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Development of a 10,000 Locus Genetic Map of the Sunflower Genome Based on Multiple Crosses

Genetic linkage maps have the potential to facilitate the genetic dissection of complex traits and comparative analyses of genome structure, as well as molecular breeding efforts in species of agronomic importance. Until recently, the majority of such maps was based on relatively low-throughput mark...

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Detalles Bibliográficos
Autores principales: Bowers, John E., Bachlava, Eleni, Brunick, Robert L., Rieseberg, Loren H., Knapp, Steven J., Burke, John M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Genetics Society of America 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3385978/
https://www.ncbi.nlm.nih.gov/pubmed/22870395
http://dx.doi.org/10.1534/g3.112.002659
Descripción
Sumario:Genetic linkage maps have the potential to facilitate the genetic dissection of complex traits and comparative analyses of genome structure, as well as molecular breeding efforts in species of agronomic importance. Until recently, the majority of such maps was based on relatively low-throughput marker technologies, which limited marker density across the genome. The availability of high-throughput genotyping technologies has, however, made possible the efficient development of high-density genetic maps. Here, we describe the analysis and integration of genotypic data from four sunflower (Helianthus annuus L.) mapping populations to produce a consensus linkage map of the sunflower genome. Although the individual maps (which contained 3500–5500 loci each) were highly colinear, we observed localized variation in recombination rates in several genomic regions. We also observed several gaps up to 26 cM in length that completely lacked mappable markers in individual crosses, presumably due to regions of identity by descent in the mapping parents. Because these regions differed by cross, the consensus map of 10,080 loci contained no such gaps, clearly illustrating the value of simultaneously analyzing multiple mapping populations.