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ARS Home » Northeast Area » Geneva, New York » Grape Genetics Research Unit (GGRU) » Research » Publications at this Location » Publication #301054

Title: Comparative transcriptomics of wild North American Vitis species

item OSIPOVITCH, MIKHAIL - Former ARS Employee
item Lillis, Jacquelyn
item Londo, Jason

Submitted to: Plant and Animal Genome Conference
Publication Type: Abstract Only
Publication Acceptance Date: 1/17/2014
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: The cultivated grapevine (Vitis vinifera) is one of the world’s most important fruit crops. While grapes are now cultivated across the world, biotic and abiotic stresses often limit the production of grapes. Compared with the cultivated grape, wild grapevine species possess adaptive traits for stress tolerance and may utilize different gene isoforms or novel genes to survive stress. As a result, breeding programs which use wild germplasm have been successful in increasing the growth range of grapes. Despite the availability of a genome sequence for the cultivated genotype cv. Pinot Noir, identifying the genetic basis of adaptive traits in wild species can be difficult. Therefore, we initiated a study to examine the variation in the transcriptomes of eight wild grapevine species using strand-specific RNA-sequencing. We sampled leaf, tendril, rachis, flower, unripe berry, ripe berry, root and dormant bud tissue from 24 different grapevine genotypes. Samples of leaf tissue exposed to chilling stress and cold shock were also included. Assemblies were constructed de novo using SOAP-deNovo, Oases, and Trinity assembler packages. Our sequencing recovered gene hits on 86-91% of the predicted genes in the Vitis vinifera transcriptome. The number of genes with 100% coverage was lower, approximately 10,000-15,000 of the V. vinifera genes (~50%). However, the vast majority of genes were covered at >90%. Assemblies that merged the results of the three assemblers yielded the highest number of reference gene hits. Future analysis using differential expression will be used to identify species specific and cold stress responsive genes and isoforms.