Browsing by Author "Obala, Jimmy"

Now showing 1 - 12 of 12
  • Thumbnail Image
    Item
    Characterization and mapping of Dt1 locus which co‑segregates with CcTFL1 for growth habit in pigeonpea
    (Theor Appl Genet, 2017) Saxena, Rachit K; Obala, Jimmy; Sinjushin, Andrey; Kumar, C.V. Sameer; Saxena, K.B.; Varshney, Rajeev K.
    Pigeonpea (Cajanus cajan) is one of the most important legume crops grown in arid and semi-arid regions of the world. It is characterized with few unique features compared with other legume species, such as Lotus, Med icago, and Glycine. One of them is growth habit, an impor tant agronomic trait. In the present study, identifcation of mutations affecting growth habit accompanied by a pre cise analysis of phenotype has been done which will shed more light upon developmental regulation in pigeonpea. A genetic study was conducted to examine the inheritance of growth habit and a genotyping by sequencing (GBS)-based genetic map constructed using F2 mapping population derived from crossing parents ICP 5529 and ICP 11605. Inheritance studies clearly demonstrated the dominance of indeterminate (IDT) growth habit over determinate (DT) growth habit in F2 and F2:3 progenies. A total of 787 SNP markers were mapped in the genetic map of 1454 cM map length. Growth habit locus (Dt1) was mapped on the CcLG03 contributing more than 61% of total phenotypic variations. Subsequently, QTL analysis highlighted one gene, CcTFL1, as a candidate for determinacy in pigeon pea, since an Indel marker derived from this gene co-seg regated with the Dt1 locus. Ability of this Indel-derived marker to differentiate DT/IDT lines was also validated on 262 pigeonpea lines. This study clearly demonstrated that CcTFL1 is a candidate gene for growth habit in pigeonpea and a user-friendly marker was developed in the present study which will allow low-cost genotyping without need of automation.
  • Thumbnail Image
    Item
    Development of sequence-based markers for seed protein content in pigeonpea
    (Molecular Genetics and Genomics, 2019) Obala, Jimmy; Saxena, Rachit K.; Singh, Vikas K.; Kumar, C. V. Sameer; Saxena, K. B.; Tongoona, Pangirayi; Sibiya, Julia; Varshney, Rajeev K.
    Pigeonpea is an important source of dietary protein to over a billion people globally, but genetic enhancement of seed protein content (SPC) in the crop has received limited attention for a long time. Use of genomics-assisted breeding would facilitate accelerating genetic gain for SPC. However, neither genetic markers nor genes associated with this important trait have been identified in this crop. Therefore, the present study exploited whole genome re-sequencing (WGRS) data of four pigeonpea genotypes (~ 12X coverage) to identify sequence-based markers and associated candidate genes for SPC. By combining a common variant filtering strategy on available WGRS data with knowledge of gene functions in relation to SPC, 108 sequence variants from 57 genes were identified. These genes were assigned to 19 GO molecular function categories with 56% belonging to only two categories. Furthermore, Sanger sequencing confirmed presence of 75.4% of the variants in 37 genes. Out of 30 sequence variants converted into CAPS/dCAPS markers, 17 showed high level of polymorphism between low and high SPC genotypes. Assay of 16 of the polymorphic CAPS/dCAPS markers on an F2 population of the cross ICP 5529 (high SPC)×ICP 11605 (low SPC), resulted in four of the CAPS/dCAPS markers significantly (P<0.05) co-segregated with SPC. In summary, four markers derived from mutations in four genes will be useful for enhancing/regulating SPC in pigeonpea crop improvement programs
  • Thumbnail Image
    Item
    Effect of improved seed system on potato yields in Uganda
    (RUFORUM Working Document Series, 2018) Kigambo, M; Wasswa, P; Obala, Jimmy; Mugisha, J
    Potato seed quality is an important determinant of crop performance, final yield and quality. The quality of seed used by farmers depend on the existing seed system. In Uganda, since the formal sector has limited capacity to produce and deliver certified potato seed, the informal sector prevails providing over 93% of potato seed used by farmers. The informal sector is not regulated thus informal seed that is often used by farmers is usually of poor quality which has stagnated national yields at 7.5 t ha-1. This review looks at the general potato seed system in Uganda with an emphasis on potato seed quality while giving recommendations on how this problem can be alleviated. This is a narrative review organized under sub-topics to give the reader a comprehensive overview and easier tracking of the afore mentioned reviewed topic. In summary, this review revealed that although intervention have been used to improve quality and quantity of potato seed, a big gap still exists thus more interventions are needed both in the formal and informal sector. In addition, it revealed that if the quality of potato seed used by farmers can be improved either by making certified seed more available and affordable or improving the quality of seed obtained from the informal sector, it would be possible to increase potato yields in Uganda substantially.
  • Thumbnail Image
    Item
    Effect of potato-bean intercrop arrangement, plant spacing and fertiliser usage on plant growth and tuber yield in different environments
    (Makerere University Journal of Agricultural and Environmental Sciences, 2022) Nakibuule, J; Obala, Jimmy; Kigambo, M; Kajunju, N.H.B; Mugisha, J
    In Uganda, potato (Solanum tuberosum. L) is an important cash and food crop but its productivity has stagnated at around 3.5 t ha-1, far below potential (20 t ha-1), mainly due to soil exhaustion resulting from land shortages, and poor agronomic practices. It is vital to enhance production and efficient use of land resources by embracing elements of the systems of crop intensification. The study aimed at generating knowledge on the best combinations of crop management practices to increase productivity and improve land use. A split-split plot randomised complete block experiment was established in the districts of Kabale (high altitude), Rukiga (mid altitude), and Mbarara (descriptor of elevation) for two consecutive seasons (2018B and 2019A). The study investigated the effect of intercropping potato and beans (Phaseolus vulgaris) (in ratios of 1P:1B, 1P:2B, 2P:2B vs. sole potato, and sole bean), at two plant spacing levels (75 cm × 30 cm and 60 cm × 50 cm), and fertiliser usage (NPK and No NPK) on the growth and yield of potato. Results indicated that performance was favourable at high altitude. Intercropping potato and beans at the studied plant densities increased the quantity and quality of potato yield. Whereas the intercrop arrangements of 1P:1B and 1P:2B out yielded sole potato in tuber yield in the favourable highland areas; 1P:1B was at per with sole potato in terms of marketable yield. Intercropping potato with beans in the 1P:2B arrangement increased potato yields by 1.2 t ha-1 and also contributed highly to efficient utilisation of land resources (LER = 2.54) compared to sole potato. Addition of NPK increased potato yield, more so at the 75 cm × 30 cm spacing.
  • Thumbnail Image
    Item
    Genetic variation and relationships of total seed protein content with some agronomic traits in pigeonpea (Cajanus cajan (L.) Millsp.)
    (Australian Journal of Crop Science, 2018) Obala, Jimmy; Saxena, Rachit K.; Singh, Vikas K.; Vechalapu, Suryanarayana; Das, Roma; Rathore, Abhishek; Sameer-Kumar, Chanda V; Saxena, Kulbhushan; Tongoona, Pangirayi; Sibiya, Julia; Varshney, Rajeev K.
    Seed protein content (SPC) is an important grain quality trait, which impacts the nutritional importance of pigeonpea seed in the diet of over a billion people globally. The present study was carried out to determine variation in SPC and its relationships with some agronomic traits among 23 parental lines of different types of pigeonpea mapping populations. The parental lines were evaluated under field conditions during 2014-2015 growing season. A randomised complete block design in two replications was used. Data were recorded on SPC, days to first flower (DTF), plant height at maturity (PltH), number of pods per plant (NPP), number of seeds per pod (NSP), hundred-seed weight (SW) and seed yield per plant (SY). There were significant differences among genotypes for all traits. Broad-sense heritability was 0.693 for SPC but ranged from 0.519 (NPP) to 0.999 (DTF) while genetic advance was 2.4% for SPC but ranged from 1.2 % (NSP) to 141.2 % (SY), and genetic gain ranged from 11.0 % (SPC) to 230.0 % (SY). Simple correlation showed that SPC is only significantly but negatively correlated with SW (r = -0.30, P < 0.05), while path analyses revealed that SPC is negatively associated SW and NPP but positively with DTF, PltH, NSP and SY. It is concluded that genetic variation for SPC and agronomic traits exist among pigeonpea genotypes studied. The variation is accompanied by both favourable and unfavourable relationships of SPC with the agronomic traits.
  • Thumbnail Image
    Item
    Genomics-assisted breeding for boosting crop improvement in pigeonpea (Cajanus cajan)
    (Frontiers in plant science, 2015) Pazhamala, Lekha; Saxena, Rachit K.; Singh, Vikas K.; Sameerkumar, C. V.; Kumar, Vinay; Sinha, Pallavi; Patel, Kishan; Obala, Jimmy; Kaoneka, Seleman R.; Tongoona, P.; Shimelis, Hussein A.; Gangarao, N. V. P. R.; Odeny, Damaris; Rathore, Abhishek; Dharmaraj, P. S.; Yamini, K. N.; Varshney, Rajeev K.
    Pigeonpea is an important pulse crop grown predominantly in the tropical and sub-tropical regions of the world. Although pigeonpea growing area has considerably increased, yield has remained stagnant for the last six decades mainly due to the exposure of the crop to various biotic and abiotic constraints. In addition, low level of genetic variability and limited genomic resources have been serious impediments to pigeonpea crop improvement through modern breeding approaches. In recent years, however, due to the availability of next generation sequencing and high-throughput genotyping technologies, the scenario has changed tremendously. The reduced sequencing costs resulting in the decoding of the pigeonpea genome has led to the development of various genomic resources including molecular markers, transcript sequences and comprehensive genetic maps. Mapping of some important traits including resistance to Fusarium wilt and sterility mosaic disease, fertility restoration, determinacy with other agronomically important traits have paved the way for applying genomics-assisted breeding (GAB) through marker assisted selection as well as genomic selection (GS). This would accelerate the development and improvement of both varieties and hybrids in pigeonpea. Particularly for hybrid breeding programme, mitochondrial genomes of cytoplasmic male sterile (CMS) lines, maintainers and hybrids have been sequenced to identify genes responsible for cytoplasmic male sterility. Furthermore, several diagnostic molecular markers have been developed to assess the purity of commercial hybrids. In summary, pigeonpea has become a genomic resources-rich crop and efforts have already been initiated to integrate these resources in pigeonpea breeding.
  • Thumbnail Image
    Item
    Improvement of resistance to Fusarium root rot through gene pyramiding and validation of SSR PVBR87 marker in common bean
    (Makerere University, 2011) Obala, Jimmy
    Fusarium root rot caused by Fusarium solani f. sp. phaseoli is among the most serious diseases of the common bean in Uganda causing total crop loss in susceptible cultivars. Studies have indicated that 2-9 genes located at different loci govern resistance to Fusarium root rot among different resistance sources. Accumulation of several of these genes from the different sources into a single genetic background has been proposed to result in an increased level of resistance to Fusarium root rot, and more effective transfer of this resistance into consumer-preferred cultivars. Use of molecular markers together with phenotypic selection could speed up breeding progress for Fusarium root rot resistance. A simple sequence repeat (SSR) PVBR87 marker linked to Fusarium root rot resistance quantitative trait loci (QTL) was identified in a previous study but its use in identifying resistant genotypes outside the original two mapping populations has not been determined. This study estimated the number of pyramided Fusarium root rot resistance genes from four sources of resistance, their interaction and effectiveness in improving Fusarium root rot resistance levels. The study also validated the association of the SSR PVBR87 marker with resistance to Fusarium root rot in an additional population. The study was conducted at the International Centre for Tropical Agriculture (CIAT) based at the National Agricultural Research Laboratories – Kawanda, Uganda. Four Fusarium root rot resistant (R) inbred lines: MLB-48-89A (48), MLB-49-89A (49), G2333 (G2) and G685 (G6), and two susceptible (S) lines: K20 and Kanyebwa (Kan) were used in the study. A double cross (DC) was developed from the four resistant parents. The DC F1 and each resistant parent were crossed to the two susceptible cultivars to form five-parent crosses and single crosses, respectively. Parental, F1 and F2 populations were subjected to Fusarium solani f. sp. phasoeli isolate-3. Twenty one days xi after planting, symptom severity was assessed on a scale of 1-9 (varied at 1,2,3,4,5,6,7,8,9). Plants of each cross were grouped into resistant (score 1-4) and susceptible (score 5-9). F2 plants of K20 x G2 and 49 x Kan were screened with SSR PVBR87 marker. The estimated number of genes and gene interactions were determined using X2 goodness-of-fit test (P = 0.05) and means were compared by “Students t-test” (P = 0.05). The association of SSR PVBR87 marker to Fusarium root rot resistance was determined using X2 test of independence and single marker regression analysis (P = 0.05). Two to three genes segregated in the R x R single crosses and at least four genes segregated in the double cross population indicating three of the four resistant parents differed from each other by at least one gene and two of the four parents have at least one gene in common. Genetic effects among the crosses included additive and dominance effects and epistatic interactions. Five-parent crosses performed better than the single crosses, demonstrating the potential of using combined resistance in improving resistance to Fusarium root rot in susceptible bean cultivars. The SSR PVBR87 marker showed significant association to Fusarium root rot resistance in both K20 x G2 and Kan x 49 indicating its stability in different genetic background but still requires further validation in different environments and in additional genetic backgrounds to determine its use for marker-assisted breeding for improving resistance to Fusarium root rot. The genes responsible for the higher levels of Fusarium root rot resistance in the pyramids are not specifically known. It is necessary that these resistance genes be tagged with molecular markers. Tagging of the genes with molecular markers would provide knowledge of their genomic locations, the nature of their interactions and also facilitate the transfer of these genes or alleles, through molecular marker-assisted gene introgression, into other agronomically superior, but Fusarium root xii rot susceptible cultivars. Since no selection for Fusarium root rot resistance or any other desirable agronomic traits was practiced in this study, there is need to select between and within families from among the five-parent cross populations and the single crosses for resistance to Fusarium root rot. However, the predominance of non-additive gene effects for Fusarium root rot resistance, especially in the five-parent crosses suggests that selection for resistance would be more effective at advanced generations of selfing. The bean parents used in constructing the five-parent cross populations are of diverse seed character, growth habit, maturity period, and have varied response to several abiotic and biotic constraints. There is also need to select for these traits in the populations developed in this study as these traits eventually affect acceptability of any potential new variety. The amounts of phenotypic variation explained by the SSR PVBR87 in two populations were low; hence, there is still need to further validate the marker in additional populations and in several environments to determine its efficacy for marker-assisted breeding for Fusarium root rot resistance
  • Thumbnail Image
    Item
    Molecular mapping of seed protein content in pigeonpea – a drought tolerant crop of the semi-arid tropics
    (: InterDrought, 2017) Obala, Jimmy; Saxena, R.K.; Singh, V.K; Kale, S.M.; Garg, V.; Kumar, V.; Sameer Kumar, C.V; Tongoona, P; Sibiya, J.; Saxena, K.B
    Pigeonpea is a uniquely drought and heat tolerant crop that provides a major source of dietary protein to nearly a billion people in the tropical and semi-arid tropics of the world. Despite its importance as a source of dietary protein the genetic control of its seed protein content (SPC) is poorly understood. The present study used high density linkage maps to identify quantitative trait loci (QTL) associated with SPC and its relationship with 100-seed weight (HSW), seed yield (SY), days to first flower (DTFF) and growth habit (GH). Five F2 mapping populations segregating for SPS including ICP 11605 × ICP 14209, ICP 8863 × ICP 11605, HPL 24 × ICP 11605, ICP 5529 × ICP 11605 and ICP 8863 × ICPL 87119 were genotyped using genotyping-by-sequencing and phenotyped for the traits. The average inter-marker distance on the population-specific maps varied from 1.6cM to 3.5cM.On the basis of the population-specific and consensus linkage maps, 48main effect QTLs (M-QTLs)with phenotypic variance explained (PVE) ranging from 0.7 to 23.5% were detected across five populations, of which 15 M-QTLs were major (PVE≥10). Twenty seven of the M-QTLs could be collapsed into six consensus QTL regions. In addition, 34 epistatic QTLs (E-QTLs) with PVE ranging from 6.3% to 69.8% were detected across populations. Co-localization of M-QTLs and E-QTLs affecting SPC and the agronomic traits explained the genetic basis of the significant (P < 0.05) correlations of SPC with HSW (r2 = 0.22 to 0.30), SY (r2 = -0.18 to -0.28), DTFF (r2 = -0.17 to -0.31) and GH (r2 = 0.18 to 0.34). The quantitative nature of genetic control of SPC and its relationship with agronomic traits suggest that marker-assisted recurrent selection or genomic selection would be effective for the simultaneous improvement of SPC and other important traits
  • Thumbnail Image
    Item
    Pyramiding Fusarium root rot resistance genes and validation of SSR PVBR87 in common bean
    (RUFORUM, 2010) Obala, Jimmy; Rubaihayo, P.R; Mukankusi, C; Gibson, P
    This study determined effectiveness of pyramided Fusarium root rot (FRR) resistance genes and validated association of SSR PVBR87 marker with FRR resistance in common bean. A double cross (DC) involving four resistance sources was used to accumulate FRR resistance genes into one background. The DC F1 and each resistant line were crossed to two susceptible cultivars. Parents, F1 and F2 populations were subjected to FSP-3 in a screenhouse. Two single cross (SC) F2 populations were screened with SSR PVBR87 marker. Five parent crosses performed better than single crosses. SSR PVBR87 marker showed association with FRR resistance in the two SC F2 populations.
  • Thumbnail Image
    Item
    QTL-seq for the identification of candidate genes for days to flowering and leaf shape in pigeonpea
    (Heredity, 2022) Singh, Vikas; Sinha, Pallavi; Obala, Jimmy; Khan, Aamir W.; Chitikinen, Annapurna; Saxena, Rachit K.; Varshney, Rajeev K.
    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.
  • Thumbnail Image
    Item
    Seed protein content and its relationships with agronomic traits in pigeonpea is controlled by both main and epistatic efects QTLs
    (Scientific Reports, 2020) Obala, Jimmy; Saxena, Rachit K.; Singh, Vikas K.; Kale, Sandip M.; Garg, Vanika; Kumar, C.V. Sameer; Saxena, K. B.; Tongoona, Pangirayi; Sibiya, Julia; Varshney, Rajeev K.
    The genetic architecture of seed protein content (SPC) and its relationships to agronomic traits in pigeonpea is poorly understood. Accordingly, fve F2 populations segregating for SPC and four agronomic traits (seed weight (SW), seed yield (SY), growth habit (GH) and days to frst fowering (DFF)) were phenotyped and genotyped using genotyping-by-sequencing approach. Five high-density population-specifc genetic maps were constructed with an average inter-marker distance of 1.6 to 3.5cM, and subsequently, integrated into a consensus map with average marker spacing of 1.6cM. Based on analysis of phenotyping data and genotyping data, 192 main efect QTLs (M-QTLs) with phenotypic variation explained (PVE) of 0.7 to 91.3% were detected for the fve traits across the fve populations. Major efect (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 signifcant (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 efective for the simultaneous improvement of SPC and other important traits.
  • Thumbnail Image
    Item
    Study of inheritance and identification of molecular markers for seed protein content in pigeonpea (Cajanus cajan (L.) Millsp.)
    (University of KwaZulu-Natal, Pietermaritzburg, Republic of South Africa, 2017) Obala, Jimmy
    Pigeonpea is an important source of protein to the vegetarian and poor families around the globe, however, very little is known about the genetic control of seed protein content (SPC) and how it relates with other traits of agronomic importance in the crop. Availability of genomic resources such as a reference genome and whole genome resequencing data of germplasm lines in pigeonpea coupled with recent advances in next generation sequencing technologies provide opportunity to dissect the genetic architecture of SPC in the crop. The objectives of this study were to: (i) determine variation of SPC and its relationship with agronomic traits of importance in a set of breeding lines and landraces, (ii) study the inheritance of SPC and its relationship with seed weight and seed yield, (iii) identify quantitative trait loci (QTLs) conditioning SPC, and (iv) identify candidate genes involved in the accumulation of SPC using whole genome sequencing approach. To determine variation in SPC and its relationship with some agronomic traits in pigeonpea, 23 pigeonpea genotypes were used. The genotypes are parents of different mapping populations presently being developed at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India. The 23 genotypes were evaluated under field conditions at ICRISAT in 2014-2015 growing season. The experiment was carried out in RCB design with two replications. Data were recorded on SPC, number of days to first flowering (DTF), plant height (PH) at maturity, number of pods per plant (NPP), number of seeds per pod (NSP), 100- seed weight (SW) and seed yield per plant (SY). Seed protein content ranged from 19.3 to 25.5%, DTF (48 to 156 days), PH (67.5 to 230 cm), NPP (31.7 to 582 pods), NSP (2.9 to 4.6 seeds/pod), SW (6.2 to 20.8 g) and SY (7.9 to 333.4 g). There were significant differences among genotypes for all traits. Broad-sense heritability was 0.693 for SPC and ranged from 0.517 to 0.999 among the agronomic traits. Genetic advance (GA) was 2.4 % for SPC but ranged from 1.2 % to 141. % among the agronomic traits. Genetic gain, which is GA expressed as a percentage of the trait’s grand mean, was 11.0 % for SPC but ranged from 56.4 to 713.4 % among the agronomic traits. Simple correlation indicated that SPC is generally negatively associated with all measured traits but only significantly with SW. However, path coefficient analysis revealed that, in addition to SW, NPP also had a strong negative direct influence on SPC, whereas SY had strong positive direct effect on SPC. Indirect effects of the agronomic ii traits on SPC were also noticeable with NPP and SW having strong negative and positive effects, respectively on SPC via SY. To investigate inheritance pattern of SPC in pigeonpea, four elite germplasm lines of varying SPC were used to develop three crosses. Six generations (P1, P2, F1, F2, BC1P1 and BC1P2) were generated. Generation mean analysis (GMA) revealed the importance of dominance and epistatic effects for SPC. Duplicate and negative additive × additive epistasis were predominant. Transgressive segregation for SPC was conspicuous. Additive genetic variance component was higher than the environmental and dominance components. Broad-sense heritability ranged from 0.52 to 0.60. Predicted genetic gain after one cycle of selection was highest at 5% selection intensity. Seed weight and yield were positively and negatively correlated with SPC, respectively. The results suggests that careful selection of parents, and recurrent selection procedure targeting transgressive segregants should be effective for improving SPC in pigeonpea. For the identification of QTLs associated with SPC and its relationship with some agronomic traits, five F2 mapping populations segregating for SPC were developed, genotyped using genotyping-by-sequencing and phenotyped for SPC, 100-seed weight (SW), seed yield (SY), days to first flower (DTF) and growth habit (GH) under field conditions. The average inter marker distance in the population-specific maps varied from 1.6 cM to 3.5 cM. On the basis of the population-specific and consensus linkage maps, a total of 196 main effect QTLs (M QTLs) across all traits were detected that explained 0.7 to 91.3% of the phenotypic variation for the five traits across the five F2 mapping populations. In the case of SPC as the core trait in the present study, a total of 48 main effect QTLs (M-QTLs) with phenotypic variance explained (PVE) ranging from 0.7 to 23.5% were detected across five populations of which 15 M-QTLs were major (PVE≥10). Twenty seven of the M-QTLs from the five F2 mapping populations could be projected into six consensus M-QTL regions. Out of 573 epistatic QTLs (E-QTLs) detected with PVE ranging from 6.3 to 99.4% across traits and populations, 34 involved SPC with PVE ranging from 6.3 to 69.8%. Several co-localization of M-QTLs and E-QTLs affecting SPC and the agronomic traits were also detected and could explain the genetic basis of the significant (P < 0.05) correlations of SPC with SW (r2 = 0.22 to 0.30), SY iii (r2 = -0.18 to -0.28), DTF (r2 = -0.17 to -0.31) and GH (r2 = 0.18 to 0.34). The quantitative nature of genetic control of SPC and its relationship with agronomic traits suggest that marker assisted recurrent selection or genomic selection would be effective for the simultaneous improvement of SPC and other important traits. To identify candidate variants and genes associated with SPC, whole genome resequencing (WGRS) data with an average of 12× coverage per genotype when compared to the Asha (ICPL 87119) reference genome was used. By combining a common variant (CV) filtering strategy with knowledge of gene functions in relation to SPC, 108 sequence variants whose presence lead to protein change were selected. The variants were found in 57 genes spread over all chromosomes except CcLG05. Identified genes were assigned to 19 categories based on gene ontology molecular function with fifty six percent of the identified genes belonging to only two functional categories. Sanger sequencing confirmed the presence of 52 (75.4%) sequence variants in 37 genes between low and high SPC genotypes. Fifty nine variants were converted into CAPS/dCAPS markers and assayed for polymorphism. Highest level of polymorphism was in low by high SPC parental pairs, while the lowest was in high by high parental pairs. Assay of 16 polymorphic CAPS/dCAPS markers on an F2 segregating population of the cross ICP 5529 × ICP 11605 (high × low), resulted in 11 of the markers being incorporated into a GBS-derived SNPs genetic map. Single marker analysis (SMA) indicated four of the 16 CAPS/dCAPS markers to be significantly correlated with SPC. Three out of the four markers were positioned at <10.0 cM distance away from main effect SPC QTLs all on CcLG02. All the three markers found in close proximity to SPC QTL positions and those with significant association to SPC were derived from mutations in the same genes including NADH-GOGAT, copper transporter and BLISTER all on CcLG02. Results from this study provide a foundation for future basic research and marker-assisted breeding of pigeonpea for increased SPC. In general, the complex nature of the genetic architecture of SPC as revealed by classical quantitative genetic analysis, QTL analysis and candidate gene analysis suggests that breeding approaches that target genome wide variations for crop improvement would be more appropriate in achieving larger genetic gains for SPC in shorter periods than using conventional phenotype-based selection