A multi-parent advanced generation inter-cross (MAGIC) population for genetic analysis and improvement of cowpea (Vigna unguiculata L. Walp.)

The pattern of genetic variability in a core collection of 2,021 cowpea accessions

Cowpea is a highly drought-adapted leguminous crop with great promise for improving agricultural sustainability and food security. Here, we report analyses derived from array-based genotyping of 2,021 accessions constituting a core subset of the world's largest cowpea collection, held at the International Institute of Tropical Agriculture (IITA) in Ibadan, Nigeria. We used this dataset to examine genetic variation and population structure in worldwide cowpea. We confirm that the primary pattern of population structure is two geographically defined subpopulations originating in West and East Africa, respectively, and that population structure is associated with shifts in phenotypic distribution. Furthermore, we establish the cowpea core collection as a resource for genome-wide association studies by mapping the genetic basis of several phenotypes, with a focus on seed coat pigmentation patterning and color. We anticipate that the genotyped IITA Cowpea Core Collection will serve as a powerful tool for mapping complex traits, facilitating the acceleration of breeding programs to enhance the resilience of this crop in the face of rapid global climate change.

Crop Landraces and Indigenous Varieties: A Valuable Source of Genes for Plant Breeding

Landraces and indigenous varieties comprise valuable sources of crop species diversity. Their utilization in plant breeding may lead to increased yield and enhanced quality traits, as well as resilience to various abiotic and biotic stresses. Recently, new approaches based on the rapid advancement of genomic technologies such as deciphering of pangenomes, multi-omics tools, marker-assisted selection (MAS), genome-wide association studies (GWAS), and CRISPR/Cas9 gene editing greatly facilitated the exploitation of landraces in modern plant breeding. In this paper, we present a comprehensive overview of the implementation of new genomic technologies and highlight their importance in pinpointing the genetic basis of desirable traits in landraces and indigenous varieties of annual, perennial herbaceous, and woody crop species cultivated in the Mediterranean region. The need for further employment of advanced -omic technologies to unravel the full potential of landraces and indigenous varieties underutilized genetic diversity is also indicated. Ultimately, the large amount of genomic data emerging from the investigation of landraces and indigenous varieties reveals their potential as a source of valuable genes and traits for breeding. The role of landraces and indigenous varieties in mitigating the ongoing risks posed by climate change in agriculture and food security is also highlighted.

Quantitative trait loci and genomic prediction for grain sugar and mineral concentrations of cowpea [Vigna unguiculata (L.) Walp.]

Development of high yielding cowpea varieties coupled with good taste and rich in essential minerals can promote consumption and thus nutrition and profitability. The sweet taste of cowpea grain is determined by its sugar content, which comprises mainly sucrose and galacto-oligosaccharides (GOS) including raffinose and stachyose. However, GOS are indigestible and their fermentation in the colon can produce excess intestinal gas, causing undesirable bloating and flatulence. In this study, we aimed to examine variation in grain sugar and mineral concentrations, then map quantitative trait loci (QTLs) and estimate genomic-prediction (GP) accuracies for possible application in breeding. Grain samples were collected from a multi-parent advanced generation intercross (MAGIC) population grown in California during 2016-2017. Grain sugars were assayed using high-performance liquid chromatography. Grain minerals were determined by inductively coupled plasma-optical emission spectrometry and combustion. Considerable variation was observed for sucrose (0.6-6.9%) and stachyose (2.3-8.4%). Major QTLs for sucrose (QSuc.vu-1.1), stachyose (QSta.vu-7.1), copper (QCu.vu-1.1) and manganese (QMn.vu-5.1) were identified. Allelic effects of major sugar QTLs were validated using the MAGIC grain samples grown in West Africa in 2017. GP accuracies for minerals were moderate (0.4-0.58). These findings help guide future breeding efforts to develop mineral-rich cowpea varieties with desirable sugar content.

A Mid-Density Single-Nucleotide Polymorphism Panel for Molecular Applications in Cowpea (Vigna unguiculata (L.) Walp)

Molecular markers are increasingly being deployed to accelerate genetic gain in crop plants. The objective of this study was to assess the potential of a mid-density genotyping panel for molecular applications in cowpea breeding. A core set of 2,602 targeted diversity array technology (DArTag) single-nucleotide polymorphisms (SNPs) was designed from an existing 51,128 Cowpea iSelect Consortium Array. The panel's usefulness was assessed using 376 genotypes from different populations of known genetic backgrounds. The panel was informative, with over 78% of SNPs exceeding a minor allele frequency of 0.20. The panel decoded three stratifications in the constituted population, as was expected. Linkage disequilibrium (LD) decay was correctly depicted as slower in a biparental subset than in other populations. A known flower and seed coat color gene region was located on chromosome Vu07, suggesting that the mid-density panel may be used to hypothesize genomic regions underlying target traits in cowpea. Unexpected heterozygosity was detected in some lines and highly among F1 progenies, divulging the panel's potential application in germplasm purity and hybridity verification. The study unveils the potential of an excellent genomic resource that can be tapped to enhance the development of improved cowpea cultivars.

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.

Green revolution to genome revolution: driving better resilient crops against environmental instability

Crop improvement programmes began with traditional breeding practices since the inception of agriculture. Farmers and plant breeders continue to use these strategies for crop improvement due to their broad application in modifying crop genetic compositions. Nonetheless, conventional breeding has significant downsides in regard to effort and time. Crop productivity seems to be hitting a plateau as a consequence of environmental issues and the scarcity of agricultural land. Therefore, continuous pursuit of advancement in crop improvement is essential. Recent technical innovations have resulted in a revolutionary shift in the pattern of breeding methods, leaning further towards molecular approaches. Among the promising approaches, marker-assisted selection, QTL mapping, omics-assisted breeding, genome-wide association studies and genome editing have lately gained prominence. Several governments have progressively relaxed their restrictions relating to genome editing. The present review highlights the evolutionary and revolutionary approaches that have been utilized for crop improvement in a bid to produce climate-resilient crops observing the consequence of climate change. Additionally, it will contribute to the comprehension of plant breeding succession so far. Investing in advanced sequencing technologies and bioinformatics will deepen our understanding of genetic variations and their functional implications, contributing to breakthroughs in crop improvement and biodiversity conservation.

Genome-wide association study as a powerful tool for dissecting competitive traits in legumes

Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.

Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals

Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The rising population is posing increased demand for food, thereby pushing for an acceleration in agricultural production. Furthermore, increased anthropogenic activities have resulted in environmental pollution such as water pollution and soil degradation as well as alterations in the composition and concentration of environmental gases. These changes are affecting not only biodiversity loss but also affecting the physio-biochemical processes of crop plants, resulting in a stress-induced decline in crop yield. To overcome such problems and ensure the supply of food material, consistent efforts are being made to develop strategies and techniques to increase crop yield and to enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication and initially remained dependent on phenotype-based selection for crop improvement. But it has grown through cytological and biochemical methods, and the newer contemporary methods are based on DNA-marker-based strategies that help in the selection of agronomically useful traits. These are now supported by high-end molecular biology tools like PCR, high-throughput genotyping and phenotyping, data from crop morpho-physiology, statistical tools, bioinformatics, and machine learning. After establishing its worth in animal breeding, genomic selection (GS), an improved variant of marker-assisted selection (MAS), has made its way into crop-breeding programs as a powerful selection tool. To develop novel breeding programs as well as innovative marker-based models for genetic evaluation, GS makes use of molecular genetic markers. GS can amend complex traits like yield as well as shorten the breeding period, making it advantageous over pedigree breeding and marker-assisted selection (MAS). It reduces the time and resources that are required for plant breeding while allowing for an increased genetic gain of complex attributes. It has been taken to new heights by integrating innovative and advanced technologies such as speed breeding, machine learning, and environmental/weather data to further harness the GS potential, an approach known as integrated genomic selection (IGS). This review highlights the IGS strategies, procedures, integrated approaches, and associated emerging issues, with a special emphasis on cereal crops. In this domain, efforts have been taken to highlight the potential of this cutting-edge innovation to develop climate-smart crops that can endure abiotic stresses with the motive of keeping production and quality at par with the global food demand.

A Genome-Wide Association Study Reveals Region Associated with Seed Protein Content in Cowpea

Cowpea (Vigna unguiculata L. Walp., 2n = 2x = 22) is a protein-rich crop that complements staple cereals for humans and serves as fodder for livestock. It is widely grown in Africa and other developing countries as the primary source of protein in the diet; therefore, it is necessary to identify the protein-related loci to improve cowpea breeding. In the current study, we conducted a genome-wide association study (GWAS) on 161 cowpea accessions (151 USDA germplasm plus 10 Arkansas breeding lines) with a wide range of seed protein contents (21.8~28.9%) with 110,155 high-quality whole-genome single-nucleotide polymorphisms (SNPs) to identify markers associated with protein content, then performed genomic prediction (GP) for future breeding. A total of seven significant SNP markers were identified using five GWAS models (single-marker regression (SMR), the general linear model (GLM), Mixed Linear Model (MLM), Fixed and Random Model Circulating Probability Unification (FarmCPU), and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), which are located at the same locus on chromosome 8 for seed protein content. This locus was associated with the gene Vigun08g039200, which was annotated as the protein of the thioredoxin superfamily, playing a critical function for protein content increase and nutritional quality improvement. In this study, a genomic prediction (GP) approach was employed to assess the accuracy of predicting seed protein content in cowpea. The GP was conducted using cross-prediction with five models, namely ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB), and Bayesian least absolute shrinkage and selection operator (BL), applied to seven random whole genome marker sets with different densities (10 k, 5 k, 2 k, 1 k, 500, 200, and 7), as well as significant markers identified through GWAS. The accuracies of the GP varied between 42.9% and 52.1% across the seven SNPs considered, depending on the model used. These findings not only have the potential to expedite the breeding cycle through early prediction of individual performance prior to phenotyping, but also offer practical implications for cowpea breeding programs striving to enhance seed protein content and nutritional quality.

Genome-wide association mapping for LLS resistance in a MAGIC population of groundnut (Arachis hypogaea L.)

The identified 30 functional nucleotide polymorphisms or genic SNP markers would offer essential information for marker-assisted breeding in groundnut. A genome-wide association study (GWAS) on component traits of LLS resistance in an eight-way multiparent advance generation intercross (MAGIC) population of groundnut in the field and in a light chamber (controlled conditions) was performed via an Affymetrix 48 K single-nucleotide polymorphism (SNP) 'Axiom Arachis' array. Multiparental populations with high-density genotyping enable the detection of novel alleles. In total, five quantitative trait loci (QTLs) with marker - log10(p value) scores ranging from 4.25 to 13.77 for the incubation period (IP) and six QTLs with marker - log10(p value) scores ranging from 4.33 to 10.79 for the latent period (LP) were identified across the A- and B-subgenomes. A total of 62 markers‒trait associations (MTAs) were identified across the A- and B-subgenomes. Markers for LLS scores and the area under the disease progression curve (AUDPC) recorded for plants in the light chamber and under field conditions presented - log10 (p value) scores ranging from 4.22 to 27.30. The highest number of MTAs (six) was identified on chromosomes A05, B07 and B09. Out of a total of 73 MTAs, 37 and 36 MTAs were detected in subgenomes A and B, respectively. Taken together, these results suggest that both subgenomes have equal potential genomic regions contributing to LLS resistance. A total of 30 functional nucleotide polymorphisms or genic SNP markers were detected, among which eight genes were found to encode leucine-rich repeat (LRR) receptor-like protein kinases and putative disease resistance proteins. These important SNPs can be used in breeding programmes for the development of cultivars with improved disease resistance.

Unlocking the hidden variation from wild repository for accelerating genetic gain in legumes

The fluctuating climates, rising human population, and deteriorating arable lands necessitate sustainable crops to fulfil global food requirements. In the countryside, legumes with intriguing but enigmatic nitrogen-fixing abilities and thriving in harsh climatic conditions promise future food security. However, breaking the yield plateau and achieving higher genetic gain are the unsolved problems of legume improvement. Present study gives emphasis on 15 important legume crops, i.e., chickpea, pigeonpea, soybean, groundnut, lentil, common bean, faba bean, cowpea, lupin, pea, green gram, back gram, horse gram, moth bean, rice bean, and some forage legumes. We have given an overview of the world and India's area, production, and productivity trends for all legume crops from 1961 to 2020. Our review article investigates the importance of gene pools and wild relatives in broadening the genetic base of legumes through pre-breeding and alien gene introgression. We have also discussed the importance of integrating genomics, phenomics, speed breeding, genetic engineering and genome editing tools in legume improvement programmes. Overall, legume breeding may undergo a paradigm shift once genomics and conventional breeding are integrated in the near future.

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.

SoyMAGIC: An Unprecedented Platform for Genetic Studies and Breeding Activities in Soybean

Multi-Parent Advanced Generation Inter-Cross (MAGIC) populations are emerging genetic platforms for high-resolution and fine mapping of quantitative traits, such as agronomic and seed composition traits in soybean (Glycine max L.). We have established an eight-parent MAGIC population, comprising 721 recombinant inbred lines (RILs), through conical inter-mating of eight soybean lines. The parental lines were genetically diverse elite cultivars carrying different agronomic and seed composition characteristics, including amino acids and fatty acids, as well as oil and protein concentrations. This study aimed to introduce soybean MAGIC (SoyMAGIC) population as an unprecedented platform for genotypic and phenotypic investigation of agronomic and seed quality traits in soybean. The RILs were evaluated for important seed composition traits using replicated field trials during 2020 and 2021. To measure the seed composition traits, near-infrared reflectance (NIR) was employed. The RILs were genotyped using genotyping-by-sequencing (GBS) method to decipher the genome and discover single-nucleotide polymorphic (SNP) markers among the RILs. A high-density linkage map was constructed through inclusive composite interval mapping (ICIM). The linkage map was 3,770.75 cM in length and contained 12,007 SNP markers. Chromosomes 11 and 18 were recorded as the shortest and longest linkage groups with 71.01 and 341.15 cM in length, respectively. Observed transgressive segregation of the selected traits and higher recombination frequency across the genome confirmed the capability of MAGIC population in reshuffling the diversity in the soybean genome among the RILs. The assessment of haplotype blocks indicated an uneven distribution of the parents' genomes in RILs, suggesting cryptic influence against or in favor of certain parental genomes. The SoyMAGIC population is a recombined genetic material that will accelerate further genomic studies and the development of soybean cultivars with improved seed quality traits through the development and implementation of reliable molecular-based toolkits.

Genetically-determined variations in photosynthesis indicate roles for specific fatty acid species in chilling responses

Using a population of recombinant inbred lines (RILs) cowpea (Vigna unguiculata. L. Walp), we tested for co-linkages between lipid contents and chilling responses of photosynthesis. Under low-temperature conditions (19°C/13°C, day/night), we observed co-linkages between quantitative trait loci intervals for photosynthetic light reactions and specific fatty acids, most strikingly, the thylakoid-specific fatty acid 16:1^Δ3trans found exclusively in phosphatidylglycerol (PG 16:1t). By contrast, we did not observe co-associations with bulk polyunsaturated fatty acids or high-melting-point-PG (sum of PG 16:0, PG 18:0 and PG 16:1t) previously thought to be involved in chilling sensitivity. These results suggest that in cowpea, chilling sensitivity is modulated by specific lipid interactions rather than bulk properties. We were able to recapitulate the predicted impact of PG 16:1t levels on photosynthetic responses at low temperature using mutants and transgenic Arabidopsis lines. Because PG 16:1t synthesis requires the activity of peroxiredoxin-Q, which is activated by H₂ O₂ and known to be involved in redox signalling, we hypothesise that the accumulation of PG 16:1t occurs as a result of upstream effects on photosynthesis that alter redox status and production of reactive oxygen species.

Genetic mapping and prediction of flowering time and plant height in a maize Stiff Stalk MAGIC population

The Stiff Stalk heterotic pool is a foundation of US maize seed parent germplasm and has been heavily utilized by both public and private maize breeders since its inception in the 1930's. Flowering time and plant height are critical characteristics for both inbred parents and their test crossed hybrid progeny. To study these traits, a six parent multiparent advanced generation intercross (MAGIC) population was developed including maize inbred lines B73, B84, PHB47 (B37 type), LH145 (B14 type), PHJ40 (novel early Stiff Stalk), and NKH8431 (B73/B14 type). A set of 779 doubled haploid lines were evaluated for flowering time and plant height in two field replicates in 2016 and 2017, and a subset of 689 and 561 doubled haploid lines were crossed to two testers, respectively, and evaluated as hybrids in two locations in 2018 and 2019 using an incomplete block design. Markers were derived from a Practical Haplotype Graph built from the founder whole genome assemblies and genotype-by-sequencing and exome capture-based sequencing of the population. Genetic mapping utilizing an update to R/qtl2 revealed differing profiles of significant loci for both traits between 635 of the DH lines and two sets of 570 and 471 derived hybrids. Genomic prediction was used to test the feasibility of predicting hybrid phenotypes based on the per se data. Predictive abilities were highest on direct models trained using the data they would predict (0.55 to 0.63), and indirect models trained using per se data to predict hybrid traits had slightly lower predictive abilities (0.49 to 0.55). Overall, this finding is consistent with the overlapping and non-overlapping significant QTL found within the per se and hybrid populations and suggests that selections for phenology traits can be made effectively on doubled haploid lines before hybrid data is available.

Newly Developed MAGIC Population Allows Identification of Strong Associations and Candidate Genes for Anthocyanin Pigmentation in Eggplant

Multi-parent advanced generation inter-cross (MAGIC) populations facilitate the genetic dissection of complex quantitative traits in plants and are valuable breeding materials. We report the development of the first eggplant MAGIC population (S3 Magic EGGplant InCanum, S3MEGGIC; 8-way), constituted by the 420 S3 individuals developed from the intercrossing of seven cultivated eggplant (Solanum melongena) and one wild relative (S. incanum) parents. The S3MEGGIC recombinant population was genotyped with the eggplant 5k probes SPET platform and phenotyped for anthocyanin presence in vegetative plant tissues (PA) and fruit epidermis (FA), and for the light-insensitive anthocyanic pigmentation under the calyx (PUC). The 7,724 filtered high-confidence single-nucleotide polymorphisms (SNPs) confirmed a low residual heterozygosity (6.87%), a lack of genetic structure in the S3MEGGIC population, and no differentiation among subpopulations carrying a cultivated or wild cytoplasm. Inference of haplotype blocks of the nuclear genome revealed an unbalanced representation of the founder genomes, suggesting a cryptic selection in favour or against specific parental genomes. Genome-wide association study (GWAS) analysis for PA, FA, and PUC detected strong associations with two myeloblastosis (MYB) genes similar to MYB113 involved in the anthocyanin biosynthesis pathway, and with a COP1 gene which encodes for a photo-regulatory protein and may be responsible for the PUC trait. Evidence was found of a duplication of an ancestral MYB113 gene with a translocation from chromosome 10 to chromosome 1 compared with the tomato genome. Parental genotypes for the three genes were in agreement with the identification of the candidate genes performed in the S3MEGGIC population. Our new eggplant MAGIC population is the largest recombinant population in eggplant and is a powerful tool for eggplant genetics and breeding studies.

Genetic architecture of salt tolerance in a Multi-Parent Advanced Generation Inter-Cross (MAGIC) cowpea population

Background

Previous reports have shown that soil salinity is a growing threat to cowpea production, and thus the need for breeding salt-tolerant cowpea cultivars. A total of 234 Multi-Parent Advanced Generation Inter-Cross (MAGIC) lines along with their 8 founders were evaluated for salt tolerance under greenhouse conditions. The objectives of this study were to evaluate salt tolerance in a multi-parent advanced generation inter-cross (MAGIC) cowpea population, to identify single nucleotide polymorphism (SNP) markers associated with salt tolerance, and to assess the accuracy of genomic selection (GS) in predicting salt tolerance, and to explore possible epistatic interactions affecting salt tolerance in cowpea. Phenotyping was validated through the use of salt-tolerant and salt-susceptible controls that were previously reported. Genome-wide association study (GWAS) was conducted using a total of 32,047 filtered SNPs. The epistatic interaction analysis was conducted using the PLINK platform.

Results

Results indicated that: (1) large variation in traits evaluated for salt tolerance was identified among the MAGIC lines, (2) a total of 7, 2, 18, 18, 3, 2, 5, 1, and 23 were associated with number of dead plants, salt injury score, leaf SPAD chlorophyll under salt treatment, relative tolerance index for leaf SPAD chlorophyll, fresh leaf biomass under salt treatment, relative tolerance index for fresh leaf biomass, relative tolerance index for fresh stem biomass, relative tolerance index for the total above-ground fresh biomass, and relative tolerance index for plant height, respectively, with overlapping SNP markers between traits, (3) candidate genes encoding for proteins involved in ion transport such as Na+/Ca2+ K+ independent exchanger and H+/oligopeptide symporter were identified, and (4) epistatic interactions were identified.

Conclusions

These results will have direct applications in breeding programs aiming at improving salt tolerance in cowpea through marker-assisted selection. To the best of our knowledge, this study was one of the earliest reports using a MAGIC population to investigate the genetic architecture of salt tolerance in cowpea.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08332-y.

Physiological and Multi-Omics Approaches for Explaining Drought Stress Tolerance and Supporting Sustainable Production of Rice

Drought differs from other natural disasters in several respects, largely because of the complexity of a crop's response to it and also because we have the least understanding of a crop's inductive mechanism for addressing drought tolerance among all abiotic stressors. Overall, the growth and productivity of crops at a global level is now thought to be an issue that is more severe and arises more frequently due to climatic change-induced drought stress. Among the major crops, rice is a frontline staple cereal crop of the developing world and is critical to sustaining populations on a daily basis. Worldwide, studies have reported a reduction in rice productivity over the years as a consequence of drought. Plants are evolutionarily primed to withstand a substantial number of environmental cues by undergoing a wide range of changes at the molecular level, involving gene, protein and metabolite interactions to protect the growing plant. Currently, an in-depth, precise and systemic understanding of fundamental biological and cellular mechanisms activated by crop plants during stress is accomplished by an umbrella of -omics technologies, such as transcriptomics, metabolomics and proteomics. This combination of multi-omics approaches provides a comprehensive understanding of cellular dynamics during drought or other stress conditions in comparison to a single -omics approach. Thus a greater need to utilize information (big-omics data) from various molecular pathways to develop drought-resilient crop varieties for cultivation in ever-changing climatic conditions. This review article is focused on assembling current peer-reviewed published knowledge on the use of multi-omics approaches toward expediting the development of drought-tolerant rice plants for sustainable rice production and realizing global food security.

No disruption of rhizobial symbiosis during early stages of cowpea domestication

Modern agriculture intensely selects aboveground plant structures, while often neglecting belowground features, and evolutionary tradeoffs between these traits are predicted to disrupt host control over microbiota. Moreover, drift, inbreeding, and relaxed selection for symbiosis in crops might degrade plant mechanisms that support beneficial microbes. We studied the impact of domestication on the nitrogen fixing symbiosis between cowpea and root-nodulating Bradyrhizobium. We combined genome-wide analyses with a greenhouse inoculation study to investigate genomic diversity, heritability, and symbiosis trait variation among wild and early-domesticated cowpea genotypes. Cowpeas experienced modest decreases in genome-wide diversity during early domestication. Nonetheless, domesticated cowpeas responded efficiently to variation in symbiotic effectiveness, by forming more root nodules with nitrogen-fixing rhizobia and sanctioning non-fixing strains. Domesticated populations invested a larger proportion of host tissues into root nodules than wild cowpeas. Unlike soybean and wheat, cowpea showed no compelling evidence for degradation of symbiosis during domestication. Domesticated cowpeas experienced a less severe bottleneck than these crops and the low nutrient conditions in Africa where cowpea landraces were developed likely favored plant genotypes that gain substantial benefits from symbiosis. Breeders have largely neglected symbiosis traits, but artificial selection for improved plant responses to microbiota could increase plant performance and sustainability. This article is protected by copyright. All rights reserved.

Gene activation via Cre/lox-mediated excision in cowpea (Vigna unguiculata)

Expression of Cre recombinase by AtRps5a_pro or AtDD45_pro enabled Cre/lox-mediated recombination at an early embryonic developmental stage upon crossing, activating transgenes in the hybrid cowpea and tobacco. Genetic engineering ideally results in precise spatiotemporal control of transgene expression. To activate transgenes exclusively in a hybrid upon fertilization, we evaluated a Cre/lox-mediated gene activation system with the Cre recombinase expressed by either AtRps5a or AtDD45 promoters that showed activity in egg cells and young embryos. In crosses between Cre recombinase lines and transgenic lines harboring a lox-excision reporter cassette with ZsGreen driven by the AtUbq3 promoter after Cre/lox-mediated recombination, we observed complete excision of the lox-flanked intervening DNA sequence between the AtUbq3_pro and the ZsGreen coding sequence in F₁ progeny upon genotyping but no ZsGreen expression in F₁ seeds or seedlings. The incapability to observe ZsGreen fluorescence was attributed to the activity of the AtUbq3_pro. Strong ZsGreen expression in F₁ seeds was observed after recombination when ZsGreen was driven by the AtUbq10 promoter. Using the AtDD45_pro to express Cre resulted in more variation in recombination frequencies between transgenic lines and crosses. Regardless of the promoter used to regulate Cre, mosaic F₁ progeny were rare, suggesting gene activation at an early embryo-developmental stage. Observation of ZsGreen-expressing tobacco embryos at the globular stage from crosses with the AtRps5a_proCre lines pollinated by the AtUbq3_prolox line supported the early activation mode.

Two decades of association mapping: Insights on disease resistance in major crops

Climate change across the globe has an impact on the occurrence, prevalence, and severity of plant diseases. About 30% of yield losses in major crops are due to plant diseases; emerging diseases are likely to worsen the sustainable production in the coming years. Plant diseases have led to increased hunger and mass migration of human populations in the past, thus a serious threat to global food security. Equipping the modern varieties/hybrids with enhanced genetic resistance is the most economic, sustainable and environmentally friendly solution. Plant geneticists have done tremendous work in identifying stable resistance in primary genepools and many times other than primary genepools to breed resistant varieties in different major crops. Over the last two decades, the availability of crop and pathogen genomes due to advances in next generation sequencing technologies improved our understanding of trait genetics using different approaches. Genome-wide association studies have been effectively used to identify candidate genes and map loci associated with different diseases in crop plants. In this review, we highlight successful examples for the discovery of resistance genes to many important diseases. In addition, major developments in association studies, statistical models and bioinformatic tools that improve the power, resolution and the efficiency of identifying marker-trait associations. Overall this review provides comprehensive insights into the two decades of advances in GWAS studies and discusses the challenges and opportunities this research area provides for breeding resistant varieties.

Diversity, population structure, and linkage disequilibrium among cowpea accessions

Cowpea [Vigna unguiculata (L.) Walp] is a globally important food security crop. However, it is susceptible to pest and disease; hence, constant breeding efforts based on its diversity are required for its improvement. The present study aims to investigate the genetic diversity, population structure, and linkage disequilibrium (LD) among 274 cowpea accessions from different origins. A total of 3,127 single nucleotide polymorphism (SNP) markers generated using diversity array technology (DArT) was used. Population structure, neighbor-joining clustering, and principal component analyses indicated three subpopulations within the germplasm. Results of STRUCTURE analysis and discriminant analysis of principal components (DAPC) were complementary in assessing the structuration of the diversity among the germplasm, with the grouping of the accessions improved in DAPC. Genetic distances of 0.005-0.44 were observed among accessions. Accessions from western and central Africa, eastern and central Africa, and Asia were predominant and distributed across all subpopulations. The subpopulations had fixation indexes of 0.48-0.56. Analysis of molecular variance revealed that within subpopulation variation accounted for 81% of observed genetic variation in the germplasm. The subpopulations mainly consisted of inbred lines (inbreeding coefficient = 1) with common alleles, although they were from different geographical regions. This reflects considerable seed movement and germplasm exchange between regions. The LD was characterized by low decay for great physical distances between markers. The LD decay distance varied among chromosomes with the average distance of 80-100 kb across the genome. Thus, crop improvement is possible, and the LD will facilitate genome-wide association studies on quality attributes and critical agronomic traits in cowpea.

Crafting for a better MAGIC: systematic design and test for Multiparental Advanced Generation Inter-Cross population

Multiparental Advanced Generation Inter-Cross (MAGIC) populations are valuable crop resources with a wide array of research uses including genetic mapping of complex traits, management of genetic resources and breeding of new varieties. Multiple founders are crossed to create a rich mosaic of highly recombined founder genomes in the MAGIC recombinant inbred lines (RILs). Many variations of MAGIC population designs exist; however, a large proportion of the currently available populations have been created empirically and based on similar designs. In our evaluations of five MAGIC populations, we found that the choice of designs has a large impact on the recombination landscape in the RILs. The most popular design used in many MAGIC populations has been shown to have a bias in recombinant haplotypes and low level of unique recombinant haplotypes, and therefore is not recommended. To address this problem and provide a remedy for the future, we have developed the “magicdesign” R package for creating and testing any MAGIC population design via simulation. A Shiny app version of the package is available as well. Our “magicdesign” package provides a unifying tool and a framework for creativity and innovation in MAGIC population designs. For example, using this package, we demonstrate that MAGIC population designs can be found which are very effective in creating haplotype diversity without the requirement for very large crossing programs. Furthermore, we show that interspersing cycles of crossing with cycles of selfing is effective in increasing haplotype diversity. These approaches are applicable in species that are hard to cross or in which resources are limited.

Molecular Fingerprinting and Hybridity Authentication in Cowpea Using Single Nucleotide Polymorphism Based Kompetitive Allele-Specific PCR Assay

Optimization of a breeding program for increased genetic gain requires quality assurance (QA) and quality control (QC) at key phases of the breeding process. One vital phase in a breeding program that requires QC and QA is the choice of parents and successful hybridizations to combine parental attributes and create variations. The objective of this study was to determine parental diversity and confirm hybridity of cowpea F₁ progenies using KASP (Kompetitive Allele-Specific PCR)-based single nucleotide polymorphism (SNP) markers. A total of 1,436 F₁ plants were derived from crossing 220 cowpea breeding lines and landraces to 2 elite sister lines IT99K-573-1-1 and IT99K-573-2-1 as male parents, constituting 225 cross combinations. The progenies and the parents were genotyped with 17 QC SNP markers via high-throughput KASP genotyping assay. The QC markers differentiated the parents with mean efficiency of 37.90% and a range of 3.4-82.8%, revealing unique fingerprints of the parents. Neighbor-Joining cladogram divided the 222 parents into 3 clusters. Genetic distances between parents ranged from 0 to 3.74 with a mean of 2.41. Principal component analysis (PCA) depicted a considerable overlap between parents and F₁ progenies with more scatters among parents than the F₁s. The differentiation among parents and F₁s was best contributed to by 82% of the markers. As expected, parents and F₁s showed a significant contrast in proportion of heterozygous individuals, with mean values of 0.02 and 0.32, respectively. KASP markers detected true hybridity with 100% success rate in 72% of the populations. Overall, 79% of the putative F₁ plants were true hybrids, 14% were selfed plants, and 7% were undetermined due to missing data and lack of marker polymorphism between parents. The study demonstrated an effective application of KASP-based SNP assay in fingerprinting, confirmation of hybridity, and early detection of false F₁ plants. The results further uncovered the need to deploy markers as a QC step in a breeding program.

Disparate genetic variants associated with distinct components of cowpea resistance to the seed beetle Callosobruchus maculatus

Polygenic genome-wide association mapping identified two regions of the cowpea genome associated with different components of resistance to its major post-harvest pest, the seed beetle Callosobruchus maculatus. Cowpea (Vigna unguiculata) is an important grain and fodder crop in arid and semi-arid regions of Africa, Asia, and South America, where the cowpea seed beetle, Callosobruchus maculatus, is a serious post-harvest pest. Development of cultivars resistant to C. maculatus population growth in storage could increase grain yield and quality and reduce reliance on insecticides. Here, we use a MAGIC (multi-parent, advanced-generation intercross) population of cowpea consisting of 305 recombinant inbred lines (RILs) to identify genetic variants associated with resistance to seed beetles. Because inferences regarding the genetic basis of resistance may depend on the source of the pest or the assay protocol, we used two divergent geographic populations of C. maculatus and two complementary assays to measure several aspects of resistance. Using polygenic genome-wide association mapping models, we found that the cowpea RILs harbor substantial additive-genetic variation for most resistance measures. Variation in several components of resistance, including larval development time and survival, was largely explained by one or several linked loci on chromosome 5. A second region on chromosome 8 explained increased seed resistance via the induction of early-exiting larvae. Neither of these regions contained genes previously associated with resistance to insects that infest grain legumes. We found some evidence of gene-gene interactions affecting resistance, but epistasis did not contribute substantially to resistance variation in this mapping population. The combination of mostly high heritabilities and a relatively consistent and simple genetic architecture increases the feasibility of breeding for enhanced resistance to C. maculatus.

Genomics and breeding innovations for enhancing genetic gain for climate resilience and nutrition traits

KEY MESSAGE

Integrating genomics technologies and breeding methods to tweak core parameters of the breeder's equation could accelerate delivery of climate-resilient and nutrient rich crops for future food security. Accelerating genetic gain in crop improvement programs with respect to climate resilience and nutrition traits, and the realization of the improved gain in farmers' fields require integration of several approaches. This article focuses on innovative approaches to address core components of the breeder's equation. A prerequisite to enhancing genetic variance (σ2g) is the identification or creation of favorable alleles/haplotypes and their deployment for improving key traits. Novel alleles for new and existing target traits need to be accessed and added to the breeding population while maintaining genetic diversity. Selection intensity (i) in the breeding program can be improved by testing a larger population size, enabled by the statistical designs with minimal replications and high-throughput phenotyping. Selection priorities and criteria to select appropriate portion of the population too assume an important role. The most important component of breeder's equation is heritability (h2). Heritability estimates depend on several factors including the size and the type of population and the statistical methods. The present article starts with a brief discussion on the potential ways to enhance σ2g in the population. We highlight statistical methods and experimental designs that could improve trait heritability estimation. We also offer a perspective on reducing the breeding cycle time (t), which could be achieved through the selection of appropriate parents, optimizing the breeding scheme, rapid fixation of target alleles, and combining speed breeding with breeding programs to optimize trials for release. Finally, we summarize knowledge from multiple disciplines for enhancing genetic gains for climate resilience and nutritional traits.

Development of an Australian Bread Wheat Nested Association Mapping Population, a New Genetic Diversity Resource for Breeding under Dry and Hot Climates

Genetic diversity, knowledge of the genetic architecture of the traits of interest and efficient means of transferring the desired genetic diversity into the relevant genetic background are prerequisites for plant breeding. Exotic germplasm is a rich source of genetic diversity; however, they harbor undesirable traits that limit their suitability for modern agriculture. Nested association mapping (NAM) populations are valuable genetic resources that enable incorporation of genetic diversity, dissection of complex traits and providing germplasm to breeding programs. We developed the OzNAM by crossing and backcrossing 73 diverse exotic parents to two Australian elite varieties Gladius and Scout. The NAM parents were genotyped using the iSelect wheat 90K Infinium SNP array, and the progeny were genotyped using a custom targeted genotyping-by-sequencing assay based on molecular inversion probes designed to target 12,179 SNPs chosen from the iSelect wheat 90K Infinium SNP array of the parents. In total, 3535 BC1F4:6 RILs from 125 families with 21 to 76 lines per family were genotyped and we found 4964 polymorphic and multi-allelic haplotype markers that spanned the whole genome. A subset of 530 lines from 28 families were evaluated in multi-environment trials over three years. To demonstrate the utility of the population in QTL mapping, we chose to map QTL for maturity and plant height using the RTM-GWAS approach and we identified novel and known QTL for maturity and plant height.

Loci discovery, network-guided approach, and genomic prediction for drought tolerance index in a multi-parent advanced generation intercross (MAGIC) cowpea population

Cowpea is a nutrient-dense legume that significantly contributes to the population's diet in sub-Saharan Africa and other regions of the world. Improving cowpea cultivars to be more resilient to abiotic stress such as drought would be of great importance. The use of a multi-parent advanced generation intercross (MAGIC) population has been shown to be efficient in increasing the frequency of rare alleles that could be associated with important agricultural traits. In addition, drought tolerance index has been reported to be a reliable parameter for assessing crop tolerance to water-deficit conditions. Therefore, the objectives of this study were to evaluate the drought tolerance index for plant growth habit, plant maturity, flowering time, 100-seed weight, and grain yield in a MAGIC cowpea population, to conduct genome-wide association study (GWAS) and identify single nucleotide polymorphism (SNP) markers associated with the drought tolerance indices, to investigate the potential relationship existing between the significant loci associated with the drought tolerance indices, and to conduct genomic selection (GS). These analyses were performed using the existing phenotypic and genotypic data published for the MAGIC population which consisted of 305 F8 recombinant inbred lines (RILs) developed at University of California, Riverside. The results indicated that: (1) large variation in drought tolerance indices existed among the cowpea genotypes, (2) a total of 14, 18, 5, 5, and 35 SNPs were associated with plant growth habit change due to drought stress, and drought tolerance indices for maturity, flowering time, 100-seed weight, and grain yield, respectively, (3) the network-guided approach revealed clear interactions between the loci associated with the drought tolerance traits, and (4) the GS accuracy varied from low to moderate. These results could be applied to improve drought tolerance in cowpea through marker-assisted selection (MAS) and genomic selection (GS). To the best of our knowledge, this is the first report on marker loci associated with drought tolerance indices in cowpea.

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.

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.

Assessing diversity in canopy architecture, photosynthesis, and water-use efficiency in a cowpea magic population

Optimizing crops to improve light absorption and CO2 assimilation throughout the canopy is a proposed strategy to increase yield and meet the needs of a growing population by 2050. Globally, the greatest population increase is expected to occur in Sub-Saharan Africa where large yield gaps currently persist; therefore, it is crucial to develop high-yielding crops adapted to this region. In this study, we screened 50 cowpea (Vigna unguiculata (L.) Walp) genotypes from the multi-parent advanced generation inter-cross (MAGIC) population for canopy architectural traits, canopy photosynthesis, and water-use efficiency using a canopy gas exchange chamber in order to improve our understanding of the relationships among those traits. Canopy architecture contributed to 38.6% of the variance observed in canopy photosynthesis. The results suggest that the light environment within the canopy was a limiting factor for canopy CO2 assimilation. Traits favoring greater exposure of leaf area to light such as the width of the canopy relative to the total leaf area were associated with greater canopy photosynthesis, especially in canopies with high biomass. Canopy water-use efficiency was highly determined by canopy photosynthetic activity and therefore canopy architecture, which indicates that optimizing the canopy will also contribute to improving canopy water-use efficiency. We discuss different breeding strategies for future programs aimed at the improvement of cowpea yield for the Sub-Saharan African region. We show that breeding for high biomass will not optimize canopy CO2 assimilation and suggest that selection should include multiple canopy traits to improve light penetration.

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.

Genetic Mapping with Background Control for Quantitative Trait Locus (QTL) in 8-Parental Pure-Line Populations

Multiparental advanced generation intercross (MAGIC) populations provide abundant genetic variation for use in plant genetics and breeding. In this study, we developed a method for quantitative trait locus (QTL) detection in pure-line populations derived from 8-way crosses, based on the principles of inclusive composite interval mapping (ICIM). We considered 8 parents carrying different alleles with different effects. To estimate the 8 genotypic effects, 1-locus genetic model was first built. Then, an orthogonal linear model of phenotypes against marker variables was established to explain genetic effects of the locus. The linear model was estimated by stepwise regression and finally used for phenotype adjustment and background genetic variation control in QTL mapping. Simulation studies using 3 genetic models demonstrated that the proposed method had higher detection power, lower false discovery rate (FDR), and unbiased estimation of QTL locations compared with other methods. Marginal bias was observed in the estimation of QTL effects. An 8-parental recombinant inbred line (RIL) population previously reported in cowpea and analyzed by interval mapping (IM) was reanalyzed by ICIM and genome-wide association mapping implemented in software FarmCPU. The results indicated that ICIM identified more QTLs explaining more phenotypic variation than did IM; ICIM provided more information on the detected QTL than did FarmCPU; and most QTLs identified by IM and FarmCPU were also detected by ICIM.

Developing the role of legumes in West Africa under climate change

West Africa is faced with significant challenges from climate change, including parts of the region becoming hotter with more variable rainfall. The Sahelian region in particular is already subject to severe droughts. To address this better adapted crop varieties (such as for cowpea) are clearly a central element, a complementary one is a greater use of resilient alternative crops especially underutilized legumes particularly Bambara groundnut, African yam bean, winged bean and Kersting's groundnut. Genetic diversity of these crops conserved in genebanks and farmer's field provides an opportunity to exploit climate resilient traits using cutting-edge genomic tools and to use genomics-assisted breeding to accelerate genetic gains in combination of rapid cycle breeding strategy to develop climate-resilient cultivars for sub-Saharan Africa.

Photosynthesis in a Changing Global Climate: Scaling Up and Scaling Down in Crops

Photosynthesis is the major process leading to primary production in the Biosphere. There is a total of 7000bn tons of CO2 in the atmosphere and photosynthesis fixes more than 100bn tons annually. The CO2 assimilated by the photosynthetic apparatus is the basis of crop production and, therefore, of animal and human food. This has led to a renewed interest in photosynthesis as a target to increase plant production and there is now increasing evidence showing that the strategy of improving photosynthetic traits can increase plant yield. However, photosynthesis and the photosynthetic apparatus are both conditioned by environmental variables such as water availability, temperature, [CO2], salinity, and ozone. The "omics" revolution has allowed a better understanding of the genetic mechanisms regulating stress responses including the identification of genes and proteins involved in the regulation, acclimation, and adaptation of processes that impact photosynthesis. The development of novel non-destructive high-throughput phenotyping techniques has been important to monitor crop photosynthetic responses to changing environmental conditions. This wealth of data is being incorporated into new modeling algorithms to predict plant growth and development under specific environmental constraints. This review gives a multi-perspective description of the impact of changing environmental conditions on photosynthetic performance and consequently plant growth by briefly highlighting how major technological advances including omics, high-throughput photosynthetic measurements, metabolic engineering, and whole plant photosynthetic modeling have helped to improve our understanding of how the photosynthetic machinery can be modified by different abiotic stresses and thus impact crop production.

Genetic diversity, SNP-trait associations and genomic selection accuracy in a west African collection of Kersting's groundnut [Macrotyloma geocarpum(Harms) Maréchal & Baudet]

Understanding the mechanisms governing complex traits variation is a requirement for efficient crop improvement. In this study, the molecular characterization, marker-trait associations and the possibility for genomic selection in a collection of 281 Kersting's groundnut accessions were carried out. The diversity panel was phenotyped using an Alpha lattice design with two replicates in two contrasting environments. Accessions were genotyped using genotyping by sequencing technology. Genome-wide association analyses were performed between single nucleotide polymorphism markers and yield-related traits across tested environments. SNP markers were used to calculate the observed (Ho) and expected heterozygosity (He), and the total gene diversity (Ht). Genetic differentiation among accessions across ecological regions of origin was analysed. Our results revealed 493 quality SNPs of which 113 had a minor allele frequency>0.05, a total gene diversity of 0.43 and average Ho and He values of 0.04 and 0.22, respectively. Four clusters, highly differentiated by seed coat colour (Fst = 0.79), were identified. The population structure analysis showed two subpopulations with high differentiation across ecological regions (Fst = 0.37). The GWAS revealed 10 significant marker-trait associations, of which six SNPs were consistent across environments. The genomic selection through cross-validation showed moderate to high prediction accuracies for leaflet length, seed dimension traits, 100 seed weight, days to 50% flowering and days to maturity. This demonstrates the existence of genetic variability within Kersting's groundnut and shows the potential for the improvement of the species. The findings also provide a first insight into the phenotype-to-genotype relationships in Kersting's groundnut, using SNP markers.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Construction and integration of genetic linkage maps from three multi-parent advanced generation inter-cross populations in rice

BACKGROUND

The construction of genetic maps based on molecular markers is a crucial step in rice genetic and genomic studies. Pure lines derived from multiple parents provide more abundant genetic variation than those from bi-parent populations. Two four-parent pure-line populations (4PL1 and 4PL2) and one eight-parent pure-line population (8PL) were developed from eight homozygous indica varieties of rice by the International Rice Research Institute (IRRI). To the best of our knowledge, there have been no reports on linkage map construction and their integration in multi-parent populations of rice.

RESULTS

We constructed linkage maps for the three multi-parent populations and conducted quantitative trait locus (QTL) mapping for heading date (HD) and plant height (PH) based on the three maps by inclusive composite interval mapping (ICIM). An integrated map was built from the three individual maps and used for QTL projection and meta-analysis. QTL mapping of the three populations was also conducted based on the integrated map, and the mapping results were compared with those from meta-analysis. The three linkage maps developed for 8PL, 4PL1 and 4PL2 had 5905, 4354 and 5464 bins and were 1290.16, 1720.01 and 1560.30 cM in length, respectively. The integrated map was 3022.08 cM in length and contained 10,033 bins. Based on the three linkage maps, 3, 7 and 9 QTLs were detected for HD while 6, 9 and 10 QTLs were detected for PH in 8PL, 4PL1 and 4PL2, respectively. In contrast, 19 and 25 QTLs were identified for HD and PH by meta-analysis using the integrated map, respectively. Based on the integrated map, 5, 9, and 10 QTLs were detected for HD while 3, 10, and 12 QTLs were detected for PH in 8PL, 4PL1 and 4PL2, respectively. Eleven of these 49 QTLs coincided with those from the meta-analysis.

CONCLUSIONS

In this study, we reported the first rice linkage map constructed from one eight-parent recombinant inbred line (RIL) population and the first integrated map from three multi-parent populations, which provide essential information for QTL linkage mapping, meta-analysis, and map-based cloning in rice genetics and breeding.

A genome-wide association and meta-analysis reveal regions associated with seed size in cowpea [Vigna unguiculata (L.) Walp]

This paper combined GWAS, meta-analysis and sequence homology comparison with common bean to identify regions associated with seed size variation in domesticated cowpea. Seed size is an important trait for yield and commercial value in dry-grain cowpea. Seed size varies widely among different cowpea accessions, and the genetic basis of such variation is not yet well understood. To better decipher the genetic basis of seed size, a genome-wide association study (GWAS) and meta-analysis were conducted on a panel of 368 cowpea diverse accessions from 51 countries. Four traits, including seed weight, length, width and density were evaluated across three locations. Using 51,128 single nucleotide polymorphisms covering the cowpea genome, 17 loci were identified for these traits. One locus was common to weight, width and length, suggesting pleiotropy. By integrating synteny-based analysis with common bean, six candidate genes (Vigun05g036000, Vigun05g039600, Vigun05g204200, Vigun08g217000, Vigun11g187000, and Vigun11g191300) which are implicated in multiple functional categories related to seed size such as endosperm development, embryo development, and cell elongation were identified. These results suggest that a combination of GWAS meta-analysis with synteny comparison in a related plant is an efficient approach to identify candidate gene (s) for complex traits in cowpea. The identified loci and candidate genes provide useful information for improving cowpea varieties and for molecular investigation of seed size.

Seed Coat Pattern QTL and Development in Cowpea (Vigna unguiculata [L.] Walp.)

The appearance of the seed is an important aspect of consumer preference for cowpea (Vigna unguiculata [L.] Walp.). Seed coat pattern in cowpea has been a subject of study for over a century. This study makes use of newly available resources, including mapping populations, a reference genome and additional genome assemblies, and a high-density single nucleotide polymorphism genotyping platform, to map various seed coat pattern traits to three loci, concurrent with the Color Factor (C), Watson (W), and Holstein (H) factors identified previously. Several gene models encoding proteins involved in regulating the later stages of the flavonoid biosynthesis pathway have been identified as candidate genes, including a basic helix-loop-helix gene (Vigun07g110700) for the C locus, a WD-repeat gene (Vigun09g139900) for the W locus and an E3 ubiquitin ligase gene (Vigun10g163900) for the H locus. A model of seed coat development, consisting of six distinct stages, is described to explain some of the observed pattern phenotypes.

Components of Cowpea Resistance to the Seed Beetle Callosobruchus maculatus (Coleoptera: Chrysomelidae: Bruchinae)

Cowpea, Vigna unguiculata (L.) Walp., serves as a major source of dietary protein in many tropical and subtropical regions around the world. To identify loci associated with agronomically desirable traits, eight elite cowpea cultivars were systematically inter-crossed for eight generations to yield 305 recombinant inbred lines. Here, we investigated whether these founder parents also possess resistance to the seed beetle Callosobruchus maculatus (F.), a highly destructive post-harvest pest. We estimated larval survival in seeds, egg-to-adult development time, adult mass at emergence, and seed acceptance for oviposition. Survival varied significantly among cowpea cultivars, but the pattern was complicated by an unexpected source of mortality; on three cultivars, mature larvae in a substantial fraction of seeds (20-36%) exited seeds prematurely, and consequently failed to molt into viable adults. Even if such seeds were eliminated from the analysis, survival in the remaining seeds varied from 49 to 92% across the eight parents. Development time and body mass also differed among hosts, with particularly slow larval development on three closely related cultivars. Egg-laying females readily accepted all cultivars except one with a moderately rugose seed coat. Overall, suitability ranks of the eight cultivars depended on beetle trait; a cultivar that received the most eggs (IT82E-18) also conferred low survival. However, one cultivar (IT93K-503-1) was a relatively poor host for all traits. Given the magnitude of variation among parental cultivars, future assays of genotyped recombinant progeny can identify genomic regions and candidate genes associated with resistance to seed beetles.

Epistasis Detection and Modeling for Genomic Selection in Cowpea (Vigna unguiculata L. Walp.)

Genetic architecture reflects the pattern of effects and interaction of genes underlying phenotypic variation. Most mapping and breeding approaches generally consider the additive part of variation but offer limited knowledge on the benefits of epistasis which explains in part the variation observed in traits. In this study, the cowpea multiparent advanced generation inter-cross (MAGIC) population was used to characterize the epistatic genetic architecture of flowering time, maturity, and seed size. In addition, consideration for epistatic genetic architecture in genomic-enabled breeding (GEB) was investigated using parametric, semi-parametric, and non-parametric genomic selection (GS) models. Our results showed that large and moderate effect-sized two-way epistatic interactions underlie the traits examined. Flowering time QTL colocalized with cowpea putative orthologs of Arabidopsis thaliana and Glycine max genes like PHYTOCLOCK1 (PCL1 [Vigun11g157600]) and PHYTOCHROME A (PHY A [Vigun01g205500]). Flowering time adaptation to long and short photoperiod was found to be controlled by distinct and common main and epistatic loci. Parametric and semi-parametric GS models outperformed non-parametric GS model, while using known quantitative trait nucleotide(s) (QTNs) as fixed effects improved prediction accuracy when traits were controlled by large effect loci. In general, our study demonstrated that prior understanding of the genetic architecture of a trait can help make informed decisions in GEB.

The genome of cowpea (Vigna unguiculata [L.] Walp.)

Cowpea (Vigna unguiculata [L.] Walp.) is a major crop for worldwide food and nutritional security, especially in sub-Saharan Africa, that is resilient to hot and drought-prone environments. An assembly of the single-haplotype inbred genome of cowpea IT97K-499-35 was developed by exploiting the synergies between single-molecule real-time sequencing, optical and genetic mapping, and an assembly reconciliation algorithm. A total of 519 Mb is included in the assembled sequences. Nearly half of the assembled sequence is composed of repetitive elements, which are enriched within recombination-poor pericentromeric regions. A comparative analysis of these elements suggests that genome size differences between Vigna species are mainly attributable to changes in the amount of Gypsy retrotransposons. Conversely, genes are more abundant in more distal, high-recombination regions of the chromosomes; there appears to be more duplication of genes within the NBS-LRR and the SAUR-like auxin superfamilies compared with other warm-season legumes that have been sequenced. A surprising outcome is the identification of an inversion of 4.2 Mb among landraces and cultivars, which includes a gene that has been associated in other plants with interactions with the parasitic weed Striga gesnerioides. The genome sequence facilitated the identification of a putative syntelog for multiple organ gigantism in legumes. A revised numbering system has been adopted for cowpea chromosomes based on synteny with common bean (Phaseolus vulgaris). An estimate of nuclear genome size of 640.6 Mbp based on cytometry is presented.

Identification of Candidate Genes Controlling Black Seed Coat and Pod Tip Color in Cowpea (Vigna unguiculata [L.] Walp)

Seed coat color is an important part of consumer preferences for cowpea (Vigna unguiculata [L.] Walp). Color has been studied in numerous crop species and has often been linked to loci controlling the anthocyanin biosynthesis pathway. This study makes use of available resources, including mapping populations, a reference genome, and a high-density single nucleotide polymorphism genotyping platform, to map the black seed coat and purple pod tip color traits, with the gene symbol Bl, in cowpea. Several gene models encoding MYB domain protein 113 were identified as candidate genes. MYB domain proteins have been shown in other species to control expression of genes encoding enzymes for the final steps in the anthocyanin biosynthesis pathway. PCR analysis indicated that a presence/absence variation of one or more MYB113 genes may control the presence or absence of black pigment. A PCR marker has been developed for the MYB113 gene Vigun05g039500, a candidate gene for black seed coat color in cowpea.

Can genomics deliver climate-change ready crops?

Development of climate resilient crops with accelerating genetic gains in crops will require integration of different disciplines/technologies, to see the impact in the farmer's field. In this review, we summarize how we are utilizing our germplasm collections to identify superior alleles/haplotypes through NGS based sequencing approaches and how genomics-enabled technologies together with precise phenotyping are being used in crop breeding. Pre-breeding and genomics-assisted breeding approaches are contributing to the more efficient development of climate-resilient crops. It is anticipated that the integration of several disciplines/technologies will result in the delivery of climate change ready crops in less time.

Genome-Wide Association Study and Selection Signatures Detect Genomic Regions Associated with Seed Yield and Oil Quality in Flax

A genome-wide association study (GWAS) was performed on a set of 260 lines which belong to three different bi-parental flax mapping populations. These lines were sequenced to an averaged genome coverage of 19× using the Illumina Hi-Seq platform. Phenotypic data for 11 seed yield and oil quality traits were collected in eight year/location environments. A total of 17,288 single nucleotide polymorphisms were identified, which explained more than 80% of the phenotypic variation for days to maturity (DTM), iodine value (IOD), palmitic (PAL), stearic, linoleic (LIO) and linolenic (LIN) acid contents. Twenty-three unique genomic regions associated with 33 quantitative trait loci (QTL) for the studied traits were detected, thereby validating four genomic regions previously identified. The 33 QTL explained 48–73% of the phenotypic variation for oil content, IOD, PAL, LIO and LIN but only 8–14% for plant height, DTM and seed yield. A genome-wide selective sweep scan for selection signatures detected 114 genomic regions that accounted for 7.82% of the flax pseudomolecule and overlapped with the 11 GWAS-detected genomic regions associated with 18 QTL for 11 traits. The results demonstrate the utility of GWAS combined with selection signatures for dissection of the genetic structure of traits and for pinpointing genomic regions for breeding improvement.