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Summary Pre‐mRNA splicing is an essential step for the regulation of gene expression. In order to specifically capture splicing variants in plants for genome‐wide association studies (GWAS), we developed a software tool to quantify and visualise Variations of Splicing in Population (VaSP).VaSP can quantify splicing variants from short‐read RNA‐seq datasets and discover genotype‐specific splicing (GSS) events, which can be used to prioritise causal pre‐mRNA splicing events in GWAS. We applied our method to an RNA‐seq dataset with 328 samples from 82 genotypes from a rice diversity panel exposed to optimal and saline growing conditions.In total, 764 significant GSS events were identified in salt stress conditions. GSS events were used as markers for a GWAS with the shoot Na⁺accumulation, which identified six GSS events in five genes significantly associated with the shoot Na⁺content. Two of these genes,OsNUC1andOsRAD23emerged as top candidate genes with splice variants that exhibited significant divergence between the variants for shoot growth under salt stress conditions.VaSP is a versatile tool for alternative splicing analysis in plants and a powerful tool for prioritising candidate causal pre‐mRNA splicing and corresponding genomic variations in GWAS. 

Abstract Rice, an important food resource, is highly sensitive to salt stress, which is directly related to food security. Although many studies have identified physiological mechanisms that confer tolerance to the osmotic effects of salinity, the link between rice genotype and salt tolerance is not very clear yet. Association of gene co‐expression network and rice phenotypic data under stress has penitential to identify stress‐responsive genes, but there is no standard method to associate stress phenotype with gene co‐expression network. A novel method for integration of gene co‐expression network and stress phenotype data was developed to conduct a system analysis to link genotype to phenotype. We applied aLASSO‐based method to the gene co‐expression network of rice with salt stress to discover key genes and their interactions for salt tolerance‐related phenotypes. Submodules in gene modules identified from the co‐expression network were selected by theLASSOregression, which establishes a linear relationship between gene expression profiles and physiological responses, that is, sodium/potassium condenses under salt stress. Genes in these submodules have functions related to ion transport, osmotic adjustment, and oxidative tolerance. We argued that these genes in submodules are biologically meaningful and useful for studies on rice salt tolerance. This method can be applied to other studies to efficiently and reliably integrate co‐expression network and phenotypic data.