Cotton bacterial leaf blight (CBB), caused by Xanthomonas citri subsp. malvacearum (Xcm) has been periodically a damaging disease in the U.S.A. Identi cation and deployment of genetic resistance in the cotton cultivars is the most economical and e cient means of reducing the crop losses due to CBB. In the current study, a combined genome-wide association study (GWAS) and linkage-mapping approach was used to map the CBB resistance gene in Upland cotton. An elite diversity panel of 380 accessions, genotyped with the Cotton 63K single nucleotide polymorphism (SNP) array and phenotyped with race-18 of CBB was used in the GWAS. The GWAS localized the CBB resistance to a 2.01 Mb region in the long arm of chromosome D02. Mapping of this CBB resistance was further resolved using linkage mapping in an F 6 recombinant inbred line (RIL) population derived from Acala Maxxa × Arkot 8102. The CBB resistance in Arkot 8102 showed monogenic inheritance. The CBB resistance locus (BB-13) was mapped within the 0.95 cM interval near the telomeric region in the long arm of chromosome D02. Flanking SNP markers, i25755Gh (p = 19.29) and i46775Gh (p = 19.29) of the BB-13 locus from the linkage analysis showed the highest signi cant marker-trait associations (MTAs) in the GWAS study. Using these SNPs, we targeted the BB-13 locus to a 371 Kb genomic region on chromosome D02. Candidate gene analysis identi ed thirty putative gene sequences in the targeted region. Nine of the thirty putative genes were involved in disease resistance in plants. Key MessageIdenti cation and genomic characterization of major resistance locus against cotton bacterial blight (CBB) using GWAS and linkage mapping to enable genomics-based development of durable CBB resistance and gene discovery in cotton.

Yellow Mosaic Virus (YMV) is a serious disease of soybean. Resistance to YMV was mapped in 180 soybean genotypes through association mapping approach using 121 simple sequence repeats (SSR) and four resistance gene analogue (RGA)-based markers. The association mapping population (AMP) (96 genotypes) and confirmation population (CP) (84 genotypes) was tested for resistance to YMV at hot-spot consecutively for 3 years (2007-2009). The genotypes exhibited significant variability for YMV resistance (P < 0.01). Molecular genotyping and population structure analysis with 'admixture' co-ancestry model detected seven optimal sub-populations in the AMP. Linkage disequilibrium (LD) between the markers extended up to 35 and 10 cM with r2 > 0.15, and >0.25, respectively. The 4 RGA-based markers showed no association with YMV resistance. Two SSR markers, Satt301 and GMHSP179 on chromosome 17 were found to be in significant LD with YMV resistance. Contingency Chi-square test confirmed the association (P < 0.01) and the utility of the markers was validated in the CP. It would pave the way for marker assisted selection for YMV resistance in soybean. This is the first report of its kind in soybean.

No abstract

Conventional breeding interventions in cotton have been successful and these techniques have doubled the productivity of cotton, but it took around 40 years. One of the techniques of molecular biology i.e., genetic engineering has brought significant improvement in productivity within the year of introduction. With cotton genomics maturing, many reference genomes and related genomic resources have been developed. Newer wild species have been discovered and many countries are conserving genetic resources within and between species. This valuable germplasm can be exchanged among countries for increasing cotton productivity. As many as 249 Mapping and Association studies have been carried out and many QTLs have been discovered and it is high time for researchers to get into fine-mapping studies. Techniques of genomic selection hold valuable trust for deciphering quantitative traits like fiber quality and productivity since they take in to account all minor QTLs. There are just two studies involving genomic selection in cotton, underlining its huge prospects in cotton research. Genome editing and transformation techniques have been widely used in cotton with as many as 65 events being developed across various characters, and eight studies carried out using crisper technology. These promising technologies have huge prospects for cotton production sustainability.

The identification of quantitative trait loci (QTL) across different environments is a prerequisite for marker‐assisted selection (MAS) in crop improvement programmes. CottonSNP63k Illumina infinium array was used for genotyping 178 inter‐specific recombinant inbred lines and the parents, and identified 1,667 homozygous polymorphic markers between the parents. Of these, 1,430 markers were used for the construction of linkage map after removing 237 redundant markers. The genetic map spans a total genetic length of 3,149.8 cM with an average marker interval size of 2.2 cM. The phenotypic data from five environments were analysed separately using inclusive composite interval mapping which identified a total of 56 QTL explaining phenotypic variances (PVE) in the range of 8.18%–28.91%. There were 11 and 24 major QTL found for fibre quality and yield components, respectively. A total of 64 QTL were identified through Multi‐Environment Trials analysis, of which 34 recorded QTL × Environment interactions.