Genome-Wide Association Analyses Track Genomic Regions for Resistance to Ascochyta rabiei in Australian Chickpea Breeding Germplasm

Mousa K, Istanbuli T, Abd El-Maksoud MM, Tawkaz S, Hamwieh A. Unveiling the genetic basis of Fusarium wilt resistance in chickpea using GWAS analysis and characterization of candidate genes

Introduction: Chickpea is a legume crop that thrives in regions with semi-arid or temperate climates. Its seeds are an excellent source of proteins, carbohydrates, and minerals, especially high-quality proteins. Chickpea cultivation faces several challenges including Fusarium wilt (FW), a major fungal disease that significantly reduces productivity. Methods: In this study, a Genome-wide Association Analysis (GWAS) was conducted to identify multiple genomic loci associated with FW resistance in chickpea. We conducted a comprehensive evaluation of 180 chickpea genotypes for FW resistance across three distinct locations (Ethiopia, Tunisia, and Lebanon) during the 2-year span from 2015 to 2016. Disease infection measurements were recorded, and the wilt incidence of each genotype was calculated. We employed a set of 11,979 single nucleotide polymorphisms (SNPs) markers distributed across the entire chickpea genome for SNP genotyping. Population structure analysis was conducted to determine the genetic structure of the genotypes. Results and Discussion: The population structure unveiled that the analyzed chickpea germplasm could be categorized into four sub-populations. Notably, these sub-populations displayed diverse geographic origins. The GWAS identified 11 SNPs associated with FW resistance, dispersed across the genome. Certain SNPs were consistent across trials, while others were specific to particular environments. Chromosome CA2 harbored five SNP markers, CA5 featured two, and CA4, CA6, CA7, and CA8 each had one representative marker. Four SNPs demonstrated an association with FW resistance, consistently observed across a minimum of three distinct environments. These SNPs included SNP5826041, SNP5825086, SNP11063413, SNP5825195, which located in CaFeSOD, CaS13like, CaNTAQ1, and CaAARS genes, respectively. Further investigations were conducted to gain insights into the functions of these genes and their role in FW resistance. This progress holds promise for reducing the negative impact of the disease on chickpea production.

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.

Genome wide association study of genes controlling resistance to Didymella rabiei Pathotype IV through genotyping by sequencing in chickpeas (Cicer arietinum)

Ascochyta blight (AB) is a major disease in chickpeas (Cicer arietinum L.) that can cause a yield loss of up to 100%. Chickpea germplasm collections at the center of origin offer great potential to discover novel sources of resistance to pests and diseases. Herein, 189 Cicer arietinum samples were genotyped via genotyping by sequencing. This chickpea collection was phenotyped for resistance to an aggressive Turkish Didymella rabiei Pathotype IV isolate. Genome-wide association studies based on different models revealed 19 single nucleotide polymorphism (SNP) associations on chromosomes 1, 2, 3, 4, 7, and 8. Although eight of these SNPs have been previously reported, to the best of our knowledge, the remaining ten were associated with AB resistance for the first time. The regions identified in this study can be addressed in future studies to reveal the genetic mechanism underlying AB resistance and can also be utilized in chickpea breeding programs to improve AB resistance in new chickpea varieties.

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

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

Multi-locus genome-wide association study of chickpea reference set identifies genetic determinants of Pratylenchus thornei resistance

Pratylenchus thornei is an economically important species of root-lesion nematode adversely affecting chickpea (Cicer arietinum) yields globally. Integration of resistant crops in farming systems is recognised as the most effective and sustainable management strategy for plant-parasitic nematodes. However, breeding for P. thornei resistance in chickpea is limited by the lack of genetic diversity. We deployed a genome-wide association approach to identify genomic regions and candidate genes associated with P. thornei resistance in 285 genetically diverse chickpea accessions. Chickpea accessions were phenotyped for P. thornei resistance in replicated glasshouse experiments performed for two years (2018 and 2020). Whole genome sequencing data comprising 492,849 SNPs were used to implement six multi-locus GWAS models. Fourteen chickpea genotypes were found to be resistant to P. thornei. Of the six multi-locus GWAS methods deployed, FASTmrMLM was found to be the best performing model. In all, 24 significant quantitative trait nucleotides (QTNs) were identified, of which 13 QTNs were associated with lower nematode population density and 11 QTNs with higher nematode population density. These QTNs were distributed across all of the chickpea chromosomes, except chromosome 8. We identified, receptor-linked kinases (RLKs) on chromosomes 1, 4 and 6, GDSL-like Lipase/Acylhydrolase on chromosome 3, Aspartic proteinase-like and Thaumatin-like protein on chromosome 4, AT-hook DNA-binding and HSPRO2 on chromosome 6 as candidate genes for P. thornei resistance in the chickpea reference set. New sources of P. thornei resistant genotypes were identified that can be harnessed into breeding programs and putative candidate P. thornei resistant genes were identified that can be explored further to develop molecular markers and accelerate the incorporation of improved P. thornei resistance into elite chickpea cultivars.

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

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