Large-scale variant identification and annotation from whole-genome-sequencing data enables functional prediction in grapevine
Abstract
Grapevine (Vitis vinifera) is amongst the world’s most cultivated fruit crops, and of global and economic significance. The genus Vitis, encompassing approximately 70 naturally occurring inter-fertile species, exhibits extensive genetic and phenotypic diversity, highlighted by the global cultivation of thousands of predominantly Vitis vinifera cultivars. Despite the importance of harnessing its naturally occurring genetic diversity to pursue traits of interest, the systematic characterization of available functional genetic variants remains limited. Such characterizations hold the potential not only as a critical tool for directed breeding, including the identification of molecular markers for genetic selection, but would also enable the functional characterization of genes that may exert influence over key functional traits. With over 5,000 Illumina-sequenced accessions available, detecting and comparing sequence variation (e.g., single nucleotide polymorphisms; SNPs) across the grapevine germplasm presents a unique opportunity to integrate heterogeneous sequencing information and improve candidate gene exploration. To this end, we developed Vinotype, a Nextflow-based pipeline for efficient and reproducible large-scale variant identification and annotation of Vitis whole-genome-sequencing (WGS) datasets. We validated Vinotype’s performance using genomic regions with known functionally characterized variants within DXS1 and AGL11, and benchmarked results against a commercially available SNP-array, demonstrating high concordance (> 95 % genotyping accuracy) in variant discovery capabilities. Analysis of over 177,000 putatively high-to-moderate impact SNPs identified several candidate variants linked to genes associated with specialized metabolism, fruit-related characteristics and development, in addition to biotic and abiotic stress responses. To further demonstrate the pipeline’s scalability and efficiency, we processed over 3,000 publicly available WGS datasets providing a valuable resource for allele-mining and candidate gene prioritization in grapevine. This large-scale cataloguing of coding region sequence variation provides the foundation for future predictions regarding the impact of genetic variations on protein structure and function, facilitating the identification of beneficial alleles and novel sequence-trait associations, ultimately aiming to accelerate genetic improvement programs and the development of cultivars with enhanced attributes.
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Acknowledgements
Funding provided by the National Research Foundation (NRF) (Grant number PMDS230626121748) of South Africa is herebyacknowledged.
Issue: GBG 2026
Type: Oral
Authors
1 Department of Genetics, Stellenbosch University. (7600) Stellenbosch, South Africa
2 Instituto de Ciencias de la Vid y del Vino, ICVV, CSIC – Universidad de La Rioja – Gobierno de La Rioja. (26007) La Rioja, Logroño, Spain