorophyll content measured at anthesis growth stages was significantly correlated with YII and non-photochemical quenching under drought conditions, suggesting that high throughput chlorophyll content screening can serve as a good indicator of plant drought tolerance status in wheat. Breeding significantly increased the photosynthetic efficiency as newer released genotypes had higher YII and chlorophyll content than the older ones. GWAS identified a stable drought-responsive QTL on chromosome 3A for YII, while under rainfed conditions, it detected another QTL on chromosome 7A for chlorophyll content across both growing seasons. Molecular analysis revealed that the associated alleles of AX-158576783 (515.889 Mbp) on 3A co-segregates with the NADH-ubiquinone oxidoreductase (TraesCS3A02G287600) gene involved in ATP synthesis coupled electron transport and is proximal to WKRY transcription factor locus. This allele on 3A has been positively selected through breeding and has contributed to increasing the grain yield.

Genome-wide association study for grain yield and component traits in bread wheat (Triticum aestivum L.)

Genomic regions governing days to heading (DH), grain filling duration (GFD), grain number per spike (GNPS), grain weight per spike (GWPS), plant height (PH), and grain yield (GY) were investigated in a set of 280 diverse bread wheat genotypes. The genome-wide association studies (GWAS) panel was genotyped using a 35K Axiom Array and phenotyped in five environments. The GWAS analysis showed a total of 27 Bonferroni-corrected marker-trait associations (MTAs) on 15 chromosomes representing all three wheat subgenomes. The GFD showed the highest MTAs (8), followed by GWPS (7), GY (4), GNPS (3), PH (3), and DH (2). Furthermore, 20 MTAs were identified with more than 10% phenotypic variation. A total of five stable MTAs (AX-95024590, AX-94425015, AX-95210025 AX-94539354, and AX-94978133) were identified in more than one environment and associated with the expression of DH, GFD, GNPS, and GY. Similarly, two novel pleiotropic genomic regions with associated MTAs i.e. AX-94978133 (4D) and AX-94539354 (6A) harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the SNPs were located on important putative candidate genes such as F-box-like domain superfamily, Lateral organ boundaries, LOB, Thioredoxin-like superfamily Glutathione S-transferase, RNA-binding domain superfamily, UDP-glycosyltransferase family, Serine/threonine-protein kinase, Expansin, Patatin, Exocyst complex component Exo70, DUF1618 domain, Protein kinase domain involved in the regulation of grain size, grain number, growth and development, grain filling duration, and abiotic stress tolerance. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).

Association Analysis for Some Biochemical Traits in Wild Relatives of Wheat under Drought Stress Conditions

In the present study, we estimated genetic diversity and population structure in 186 accessions of Triticum and Aegilops species using 24 simple sequence repeat markers (SSR). Furthermore, an association analysis was performed for antioxidant activities, including guaiacol peroxidase (GPX), ascorbate peroxidase (APX), peroxidase (POX), catalase (CAT), and dry matter (DM) under two control and drought stress conditions. Our findings showed that drought treatment significantly decreased DM, whereas activities of all antioxidant enzymes were increased compared to the control conditions. The results of correlation analysis indicated that, under drought stress conditions, all biochemical traits had a positive and significant association with each other and with dry matter. In the molecular section, the results of the analysis of molecular variance (AMOVA) indicated that the molecular variation within species is more than within them. The dendrogram obtained by cluster analysis showed that grouping the investigated accessions was in accordance with their genomic constitutions. The results of association analysis revealed 8 and 9 significant marker–trait associations (MTA) under control and drought stress conditions, respectively. Among identified MTAs, two associations were simultaneously found in both growing conditions. Moreover, several SSR markers were associated with multiple traits across both conditions. In conclusion, our results could provide worthwhile information regarding marker-assisted selection for the activity of antioxidant enzymes in future breeding programs.

Genome-wide association mapping for component traits of drought and heat tolerance in wheat

Identification of marker trait association is a prerequisite for marker-assisted breeding. To find markers linked with traits under heat and drought stress in bread wheat (Triticum aestivum L.), we performed a genome-wide association study (GWAS). GWAS mapping panel used in this study consists of advanced breeding lines from the IARI stress breeding programme produced by pairwise and complex crosses. Phenotyping was done at multi locations namely New Delhi, Karnal, Indore, Jharkhand and Pune with augmented-RCBD design under different moisture and heat stress regimes, namely timely sown irrigated (IR), timely sown restricted irrigated (RI) and late sown (LS) conditions. Yield and its component traits, viz., Days to Heading (DH), Days to Maturity (DM), Normalized Difference Vegetation Index (NDVI), Chlorophyll Content (SPAD), Canopy temperature (CT), Plant Height (PH), Thousand grain weight (TGW), Grain weight per spike (GWPS), Plot Yield (PLTY) and Biomass (BMS) were phenotyped. Analysis of variance and descriptive statistics revealed significant differences among the studied traits. Genotyping was done using the 35k SNP Wheat Breeder's Genotyping Array. Population structure and diversity analysis using filtered 10,546 markers revealed two subpopulations with sufficient diversity. A large whole genome LD block size of 7.15 MB was obtained at half LD decay value. Genome-wide association search identified 57 unique markers associated with various traits across the locations. Twenty-three markers were identified to be stable, among them nine pleiotropic markers were also identified. In silico search of the identified markers against the IWGSC ref genome revealed the presence of a majority of the SNPs at or near the gene coding region. These SNPs can be used for marker-assisted transfer of genes/QTLs after validation to develop climate-resilient cultivars.

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.

Genome-Wide Association Study of Leaf Rust and Stem Rust Seedling and Adult Resistances in Tetraploid Wheat Accessions Harvested in Kazakhstan

Leaf rust (LR) and stem rust (SR) are diseases increasingly impacting wheat production worldwide. Fungal pathogens producing rust diseases in wheat may cause yield losses of up to 50−60%. One of the most effective methods for preventing such losses is the development of resistant cultivars with high yield potential. This goal can be achieved through complex breeding studies, including the identification of key genetic factors controlling rust disease resistance. The objective of this study was to identify sources of tetraploid wheat resistance to LR and SR races, both at the seedling growth stage in the greenhouse and at the adult plant stage in field experiments, under the conditions of the North Kazakhstan region. A panel consisting of 193 tetraploid wheat accessions was used in a genome-wide association study (GWAS) for the identification of quantitative trait loci (QTLs) associated with LR and SR resistance, using 16,425 polymorphic single-nucleotide polymorphism (SNP) markers in the seedling and adult stages of plant development. The investigated panel consisted of seven tetraploid subspecies (Triticum turgidum ssp. durum, ssp. turanicum, ssp. turgidum, ssp. polonicum, ssp. carthlicum, ssp. dicoccum, and ssp. dicoccoides). The GWAS, based on the phenotypic evaluation of the tetraploid collection’s reaction to the two rust species at the seedling (in the greenhouse) and adult (in the field) stages, revealed 38 QTLs (p < 0.001), comprising 17 for LR resistance and 21 for SR resistance. Ten QTLs were associated with the reaction to LR at the seedling stage, while six QTLs were at the adult plant stage and one QTL was at both the seedling and adult stages. Eleven QTLs were associated with SR response at the seedling stage, while nine QTLs were at the adult plant stage and one QTL was at both the seedling and adult stages. A comparison of these results with previous LR and SR studies indicated that 11 of the 38 QTLs are presumably novel loci. The QTLs identified in this work can potentially be used for marker-assisted selection of tetraploid and hexaploid wheat for the breeding of new LR- and SR-resistant cultivars.

Exploiting Wild Emmer Wheat Diversity to Improve Wheat A and B Genomes in Breeding for Heat Stress Adaptation

Wheat is highly sensitive to temperature beyond the optimum. To improve wheat adaptation to heat stress, the best option is to exploit the diversity of wild wheat progenitors. This study aimed to identify germplasm and quantitative trait loci associated with heat stress tolerance from wild emmer wheat diversity. We evaluated a diverse set of multiple derivative lines harboring chromosome segments from nine wild emmer wheat parents under four environments: two optimum environments at Tottori, Japan and Dongola, Sudan, one moderate heat stress environment, and one severe heat stress environment at Wad Medani, Sudan. Genome-wide association analysis was conducted with 13,312 SNP markers. Strong marker-trait associations (MTAs) were identified for chlorophyll content at maturity on chromosomes 1A and 5B: these MTAs explained 28.8 and 26.8% of the variation, respectively. A region on chromosome 3A (473.7-638.4 Mbp) contained MTAs controlling grain yield, under optimum and severe heat stress. Under severe heat stress, regions on chromosomes 3A (590.4-713.3 Mbp) controlled grain yield, biomass, days to maturity and thousand kernel weight, and on 3B (744.0-795.2 Mbp) grain yield and biomass. Heat tolerance efficiency (HTE) was controlled by three MTAs, one each on chromosomes 2A, 2B, and 5A under moderate heat stress and one MTA on chromosome 3A under severe heat stress. Some of the MTAs found here were previously reported, but the new ones originated from the wild emmer wheat genomes. The favorable alleles identified from wild emmer wheat were absent or rare in the elite durum wheat germplasm being bred for heat stress tolerance. This study provides potential genetic materials, alleles, MTAs, and quantitative trait loci for enhancing wheat adaptation to heat stress. The derivative lines studied here could be investigated to enhance other stress tolerance such as drought and salinity.

Indian Wheat Genomics Initiative for Harnessing the Potential of Wheat Germplasm Resources for Breeding Disease-Resistant, Nutrient-Dense, and Climate-Resilient Cultivars

Wheat is one of the major staple cereal food crops in India. However, most of the wheat-growing areas experience several biotic and abiotic stresses, resulting in poor quality grains and reduced yield. To ensure food security for the growing population in India, there is a compelling need to explore the untapped genetic diversity available in gene banks for the development of stress-resistant/tolerant cultivars. The improvement of any crop lies in exploring and harnessing the genetic diversity available in its genetic resources in the form of cultivated varieties, landraces, wild relatives, and related genera. A huge collection of wheat genetic resources is conserved in various gene banks across the globe. Molecular and phenotypic characterization followed by documentation of conserved genetic resources is a prerequisite for germplasm utilization in crop improvement. The National Genebank of India has an extensive and diverse collection of wheat germplasm, comprising Indian wheat landraces, primitive cultivars, breeding lines, and collection from other countries. The conserved germplasm can contribute immensely to the development of wheat cultivars with high levels of biotic and abiotic stress tolerance. Breeding wheat varieties that can give high yields under different stress environments has not made much headway due to high genotypes and environmental interaction, non-availability of truly resistant/tolerant germplasm, and non-availability of reliable markers linked with the QTL having a significant impact on resistance/tolerance. The development of new breeding technologies like genomic selection (GS), which takes into account the G × E interaction, will facilitate crop improvement through enhanced climate resilience, by combining biotic and abiotic stress resistance/tolerance and maximizing yield potential. In this review article, we have summarized different constraints being faced by Indian wheat-breeding programs, challenges in addressing biotic and abiotic stresses, and improving quality and nutrition. Efforts have been made to highlight the wealth of Indian wheat genetic resources available in our National Genebank and their evaluation for the identification of trait-specific germplasm. Promising genotypes to develop varieties of important targeted traits and the development of different genomics resources have also been highlighted.

Association Mapping of Drought Tolerance Indices in Ethiopian Durum Wheat (Triticum turgidum ssp. durum)

Ethiopia is a major producer of durum wheat in sub-Saharan Africa. However, its production is prone to drought stress as it is fully dependent on rain, which is erratic and unpredictable. This study aimed to detect marker-trait associations (MTAs) and quantitative trait loci (QTLs) related to indices. Six drought tolerance indices, i.e., drought susceptibility index (DSI), geometric mean productivity (GMP), relative drought index (RDI), stress tolerance index (STI), tolerance index (TOL), and yield stability index (YSI) were calculated from least-square means (lsmeans) of grain yield (GY) and traits significantly (p < 0.001) correlated with grain yield (GY) under field drought stress (FDS) and field non-stress (FNS) conditions. GY, days to grain filling (DGF), soil plant analysis development (SPAD) chlorophyll meter, seeds per spike (SPS), harvest index (HI), and thousand kernel weight (TKW) were used to calculate DSI, GMP, RDI, STI, TOL, and YSI drought indices. Accessions, DW084, DW082, DZ004, C037, and DW092 were selected as the top five drought-tolerant based on DSI, RDI, TOL, and YSI combined ranking. Similarly, C010, DW033, DW080, DW124-2, and C011 were selected as stable accessions based on GMP and STI combined ranking. A total of 184 MTAs were detected linked with drought indices at -log₁₀p ≥ 4.0,79 of which were significant at a false discovery rate (FDR) of 5%. Based on the linkage disequilibrium (LD, r ² ≥ 0.2), six of the MTAs with a positive effect on GY-GMP were detected on chromosomes 2B, 3B, 4A, 5B, and 6B, explaining 14.72, 10.07, 26.61, 21.16, 21.91, and 22.21% of the phenotypic variance, respectively. The 184 MTAs were clustered into 102 QTLs. Chromosomes 1A, 2B, and 7A are QTL hotspots with 11 QTLs each. These chromosomes play a key role in drought tolerance and respective QTL may be exploited by marker-assisted selection for improving drought stress tolerance in wheat.

Genome-Wide Association Study Identifies Two Loci for Stripe Rust Resistance in a Durum Wheat Panel from Iran

Stripe rust (Puccinia striiformis f. sp. tritici (Pst)) is one of the most devastating fungal diseases of durum wheat (Triticum turgidum L. var. durum Desf.). Races of Pst with new virulence combinations are emerging more regularly on wheat-growing continents, which challenges wheat breeding for resistance. This study aimed to identify and characterize resistance to Pst races based on a genome-wide association study. GWAS is an approach to analyze the associations between a genome-wide set of single-nucleotide polymorphisms (SNPs) and target phenotypic traits. A total of 139 durum wheat accessions from Iran were evaluated at the seedling stage against isolates Pstv-37 and Pstv-40 of Pst and then genotyped using a 15K SNP chip. In total, 230 significant associations were identified across 14 chromosomes, of which 30 were associated with resistance to both isolates. Furthermore, 17 durum wheat landraces showed an immune response against both Pst isolates. The SNP markers and resistant accessions identified in this study may be useful in programs breeding durum wheat for stripe rust resistance.

Combined GWAS and Transcriptome Analyses Provide New Insights Into the Response Mechanisms of Sunflower Against Drought Stress

Sunflower is one of the most important oil crops in the world, and drought stress can severely limit its production and quality. To understand the underlying mechanism of drought tolerance, and identify candidate genes for drought tolerance breeding, we conducted a combined genome-wide association studies (GWAS) and RNA-seq analysis. A total of 226 sunflower inbred lines were collected from different regions of China and other countries. Eight phenotypic traits were evaluated under control and drought stress conditions. Genotyping was performed using a Specific-Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 934.08 M paired-end reads were generated, with an average Q30 of 91.97%. Based on the 243,291 polymorphic SLAF tags, a total of 94,162 high-quality SNPs were identified. Subsequent analysis of linkage disequilibrium (LD) and population structure in the 226 accessions was carried out based on the 94,162 high-quality SNPs. The average LD decay across the genome was 20 kb. Admixture analysis indicated that the entire population most likely originated from 11 ancestors. GWAS was performed using three methods (MLM, FarmCPU, and BLINK) simultaneously. A total of 80 SNPs showed significant associations with the 8 traits (p < 1.062 × 10-6). Next, a total of 118 candidate genes were found. To obtain more reliable candidate genes, RNA-seq analysis was subsequently performed. An inbred line with the highest drought tolerance was selected according to phenotypic traits. RNA was extracted from leaves at 0, 7, and 14 days of drought treatment. A total of 18,922 differentially expressed genes were obtained. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed up-regulated genes were mainly enriched in the branched-chain amino acid catabolic process, while the down-regulated genes were mainly enriched in the photosynthesis-related process. Six DEGs were randomly selected from all DEGs for validation; these genes showed similar patterns in RNA-seq and RT-qPCR analysis, with a correlation coefficient of 0.8167. Through the integration of the genome-wide association study and the RNA-sequencing, 14 candidate genes were identified. Four of them (LOC110885273, LOC110872899, LOC110891369, LOC110920644) were abscisic acid related protein kinases and transcription factors. These genes may play an important role in sunflower drought response and will be used for further study. Our findings provide new insights into the response mechanisms of sunflowers against drought stress and contribute to further genetic breeding.

Multi-locus genome-wide association studies (ML-GWAS) reveal novel genomic regions associated with seedling and adult plant stage leaf rust resistance in bread wheat (Triticum aestivum L.)

Leaf rust is one of the important diseases limiting global wheat production and productivity. To identify quantitative trait nucleotides (QTNs) or genomic regions associated with seedling and adult plant leaf rust resistance, multilocus genome-wide association studies (ML-GWAS) were performed on a panel of 400 diverse wheat genotypes using 35 K single-nucleotide polymorphism (SNP) genotyping assays and trait data of leaf rust resistance. Association analyses using six multi-locus GWAS models revealed a set of 201 significantly associated QTNs for seedling and 65 QTNs for adult plant resistance (APR), explaining 1.98-31.72% of the phenotypic variation for leaf rust. Among these QTNs, 51 reliable QTNs for seedling and 15 QTNs for APR were consistently detected in at least two GWAS models and were considered reliable QTNs. Three genomic regions were pleiotropic, each controlling two to three pathotype-specific seedling resistances to leaf rust. We also identified candidate genes, such as leucine-rich repeat receptor-like (LRR) protein kinases, P-loop containing nucleoside triphosphate hydrolase and serine-threonine/tyrosine-protein kinases (STPK), which have a role in pathogen recognition and disease resistance linked to the significantly associated genomic regions. The QTNs identified in this study can prove useful in wheat molecular breeding programs aimed at enhancing resistance to leaf rust and developing next-generation leaf rust-resistant varieties.

Bringing more players into play: Leveraging stress in genome wide association studies

In order to meet the demand of the burgeoning human population as well as to adapt crops to the enhanced abiotic and biotic stress caused by the global climatic change, breeders focus on identifying valuable genes to improve both crop stress tolerance and crop quality. Recently, with the development of next-generation sequencing methods, millions of high quality single-nucleotide polymorphisms (SNPs) have been made available and genome-wide association studies (GWAS) are widely used in crop improvement studies to identify the associations between genetic variants of genomes and relevant crop agronomic traits. Here, we review classic cases of use of GWAS to identify genetic variants associated with valuable traits such as geographic adaptation, crop quality and metabolites. We discuss the power of stress GWAS to identify further associations including those with genes that are not, or only lowly, expressed during optimal growth conditions. Finally, we emphasize recent demonstrations of the efficiency and accuracy of time-resolved dynamic stress GWAS and GWAS based on genomic gene expression and structural variations, which can be applied to resolve more comprehensively the genetic regulation mechanisms of complex traits.

Impacts, Tolerance, Adaptation, and Mitigation of Heat Stress on Wheat under Changing Climates

Heat stress (HS) is one of the major abiotic stresses affecting the production and quality of wheat. Rising temperatures are particularly threatening to wheat production. A detailed overview of morpho-physio-biochemical responses of wheat to HS is critical to identify various tolerance mechanisms and their use in identifying strategies to safeguard wheat production under changing climates. The development of thermotolerant wheat cultivars using conventional or molecular breeding and transgenic approaches is promising. Over the last decade, different omics approaches have revolutionized the way plant breeders and biotechnologists investigate underlying stress tolerance mechanisms and cellular homeostasis. Therefore, developing genomics, transcriptomics, proteomics, and metabolomics data sets and a deeper understanding of HS tolerance mechanisms of different wheat cultivars are needed. The most reliable method to improve plant resilience to HS must include agronomic management strategies, such as the adoption of climate-smart cultivation practices and use of osmoprotectants and cultured soil microbes. However, looking at the complex nature of HS, the adoption of a holistic approach integrating outcomes of breeding, physiological, agronomical, and biotechnological options is required. Our review aims to provide insights concerning morpho-physiological and molecular impacts, tolerance mechanisms, and adaptation strategies of HS in wheat. This review will help scientific communities in the identification, development, and promotion of thermotolerant wheat cultivars and management strategies to minimize negative impacts of HS.

'Omics' approaches in developing combined drought and heat tolerance in food crops

Global climate change will significantly increase the intensity and frequency of hot, dry days. The simultaneous occurrence of drought and heat stress is also likely to increase, influencing various agronomic characteristics, such as biomass and other growth traits, phenology, and yield-contributing traits, of various crops. At the same time, vital physiological traits will be seriously disrupted, including leaf water content, canopy temperature depression, membrane stability, photosynthesis, and related attributes such as chlorophyll content, stomatal conductance, and chlorophyll fluorescence. Several metabolic processes contributing to general growth and development will be restricted, along with the production of reactive oxygen species (ROS) that negatively affect cellular homeostasis. Plants have adaptive defense strategies, such as ROS-scavenging mechanisms, osmolyte production, secondary metabolite modulation, and different phytohormones, which can help distinguish tolerant crop genotypes. Understanding plant responses to combined drought/heat stress at various organizational levels is vital for developing stress-resilient crops. Elucidating the genomic, proteomic, and metabolic responses of various crops, particularly tolerant genotypes, to identify tolerance mechanisms will markedly enhance the continuing efforts to introduce combined drought/heat stress tolerance. Besides agronomic management, genetic engineering and molecular breeding approaches have great potential in this direction.

Genetic characterization and genome-wide association mapping for stem rust resistance in spring bread wheat

Background

Emerging wheat stem rust races have become a major threat to global wheat production. Finding additional loci responsible for resistance to these races and incorporating them into currently cultivated varieties is the most economic and environmentally sound strategy to combat this problem. Thus, this study was aimed at characterizing the genetic diversity and identifying the genetic loci conferring resistance to the stem rust of wheat. To accomplish this, 245 elite lines introduced from the International Center for Agricultural Research in the Dry Areas (ICARDA) were evaluated under natural stem rust pressure in the field at the Debre Zeit Agricultural Research Center, Ethiopia. The single nucleotide polymorphisms (SNP) marker data was retrieved from a 15 K SNP wheat array. A mixed linear model was used to investigate the association between SNP markers and the best linear unbiased prediction (BLUP) values of the stem rust coefficient of infection (CI).

Results

Phenotypic analysis revealed that 46% of the lines had a coefficient of infection (CI) in a range of 0 to 19. Genome-wide average values of 0.38, 0.20, and 0.71 were recorded for Nei’s gene diversity, polymorphism information content, and major allele frequency, respectively. A total of 46 marker-trait associations (MTAs) encompassed within eleven quantitative trait loci (QTL) were detected on chromosomes 1B, 3A, 3B, 4A, 4B, and 5A for CI. Two major QTLs with –log₁₀ (p) ≥ 4 (EWYP1B.1 and EWYP1B.2) were discovered on chromosome 1B.

Conclusions

This study identified several novel markers associated with stem rust resistance in wheat with the potential to facilitate durable rust resistance development through marker-assisted selection. It is recommended that the resistant wheat genotypes identified in this study be used in the national wheat breeding programs to improve stem rust resistance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01030-4.

Interpretation of Manhattan Plots and Other Outputs of Genome-Wide Association Studies

With increasing marker density, estimation of recombination rate between a marker and a causal mutation using linkage analysis becomes less important. Instead, linkage disequilibrium (LD) becomes the major indicator for gene mapping through genome-wide association studies (GWAS). In addition to the linkage between the marker and the causal mutation, many other factors may contribute to the LD, including population structure and cryptic relationships among individuals. As statistical methods and software evolve to improve statistical power and computing speed in GWAS, the corresponding outputs must also evolve to facilitate the interpretation of input data, the analytical process, and final association results. In this chapter, our descriptions focus on (1) considerations in creating a Manhattan plot displaying the strength of LD and locations of markers across a genome; (2) criteria for genome-wide significance threshold and the different appearance of Manhattan plots in single-locus and multiple-locus models; (3) exploration of population structure and kinship among individuals; (4) quantile-quantile (QQ) plot; (5) LD decay across the genome and LD between the associated markers and their neighbors; (6) exploration of individual and marker information on Manhattan and QQ plots via interactive visualization using HTML. The ultimate objective of this chapter is to help users to connect input data to GWAS outputs to balance power and false positives, and connect GWAS outputs to the selection of candidate genes using LD extent.