Search

The development of genomic selection (GS) methods has allowed plant breeding programs to select favorable lines using genomic data before performing field trials. Improvements in genotyping technology have yielded high-dimensional genomic marker data which can be difficult to incorporate into statistical models. In this paper, we investigated the utility of applying dimensionality reduction (DR) methods as a pre-processing step for GS methods. We compared five DR methods and studied the trend in the prediction accuracies of each method as a function of the number of features retained. The effect of DR methods was studied using three models that involved the main effects of line, environment, marker, and the genotype by environment interactions. The methods were applied on a real data set containing 315 lines phenotyped in nine environments with 26,817 markers each. Regardless of the DR method and prediction model used, only a fraction of features was sufficient to achieve maximum correlation. Our results underline the usefulness of DR methods as a key pre-processing step in GS models to improve computational efficiency in the face of ever-increasing size of genomic data.

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), β-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.

Chickpea yield is severely affected by drought stress, which is a complex quantitative trait regulated by multiple small-effect genes. Identifying genomic regions associated with drought tolerance component traits may increase our understanding of drought tolerance mechanisms and assist in the development of drought-tolerant varieties. Here, a total of 187 F8 recombinant inbred lines (RILs) developed from an interspecific cross between drought-tolerant genotype GPF 2 (Cicer arietinum) and drought-sensitive accession ILWC 292 (C. reticulatum) were evaluated to identify quantitative trait loci (QTLs) associated with drought tolerance component traits. A total of 21 traits, including 12 morpho-physiological traits and nine root-related traits, were studied under rainfed and irrigated conditions. Composite interval mapping identified 31 QTLs at Ludhiana and 23 QTLs at Faridkot locations for morphological and physiological traits, and seven QTLs were identified for root-related traits. QTL analysis identified eight consensus QTLs for six traits and five QTL clusters containing QTLs for multiple traits on linkage groups CaLG04 and CaLG06. The identified major QTLs and genomic regions associated with drought tolerance component traits can be introgressed into elite cultivars using genomics-assisted breeding to enhance drought tolerance in chickpea.

Pusa 391, a megadesichickpea variety with medium maturity duration is extensively cultivated in the Central Zone of India. Of late, this variety has become susceptible to Fusarium wilt (FW), which has drastic impact on its yield. Presence of variability in the wilt causing pathogen,Fusarium oxysporumf.sp.ciceri(foc) across geographical locations necessitates the role of pyramiding for FW resistance for different races (foc1,2,3,4 and 5). Subsequently, the introgression lines developed in Pusa 391 genetic background were subjected to foreground selection using three SSR markers (GA16, TA 27 and TA 96) while 48 SSR markers uniformly distributed on all chromosomes, were used for background selection to observe the recovery of recurrent parent genome (RPG). BC1F1lines with 75–85% RPG recovery were used to generate BC2F1. The plants that showed more than 90% RPG recovery in BC2F1were used for generating BC3F1. The plants that showed more than 96% RPG recovery were selected and selfed to generate BC3F3. Multi-location evaluation of advanced introgression lines (BC2F3) in six locations for grain yield (kg/ha), days to fifty percent flowering, days to maturity, 100 seed weight and disease incidence was done. In case of disease incidence, the genotype IL1 (BGM 20211) was highly resistant to FW in Junagarh, Indore, New Delhi, Badnapur and moderately resistant at Sehore and Nandyal. GGE biplot analysis revealed that IL1(BGM20211) was the most stable genotype at Junagadh, Sehore and Nandyal. GGE biplot analysis revealed that IL1(BGM 20211) and IL4(BGM 20212) were the top performers in yield and highly stable across six environments and were nominated for Advanced Varietal Trials (AVT) of AICRP (All India Coordinated Research Project on Chickpea) in 2018–19. BGM20211 and BGM 20212 recorded 29 and 28.5% average yield gain over the recurrent parent Pusa 391, in the AVT-1 and AVT-2 over five environments. Thus, BGM20211 was identified for release and notified as Pusa Manav/Pusa Chickpea 20211 for Madhya Pradesh, Gujarat and Maharashtra, Southern Rajasthan, Bundhelkhand region of Uttar Pradesh states by the Central Sub-Committees on Crop Standards, Notification and Release of Varieties of Agricultural Crops, Ministry of Agriculture and Farmers Welfare, Government of India, for commercial cultivation in India (Gazette notification number S.O.500 (E) dt. 29-1-2021).Such pyramided lines give resilience to multiple races of fusarium wilt with added yield advantage.

The world faces a grave situation of nutrient deficiency as a consequence of increased uptake of calorie-rich food that threaten nutritional security. More than half the world’s population is affected by different forms of malnutrition. Unhealthy diets associated with poor nutrition carry a significant risk of developing non-communicable diseases, leading to a high mortality rate. Although considerable efforts have been made in agriculture to increase nutrient content in cereals, the successes are insufficient. The number of people affected by different forms of malnutrition has not decreased much in the recent past. While legumes are an integral part of the food system and widely grown in sub- Saharan Africa and South Asia, only limited efforts have been made to increase their nutrient content in these regions. Genetic variation for a majority of nutritional traits that ensure nutritional security in adverse conditions exists in the germplasm pool of legume crops. This diversity can be utilized by selective breeding for increased nutrients in seeds. The targeted identification of precise factors related to nutritional traits and their utilization in a breeding program can help mitigate malnutrition. The principal objective of this review is to present the molecular mechanisms of nutrient acquisition, transport and metabolism to support a biofortification strategy in legume crops to contribute to addressing malnutrition.

Legumes play a vital role in ensuring global nutritional food security and improving soil quality through nitrogen fixation. Accelerated higher genetic gains is required to meet the demand of ever increasing global population. In recent years, speedy developments have been witnessed in legume genomics due to advancements in next-generation sequencing (NGS) and high-throughput genotyping technologies. Reference genome sequences for many legume crops have been reported in the last 5 years. The availability of the draft genome sequences and re-sequencing of elite genotypes for several important legume crops have made it possible to identify structural variations at large scale. Availability of large-scale genomic resources and low-cost and high-throughput genotyping technologies are enhancing the efficiency and resolution of genetic mapping and marker-trait association studies. Most importantly, deployment of molecular breeding approaches has resulted in development of improved lines in some legume crops such as chickpea and groundnut. In order to support genomics-driven crop improvement at a fast pace, the deployment of breeder-friendly genomics and decision support tools seems appear to be critical in breeding programs in developing countries. This review provides an overview of emerging genomics and informatics tools/approaches that will be the key driving force for accelerating genomics-assisted breeding and ultimately ensuring nutritional and food security in developing countries.