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Assessing genetic diversity and identifying trait-specific germplasm within germplasm collections is necessary for a varietal development programme. Agronomic features were investigated in 318 diverse dry bean germplasm accessions, including check varieties. We observed a lot of genetic variability for the traits studied. A wide range of variations was noticed for days to 50% flowering, days to maturity, pod length, the number of seeds per pod and 100-seed weight (HSW). For eight of the agronomic features evaluated, the analysis of variance revealed substantial differences among the accessions. For all characters, phenotypic coefficient of variation estimations were more significant than genotypic coefficient of variation. Plant height, days to 50% flowering, seed yield (q/ha) and HSW had high heritability and genetic advance as a per cent of the mean. Association analysis revealed a significant positive relationship between HSW, plant height, pod length and seed yield (q/ha). According to a hierarchical clustering analysis based on agronomic features, the diversity of dry bean germplasm has no significant association with their geographical origin. The number of pods per plant, plant height, days to maturity, days to 50% flowering and seed yield had relatively long vectors based on principal components 1 and 2, indicating that genotypes differ significantly. Additionally, the trait-specific donors and bean common mosaic virus disease-resistant accessions, IC360831, ET4515, EC150250, IC340947, IC564797B, EC565693 and ET8409 could be of value for dry bean improvement.

Madhya Pradesh ranks first both in terms of area (25%) and production (32%) of pulses in India. However, it ranks sixth after Uttar Pradesh, Bihar, Haryana, West Bengal and Gujarat in terms of productivity. To realize better yield; recommended production and protection technologies have to be followed. Most of the pigeonpea varieties have been developed by traditional breeding either by pedigree method or selection from landraces or by bi-parental mating. After getting stable male sterile and restorer lines, development of hybrid pigeonpea have been major breeding objectives. Availably of genomic tools by decoding the genome sequence, pigeonpea have been equipped with modern genetic and genomic tools for use in the research programmes. Different approached like mining superior alleles by re-sequencing of wild species, fine mapping for drought tolerance, fertility restoration and developing superior lines by genomic selection, identification of candidate genes which are associated with hybrid vigour by using epi-genomics and mitochondrial genome sequencing and identification of candidate genes and functional markers for water-logging tolerance are already in progress. Transgenic approach has also been initiated to develop resistance against pod borer. Collaborative efforts among ICRISAT, IARI and IIPR-Kanpur are on the way for use of different transgenes and promoter options for developing transgenic plants and their evaluations for effectiveness and bio-safety concerns.

Understanding the crop response to elevated carbon dioxide (e[CO

The genetic base of 150 pigeonpea varieties released in India during1960 to 2018 was examined. Of these, 89, 57, three, and one variety were developed by pedigree selection, pureline selection, mutation and population improvement, respectively. Examination of pedigree records of 89 pigeonpea varieties developed through pedigree breeding method between 1971 and 2018 traced back to 113 ancestors. The highest mean genetic contribution was recorded for the genotype T 190 (0.051) accompanied by UPAS 120 (0.049) and ICP 8863 (0.043). The ancestor T 190 appeared with highest frequency of 21, directly as one of the parent (male/female) in four varieties and indirectly in the development of 17 varieties. Similarly, the ancestors UPAS 120 and ICP 8863 were more frequently used (in nine varieties) as direct parents followed by T 21 and C 11 (in five varieties). The variety PRG 176 involved the highest number (9) of ancestors during the course of its development followed by the variety VBN (Rg) 3 with eight ancestors. Results indicated that 51.69% (46 of the 89 varieties) of released varieties were developed through bi-parental crossing whereas 48.31% involved multiple parents. The frequent use of a limited number of ancestors has caused the narrow genetic base of released pigeonpea varieties. We recommend large-scale deployment of novel germplasm resources for generating broad-base breeding populations. This will help to obtain improved pigeonpea cultivars with high grain yield, biotic tolerance and climate adaptation.

Pigeonpea productivity is greatly constrained by poor plant ideotype of existing Indian cultivars. Enhancing pigeonpea yield demands a renewed focus on restructuring the ideal plant type by using more efficient approaches like genomic tools. Therefore, the present study aims to identify and validate a set of QTLs/gene(s) presumably associated with various plant ideotype traits in pigeonpea. A total of 133 pigeonpea germplasms were evaluated along with four checks in the augmented design for various ideotype traits i.e. initiation of flowering (IF), days to 50% flowering (DFF), days to maturity (DM), plant height (PH), primary branches (PB), seeds per pod (SP) and pod length (PL). We observed significant genetic diversity in the germplasm lines for these traits. The genetic control of IF, DFF, DM and PH renders these traits suitable for detection of marker trait associations. By using residual maximum likelihood algorithm, we obtained appropriate variance–covariance structures for modeling heterogeneity, correlation of genetic effects and non-genetic residual effects. The estimates of genetic correlations indicated a strong association among earliness traits. The best linear unbiased prediction values were calculated for individual traits, and association analysis was performed in a panel of 95 diverse genotypes with 19 genic SSRs. Out of five QTL-flanking SSRs used here for validation, only ASSR295 could show significant association with FDR and Bonferroni corrections, and accounted for 15.4% IF, 14.2% DFF and 16.2% DM of phenotypic variance (PV). Remaining SSR markers (ASSR1486, ASSR206 and ASSR408) could not qualify false discovery rate (FDR) and Bonferroni criteria, hence declared as false positives. Additionally, we identified two highly significant SSR markers, ASSR8 and ASSR390 on LG 1 and LG 2, respectively. The SSR marker ASSR8 explained up to 22 and 11% PV for earliness traits and PB respectively, whereas ASSR390 controlled up to 17% PV for earliness traits. The validation and identification of new QTLs in pigeonpea across diverse genetic backgrounds brightens the prospects for marker-assisted selection to improve yield gains in pigeonpea.

The long-stagnated productivity of pigeonpea may be attributed to its vulnerability to several diseases of which vascular wilt caused by Fusarium udum Butler is of paramount significance. Disease management approaches that rely on chemicals are not very appropriate especially in view of rising environmental concerns and resource poor nature of marginal farmers. Therefore, deploying host plant resistance in genetic improvement schemes through molecular tagging of underlying resistance genes is central to resistance breeding. To this end, here we offer SSR markers for resistance to race 2 of Fusarium wilt (FW) in KPL 43 (resistant) through bulked segregant analysis (BSA). The analysis of disease incidence data on 271 F 2 individuals derived from Bahar (susceptible) × KPL 43 (resistant) revealed the involvement of two or more recessive genes (1:15) with duplicate dominant epistasis. Marker polymorphism survey using 270 hypervariable pigeonpea-specific SSR markers (HASSRs) yielded 115 polymorphic markers (42.6%) between the parents. SSR markers HASSR8 190 , HASSR58 180 and HASSR121 170 differentiated resistant and susceptible bulks. A joint segregation analysis between the each marker with FW resistance in F 2 population supported the linkage between FW and the SSRs. Recessive class analysis (RCA) based on genotypic data of ten resistant F 2 individual also confirmed linkage between SSRs and FW resistance gene. The independent assortments was observed between the pair of associated SSR markers, and this corroborated with the alignment of these three SSR markers on three different chromosomes in the pigeonpea genome. The association of SSR markers HASSR8 190 and HASSR58 180 with FW resistance was further validated in a panel of 89 pigeonpea genotypes through single marker analysis (SMA) and Kruskal Wallis test. Given the recessive nature of the genes conferring FW resistance, these SSR markers have tremendous implications for breeding FW resistant pigeonpea genotypes.

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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13205-020-02423-x) contains supplementary material, which is available to authorized users.

Pigeonpea productivity is greatly constrained by poor plant ideotype of existing Indian cultivars. Enhancing pigeonpea yield demands a renewed focus on restructuring the ideal plant type by using more efficient approaches like genomic tools. Therefore, the present study aims to identify and validate a set of QTLs/gene(s) presumably associated with various plant ideotype traits in pigeonpea. A total of 133 pigeonpea germplasms were evaluated along with four checks in the augmented design for various ideotype traits i.e. initiation of flowering (IF), days to 50% flowering (DFF), days to maturity (DM), plant height (PH), primary branches (PB), seeds per pod (SP) and pod length (PL). We observed significant genetic diversity in the germplasm lines for these traits. The genetic control of IF, DFF, DM and PH renders these traits suitable for detection of marker trait associations. By using residual maximum likelihood algorithm, we obtained appropriate variance–covariance structures for modeling heterogeneity, correlation of genetic effects and non-genetic residual effects. The estimates of genetic correlations indicated a strong association among earliness traits. The best linear unbiased prediction values were calculated for individual traits, and association analysis was performed in a panel of 95 diverse genotypes with 19 genic SSRs. Out of five QTL-flanking SSRs used here for validation, only ASSR295 could show significant association with FDR and Bonferroni corrections, and accounted for 15.4% IF, 14.2% DFF and 16.2% DM of phenotypic variance (PV). Remaining SSR markers (ASSR1486, ASSR206 and ASSR408) could not qualify false discovery rate (FDR) and Bonferroni criteria, hence declared as false positives. Additionally, we identified two highly significant SSR markers, ASSR8 and ASSR390 on LG 1 and LG 2, respectively. The SSR marker ASSR8 explained up to 22 and 11% PV for earliness traits and PB respectively, whereas ASSR390 controlled up to 17% PV for earliness traits. The validation and identification of new QTLs in pigeonpea across diverse genetic backgrounds brightens the prospects for marker-assisted selection to improve yield gains in pigeonpea. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12298-018-0584-6) contains supplementary material, which is available to authorized users.

Draft genome sequence in pigeonpea offers unprecedented opportunities for genomics assisted crop improvement via enabling access to genome-wide genetic markers. In the present study, 421 hypervariable simple sequence repeat (SSR) markers from the pigeonpea genome were screened on a panel of eight pigeonpea genotypes yielding marker validation and polymorphism percentages of 95.24 and 54.11%, respectively. The SSR marker assay uncovered a total of 570 alleles with three as an average number of alleles per marker. Similarly, the mean values for gene diversity and PIC were 0.44 and 0.37, respectively. The number of polymorphic markers ranged from 39 to 89 for different parental combinations. Further, 60 of these SSRs were assayed on 94 genotypes, and model based clustering using STRUCTURE resulted in the identification of the two subpopulations (K = 2). This remained in close agreement with the clustering patterns inferred from genetic distance (GD)-based approaches i.e., dendrogram, factorial and principal coordinate analysis (PCoA). The AMOVA accounted majority of the genetic variation within groups (89%) in comparison to the variation existing between the groups (11%). A subset of these markers was implicated for hybrid purity testing. We also demonstrated utility of these SSR markers in trait mapping through association and bi-parental linkage analyses. The general linear (GLM) and mixed linear (MLM) models both detected a single SSR marker (CcGM03681) with R2 = 16.4 as associated with the resistance to Fusarium wilt variant 2. Similarly, by using SSR data in a segregating backcross population, the corresponding restorer-of-fertility (Rf) locus was putatively mapped at 39 cM with the marker CcGM08896. However, The marker-trait associations (MTAs) detected here represent a very preliminary type and hence demand deeper investigations for conclusive evidence. Given their ability to reveal polymorphism in simple agarose gels, the hypervariable SSRs are valuable genomic resource for pigeonpea research community, particularly in South Asia and East Africa where pigeonpea is primarily grown.

Pigeonpea owing to its ability to sustain harsh environment and limited input/water requirement remains an excellent remunerative crop in the face of increasing climatic adversities. With nearly 70% share in global pigeonpea production, India is the leading pigeonpea producing country. Since the mid-1900s, constant research efforts directed to improve yield and resistance levels of pigeonpea have resulted in the development and deployment of several commercially accepted cultivars in India, accommodating into diverse agro-climatic zones. However, the crop productivity needs incremental improvements in order to meet the growing nutritional demands, especially in developing countries like India where pigeonpea forms a dominant part of vegetarian diet. Empowering crop improvement strategies with genomic tool kit is imperative to attain the project gains in crop yield. In the context, adoption of next-generation sequencing (NGS) technology has helped establish a wide range of genomic resources to support pigeonpea breeding, and the existing molecular tool kit includes genome-wide genetic markers, transcriptome/genome assemblies, and candidate genes/QTLs for target traits. Similarly, availability of whole mitochondrial genome sequence and derived DNA markers is immensely relevant in order to furthering the understanding of cytoplasmic male sterility (CMS) system and hybrid breeding. This chapter covers the progress of developing modern genomic resources in pigeonpea and highlights their vital role in designing future crop breeding schemes.

A total of 24 pigeonpea (Cajanus cajan L. Millspaugh) cultivars representing different maturity groups were evaluated for genetic diversity analysis using 10 pigeonpea specific and 66 cross-genera microsatellite markers. Of the cross-genera microsatellite markers, only 12 showed amplification. A total of 45 alleles were amplified by the 22 markers. Nine markers showed 100 % polymorphism. Markers Lc 14, BMd 48 and CCB 9 amplified maximum number (5) of alleles each. One genotype specific unique band in Pusa 9 was generated by markers CCB 8. Maximum genetic diversity (74 %) was observed between cultivars MA 3 and CO 6, while the minimum diversity (12 %) was observed between NDA 1 and DA 11. The average diversity among the cultivars was estimated to be 45.6 %. SSR primers from pigeonpea were found to be more polymorphic (37 %) as compared to common bean and lentil markers. The arithmetic mean heterozygosity (Hav) and marker index (MI) were found to be 0.014 and 0.03, respectively, indicating the potential of common bean and lentil microsatellite markers for genetic mapping, diversity analysis and genotyping in Cajanus.