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.
M. Jahanzaib, Kun-Hui He, S. Rehman et al.· bioRxiv· 0 citations
INTRODUCTION
Rice panicle development is a key agronomic trait that critically determining grain yield and quality. However, the underlying molecular networks, particularly those regulated by de novo genes, remain inadequately characterized.
OBJECTIVES
To address this gap, we performed an integrated transcriptomic, metabolomic, and proteomic analysis of the de novo gene GRAIN SHAPE ON CHROMOSOME 9(GSE9) during panicle development.
RESULTS
Our findings demonstrate that GSE9 disruption activates extensive transcriptomic reprogramming during critical stages. Functional analyses revealed that GSE9 may direct a hierarchical regulatory network, possibly by modulating key transcription factors-such as ERF, WRKY, and bZIP-to integrate hormone signaling pathways, including gibberellin and abscisic acid. Concurrently, GSE9 deficiency led to widespread metabolic dysregulation, particularly in secondary metabolism involving phenylpropanoid and flavonoid biosynthesis that affects spikelet hull properties. A machine learning (KANMB) approach applied to the metabolomic data identified a core set of metabolites and co-expressed genes, indicating that GSE9 coordinately regulates starch metabolism and secondary metabolite biosynthesis. Proteomic profiling further confirmed alterations in these pathways. Critically,GSE9 knockout induced genome-wide transcriptional-translational decoupling, specifically impairing synchronous mRNA-protein coordination rather than simply introducing a temporal delay between transcription and translation. Further analysis revealed that this effect stems from a transcription-dominant regulatory mode, potentially accompanied by translational compensation, while direct evidence is lacking.
CONCLUSIONS
This study delineates a multi-level regulatory mechanism by which GSE9 determines grain shape and underscores the broad network-wide effects of gene editing, providing crucial insights for fundamental research and precision crop breeding.
Shoukun Chen, Zhijun Chen, Hao Zhang et al.· Journal of Advanced Research· 0 citations
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