Summary Rice sheath blight disease, caused by the basidiomycetous necrotroph Rhizoctonia solani, became one of the major threats to the rice cultivation worldwide, especially after the adoption of high‐yielding varieties. The pathogen is challenging to manage because of its extensively broad host range and high genetic variability and also due to the inability to find any satisfactory level of natural resistance from the available rice germplasm. It is high time to find remedies to combat the pathogen for reducing rice yield losses and subsequently to minimize the threat to global food security. The development of genetic resistance is one of the alternative means to avoid the use of hazardous chemical fungicides. This review mainly focuses on the effort of better understanding the host–pathogen relationship, finding the gene loci/markers imparting resistance response and modifying the host genome through transgenic development. The latest development and trend in the R. solani–rice pathosystem research with gap analysis are provided.

Haplotype-based breeding, a recent promising breeding approach to develop tailor-made crop varieties, deals with identification of superior haplotypes and their deployment in breeding programmes. In this context, whole genome re-sequencing data of 292 genotypes from pigeonpea reference set were mined to identify the superior haplotypes for 10 droughtresponsive candidate genes. A total of 83, 132 and 60 haplotypes were identified in breeding lines, landraces and wild species, respectively. Candidate gene-based association analysis of these 10 genes on a subset of 137 accessions of the pigeonpea reference set revealed 23 strong marker-trait associations (MTAs) in five genes influencing seven drought-responsive component traits. Haplo-pheno analysis for the strongly associated genes resulted in the identification of most promising haplotypes for three genes regulating five component drought traits. The haplotype C. cajan_23080-H2 for plant weight (PW), fresh weight (FW) and turgid weight (TW), the haplotype C. cajan_30211-H6 for PW, FW, TW and dry weight (DW), the haplotype C. cajan_26230-H11 for FW and DW and the haplotype C. cajan_26230-H5 for relative water content (RWC) were identified as superior haplotypes under drought stress condition. Furthermore, 17 accessions containing superior haplotypes for three drought-responsive genes were identified. The identified superior haplotypes and the accessions carrying these superior haplotypes will be very useful for deploying haplotype-based breeding to develop nextgeneration tailor-made better drought-responsive pigeonpea cultivars.

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.

Background: Restoration of fertility (Rf) is an important trait for pigeonpea hybrid breeding. Few coarse quantitative trait locus (QTL) studies conducted in the past identified QTLs with large confidence intervals on the genetic map and could not provide any information on possible genes responsible for Rf in pigeonpea. Therefore, a larger population comprising of 369 F 2 s derived from ICPA 2039 × ICPL 87119 was genotyped with high density Axiom Cajanus SNP Array with 56 K single nucleotide polymorphism (SNPs) for high resolution mapping of Rf. Results: A genetic map with 4867 markers was developed and a total of four QTLs for Rf were identified. While one major effect QTL (qRf8.1) was co-localized with the QTL identified in two previous studies and its size was refined from 1.2 Mb to 0.41 Mb. Further analysis of qRf8.1 QTL with genome sequence provided 20 genes including two genes namely flowering locus protein T and 2-oxoglutarate/Fe (II)-dependent dioxygenases (2-ODDs) superfamily protein with known function in the restoration of fertility. Conclusion: The qRf8.1 QTL and the potential candidate genes present in this QTL will be valuable for genomicsassisted breeding and identification of causal genes/nucleotides for the restoration of fertility in the hybrid breeding program of pigeonpea.

Genetic diversity studies provide important details on target trait availability and its variability, for the success of breeding programs. In this study, GBS approach was used to reveal a new structuration of genetic diversity and population structure of pigeonpea in Benin. We used a total of 688 high-quality Single Nucleotide Polymorphism markers for a total of 44 pigeonpea genotypes. The distribution of SNP markers on the 11 chromosomes ranged from 14 on chromosome 5 to 133 on chromosome 2. The Polymorphism Information Content and gene diversity values were 0.30 and 0.34 respectively. The analysis of population structure revealed four clear subpopulations. The Weighted Neighbor Joining tree agreed with structure analyses by grouping the 44 genotypes into four clusters. The PCoA revealed that genotypes from subpopulations 1, 2 and 3 intermixed among themselves. The Analysis of Molecular Variance showed 7% of the total variation among genotypes while the rest of variation (93%) was within genotypes from subpopulations indicating a high gene exchange (Nm = 7.13) and low genetic differentiation (PhiPT = 0.07) between subpopulations. Subpopulation 2 presented the highest mean values of number of different alleles (Na = 1.57), number of loci with private alleles (Pa = 0.11) and the percentage of polymorphic loci (P = 57.12%). We discuss our findings and demonstrate how the genetic diversity and the population structure of this specie can be used through the Genome Wide Association Studies and Marker-Assisted Selection to enhance genetic gain in pigeonpea breeding programs in Benin.