UMER, M. J. | bioRxiv Science

bioRxiv2026

Whole-genome resequencing identified loci underwent divergent selection and improved local adaptability in groundnut (Arachis hypogaea)

There is an urgent need to expand groundnut genomics knowledge base to improve yield and adaptability in the target environments. Whole-genome sequencing can discover selective sweeps in the genomic regions distinguishing adaptive from non-adaptive germplasm within target environments. When combined with genome-wide association studies (GWAS), this approach can reveal genes underpinning local adaptability and yield advantage. The objective of this study was to establish a genome-wide quantitative framework form identifying genomic regions under selection, with a particular focus on narrowing down regions associated with important yield and adaptive traits. Moreover, validation of elite haplotype distributions in an independent fully sequenced groundnut panel. A panel of 197 groundnut accessions was subjected to whole-genome sequencing and phenotypic evaluation to dissect the collection into adaptive and non-adaptive subsets to uncover the genomic regions under selection. This was then combined with GWAS to uncover genetic variants governing agronomic traits associated with yield and adaptability. The stringent single and multi-trait analysis identified 60 loci for 12 agronomic traits, of which seven loci controlled multiple yield related traits and were pleiotropic. Within our diversity panel, 48 genomic regions showed signs of selection. Among these selective sweeps, six positively selected loci were co-localized with trait associated loci. A large genomic region on chr2 spanning [~]78 Mb was under divergent selection and harbored genes underpinning yield and 20-pod length. A F-box transcription factor, Arahy.37HYKA, on chr9, and an alanine transferase protein gene, Arahy.E9MTVL, on chr12 carried peak SNPs associated with yield and related traits. We further cross-validated our results in another groundnut355 panel, where the corresponding genes within LD blocks showed significant effects on HKW, pod length and pod weight. The genomic resources developed here provide a high-resolution variation map to delineate the genes underpinning yield and developmental traits in groundnut, improved our understanding of the genetic basis of important agronomic traits, and provide a valuable resource for further functional genomics studies and groundnut improvement programs.

genomics↗

bioRxiv2022

Dynamic characteristics and Functional Analysis Provide new insights into the role of GauERF105 in resistance against Verticillium wilt in Cotton

Verticillium wilt is the most devastating disease of cotton and it results in huge yield losses every year in the fields. The underlying mechanisms of VW in cotton are not well explored yet. In the current approach we used the transcriptome data from G. australe in response to Verticillium wilt attack to mine the ERF TFs and prove their potential role in resistance against VW attack in cotton. We identified 23 ERFs in total, and on the basis of expression at different time points i.e., 24h, 48h and 72h post inoculation and selected GauERF105 for further validation. We performed VIGS in cotton and over expression in Arabidopsis respectively. Moreover, DAB and trypan staining also suggests that the impact of disease was more in the wildtype as compared to transgene lines. On the basis of our results, we confirmed that GauERF105 is the key candidate and playing a key role for defending cotton against VW attack. Current finding might be helpful for generating resistance germplasm in cotton and it will be beneficial to recover the yield losses in field.

pathology↗