Association mapping for frost tolerance using multi-parent advanced generation inter-cross (MAGIC) population in faba bean (Vicia faba L.)

New Insights into the Genetic Basis of Lysine Accumulation in Rice Revealed by Multi-Model GWAS

Lysine is an essential amino acid that cannot be synthesized in humans. Rice is a global staple food for humans but has a rather low lysine content. Identification of the quantitative trait nucleotides (QTNs) and genes underlying lysine content is crucial to increase lysine accumulation. In this study, five grain and three leaf lysine content datasets and 4,630,367 single nucleotide polymorphisms (SNPs) of 387 rice accessions were used to perform a genome-wide association study (GWAS) by ten statistical models. A total of 248 and 71 common QTNs associated with grain/leaf lysine content were identified. The accuracy of genomic selection/prediction RR-BLUP models was up to 0.85, and the significant correlation between the number of favorable alleles per accession and lysine content was up to 0.71, which validated the reliability and additive effects of these QTNs. Several key genes were uncovered for fine-tuning lysine accumulation. Additionally, 20 and 30 QTN-by-environment interactions (QEIs) were detected in grains/leaves. The QEI-sf0111954416 candidate gene LOC_Os01g21380 putatively accounted for gene-by-environment interaction was identified in grains. These findings suggested the application of multi-model GWAS facilitates a better understanding of lysine accumulation in rice. The identified QTNs and genes hold the potential for lysine-rich rice with a normal phenotype.

Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.

Genome-wide association mapping highlights candidate genes and immune genotypes for net blotch and powdery mildew resistance in barley

Net blotch (NB) and powdery mildew (PM) are major barley diseases with the potential to cause a dramatic loss in grain yield. Breeding for resistant barley genotypes in combination with identifying candidate resistant genes will accelerate the genetic improvement for resistance to NB and PM. To address this challenge, a set of 122 highly diverse barley genotypes from 34 countries were evaluated for NB and PM resistance under natural infection for in two growing seasons. Moreover, four yield traits; plant height (Ph), spike length (SL), spike weight (SW), and the number of spikelets per spike (NOS) were recorded. High genetic variation was found among genotypes in all traits scored in this study. No significant phenotypic correlation was found in the resistance between PM and NB. Immune genotypes for NB and PM were identified. A total of 21 genotypes were immune to both diseases. Of the 21 genotypes, the German genotype HOR_9570 was selected as the most promising genotype that can be used for future breeding programs. Furthermore, a genome-wide association study (GWAS) was used to identify resistant alleles to PM and NB. The results of GWAS revealed a set of 14 and 25 significant SNPs that were associated with increased resistance to PM and NB, respectively. This study provided very important genetic resources that are highly resistant to the Egyptian PM and NB pathotypes and revealed SNP markers that can be utilized to genetically improve resistance to PM and NB.

Reference genome facilitates trait development for faba beans

Reference genomes facilitate trait improvement by aiding in the elucidation of causal genetic elements. Thanks to the recent release of a reference sequence for the faba bean, breeders and geneticists are poised to accelerate precision breeding and genetic improvement of this important crop.

Discovering useful genetic variation in the seed parent gene pool for sorghum improvement

Multi-parent populations contain valuable genetic material for dissecting complex, quantitative traits and provide a unique opportunity to capture multi-allelic variation compared to the biparental populations. A multi-parent advanced generation inter-cross (MAGIC) B-line (MBL) population composed of 708 F6 recombinant inbred lines (RILs), was recently developed from four diverse founders. These selected founders strategically represented the four most prevalent botanical races (kafir, guinea, durra, and caudatum) to capture a significant source of genetic variation to study the quantitative traits in grain sorghum [Sorghum bicolor (L.) Moench]. MBL was phenotyped at two field locations for seven yield-influencing traits: panicle type (PT), days to anthesis (DTA), plant height (PH), grain yield (GY), 1000-grain weight (TGW), tiller number per meter (TN) and yield per panicle (YPP). High phenotypic variation was observed for all the quantitative traits, with broad-sense heritabilities ranging from 0.34 (TN) to 0.84 (PH). The entire population was genotyped using Diversity Arrays Technology (DArTseq), and 8,800 single nucleotide polymorphisms (SNPs) were generated. A set of polymorphic, quality-filtered markers (3,751 SNPs) and phenotypic data were used for genome-wide association studies (GWAS). We identified 52 marker-trait associations (MTAs) for the seven traits using BLUPs generated from replicated plots in two locations. We also identified desirable allelic combinations based on the plant height loci (Dw1, Dw2, and Dw3), which influences yield related traits. Additionally, two novel MTAs were identified each on Chr1 and Chr7 for yield traits independent of dwarfing genes. We further performed a multi-variate adaptive shrinkage analysis and 15 MTAs with pleiotropic effect were identified. The five best performing MBL progenies were selected carrying desirable allelic combinations. Since the MBL population was designed to capture significant diversity for maintainer line (B-line) accessions, these progenies can serve as valuable resources to develop superior sorghum hybrids after validation of their general combining abilities via crossing with elite pollinators. Further, newly identified desirable allelic combinations can be used to enrich the maintainer germplasm lines through marker-assisted backcross breeding.

In-Depth Understanding of the Genetic Control of Stripe Rust Resistance (Puccinia striiformis f. sp. tritici) Induced in Wheat (Triticum aestivum) by Trichoderma asperellum T34

Wheat stripe rust (caused by Puccinia striiformis f. tritici Erikss.) causes severe yield losses worldwide. Due to the continuous appearance of new stripe rust races, resistance has been broken in most of the highly resistant genotypes in Egypt and worldwide. Therefore, looking for new ways to resist such a severe disease is urgently needed. Trichoderma asperellum strain T34 has been known as an effective bioagent against many crop diseases. It exists naturally in Egyptian fields. Therefore, in our study, the effectiveness of strain T34 was tested as a bioagent against wheat stripe rust. For this purpose, 198 spring wheat genotypes were tested for their resistance against two different P. striiformis f. tritici populations collected from the Egyptian fields. The most highly aggressive P. striiformis f. tritici population was used to test the effectiveness of strain T34. Highly significant differences were found between strain T34 and stripe rust, suggesting the effectiveness of strain T34 in stripe rust resistance. A genome-wide association study identified 48 gene models controlling resistance under normal conditions and 46 gene models controlling strain T34-induced resistance. Of these gene models, only one common gene model was found, suggesting the presence of two different genetic systems controlling resistance under each condition. The pathways of the biological processes were investigated under both conditions. This study provided in-depth understanding of genetic control and, hence, will accelerate the future of wheat breeding programs for stripe rust resistance.

Genome-Wide Association Study Revealed SNP Alleles Associated with Seed Size Traits in African Yam Bean (Sphenostylis stenocarpa (Hochst ex. A. Rich.) Harms)

Seed size is an important yield and quality-determining trait in higher plants and is also crucial to their evolutionary fitness. In African yam bean (AYB), seed size varies widely among different accessions. However, the genetic basis of such variation has not been adequately documented. A genome-wide marker-trait association study was conducted to identify genomic regions associated with four seed size traits (seed length, seed width, seed thickness, and 100-seed weight) in a panel of 195 AYB accessions. A total of 5416 SNP markers were generated from the diversity array technology sequence (DArTseq) genotype-by-sequencing (GBS)- approach, in which 2491 SNPs were retained after SNP quality control and used for marker-trait association analysis. Significant phenotypic variation was observed for the traits. Broad-sense heritability ranged from 50.0% (seed width) to 66.4% (seed length). The relationships among the traits were positive and significant. Genome-wide association study (GWAS) using the general linear model (GLM) and the mixed linear model (MLM) approaches identified 12 SNP markers significantly associated with seed size traits across the six test environments. The 12 makers explained 6.5-10.8% of the phenotypic variation. Two markers (29420334|F|0-52:C>G-52:C>G and 29420736|F|0-57:G>T-57:G>T) with pleiotropic effects associated with seed width and seed thickness were found. A candidate gene search identified five significant markers (100026424|F|0-37:C>T-37:C>T, 100041049|F|0-42:G>C-42:G>C, 100034480|F|0-31:C>A-31:C>A, 29420365|F|0-55:C>G-55:C>G, and 29420736|F|0-57:G>T-57:G>T) located close to 43 putative genes whose encoding protein products are known to regulate seed size traits. This study revealed significant makers not previously reported for seed size in AYB and could provide useful information for genomic-assisted breeding in AYB.

Advances in disease and pest resistance in faba bean

Faba bean (Vicia faba) is a grain legume crop widely cultivated in temperate areas for food and feed. Its productivity can be constrained by numerous diseases and pests that can be managed by a number of strategies, complemented with the deployment of resistant cultivars in an integrated manner. Few sources of resistance are available to some of them, although their phenotypic expression is usually insufficiently described, and their genetic basis is largely unknown. A few DNA markers have been developed for resistance to rust, ascochyta blight, and broomrape, but not yet for other diseases or pests. Still, germplasm screenings are allowing the identification of resistances that are being accumulated by classical breeding, succeeding in the development of cultivars with moderate levels of resistance. The adoption of novel phenotyping approaches and the unprecedented development of genomic resources along with speed breeding tools are speeding up resistance characterization and effective use in faba bean breeding.

A QTL approach in faba bean highlights the conservation of genetic control of frost tolerance among legume species

Frost is a major abiotic stress of winter type faba beans (Vica faba L.) and has adverse effects on crop yield. Climate change, far from reducing the incidence of frost events, is making these phenomena more and more common, severe, and prolonged. Despite the important interaction that the environment has in the tolerance of faba bean to frost, this trait seems to have good levels of heritability. Several QTLs for frost tolerance have already been reported, however, a more robust identification is needed to more precisely identify the genomic regions involved in faba bean tolerance to sub-zero temperatures. Several pea (Pisum sativum L.) and barrel medic (Medicago truncatula L.) frost tolerance QTLs appear to be conserved between these two species, furthering the hypothesis that the genetic control of frost tolerance in legume species might be more generally conserved. In this work, the QTL mapping in two faba bean recombinant inbred line (RIL) populations connected by a common winter-type parent has led to the identification of five genomic regions involved in the control of frost tolerance on linkage groups I, III, IV, and V. Among them, a major and robust QTL of great interest for marker-assisted selection was identified on the lower part of the long-arm of LGI. The synteny between the faba bean frost tolerance QTLs and those previously identified in other legume species such as barrel medic, pea or soybean highlighted at least partial conservation of the genetic control of frost tolerance among different faba bean genetic pools and legume species. Four novel RILs showing high and stable levels of tolerance and the ability to recover from freezing temperatures by accumulating frost tolerance QTLs are now available for breeding programs.

Genome-wide association mapping for root traits associated with frost tolerance in faba beans using KASP-SNP markers

Frost is an abiotic stress factor that threatens plant development and crop productivity not only in cold regions but also in temperate zones. Roots play an important role in plant growth during frost stress. Therefore, variation in root characteristics could be studied to improve frost tolerance in winter faba bean. The present study aimed to identify the genomic regions that control frost tolerance in a winter faba bean population by focusing on root-related traits. A set of 185 genotypes were tested for frost tolerance under artificial frost growth conditions at −16°C, −18°C, and −19°C in a growth chamber. Frost stress reduced the root-related parameters in all genotypes, with a wide variation among genotypes. A genome-wide association study identified nine novel single-nucleotide polymorphisms that are associated with the root-related traits. The most frost-tolerant genotypes were identified; two genotypes, S_028 and S_220, exhibited remarkable performance under frost stress. Moreover, they harbored all four of the alleles favorable for frost tolerance. Remarkably, two markers showed genetic pleiotropic effects with positive allele effects on root fresh matter and root dry matter. Thus, both genotypes can be implemented in a breeding program to provide the alleles for healthier roots under frost conditions to develop more frost-tolerant varieties, and the two markers can be used to screen large collections to select for frost tolerance. These results may provide novel insights for improving frost tolerance in faba beans and in other legume crops.

Identifying loci controlling total starch content of leaf in Nicotiana tabacum through genome-wide association study

Starch is an important primary metabolite in plants, which can provide bioenergy for fuel ethanol production. There are many studies focusing on starch metabolism in Arabidopsis, maize, and rice, but few reports have been made on the starch content of tobacco leaves. Hence, to identify the marker-trait associations and isolate the candidate genes related to starch content of tobacco leaf, the genome-wide association study (GWAS) was performed using a multiparent advanced generation intercross (MAGIC) population consisting of 276 accessions genotyped by a 430 K SNP array. In this study, we detected the leaf starch content of tobacco plants cultivated in two places (Zhucheng and Chenzhou), which showed a wide variation of starch content in the population. A total of 28 and 45 significant single-nucleotide polymorphism (SNP) loci associated with leaf starch content were identified by single-locus and multi-locus GWAS models, respectively, and the phenotypic variance explained by these loci varied from 1.80 to - 14.73%. Furthermore, among these quantitative trait loci (QTLs), one SNP, AX-106011713 located on chromosome 19, was detected repeatedly in multiple models and two environments, which was selected for linkage disequilibrium (LD) analysis to obtain the target candidate region. Through gene annotation, haplotype, and gene expression analysis, two candidate genes encoding E3 ubiquitin-protein ligase (Ntab0823160) and fructose-bisphosphate aldolase (Ntab0375050) were obtained. Results showed that the variety carrying the beneficial alleles of the two candidate genes had higher gene expression level and leaf starch content, suggesting the potential role of candidate genes in enhancing the level of tobacco leaf starch content. Furthermore, silencing of Ntab0823160 in tobacco leaves reduced the content of total starch to 39.41-69.75% of that in the wide type plants. Taken together, our results provide useful resources for further investigation of the starch metabolic pathway and are also beneficial for the creation of eco-friendly cultivars with increased accumulation of leaf starch content.

Genetic Augmentation of Legume Crops Using Genomic Resources and Genotyping Platforms for Nutritional Food Security

Recent advances in next generation sequencing (NGS) technologies have led the surge of genomic resources for the improvement legume crops. Advances in high throughput genotyping (HTG) and high throughput phenotyping (HTP) enable legume breeders to improve legume crops more precisely and efficiently. Now, the legume breeder can reshuffle the natural gene combinations of their choice to enhance the genetic potential of crops. These genomic resources are efficiently deployed through molecular breeding approaches for genetic augmentation of important legume crops, such as chickpea, cowpea, pigeonpea, groundnut, common bean, lentil, pea, as well as other underutilized legume crops. In the future, advances in NGS, HTG, and HTP technologies will help in the identification and assembly of superior haplotypes to tailor the legume crop varieties through haplotype-based breeding. This review article focuses on the recent development of genomic resource databases and their deployment in legume molecular breeding programmes to secure global food security.

Genome-Wide Screening of Broad-Spectrum Resistance to Leaf Rust (Puccinia triticina Eriks) in Spring Wheat (Triticum aestivum L.)

Wheat leaf rust (LR) causes significant yield losses worldwide. In Egypt, resistant cultivars began to lose their efficiency in leaf rust resistance. Therefore, a diverse spring wheat panel was evaluated at the seedling stage to identify new sources of broad-spectrum seedling resistance against the Egyptian Puccinia triticina (Pt) races. In three different experiments, seedling evaluation was done using Pt spores collected from different fields and growing seasons. Highly significant differences were found among experiments confirming the presence of different races population in each experiment. Highly significant differences were found among the tested genotypes confirming the ability to select superior genotypes. Genome-wide association study (GWAS) was conducted for each experiment and a set of 87 markers located within 48 gene models were identified. The identified gene models were associated with disease resistance in wheat. Five gene models were identified to resist all Pt races in at least two experiments and could be identified as stable genes under Egyptian conditions. Ten genotypes from five different countries were stable against all the tested Pt races but showed different degrees of resistance.

Genetic Dissection of Heat Stress Tolerance in Faba Bean (Vicia faba L.) Using GWAS

Heat waves are expected to become more frequent and intense, which will impact faba bean cultivation globally. Conventional breeding methods are effective but take considerable time to achieve breeding goals, and, therefore, the identification of molecular markers associated with key genes controlling heat tolerance can facilitate and accelerate efficient variety development. We phenotyped 134 accessions in six open field experiments during summer seasons at Terbol, Lebanon, at Hudeiba, Sudan, and at Central Ferry, WA, USA from 2015 to 2018. These accessions were genotyped using genotyping by sequencing (GBS), and 10,794 high quality single nucleotide polymorphisms (SNPs) were discovered. These accessions were clustered in one diverse large group, although several discrete groups may exist surrounding it. Fifteen lines belonging to different botanical groups were identified as tolerant to heat. SNPs associated with heat tolerance using single-trait (ST) and multi-trait (MT) genome-wide association studies (GWASs) showed 9 and 11 significant associations, respectively. Through the annotation of the discovered significant SNPs, we found that SNPs from transcription factor helix-loop-helix bHLH143-like S-adenosylmethionine carrier, putative pentatricopeptide repeat-containing protein At5g08310, protein NLP8-like, and photosystem II reaction center PSB28 proteins are associated with heat tolerance.

Genomic regions associated with herbicide tolerance in a worldwide faba bean (Vicia faba L.) collection

Weeds represent one of the major constraints for faba bean crop. The identification of molecular markers associated with key genes imparting tolerance to herbicides can facilitate and fasten the efficient and effective development of herbicide tolerant cultivars. We phenotyped 140 faba bean genotypes in three open field experiments at two locations in Lebanon and Morocco against three herbicide treatments (T1 metribuzin 250 g ai/ha; T2 imazethapyr 75 g ai/ha; T3 untreated) and one in greenhouse where T1 and T3 were applied. The same set was genotyped using genotyping by sequencing (GBS) which yield 10,794 high quality single nucleotide polymorphisms (SNPs). ADMIXTURE software was used to infer the population structure which revealed two ancestral subpopulations. To identify SNPs associated with phenological and yield related traits under herbicide treatments, Single-trait (ST) and Multi-trait (MT) Genome Wide Association Studies (GWAS) were fitted using GEMMA software, showing 10 and 14 highly significant associations, respectively. Genomic sequences containing herbicide tolerance associated SNPs were aligned against the NCBI database using BLASTX tool using default parameters to annotate candidate genes underlying the causal variants. SNPs from acidic endochitinase, LRR receptor-like serine/threonine-protein kinase RCH1, probable serine/threonine-protein kinase NAK, malate dehydrogenase, photosystem I core protein PsaA and MYB-related protein P-like were significantly associated with herbicide tolerance traits.

Quantitative Trait Loci Mapping of Adult Plant and Seedling Resistance to Stripe Rust (Puccinia striiformis Westend.) in a Multiparent Advanced Generation Intercross Wheat Population

Stripe rust caused by the biotrophic fungus Puccinia striiformis Westend. is one of the most important diseases of wheat worldwide, causing high yield and quality losses. Growing resistant cultivars is the most efficient way to control stripe rust, both economically and ecologically. Known resistance genes are already present in numerous cultivars worldwide. However, their effectiveness is limited to certain races within a rust population and the emergence of stripe rust races being virulent against common resistance genes forces the demand for new sources of resistance. Multiparent advanced generation intercross (MAGIC) populations have proven to be a powerful tool to carry out genetic studies on economically important traits. In this study, interval mapping was performed to map quantitative trait loci (QTL) for stripe rust resistance in the Bavarian MAGIC wheat population, comprising 394 F6 : 8 recombinant inbred lines (RILs). Phenotypic evaluation of the RILs was carried out for adult plant resistance in field trials at three locations across three years and for seedling resistance in a growth chamber. In total, 21 QTL for stripe rust resistance corresponding to 13 distinct chromosomal regions were detected, of which two may represent putatively new QTL located on wheat chromosomes 3D and 7D.

Unraveling the complexity of faba bean (Vicia faba L.) transcriptome to reveal cold-stress-responsive genes using long-read isoform sequencing technology

Faba bean (Vicia faba L.), a globally important grain legume providing a stable source of dietary protein, was one of the earliest plant cytogenetic models. However, the lack of draft genome annotations and unclear structural information on mRNA transcripts have impeded its genetic improvement. To address this, we sequenced faba bean leaf transcriptome using the PacBio single-molecule long-read isoform sequencing platform. We identified 28,569 nonredundant unigenes, ranging from 108 to 9669 bp, with a total length of 94.5 Mb. Many unigenes (3597, 12.5%) had 2-20 isoforms, indicating a highly complex transcriptome. Approximately 96.5% of the unigenes matched sequences in public databases. The predicted proteins and transcription factors included NB-ARC, Myb_domain, C3H, bHLH, and heat shock proteins, implying that this genome has an abundance of stress resistance genes. To validate our results, we selected WCOR413-15785, DHN2-12403, DHN2-14197, DHN2-14797, COR15-14478, and HVA22-15 unigenes from the ICE-CBF-COR pathway to analyze their expression patterns in cold-treated samples via qRT-PCR. The expression of dehydrin-related genes was induced by cold stress. The assembled data provide the first insights into the deep sequencing of full-length RNA from faba bean at the single-molecule level. This study provides an important foundation to improve gene modeling and protein prediction.

Precision Mapping of a Maize MAGIC Population Identified a Candidate Gene for the Senescence-Associated Physiological Traits

Senescence is an important trait in maize (Zea mais L.), a key crop that provides nutrition values and a renewable source of bioenergy worldwide. Genome-wide association studies (GWAS) can be used to identify causative genetic variants that influence the major physiological measures of senescence, which is used by plants as a defense mechanism against abiotic and biotic stresses affecting its performance. We measured four physiological and two agronomic traits that affect senescence. Six hundred seventy-two recombinant inbred lines (RILs) were evaluated in two consecutive years. Thirty-six candidate genes were identified by genome-wide association study (GWAS), and 11 of them were supported by additional evidence for involvement in senescence-related processes including proteolysis, sugar transport, and sink activity. We identified a candidate gene, Zm00001d043586, significantly associated with chlorophyll, and independently studied its transcription expression in an independent panel. Our results showed that Zm00001d043586 affects chlorophyl rate degradation, a key determinant of senescence, at late plant development stages. These results contribute to better understand the genetic relationship of the important trait senescence with physiology related parameters in maize and provide new putative molecular markers that can be used in marker assisted selection for line development.

Recent advances in faba bean genetic and genomic tools for crop improvement

Faba bean (Vicia faba L.), a member of the Fabaceae family, is one of the important food legumes cultivated in cool temperate regions. It holds great importance for human consumption and livestock feed because of its high protein content, dietary fibre, and nutritional value. Major faba bean breeding challenges include its mixed breeding system, unknown wild progenitor, and genome size of ~13 Gb, which is the largest among diploid field crops. The key breeding objectives in faba bean include improved resistance to biotic and abiotic stress and enhanced seed quality traits. Regarding quality traits, major progress on reduction of vicine-convicine and seed coat tannins, the main anti-nutritional factors limiting faba bean seed usage, have been recently achieved through gene discovery. Genomic resources are relatively less advanced compared with other grain legume species, but significant improvements are underway due to a recent increase in research activities. A number of bi-parental populations have been constructed and mapped for targeted traits in the last decade. Faba bean now benefits from saturated synteny-based genetic maps, along with next-generation sequencing and high-throughput genotyping technologies that are paving the way for marker-assisted selection. Developing a reference genome, and ultimately a pan-genome, will provide a foundational resource for molecular breeding. In this review, we cover the recent development and deployment of genomic tools for faba bean breeding.

Haplotype analysis from unmanned aerial vehicle imagery of rice MAGIC population for the trait dissection of biomass and plant architecture

Unmanned aerial vehicles (UAVs) are popular tools for high-throughput phenotyping of crops in the field. However, their use for evaluation of individual lines is limited in crop breeding because research on what the UAV image data represent is still developing. Here, we investigated the connection between shoot biomass of rice plants and the vegetation fraction (VF) estimated from high-resolution orthomosaic images taken by a UAV 10 m above a field during the vegetative stage. Haplotype-based genome-wide association studies of multi-parental advanced generation inter-cross (MAGIC) lines revealed four quantitative trait loci (QTLs) for VF. VF was correlated with shoot biomass, but the haplotype effect on VF was better correlated with that on shoot biomass at these QTLs. Further genetic characterization revealed the relationships between these QTLs and plant spreading habit, final shoot biomass and panicle weight. Thus, genetic analysis using high-throughput phenotyping data derived from low-altitude, high-resolution UAV images during early stages of rice growing in the field provides insights into plant growth, architecture, final biomass, and yield.

GWAS revealed effect of genotype × environment interactions for grain yield of Nebraska winter wheat

Background

Improving grain yield in cereals especially in wheat is a main objective for plant breeders. One of the main constrains for improving this trait is the G × E interaction (GEI) which affects the performance of wheat genotypes in different environments. Selecting high yielding genotypes that can be used for a target set of environments is needed. Phenotypic selection can be misleading due to the environmental conditions. Incorporating information from phenotypic and genomic analyses can be useful in selecting the higher yielding genotypes for a group of environments.

Results

A set of 270 F_3:6 wheat genotypes in the Nebraska winter wheat breeding program was tested for grain yield in nine environments. High genetic variation for grain yield was found among the genotypes. G × E interaction was also highly significant. The highest yielding genotype differed in each environment. The correlation for grain yield among the nine environments was low (0 to 0.43). Genome-wide association study revealed 70 marker traits association (MTAs) associated with increased grain yield. The analysis of linkage disequilibrium revealed 16 genomic regions with a highly significant linkage disequilibrium (LD). The candidate parents’ genotypes for improving grain yield in a group of environments were selected based on three criteria; number of alleles associated with increased grain yield in each selected genotype, genetic distance among the selected genotypes, and number of different alleles between each two selected parents.

Conclusion

Although G × E interaction was present, the advances in DNA technology provided very useful tools and analyzes. Such features helped to genetically select the highest yielding genotypes that can be used to cross grain production in a group of environments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07308-0.

Multiparental Population in Crops: Methods of Development and Dissection of Genetic Traits

Multiparental populations are located midway between association mapping that relies on germplasm collections and classic linkage analysis, based upon biparental populations. They provide several key advantages such as the possibility to include a higher number of alleles and increased level of recombination with respect to biparental populations, and more equilibrated allelic frequencies than association mapping panels. Moreover, in these populations new allele's combinations arise from recombination that may reveal transgressive phenotypes and make them a useful pre-breeding material. Here we describe the strategies for working with multiparental populations, focusing on nested association mapping populations (NAM) and multiparent advanced generation intercross populations (MAGIC). We provide details from the selection of founders, population development, and characterization to the statistical methods for genetic mapping and quantitative trait detection.

QTL mapping of adult plant and seedling resistance to leaf rust (Puccinia triticina Eriks.) in a multiparent advanced generation intercross (MAGIC) wheat population

The Bavarian MAGIC Wheat population, comprising 394 F6:8 recombinant inbred lines was phenotyped for Puccinia triticina resistance in multi-years' field trials at three locations and in a controlled environment seedling test. Simple intervall mapping revealed 19 QTL, corresponding to 11 distinct chromosomal regions. The biotrophic rust fungus Puccinia triticina is one of the most important wheat pathogens with the potential to cause yield losses up to 70%. Growing resistant cultivars is the most cost-effective and environmentally friendly way to encounter this problem. The emergence of leaf rust races being virulent against common resistance genes increases the demand for wheat varieties with novel resistances. In the past decade, the use of complex experimental populations, like multiparent advanced generation intercross (MAGIC) populations, has risen and offers great advantages for mapping resistances. The genetic diversity of multiple parents, which has been recombined over several generations, leads to a broad phenotypic diversity, suitable for high-resolution mapping of quantitative traits. In this study, interval mapping was performed to map quantitative trait loci (QTL) for leaf rust resistance in the Bavarian MAGIC Wheat population, comprising 394 F_6:8 recombinant inbred lines (RILs). Phenotypic evaluation of the RILs for adult plant resistance was carried out in field trials at three locations and two years, as well as in a controlled-environment seedling inoculation test. In total, interval mapping revealed 19 QTL, which corresponded to 11 distinct chromosomal regions controlling leaf rust resistance. Six of these regions may represent putative new QTL. Due to the elite parental material, RILs identified to be resistant to leaf rust can be easily introduced in breeding programs.

Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding

Crop populations derived from experimental crosses enable the genetic dissection of complex traits and support modern plant breeding. Among these, multi-parent populations now play a central role. By mixing and recombining the genomes of multiple founders, multi-parent populations combine many commonly sought beneficial properties of genetic mapping populations. For example, they have high power and resolution for mapping quantitative trait loci, high genetic diversity and minimal population structure. Many multi-parent populations have been constructed in crop species, and their inbred germplasm and associated phenotypic and genotypic data serve as enduring resources. Their utility has grown from being a tool for mapping quantitative trait loci to a means of providing germplasm for breeding programmes. Genomics approaches, including de novo genome assemblies and gene annotations for the population founders, have allowed the imputation of rich sequence information into the descendent population, expanding the breadth of research and breeding applications of multi-parent populations. Here, we report recent successes from crop multi-parent populations in crops. We also propose an ideal genotypic, phenotypic and germplasm 'package' that multi-parent populations should feature to optimise their use as powerful community resources for crop research, development and breeding.

Genomic interventions for sustainable agriculture

Agricultural production faces a Herculean challenge to feed the increasing global population. Food production systems need to deliver more with finite land and water resources while exerting the least negative influence on the ecosystem. The unpredictability of climate change and consequent changes in pests/pathogens dynamics aggravate the enormity of the challenge. Crop improvement has made significant contributions towards food security, and breeding climate-smart cultivars are considered the most sustainable way to accelerate food production. However, a fundamental change is needed in the conventional breeding framework in order to respond adequately to the growing food demands. Progress in genomics has provided new concepts and tools that hold promise to make plant breeding procedures more precise and efficient. For instance, reference genome assemblies in combination with germplasm sequencing delineate breeding targets that could contribute to securing future food supply. In this review, we highlight key breakthroughs in plant genome sequencing and explain how the presence of these genome resources in combination with gene editing techniques has revolutionized the procedures of trait discovery and manipulation. Adoption of new approaches such as speed breeding, genomic selection and haplotype-based breeding could overcome several limitations of conventional breeding. We advocate that strengthening varietal release and seed distribution systems will play a more determining role in delivering genetic gains at farmer's field. A holistic approach outlined here would be crucial to deliver steady stream of climate-smart crop cultivars for sustainable agriculture.

Genetic mapping for agronomic traits in a MAGIC population of common bean (Phaseolus vulgaris L.) under drought conditions

BACKGROUND

Common bean is an important staple crop in the tropics of Africa, Asia and the Americas. Particularly smallholder farmers rely on bean as a source for calories, protein and micronutrients. Drought is a major production constraint for common bean, a situation that will be aggravated with current climate change scenarios. In this context, new tools designed to understand the genetic basis governing the phenotypic responses to abiotic stress are required to improve transfer of desirable traits into cultivated beans.

RESULTS

A multiparent advanced generation intercross (MAGIC) population of common bean was generated from eight Mesoamerican breeding lines representing the phenotypic and genotypic diversity of the CIAT Mesoamerican breeding program. This population was assessed under drought conditions in two field trials for yield, 100 seed weight, iron and zinc accumulation, phenology and pod harvest index. Transgressive segregation was observed for most of these traits. Yield was positively correlated with yield components and pod harvest index (PHI), and negative correlations were found with phenology traits and micromineral contents. Founder haplotypes in the population were identified using Genotyping by Sequencing (GBS). No major population structure was observed in the population. Whole Genome Sequencing (WGS) data from the founder lines was used to impute genotyping data for GWAS. Genetic mapping was carried out with two methods, using association mapping with GWAS, and linkage mapping with haplotype-based interval screening. Thirteen high confidence QTL were identified using both methods and several QTL hotspots were found controlling multiple traits. A major QTL hotspot located on chromosome Pv01 for phenology traits and yield was identified. Further hotspots affecting several traits were observed on chromosomes Pv03 and Pv08. A major QTL for seed Fe content was contributed by MIB778, the founder line with highest micromineral accumulation. Based on imputed WGS data, candidate genes are reported for the identified major QTL, and sequence changes were identified that could cause the phenotypic variation.

CONCLUSIONS

This work demonstrates the importance of this common bean MAGIC population for genetic mapping of agronomic traits, to identify trait associations for molecular breeding tool design and as a new genetic resource for the bean research community.

Detailed Genetic Analysis for Identifying QTLs Associated with Drought Tolerance at Seed Germination and Seedling Stages in Barley

Drought induces several challenges for plant development, growth, and production. These challenges become more severe, in particular, in arid and semiarid countries like Egypt. In terms of production, barley ranks fourth after wheat, maize, and rice. Seed germination and seedling stages are critical stages for plant establishment and growth. In the current study, 60 diverse barley genotypes were tested for drought tolerance using two different treatments: control (0-PEG) and drought (20%-PEG). Twenty-two traits were estimated for seed germination and seedling parameters. All traits were reduced under drought stress, and a significant variation was found among genotypes under control and stress conditions. The broad-sense heritability estimates were very high under both control and drought for all traits. It ranged from 0.63 to 0.97 under the control condition and from 0.89 to 0.97 under drought, respectively. These high heritabilities suggested that genetic improvement of drought tolerance in barley at both stages is feasible. The principal component analysis revealed that root-related parameters account for the largest portion of phenotypic variation in this collection. The single-marker analysis (SMA) resulted in 71 quantitative trait loci (QTLs) distributed across the seven chromosomes of barley. Thirty-three QTLs were detected for root-length-related traits. Many hotspots of QTLs were detected for various traits. Interestingly, some markers controlled many traits in a pleiotropic manner; thus, they can be used to control multiple traits at a time. Some QTLs were constitutive, i.e., they are mapped under control and drought, and targeting these QTLs makes the selection for drought tolerance a single-step process. The results of gene annotation analysis revealed very potential candidate genes that can be targeted to select for drought tolerance.

The Dawn of the Age of Multi-Parent MAGIC Populations in Plant Breeding: Novel Powerful Next-Generation Resources for Genetic Analysis and Selection of Recombinant Elite Material

The compelling need to increase global agricultural production requires new breeding approaches that facilitate exploiting the diversity available in the plant genetic resources. Multi-parent advanced generation inter-cross (MAGIC) populations are large sets of recombinant inbred lines (RILs) that are a genetic mosaic of multiple founder parents. MAGIC populations display emerging features over experimental bi-parental and germplasm populations in combining significant levels of genetic recombination, a lack of genetic structure, and high genetic and phenotypic diversity. The development of MAGIC populations can be performed using “funnel” or “diallel” cross-designs, which are of great relevance choosing appropriate parents and defining optimal population sizes. Significant advances in specific software development are facilitating the genetic analysis of the complex genetic constitutions of MAGIC populations. Despite the complexity and the resources required in their development, due to their potential and interest for breeding, the number of MAGIC populations available and under development is continuously growing, with 45 MAGIC populations in different crops being reported here. Though cereals are by far the crop group where more MAGIC populations have been developed, MAGIC populations have also started to become available in other crop groups. The results obtained so far demonstrate that MAGIC populations are a very powerful tool for the dissection of complex traits, as well as a resource for the selection of recombinant elite breeding material and cultivars. In addition, some new MAGIC approaches that can make significant contributions to breeding, such as the development of inter-specific MAGIC populations, the development of MAGIC-like populations in crops where pure lines are not available, and the establishment of strategies for the straightforward incorporation of MAGIC materials in breeding pipelines, have barely been explored. The evidence that is already available indicates that MAGIC populations will play a major role in the coming years in allowing for impressive gains in plant breeding for developing new generations of dramatically improved cultivars.

Molecular genetic analysis of spring wheat core collection using genetic diversity, population structure, and linkage disequilibrium

Background

Wheat (Triticum aestivium L.) is an important crop globally which has a complex genome. To identify the parents with useful agronomic characteristics that could be used in the various breeding programs, it is very important to understand the genetic diversity among global wheat genotypes. Also, understanding the genetic diversity is useful in breeding studies such as marker-assisted selection (MAS), genome-wide association studies (GWAS), and genomic selection.

Results

To understand the genetic diversity in wheat, a set of 103 spring wheat genotypes which represented five different continents were used. These genotypes were genotyped using 36,720 genotyping-by-sequencing derived SNPs (GBS-SNPs) which were well distributed across wheat chromosomes. The tested 103-wheat genotypes contained three different subpopulations based on population structure, principle coordinate, and kinship analyses. A significant variation was found within and among the subpopulations based on the AMOVA. Subpopulation 1 was found to be the more diverse subpopulation based on the different allelic patterns (Na, Ne, I, h, and uh). No high linkage disequilibrium was found between the 36,720 SNPs. However, based on the genomic level, D genome was found to have the highest LD compared with the two other genomes A and B. The ratio between the number of significant LD/number of non-significant LD suggested that chromosomes 2D, 5A, and 7B are the highest LD chromosomes in their genomes with a value of 0.08, 0.07, and 0.05, respectively. Based on the LD decay, the D genome was found to be the lowest genome with the highest number of haplotype blocks on chromosome 2D.

Conclusion

The recent study concluded that the 103-spring wheat genotypes and their GBS-SNP markers are very appropriate for GWAS studies and QTL-mapping. The core collection comprises three different subpopulations. Genotypes in subpopulation 1 are the most diverse genotypes and could be used in future breeding programs if they have desired traits. The distribution of LD hotspots across the genome was investigated which provides useful information on the genomic regions that includes interesting genes.

GWAS: Fast-forwarding gene identification and characterization in temperate Cereals: lessons from Barley - A review

Understanding the genetic complexity of traits is an important objective of small grain temperate cereals yield and adaptation improvements. Bi-parental quantitative trait loci (QTL) linkage mapping is a powerful method to identify genetic regions that co-segregate in the trait of interest within the research population. However, recently, association or linkage disequilibrium (LD) mapping using a genome-wide association study (GWAS) became an approach for unraveling the molecular genetic basis underlying the natural phenotypic variation. Many causative allele(s)/loci have been identified using the power of this approach which had not been detected in QTL mapping populations. In barley (Hordeum vulgare L.), GWAS has been successfully applied to define the causative allele(s)/loci which can be used in the breeding crop for adaptation and yield improvement. This promising approach represents a tremendous step forward in genetic analysis and undoubtedly proved it is a valuable tool in the identification of candidate genes. In this review, we describe the recently used approach for genetic analyses (linkage mapping or association mapping), and then provide the basic genetic and statistical concepts of GWAS, and subsequently highlight the genetic discoveries using GWAS. The review explained how the candidate gene(s) can be detected using state-of-art bioinformatic tools.

Usefulness of a Multiparent Advanced Generation Intercross Population With a Greatly Reduced Mating Design for Genetic Studies in Winter Wheat

Multiparent advanced generation intercross (MAGIC) populations were recently developed to allow the high-resolution mapping of quantitative traits. We present a genetic linkage map of an elite but highly diverse eight-founder MAGIC population in common wheat (Triticum aestivum L.). Our MAGIC population is composed of 394 F6:8 recombinant inbred lines lacking significant signatures of population structure. The linkage map included 5435 SNP markers distributed over 2804 loci and spanning 5230 cM. The analysis of population parameters, including genetic structure, kinship, founder probabilities, and linkage disequilibrium and congruency to other maps indicated appropriate construction of both the population and the genetic map. It was shown that eight-founder MAGIC populations exhibit a greater number of loci and higher recombination rates, especially in the pericentromeric regions, compared to four-founder MAGIC, and biparental populations. In addition, our greatly simplified eight-parental MAGIC mating design with an additional eight-way intercross step was found to be equivalent to a MAGIC design with all 210 possible four-way crosses regarding the levels of missing founder assignments and the number of recombination events. Furthermore, the MAGIC population captured 71.7% of the allelic diversity available in the German wheat breeding gene pool. As a proof of principle, we demonstrated the application of the resource for quantitative trait loci mapping analyzing seedling resistance to powdery mildew. As wheat is a crop with many breeding objectives, this resource will allow scientists and breeders to carry out genetic studies for a wide range of breeder-relevant parameters in a single genetic background and reveal possible interactions between traits of economic importance.

On the Road to Breeding 4.0: Unraveling the Good, the Bad, and the Boring of Crop Quantitative Genomics

Understanding the quantitative genetics of crops has been and will continue to be central to maintaining and improving global food security. We outline four stages that plant breeding either has already achieved or will probably soon achieve. Top-of-the-line breeding programs are currently in Breeding 3.0, where inexpensive, genome-wide data coupled with powerful algorithms allow us to start breeding on predicted instead of measured phenotypes. We focus on three major questions that must be answered to move from current Breeding 3.0 practices to Breeding 4.0: ( a) How do we adapt crops to better fit agricultural environments? ( b) What is the nature of the diversity upon which breeding can act? ( c) How do we deal with deleterious variants? Answering these questions and then translating them to actual gains for farmers will be a significant part of achieving global food security in the twenty-first century.

Genetic diversity and genetic variation in morpho-physiological traits to improve heat tolerance in Spring barley

Heat stress is one of the abiotic stresses that limit the production and productivity of barley. Understanding the genetic variation, changes in physiological processes and level of genetic diversity existing among genotypes are needed to produce new cultivars not only having a high tolerance to heat stress, but also displaying high yield. To address this challenge, a set of 60 highly homozygous, diverse barley genotypes were evaluated under normal and heat stress conditions in two seasons of 2014/2015 and 2015/2016. Seedling vigor (SV) as a morphological trait was visually scored under normal conditions. Plant height (Ph), days to flowering (DOF), 1000-kernel weight (TKW), grain yield per spike (GYPS), yield per plot (YPP) and biological yield (BY) were measured. Moreover, proline content (ProC), soluble carbohydrate content (SCC), starch content, soluble protein (SP), and amino acid (AA) content as physiological parameters were analyzed from the grains. High genetic variation was observed among genotypes for all traits scored in this study. All traits had high broad-sense heritability estimates ranging from 0.59 (SV) to 0.97 (TKW) for yield traits. Seedling vigor was significantly correlated with all yield traits under both conditions. Among all physiological traits, the increase in ProC and reduction in starch content due to heat stress had significant correlations with the reduction due to heat stress in YPP, GYPS, TKW, and BY. Furthermore, the genetic diversity based on genetic distance (GD) among genotypes was investigated using 206 highly polymorphic SSR marker alleles. The GD ranged from 0.70 to 0.98 indicating that these genotypes are highly and genetically dissimilar. The combination of analyses using molecular markers, genetic variation in yield traits, and changes in physiological traits provided useful information in identifying the tolerant genotypes which can be used to improve heat tolerance in barley through breeding.

Discovery of QTL Alleles for Grain Shape in the Japan-MAGIC Rice Population Using Haplotype Information

A majority of traits are determined by multiple quantitative trait loci (QTL) that can have pleiotropic effects. A multi-parent advanced generation inter-cross (MAGIC) population is well suited for genetically analyzing the effects of multiple QTL on traits of interest because it contains a higher number of QTL alleles than a biparental population. We previously produced the JAPAN-MAGIC (JAM) population, derived from eight rice (Oryza sativa L.) cultivars with high yield and biomass in Japan, and developed the method of genome-wide association study (GWAS) using haplotype information on the JAM lines. This method was effective for identifying major genes such as Waxy for eating quality and Sd1 for culm length. Here, we show that haplotype-based GWAS is also effective for the evaluation of multiple QTL with small effects on rice grain shape in the JAM lines. Although both the haplotype- and SNP-based GWAS identified multiple QTL for grain length and width, the sum of the estimated trait values of each allele for the QTL detected by haplotype-based GWAS had higher correlation with observed values than those detected by SNP-based GWAS, indicating high-accuracy QTL detection in the haplotype-based GWAS. Furthermore, the study revealed pleiotropic effects of some QTL regions in regulation of grain shape, suggesting that the haplotype-based GWAS using the JAM lines is an effective means to evaluate the main and side effects of haplotypes at each QTL. Information on the pleiotropic effects of haplotypes on various traits will be useful for designing ideal lines in a breeding program.

Haplotype-based allele mining in the Japan-MAGIC rice population

Multi-parent advanced generation inter-cross (MAGIC) lines have broader genetic variation than bi-parental recombinant inbred lines. Genome-wide association study (GWAS) using high number of DNA polymorphisms such as single-nucleotide polymorphisms (SNPs) is a popular tool for allele mining in MAGIC populations, in which the associations of phenotypes with SNPs are investigated; however, the effects of haplotypes from multiple founders on phenotypes are not considered. Here, we describe an improved method of allele mining using the newly developed Japan-MAGIC (JAM) population, which is derived from eight high-yielding rice cultivars in Japan. To obtain information on the haplotypes in the JAM lines, we predicted the haplotype blocks in the whole chromosomes using 16,345 SNPs identified via genotyping-by-sequencing analysis. Using haplotype-based GWAS, we clearly detected the loci controlling the glutinous endosperm and culm length traits. Information on the alleles of the eight founders, which was based on the effects of mutations revealed by the analysis of next-generation sequencing data, was used to narrow down the candidate genes and reveal the associations between alleles and phenotypes. The haplotype-based allele mining (HAM) proposed in this study is a promising approach to the detection of allelic variation in genes controlling agronomic traits in MAGIC populations.

SSR-based association mapping of fiber quality in upland cotton using an eight-way MAGIC population

The quality of fiber is significant in the upland cotton industry. As complex quantitative traits, fiber quality traits are worth studying at a genetic level. To investigate the genetic architecture of fiber quality traits, we conducted an association analysis using a multi-parent advanced generation inter-cross (MAGIC) population developed from eight parents and comprised of 960 lines. The reliable phenotypic data for six major fiber traits of the MAGIC population were collected from five environments in three locations. Phenotypic analysis showed that the MAGIC lines have a wider variation amplitude and coefficient than the founders. A total of 284 polymorphic SSR markers among eight parents screened from a high-density genetic map were used to genotype the MAGIC population. The MAGIC population showed abundant genetic variation and fast linkage disequilibrium (LD) decay (0.76 cM, r² > 0.1), which revealed the advantages of high efficiency and power in QTL exploration. Association mapping via a mixed linear model identified 52 significant loci associated with six fiber quality traits; 14 of them were mapped in reported QTL regions with fiber-related or other agronomic traits. Nine markers demonstrated the pleiotropism that controls more than two fiber traits. Furthermore, two SSR markers, BNL1231 and BNL3452, were authenticated as hotspots that were mapped with multi-traits. In addition, we provided candidate regions and screened six candidate genes for identified loci according to the LD decay distance. Our results provide valuable QTL for further genetic mapping and will facilitate marker-based breeding for fiber quality in cotton.

A roadmap for breeding orphan leafy vegetable species: a case study of Gynandropsis gynandra (Cleomaceae)

Despite an increasing awareness of the potential of "orphan" or unimproved crops to contribute to food security and enhanced livelihoods for farmers, coordinated research agendas to facilitate production and use of orphan crops by local communities are generally lacking. We provide an overview of the current knowledge on leafy vegetables with a focus on Gynandropsis gynandra, a highly nutritious species used in Africa and Asia, and highlight general and species-specific guidelines for participatory, genomics-assisted breeding of orphan crops. Key steps in genome-enabled orphan leafy vegetables improvement are identified and discussed in the context of Gynandropsis gynandra breeding, including: (1) germplasm collection and management; (2) product target definition and refinement; (3) characterization of the genetic control of key traits; (4) design of the 'process' for cultivar development; (5) integration of genomic data to optimize that 'process'; (6) multi-environmental participatory testing and end-user evaluation; and (7) crop value chain development. The review discusses each step in detail, with emphasis on improving leaf yield, phytonutrient content, organoleptic quality, resistance to biotic and abiotic stresses and post-harvest management.

The application of genomics and bioinformatics to accelerate crop improvement in a changing climate

The changing climate and growing global population will increase pressure on our ability to produce sufficient food. The breeding of novel crops and the adaptation of current crops to the new environment are required to ensure continued food production. Advances in genomics offer the potential to accelerate the genomics based breeding of crop plants. However, relating genomic data to climate related agronomic traits for use in breeding remains a huge challenge, and one which will require coordination of diverse skills and expertise. Bioinformatics, when combined with genomics has the potential to help maintain food security in the face of climate change through the accelerated production of climate ready crops.

Identification and Verification of QTL Associated with Frost Tolerance Using Linkage Mapping and GWAS in Winter Faba Bean

Frost stress is one of the abiotic stresses that causes a significant reduction in winter faba bean yield in Europe. The main objective of this work is to genetically improve frost tolerance in winter faba bean by identifying and validating QTL associated with frost tolerance to be used in marker-assisted selection (MAS). Two different genetic backgrounds were used: a biparental population (BPP) consisting of 101 inbred lines, and 189 genotypes from single seed descent (SSD) from the Gottingen Winter bean Population (GWBP). All experiments were conducted in a frost growth chamber under controlled conditions. Both populations were genotyped using the same set of 189 SNP markers. Visual scoring for frost stress symptoms was used to define frost tolerance in both populations. In addition, leaf fatty acid composition (FAC) and proline content were analyzed in BPP as physiological traits. QTL mapping (for BPP) and genome wide association studies (for GWBP) were performed to detect QTL associated with frost tolerance. High genetic variation between genotypes, and repeatability estimates, were found for all traits. QTL mapping and GWAS identified new putative QTL associated with promising frost tolerance and related traits. A set of 54 SNP markers common in both genetic backgrounds showed a high genetic diversity with polymorphic information content (PIC) ranging from 0.31 to 0.37 and gene diversity ranging from 0.39 to 0.50. This indicates that these markers may be polymorphic for many faba bean populations. Five SNP markers showed a significant marker-trait association with frost tolerance and related traits in both populations. Moreover, synteny analysis between Medicago truncatula (a model legume) and faba bean genomes was performed to identify candidate genes for these markers. Collinearity was evaluated between the faba bean genetic map constructed in this study and the faba bean consensus map, resulting in identifying possible genomic regions in faba bean which may control frost tolerance genes. The two genetic backgrounds were useful in detecting new variation for improving frost tolerance in winter faba bean. Of the five validated SNP markers, one (VF_Mt3g086600) was found to be associated with frost tolerance and FAC in both populations. This marker was also associated with winter hardiness and high yield in earlier studies. This marker is located in a gene of unknown function.