To understand the genetic basis of tolerance to drought and heat stresses in chickpea, a comprehensive association mapping approach has been undertaken. Phenotypic data were generated on the reference set (300 accessions, including 211 mini-core collection accessions) for drought tolerance related root traits, heat tolerance, yield and yield component traits from 1–7 seasons and 1–3 locations in India (Patancheru, Kanpur, Bangalore) and three locations in Africa (Nairobi, Egerton in Kenya and Debre Zeit in Ethiopia). Diversity Array Technology (DArT) markers equally distributed across chickpea genome were used to determine population structure and three sub-populations were identified using admixture model in STRUCTURE. The pairwise linkage disequilibrium (LD) estimated using the squared-allele frequency correlations (r2; when r2<0.20) was found to decay rapidly with the genetic distance of 5 cM. For establishing marker-trait associations (MTAs), both genome-wide and candidate gene-sequencing based association mapping approaches were conducted using 1,872 markers (1,072 DArTs, 651 single nucleotide polymorphisms [SNPs], 113 gene-based SNPs and 36 simple sequence repeats [SSRs]) and phenotyping data mentioned above employing mixed linear model (MLM) analysis with optimum compression with P3D method and kinship matrix. As a result, 312 significant MTAs were identified and a maximum number of MTAs (70) was identified for 100-seed weight. A total of 18 SNPs from 5 genes (ERECTA, 11 SNPs; ASR, 4 SNPs; DREB, 1 SNP; CAP2 promoter, 1 SNP and AMDH, 1SNP) were significantly associated with different traits. This study provides significant MTAs for drought and heat tolerance in chickpea that can be used, after validation, in molecular breeding for developing superior varieties with enhanced drought and heat tolerance.

Optimum flowering time is the key to maximize canola production in order to meet global demand of vegetable oil, biodiesel and canola-meal. We reveal extensive variation in flowering time across diverse genotypes of canola under f ield, glasshouse and controlled environmental conditions. We conduct a genome-wide association study and identify 69 single nucleotide polymorphism (SNP) markers associated with flowering time, which are repeatedly detected across experiments. Several associated SNPs occur in clusters across the canola genome; seven of them were detected within 20 Kb regions of a priori candidate genes; FLOWERING LOCUS T, FRUIT-FUL, FLOWERING LOCUS C, CONSTANS, FRIGIDA, PHYTOCHROME B and an additional five SNPs were localized within 14 Kb of a previously identified quantitative trait loci for flowering time. Expression analyses showed that among FLC paralogs, BnFLC.A2 accounts for~23% of natural variation in diverse accessions. Genome-wide association analysis for FLC expression levels mapped not only BnFLC. C2 but also other loci that contribute to variation in FLC expression. In addition to revealing the complex genetic architecture of flowering time variation, we demonstrate that the identified SNPs can be modelled to predict flowering time in diverse canola germplasm accurately and hence are suitable for genomic selection of adaptative traits in canola improvement programmes.

Several molecular marker systems have been developed for assessing genetic diversity in crop germplasm collections. A trade-off often exists between the number of loci that can feasibly be sampled by a marker system and the amount of information provided by each locus. We compared the usefulness of two marker systems for revealing genetic diversity and population structure in cassava (Manihot esculenta Crantz): simple sequence repeats (SSRs) and diversity array technology (DArT) markers. DArTs survey many more loci per reaction than do SSRs; however, as bi-allelic, dominant markers, DArTs provide less polymorphism information per locus. Genetic differentiation was assessed in a randomly selected set of 436 cassava accessions, consisting of 155 African and 281 Latin American accessions. A genome-wide set of 36 SSR markers and a DArT array of approximately 1000 polymorphic clones were used to assess genetic diversity and differentiation. Cluster analyses were performed using principal coordinate analysis (PCoA). Results were compared with a priori expectations of genetic differentiation based on previous genetic analyses. Analyses of the two datasets generated broadly similar clustering patterns. However, SSRs revealed greater differentiation than DArTs, and more effectively recovered patterns of genetic differentiation observed in previous analyses (differentiation between Latin American and African accessions, and some geographical differentiation within each of these groups). These results suggest that SSR markers, while low throughput in comparison with DArTs, are relatively better at detecting genetic differentiation in cassava germplasm collections. Nonetheless, DArTs will likely prove useful in ‘orphan crop’ species, where alternative molecular markers have not been developed.

Canola varieties exhibit variation in drought avoidance and drought escape traits, reflecting adaptation to water‐deficit environments. Our understanding of underlying genes and their interaction across environments in improving crop productivity is limited. A doubled haploid population was analysed to identify quantitative trait loci (QTL) associated with water‐use efficiency (WUE) related traits. High WUE in the vegetative phase was associated with low seed yield. Based on the resequenced parental genome data, we developed sequence‐capture‐based markers and validated their linkage with carbon isotope discrimination (Δ13C) in an F2 population. RNA sequencing was performed to determine the expression of candidate genes underlying Δ13C QTL. QTL contributing to main and QTL × environment interaction effects for Δ13C and yield were identified. One multiple‐trait QTL for Δ13C, days to flower, plant height, and seed yield was identified on chromosome A09. Interestingly, this QTL region overlapped with a homoeologous exchange (HE) event, suggesting its association with the multiple traits. Transcriptome analysis revealed 121 significantly differentially expressed genes underlying Δ13C QTL on A09 and C09, including in HE regions. Sorting out the negative relationship between vegetative WUE and seed yield is a priority. Genetic and genomic resources and knowledge so developed could improve canola WUE and yield.

Wheat is a staple crop in Nepal and is the third major cereal crop grown across the country. To improve productivity and increase the number of farmers growing wheat, the Nepal Agricultural Research Council (NARC), since 1962, has been releasing new wheat varieties with higher productivity and disease resistance. Accurate identification of the varieties grown in farmer's fields is critical for assessing the adoption levels and the impact of new varieties. This understanding can change the landscape of the wheat market and the overall vulnerability of the crop to diseases and abiotic stresses. Current methods of identification that rely on farmer description and morphological traits have been associated with ambiguity. The objective of this study was to determine the varietal adoption of wheat in the seven wheat-growing provinces of Nepal using DNA fingerprinting technology. The study revealed that 'Gautam' and 'Vijay' are the most popular wheat varieties planted in the plain areas of Nepal. The area covered in these varieties during the 2018-2019 wheat season was 20.3 and 19.5% respectively. 'WK1204' was popular and mostly planted in the mountainous areas of Nepal during the October-May cropping season. The decommissioned varieties, including 'Pitic62', 'Kalyansona', 'Siddhartha', 'Vaskar', 'Vinayak', and 'NL 251' are still in use by 8% of wheat farmers across Nepal. Almost 38% of the varieties currently grown were released 20 yr ago. The varietal adoption was determined using molecular markers through fingerprinting, and its implications are discussed in this paper.