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Crop Science Society of America, Plant Genome, The, 1(7), 2014

DOI: 10.3835/plantgenome2013.12.0042

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Spud DB: A Resource for Mining Sequences, Genotypes, and Phenotypes to Accelerate Potato Breeding

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Potato is the world's third most important crop, and is becoming increasingly important in developing countries. Cultivated potato is a highly heterozygous tetraploid (2n = 4x = 48) and suffers from significant inbreeding depression when selfed. As potato can be vegetatively propagated, breeding has been based primarily on phenotypic selection in F1 populations. However, recent advances in genome sequencing and genotyping methods have resulted in the development of large genomic, genetic, and phenotypic datasets that will enable more efficient and rapid breeding approaches. We have developed Spud DB ( http://potato.plantbiology.msu.edu/ ) for the community to access the potato genome sequence and associated annotation datasets, along with phenotypic and genotypic data from a diversity panel of 250 potato clones. The Breeder's Assistant is a web tool to retrieve pertinent phenotypic and genotypic data in a user-guided manner, and query polymorphic markers such as single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs) to identify custom sets of markers for a gene or region of interest. To browse and query the potato genome, a genome browser with 94 tracks of genome annotation, sequence variants, and expression abundance has been deployed. Spud DB also provides a comprehensive search page to data mine the potato genome through tools that query sequence identifiers, functional annotation, gene ontology (GO), InterPro domains, and basic local alignment search tool (BLAST) databases. Collectively, this resource links potato genomic data with phenotypic and genotypic data from a large collection of potato lines for use by the potato community, especially breeders and geneticists.