Key message Genetic mapping identified large number of epistatic interactions indicating the complex genetic architecture for stem rot disease resistance. Abstract Groundnut (Arachis hypogaea) is an important global crop commodity and serves as a major source of cooking oil, diverse confectionery preparations and livestock feed. Stem rot disease caused by Sclerotium rolfsii is the most devastating disease of groundnut and can cause up to 100% yield loss. Genomic-assisted breeding (GAB) has potential for accelerated development of stem rot resistance varieties in short period with more precision. In this context, linkage analysis and quantitative trait locus (QTL) mapping for resistance to stem rot disease was performed in a bi-parental recombinant inbred line population developed from TG37A (susceptible) × NRCG-CS85 (resistant) comprising of 270 individuals. Genotyping-bysequencing approach was deployed to generate single nucleotide polymorphism (SNP) genotyping data leading to development of a genetic map with 585 SNP loci spanning map distance of 2430 cM. QTL analysis using multi-season phenotyping and genotyping data could not detect any major main-effect QTL but identified 44 major epistatic QTLs with phenotypic variation explained ranging from 14.32 to 67.95%. Large number interactions indicate the complexity of genetic architecture of resistance to stem rot disease. A QTL of physical map length 5.2 Mb identified on B04 comprising 170 different genes especially leucine reach repeats, zinc finger motifs and ethyleneresponsivefactors, etc., was identified. The identified genomic regions and candidate genes will further validate and facilitate marker development to deploy GAB for developing stem rot disease resistance groundnut varieties.Communicated by Henry T. Nguyen. Electronic supplementary materialThe online version of this article (https ://doi.org/10.1007/s0012 2-018-3255-7) contains supplementary material, which is available to authorized users. * Rajeev K. Varshney

Stem rot, a devastating fungal disease of peanut, is caused by Sclerotium rolfsii. RNAsequencing approaches have been used to unravel the mechanisms of resistance to stem rot in peanut over the course of fungal infection in resistant (NRCG-CS85) and susceptible (TG37A) genotypes under control conditions and during the course of infection. Out of about 290 million reads, nearly 251 million (92.22%) high-quality reads were obtained and aligned to the Arachis duranensis and Arachis ipaensis genomes with the average mapping of 78.91% and 78.61%, respectively. In total, about 48.6% of genes were commonly regulated, while approximately 21.8% and 29.6% of uniquely regulated genes from A. duranensis and A. ipaensis genomes, respectively, were identified. Several annotated transcripts, such as receptor-like kinases, jasmonic acid pathway enzymes, and transcription factors (TFs), including WRKY, Zinc finger protein, and C2-H2 zinc finger, showed higher expression in resistant genotypes upon infection. These transcripts have a known role in channelizing the downstream of pathogen perception. The higher expression of WRKY transcripts might have induced the systemic acquired resistance (SAR) by the activation of the jasmonic acid defense signaling pathway. Furthermore, a set of 30 transcripts involved in the defense mechanisms were validated with quantitative real-time PCR. This study suggested PAMP-triggered immunity as a probable mechanism of resistance, while the jasmonic acid signaling pathway was identified as a possible defense mechanism in peanut. The information generated is of immense importance in developing more effective ways to combat the stem rot disease in peanut.

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Aim: Methodology:Results: Interpretation:Identification of diverse sugar beet (Beta vulgaris L.) genotypes is essential for using them as parents in sugar beet improvement programme of India. Hence, genetic variation and diversity of elite sugar beet germplasm collection was analysed using microsatellite markers.Genomic DNA of thirteen genotypes was amplified using 14 microsatellite primers containing dinucleotide to compound repeat motifs. Amplified bands were scored on gel, transformed into a binary character matrix and analyzed through NTSYS software for clustering in heterotic groups.A total of 243 amplicons were resolved and grouped into 88 alleles of distinct molecular weight ranging from 124 to 1222 bp with an average of 17.36 amplicons/primer, 4 to10 alleles/SSR locus and moderate to high PIC ranging from 0.625-0.851. Similarity coefficients ( S M ) b a s e d o n t h e presence/absence of alleles ranged from 0.47 to 0.89 (mean value of 0.65). UPGMA dendrogram based on SM, grouped these genotypes in two major taxonomical groups with five clusters having one, four, three, three and two genotypes each. Clustering pattern of UPGMA matched with the 2D and 3D scatter plots of MDS and PCA. The highly significant cophenetic coefficient of r = 0.96 proved that these SSR markers efficiently analyzed the genetic relationships of sugar beet genotypes.Microsatellite markers can be used as a potential cost effective method for exploring molecular genetic diversity in sugar beet in order to obtain new genetic combinations.