Development of sequence-based markers for seed protein content in pigeonpea

Underutilized legumes: nutrient status and advanced breeding approaches for qualitative and quantitative enhancement

Underutilized/orphan legumes provide food and nutritional security to resource-poor rural populations during periods of drought and extreme hunger, thus, saving millions of lives. The Leguminaceae, which is the third largest flowering plant family, has approximately 650 genera and 20,000 species and are distributed globally. There are various protein-rich accessible and edible legumes, such as soybean, cowpea, and others; nevertheless, their consumption rate is far higher than production, owing to ever-increasing demand. The growing global urge to switch from an animal-based protein diet to a vegetarian-based protein diet has also accelerated their demand. In this context, underutilized legumes offer significant potential for food security, nutritional requirements, and agricultural development. Many of the known legumes like Mucuna spp., Canavalia spp., Sesbania spp., Phaseolus spp., and others are reported to contain comparable amounts of protein, essential amino acids, polyunsaturated fatty acids (PUFAs), dietary fiber, essential minerals and vitamins along with other bioactive compounds. Keeping this in mind, the current review focuses on the potential of discovering underutilized legumes as a source of food, feed and pharmaceutically valuable chemicals, in order to provide baseline data for addressing malnutrition-related problems and sustaining pulse needs across the globe. There is a scarcity of information about underutilized legumes and is restricted to specific geographical zones with local or traditional significance. Around 700 genera and 20,000 species remain for domestication, improvement, and mainstreaming. Significant efforts in research, breeding, and development are required to transform existing local landraces of carefully selected, promising crops into types with broad adaptability and economic viability. Different breeding efforts and the use of biotechnological methods such as micro-propagation, molecular markers research and genetic transformation for the development of underutilized crops are offered to popularize lesser-known legume crops and help farmers diversify their agricultural systems and boost their profitability.

Grain Nutrients Variability in Pigeonpea Genebank Collection and Its Potential for Promoting Nutritional Security in Dryland Ecologies

Pigeonpea, a climate-resilient legume, is nutritionally rich and of great value in Asia, Africa, and Caribbean regions to alleviate malnutrition. Assessing the grain nutrient variability in genebank collections can identify potential sources for biofortification. This study aimed to assess the genetic variability for grain nutrients in a set of 600 pigeonpea germplasms conserved at the RS Paroda Genebank, ICRISAT, India. The field trials conducted during the 2019 and 2020 rainy seasons in augmented design with four checks revealed significant differences among genotypes for all the agronomic traits and grain nutrients studied. The germplasm had a wider variation for agronomic traits like days to 50% flowering (67-166 days), days to maturity (112-213 days), 100-seed weight (1.69-22.17 g), and grain yield per plant (16.54-57.93 g). A good variability was observed for grain nutrients, namely, protein (23.35-29.50%), P (0.36-0.50%), K (1.43-1.63%), Ca (1,042.36-2,099.76 mg/kg), Mg (1,311.01-1,865.65 mg/kg), Fe (29.23-40.98 mg/kg), Zn (24.14-35.68 mg/kg), Mn (8.56-14.01 mg/kg), and Cu (7.72-14.20 mg/kg). The germplasm from the Asian region varied widely for grain nutrients, and the ones from African region had high nutrient density. The significant genotype × environment interaction for most of the grain nutrients (except for P, K, and Ca) indicated the sensitivity of nutrient accumulation to the environment. Days to 50% flowering and days to maturity had significant negative correlation with most of the grain nutrients, while grain yield per plant had significant positive correlation with protein and magnesium, which can benefit simultaneous improvement of agronomic traits with grain nutrients. Clustering of germplasms based on Ward.D2 clustering algorithm revealed the co-clustering of germplasm from different regions. The identified top 10 nutrient-specific and 15 multi-nutrient dense landraces can serve as promising sources for the development of biofortified lines in a superior agronomic background with a broad genetic base to fit the drylands. Furthermore, the large phenotypic data generated in this study can serve as a raw material for conducting SNP/haplotype-based GWAS to identify genetic variants that can accelerate genetic gains in grain nutrient improvement.

QTL-seq for the identification of candidate genes for days to flowering and leaf shape in pigeonpea

To identify genomic segments associated with days to flowering (DF) and leaf shape in pigeonpea, QTL-seq approach has been used in the present study. Genome-wide SNP profiling of extreme phenotypic bulks was conducted for both the traits from the segregating population (F₂) derived from the cross combination- ICP 5529 × ICP 11605. A total of 126.63 million paired-end (PE) whole-genome resequencing data were generated for five samples, including one parent ICP 5529 (obcordate leaf and late-flowering plant), early and late flowering pools (EF and LF) and obcordate and lanceolate leaf shape pools (OLF and LLS). The QTL-seq identified two significant genomic regions, one on CcLG03 (1.58 Mb region spanned from 19.22 to 20.80 Mb interval) for days to flowering (LF and EF pools) and another on CcLG08 (2.19 Mb region spanned from 6.69 to 8.88 Mb interval) for OLF and LLF pools, respectively. Analysis of genomic regions associated SNPs with days to flowering and leaf shape revealed 5 genic SNPs present in the unique regions. The identified genomic regions for days to flowering were also validated with the genotyping-by-sequencing based classical QTL mapping method. A comparative analysis of the identified seven genes associated with days to flowering on 12 Fabaceae genomes, showed synteny with 9 genomes. A total of 153 genes were identified through the synteny analysis ranging from 13 to 36. This study demonstrates the usefulness of QTL-seq approach in precise identification of candidate gene(s) for days to flowering and leaf shape which can be deployed for pigeonpea improvement.

QTL-seq approach was utilized for mapping of genomic regions/genes associated with days to flowering and leaf shape in pigeonpea. Analysis of genomic regions and associated SNPs with days to flowering and leaf shape revealed 1 and 4 non-synonymous SNPs, respectively. The study demonstrated sequencing-based trait mapping approach can accelerate trait mapping of the targeted traits.

Systems biology for crop improvement

In recent years, generation of large-scale data from genome, transcriptome, proteome, metabolome, epigenome, and others, has become routine in several plant species. Most of these datasets in different crop species, however, were studied independently and as a result, full insight could not be gained on the molecular basis of complex traits and biological networks. A systems biology approach involving integration of multiple omics data, modeling, and prediction of the cellular functions is required to understand the flow of biological information that underlies complex traits. In this context, systems biology with multiomics data integration is crucial and allows a holistic understanding of the dynamic system with the different levels of biological organization interacting with external environment for a phenotypic expression. Here, we present recent progress made in the area of various omics studies-integrative and systems biology approaches with a special focus on application to crop improvement. We have also discussed the challenges and opportunities in multiomics data integration, modeling, and understanding of the biology of complex traits underpinning yield and stress tolerance in major cereals and legumes.

A diagnostic marker kit for Fusarium wilt and sterility mosaic diseases resistance in pigeonpea

Fusarium wilt (FW) and sterility mosaic diseases (SMD) are key biotic constraints to pigeonpea production. Occurrence of these two diseases in congenial conditions is reported to cause complete yield loss in susceptible pigeonpea cultivars. Various studies to elucidate genomic architecture of the two traits have revealed significant marker-trait associations for use in breeding programs. However, these DNA markers could not be used effectively in genomics-assisted breeding for developing FW and SMD resistant varieties primarily due to pathogen variability, location or background specificity, lesser phenotypic variance explained by the reported QTL and cost-inefficiency of the genotyping assays. Therefore, in the present study, a novel approach has been used to develop a diagnostic kit for identification of suitable FW and SMD resistant lines. This kit was developed with 10 markers each for FW and SMD resistance. Investigation of the diversity of these loci has shown the role of different alleles in different resistant genotypes. Two genes (C.cajan_03691 and C.cajan_18888) for FW resistance and four genes (C.cajan_07858, C.cajan_20995, C.cajan_21801 and C.cajan_17341) for SMD resistance have been identified. More importantly, we developed a customized and cost-effective Kompetitive allele-specific PCR genotyping assay for the identified genes in order to encourage their downstream applications in pigeonpea breeding programs. The diagnostic marker kit developed here will offer great strength to pigeonpea varietal development program, since the resistance against these two diseases is essentially required for nominating an improved line in varietal release pipeline.

Mapping QTL for important seed traits in an interspecific F2 population of pigeonpea

Seed traits present important breeding targets for enhancing grain yield and quality in various grain legume crops including pigeonpea. The present study reports significant genetic variation for six seed traits including seed length (SL), seed width (SW), seed thickness (ST), seed weight (SWT), electrical conductivity (EC) and water uptake (WU) among Cajanus cajan (L.) Millspaugh acc. ICPL 20340 and Cajanus scarabaeoides (L.) Thouars acc. ICP 15739 and an F2 population derived from this interspecific cross. Maximum phenotypic values recorded for the F2 population were higher than observed in the parent ICPL 20340 [F2 max vs ICPL 20340: SW (7.05 vs 5.38), ST (4.63 vs 4.51), EC (65.17 vs 9.72), WU (213.17 vs 109.5)], which suggested contribution of positive alleles from the wild parent, ICP 15739. Concurrently, to identify the QTL controlling these seed traits, we assayed two parents and 94 F2 individuals with 113 polymorphic simple sequence repeat (SSR) markers. In the F2 population, 98 of the 113 SSRs showed Mendelian segregation ratio 1:2:1, whereas significant deviations were observed for 15 SSRs with their χ ² values ranging between 6.26 and 20.62. A partial genetic linkage map comprising 83 SSR loci was constructed. QTL analysis identified 15 marker-trait associations (MTAs) for seed traits on four linkage groups i.e. LG01, LG02, LG04 and LG05. Phenotypic variations (PVs) explained by these QTL ranged from 4.4 (WU) to 19.91% (EC). These genomic regions contributing significantly towards observed variability of seed traits would serve as potential candidates for future research that aims to improve seed traits in pigeonpea.

Genomics-assisted breeding for pigeonpea improvement

The review outlines advances in pigeonpea genomics, breeding and seed delivery systems to achieve yield gains at farmers' field. Pigeonpea is a nutritious and stress-tolerant grain legume crop of tropical and subtropical regions. Decades of breeding efforts in pigeonpea have resulted in development of a number of high-yielding cultivars. Of late, the development of CMS-based hybrid technology has allowed the exploitation of heterosis for yield enhancement in this crop. Despite these positive developments, the actual on-farm yield of pigeonpea is still well below its potential productivity. Growing needs for high and sustainable pigeonpea yields motivate scientists to improve the breeding efficiency to deliver a steady stream of cultivars that will provide yield benefits under both ideal and stressed environments. To achieve this objective in the shortest possible time, it is imperative that various crop breeding activities are integrated with appropriate new genomics technologies. In this context, the last decade has seen a remarkable rise in the generation of important genomic resources such as genome-wide markers, high-throughput genotyping assays, saturated genome maps, marker/gene-trait associations, whole-genome sequence and germplasm resequencing data. In some cases, marker/gene-trait associations are being employed in pigeonpea breeding programs to improve the valuable yield and market-preferred traits. Embracing new breeding tools like genomic selection and speed breeding is likely to improve genetic gains. Breeding high-yielding pigeonpea cultivars with key adaptation traits also calls for a renewed focus on systematic selection and utilization of targeted genetic resources. Of equal importance is to overcome the difficulties being faced by seed industry to take the new cultivars to the doorstep of farmers.

Genotyping-by-sequencing and multilocation evaluation of two interspecific backcross populations identify QTLs for yield-related traits in pigeonpea

This study has identified single-nucleotide polymorphism (SNP) markers associated with nine yield-related traits in pigeonpea by using two backcross populations (BP) developed through interspecific crosses and evaluating them at two locations and 3 years. In both the populations, markers have shown strong segregation distortion; therefore, a quantitative trait locus (QTL) mapping mixed model was used. A total of 86 QTLs explaining 12-21% phenotypic variation were detected in BP-1. On the other hand, 107 QTLs explaining 11-29% phenotypic variation were detected in BP-2. Although most QTLs were environment and trait specific, few stable and consistent QTLs were also detected. Interestingly, 11 QTLs in BP-2 were associated with more than one trait. Among these QTLs, eight QTLs associated with days to 50% flowering and days to 75% maturity were located on CcLG07. One SNP "S7_14185076" marker in BP-2 population has been found associated with four traits, namely days to 50% flowering, days to 75% maturity, primary branches per plant and secondary branches per plant with positive additive effect. Hence, the present study has not only identified QTLs for yield-related traits, but also discovered novel alleles from wild species, which can be used for improvement of traits through genomics-assisted breeding.

Seed protein content and its relationships with agronomic traits in pigeonpea is controlled by both main and epistatic effects QTLs

The genetic architecture of seed protein content (SPC) and its relationships to agronomic traits in pigeonpea is poorly understood. Accordingly, five F₂ populations segregating for SPC and four agronomic traits (seed weight (SW), seed yield (SY), growth habit (GH) and days to first flowering (DFF)) were phenotyped and genotyped using genotyping-by-sequencing approach. Five high-density population-specific genetic maps were constructed with an average inter-marker distance of 1.6 to 3.5 cM, and subsequently, integrated into a consensus map with average marker spacing of 1.6 cM. Based on analysis of phenotyping data and genotyping data, 192 main effect QTLs (M-QTLs) with phenotypic variation explained (PVE) of 0.7 to 91.3% were detected for the five traits across the five populations. Major effect (PVE ≥ 10%) M-QTLs included 14 M-QTLs for SPC, 16 M-QTLs for SW, 17 M-QTLs for SY, 19 M-QTLs for GH and 24 M-QTLs for DFF. Also, 573 epistatic QTLs (E-QTLs) were detected with PVE ranging from 6.3 to 99.4% across traits and populations. Colocalization of M-QTLs and E-QTLs explained the genetic basis of the significant (P < 0.05) correlations of SPC with SW, SY, DFF and GH. The nature of genetic architecture of SPC and its relationship with agronomic traits suggest that genomics-assisted breeding targeting genome-wide variations would be effective for the simultaneous improvement of SPC and other important traits.

An "Axiom Cajanus SNP Array" based high density genetic map and QTL mapping for high-selfing flower and seed quality traits in pigeonpea

BACKGROUND

Pigeonpea has considerable extent of insect-aided natural out-crossing that impedes genetic purity of seeds. Pre-anthesis cleistogamy in pigeonpea promotes self-pollination which helps in maintaining genetic purity. The cleistogamous flowers are linked with shriveled seeds, an undesirable trait from variety adoption point of view, and breeding using genomics tools can help in overcoming this constraint. Therefore, in order to identify genomic regions governing these target traits, one recombinant inbred line (RIL) population was developed using contrasting parents (ICPL 99010 and ICP 5529) for flower shape and shriveled seeds. The RILs were phenotyped for two years and genotyped using the Axiom Cajanus SNP Array.

RESULTS

Out of the 56,512 unique sequence variations on the array, the mapping population showed 8634 single nucleotide polymorphism (SNPs) segregating across the genome. These data facilitated generation of a high density genetic map covering 6818 SNPs in 974 cM with an average inter-marker distance of 0.1 cM, which is the lowest amongst all pigeonpea genetic maps reported. Quantitative trait loci (QTL) analysis using this genetic map and phenotyping data identified 5 QTLs associated with cleistogamous flower, 3 QTLs for shriveled seed and 1 QTL for seed size. The phenotypic variance explained by these QTLs ranged from 9.1 to 50.6%. A consistent QTL "qCl3.2" was identified for cleistogamous flower on CcLG03 covering a span of 42 kb in the pigeonpea genome. Epistatic QTLs were also identified for cleistogamous flower and shriveled seed traits.

CONCLUSION

Identified QTLs and genomic interactions for cleistogamous flower, shriveled seed and seed size will help in incorporating the required floral architecture in pigeonpea varieties/lines. Besides, it will also be useful in understanding the molecular mechanisms, and map-based gene cloning for the target traits.