Genetic dissection of grain iron and zinc concentrations in lentil (Lens culinaris Medik.)

Delineation of novel genomic loci and putative candidate genes associated with seed iron and zinc content in lentil (Lens culinaris Medik.)

The use of molecular breeding approaches for development of lentil genotypes biofortified with essential micro-nutrients such as iron and zinc, could serve as a promising solution to address the problem of global malnutrition. Thus, genome-wide association study (GWAS) strategy was adopted in this study to identify the genomic regions associated with seed iron and zinc content in lentil. A panel of 95 diverse lentil genotypes, grown across three different geographical locations and evaluated for seed iron and zinc content, exhibited a wide range of variation. Genotyping-by-sequencing (GBS) analysis of the panel identified 33,745 significant single nucleotide polymorphisms (SNPs) that were distributed across all the 7 lentil chromosomes. Association mapping revealed 23 SNPs associated with seed iron content that were distributed across all the chromosomes except chromosome 3. Similarly, 14 SNPs associated with seed zinc content were also identified that were distributed across chromosomes 1, 2, 4, 5 and 6. Further, 80 genes were identified in the proximity of iron associated markers and 36 genes were identified in the proximity of zinc associated markers. Functional annotation of these genes revealed their putative involvement in iron and zinc metabolism. For seed iron content, two highly significant SNPs were found to be located within two putative candidate genes namely iron-sulfur cluster assembly (ISCA) and flavin binding monooxygenase (FMO) respectively. For zinc content, a highly significant SNP was detected in a gene encoding UPF0678 fatty acid-binding protein. Expression analysis of these genes and their putative interacting partners suggests their involvement in iron and zinc metabolism in lentil. Overall, in this study we have identified markers, putative candidate genes and predicted putative interacting protein partners significantly associated with iron and zinc metabolism that could be utilized in future breeding studies of lentil for nutrient biofortification.

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.

Strategies for identifying stable lentil cultivars (Lens culinaris Medik) for combating hidden hunger, malnourishment, and climate variability

Iron and zinc malnutrition is a global humanitarian concern that mostly affects newborns, children, and women in low- and middle-income countries where plant-based diets are regularly consumed. This kind of malnutrition has the potential to result in a number of immediate and long-term implications, including stunted growth, an elevated risk of infectious diseases, and poor development, all of which may ultimately cause children to not develop to the fullest extent possible. A determination of the contributions from genotype, environment, and genotype by environment interactions is necessary for the production of nutrient-dense lentil varieties that offer greater availability of iron and zinc with a high level of trait stability. Understanding the genotype and environmental parameters that affect G x E (Genotype x Environment) interactions is essential for plant breeding. We used GGE(Genotype, Genotype x Environment interactions) and AMMI (Additive Main effects and Multiplicative Interaction) models to study genetic stability and GE(Genotype x Environment interactions) for grain Fe, Zn, Al, and anti-nutritional factors like phytic acid content in sixteen commercially produced lentil cultivars over several different six geographical locations across India. Significant genetic variability was evident in the Fe and Zn levels of different genotypes of lentils. The amounts of grain iron, zinc, and phytic acid varied from 114.10 to 49.90 mg/kg, 74.62 to 21.90 mg/kg, and 0.76 to 2.84 g/100g (dw) respectively. The environment and GE (Genotype x Environment interactions) had an impact on the concentration of grain Fe, Zn, and phytic acid (PA). Heritability estimations ranged from low to high (53.18% to 99.48%). The study indicated strong correlation between the contents of Fe and Zn, a strategy for simultaneously increasing Fe and Zn in lentils may be recommended. In addition, our research revealed that the stable and ideal lentil varieties L4076 (Pusa Shivalik) for Fe concentration and L4717 (Pusa Ageti) for Zn content, which have lower phytic acid contents, will not only play an essential role as stable donors in the lentil bio-fortification but will also enable the expansion of the growing area of bio-fortified crops for the security of health and nutrition.

The Prospects of gene introgression from crop wild relatives into cultivated lentil for climate change mitigation

Crop wild relatives (CWRs), landraces and exotic germplasm are important sources of genetic variability, alien alleles, and useful crop traits that can help mitigate a plethora of abiotic and biotic stresses and crop yield reduction arising due to global climatic changes. In the pulse crop genus Lens, the cultivated varieties have a narrow genetic base due to recurrent selections, genetic bottleneck and linkage drag. The collection and characterization of wild Lens germplasm resources have offered new avenues for the genetic improvement and development of stress-tolerant, climate-resilient lentil varieties with sustainable yield gains to meet future food and nutritional requirements. Most of the lentil breeding traits such as high-yield, adaptation to abiotic stresses and resistance to diseases are quantitative and require the identification of quantitative trait loci (QTLs) for marker assisted selection and breeding. Advances in genetic diversity studies, genome mapping and advanced high-throughput sequencing technologies have helped identify many stress-responsive adaptive genes, quantitative trait loci (QTLs) and other useful crop traits in the CWRs. The recent integration of genomics technologies with plant breeding has resulted in the generation of dense genomic linkage maps, massive global genotyping, large transcriptomic datasets, single nucleotide polymorphisms (SNPs), expressed sequence tags (ESTs) that have advanced lentil genomic research substantially and allowed for the identification of QTLs for marker-assisted selection (MAS) and breeding. Assembly of lentil and its wild species genomes (~4Gbp) opens up newer possibilities for understanding genomic architecture and evolution of this important legume crop. This review highlights the recent strides in the characterization of wild genetic resources for useful alleles, development of high-density genetic maps, high-resolution QTL mapping, genome-wide studies, MAS, genomic selections, new databases and genome assemblies in traditionally bred genus Lens for future crop improvement amidst the impending global climate change.

M. S, Aski MS, Mishra GP, Sinha SK, Vijay D, C. T. MP, Das S, Pawar PAM, Mishra DC, Singh AK, Kumar A, Tripathi K, Kumar RR, Gupta S, Kumar S, Dikshit HK. Morpho-biochemical characterization of a RIL population for seed parameters and identification of candidate genes regulating seed size trait in lentil (Lens culinaris Medik.)

The seed size and shape in lentil (Lens culinaris Medik.) are important quality traits as these influences the milled grain yield, cooking time, and market class of the grains. Linkage analysis was done for seed size in a RIL (F_5:6) population derived by crossing L830 (20.9 g/1000 seeds) with L4602 (42.13 g/1000 seeds) which consisted of 188 lines (15.0 to 40.5 g/1000 seeds). Parental polymorphism survey using 394 SSRs identified 31 polymorphic primers, which were used for the bulked segregant analysis (BSA). Marker PBALC449 differentiated the parents and small seed size bulk only, whereas large seeded bulk or the individual plants constituting the large-seeded bulk could not be differentiated. Single plant analysis identified only six recombinant and 13 heterozygotes, of 93 small-seeded RILs (<24.0 g/1000 seed). This clearly showed that the small seed size trait is very strongly regulated by the locus near PBLAC449; whereas, large seed size trait seems governed by more than one locus. The PCR amplified products from the PBLAC449 marker (149bp from L4602 and 131bp from L830) were cloned, sequenced and BLAST searched using the lentil reference genome and was found amplified from chromosome 03. Afterward, the nearby region on chromosome 3 was searched, and a few candidate genes like ubiquitin carboxyl-terminal hydrolase, E3 ubiquitin ligase, TIFY-like protein, and hexosyltransferase having a role in seed size determination were identified. Validation study in another RIL mapping population which is differing for seed size, showed a number of SNPs and InDels among these genes when studied using whole genome resequencing (WGRS) approach. Biochemical parameters like cellulose, lignin, and xylose content showed no significant differences between parents and the extreme RILs, at maturity. Various seed morphological traits like area, length, width, compactness, volume, perimeter, etc., when measured using VideometerLab 4.0 showed significant differences for the parents and RILs. The results have ultimately helped in better understanding the region regulating the seed size trait in genomically less explored crops like lentils.

Biofortification to avoid malnutrition in humans in a changing climate: Enhancing micronutrient bioavailability in seed, tuber, and storage roots

Malnutrition results in enormous socio-economic costs to the individual, their community, and the nation's economy. The evidence suggests an overall negative impact of climate change on the agricultural productivity and nutritional quality of food crops. Producing more food with better nutritional quality, which is feasible, should be prioritized in crop improvement programs. Biofortification refers to developing micronutrient -dense cultivars through crossbreeding or genetic engineering. This review provides updates on nutrient acquisition, transport, and storage in plant organs; the cross-talk between macro- and micronutrients transport and signaling; nutrient profiling and spatial and temporal distribution; the putative and functionally characterized genes/single-nucleotide polymorphisms associated with Fe, Zn, and β-carotene; and global efforts to breed nutrient-dense crops and map adoption of such crops globally. This article also includes an overview on the bioavailability, bioaccessibility, and bioactivity of nutrients as well as the molecular basis of nutrient transport and absorption in human. Over 400 minerals (Fe, Zn) and provitamin A-rich cultivars have been released in the Global South. Approximately 4.6 million households currently cultivate Zn-rich rice and wheat, while ~3 million households in sub-Saharan Africa and Latin America benefit from Fe-rich beans, and 2.6 million people in sub-Saharan Africa and Brazil eat provitamin A-rich cassava. Furthermore, nutrient profiles can be improved through genetic engineering in an agronomically acceptable genetic background. The development of "Golden Rice" and provitamin A-rich dessert bananas and subsequent transfer of this trait into locally adapted cultivars are evident, with no significant change in nutritional profile, except for the trait incorporated. A greater understanding of nutrient transport and absorption may lead to the development of diet therapy for the betterment of human health.

Integrated breeding approaches to enhance the nutritional quality of food legumes

Global food security, both in terms of quantity and quality remains as a challenge with the increasing population. In parallel, micronutrient deficiency in the human diet leads to malnutrition and several health-related problems collectively known as "hidden hunger" more prominent in developing countries around the globe. Biofortification is a potential tool to fortify grain legumes with micronutrients to mitigate the food and nutritional security of the ever-increasing population. Anti-nutritional factors like phytates, raffinose (RFO's), oxalates, tannin, etc. have adverse effects on human health upon consumption. Reduction of the anti-nutritional factors or preventing their accumulation offers opportunity for enhancing the intake of legumes in diet besides increasing the bioavailability of micronutrients. Integrated breeding methods are routinely being used to exploit the available genetic variability for micronutrients through modern "omic" technologies such as genomics, transcriptomics, ionomics, and metabolomics for developing biofortified grain legumes. Molecular mechanism of Fe/Zn uptake, phytate, and raffinose family oligosaccharides (RFOs) biosynthesis pathways have been elucidated. Transgenic, microRNAs and genome editing tools hold great promise for designing nutrient-dense and anti-nutrient-free grain legumes. In this review, we present the recent efforts toward manipulation of genes/QTLs regulating biofortification and Anti-nutrient accumulation in legumes using genetics-, genomics-, microRNA-, and genome editing-based approaches. We also discuss the success stories in legumes enrichment and recent advances in development of low Anti-nutrient lines. We hope that these emerging tools and techniques will expedite the efforts to develop micronutrient dense legume crop varieties devoid of Anti-nutritional factors that will serve to address the challenges like malnutrition and hidden hunger.

Morphological, Molecular, and Biochemical Characterization of a Unique Lentil (Lens culinaris Medik.) Genotype Showing Seed-Coat Color Anomalies Due to Altered Anthocyanin Pathway

This study reports the identification of a unique lentil (Lens culinaris Medik.) genotype L4717-NM, a natural mutant (NM) derived from a variety L4717, producing brown, black, and spotted seed-coat colored seeds in a single plant, generation after generation, in different frequencies. The genetic similarity of L4717 with that of L4717-NM expressing anomalous seed-coat color was established using 54 SSR markers. In addition, various biochemical parameters such as TPC (total phenolic content), TFC (total flavonoid content), DPPH (2,2-diphenyl-1-picrylhydrazyl), FRAP (ferric reducing antioxidant power), H2O2 (peroxide quantification), TCC (total carotenoids content), TAC (total anthocyanin content), and TAA (total ascorbic acid) were also studied in the seeds, sprouts, and seedlings of L4717, brown, black, and spotted seed-coat colored seeds. Stage-specific variations for the key biochemical parameters were recorded, and seedling stage was found the best for many parameters. Moreover, seeds with black seed coat showed better nutraceutical values for most of the studied traits. A highly significant (p ≤ 0.01) and positive correlation was observed between DPPH and TPC, TAA, TFC, etc., whereas, protein content showed a negative correlation with the other studied parameters. The seed coat is maternal tissue and we expect expression of seed-coat color as per the maternal genotype. However, such an anomalous seed-coat expression, which seems to probably be governed by some transposable element in the identified genotype, warrants more detailed studies involving exploitation of the anthocyanin pathway.

Genotypic variation in root architectural traits under contrasting phosphorus levels in Mediterranean and Indian origin lentil genotypes

The development of phosphorus-efficient crop cultivars boosts productivity while lowering eutrophication in the environment. It is feasible to improve the efficiency of phosphorus (P) absorption in lentils by enhancing phosphorus absorption through root architectural traits. The root architectural traits of 110 diverse lentil genotypes of Indian and Mediterranean origin were assessed, and the relationships between traits were investigated. In a hydroponics experiment, the lentil lines were examined at the seedling stage under two conditions: adequate P supply and deficient P supply. The Pearson correlation coefficients between root architectural traits and genetic diversity among lentil lines were assessed. To estimate variance components, a model (fixed factor) was used. In this experiment, both phosphorus (P) and genotype were fixed variables. Our lentil lines showed significant genetic variability and considerable genetic diversity for all traits under both treatments. The TRL (total root length) and PRL (primary root length) showed strong positive associations with all other characteristics excluding root average diameter (RAD) in both P treatments. In both P treatments, the RAD revealed a negative significant association with Total Root Tips (TRT), as well as total root volume (TRV) and total root forks (TRF) in the deficit conditions of P. Total root volume (TRV), total surface area (TSA), and total root tips had higher coefficient variance values. The first two principal components represented 67.88% and 66.19% of the overall variance in the adequate and deficit P treatments respectively. The Shannon-Weaver diversity index (H') revealed that RAD, PRL, and TSA had more variability than TRT and TRF under both treatments. According to the Comprehensive Phosphorus Efficiency Measure (CPEM), the best five highly efficient genotypes are PLL 18-09, PLS 18-01, PLL 18-25, PLS 18-23, and PLL 18-07, while IG112131, P560206, IG334, L11-231, and PLS18-67 are highly inefficient genotypes. The above contrasting diverse lentil genotypes can be utilized to produce P-efficient lentil cultivars. The lentil germplasm with potentially favorable root traits can be suggested to evaluated for other abiotic stress to use them in crop improvement programme. The scientific breakthroughs in root trait phenotyping have improved the chances of establishing trait-allele relationships. As a result, genotype-to-phenotype connections can be predicted and verified with exceptional accuracy, making it easier to find and incorporate favourable nutrition-related genes/QTLs in to breeding programme.

Association Mapping for Yield Attributing Traits and Yellow Mosaic Disease Resistance in Mung Bean [Vigna radiata (L.) Wilczek]

Mung bean [Vigna radiata (L.) Wilczek] is an important short-duration grain legume widely known for its nutritional, soil ameliorative, and cropping system intensification properties. This study aims at evaluating genetic diversity among mung bean genotypes and detecting genomic regions associated with various yield attributing traits and yellow mosaic disease (YMD) resistance by association mapping. A panel of 80 cultivars and advanced breeding lines was evaluated for 10 yield-related and YMD resistance traits during kharif (monsoon) and summer seasons of 2018-2019 and 2019-2020. A total of 164 genome-wide simple sequence repeat (SSR) markers were initially screened, out of which 89 were found polymorphic which generated 317 polymorphic alleles with an average of 3.56 alleles per SSR locus. The number of alleles at each locus varied from 2 to 7. The population genetic structure analysis grouped different genotypes in three major clusters and three genetically distinct subpopulations (SPs) (i.e., SP-1, SP-2, and SP-3) with one admixture subpopulation (SP-4). Both cluster and population genetic structure analysis categorized the advanced mung bean genotypes in a single group/SP and the released varieties in other groups/SPs, suggesting that the studied genotypes may have common ancestral history at some level. The population genetic structure was also in agreement with the genetic diversity analysis. The estimate of the average degree of linkage disequilibrium (LD) present at the genome level in 80 mung bean genotypes unveiled significant LD blocks. Over the four seasons, 10 marker-trait associations were observed significant for YMD and four seed yield (SY)-related traits viz., days to flowering, days to maturity, plant height, and number of pods per plant using the mixed linear model (MLM) method. These associations may be useful for marker-assisted mung bean yield improvement programs and YMD resistance.

Omics Path to Increasing Productivity in Less-Studied Crops Under Changing Climate-Lentil a Case Study

Conventional breeding techniques for crop improvement have reached their full potential, and hence, alternative routes are required to ensure a sustained genetic gain in lentils. Although high-throughput omics technologies have been effectively employed in major crops, less-studied crops such as lentils have primarily relied on conventional breeding. Application of genomics and transcriptomics in lentils has resulted in linkage maps and identification of QTLs and candidate genes related to agronomically relevant traits and biotic and abiotic stress tolerance. Next-generation sequencing (NGS) complemented with high-throughput phenotyping (HTP) technologies is shown to provide new opportunities to identify genomic regions and marker-trait associations to increase lentil breeding efficiency. Recent introduction of image-based phenotyping has facilitated to discern lentil responses undergoing biotic and abiotic stresses. In lentil, proteomics has been performed using conventional methods such as 2-D gel electrophoresis, leading to the identification of seed-specific proteome. Metabolomic studies have led to identifying key metabolites that help differentiate genotypic responses to drought and salinity stresses. Independent analysis of differentially expressed genes from publicly available transcriptomic studies in lentils identified 329 common transcripts between heat and biotic stresses. Similarly, 19 metabolites were common across legumes, while 31 were common in genotypes exposed to drought and salinity stress. These common but differentially expressed genes/proteins/metabolites provide the starting point for developing high-yielding multi-stress-tolerant lentils. Finally, the review summarizes the current findings from omic studies in lentils and provides directions for integrating these findings into a systems approach to increase lentil productivity and enhance resilience to biotic and abiotic stresses under changing climate.

Identification of anthracnose race 1 resistance loci in lentil by integrating linkage mapping and genome-wide association study

Anthracnose, caused byColletotrichum lentis, is a devastating disease of lentil (Lens culinaris Medik.) in western Canada. Growing resistant lentil cultivars is the most cost-effective and environmentally friendly approach to prevent seed yield losses that can exceed 70%. To identify loci conferring resistance to anthracnose race 1 in lentil, biparental quantitative trait loci (QTL) mapping of two recombinant inbred line (RIL) populations was integrated with a genome-wide association study (GWAS) using 200 diverse lentil accessions from a lentil diversity panel. A major-effect QTL (qAnt1.Lc-3) conferring resistance to race 1 was mapped to lentil chromosome 3 and colocated on the lentil physical map for both RIL populations. Clusters of candidate nucleotide-binding leucine-rich repeat (NB-LRR) and other defense-related genes were uncovered within the QTL region. A GWAS detected 14 significant single nucleotide polymorphism (SNP) markers associated with race 1 resistance on chromosomes 3, 4, 5, and 6. The most significant GWAS SNPs on chromosome 3 supported qAnt1.Lc-3 and delineated a region of 1.6 Mb containing candidate resistance genes. The identified SNP markers can be directly applied in marker-assisted selection (MAS) to accelerate the introgression of race 1 resistance in lentil breeding.