Browsing by Author "Varshney, Rajeev K."
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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.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 programsItem 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.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.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.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.