Genome-wide association mapping reveals novel genes and genomic regions controlling root-lesion nematode resistance in chickpea mini core collection.

Root-lesion nematodes (RLN) pose a significant threat to chickpea (Cicer arietinum L.) by damaging the root system and causing up to 25% economic losses due to reduced yield. Worldwide commercially grown chickpea varieties lack significant genetic resistance to RLN, necessitating the identification of genetic variants contributing to natural resistance. This study identifies genomic loci responsible for resistance to the RLN, Pratylenchus thornei Sher & Allen, in chickpea by utilizing high-quality single nucleotide polymorphisms from whole-genome sequencing data of 202 chickpea accessions. Phenotypic evaluations of the genetically diverse set of chickpea accessions in India and Australia revealed a wide range of responses from resistant to susceptible. Genome-wide association studies (GWAS) employing Fixed and Random Model Circulating Probability Unification (FarmCPU) and Bayesian-Information and Linkage-Disequilibrium Iteratively Nested Keyway (BLINK) models identified 44 marker-trait associations distributed across all chromosomes except Ca1. Crucially, genomic regions on Ca2 and Ca5 consistently display significant associations across locations. Of 25 candidate genes identified, five genes were putatively involved in RLN resistance response (glucose-6-phosphate dehydrogenase, heat shock proteins, MYB-like DNA-binding protein, zinc finger FYVE protein and pathogenesis-related thaumatin-like protein). One notably identified gene (Ca_10016) presents four haplotypes, where haplotypes 1-3 confer moderate susceptibility, and haplotype 4 contributes to high susceptibility to RLN. This information provides potential targets for marker development to enhance breeding for RLN resistance in chickpea. Additionally, five potential resistant genotypes (ICC3512, ICC8855, ICC5337, ICC8950, and ICC6537) to P. thornei were identified based on their performance at a specific location. The study's significance lies in its comprehensive approach, integrating multiple-location phenotypic evaluations, advanced GWAS models, and functional genomics to unravel the genetic basis of P. thornei resistance. The identified genomic regions, candidate genes, and haplotypes offer valuable insights for breeding strategies, paving the way for developing chickpea varieties resilient to P. thornei attack.

Genome-wide identification and expression profiling of growth­regulating factor (GRF) and GRF­interacting factor (GIF) gene families in chickpea and pigeonpea.

The growth-regulating factor (GRF) and GRF-interacting factor (GIF) families encode plant-specific transcription factors and play vital roles in plant development and stress response processes. Although GRF and GIF genes have been identified in various plant species, there have been no reports of the analysis and identification of the GRF and GIF transcription factor families in chickpea (Cicer arietinum) and pigeonpea (Cajanus cajan). The present study identified seven CaGRFs, eleven CcGRFs, four CaGIFs, and four CcGIFs. The identified proteins were grouped into eight and three clades for GRFs and GIFs, respectively based on their phylogenetic relationships. A comprehensive in-silico analysis was performed to determine chromosomal location, sub-cellular localization, and types of regulatory elements present in the putative promoter region. Synteny analysis revealed that GRF and GIF genes showed diploid-polyploid topology in pigeonpea, but not in chickpea. Tissue-specific expression data at the vegetative and reproductive stages of the plant showed that GRFs and GIFs were strongly expressed in tissues like embryos, pods, and seeds, indicating that GRFs and GIFs play vital roles in plant growth and development. This research characterized GRF and GIF families and hints at their primary roles in the chickpea and pigeonpea growth and developmental process. Our findings provide potential gene resources and vital information on GRF and GIF gene families in chickpea and pigeonpea, which will help further understand the regulatory role of these gene families in plant growth and development.

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

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

Genome-wide association mapping of nutritional traits for designing superior chickpea varieties.

Micronutrient malnutrition is a serious concern in many parts of the world; therefore, enhancing crop nutrient content is an important challenge. Chickpea (Cicer arietinum L.), a major food legume crop worldwide, is a vital source of protein and minerals in the vegetarian diet. This study evaluated a diverse set of 258 chickpea germplasm accessions for 12 key nutritional traits. A significant variation was observed for several nutritional traits, including crude protein (16.56-24.64/100 g), ß-Carotene (0.003-0.104 mg/100 g), calcium (60.69-176.55 mg/100 g), and folate (0.413-6.537 mg/kg). These data, combined with the available whole-genome sequencing data for 318,644 SNPs, were used in genome-wide association studies comprising single-locus and multi-locus models. We also explored the effect of varying the minor allele frequency (MAF) levels and heterozygosity. We identified 62 significant marker-trait associations (MTAs) explaining up to 28.63% of the phenotypic variance (PV), of which nine were localized within genes regulating G protein-coupled receptor signaling pathway, proteasome assembly, intracellular signal transduction, and oxidation-reduction process, among others. The significant effect MTAs were located primarily on Ca1, Ca3, Ca4, and Ca6. Importantly, varying the level of heterozygosity was found to significantly affect the detection of associations contributing to traits of interest. We further identified seven promising accessions (ICC10399, ICC1392, ICC1710, ICC2263, ICC1431, ICC4182, and ICC16915) with superior agronomic performance and high nutritional content as potential donors for developing nutrient-rich, high-yielding chickpea varieties. Validation of the significant MTAs with higher PV could identify factors controlling the nutrient acquisition and facilitate the design of biofortified chickpeas for the future.

A chickpea genetic variation map based on the sequencing of 3,366 genomes.

Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources1. So far, few chickpea (Cicer arietinum) germplasm accessions have been characterized at the genome sequence level2. Here we present a detailed map of variation in 3,171 cultivated and 195 wild accessions to provide publicly available resources for chickpea genomics research and breeding. We constructed a chickpea pan-genome to describe genomic diversity across cultivated chickpea and its wild progenitor accessions. A divergence tree using genes present in around 80% of individuals in one species allowed us to estimate the divergence of Cicer over the last 21 million years. Our analysis found chromosomal segments and genes that show signatures of selection during domestication, migration and improvement. The chromosomal locations of deleterious mutations responsible for limited genetic diversity and decreased fitness were identified in elite germplasm. We identified superior haplotypes for improvement-related traits in landraces that can be introgressed into elite breeding lines through haplotype-based breeding, and found targets for purging deleterious alleles through genomics-assisted breeding and/or gene editing. Finally, we propose three crop breeding strategies based on genomic prediction to enhance crop productivity for 16 traits while avoiding the erosion of genetic diversity through optimal contribution selection (OCS)-based pre-breeding. The predicted performance for 100-seed weight, an important yield-related trait, increased by up to 23% and 12% with OCS- and haplotype-based genomic approaches, respectively.

Major QTLs and Potential Candidate Genes for Heat Stress Tolerance Identified in Chickpea (Cicer arietinum L.).

In the context of climate change, heat stress during the reproductive stages of chickpea (Cicer arietinum L.) leads to significant yield losses. In order to identify the genomic regions responsible for heat stress tolerance, a recombinant inbred line population derived from DCP 92-3 (heat sensitive) and ICCV 92944 (heat tolerant) was genotyped using the genotyping-by-sequencing approach and evaluated for two consecutive years (2017 and 2018) under normal and late sown or heat stress environments. A high-density genetic map comprising 788 single-nucleotide polymorphism markers spanning 1,125 cM was constructed. Using composite interval mapping, a total of 77 QTLs (37 major and 40 minor) were identified for 12 of 13 traits. A genomic region on CaLG07 harbors quantitative trait loci (QTLs) explaining >30% phenotypic variation for days to pod initiation, 100 seed weight, and for nitrogen balance index explaining >10% PVE. In addition, we also reported for the first time major QTLs for proxy traits (physiological traits such as chlorophyll content, nitrogen balance index, normalized difference vegetative index, and cell membrane stability). Furthermore, 32 candidate genes in the QTL regions that encode the heat shock protein genes, heat shock transcription factors, are involved in flowering time regulation as well as pollen-specific genes. The major QTLs reported in this study, after validation, may be useful in molecular breeding for developing heat-tolerant superior lines or varieties.

Genome-Wide SNP Discovery and Mapping QTLs for Seed Iron and Zinc Concentrations in Chickpea (Cicer arietinum L.).

Biofortification through plant breeding is a cost-effective and sustainable approach towards addressing micronutrient malnutrition prevailing across the globe. Screening cultivars for micronutrient content and identification of quantitative trait loci (QTLs)/genes and markers help in the development of biofortified varieties in chickpea (Cicer arietinum L.). With the aim of identifying the genomic regions controlling seed Fe and Zn concentrations, the F2:3 population derived from a cross between MNK-1 and Annigeri 1 was genotyped using genotyping by sequencing approach and evaluated for Fe and Zn concentration. An intraspecific genetic linkage map comprising 839 single nucleotide polymorphisms (SNPs) spanning a total distance of 1,088.04 cM with an average marker density of 1.30 cM was constructed. By integrating the linkage map data with the phenotypic data of the F2:3 population, a total of 11 QTLs were detected for seed Fe concentration on CaLG03, CaLG04, and CaLG05, with phenotypic variation explained ranging from 7.2% (CaqFe3.4) to 13.4% (CaqFe4.2). For seed Zn concentration, eight QTLs were identified on CaLG04, CaLG05, and CaLG08. The QTLs individually explained phenotypic variations ranging between 5.7% (CaqZn8.1) and 13.7% (CaqZn4.3). Three QTLs for seed Fe and Zn concentrations (CaqFe4.4, CaqFe4.5, and CaqZn4.1) were colocated in the "QTL-hotspot" region on CaLG04 that harbors several drought tolerance-related QTLs. We identified genes in the QTL regions that encode iron-sulfur metabolism and zinc-dependent alcohol dehydrogenase activity on CaLG03, iron ion binding oxidoreductase on CaLG04, and zinc-induced facilitator-like protein and ZIP zinc/iron transport family protein on CaLG05. These genomic regions and the associated markers can be used in marker-assisted selection to increase seed Fe and Zn concentrations in agronomically superior chickpea varieties.

Abnormal accumulation of human transmembrane (TMEM)-176A and 176B proteins is associated with cancer pathology.

Transmembrane (TMEM)-176A and 176B proteins belong to the MS4A family of proteins whose function in the immune system remains unclear. TMEM176A transcripts were previously shown to be elevated in liver cancer or kidney tissue with proteinuria, while marked changes in TMEM176B transcripts have been found in tolerated tissue allografts and neoplastic fibroblasts. To study the functional relationship between human TMEM176A and 176B and their putative link to cancer, we used polymerase chain reaction and biochemical assays. Here, we show that TMEM176A and 176B are widely expressed in all human tissues examined. Co-immunoprecipitation of heterologously expressed TMEM176A and 176B revealed direct physical interaction. To determine the relevance of such interaction to cancer pathology, we analyzed biopsied tissue samples from a variety of normal and cancer tissues. Our data reveal that human TMEM176A and 176B protein levels are significantly elevated in lymphoma, but not in normal tissues. The protein levels of TMEM176A are also significantly increased in lung carcinoma. Finally, analysis of the protein expression ratio of TMEM176A over 176B showed significant differences between normal and cancer tissues of the breast, lymph, skin, and liver, which indicates that both TMEM proteins could be potential useful markers for certain human cancers.