Association mapping in crop plants: opportunities and challenges

GWAS for the identification of introgressed candidate genes of Sinapis alba with increased branching numbers in backcross lines of the allohexaploid Brassica

Plant architecture is a crucial determinant of crop yield. The number of primary (PB) and secondary branches (SB) is particularly significant in shaping the architecture of Indian mustard. In this study, we analyzed a panel of 86 backcross introgression lines (BCILs) derived from the first stable allohexaploid Brassicas with 170 Sinapis alba genome-specific SSR markers to identify associated markers with higher PB and SB through association mapping. The structure analysis revealed three subpopulations, i.e., P1, P2, and P3, in the association panel containing a total of 11, 33, and 42 BCILs, respectively. We identified five novel SSR markers linked to higher PB and SB. Subsequently, we explored the 20 kb up- and downstream regions of these SSR markers to predict candidate genes for improved branching and annotated them through BLASTN. As a result, we predicted 47 complete genes within the 40 kb regions of all trait-linked markers, among which 35 were identified as candidate genes for higher PB and SB numbers in BCILs. These candidate genes were orthologous to ANT, RAMOSUS, RAX, MAX, MP, SEU, REV, etc., branching genes. The remaining 12 genes were annotated for additional roles using BLASTP with protein databases. This study identified five novel S. alba genome-specific SSR markers associated with increased PB and SB, as well as 35 candidate genes contributing to plant architecture through improved branching numbers. To the best of our knowledge, this is the first report of introgressive genes for higher branching numbers in B. juncea from S. alba.

Novel SNP markers and other stress-related genomic regions associated with nitrogen use efficiency in cassava

Cassava productivity is constrained by low soil nitrogen, which is predominant in most cassava-growing regions in the tropics and subtropical agroecology. Improving the low nitrogen tolerance of cassava has become an important breeding objective. The current study aimed to develop cassava varieties with improved nitrogen use efficiency by identifying genomic regions and candidate genes linked to nitrogen use efficiency in cassava. A genome-wide association study (GWAS) was performed using the Genome Association and Prediction Integrated Tool (GAPIT). A panel of 265 diverse cassava genotypes was phenotyped for 10 physiological and agronomic traits under optimum and low-nitrogen regimes. Whole-genome genotyping of these cassava cloneswas performed using the Diversity Arrays Technology (DArTseq) sequencing platform. A total of 68,814 single nucleotide polymorphisms (SNPs) were identified, which were spread across the entire 18 chromosomes of the cassava genome, of which 52 SNPs at various densities were found to be associated with nitrogen use efficiency in cassava and other yield-related traits. The putative genes identified through GWAS, especially those with significant associated SNP markers for NUE and related traits have the potential, if deployed appropriately, to develop cassava varieties with improved nitrogen use efficiency, which would translate to a reduction in the economic and environmental cost of cassava production.

Identification and Genetic Dissection of Resistance to Red Crown Rot Disease in a Diverse Soybean Germplasm Population

Red crown rot (RCR) disease caused by Calonectria ilicicola negatively impacts soybean yield and quality. Unfortunately, the knowledge of the genetic architecture of RCR resistance in soybeans is limited. In this study, 299 diverse soybean accessions were used to explore their genetic diversity and resistance to RCR, and to mine for candidate genes via emergence rate (ER), survival rate (SR), and disease severity (DS) by a multi-locus random-SNP-effect mixed linear model of GWAS. All accessions had brown necrotic lesions on the primary root, with five genotypes identified as resistant. Nine single-nucleotide polymorphism (SNP) markers were detected to underlie RCR response (ER, SR, and DS). Two SNPs colocalized with at least two traits to form a haplotype block which possessed nine genes. Based on their annotation and the qRT-PCR, three genes, namely Glyma.08G074600, Glyma.08G074700, and Glyma.12G043600, are suggested to modulate soybean resistance to RCR. The findings from this study could serve as the foundation for breeding RCR-tolerant soybean varieties, and the candidate genes could be validated to deepen our understanding of soybean response to RCR.

Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.

Genotyping SNPs in lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2) exhibits association with wood density in teak (Tectona grandis L.f.)

BACKGROUND

Teak (Tectona grandis L.f.), an important source of tropical timber with immense economic value, is a highly outcrossing forest tree species. 150 unrelated accessions of teak (Tectona grandis L.f.) plus trees assembled as clones at National Teak Germplasm Bank, Chandrapur, Maharashtra, India was investigated for association mapping of candidate lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2).

METHODS AND RESULTS

The CAD1, MYB1 and MYB2 were amplified using specifically designed primers. The amplified sequences were then sequenced and genotyped for 112 SNPs/11 indels. We evaluated the association between SNPs and wood density in teak accessions using GLM and MLM statistical models, with Bonferroni correction applied. The teak accessions recorded an average wood density of 416.69 kg.m-3 (CV 4.97%) and comprised of three loosely structured admixed sub-populations (K = 3), containing 72.05% genetic variation within sub-populations with low intragenic LD (0-21% SNP pairs) at P < 0.05 and high LD decay (33-934 bp) at R2 = 0.1. GLM and MLM models discounting systematic biases (Q and K matrices) to avoid false discovery revealed five loci at rare variants (MAF 0.003) and three loci at common variants (MAF 0.05) to be significantly (P < 0.05) associated with the wood density. However, the stringent Bonferroni correction (4.06-7.04 × 10-4) yielded only a single associated locus (B1485C/A) from exon of MYB1 transcription factor, contributing to about 10.35% phenotypic variation in wood density trait.

CONCLUSION

Scored SNP locus (B1485C/A) can be developed as a molecular probe for selection of improved planting stock with proven wood density trait for a large-scale teak plantation.

Physiological and Molecular Responses of Pyrus pyraster Seedlings to Salt Treatment Analyzed by miRNA and Cytochrome P450 Gene-Based Markers

Physiological and molecular marker-based changes were studied in the tissues of two-year-old Pyrus pyraster (L.) Burgsd. seedlings under salt treatment. For 60 days, 5 mL of 100 mM NaCl solution was applied to each plant per day to a cumulative volume of 300 mL in the substrate. In response to osmotic stress, the seedlings increased their water use efficiency (WUE) on day 20 of regular NaCl application and maintained a stable net photosynthetic rate (An) per unit area. Under conditions of increasing salinity, the young plants maintained a balanced water regime of the leaf tissues (Ψwl). The seedlings invested mass to their root growth (R/S), retained a substantial portion (72%) of Na+ ions in the roots, and protected their leaves against intoxication and damage. A significant decrease in the leaf gas exchange parameters (gs, E, An) was manifested on day 60 of the experiment when the cumulative NaCl intake was 300 mL per plant. The variability in the reactions of the seedlings to salinity is related to the use of open-pollinated progeny (54 genotypes) in the experiment. Lus-miR168 showed tissue- and genotype-specific genome responses to the applied stress. Polymorphic miRNA-based loci were mostly detected in the root samples on the 20th and 35th days of the experiment. The cumulative effect of the salt treatment was reflected in the predominance of polymorphic loci in the leaves. We can confirm that miRNA-based markers represent a sensitive detection tool for plant stress response on an individual level. The screening and selection of the optimal type of miRNA for this type of research is crucial. The cytochrome P450-Based Analog (PBA) techniques were unable to detect polymorphism among the control and treated seedlings, except for the primer pair CYP2BF+R, where, in the roots of the stressed plant, insertions in the amplicons were obtained. The expression ratios of cytochrome P450 in the salt-stressed plants were higher in the roots in the case of 20/100 mL and in the leaves with higher doses. The observed physiological and molecular responses to salinity reflect the potential of P. pyraster seedlings in adaptation to osmotic and ionic stress.

Multi-environment GWAS identifies genomic regions underlying grain nutrient traits in foxtail millet (Setaria italica)

KEY MESSAGE

A total of 104 foxtail millet accessions were evaluated for 11 nutrients in three environments and 67 high-confidence marker-trait associations (MTAs) were identified. Six SNPs showed pleiotropic effect and associated with two or more nutrients, whereas 24 candidate genes were identified for 28 MTAs involving seven traits. Millets are known for their better nutritional profiles compared to major cereals. Foxtail millet (Setaria italica) is rich in nutrients essential to circumvent malnutrition and hidden hunger. However, the genetic determinants underlying this trait remain elusive. In this context, we evaluated 104 diverse foxtail millet accessions in three different environments (E1, E2, and E3) for 11 nutrients and genotyped with 30K SNPs. The genome-wide association study showed 67 high-confidence (Bonferroni-corrected) marker-trait associations (MTAs) for the nutrients except for phosphorus. Six pleiotropic SNPs were also identified, which were associated with two or more nutrients. Around 24 candidate genes (CGs) were identified for 28 MTAs involving seven nutrients. A total of 17 associated SNPs were present within the gene region, and five (5) were mapped in the exon of the CGs. Significant SNPs, desirable alleles and CGs identified in the present study will be useful in breeding programmes for trait improvement.

Mendelian randomization suggests a causal relationship between gut dysbiosis and thyroid cancer

Background

Alterations in gut microbiota composition and function have been linked to the development and progression of thyroid cancer (TC). However, the exact nature of the causal relationship between them remains uncertain.

Methods

A bidirectional two-sample Mendelian randomization (TSMR) analysis was conducted to assess the causal connection between gut microbiota (18,340 individuals) and TC (6,699 cases combined with 1,613,655 controls) using data from a genome-wide association study (GWAS). The primary analysis used the inverse-variance weighted (IVW) method to estimate the causal effect, with supplementary approaches including the weighted median, weighted mode, simple mode, and MR-Egger. Heterogeneity and pleiotropy were assessed using the Cochrane Q test, MR-Egger intercept test, and MR-PRESSO global test. A reverse TSMR analysis was performed to explore reverse causality.

Results

This study identified seven microbial taxa with significant associations with TC. Specifically, the genus Butyrivibrio (OR: 1.127, 95% CI: 1.008-1.260, p = 0.036), Fusicatenibacter (OR: 1.313, 95% CI: 1.066-1.618, p = 0.011), Oscillospira (OR: 1.240, 95% CI: 1.001-1.536, p = 0.049), Ruminococcus2 (OR: 1.408, 95% CI: 1.158-1.711, p < 0.001), Terrisporobacter (OR: 1.241, 95% CI: 1.018-1.513, p = 0.032) were identified as risk factors for TC, while The genus Olsenella (OR: 0.882, 95% CI: 0.787-0.989, p = 0.031) and Ruminococcaceae UCG004 (OR: 0.719, 95% CI: 0.566-0.914, p = 0.007) were associated with reduced TC risk. The reverse MR analysis found no evidence of reverse causality and suggested that TC may lead to increased levels of the genus Holdemanella (β: 0.053, 95% CI: 0.012~0.094, p = 0.011) and decreased levels of the order Bacillales (β: -0.075, 95% CI: -0.143~-0.006, p = 0.033). No significant bias, heterogeneity, or pleiotropy was detected in this study.

Conclusion

This study suggests a potential causal relationship between gut microbiota and TC, providing new insights into the role of gut microbiota in TC. Further research is needed to explore the underlying biological mechanisms.

Genetic analysis of iron, zinc and grain yield in wheat-Aegilops derivatives using multi-locus GWAS

BACKGROUND

Wheat is a major staple crop and helps to reduce worldwide micronutrient deficiency. Investigating the genetics that control the concentrations of iron (Fe) and zinc (Zn) in wheat is crucial. Hence, we undertook a comprehensive study aimed at elucidating the genomic regions linked to the contents of Fe and Zn in the grain.

METHODS AND RESULTS

We performed the multi-locus genome-wide association (ML-GWAS) using a panel of 161 wheat-Aegilops substitution and addition lines to dissect the genomic regions controlling grain iron (GFeC), and grain zinc (GZnC) contents. The wheat panel was genotyped using 10,825 high-quality SNPs and phenotyped in three different environments (E1-E3) during 2017-2019. A total of 111 marker-trait associations (MTAs) (at p-value < 0.001) were detected that belong to all three sub-genomes of wheat. The highest number of MTAs were identified for GFeC (58), followed by GZnC (44) and yield (9). Further, six stable MTAs were identified for these three traits and also two pleiotropic MTAs were identified for GFeC and GZnC. A total of 1291 putative candidate genes (CGs) were also identified for all three traits. These CGs encode a diverse set of proteins, including heavy metal-associated (HMA), bZIP family protein, AP2/ERF, and protein previously associated with GFeC, GZnC, and grain yield.

CONCLUSIONS

The significant MTAs and CGs pinpointed in this current study are poised to play a pivotal role in enhancing both the nutritional quality and yield of wheat, utilizing marker-assisted selection (MAS) techniques.

Delineation of novel genomic loci and putative candidate genes associated with seed iron and zinc content in lentil (Lens culinaris Medik.)

The use of molecular breeding approaches for development of lentil genotypes biofortified with essential micro-nutrients such as iron and zinc, could serve as a promising solution to address the problem of global malnutrition. Thus, genome-wide association study (GWAS) strategy was adopted in this study to identify the genomic regions associated with seed iron and zinc content in lentil. A panel of 95 diverse lentil genotypes, grown across three different geographical locations and evaluated for seed iron and zinc content, exhibited a wide range of variation. Genotyping-by-sequencing (GBS) analysis of the panel identified 33,745 significant single nucleotide polymorphisms (SNPs) that were distributed across all the 7 lentil chromosomes. Association mapping revealed 23 SNPs associated with seed iron content that were distributed across all the chromosomes except chromosome 3. Similarly, 14 SNPs associated with seed zinc content were also identified that were distributed across chromosomes 1, 2, 4, 5 and 6. Further, 80 genes were identified in the proximity of iron associated markers and 36 genes were identified in the proximity of zinc associated markers. Functional annotation of these genes revealed their putative involvement in iron and zinc metabolism. For seed iron content, two highly significant SNPs were found to be located within two putative candidate genes namely iron-sulfur cluster assembly (ISCA) and flavin binding monooxygenase (FMO) respectively. For zinc content, a highly significant SNP was detected in a gene encoding UPF0678 fatty acid-binding protein. Expression analysis of these genes and their putative interacting partners suggests their involvement in iron and zinc metabolism in lentil. Overall, in this study we have identified markers, putative candidate genes and predicted putative interacting protein partners significantly associated with iron and zinc metabolism that could be utilized in future breeding studies of lentil for nutrient biofortification.

k-mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives

Genome-wide association studies (GWAS) have allowed the discovery of marker-trait associations in crops over recent decades. However, their power is hampered by a number of limitations, with the key one among them being an overreliance on single-nucleotide polymorphisms (SNPs) as molecular markers. Indeed, SNPs represent only one type of genetic variation and are usually derived from alignment to a single genome assembly that may be poorly representative of the population under study. To overcome this, k-mer-based GWAS approaches have recently been developed. k-mer-based GWAS provide a universal way to assess variation due to SNPs, insertions/deletions, and structural variations without having to specifically detect and genotype these variants. In addition, k-mer-based analyses can be used in species that lack a reference genome. However, the use of k-mers for GWAS presents challenges such as data size and complexity, lack of standard tools, and potential detection of false associations. Nevertheless, efforts are being made to overcome these challenges and a general analysis workflow has started to emerge. We identify the priorities for k-mer-based GWAS in years to come, notably in the development of user-friendly programs for their analysis and approaches for linking significant k-mers to sequence variation.

Genome-Wide Association Study of Agronomic and Physiological Traits Related to Drought Tolerance in Potato

Potato (Solanum tuberosum L.) is often considered a water-sensitive crop and its production can be threatened by drought events, making water stress tolerance a trait of increasing interest. In this study, a panel of 144 tetraploid potato genotypes was evaluated for two consecutive years (2019 and 2020) to observe the variation of several physiological traits such as chlorophyll content and fluorescence, stomatal conductance, NDVI, and leaf area and circumference. In addition, agronomic parameters such as yield, tuber fresh weight, tuber number, starch content, dry matter and reducing sugars were determined. GGP V3 Potato array was used to genotype the population, obtaining a total of 18,259 high-quality SNP markers. Marker-trait association was performed using GWASpoly package in R software and Q + K linear mixed models were considered. This approach allowed us to identify eighteen SNP markers significantly associated with the studied traits in both treatments and years, which were related to genes with known functions. Markers related to chlorophyll content and number of tubers under control and stress conditions, and related to stomatal conductance, NDVI, yield and reducing sugar content under water stress, were identified. Although these markers were distributed throughout the genome, the SNPs associated with the traits under control conditions were found mainly on chromosome 11, while under stress conditions they were detected on chromosome 4. These results contribute to the knowledge of the mechanisms of potato tolerance to water stress and are useful for future marker-assisted selection programs.

Genetics of spot blotch resistance in bread wheat (Triticum aestivum L.) using five models for GWAS

Genetic architecture of resistance to spot blotch in wheat was examined using a Genome-Wide Association Study (GWAS) involving an association panel comprising 303 diverse genotypes. The association panel was evaluated at two different locations in India including Banaras Hindu University (BHU), Varanasi (Uttar Pradesh), and Borlaug Institute for South Asia (BISA), Pusa, Samastipur (Bihar) for two consecutive years (2017-2018 and 2018-2019), thus making four environments (E1, BHU 2017-18; E2, BHU 2018-19; E3, PUSA, 2017-18; E4, PUSA, 2018-19). The panel was genotyped for 12,196 SNPs based on DArT-seq (outsourced to DArT Ltd by CIMMYT); these SNPs included 5,400 SNPs, which could not be assigned to individual chromosomes and were therefore, described as unassigned by the vendor. Phenotypic data was recorded on the following three disease-related traits: (i) Area Under Disease Progress Curve (AUDPC), (ii) Incubation Period (IP), and (iii) Lesion Number (LN). GWAS was conducted using each of five different models, which included two single-locus models (CMLM and SUPER) and three multi-locus models (MLMM, FarmCPU, and BLINK). This exercise gave 306 MTAs, but only 89 MTAs (33 for AUDPC, 30 for IP and 26 for LN) including a solitary MTA detected using all the five models and 88 identified using four of the five models (barring SUPER) were considered to be important. These were used for further analysis, which included identification of candidate genes (CGs) and their annotation. A majority of these MTAs were novel. Only 70 of the 89 MTAs were assigned to individual chromosomes; the remaining 19 MTAs belonged to unassigned SNPs, for which chromosomes were not known. Seven MTAs were selected on the basis of minimum P value, number of models, number of environments and location on chromosomes with respect to QTLs reported earlier. These 7 MTAs, which included five main effect MTAs and two for epistatic interactions, were considered to be important for marker-assisted selection (MAS). The present study thus improved our understanding of the genetics of resistance against spot blotch in wheat and provided seven MTAs, which may be used for MAS after due validation.

Genome-wide association mapping of septoria nodorum blotch resistance in Nordic winter and spring wheat collections

A new QTL for SNB, QSnb.nmbu-2AS, was found in both winter and spring wheat panels that can greatly advance SNB resistance breeding Septoria nodorum blotch (SNB), caused by the necrotrophic fungal pathogen Parastagonospora nodorum, is the dominant leaf blotch pathogen of wheat in Norway. Resistance/susceptibility to SNB is a quantitatively inherited trait, which can be partly explained by the interactions between wheat sensitivity loci (Snn) and corresponding P. nodorum necrotrophic effectors (NEs). Two Nordic wheat association mapping panels were assessed for SNB resistance in the field over three to four years: a spring wheat and a winter wheat panel (n = 296 and 102, respectively). Genome-wide association studies found consistent SNB resistance associated with quantitative trait loci (QTL) on eleven wheat chromosomes, and ten of those QTL were common in the spring and winter wheat panels. One robust QTL on the short arm of chromosome 2A, QSnb.nmbu-2AS, was significantly detected in both the winter and spring wheat panels. For winter wheat, using the four years of SNB field severity data in combination with five years of historical data, the effect of QSnb.nmbu-2AS was confirmed in seven of the nine years, while for spring wheat, the effect was confirmed for all tested years including the historical data from 2014 to 2015. However, lines containing the resistant haplotype are rare in both Nordic spring (4.0%) and winter wheat cultivars (15.7%), indicating the potential of integrating this QTL in SNB resistance breeding programs. In addition, clear and significant additive effects were observed by stacking resistant alleles of the detected QTL, suggesting that marker-assisted selection can greatly facilitate SNB resistance breeding.

Genome-wide association analysis to delineate high-quality SNPs for seed micronutrient density in chickpea (Cicer arietinum L.)

Chickpea is the most important nutrient-rich grain legume crop in the world. A diverse core set of 147 chickpea genotypes was genotyped with a Axiom(®)50K CicerSNP array and trait phenotyped in two different environments for four seed micronutrients (Zn, Cu, Fe and Mn). The trait data and high-throughput 50K SNP genotypic data were used for the genome-wide association study (GWAS). The study led to the discovery of genes/QTLs for seed Zn, Cu, Fe and Mn, concentrations in chickpea. The analysis of seed micronutrient data revealed significant differences for all four micronutrient concentrations (P ≤ 0.05). The mean concentrations of seed Zn, Cu, Fe and Mn pooled over the 2 years were 45.9 ppm, 63.8 ppm 146.1 ppm, and 27.0 ppm, respectively. The analysis of results led to the identification of 35 SNPs significantly associated with seed Zn, Cu, Fe and Mn concentrations. Among these 35 marker-trait associations (MTAs), 5 were stable (consistently identified in different environments), 6 were major (explaining more than 15% of the phenotypic variation for an individual trait) and 3 were both major and stable MTAs. A set of 6 MTAs, MTAs (3 for Mn, 2 for Fe, and 1 for Cu) reported by us during the present study have been also reported in the same/almost same genomic regions in earlier studies and therefore declared as validated MTAs. The stable, major and validated MTAs identified during the present study will prove useful in future chickpea molecular breeding programs aimed at enhancing the seed nutrient density of chickpea.

Multi-locus genome-wide association studies reveal novel alleles for flowering time under vernalisation and extended photoperiod in a barley MAGIC population

Key genes controlling flowering and interactions of different photoperiod alleles with various environments were identified in a barley MAGIC population. A new candidate gene for vernalisation requirements was also detected. Optimal flowering time has a major impact on grain yield in crop species, including the globally important temperate cereal crop barley (Hordeum vulgare L.). Understanding the genetics of flowering is a key avenue to enhancing yield potential. Although bi-parental populations were used intensively to map genes controlling flowering, their lack of genetic diversity requires additional work to obtain desired gene combinations in the selected lines, especially when the two parental cultivars did not carry the genes. Multi-parent mapping populations, which use a combination of four or eight parental cultivars, have higher genetic and phenotypic diversity and can provide novel genetic combinations that cannot be achieved using bi-parental populations. This study uses a Multi-parent advanced generation intercross (MAGIC) population from four commercial barley cultivars to identify genes controlling flowering time in different environmental conditions. Genome-wide association studies (GWAS) were performed using 5,112 high-quality markers from Diversity Arrays Technology sequencing (DArT-seq), and Kompetitive allele-specific polymerase chain reaction (KASP) genetic markers were developed. Phenotypic data were collected from fifteen different field trials for three consecutive years. Planting was conducted at various sowing times, and plants were grown with/without additional vernalisation and extended photoperiod treatments. This study detected fourteen stable regions associated with flowering time across multiple environments. GWAS combined with pangenome data highlighted the role of CEN gene in flowering and enabled the prediction of different CEN alleles from parental lines. As the founder lines of the multi-parental population are elite germplasm, the favourable alleles identified in this study are directly relevant to breeding, increasing the efficiency of subsequent breeding strategies and offering better grain yield and adaptation to growing conditions.

Sorghum Association Panel whole-genome sequencing establishes cornerstone resource for dissecting genomic diversity

Association mapping panels represent foundational resources for understanding the genetic basis of phenotypic diversity and serve to advance plant breeding by exploring genetic variation across diverse accessions. We report the whole-genome sequencing (WGS) of 400 sorghum (Sorghum bicolor (L.) Moench) accessions from the Sorghum Association Panel (SAP) at an average coverage of 38× (25-72×), enabling the development of a high-density genomic marker set of 43 983 694 variants including single-nucleotide polymorphisms (approximately 38 million), insertions/deletions (indels) (approximately 5 million), and copy number variants (CNVs) (approximately 170 000). We observe slightly more deletions among indels and a much higher prevalence of deletions among CNVs compared to insertions. This new marker set enabled the identification of several novel putative genomic associations for plant height and tannin content, which were not identified when using previous lower-density marker sets. WGS identified and scored variants in 5-kb bins where available genotyping-by-sequencing (GBS) data captured no variants, with half of all bins in the genome falling into this category. The predictive ability of genomic best unbiased linear predictor (GBLUP) models was increased by an average of 30% by using WGS markers rather than GBS markers. We identified 18 selection peaks across subpopulations that formed due to evolutionary divergence during domestication, and we found six F_st peaks resulting from comparisons between converted lines and breeding lines within the SAP that were distinct from the peaks associated with historic selection. This population has served and continues to serve as a significant public resource for sorghum research and demonstrates the value of improving upon existing genomic resources.

Cytogenetics to functional genomics: six decades journey of Professor P.K. Gupta

We had the fortune of starting our scientific/research careers in the Molecular Biology and Crop Biotechnology Laboratory of Professor P.K. Gupta at Ch. Charan Singh University, Meerut, UP, India. Here, we describe the most important scientific contributions of our beloved mentor in the area of cytotaxonomy, cytogenetics, mutation breeding, quantitative genetics, molecular biology, crop biotechnology and plant genomics, on his 85th birthday. Important contributions made in the development and use of genomics resources including the development and use of different kinds of molecular markers, genetic and physical mapping, quantitative trait locus (QTL) interval mapping, genome-wide association mapping and molecular breeding including marker-assisted selection have been briefly summarized. Efforts have been also made to give readers a glimpse of important contributions in the study of cytology/apomixis of grasses, cytotaxonomic studies in asteraceae/fabaceae, nuclear/repetitive DNA content in Lolium, interspecific/intergeneric relationships involving the genus Hordeum and re-examining taxonomy of the tribe Triticeae.

Mining the Vavilov wheat diversity panel for new sources of adult plant resistance to stripe rust

Multi-year evaluation of the Vavilov wheat diversity panel identified new sources of adult plant resistance to stripe rust. Genome-wide association studies revealed the key genomic regions influencing resistance, including seven novel loci. Wheat stripe rust (YR) caused by Puccinia striiformis f. sp. tritici (Pst) poses a significant threat to global food security. Resistance genes commonly found in many wheat varieties have been rendered ineffective due to the rapid evolution of the pathogen. To identify novel sources of adult plant resistance (APR), 292 accessions from the N.I. Vavilov Institute of Plant Genetic Resources, Saint Petersburg, Russia, were screened for known APR genes (i.e. Yr18, Yr29, Yr46, Yr33, Yr39 and Yr59) using linked polymerase chain reaction (PCR) molecular markers. Accessions were evaluated against Pst (pathotype 134 E16 A + Yr17 + Yr27) at seedling and adult plant stages across multiple years (2014, 2015 and 2016) in Australia. Phenotypic analyses identified 132 lines that potentially carry novel sources of APR to YR. Genome-wide association studies (GWAS) identified 68 significant marker-trait associations (P < 0.001) for YR resistance, representing 47 independent quantitative trait loci (QTL) regions. Fourteen genomic regions overlapped with previously reported Yr genes, including Yr29, Yr56, Yr5, Yr43, Yr57, Yr30, Yr46, Yr47, Yr35, Yr36, Yrxy1, Yr59, Yr52 and YrYL. In total, seven QTL (positioned on chromosomes 1D, 2A, 3A, 3D, 5D, 7B and 7D) did not collocate with previously reported genes or QTL, indicating the presence of promising novel resistance factors. Overall, the Vavilov diversity panel provides a rich source of new alleles which could be used to broaden the genetic bases of YR resistance in modern wheat varieties.

GWAS for main effects and epistatic interactions for grain morphology traits in wheat

In the present study in wheat, GWAS was conducted for identification of marker trait associations (MTAs) for the following six grain morphology traits: (1) grain cross-sectional area (GCSA), (2) grain perimeter (GP), (3) grain length (GL), (4) grain width (GWid), (5) grain length-width ratio (GLWR) and (6) grain form-density (GFD). The data were recorded on a subset of spring wheat reference set (SWRS) comprising 225 diverse genotypes, which were genotyped using 10,904 SNPs and phenotyped for two consecutive years (2017-2018, 2018-2019). GWAS was conducted using five different models including two single-locus models (CMLM, SUPER), one multi-locus model (FarmCPU), one multi-trait model (mvLMM) and a model for Q x Q epistatic interactions. False discovery rate (FDR) [P value -log10(p) ≥ 5] and Bonferroni correction [P value -log10(p) ≥ 6] (corrected p value < 0.05) were applied to eliminate false positives due to multiple testing. This exercise gave 88 main effect and 29 epistatic MTAs after FDR and 13 main effect and 6 epistatic MTAs after Bonferroni corrections. MTAs obtained after Bonferroni corrections were further utilized for identification of 55 candidate genes (CGs). In silico expression analysis of CGs in different tissues at different parts of the seed at different developmental stages was also carried out. MTAs and CGs identified during the present study are useful addition to available resources for MAS to supplement wheat breeding programmes after due validation and also for future strategic basic research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-022-01164-w.

Biparental Crossing and QTL Mapping for Validation of Genome-Wide Association Studies

Association mapping (AM), also known as genome-wide association studies (GWAS), is increasingly being employed in crop plants for the identification of QTL/genes and marker-trait associations (MTAs) in natural populations. Large numbers of such associations have been identified for variety of traits in different crop plants. However, not many of these associations have been used practically in the crop improvement program due to lack of validation. Although there are different ways through which the results of AM/GWAS could be validated, the best approach is to develop a biparental population for the trait of interest. An overview of the steps involved in the validation of results of AM using biparental mapping population in plants is provided in this chapter.

Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies

Genome-wide association studies (GWAS) are effectively applied to detect the marker trait associations (MTAs) using whole genome-wide variants for complex quantitative traits in different crop species. GWAS has been applied in wheat for different quality, biotic and abiotic stresses, and agronomic and yield-related traits. Predictions for marker-trait associations are controlled with the development of better statistical models taking population structure and familial relatedness into account. In this review, we have provided a detailed overview of the importance of association mapping, population design, high-throughput genotyping and phenotyping platforms, advancements in statistical models and multiple threshold comparisons, and recent GWA studies conducted in wheat. The information about MTAs utilized for gene characterization and adopted in breeding programs is also provided. In the literature that we surveyed, as many as 86,122 wheat lines have been studied under various GWA studies reporting 46,940 loci. However, further utilization of these is largely limited. The future breakthroughs in area of genomic selection, multi-omics-based approaches, machine, and deep learning models in wheat breeding after exploring the complex genetic structure with the GWAS are also discussed. This is a most comprehensive study of a large number of reports on wheat GWAS and gives a comparison and timeline of technological developments in this area. This will be useful to new researchers or groups who wish to invest in GWAS.

Understanding population structure and detection of QTLs for curding-related traits in Indian cauliflower by genotyping by sequencing analysis

Curd initiation and development are complex traits and highly responsive for different temperature ranges in cauliflower. The present study was aimed to identify QTLs for eight traits associated with curding behaviour in diverse germplasm of Indian cauliflower. For this, 92 genotypes of cauliflower and 2 each of tropical broccoli and cabbage were genotyped through genotyping by sequencing (GBS). It generated ≈302 million reads (9.1226E + 10 bp) and identified 35,381 SNPs, maximum from chromosome 3 (4735) with a mean value of 3981.1 SNPs. Ts/Tv ratio was 1.74, suggesting transition bias. STRUCTURE analysis revealed delta value of K = 4 and four subpopulations and prominence of population admixture. In total, 121 significant SNPs were detected for eight traits, 38 for Delhi (North Indian plain) and 83 for Barapani (North-East India). Twelve QTLs were detected for traits associated with regulation of curd formation and development, five of which were for marketable curd length, curd width, days to 50% curd harvest and marketable curd weight from Delhi region and seven for curd length, curd width, days to 50% curd harvest, gross plant weight, leaf length, marketable/net curd weight and number of leaves per plant for Barapani area of North East India. The SNPs identified will be useful for development of markers for curding-related traits and their use in breeding varieties with wider curding plasticity.

GWAS for genetics of complex quantitative traits: Genome to pangenome and SNPs to SVs and k-mers

The development of improved methods for genome-wide association studies (GWAS) for genetics of quantitative traits has been an active area of research during the last 25 years. This activity initially started with the use of mixed linear model (MLM), which was variously modified. During the last decade, however, with the availability of high throughput next generation sequencing (NGS) technology, development and use of pangenomes and novel markers including structural variations (SVs) and k-mers for GWAS has taken over as a new thrust area of research. Pangenomes and SVs are now available in humans, livestock, and a number of plant species, so that these resources along with k-mers are being used in GWAS for exploring additional genetic variation that was hitherto not available for analysis. These developments have resulted in significant improvement in GWAS methodology for detection of marker-trait associations (MTAs) that are relevant to human healthcare and crop improvement.

Identifying SSR Markers Related to Seed Fatty Acid Content in Perilla Crop (Perilla frutescens L.)

Perilla seed oil has been attracting attention in South Korea as a health food. Five fatty acids of 100 Perilla accessions were identified as follows: palmitic acid (PA) (5.10-9.13%), stearic acid (SA) (1.70-3.99%), oleic acid (OA) (11.1-21.9%), linoleic acid (LA) (10.2-23.4%), and linolenic acid (LNA) (54.3-75.4%). Additionally, the 100 Perilla accessions were divided into two groups (high or low) based on the total fatty acid content (TFAC). By using an association analysis of 40 simple sequence repeat (SSR) markers and the six Perilla seed oil traits in the 100 Perilla accessions, we detected four SSR markers associated with TFAC, five SSR markers associated with LNA, one SSR marker associated with LA, two SSR markers each associated with OA and PA, and four SSR markers associated with SA. Among these SSR markers, four SSR markers (KNUPF14, KNUPF62, KNUPF72, KNUPF85) were all associated with TFAC and LNA. Moreover, two SSR markers (KNUPF62, KNUPF85) were both associated with TFAC, LNA, and OA. Therefore, these SSR markers are considered to be useful molecular markers for selecting useful accessions related to fatty acid contents in Perilla germplasm and for improving the seed oil quality of Perilla crop through marker-assisted selection (MAS) breeding programs.

Single-trait, multi-locus and multi-trait GWAS using four different models for yield traits in bread wheat

A genome-wide association study (GWAS) for 10 yield and yield component traits was conducted using an association panel comprising 225 diverse spring wheat genotypes. The panel was genotyped using 10,904 SNPs and evaluated for three years (2016-2019), which constituted three environments (E1, E2 and E3). Heritability for different traits ranged from 29.21 to 97.69%. Marker-trait associations (MTAs) were identified for each trait using data from each environment separately and also using BLUP values. Four different models were used, which included three single trait models (CMLM, FarmCPU, SUPER) and one multi-trait model (mvLMM). Hundreds of MTAs were obtained using each model, but after Bonferroni correction, only 6 MTAs for 3 traits were available using CMLM, and 21 MTAs for 4 traits were available using FarmCPU; none of the 525 MTAs obtained using SUPER could qualify after Bonferroni correction. Using BLUP, 20 MTAs were available, five of which also figured among MTAs identified for individual environments. Using mvLMM model, after Bonferroni correction, 38 multi-trait MTAs, for 15 different trait combinations were available. Epistatic interactions involving 28 pairs of MTAs were also available for seven of the 10 traits; no epistatic interactions were available for GNPS, PH, and BYPP. As many as 164 putative candidate genes (CGs) were identified using all the 50 MTAs (CMLM, 3; FarmCPU, 9; mvLMM, 6, epistasis, 21 and BLUP, 11 MTAs), which ranged from 20 (CMLM) to 66 (epistasis) CGs. In-silico expression analysis of CGs was also conducted in different tissues at different developmental stages. The information generated through the present study proved useful for developing a better understanding of the genetics of each of the 10 traits; the study also provided novel markers for marker-assisted selection (MAS) to be utilized for the development of wheat cultivars with improved agronomic traits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01240-1.

Quantitative genetics: pan-genomes, SVs, and k-mers for GWAS

For identification of marker-trait associations (MTAs) for complex traits in animals and plants, thousands of genome-wide association studies (GWAS) were conducted during the past two decades. This involved regular improvement in methodology. Initially, a reference genome and SNPs were used; more recently pan-genomes and the markers structural variations (SVs)/k-mers are also being used.

Genome-wide association analysis permits characterization of Stagonospora nodorum blotch (SNB) resistance in hard winter wheat

Stagonospora nodorum blotch (SNB) is an economically important wheat disease caused by the necrotrophic fungus Parastagonospora nodorum. SNB resistance in wheat is controlled by several quantitative trait loci (QTLs). Thus, identifying novel resistance/susceptibility QTLs is crucial for continuous improvement of the SNB resistance. Here, the hard winter wheat association mapping panel (HWWAMP) comprising accessions from breeding programs in the Great Plains region of the US, was evaluated for SNB resistance and necrotrophic effectors (NEs) sensitivity at the seedling stage. A genome-wide association study (GWAS) was performed to identify single‐nucleotide polymorphism (SNP) markers associated with SNB resistance and effectors sensitivity. We found seven significant associations for SNB resistance/susceptibility distributed over chromosomes 1B, 2AL, 2DS, 4AL, 5BL, 6BS, and 7AL. Two new QTLs for SNB resistance/susceptibility at the seedling stage were identified on chromosomes 6BS and 7AL, whereas five QTLs previously reported in diverse germplasms were validated. Allele stacking analysis at seven QTLs explained the additive and complex nature of SNB resistance. We identified accessions (‘Pioneer-2180’ and ‘Shocker’) with favorable alleles at five of the seven identified loci, exhibiting a high level of resistance against SNB. Further, GWAS for sensitivity to NEs uncovered significant associations for SnToxA and SnTox3, co-locating with previously identified host sensitivity genes (Tsn1 and Snn3). Candidate region analysis for SNB resistance revealed 35 genes of putative interest with plant defense response-related functions. The QTLs identified and validated in this study could be easily employed in breeding programs using the associated markers to enhance the SNB resistance in hard winter wheat.

Genome-wide association study of multiple traits linked to heat tolerance in emmer-derived hexaploid wheat genotypes

Heat stress tolerance in plants is a complex trait controlled by multiple genes of minor effect which are influenced by the environment and this makes breeding and selection complicated. Emmer wheat (Triticum dicoccon Schrank) carries valuable diversity that can be used to improve the heat tolerance of modern bread wheat. A diverse set of emmer-based genotypes was developed by crossing emmer wheat with hexaploid wheat. These materials, along with their hexaploid recurrent parents and commercial cultivars, were evaluated at optimum (E1) and heat stressed (E2) sowing times in the field for three consecutive years (2014-2016). The material was genotyped using the Infinium iSelect SNP 90K SNP Assay. The phenotypic data were combined across years within each sowing time and best linear unbiased estimators calculated for each genotype in each environment. These estimates were used for GWAS analysis. Significant phenotypic and genotypic variation was observed for all traits. A total of 125 and 142 marker-trait associations (MTAs) were identified in E1 and E2, respectively. The highest number of MTAs were observed on the A genome (106), followed by the B (105) and D (56) genomes. MTAs with pleiotropic effects within and across the environments were observed. Many of the MTAs found were reported previously for various traits, and a few significant MTAs under heat stress were new and linked to emmer genome. Genomic regions identified on chromosomes 2B and 3A had a significant positive impact on grain yield under stress with a 7% allelic effect. Genomic regions on chromosomes 1A and 4B contributed 11% and 9% of the variation for thousand kernel weight (TKW) under heat stress respectively. Following fine mapping, these regions could be used for marker-assisted selection to improve heat tolerance in wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01222-3.

Association Mapping in Plants

Quantitative trait loci mapping has become a common practice in crop plants and can be accomplished using either biparental populations following interval mapping or natural populations following the approach of association mapping. Because of its ability to use the natural diversity and to search for functional variants in a broader germplasm, association mapping is becoming popular among researchers. An overview of the different steps involved in association mapping in plants is provided in this chapter.

Genome-wide association study uncovers genomic regions associated with grain iron, zinc and protein content in pearl millet

Pearl millet hybrids biofortified with iron (Fe) and zinc (Zn) promise to be part of a long-term strategy to combat micronutrient malnutrition in the arid and semi-arid tropical (SAT) regions of the world. Biofortification through molecular breeding is the way forward to achieving a rapid trait-based breeding strategy. This genome-wide association study (GWAS) was conducted to identify significant marker-trait associations (MTAs) for Fe, Zn, and protein content (PC) for enhanced biofortification breeding. A diverse panel of 281 advanced inbred lines was evaluated for Fe, Zn, and PC over two seasons. Phenotypic evaluation revealed high variability (Fe: 32–120 mg kg⁻¹, Zn: 19–87 mg kg⁻¹, PC: 8–16%), heritability (h_bs² ≥ 90%) and significantly positive correlation among Fe, Zn and PC (P = 0.01), implying concurrent improvement. Based on the Diversity Arrays Technology (DArT) seq assay, 58,719 highly informative SNPs were filtered for association mapping. Population structure analysis showed six major genetic groups (K = 6). A total of 78 MTAs were identified, of which 18 were associated with Fe, 43 with Zn, and 17 with PC. Four SNPs viz., Pgl04_64673688, Pgl05_135500493, Pgl05_144482656, and Pgl07_101483782 located on chromosomes Pgl04 (1), Pgl05 (2) and Pgl07 (1), respectively were co-segregated for Fe and Zn. Promising genes, ‘Late embryogenesis abundant protein’, ‘Myb domain’, ‘pentatricopeptide repeat’, and ‘iron ion binding’ coded by 8 SNPs were identified. The SNPs/genes identified in the present study presents prospects for genomics assisted biofortification breeding in pearl millet.

Morphological and metabolic profiling of a tropical-adapted potato association panel subjected to water recovery treatment reveals new insights into plant vigor

Potato (Solanum tuberosum L.) is one of the world's most important crops, but it is facing major challenges due to climatic changes. To investigate the effects of intermittent drought on the natural variability of plant morphology and tuber metabolism in a novel potato association panel comprising 258 varieties we performed an augmented block design field study under normal irrigation and under water-deficit and recovery conditions in Ica, Peru. All potato genotypes were profiled for 45 morphological traits and 42 central metabolites via nuclear magnetic resonance. Statistical tests and norm of reaction analysis revealed that the observed variations were trait specific, that is, genotypic versus environmental. Principal component analysis showed a separation of samples as a result of conditional changes. To explore the relational ties between morphological traits and metabolites, correlation-based network analysis was employed, constructing one network for normal irrigation and one network for water-recovery samples. Community detection and difference network analysis highlighted the differences between the two networks, revealing a significant correlational link between fumarate and plant vigor. A genome-wide association study was performed for each metabolic trait. Eleven single nucleotide polymorphism (SNP) markers were associated with fumarate. Gene Ontology analysis of quantitative trait loci regions associated with fumarate revealed an enrichment of genes regulating metabolic processes. Three of the 11 SNPs were located within genes, coding for a protein of unknown function, a RING domain protein and a zinc finger protein ZAT2. Our findings have important implications for future potato breeding regimes, especially in countries suffering from climate change.

Genome-wide association study identifies favorable SNP alleles and candidate genes for frost tolerance in pea

BACKGROUND

Frost is a limiting abiotic stress for the winter pea crop (Pisum sativum L.) and identifying the genetic determinants of frost tolerance is a major issue to breed varieties for cold northern areas. Quantitative trait loci (QTLs) have previously been detected from bi-parental mapping populations, giving an overview of the genome regions governing this trait. The recent development of high-throughput genotyping tools for pea brings the opportunity to undertake genetic association studies in order to capture a higher allelic diversity within large collections of genetic resources as well as to refine the localization of the causal polymorphisms thanks to the high marker density. In this study, a genome-wide association study (GWAS) was performed using a set of 365 pea accessions. Phenotyping was carried out by scoring frost damages in the field and in controlled conditions. The association mapping collection was also genotyped using an Illumina Infinium® BeadChip, which allowed to collect data for 11,366 single nucleotide polymorphism (SNP) markers.

RESULTS

GWAS identified 62 SNPs significantly associated with frost tolerance and distributed over six of the seven pea linkage groups (LGs). These results confirmed 3 QTLs that were already mapped in multiple environments on LG III, V and VI with bi-parental populations. They also allowed to identify one locus, on LG II, which has not been detected yet and two loci, on LGs I and VII, which have formerly been detected in only one environment. Fifty candidate genes corresponding to annotated significant SNPs, or SNPs in strong linkage disequilibrium with the formers, were found to underlie the frost damage (FD)-related loci detected by GWAS. Additionally, the analyses allowed to define favorable haplotypes of markers for the FD-related loci and their corresponding accessions within the association mapping collection.

CONCLUSIONS

This study led to identify FD-related loci as well as corresponding favorable haplotypes of markers and representative pea accessions that might to be used in winter pea breeding programs. Among the candidate genes highlighted at the identified FD-related loci, the results also encourage further attention to the presence of C-repeat Binding Factors (CBF) as potential genetic determinants of the frost tolerance locus on LG VI.

Genetic dissection of thousand-seed weight and fine mapping of cqSW.A03-2 via linkage and association analysis in rapeseed (Brassica napus L.)

KEY MESSAGE: cqSW.A03-2, one of the six identified quantitative trait loci associated with thousand-seed weight in rapeseed, is mapped to a 61.6-kb region on chromosome A03 and corresponds to the candidate gene BnaA03G37960D. Seed weight is an important factor that determines the seed yield of oilseed rape (Brassica napus L.). To elucidate the genetic mechanism of thousand-seed weight (TSW), quantitative trait locus (QTL) mapping was conducted using a double haploid population derived from the cross between an elite line ZY50 and a pol cytoplasmic male sterility restorer line 7-5. The genetic basis of TSW was dissected into six major QTLs. One major QTL denoted as cqSW.A03-2, which explained 8.46-13.70% of the phenotypic variation, was detected across multiple environments. To uncover the genetic basis of cqSW.A03-2, a set of near-isogenic lines were developed. Based on the test of self-pollinated progenies, cqSW.A03-2 was identified as a single Mendelian factor and the ZY50 allele at cqSW.A03-2 showed a positive effect on TSW. Fine mapping delimited the cqSW.A03-2 locus into a 61.6-kb region, and 18 genes within this region were predicted. Candidate gene association analysis and expression analysis indicated that a histidine kinase gene (BnaA03G37960D) is likely to be the candidate gene for the cqSW.A03-2 locus. Our results may contribute to a better understanding of the molecular mechanism of seed weight regulation and promote the breeding program for yield improvement in rapeseed.

Genetic mapping using a wheat multi-founder population reveals a locus on chromosome 2A controlling resistance to both leaf and glume blotch caused by the necrotrophic fungal pathogen Parastagonospora nodorum

KEY MESSAGE

A locus on wheat chromosome 2A was found to control field resistance to both leaf and glume blotch caused by the necrotrophic fungal pathogen Parastagonospora nodorum. The necrotrophic fungal pathogen Parastagonospora nodorum is the causal agent of Septoria nodorum leaf blotch and glume blotch, which are common wheat (Triticum aestivum L.) diseases in humid and temperate areas. Susceptibility to Septoria nodorum leaf blotch can partly be explained by sensitivity to corresponding P. nodorum necrotrophic effectors (NEs). Susceptibility to glume blotch is also quantitative; however, the underlying genetics have not been studied in detail. Here, we genetically map resistance/susceptibility loci to leaf and glume blotch using an eight-founder wheat multiparent advanced generation intercross population. The population was assessed in six field trials across two sites and 4 years. Seedling infiltration and inoculation assays using three P. nodorum isolates were also carried out, in order to compare quantitative trait loci (QTL) identified under controlled conditions with those identified in the field. Three significant field resistance QTL were identified on chromosomes 2A and 6A, while four significant seedling resistance QTL were detected on chromosomes 2D, 5B and 7D. Among these, QSnb.niab-2A.3 for field resistance to both leaf blotch and glume blotch was detected in Norway and the UK. Colocation with a QTL for seedling reactions against culture filtrate from a Norwegian P. nodorum isolate indicated the QTL could be caused by a novel NE sensitivity. The consistency of this QTL for leaf blotch at the seedling and adult plant stages and culture filtrate infiltration was confirmed by haplotype analysis. However, opposite effects for the leaf blotch and glume blotch reactions suggest that different genetic mechanisms may be involved.

Genome-wide association study of pre-harvest sprouting tolerance using a 90K SNP array in common wheat (Triticum aestivum L.)

Three major loci for pre-harvest sprouting tolerance (PHST) were mapped on chromosomes 1AL, 3BS, and 6BL, and two CAPS and one dCAPS markers were validated. Sixteen lines with favorable alleles and increased PHST were identified. Pre-harvest sprouting (PHS) significantly affects wheat grain yield and quality. In the present study, the PHS tolerance (PHST) of 192 wheat varieties (lines) was evaluated by assessment of field sprouting, seed germination index, and period of dormancy in different environments. A high-density Illumina iSelect 90K SNP array was used to genotype the panel. A genome-wide association study (GWAS) based on single- and multi-locus mixed linear models was used to detect loci for PHST. The single-locus model identified 23 loci for PHST (P < 0.0001) and explained 6.0-18.9% of the phenotypic variance. Twenty loci were consistent with known quantitative trait loci (QTLs). Three single-nucleotide polymorphism markers closely linked with three major loci (Qphs.ahau-1A, Qphs.ahau-3B, and Qphs.ahau-6B) on chromosomes 1AL, 3BS, and 6BL, respectively, were converted to two cleaved amplified polymorphic sequences (CAPS) and one derived-CAPS markers, and validated in 374 wheat varieties (lines). The CAPS marker EX06323 for Qphs.ahau-6B co-segregated with a novel major QTL underlying PHST in a recombinant inbred line population raised from the cross Jing 411 × Wanxianbaimaizi. Linear regression showed a clear dependence of PHST on the number of favorable alleles. Sixteen varieties showing an elevated degree of PHST were identified and harbored more than 16 favorable alleles. The multi-locus model detected 39 marker-trait associations for PHST (P < 0.0001), of which five may be novel. Six loci common to the two models were identified. The combination of the two GWAS methods contributes to efficient dissection of the complex genetic mechanism of PHST.

Association Mapping for 24 Traits Related to Protein Content, Gluten Strength, Color, Cooking, and Milling Quality Using Balanced and Unbalanced Data in Durum Wheat [Triticum turgidum L. var. durum (Desf).]

Durum wheat [Triticum durum (Desf).] is mostly used to produce pasta, couscous, and bulgur. The quality of the grain and end-use products determine its market value. However, quality tests are highly resource intensive and almost impossible to conduct in the early generations in the breeding program. Modern genomics-based tools provide an excellent opportunity to genetically dissect complex quality traits to expedite cultivar development using molecular breeding approaches. This study used a panel of 243 cultivars and advanced breeding lines developed during the last 20 years to identify SNPs associated with 24 traits related to nutritional value and quality. Genome-wide association study (GWAS) identified a total of 179 marker-trait associations (MTAs), located in 95 genomic regions belonging to all 14 durum wheat chromosomes. Major and stable QTLs were identified for gluten strength on chromosomes 1A and 1B, and for PPO activity on chromosomes 1A, 2B, 3A, and 3B. As a large amount of unbalance phenotypic data are generated every year on advanced lines in all the breeding programs, the applicability of such a dataset for identification of MTAs remains unclear. We observed that ∼84% of the MTAs identified using a historic unbalanced dataset (belonging to a total of 80 environments collected over a period of 16 years) were also identified in a balanced dataset. This suggests the suitability of historic unbalanced phenotypic data to identify beneficial MTAs to facilitate local-knowledge-based breeding. In addition to providing extensive knowledge about the genetics of quality traits, association mapping identified several candidate markers to assist durum wheat quality improvement through molecular breeding. The molecular markers associated with important traits could be extremely useful in the development of improved quality durum wheat cultivars using marker-assisted selection (MAS).

Candidate genes and genome-wide association study of grain protein content and protein deviation in durum wheat

Stable QTL for grain protein content co-migrating with nitrogen-related genes have been identified by the candidate genes and genome-wide association mapping approaches useful for marker-assisted selection. Grain protein content (GPC) is one of the most important quality traits in wheat, defining the nutritional and end-use properties and rheological characteristics. Over the years, a number of breeding programs have been developed aimed to improving GPC, most of them having been prevented by the negative correlation with grain yield. To overcome this issue, a collection of durum wheat germplasm was evaluated for both GPC and grain protein deviation (GPD) in seven field trials. Fourteen candidate genes involved in several processes related to nitrogen metabolism were precisely located on two high-density consensus maps of common and durum wheat, and six of them were found to be highly associated with both traits. The wheat collection was genotyped using the 90 K iSelect array, and 11 stable quantitative trait loci (QTL) for GPC were detected in at least three environments and the mean across environments by the genome-wide association mapping. Interestingly, seven QTL were co-migrating with N-related candidate genes. Four QTL were found to be significantly associated to increases of GPD, indicating that selecting for GPC could not affect final grain yield per spike. The combined approaches of candidate genes and genome-wide association mapping led to a better understanding of the genetic relationships between grain storage proteins and grain yield per spike, and provided useful information for marker-assisted selection programs.

Genome-Wide Association Study of Major Agronomic Traits in Foxtail Millet (Setaria italica L.) Using ddRAD Sequencing

Foxtail millet (Setaria italica), the second largest cultivated millet crop after pearl millet, is utilized for food and forage globally. Further, it is also considered as a model crop for studying agronomic, nutritional and biofuel traits. In the present study, a genome-wide association study (GWAS) was performed for ten important agronomic traits in 142 foxtail millet core eco-geographically diverse genotypes using 10 K SNPs developed through GBS-ddRAD approach. Number of SNPs on individual chromosome ranged from 844 (chromosome 5) to 2153 (chromosome 8) with an average SNP frequency of 25.9 per Mb. The pairwise linkage disequilibrium (LD) estimated using the squared-allele frequency correlations was found to decay rapidly with the genetic distance of 177 Kb. However, for individual chromosome, LD decay distance ranged from 76 Kb (chromosome 6) to 357 Kb (chromosome 4). GWAS identified 81 MTAs (marker-trait associations) for ten traits across the genome. High confidence MTAs for three important agronomic traits including FLW (flag leaf width), GY (grain yield) and TGW (thousand-grain weight) were identified. Significant pyramiding effect of identified MTAs further supplemented its importance in breeding programs. Desirable alleles and superior genotypes identified in the present study may prove valuable for foxtail millet improvement through marker-assisted selection.

Identification of Ideal Allele Combinations for the Adaptation of Spring Barley to Northern Latitudes

The northwards expansion of barley production requires adaptation to longer days, lower temperatures and stronger winds during the growing season. We have screened 169 lines of the current barley breeding gene pool in the Nordic region with regards to heading, maturity, height, and lodging under different environmental conditions in nineteen field trials over 3 years at eight locations in northern and central Europe. Through a genome-wide association scan we have linked phenotypic differences observed in multi-environment field trials (MET) to single nucleotide polymorphisms (SNP). We have identified an allele combination, only occurring among a few Icelandic lines, that affects heat sum to maturity and requires 214 growing degree days (GDD) less heat sum to maturity than the most common allele combination in the Nordic spring barley gene pool. This allele combination is beneficial in a cold environment, where autumn frost can destroy a late maturing harvest. Despite decades of intense breeding efforts relying heavily on the same germplasm, our results show that there still exists considerable variation within the current breeding gene pool and we identify ideal allele combinations for regional adaptation, which can facilitate the expansion of cereal cultivation even further northwards.

Augmentation of crop productivity through interventions of omics technologies in India: challenges and opportunities

With the continuous increase in the population of developing countries and decline of natural resources, there is an urgent need to qualitatively and quantitatively augment crop productivity by using new tools and technologies for improvement of agriculturally important traits. The new scientific and technological omics-based approaches have enabled us to deal with several issues and challenges faced by modern agricultural system and provided us novel opportunities for ensuring food and nutritional security. Recent developments in sequencing techniques have made available huge amount of genomic and transcriptomic data on model and cultivated crop plants including Arabidopsis thaliana, Oryza sativa, Triticum aestivum etc. The sequencing data along with other data generated through several omics platforms have significantly influenced the disciplines of crop sciences. Gene discovery and expression profiling-based technologies are offering enormous opportunities to the scientific community which can now apply marker-assisted selection technology to assess and enhance diversity in their collected germplasm, introgress essential traits from new sources and investigate genes that control key traits of crop plants. Utilization of omics science and technologies for crop productivity, protection and management has recently been receiving a lot of attention; the majority of the efforts have been put into signifying the possible applications of various omics technologies in crop plant sciences. This article highlights the background of challenges and opportunities for augmentation of crop productivity through interventions of omics technologies in India.

Harnessing the Potential of Forage Legumes, Alfalfa, Soybean, and Cowpea for Sustainable Agriculture and Global Food Security

Substantial improvements in access to food and increased purchasing power are driving many people toward consuming nutrition-rich foods causing an unprecedented demand for protein food worldwide, which is expected to rise further. Forage legumes form an important source of feed for livestock and have potential to provide a sustainable solution for food and protein security. Currently, alfalfa is a commercially grown source of forage and feed in many countries. However, soybean and cowpea also have the potential to provide quality forage and fodder for animal use. The cultivation of forage legumes is under threat from changing climatic conditions, indicating the need for breeding cultivars that can sustain and acclimatize to the negative effects of climate change. Recent progress in genetic and genomic tools have facilitated the identification of quantitative trait loci and genes/alleles that can aid in developing forage cultivars through genomics-assisted breeding. Furthermore, transgenic technology can be utilized to manipulate the genetic makeup of plants to improve forage digestibility for better animal performance. In this article, we assess the genetic potential of three important legume crops, alfalfa, soybean, and cowpea in supplying quality fodder and feed for livestock. In addition, we examine the impact of climate change on forage quality and discuss efforts made in enhancing the adaptation of the plant to the abiotic stress conditions. Subsequently, we suggest the application of integrative approaches to achieve adequate forage production amid the unpredictable climatic conditions.

Genetic dissection of the relationships between grain yield components by genome-wide association mapping in a collection of tetraploid wheats

Increasing grain yield potential in wheat has been a major target of most breeding programs. Genetic advance has been frequently hindered by negative correlations among yield components that have been often observed in segregant populations and germplasm collections. A tetraploid wheat collection was evaluated in seven environments and genotyped with a 90K SNP assay to identify major and stable quantitative trait loci (QTL) for grain yield per spike (GYS), kernel number per spike (KNS) and thousand-kernel weight (TKW), and to analyse the genetic relationships between the yield components at QTL level. The genome-wide association analysis detected eight, eleven and ten QTL for KNS, TKW and GYS, respectively, significant in at least three environments or two environments and the mean across environments. Most of the QTL for TKW and KNS were found located in different marker intervals, indicating that they are genetically controlled independently by each other. Out of eight KNS QTL, three were associated to significant increases of GYS, while the increased grain number of five additional QTL was completely or partially compensated by decreases in grain weight, thus producing no or reduced effects on GYS. Similarly, four consistent and five suggestive TKW QTL resulted in visible increase of GYS, while seven additional QTL were associated to reduced effects in grain number and no effects on GYS. Our results showed that QTL analysis for detecting TKW or KNS alleles useful for improving grain yield potential should consider the pleiotropic effects of the QTL or the association to other QTLs.

Comparative Genome-Wide-Association Mapping Identifies Common Loci Controlling Root System Architecture and Resistance to Aphanomyces euteiches in Pea

Combining plant genetic resistance with architectural traits that are unfavorable to disease development is a promising strategy for reducing epidemics. However, few studies have identified root system architecture (RSA) traits with the potential to limit root disease development. Pea is a major cultivated legume worldwide and has a wide level of natural genetic variability for plant architecture. The root pathogen Aphanomyces euteiches is a major limiting factor of pea crop yield. This study aimed to increase the knowledge on the diversity of loci and candidate genes controlling RSA traits in pea and identify RSA genetic loci associated with resistance to A. euteiches which could be combined with resistance QTL in breeding. A comparative genome wide association (GWA) study of plant architecture and resistance to A. euteiches was conducted at the young plant stage in a collection of 266 pea lines contrasted for both traits. The collection was genotyped using 14,157 SNP markers from recent pea genomic resources. It was phenotyped for ten root, shoot and overall plant architecture traits, as well as three disease resistance traits in controlled conditions, using image analysis. We identified a total of 75 short-size genomic intervals significantly associated with plant architecture and overlapping with 46 previously detected QTL. The major consistent intervals included plant shoot architecture or flowering genes (PsLE, PsTFL1) with putative pleiotropic effects on root architecture. A total of 11 genomic intervals were significantly associated with resistance to A. euteiches confirming several consistent previously identified major QTL. One significant SNP, mapped to the major QTL Ae-Ps7.6, was associated with both resistance and RSA traits. At this marker, the resistance-enhancing allele was associated with an increased total root projected area, in accordance with the correlation observed between resistance and larger root systems in the collection. Seven additional intervals associated with plant architecture overlapped with GWA intervals previously identified for resistance to A. euteiches. This study provides innovative results about genetic interdependency of root disease resistance and RSA inheritance. It identifies pea lines, QTL, closely-linked markers and candidate genes for marker-assisted-selection of RSA loci to reduce Aphanomyces root rot severity in future pea varieties.

Genetic diversity, linkage disequilibrium, and association mapping analyses of Gossypium barbadense L. germplasm

Limited polymorphism and narrow genetic base, due to genetic bottleneck through historic domestication, highlight a need for comprehensive characterization and utilization of existing genetic diversity in cotton germplasm collections. In this study, 288 worldwide Gossypium barbadense L. cotton germplasm accessions were evaluated in two diverse environments (Uzbekistan and USA). These accessions were assessed for genetic diversity, population structure, linkage disequilibrium (LD), and LD-based association mapping (AM) of fiber quality traits using 108 genome-wide simple sequence repeat (SSR) markers. Analyses revealed structured population characteristics and a high level of intra-variability (67.2%) and moderate interpopulation differentiation (32.8%). Eight percent and 4.3% of markers revealed LD in the genome of the G. barbadense at critical values of r2 ≥ 0.1 and r2 ≥ 0.2, respectively. The LD decay was on average 24.8 cM at the threshold of r2 ≥ 0.05. LD retained on average distance of 3.36 cM at the threshold of r2 ≥ 0.1. Based on the phenotypic evaluations in the two diverse environments, 100 marker loci revealed a strong association with major fiber quality traits using mixed linear model (MLM) based association mapping approach. Fourteen marker loci were found to be consistent with previously identified quantitative trait loci (QTLs), and 86 were found to be new unreported marker loci. Our results provide insights into the breeding history and genetic relationship of G. barbadense germplasm and should be helpful for the improvement of cotton cultivars using molecular breeding and omics-based technologies.