SummaryTo map resistance genes for Fusarium wilt (FW) and sterility mosaic disease (SMD) in pigeonpea, sequencing‐based bulked segregant analysis (Seq‐BSA) was used. Resistant (R) and susceptible (S) bulks from the extreme recombinant inbred lines of ICPL 20096 × ICPL 332 were sequenced. Subsequently, SNP index was calculated between R‐ and S‐bulks with the help of draft genome sequence and reference‐guided assembly of ICPL 20096 (resistant parent). Seq‐BSA has provided seven candidate SNPs for FW and SMD resistance in pigeonpea. In parallel, four additional genotypes were re‐sequenced and their combined analysis with R‐ and S‐bulks has provided a total of 8362 nonsynonymous (ns) SNPs. Of 8362 nsSNPs, 60 were found within the 2‐Mb flanking regions of seven candidate SNPs identified through Seq‐BSA. Haplotype analysis narrowed down to eight nsSNPs in seven genes. These eight nsSNPs were further validated by re‐sequencing 11 genotypes that are resistant and susceptible to FW and SMD. This analysis revealed association of four candidate nsSNPs in four genes with FW resistance and four candidate nsSNPs in three genes with SMD resistance. Further, In silico protein analysis and expression profiling identified two most promising candidate genes namely C.cajan_01839 for SMD resistance and C.cajan_03203 for FW resistance. Identified candidate genomic regions/SNPs will be useful for genomics‐assisted breeding in pigeonpea.

Key message We report growth habit profiling following SEM, genetic mapping and QTL analysis. Highlighted CcTFL1 , a candidate for determinacy in pigeonpea, since an Indel marker derived from this gene co-segregated with Dt1 locus. AbstractPigeonpea (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, Medicago, and Glycine. One of them is growth habit, an important agronomic trait. In the present study, identification of mutations affecting growth habit accompanied by a precise 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 pigeonpea, since an Indel marker derived from this gene co-segregated 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.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-017-2924-2) contains supplementary material, which is available to authorized users.

Seven strains of bacteria [Pseudomonas plecoglossicida SRI-156, Brevibacterium antiquum SRI-158, Bacillus altitudinis SRI-178, Enterobacter ludwigii SRI-211, E. ludwigii SRI-229, Acinetobacter tandoii SRI-305 and Pseudomonas monteilii SRI-360; demonstrated previously for control of charcoal rot disease in sorghum and plant growth-promotion (PGP) in rice] were evaluated for their PGP and biofortification traits in chickpea and pigeonpea under field conditions. When treated on seed, the seven selected bacteria significantly enhanced the shoot height and root length of both chickpea and pigeonpea over the un-inoculated control. Under field conditions, in both chickpea and pigeonpea, the plots inoculated with test bacteria enhanced the nodule number, nodule weight, root and shoot weights, pod number, pod weight, leaf weight, leaf area and grain yield over the un-inoculated control plots. Among the seven bacteria, SRI-229 was found to significantly and consistently enhance all the studied PGP and yield traits including nodule number (24 and 36%), nodule weight (11 and 44%), shoot weight (22 and 20%), root weight (23 and 16%) and grain yield (19 and 26%) for both chickpea and pigeonpea, respectively. When the harvested grains were evaluated for their mineral contents, iron (up to 18 and 12%), zinc (up to 23 and 5%), copper (up to 19 and 8%), manganese (up to 2 and 39%) and calcium (up to 22 and 11%) contents in chickpea and pigeonpea, respectively, were found enhanced in test bacteria inoculated plots over the un-inoculated control plots. This study further confirms that the selected bacterial isolates not only have the potential for PGP in cereals and legumes but also have the potential for biofortification of mineral nutrients.

Key messageWe report molecular mapping and inheritance of restoration of fertility (Rf) in A4 hybrid system in pigeonpea. We have also developed PCR-based markers amenable to low-cost genotyping to identify fertility restorer lines.AbstractCommercial hybrids in pigeonpea are based on A4 cytoplasmic male sterility (CMS) system, and their fertility restoration is one of the key prerequisites for breeding. In this context, an effort has been made to understand the genetics and identify quantitative trait loci (QTL) associated with restoration of fertility (Rf). One F2 population was developed by crossing CMS line (ICPA 2039) with fertility restorer line (ICPL 87119). Genetic analysis has shown involvement of two dominant genes in regulation of restoration of fertility. In parallel, the genotyping-by-sequencing (GBS) approach has generated ~ 33 Gb data on the F2 population. GBS data have provided 2457 single nucleotide polymorphism (SNPs) segregating across the mapping population. Based on these genotyping data, a genetic map has been developed with 306 SNPs covering a total length 981.9 cM. Further QTL analysis has provided the region flanked by S8_7664779 and S8_6474381 on CcLG08 harboured major QTL explained up to 28.5% phenotypic variation. Subsequently, sequence information within the major QTLs was compared between the maintainer and the restorer lines. From this sequence information, we have developed two PCR-based markers for identification of restorer lines from non-restorer lines and validated them on parental lines of hybrids as well as on another F2 mapping population. The results obtained in this study are expected to enhance the efficiency of selection for the identification of restorer lines in hybrid breeding and may reduce traditional time-consuming phenotyping activities.Electronic supplementary materialThe online version of this article (10.1007/s00122-018-3101-y) contains supplementary material, which is available to authorized users.

Identification of candidate genomic regions associated with target traits using conventional mapping methods is challenging and time‐consuming. In recent years, a number of single nucleotide polymorphism (SNP)‐based mapping approaches have been developed and used for identification of candidate/putative genomic regions. However, in the majority of these studies, insertion–deletion (Indel) were largely ignored. For efficient use of Indels in mapping target traits, we propose Indel‐seq approach, which is a combination of whole‐genome resequencing (WGRS) and bulked segregant analysis (BSA) and relies on the Indel frequencies in extreme bulks. Deployment of Indel‐seq approach for identification of candidate genomic regions associated with fusarium wilt (FW) and sterility mosaic disease (SMD) resistance in pigeonpea has identified 16 Indels affecting 26 putative candidate genes. Of these 26 affected putative candidate genes, 24 genes showed effect in the upstream/downstream of the genic region and two genes showed effect in the genes. Validation of these 16 candidate Indels in other FW‐ and SMD‐resistant and FW‐ and SMD‐susceptible genotypes revealed a significant association of five Indels (three for FW and two for SMD resistance). Comparative analysis of Indel‐seq with other genetic mapping approaches highlighted the importance of the approach in identification of significant genomic regions associated with target traits. Therefore, the Indel‐seq approach can be used for quick and precise identification of candidate genomic regions for any target traits in any crop species.