Mapping in the era of sequencing: high density genotyping and its application for mapping TYLCV resistance in Solanum pimpinellifolium View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-12

AUTHORS

Marcela Víquez-Zamora, Myluska Caro, Richard Finkers, Yury Tikunov, Arnaud Bovy, Richard GF Visser, Yuling Bai, Sjaak van Heusden

ABSTRACT

BACKGROUND: A RIL population between Solanum lycopersicum cv. Moneymaker and S. pimpinellifolium G1.1554 was genotyped with a custom made SNP array. Additionally, a subset of the lines was genotyped by sequencing (GBS). RESULTS: A total of 1974 polymorphic SNPs were selected to develop a linkage map of 715 unique genetic loci. We generated plots for visualizing the recombination patterns of the population relating physical and genetic positions along the genome.This linkage map was used to identify two QTLs for TYLCV resistance which contained favourable alleles derived from S. pimpinellifolium. Further GBS was used to saturate regions of interest, and the mapping resolution of the two QTLs was improved. The analysis showed highest significance on Chromosome 11 close to the region of 51.3 Mb (qTy-p11) and another on Chromosome 3 near 46.5 Mb (qTy-p3). Furthermore, we explored the population using untargeted metabolic profiling, and the most significant differences between susceptible and resistant plants were mainly associated with sucrose and flavonoid glycosides. CONCLUSIONS: The SNP information obtained from an array allowed a first QTL screening of our RIL population. With additional SNP data of a RILs subset, obtained through GBS, we were able to perform an in silico mapping improvement to further confirm regions associated with our trait of interest. With the combination of different ~ omics platforms we provide valuable insight into the genetics of S. pimpinellifolium-derived TYLCV resistance. More... »

PAGES

1152

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/1471-2164-15-1152

    DOI

    http://dx.doi.org/10.1186/1471-2164-15-1152

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1004622314

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/25526885


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