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

Genome-wide analysis for root and leaf architecture traits associated with drought tolerance at the seedling stage in a highly ecologically diverse wheat population

Drought stress occurred at early growth stages in wheat affecting the following growth stages. Therefore, selecting promising drought-tolerant genotypes with highly adapted traits at the seedling stage is an important task for wheat breeders and geneticists. Few research efforts were conducted on the genetic control for drought-adaptive traits at the seedling stage in wheat. In this study, a set of 146 highly diverse spring wheat core collections representing 28 different countries was evaluated under drought stress at the seedling stage. All genotypes were exposed to drought stress for 13 days by water withholding. Leaf traits including seedling length, leaf wilting, days to wilting, leaf area, and leaf rolling were scored. Moreover, root traits such as root length, maximum width, emergence angle, tip angle, and number of roots were scored. Considerable significant genetic variation was found among all genotypes tested in these experiments. The heritability estimates ranged from 0.74 (leaf witling) to 0.99 (root tip angle). A set of nine genotypes were selected and considered drought-tolerant genotypes. Among all leaf traits, shoot length had significant correlations with all root traits under drought stress. The 146 genotypes were genotyped using the Infinium Wheat 15 K single nucleotide polymorphism (SNP) array and diversity arrays technology (DArT) marker platform. The result of genotyping revealed 12,999 SNPs and 2150 DArT markers which were used to run a genome-wide association study (GWAS). The results of GWAS revealed 169 markers associated with leaf and root traits under drought stress. Out of the 169 markers, 82 were considered major quantitative trait loci (QTL). The GWAS revealed 95 candidate genes were identified with 53 genes showing evidence for drought tolerance in wheat, while the remaining candidate genes were considered novel. No shared markers were found between leaf and root traits. The results of the study provided mapping novel markers associated with new root traits at the seedling stage. Also, the selected genotypes from different countries could be employed in future wheat breeding programs not only for improving adaptive drought-tolerant traits but also for expanding genetic diversity.

Genome-wide association study of salt tolerance at the seed germination stage in lettuce

Developing lettuce varieties with salt tolerance at the seed germination stage is essential since lettuce seeds are planted half an inch deep in soil where salt levels are often highest in the salinity-affected growing regions. Greater knowledge of genetics and genomics of salt tolerance in lettuce will facilitate breeding of improved lettuce varieties with salt tolerance. Accordingly, we conducted a genome-wide association study (GWAS) in lettuce to identify marker-trait association for salt tolerance at the seed germination stage. The study involved 445 diverse lettuce accessions and 56,820 single nucleotide polymorphism (SNP) markers obtained through genotype-by-sequencing technology using lettuce reference genome version v8. GWAS using two single-locus and three multi-locus models for germination rate (GR) under salinity stress, 5 days post seeding (GR5d_S) and a salinity susceptibility index (SSI) based on GR under salinity stress and control conditions, 5 days post seeding (SSI_GR5d) revealed 10 significant SNPs on lettuce chromosomes 2, 4, and 7. The 10 SNPs were associated with five novel QTLs for salt tolerance in lettuce, explaining phenotyping variations of 5.85%, 4.38%, 4.26%, 3.77%, and 1.80%, indicating the quantitative nature of these two salt tolerance-related traits. Using the basic local alignment search tool (BLAST) within 100 Kb upstream and downstream of each of the 10 SNPs, we identified 25 salt tolerance-related putative candidate genes including four genes encoding for major transcription factors. The 10 significant salt tolerance-related SNPs and the 25 candidate genes identified in the current study will be a valuable resource for molecular marker development and marker-assisted selection for breeding lettuce varieties with improved salt tolerance at the seed germination stage.

Effectiveness and Genetic Control of Trichoderma spp. as a Biological Control of Wheat Powdery Mildew Disease

Wheat powdery mildew (WPM) is one of the most devasting diseases that affects wheat yield worldwide. Few efforts have been made to control such a serious disease. An effective way to control WPM is urgently needed. Biological control is an effective way to control plant diseases worldwide. In this study, the efficiency of three different Trichoderma spp. in controlling WPM at the seedling growth stage was tested using 35 highly diverse wheat genotypes. Highly significant differences were found in WPM resistance among the four treatments, confirming the efficiency of Trichoderma in controlling WPM. Of the three species, T. asperellum T34 (T34) was the most effective species in controlling WPM, as it reduced the symptoms by 50.56%. A set of 196 wheat genotypes was used to identify the genetic control of the WPM resistance induced by T34. A total of 39, 27, and 18 gene models were identified to contain the significant markers under Pm, T34, and the improvement in powdery mildew resistance due to T34 (T34_improvement) conditions. Furthermore, no gene model was common between T34 and Pm, suggesting the presence of completely different genetic systems controlling the resistance under T34 and Pm. The functional annotation and biological process pathways of the detected gene models confirm their association with the normal and induced resistance. This study, for the first time, confirms the efficiency of T34 in controlling WPM and provides a deep understanding of the genetic control of induced and normal resistance to WPM.

Deciphering the genetic basis of salinity tolerance in a diverse panel of cultivated and wild soybean accessions by genome-wide association mapping

KEY MESSAGE

In a genome-wide association study involving 269 cultivated and wild soybean accessions, potential salt tolerance donors were identified along with significant markers and candidate genes, such as GmKUP6 and GmWRKY33. Salt stress remains a significant challenge in agricultural systems, notably impacting soybean productivity worldwide. A comprehensive genome-wide association study (GWAS) was conducted to elucidate the genetic underpinnings of salt tolerance and identify novel source of salt tolerance among soybean genotypes. A diverse panel comprising 269 wild and cultivated soybean accessions was subjected to saline stress under controlled greenhouse conditions. Phenotypic data revealed that salt tolerance of soybean germplasm accessions was heavily compromised by the accumulation of sodium and chloride, as indicated by highly significant positive correlations of leaf scorching score with leaf sodium/chloride content. The GWAS analysis, leveraging a dataset of 32,832 SNPs, unveiled 32 significant marker-trait associations (MTAs) across seven traits associated with salt tolerance. These markers explained a substantial portion of the phenotypic variation, ranging from 14 to 52%. Notably, 11 markers surpassed Bonferroni's correction threshold, exhibiting highly significant associations with the respective traits. Gene Ontology enrichment analysis conducted within a 100 Kb range of the identified MTAs highlighted candidate genes such as potassium transporter 6 (GmKUP6), cation hydrogen exchanger (GmCHX15), and GmWRKY33. Expression levels of GmKUP6 and GmWRKY33 significantly varied between salt-tolerant and salt-susceptible soybean accessions under salt stress. The genetic markers and candidate genes identified in this study hold promise for developing soybean varieties resilient to salinity stress, thereby mitigating its adverse effects.

Capitalizing on genebank core collections for rare and novel disease resistance loci to enhance barley resilience

In the realm of agricultural sustainability, the utilization of plant genetic resources for enhanced disease resistance is paramount. Preservation efforts in genebanks are justified by their potential contributions to future crop improvement. To capitalize on the potential of plant genetic resources, we focused on a barley core collection from the German ex situ genebank and contrasted it with a European elite collection. The phenotypic assessment included 812 plant genetic resources and 298 elites, with a particular emphasis on four disease traits (Puccinia hordei, Blumeria graminis hordei, Ramularia collo-cygni, and Rhynchosporium commune). An integrated genome-wide association study, employing both Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) and a linear mixed model, was performed to unravel the genetic underpinnings of disease resistance. A total of 932 marker-trait associations were identified and assigned to 49 quantitative trait loci. The accumulation of novel and rare resistance alleles significantly bolstered the overall resistance level in plant genetic resources. Three plant genetic resources donors with high counts of novel/rare alleles and exhibiting exceptional resistance to leaf rust and powdery mildew were identified, offering promise for targeted pre-breeding goals and enhanced resilience in future varieties. Our findings underscore the critical contribution of plant genetic resources to strengthening crop resilience and advancing sustainable agricultural practices.

Genome-wide association scan reveals the reinforcing effect of nano-potassium in improving the yield and quality of salt-stressed barley via enhancing the antioxidant defense system

Salinity is one of the major environmental factor that can greatly impact the growth, development, and productivity of barley. Our study aims to detect the natural phenotypic variation of morphological and physiological traits under both salinity and potassium nanoparticles (n-K) treatment. In addition to understanding the genetic basis of salt tolerance in barley is a critical aspect of plant breeding for stress resilience. Therefore, a foliar application of n-K was applied at the vegetative stage for 138 barley accessions to enhance salt stress resilience. Interestingly, barley accessions showed high significant increment under n-K treatment compared to saline soil. Based on genome-wide association studies (GWAS) analysis, causative alleles /reliable genomic regions were discovered underlying improved salt resilience through the application of potassium nanoparticles. On chromosome 2H, a highly significant QTN marker (A:C) was located at position 36,665,559 bp which is associated with APX, AsA, GSH, GS, WGS, and TKW under n-K treatment. Inside this region, our candidate gene is HORVU.MOREX.r3.2HG0111480 that annotated as NAC domain protein. Allelic variation detected that the accessions carrying C allele showed higher antioxidants (APX, AsA, and GSH) and barley yield traits (GS, WGS, and TKW) than the accessions carrying A allele, suggesting a positive selection of the accessions carrying C allele that could be used to develop barley varieties with improved salt stress resilience.

Genetic dissection of green pod yield in dolichos bean, an orphan vegetable legume, using new molecular markers

In the era of genomic-assisted breeding for crop improvement, developing new molecular markers and validating them for use in breeding programs are the prelude. Dolichos bean is one of the most important vegetable legume crops owing to its nutrient-rich green pods used as vegetables. Limitations in genomic resources, including molecular markers, restrict the accelerated improvement of the crop. In the present investigation, a set of 430 new simple sequence repeat markers was developed from sequence information of a reference variety. These markers included di- and tri-nucleotide repeats. The markers were assayed on an association panel, which was evaluated for green pod yield over 5 years. A multi-locus model, FarmCPU, was used to assess the marker-trait association analysis. A total of 106 marker-trait associations were identified using an efficient mixed-model approach. Tri-nucleotide repeats were more informative and predominantly associated with trait. Among these markers, 17 were associated with a high level of significance. Markers LP-D-68 and LP-D-14 were identified with a high level of significance in 5-year pooled data and explained 12.70% and 12% of the phenotypic variance, respectively. These markers associated with a high level of confidence have significant scope for use in marker-assisted selection programmes. Other associated markers may be utilized for improving parents through marker-assisted recurrent selection or genomic selection programs.

Adaptive strategies to drought stress in grasses of the poaceae family under climate change: Physiological, genetic and molecular perspectives: A review

Drought stress is one of the most critical abiotic factors which negatively impacts on growth, productivity, and survival of plants. Grass species have an important role in the sustainable intensification of cropping systems. This review focus on the specific drought tolerance characteristics in grass species and application of prevalent classical and molecular methods for genetic improvement of them to drought stress. Generally, grass species adapt to drought stress by utilizing more than one strategy including of changes in the root growth, photosynthetic pigments, activation of antioxidant enzymes, and accumulation of compatible osmolytes. They also have other specific characteristics consisted of summer dormancy, drought recovery, and persistence, which lead to drought adaptation after prolonged drought. Studies on different grasses, indicated that most of above mentioned traits usually have positive correlation with drought tolerance. Also, high heritability has been reported for most of them in different grasses. Therefore, an effective index might be considering in identification of drought tolerance genotypes. Recently, high-throughput imaging phenotyping and advanced molecular techniques such as genotyping-by-sequencing (GBS), RNA sequencing, genome-wide association study, and genome editing help conventional breeding methods to increase the accuracy, selection efficiency, genetic gains, and speed of breeding programs for developing drought tolerant cultivars.

Identification of Candidate Avirulence and Virulence Genes Corresponding to Stem Rust (Puccinia graminis f. sp. tritici) Resistance Genes in Wheat

Stem rust, caused by the biotrophic fungal pathogen Puccinia graminis f. sp. tritici (Pgt), is an important disease of wheat. However, the majority of Pgt virulence/avirulence loci and underlying genes remain uncharacterized due to the constraints of developing bi-parental populations with this obligate biotroph. Genome-wide association studies (GWAS) using a sexual Pgt population mainly collected from the Pacific Northwestern United States were used to identify candidate virulence/avirulence effector genes corresponding to the six wheat Sr genes: Sr5, Sr21, Sr8a, Sr17, Sr9a, and Sr9d. The Pgt isolates were genotyped using whole-genome shotgun sequencing that identified approximately 1.2 million single nucleotide polymorphisms (SNPs) and were phenotyped at the seedling stage on six Sr gene differential lines. Association mapping analyses identified 17 Pgt loci associated with virulence or avirulence phenotypes on six Pgt resistance genes. Among these loci, 16 interacted with a specific Sr gene, indicating Sr-gene specific interactions. However, one avirulence locus interacted with two separate Sr genes (Sr9a and Sr17), suggesting two distinct Sr genes identifying a single avirulence effector. A total of 24 unique effector gene candidates were identified, and haplotype analysis suggests that within this population, AvrSr5, AvrSr21, AvrSr8a, AvrSr17, and AvrSr9a are dominant avirulence genes, while avrSr9d is a dominant virulence gene. The putative effector genes will be fundamental for future effector gene cloning efforts, allowing for further understanding of rust effector biology and the mechanisms underlying virulence evolution in Pgt with respect to race-specific R-genes. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Combining Hyperspectral Techniques and Genome-Wide Association Studies to Predict Peanut Seed Vigor and Explore Associated Genetic Loci

Seed vigor significantly affects peanut breeding and agricultural yield by influencing seed germination and seedling growth and development. Traditional vigor testing methods are inadequate for modern high-throughput assays. Although hyperspectral technology shows potential for monitoring various crop traits, its application in predicting peanut seed vigor is still limited. This study developed and validated a method that combines hyperspectral technology with genome-wide association studies (GWAS) to achieve high-throughput detection of seed vigor and identify related functional genes. Hyperspectral phenotyping data and physiological indices from different peanut seed populations were used as input data to construct models using machine learning regression algorithms to accurately monitor changes in vigor. Model-predicted phenotypic data from 191 peanut varieties were used in GWAS, gene-based association studies, and haplotype analyses to screen for functional genes. Real-time fluorescence quantitative PCR (qPCR) was used to analyze the expression of functional genes in three high-vigor and three low-vigor germplasms. The results indicated that the random forest and support vector machine models provided effective phenotypic data. We identified Arahy.VMLN7L and Arahy.7XWF6F, with Arahy.VMLN7L negatively regulating seed vigor and Arahy.7XWF6F positively regulating it, suggesting distinct regulatory mechanisms. This study confirms that GWAS based on hyperspectral phenotyping reveals genetic relationships in seed vigor levels, offering novel insights and directions for future peanut breeding, accelerating genetic improvements, and boosting agricultural yields. This approach can be extended to monitor and explore germplasms and other key variables in various crops.

Genome-wide association study of trace elements in maize kernels

Maize (Zea mays L.), a staple food and significant economic crop, is enriched with riboflavin, micronutrients and other compounds that are beneficial for human health. As emphasis on the nutritional quality of crops increases maize research has expanded to focus on both yield and quality. This study exploreed the genetic factors influencing micronutrient levels in maize kernels through a comprehensive genome-wide association study (GWAS). We utilized a diverse panel of 244 inbred maize lines and approximately 3 million single nucleotide polymorphisms (SNPs) to investigate the accumulation of essential and trace elements including cadmium (Cd), cobalt (Co), copper (Cu), nickel (Ni), selenium (Se) and zinc (Zn). Our analysis identified 842 quantitative trait loci (QTLs), with 12 QTLs shared across multiple elements and pinpointed 524 potential genes within a 100 kb radius of these QTLs. Notably ZmHMA3 has emerged as a key candidate gene previously reported to influence the Cd accumulation. We highlighted ten pivotal genes associated with trace element transport including those encoding heavy metal ATPases, MYB transcription factors, ABC transporters and other crucial proteins involved in metal handling. Additionally, haplotype analysis revealed that eight inbred linesaccumulated relatively high levels of beneficial elements while harmful elements were minimized. These findings elucidate the genetic mechanisms underlying trace element accumulation in maize kernels and provide a foundation for the breeding of nutritionally enhanced maize varieties.

Genome-Wide Association Study as an Efficacious Approach to Discover Candidate Genes Associated with Body Linear Type Traits in Dairy Cattle

Body shape traits are very important and play a crucial role in the economic development of dairy farming. By improving the accuracy of selection for body size traits, we can enhance economic returns across the dairy industry and on farms, contributing to the future profitability of the dairy sector. Registered body conformation traits are reliable and cost-effective tools for use in national cattle breeding selection programs. These traits are significantly related to the production, longevity, mobility, health, fertility, and environmental adaptation of dairy cows. Therefore, they can be considered indirect indicators of economically important traits in dairy cows. Utilizing efficacious genetic methods, such as genome-wide association studies (GWASs), allows for a deeper understanding of the genetic architecture of complex traits through the identification and application of genetic markers. In the current review, we summarize information on candidate genes and genomic regions associated with body conformation traits in dairy cattle worldwide. The manuscript also reviews the importance of body conformation, the relationship between body conformation traits and other traits, heritability, influencing factors, and the genetics of body conformation traits. The information on candidate genes related to body conformation traits provided in this review may be helpful in selecting potential genetic markers for the genetic improvement of body conformation traits in dairy cattle.

Understanding grain development in the Poaceae family by comparing conserved and distinctive pathways through omics studies in wheat and maize

The Poaceae family, commonly known as the grass family, encompasses a diverse group of crops that play an essential role in providing food, fodder, biofuels, environmental conservation, and cultural value for both human and environmental well-being. Crops in Poaceae family are deeply intertwined with human societies, economies, and ecosystems, making it one of the most significant plant families in the world. As the major reservoirs of essential nutrients, seed grain of these crops has garnered substantial attention from researchers. Understanding the molecular and genetic processes that controls seed formation, development and maturation can provide insights for improving crop yield, nutritional quality, and stress tolerance. The diversity in photosynthetic pathways between C3 and C4 plants introduces intriguing variations in their physiological and biochemical processes, potentially affecting seed development. In this review, we explore recent studies performed with omics technologies, such as genomics, transcriptomics, proteomics and metabolomics that shed light on the mechanisms underlying seed development in wheat and maize, as representatives of C3 and C4 plants respectively, providing insights into their unique adaptations and strategies for reproductive success.

Genome-Wide Association Study for Identification of Marker-Trait Associations Conferring Resistance to Scald from Globally Collected Barley Germplasm

Scald is one of the major economically important foliar diseases in barley, causing up to 40% yield loss in susceptible varieties. The identification of quantitative trait loci and elite alleles that confer resistance to scald is imperative in reducing the threats to barley production. In this study, genome-wide association studies were conducted using a panel of 697 barley genotypes to identify quantitative trait loci for scald resistance. Field experiments were conducted over three consecutive years. Among different models used for genome-wide association studies analysis, FarmCPU was shown to be the best-suited model. Nineteen significant marker-trait associations related to scald resistance were identified across six different chromosomes. Eleven of these marker-trait associations correspond to previously reported scald resistance genes Rrs1, Rrs4, and Rrs2, respectively. Eight novel marker-trait associations were identified in this study, with the candidate genes encoding a diverse class of proteins, including region leucine-rich repeats, AP2/ERF transcription factor, homeodomain-leucine zipper, and protein kinase family proteins. The combination of identified superior alleles significantly reduces disease severity scores. The results will be valuable for marker-assisted breeding for developing scald-resistant varieties.

Genome-wide association study reveals 18 QTL for major agronomic traits in a Nordic-Baltic spring wheat germplasm

Spring wheat (Triticum aestivum L.) remains an important alternative to winter wheat cultivation at Northern latitudes due to high risk of overwintering or delayed sowing of winter wheat. We studied nine major agronomic traits in a set of 299 spring wheat genotypes in trials across 12-year-site combinations in Lithuania, Latvia, Estonia, and Norway for three consecutive years. The dataset analyzed here consisted of previously published phenotypic data collected in 2021 and 2022, supplemented with additional phenotypic data from the 2023 field season collected in this study. We combined these phenotypic datasets with previously published genotypic data generated using a 25K single nucleotide polymorphism (SNP) array that yielded 18,467 markers with a minor allele frequency above 0.05. Analysis of these datasets via genome-wide association study revealed 18 consistent quantitative trait loci (QTL) replicated in two or more trials that explained more than 5% of phenotypic variance for plant height, grain protein content, thousand kernel weight, or heading date. The most consistent markers across the tested environments were detected for plant height, thousand kernel weight, and days to heading in eight, five, and six trials, respectively. No beneficial effect of the semi-dwarfing alleles Rht-B1b and Rht-D1b on grain yield performance was observed across the 12 tested trials. Moreover, the cultivars carrying these alleles were low yielding in general. Based on principal component analysis, wheat genotypes developed in the Northern European region clustered separately from those developed at the southern latitudes, and markers associated with the clustering were identified. Important phenotypic traits, such as grain yield, days to heading, grain protein content, and thousand kernel weight were associated with this clustering of the genotype sets. Interestingly, despite being adapted to the Nordic environment, genotypes in the Northern set demonstrated lower grain yield performance across all tested environments. The results indicate that spring wheat germplasm harbors valuable QTL/alleles, and the identified trait-marker associations might be useful in improving Nordic-Baltic spring wheat germplasm under global warming conditions.

Modern Breeding Strategies and Tools for Durable Late Blight Resistance in Potato

Cultivated potato (Solanum tuberosum) is a major crop worldwide. It occupies the second place after cereals (corn, rice, and wheat). This important crop is threatened by the Oomycete Phytophthora infestans, the agent of late blight disease. This pathogen was first encountered during the Irish famine during the 1840s and is a reemerging threat to potatoes. It is mainly controlled chemically by using fungicides, but due to health and environmental concerns, the best alternative is resistance. When there is no disease, no treatment is required. In this study, we present a summary of the ongoing efforts concerning resistance breeding of potato against this devastating pathogen, P. infestans. This work begins with the search for and selection of resistance genes, whether they are from within or from outside the species. The genetic methods developed to date for gene mining, such as effectoromics and GWAS, provide researchers with the ability to identify genes of interest more efficiently. Once identified, these genes are cloned using molecular markers (MAS or QRL) and can then be introduced into different cultivars using somatic hybridization or recombinant DNA technology. More innovative technologies have been developed lately, such as gene editing using the CRISPR system or gene silencing, by exploiting iRNA strategies that have emerged as promising tools for managing Phytophthora infestans, which can be employed. Also, gene pyramiding or gene stacking, which involves the accumulation of two or more R genes on the same individual plant, is an innovative method that has yielded many promising results. All these advances related to the development of molecular techniques for obtaining new potato cultivars resistant to P. infestans can contribute not only to reducing losses in agriculture but especially to ensuring food security and safety.

Genome-wide association studies meta-analysis uncovers NOJO and SGS3 novel genes involved in Arabidopsis thaliana primary root development and plasticity

BACKGROUND

Arabidopsis thaliana primary root growth has become a model for evo-devo studies due to its simplicity and facility to record cell proliferation and differentiation. To identify new genetic components relevant to primary root growth, we used a Genome-Wide Association Studies (GWAS) meta-analysis approach using data published in the last decade. In this work, we performed intra and inter-studies analyses to discover new genetic components that could participate in primary root growth.

METHODS AND RESULTS

We used 639 accessions from nine different studies under control conditions and performed different GWAS tests. We found that primary root growth changes were associated with 41 genes, of which six (14.6%) have been previously described as inhibitors or promoters of primary root growth. The knockdown lines of two genes, Suppressor of Gene Silencing (SGS3), involved in tasiRNA processing, and a gene with a Sterile Alpha Motif (SAM) motif named NOJOCH MOOTS (NOJO), confirmed their role as repressors of primary root growth, none has been shown to participate in this developmental process before.

CONCLUSIONS

In summary, our GWAS analysis of different available studies identified new genes that participate in primary root growth; two of them were identified as repressors of primary root growth.

Natural allelic variation confers diversity in the regulation of flag leaf traits in wheat

Flag leaf (FL) dimension has been reported as a key ecophysiological aspect for boosting grain yield in wheat. A worldwide winter wheat panel consisting of 261 accessions was tested to examine the phenotypical variation and identify quantitative trait nucleotides (QTNs) with candidate genes influencing FL morphology. To this end, four FL traits were evaluated during the early milk stage under two growing seasons at the Leibniz Institute of Plant Genetics and Crop Plant Research. The results showed that all leaf traits (Flag leaf length, width, area, and length/width ratio) were significantly influenced by the environments, genotypes, and environments × genotypes interactions. Then, a genome-wide association analysis was performed using 17,093 SNPs that showed 10 novel QTNs that potentially play a role in modulating FL morphology in at least two environments. Further analysis revealed 8 high-confidence candidate genes likely involved in these traits and showing high expression values from flag leaf expansion until its senescence and also during grain development. An important QTN (wsnp_RFL_Contig2177_1500201) was associated with FL width and located inside TraesCS3B02G047300 at chromosome 3B. This gene encodes a major facilitator, sugar transporter-like, and showed the highest expression values among the candidate genes reported, suggesting their positive role in controlling flag leaf and potentially being involved in photosynthetic assimilation. Our study suggests that the detection of novel marker-trait associations and the subsequent elucidation of the genetic mechanism influencing FL morphology would be of interest for improving plant architecture, light capture, and photosynthetic efficiency during grain development.

Multi-locus genome-wide association study reveal genomic regions underlying root system architecture traits in Ethiopian sorghum germplasm

The identification of genomic regions underlying the root system architecture (RSA) is vital for improving crop abiotic stress tolerance. To improve sorghum (Sorghum bicolor L. Moench) for environmental stress tolerance, information on genetic variability and genomic regions linked to RSA traits is paramount. The aim of this study was, therefore, to investigate common quantitative trait nucleotides (QTNs) via multiple methodologies and identify genomic regions linked to RSA traits in a panel of 274 Ethiopian sorghum accessions. Multi-locus genome-wide association study was conducted using 265,944 high-quality single nucleotide polymorphism markers. Considering the QTN detected by at least three different methods, a total of 17 reliable QTNs were found to be significantly associated with root angle, number, length, and dry weight. Four QTNs were detected on chromosome SBI-05, followed by SBI-01 and SBI-02 with three QTNs each. Among the 17 QTNs, 11 are colocated with previously identified root traits quantitative trait loci and the remaining six are genome regions with novel genes. A total of 118 genes are colocated with these up- and down-streams of the QTNs. Moreover, five QTNs were found intragenic. These QTNs are S5_8994835 (number of nodal roots), S10_55702393 (number of nodal roots), S1_56872999 (nodal root angle), S9_1212069 (nodal root angle), and S5_5667192 (root dry weight) intragenic regions of Sobic.005G073101, Sobic.010G198000, Sobic.001G273000, Sobic.009G013600, and Sobic.005G054700, respectively. Particularly, Sobic.005G073101, Sobic.010G198000, and Sobic.009G013600 were found responsible for the plant growth hormone-induced RSA. These genes may regulate root development in the seedling stage. Further analysis on these genes might be important to explore the genetic structure of RSA of sorghum.

Genome-wide scanning to identify and validate single nucleotide polymorphism markers associated with drought tolerance in spring wheat seedlings

Unlike other growth stages of wheat, very few studies on drought tolerance have been done at the seedling stage, and this is due to the complexity and sensitivity of this stage to drought stress resulting from climate change. As a result, the drought tolerance of wheat seedlings is poorly understood and very few genes associated with drought tolerance at this stage were identified. To address this challenge, a set of 172 spring wheat genotypes representing 20 different countries was evaluated under drought stress at the seedling stage. Drought stress was applied on all tested genotypes by water withholding for 13 days. Two types of traits, namely morphological and physiological traits were scored on the leaves of all tested genotypes. Genome-wide association study (GWAS) is one of the effective genetic analysis methods that was used to identify target single nucleotide polymorphism (SNP) markers and candidate genes for later use in marker-assisted selection. The tested plant materials were genotyped using 25k Infinium iSelect array (25K) (herein after it will be identified as 25K) (for 172 genotypes) and genotyping-by-sequencing (GBS) (for 103 genotypes), respectively. The results of genotyping revealed 21,093 25K and 11,362 GBS-SNPs, which were used to perform GWAS analysis for all scored traits. The results of GWAS revealed that 131 and 55 significant SNPs were controlling morphological and physiological traits, respectively. Moreover, a total of eight and seven SNP markers were found to be associated with more than one morphological and physiological trait under drought stress, respectively. Remarkably, 10 significant SNPs found in this study were previously reported for their association with drought tolerance in wheat. Out of the 10 validated SNP markers, four SNPs were associated with drought at the seedling stage, while the remaining six SNPs were associated with drought stress at the reproductive stage. Moreover, the results of gene enrichment revealed 18 and six pathways as highly significant biological and molecular pathways, respectively. The selection based on drought-tolerant alleles revealed 15 genotypes with the highest number of different drought-tolerant alleles. These genotypes can be used as candidate parents in future breeding programs to produce highly drought-tolerant genotypes with high genetic diversity. Our findings in this study provide novel markers and useful information on the genetic basis of drought tolerance at early growth stages.

Sweet corn association panel and genome-wide association analysis reveal loci for chilling-tolerant germination

Sweet corn is highly susceptible to the deleterious effects of low temperatures during the initial stages of growth and development. Employing a 56K chip, high-throughput single-nucleotide polymorphism (SNP) sequencing was conducted on 100 sweet corn inbred lines. Subsequently, six germination indicators-germination rate, germination index, germination time, relative germination rate, relative germination index, and relative germination time-were utilized for genome-wide association analysis. Candidate genes were identified via comparative analysis of homologous genes in Arabidopsis and rice, and their functions were validated using quantitative real-time polymerase chain reaction (qRT-PCR). The results revealed 35,430 high-quality SNPs, 16 of which were significantly correlated. Within 50 kb upstream and downstream of the identified SNPs, 46 associated genes were identified, of which six were confirmed as candidate genes. Their expression patterns indicated that Zm11ΒHSDL5 and Zm2OGO likely play negative and positive regulatory roles, respectively, in the low-temperature germination of sweet corn. Thus, we determined that these two genes are responsible for regulating the low-temperature germination of sweet corn. This study contributes valuable theoretical support for improving sweet corn breeding and may aid in the creation of specific germplasm resources geared toward enhancing low-temperature tolerance in sweet corn.

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.

GWAS determined genetic loci associated with callus induction in oil palm tissue culture

KEY MESSAGE

GWAS identified six loci at 25 kb downstream of WAK2, a crucial gene for cell wall and callus formation, enabling development of a SNP marker for enhanced callus induction potential. Efficient callus induction is vital for successful oil palm tissue culture, yet identifying genomic loci and markers for early detection of genotypes with high potential of callus induction remains unclear. In this study, immature male inflorescences from 198 oil palm accessions (dura, tenera and pisifera) were used as explants for tissue culture. Callus induction rates were collected at one-, two- and three-months after inoculation (C1, C2 and C3) as phenotypes. Resequencing generated 11,475,258 high quality single nucleotide polymorphisms (SNPs) as genotypes. GWAS was then performed, and correlation analysis revealed a positive association of C1 with both C2 (R = 0.81) and C3 (R = 0.50), indicating that C1 could be used as the major phenotype for callus induction rate. Therefore, only significant SNPs (P ≤ 0.05) in C1 were identified to develop markers for screening individuals with high potential of callus induction. Among 21 significant SNPs in C1, LD block analysis revealed six SNPs on chromosome 12 (Chr12) potentially linked to callus formation. Subsequently, 13 SNP markers were identified from these loci and electrophoresis results showed that marker C-12 at locus Chr12_12704856 can be used effectively to distinguish the GG allele, which showed the highest probability (69%) of callus induction. Furthermore, a rapid SNP variant detection method without electrophoresis was established via qPCR-based melting curve analysis. Our findings facilitated marker-assisted selection for specific palms with high potential of callus induction using immature male inflorescence as explant, aiding ortet palm selection in oil palm tissue culture.

Genome-Wide Association Study of Rice Diversity Panel Reveals New QTLs for Tolerance to Water Deficit Under the Egyptian Conditions

Drought has a significant impact on rice yield by restricting the crop's ability to grow and develop. Producing rice cultivars adapted to water deficit conditions is still the main interest of rice breeders and geneticists. To address this challenge, a set of 413 highly diverse rice populations were evaluated under normal and water deficit conditions for two growing seasons of 2021 and 2022. High genetic variation was found among genotypes for all studied traits. The heritability estimates ranged from 0.82 (panicle length) to 0.95 (plant height). Sterility percentage (SET%) was the most trait affected by water deficit in two growing seasons. 22 Rice genotypes were classified as drought tolerant in both years. Genome-wide association mapping was performed for all traits in the two growing seasons under both conditions using a total of 700,000 SNPs. The GWAS results revealed important and major SNPs associated with all traits. 26 Significant SNPs with stable allele effects were found to be associated with yield traits under water deficit conditions in both years. The results of this study provided rice genotypes that can be adapted under water deficit conditions and important stable SNP markers that can be used for marker-assisted selection after validation in different genetic backgrounds.

GWAS in a Collection of Bulgarian Old and Modern Bread Wheat Accessions Uncovers Novel Genomic Loci for Grain Protein Content and Thousand Kernel Weight

Genetic enhancement of grain production and quality is a priority in wheat breeding projects. In this study, we assessed two key agronomic traits-grain protein content (GPC) and thousand kernel weight (TKW)-across 179 Bulgarian contemporary and historic varieties and landraces across three growing seasons. Significant phenotypic variation existed for both traits among genotypes and seasons, and no discernible difference was evident between the old and modern accessions. To understand the genetic basis of the traits, we conducted a genome-wide association study with MLM using phenotypic data from the crop seasons, best linear unbiased estimators, and genotypic data from the 25K Infinium iSelect array. As a result, we detected 16 quantitative trait nucleotides (QTNs) associated with GPC and 15 associated with TKW, all of which passed the false discovery rate threshold. Seven loci favorably influenced GPC, resulting in an increase of 1.4% to 8.1%, while four loci had a positive impact on TKW with increases ranging from 1.9% to 8.4%. While some loci confirmed previously published associations, four QTNs linked to GPC on chromosomes 2A, 7A, and 7B, as well as two QTNs related to TKW on chromosomes 1B and 6A, may represent novel associations. Annotations for proteins involved in the senescence-associated nutrient remobilization and in the following buildup of resources required for seed germination have been found for selected putative candidate genes. These include genes coding for storage proteins, cysteine proteases, cellulose-synthase, alpha-amylase, transcriptional regulators, and F-box and RWP-RK family proteins. Our findings highlight promising genomic regions for targeted breeding programs aimed at improving grain yield and protein content.

Genome-wide association study and development of molecular markers for yield and quality traits in peanut (Arachis hypogaea L.)

BACKGROUND

This study aims to decipher the genetic basis governing yield components and quality attributes of peanuts, a critical aspect for advancing molecular breeding techniques. Integrating genotype re-sequencing and phenotypic evaluations of seven yield components and two grain quality traits across four distinct environments allowed for the execution of a genome-wide association study (GWAS).

RESULTS

The nine phenotypic traits were all continuous and followed a normal distribution. The broad heritability ranged from 88.09 to 98.08%, and the genotype-environment interaction effects were all significant. There was a highly significant negative correlation between protein content (PC) and oil content (OC). The 10× genome re-sequencing of 199 peanut accessions yielded a total of 631,988 high-quality single nucleotide polymorphisms (SNPs), with 374 significant SNP loci identified in association with the nine traits of interest. Notably, 66 of these pertinent SNPs were detected in multiple environments, and 48 of them were linked to multiple traits of interest. Five loci situated on chromosome 16 (Chr16) exhibited pleiotropic effects on yield traits, accounting for 17.64-32.61% of the observed phenotypic variation. Two loci on Chr08 were found to be strongly associated with protein and oil contents, accounting for 12.86% and 14.06% of their respective phenotypic variations, respectively. Linkage disequilibrium (LD) block analysis of these seven loci unraveled five nonsynonymous variants, leading to the identification of one yield-related candidate gene and two quality-related candidate genes. The correlation between phenotypic variation and SNP loci in these candidate genes was validated by Kompetitive allele-specific PCR (KASP) marker analysis.

CONCLUSIONS

Overall, molecular markers were developed for genetic loci associated with yield and quality traits through a GWAS investigation of 199 peanut accessions across four distinct environments. These molecular tools can aid in the development of desirable peanut germplasm with an equilibrium of yield and quality through marker-assisted breeding.

Identification of superior and rare haplotypes to optimize branch number in soybean

KEY MESSAGE

Using the integrated approach in the present study, we identified eleven significant SNPs, seven stable QTLs and 20 candidate genes associated with branch number in soybean. Branch number is a key yield-related quantitative trait that directly affects the number of pods and seeds per soybean plant. In this study, an integrated approach with a genome-wide association study (GWAS) and haplotype and candidate gene analyses was used to determine the detailed genetic basis of branch number across a diverse set of soybean accessions. The GWAS revealed a total of eleven SNPs significantly associated with branch number across three environments using the five GWAS models. Based on the consistency of the SNP detection in multiple GWAS models and environments, seven genomic regions within the physical distance of ± 202.4 kb were delineated as stable QTLs. Of these QTLs, six QTLs were novel, viz., qBN7, qBN13, qBN16, qBN18, qBN19 and qBN20, whereas the remaining one, viz., qBN12, has been previously reported. Moreover, 11 haplotype blocks, viz., Hap4, Hap7, Hap12, Hap13A, Hap13B, Hap16, Hap17, Hap18, Hap19A, Hap19B and Hap20, were identified on nine different chromosomes. Haplotype allele number across the identified haplotype blocks varies from two to five, and different branch number phenotype is regulated by these alleles ranging from the lowest to highest through intermediate branching. Furthermore, 20 genes were identified underlying the genomic region of ± 202.4 kb of the identified SNPs as putative candidates; and six of them showed significant differential expression patterns among the soybean cultivars possessing contrasting branch number, which might be the potential candidates regulating branch number in soybean. The findings of this study can assist the soybean breeding programs for developing cultivars with desirable branch numbers.

Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection in Eucalyptus dunnii (Maiden)

Eucalyptus dunnii is one of the most important Eucalyptus species for short-fiber pulp production in regions where other species of the genus are affected by poor soil and climatic conditions. In this context, E. dunnii holds promise as a resource to address and adapt to the challenges of climate change. Despite its rapid growth and favorable wood properties for solid wood products, the advancement of its improvement remains in its early stages. In this work, we evaluated the performance of two single nucleotide polymorphism, (SNP), genotyping methods for population genetics analysis and Genomic Selection in E. dunnii. Double digest restriction-site associated DNA sequencing (ddRADseq) was compared with the EUChip60K array in 308 individuals from a provenance-progeny trial. The compared SNP set included 8,011 and 19,008 informative SNPs distributed along the 11 chromosomes, respectively. Although the two datasets differed in the percentage of missing data, genome coverage, minor allele frequency and estimated genetic diversity parameters, they revealed a similar genetic structure, showing two subpopulations with little differentiation between them, and low linkage disequilibrium. GS analyses were performed for eleven traits using Genomic Best Linear Unbiased Prediction (GBLUP) and a conventional pedigree-based model (ABLUP). Regardless of the SNP dataset, the predictive ability (PA) of GBLUP was better than that of ABLUP for six traits (Cellulose content, Total and Ethanolic extractives, Total and Klason lignin content and Syringyl and Guaiacyl lignin monomer ratio). When contrasting the SNP datasets used to estimate PAs, the GBLUP-EUChip60K model gave higher and significant PA values for six traits, meanwhile, the values estimated using ddRADseq gave higher values for three other traits. The PAs correlated positively with narrow sense heritabilities, with the highest correlations shown by the ABLUP and GBLUP-EUChip60K. The two genotyping methods, ddRADseq and EUChip60K, are generally comparable for population genetics and genomic prediction, demonstrating the utility of the former when subjected to rigorous SNP filtering. The results of this study provide a basis for future whole-genome studies using ddRADseq in non-model forest species for which SNP arrays have not yet been developed.

Novel SNP markers for flowering and seed quality traits in faba bean (Vicia faba L.): characterization and GWAS of a diversity panel

Faba bean (Vicia faba L.) is a legume crop grown in diverse climates worldwide. It has a high potential for increased cultivation to meet the need for more plant-based proteins in human diets, a prerequisite for a more sustainable food production system. Characterization of diversity panels of crops can identify variation in and genetic markers for target traits of interest for plant breeding. In this work, we collected a diversity panel of 220 accessions of faba bean from around the world consisting of gene bank material and commercially available cultivars. The aims of this study were to quantify the phenotypic diversity in target traits to analyze the impact of breeding on these traits, and to identify genetic markers associated with traits through a genome-wide association study (GWAS). Characterization under field conditions at Nordic latitude across two years revealed a large genotypic variation and high broad-sense heritability for eleven agronomic and seed quality traits. Pairwise correlations showed that seed yield was positively correlated to plant height, number of seeds per plant, and days to maturity. Further, susceptibility to bean weevil damage was significantly higher for early flowering accessions and accessions with larger seeds. In this study, no yield penalty was found for higher seed protein content, but protein content was negatively correlated to starch content. Our results showed that while breeding advances in faba bean germplasm have resulted in increased yields and number of seeds per plant, they have also led to a selection pressure towards delayed onset of flowering and maturity. DArTseq genotyping identified 6,606 single nucleotide polymorphisms (SNPs) by alignment to the faba bean reference genome. These SNPs were used in a GWAS, revealing 51 novel SNP markers significantly associated with ten of the assessed traits. Three markers for days to flowering were found in predicted genes encoding proteins for which homologs in other plant species regulate flowering. Altogether, this work enriches the growing pool of phenotypic and genotypic data on faba bean as a valuable resource for developing efficient breeding strategies to expand crop cultivation.

Genome-wide association study of drought tolerance in wheat (Triticum aestivum L.) identifies SNP markers and candidate genes

Drought stress poses a severe threat to global wheat production, necessitating an in-depth exploration of the genetic basis for drought tolerance associated traits. This study employed a 90 K SNP array to conduct a genome-wide association analysis, unravelling genetic determinants of key traits related to drought tolerance in wheat, namely plant height, root length, and root and shoot dry weight. Using the mixed linear model (MLM) method on 125 wheat accessions subjected to both well-watered and drought stress treatments, we identified 53 SNPs significantly associated with stress susceptibility (SSI) and tolerance indices (STI) for the targeted traits. Notably, chromosomes 2A and 3B stood out with ten and nine associated markers, respectively. Across 17 chromosomes, 44 unique candidate genes were pinpointed, predominantly located on the distal ends of 1A, 1B, 1D, 2A, 3A, 3B, 4A, 6A, 6B, 7A, 7B, and 7D chromosomes. These genes, implicated in diverse functions related to plant growth, development, and stress responses, offer a rich resource for future investigation. A clustering pattern emerged, notably with seven genes associated with SSI for plant height and four genes linked to both STI of plant height and shoot dry weight, converging on specific regions of chromosome arms of 2AS and 3BL. Additionally, shared genes encoding polygalacturonase, auxilin-related protein 1, peptide deformylase, and receptor-like kinase underscored the interconnectedness between plant height and shoot dry weight. In conclusion, our findings provide insights into the molecular mechanisms governing wheat drought tolerance, identifying promising genomic loci for further exploration and crop improvement strategies.

Advances in pharmacology, biosynthesis, and metabolic engineering of Scutellaria-specialized metabolites

Scutellaria Linn., which belongs to the family Lamiaceae, is a commonly used medicinal plant for heat clearing and detoxification. In particular, the roots of S. baicalensis and the entire herb of S. barbata have been widely used in traditional medicine for thousands of years. The main active components of Scutellaria, including: baicalein, wogonin, norwogonin, scutellarein, and their glycosides have potential or existing drug usage. However, the wild resources of Scutellaria plants have been overexploited, and degenerated germplasm resources cannot fulfill the requirements of chemical extraction and clinical usage. Metabolic engineering and green production via microorganisms provide alternative strategies for greater efficiency in the production of natural products. Here, we review the progress of: pharmacological investigations, multi-omics, biosynthetic pathways, and metabolic engineering of various Scutellaria species and their active compounds. In addition, based on multi-omics data, we systematically analyze the phylogenetic relationships of Scutellaria and predict candidate transcription factors related to the regulation of active flavonoids. Finally, we propose the prospects of directed evolution of core enzymes and genome-assisted breeding to alleviate the shortage of plant resources of Scutellaria. This review provides important insights into the sustainable utilization and development of Scutellaria resources.

Genome-wide association mapping for pre-harvest sprouting in European winter wheat detects novel resistance QTL, pleiotropic effects, and structural variation in multiple genomes

Pre-harvest sprouting (PHS), germination of seeds before harvest, is a major problem in global wheat (Triticum aestivum L.) production, and leads to reduced bread-making quality in affected grain. Breeding for PHS resistance can prevent losses under adverse conditions. Selecting resistant lines in years lacking pre-harvest rain, requires challenging of plants in the field or in the laboratory or using genetic markers. Despite the availability of a wheat reference and pan-genome, linking markers, genes, allelic, and structural variation, a complete understanding of the mechanisms underlying various sources of PHS resistance is still lacking. Therefore, we challenged a population of European wheat varieties and breeding lines with PHS conditions and phenotyped them for PHS traits, grain quality, phenological and agronomic traits to conduct genome-wide association mapping. Furthermore, we compared these marker-trait associations to previously reported PHS loci and evaluated their usefulness for breeding. We found markers associated with PHS on all chromosomes, with strong evidence for novel quantitative trait locus/loci (QTL) on chromosome 1A and 5B. The QTL on chromosome 1A lacks pleiotropic effect, for the QTL on 5B we detected pleiotropic effects on phenology and grain quality. Multiple peaks on chromosome 4A co-located with the major resistance locus Phs-A1, for which two causal genes, TaPM19 and TaMKK3, have been proposed. Mapping markers and genes to the pan-genome and chromosomal alignments provide evidence for structural variation around this major PHS-resistance locus. Although PHS is controlled by many loci distributed across the wheat genome, Phs-A1 on chromosome 4A seems to be the most effective and widely deployed source of resistance, in European wheat varieties.

Identification and In-Silico study of non-synonymous functional SNPs in the human SCN9A gene

Single nucleotide polymorphisms are the most common form of DNA alterations at the level of a single nucleotide in the genomic sequence. Genome-wide association studies (GWAS) were carried to identify potential risk genes or genomic regions by screening for SNPs associated with disease. Recent studies have shown that SCN9A comprises the NaV1.7 subunit, Na+ channels have a gene encoding of 1988 amino acids arranged into 4 domains, all with 6 transmembrane regions, and are mainly found in dorsal root ganglion (DRG) neurons and sympathetic ganglion neurons. Multiple forms of acute hypersensitivity conditions, such as primary erythermalgia, congenital analgesia, and paroxysmal pain syndrome have been linked to polymorphisms in the SCN9A gene. Under this study, we utilized a variety of computational tools to explore out nsSNPs that are potentially damaging to heath by modifying the structure or activity of the SCN9A protein. Over 14 potentially damaging and disease-causing nsSNPs (E1889D, L1802P, F1782V, D1778N, C1370Y, V1311M, Y1248H, F1237L, M936V, I929T, V877E, D743Y, C710W, D623H) were identified by a variety of algorithms, including SNPnexus, SNAP-2, PANTHER, PhD-SNP, SNP & GO, I-Mutant, and ConSurf. Homology modeling, structure validation, and protein-ligand interactions also were performed to confirm 5 notable substitutions (L1802P, F1782V, D1778N, V1311M, and M936V). Such nsSNPs may become the center of further studies into a variety of disorders brought by SCN9A dysfunction. Using in-silico strategies for assessing SCN9A genetic variations will aid in organizing large-scale investigations and developing targeted therapeutics for disorders linked to these variations.

New insights into QTNs and potential candidate genes governing rice yield via a multi-model genome-wide association study

BACKGROUND

Rice (Oryza sativa L.) is one of the globally important staple food crops, and yield-related traits are prerequisites for improved breeding efficiency in rice. Here, we used six different genome-wide association study (GWAS) models for 198 accessions, with 553,229 single nucleotide markers (SNPs) to identify the quantitative trait nucleotides (QTNs) and candidate genes (CGs) governing rice yield.

RESULTS

Amongst the 73 different QTNs in total, 24 were co-localized with already reported QTLs or loci in previous mapping studies. We obtained fifteen significant QTNs, pathway analysis revealed 10 potential candidates within 100kb of these QTNs that are predicted to govern plant height, days to flowering, and plot yield in rice. Based on their superior allelic information in 20 elite and 6 inferior genotypes, we found a higher percentage of superior alleles in the elite genotypes in comparison to inferior genotypes. Further, we implemented expression analysis and enrichment analysis enabling the identification of 73 candidate genes and 25 homologues of Arabidopsis, 19 of which might regulate rice yield traits. Of these candidate genes, 40 CGs were found to be enriched in 60 GO terms of the studied traits for instance, positive regulator metabolic process (GO:0010929), intracellular part (GO:0031090), and nucleic acid binding (GO:0090079). Haplotype and phenotypic variation analysis confirmed that LOC_OS09G15770, LOC_OS02G36710 and LOC_OS02G17520 are key candidates associated with rice yield.

CONCLUSIONS

Overall, we foresee that the QTNs, putative candidates elucidated in the study could summarize the polygenic regulatory networks controlling rice yield and be useful for breeding high-yielding varieties.

Genome-wide association mapping for seedling and adult resistance to powdery mildew in barley

KEY MESSAGE

Two new major QTL were identified for powdery mildew resistance. We confirmed that the QTL on 7HS contributed mainly to the adult-plant resistance, while another one on chromosome arm 1HS made a significant contribution to the seedling resistance. Powdery mildew (PM), caused by Blumeria hordei, can occur at all post emergent stages of barley and constantly threatens crop production. To identify more genes for effective resistance to powdery mildew for use in breeding programs, 696 barley accessions collected from different regions of the world were evaluated for PM resistance at seedling and adult growth stages in three different states of Australia. These barley accessions were genotyped using DArTSeq with over 18,000 markers for a genome-wide association study (GWAS). Using the FarmCPU model, 54 markers showed significant associations with PM resistance scored at the seedling and adult-plant stages in different states of Australia. Another 40 markers showed tentative associations (LOD > 4.0) with resistance. These markers are distributed across all seven barley chromosomes. Most of them were grouped into eleven QTL regions, coinciding with the locations of most of the reported resistance genes. Two major MTAs were identified on chromosome arms 3HS and 5HL, with one on 3HS contributing to adult plant resistance and the one on 5HL to both seedling and adult plant resistance. An MTA on 7HS contributed mainly to the adult-plant resistance, while another one on chromosome arm 1HS made a significant contribution to the seedling resistance.

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

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

Multi-model genome-wide association studies for appearance quality in rice

Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM and MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, and FASTmrMLM) genome-wide association studies were conducted in a subset of 3K-RGP consisting of 198 rice accessions with 553,831 SNP markers. A total of 594 SNP markers were identified using the mixed linear model method for grain quality traits. Additionally, 70 quantitative trait nucleotides (QTNs) detected by the ML-GWAS models were strongly associated with grain aroma (AR), head rice recovery (HRR, %), and percentage of grains with chalkiness (PGC, %). Finally, 39 QTNs were identified using single- and multi-locus GWAS methods. Among the 39 reliable QTNs, 20 novel QTNs were identified for the above-mentioned three quality-related traits. Based on annotation and previous studies, four functional candidate genes (LOC_Os01g66110, LOC_Os01g66140, LOC_Os07g44910, and LOC_Os02g14120) were found to influence AR, HRR (%), and PGC (%), which could be utilized in rice breeding to improve grain quality traits.

Comprehensive Characterization of Global Barley (Hordeum vulgare L.) Collection Using Agronomic Traits, β-Glucan Level, Phenolic Content, and Antioxidant Activities

This study characterized the diversity of 367 barley collections from 27 different countries, including 5 control cultivars, using several phenotypic traits. Morphological traits, including spike type, grain morphology, cold damage, and lodging rate, exhibited wide variations. Eighteen accessions matured early, while four accessions had longer culm and spike lengths than the controls. The ranges of total phenolic content (TPC), β-glucan content, ABTS•+ scavenging activity, DPPH• scavenging activity, and reducing power (RP) were 1.79-6.79 mg GAE/g, 0.14-8.41 g/100 g, 3.07-13.54 mg AAE/100 g, 1.56-6.24 mg AAE/g, and 1.31-7.86 mg AAE/g, respectively. Betaone, one of the controls, had the highest β-glucan content. Two accessions had β-glucan levels close to Betaone. Furthermore, 20 accessions exhibited increased TPC compared to the controls, while 5 accessions displayed elevated ABTS•+ scavenging activity. Among these, one accession also exhibited higher DPPH• scavenging activity and RP simultaneously. Based on the statistical analysis of variance, all the quantitative traits were significantly affected by the difference in origin (p < 0.05). On the other hand, grain morphology significantly affected biochemical traits. Multivariate analysis classified barley accessions into eight groups, demonstrating variations in quantitative traits. There were noteworthy correlations between biochemical and agronomical traits. Overall, this study characterized several barley varieties of different origins, anticipating future genomic research. The barley accessions with superior performances could be valuable alternatives in breeding.

Mapping yield and yield-related traits using diverse common bean germplasm

Common bean (bean) is one of the most important legume crops, and mapping genes for yield and yield-related traits is essential for its improvement. However, yield is a complex trait that is typically controlled by many loci in crop genomes. The objective of this research was to identify regions in the bean genome associated with yield and a number of yield-related traits using a collection of 121 diverse bean genotypes with different yields. The beans were evaluated in replicated trials at two locations, over two years. Significant variation among genotypes was identified for all traits analyzed in the four environments. The collection was genotyped with the BARCBean6K_3 chip (5,398 SNPs), two yield/antiyield gene-based markers, and seven markers previously associated with resistance to common bacterial blight (CBB), including a Niemann-Pick polymorphism (NPP) gene-based marker. Over 90% of the single-nucleotide polymorphisms (SNPs) were polymorphic and separated the panel into two main groups of small-seeded and large-seeded beans, reflecting their Mesoamerican and Andean origins. Thirty-nine significant marker-trait associations (MTAs) were identified between 31 SNPs and 15 analyzed traits on all 11 bean chromosomes. Some of these MTAs confirmed genome regions previously associated with the yield and yield-related traits in bean, but a number of associations were not reported previously, especially those with derived traits. Over 600 candidate genes with different functional annotations were identified for the analyzed traits in the 200-Kb region centered on significant SNPs. Fourteen SNPs were identified within the gene model sequences, and five additional SNPs significantly associated with five different traits were located at less than 0.6 Kb from the candidate genes. The work confirmed associations between two yield/antiyield gene-based markers (AYD1m and AYD2m) on chromosome Pv09 with yield and identified their association with a number of yield-related traits, including seed weight. The results also confirmed the usefulness of the NPP marker in screening for CBB resistance. Since disease resistance and yield measurements are environmentally dependent and labor-intensive, the three gene-based markers (CBB- and two yield-related) and quantitative trait loci (QTL) that were validated in this work may be useful tools for simplifying and accelerating the selection of high-yielding and CBB-resistant bean cultivars.

Hotspot Regions of Quantitative Trait Loci and Candidate Genes for Ear-Related Traits in Maize: A Literature Review

In this study, hotspot regions, QTL clusters, and candidate genes for eight ear-related traits of maize (ear length, ear diameter, kernel row number, kernel number per row, kernel length, kernel width, kernel thickness, and 100-kernel weight) were summarized and analyzed over the past three decades. This review aims to (1) comprehensively summarize and analyze previous studies on QTLs associated with these eight ear-related traits and identify hotspot bin regions located on maize chromosomes and key candidate genes associated with the ear-related traits and (2) compile major and stable QTLs and QTL clusters from various mapping populations and mapping methods and techniques providing valuable insights for fine mapping, gene cloning, and breeding for high-yield and high-quality maize. Previous research has demonstrated that QTLs for ear-related traits are distributed across all ten chromosomes in maize, and the phenotypic variation explained by a single QTL ranged from 0.40% to 36.76%. In total, 23 QTL hotspot bins for ear-related traits were identified across all ten chromosomes. The most prominent hotspot region is bin 4.08 on chromosome 4 with 15 QTLs related to eight ear-related traits. Additionally, this study identified 48 candidate genes associated with ear-related traits. Out of these, five have been cloned and validated, while twenty-eight candidate genes located in the QTL hotspots were defined by this study. This review offers a deeper understanding of the advancements in QTL mapping and the identification of key candidates associated with eight ear-related traits. These insights will undoubtedly assist maize breeders in formulating strategies to develop higher-yield maize varieties, contributing to global food security.

Analyzing genomic variation in cultivated pumpkins and identification of candidate genes controlling seed traits

Pumpkins are important vegetable crops widely grown worldwide, and seeds are considered a popular nutraceutical food and an excellent source of protein, oil, and vitamins. Seed size is one of the most important targets for commercial breeding in Cucurbita species; studies have shown that pumpkin seed size variation has a similar trend with fruit size, shape, and seed yield. However, few studies have been conducted to identify genetic loci controlling seed-related traits in cultivated pumpkins. This study analyzed the genomic characteristics of pumpkin breeding materials of 321 Cucurbita accessions collected worldwide, including Cucurbita moschata, Cucurbita maxima, and Cucurbita pepo, using extensive single nucleotide polymorphisms obtained from the genotyping-by-sequencing method, significant genetic variations were identified within and between Cucurbita species. Four major cultivar fruit types were further revealed in C. moschata species, and significant differentiation patterns were detected in several chromosomal regions. A total of 15 significant loci associated with pumpkin seed traits were mapped through a genome-wide association approach; 32 genes previously reported to be associated with seed size regulation in Arabidopsis and Oryza sativa were located in the intervals defined by linkage disequilibrium. Through this study, we gained a deep understanding of the genomic variation distribution across Cucurbita species. The available genetic resources and the associated genetic contents could be used in commercial pumpkin breeding and will facilitate molecular marker-assisted selection in pumpkin seed trait improvement.

Genetic dissection of monosaccharides contents in rice whole grain using genome-wide association study

The simplest form of carbohydrates are monosaccharides which are the building blocks for the synthesis of polymers or complex carbohydrates. Monosaccharide contents of 197 rice accessions were quantified by HPAEC-PAD in rice (Oryza sativa L.) whole grain (RWG). A genome-wide association study (GWAS) was carried out using 33,812 single nucleotide polymorphisms (SNPs) to identify corresponding genomic regions influencing neutral monosaccharides contents. In total, 49 GWAS signals contained in 17 genomic regions (quantitative trait loci [QTLs]) on seven chromosomes of rice were determined to be associated with monosaccharides contents of whole grain. The QTLs were found for fucose (1), mannose (1), xylose (2), arabinose (2), galactose (4), and rhamnose (7) contents, all of which are novel. Based on co-location of annotated rice genes in the vicinity of GWAS signals, the constituents of the whole grain were associated with the following candidate genes: arabinose content with α-N-arabinofuranosidase, pectinesterase inhibitor, and glucosamine-fructose-6-phosphate aminotransferase 1; xylose content with ZOS1-10 (a C2H2 zinc finger transcription factor [TF]); mannose content with aldose 1-epimerase-like protein and a MYB family TF; galactose content with a GT8 family member (galacturonosyltransferase-like 3), a GRAS family TF, and a GH16 family member (xyloglucan endotransglucosylase/hydrolase xyloglucan 23); fucose content with gibberellin 20 oxidase and a lysine-rich arabinogalactan protein 19, and finally rhamnose content with myo-inositol-1-phosphate synthase, UDP-arabinopyranose mutase, and COBRA-like protein precursor. The results of this study should improve our understanding of the genetic basis of the factors that might be involved in the biosynthesis, regulation, and turnover of monosaccharides in RWG, aiming to enhance the nutritional value of rice grain and impact the related industries.

Identification of QTL associated with resistance to Phytophthora fruit rot in cucumber (Cucumis sativus L.)

Phytophthora fruit rot (PFR) caused by the soilborne oomycete pathogen, Phytophthora capsici, can cause severe yield loss in cucumber. With no resistant variety available, genetic resources are needed to develop resistant varieties. The goal of this work was to identify quantitative trait loci (QTL) associated with resistance to PFR using multiple genomic approaches and populations. Two types of resistances have been identified: age-related resistance (ARR) and young fruit resistance. ARR occurs at 12-16 days post pollination (dpp), coinciding with the end of exponential fruit growth. A major QTL for ARR was discovered on chromosome 3 and a candidate gene identified based on comparative transcriptomic analysis. Young fruit resistance, which is observed during the state of rapid fruit growth prior to commercial harvest, is a quantitative trait for which multiple QTL were identified. The largest effect QTL, qPFR5.1, located on chromosome 5 was fine mapped to a 1-Mb region. Genome-wide association studies (GWAS) and extreme-phenotype genome-wide association study (XP-GWAS) for young fruit resistance were also performed on a cucumber core collection representing > 96% of the genetic diversity of the USDA cucumber germplasm. Several SNPs overlapped with the QTL identified from QTL-seq analysis on biparental populations. In addition, novel SNPs associated with the resistance were identified from the germplasm. The resistant alleles were found mostly in accessions from India and South Asia, the center of diversity for cucumber. The results from this work can be applied to future disease resistance studies and marker-assisted selection in breeding programs.

Genome wide association in Spanish bread wheat landraces identifies six key genomic regions that constitute potential targets for improving grain yield related traits

KEY MESSAGE

Association mapping conducted in 189 Spanish bread wheat landraces revealed six key genomic regions that constitute stable QTLs for yield and include 15 candidate genes. Genetically diverse landraces provide an ideal population to conduct association analysis. In this study, association mapping was conducted in a collection of 189 Spanish bread wheat landraces whose genomic diversity had been previously assessed. These genomic data were combined with characterization for yield-related traits, including grain size and shape, and phenological traits screened across five seasons. The association analysis revealed a total of 881 significant marker trait associations, involving 434 markers across the genome, that could be grouped in 366 QTLs based on linkage disequilibrium. After accounting for days to heading, we defined 33 high density QTL genomic regions associated to at least four traits. Considering the importance of detecting stable QTLs, 6 regions associated to several grain traits and thousand kernel weight in at least three environments were selected as the most promising ones to harbour targets for breeding. To dissect the genetic cause of the observed associations, we studied the function and in silico expression of the 413 genes located inside these six regions. This identified 15 candidate genes that provide a starting point for future analysis aimed at the identification and validation of wheat yield related genes.

Assessment of genetic variation among wheat genotypes for drought tolerance utilizing microsatellite markers and morpho-physiological characteristics

Drought is a major abiotic stress that severely limits sustainable wheat (Triticum aestivum L.) productivity via morphological and physio-biochemical alterations of cellular processes. The complex nature and polygenic control of drought tolerance traits make breeding tolerant genotypes quite challenging. However, naturally occurring variabilities among wheat germplasm resources could potentially help combating drought. The present study was conducted to assess the drought tolerance of 18 Bangladeshi hexaploid wheat genotypes, focusing on the identification of potent sources of diversity by combining microsatellite markers, also known as single sequence repeat markers, and morpho-physiological characteristics that might help accelerating wheat crop improvement programs. Initially, the genotypes were evaluated using 25 microsatellite markers followed by an on-field evaluation of 7 morphological traits (plant height, spike number, spike length, grains per spike, 1000-grain weight, grain yield, biological yield) and 6 physiological traits (SPAD value, membrane stability index, leaf relative water content, proline content, canopy temperature depression, and leaf K+ ion content). The field-trial was conducted in a factorial fashion of 18 wheat genotypes and two water regimes (control and drought) following a split-plot randomized complete block design. Regardless of genotype, drought was significantly damaging for all the tested traits; however, substantial variability in drought stress tolerance was evident among the genotypes. Spike length, 1000-grain weight, SPAD value, leaf relative water content, canopy temperature depression, proline content, and potassium (K+) ion content were the most representative of drought-induced growth and yield impairments and also correlated well with the contrasting ability of genotypic tolerance. Microsatellite markers amplified 244 alleles exhibiting 79% genetic diversity. Out of 25 markers, 23 was highly polymorphic showing 77% average polymorphism. Morpho-physiological trait-based hierarchical clustering and microsatellite marker-based neighbor-jointing clustering both revealed three genotypic clusters with 71% co-linearity between them. In both cases, the genotypes Kanchan, BAW-1147, BINA Gom 1, BARI Gom 22, BARI Gom 26, and BARI Gom 33 were found to be comparatively more tolerant than the other tested genotypes, showing potential for cultivation in water-deficit environments. The findings of this study would contribute to the present understanding of drought tolerance in wheat and would provide a basis for future genotype selection for drought-tolerant wheat breeding programs.

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

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

Detection and characterization of spike architecture based on deep learning and X-ray computed tomography in barley

BACKGROUND

Spike is the grain-bearing organ in cereal crops, which is a key proxy indicator determining the grain yield and quality. Machine learning methods for image analysis of spike-related phenotypic traits not only hold the promise for high-throughput estimating grain production and quality, but also lay the foundation for better dissection of the genetic basis for spike development. Barley (Hordeum vulgare L.) is one of the most important crops globally, ranking as the fourth largest cereal crop in terms of cultivated area and total yield. However, image analysis of spike-related traits in barley, especially based on CT-scanning, remains elusive at present.

RESULTS

In this study, we developed a non-invasive, high-throughput approach to quantitatively measuring the multitude of spike architectural traits in barley through combining X-ray computed tomography (CT) and a deep learning model (UNet). Firstly, the spikes of 11 barley accessions, including 2 wild barley, 3 landraces and 6 cultivars were used for X-ray CT scanning to obtain the tomographic images. And then, an optimized 3D image processing method was used to point cloud data to generate the 3D point cloud images of spike, namely 'virtual' spike, which is then used to investigate internal structures and morphological traits of barley spikes. Furthermore, the virtual spike-related traits, such as spike length, grain number per spike, grain volume, grain surface area, grain length and grain width as well as grain thickness were efficiently and non-destructively quantified. The virtual values of these traits were highly consistent with the actual value using manual measurement, demonstrating the accuracy and reliability of the developed model. The reconstruction process took 15 min approximately, 10 min for CT scanning and 5 min for imaging and features extraction, respectively.

CONCLUSIONS

This study provides an efficient, non-invasive and useful tool for dissecting barley spike architecture, which will contribute to high-throughput phenotyping and breeding for high yield in barley and other crops.

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.

Association mapping in bambara groundnut [Vigna subterranea (L.) Verdc.] reveals loci associated with agro-morphological traits

BACKGROUND

Genome-wide association studies (GWAS) are important for the acceleration of crop improvement through knowledge of marker-trait association (MTA). This report used DArT SNP markers to successfully perform GWAS on agro-morphological traits using 270 bambara groundnut [Vigna subterranea (L.) Verdc.] landraces sourced from diverse origins. The study aimed to identify marker traits association for nine agronomic traits using GWAS and their candidate genes. The experiment was conducted at two different locations laid out in alpha lattice design. The cowpea [Vigna unguiculata (L.) Walp.] reference genome (i.e. legume genome most closely related to bambara groundnut) assisted in the identification of candidate genes.

RESULTS

The analyses showed that linkage disequilibrium was found to decay rapidly with an average genetic distance of 148 kb. The broadsense heritability was relatively high and ranged from 48.39% (terminal leaf length) to 79.39% (number of pods per plant). The GWAS identified a total of 27 significant marker-trait associations (MTAs) for the nine studied traits explaining 5.27% to 24.86% of phenotypic variations. Among studied traits, the highest number of MTAs was obtained from seed coat colour (6) followed by days to flowering (5), while the least is days to maturity (1), explaining 5.76% to 11.03%, 14.5% to 19.49%, and 11.66% phenotypic variations, respectively. Also, a total of 17 candidate genes were identified, varying in number for different traits; seed coat colour (6), days to flowering (3), terminal leaf length (2), terminal leaf width (2), number of seed per pod (2), pod width (1) and days to maturity (1).

CONCLUSION

These results revealed the prospect of GWAS in identification of SNP variations associated with agronomic traits in bambara groundnut. Also, its present new opportunity to explore GWAS and marker assisted strategies in breeding of bambara groundnut for acceleration of the crop improvement.