Map-based molecular diversity, linkage disequilibrium and association mapping of fruit traits in melon View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-04

AUTHORS

Yan Tomason, Padma Nimmakayala, Amnon Levi, Umesh K. Reddy

ABSTRACT

Melon has tremendous fruit diversity, the product of complex interactions of consumer preferences in different countries and a wide range of agro-climatic zones. Understanding footprints of divergence underlying formation of various morphotypes is important for developing sustainable and high-quality melons. Basic understanding of population structure and linkage disequilibrium (LD) is limited in melon and has lagged behind other crops. Characterization of population structure and LD are essential for carrying out association mapping of quantitative trait loci (QTL) underlying various complex traits. Mapped single-locus microsatellite markers are known to be very valuable for resolving the population structure and 268 such markers were used in the current study to resolve population structure and LD pattern using 87 accessions of melons belonging to Eastern European, Euro-North American and Asian types. A mixed linear model was implemented to detect QTL for various fruit traits. Various levels of QTL with high to moderate stringency were detected for fruit shape, fruit weight, soluble solids, and rind pressure and a majority of them was found to be in agreement with the previously published data, indicating that association mapping can be very useful for melon molecular breeding. Minor discrepancies in the position, strength and the variation explained by the QTL present between the methods of association and recombinant mapping approaches can be bridged if more melon groups and larger sets of accessions are involved in future studies, combined with high-throughput marker panels. More... »

PAGES

829-841

References to SciGraph publications

  • 2010-08. Association mapping of leaf rust response in durum wheat in MOLECULAR BREEDING
  • 2002-06. Genetic variation and phylogenetic relationships in East and South Asian melons, Cucumis melo L., based on the analysis of five isozymes in EUPHYTICA
  • 2012-09. Comparison of biometrical approaches for QTL detection in multiple segregating families in THEORETICAL AND APPLIED GENETICS
  • 2003-09-01. Power of genome-wide linkage disequilibrium testing by using microsatellite markers in JOURNAL OF HUMAN GENETICS
  • 1999-09. Intraspecific classification of melons (Cucumis melo L.) in view of their phenotypic and molecular variation in PLANT SYSTEMATICS AND EVOLUTION
  • 2010-08. Genetic diversity and population structure of a diverse set of rice germplasm for association mapping in THEORETICAL AND APPLIED GENETICS
  • 1991-08. Estimation of nuclear DNA content of plants by flow cytometry in PLANT MOLECULAR BIOLOGY REPORTER
  • 2004-02. Identification of quantitative trait loci involved in fruit quality traits in melon (Cucumis melo L.) in THEORETICAL AND APPLIED GENETICS
  • 1986-06. A Quasi-equilibrium theory of the distribution of rare alleles in a subdivided population in HEREDITY
  • 2007. Applications of Linkage Disequilibrium and Association Mapping in Crop Plants in GENOMICS-ASSISTED CROP IMPROVEMENT
  • 2010-12. MHC allele frequency distributions under parasite-driven selection: A simulation model in BMC EVOLUTIONARY BIOLOGY
  • 2009-12. A set of EST-SNPs for map saturation and cultivar identification in melon in BMC PLANT BIOLOGY
  • 2002-10. The origin and genetic affinities of wild populations of melon (Cucumis melo, Cucurbitaceae) in North America in PLANT SYSTEMATICS AND EVOLUTION
  • 2011-12. A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon (Cucumis meloL.) in BMC PLANT BIOLOGY
  • 2012-08. Genetic structure and linkage disequilibrium pattern of a rapeseed (Brassica napus L.) association mapping panel revealed by microsatellites in THEORETICAL AND APPLIED GENETICS
  • 2010-08. A genetic map of melon highly enriched with fruit quality QTLs and EST markers, including sugar and carotenoid metabolism genes in THEORETICAL AND APPLIED GENETICS
  • 2011-11. Association mapping of dynamic developmental plant height in common wheat in PLANTA
  • 2007-05. Detection of QTL for yield-related traits using recombinant inbred lines derived from exotic and elite US Western Shipping melon germplasm in THEORETICAL AND APPLIED GENETICS
  • 2010-10. Population structure and linkage disequilibrium unravelled in tetraploid potato in THEORETICAL AND APPLIED GENETICS
  • 2000-10. Comparative analysis of cultivated melon groups (Cucumis melo L.) using random amplified polymorphic DNA and simple sequence repeat markers in EUPHYTICA
  • 2007-01. Molecular characterization of South and East Asian melon, Cucumis melo L., and the origin of Group Conomon var. makuwa and var. conomon revealed by RAPD analysis in EUPHYTICA
  • 2008-10. Genetic dissection of fruit quality components in melon (Cucumis melo L.) using a RIL population derived from exotic × elite US Western Shipping germplasm in MOLECULAR BREEDING
  • 2012-12. Transcriptome sequencing for SNP discovery across Cucumis melo in BMC GENOMICS
  • 2006-12. Analysis of molecular diversity, population structure and linkage disequilibrium in a worldwide survey of cultivated barley germplasm (Hordeum vulgare L.) in BMC GENETICS
  • 2008. Melon in VEGETABLES I
  • 2011-08. Comparison of SSRs and SNPs in assessment of genetic relatedness in maize in GENETICA
  • 1985. The Statistics of Natural Selection on Animal Populations in NONE
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    http://scigraph.springernature.com/pub.10.1007/s11032-013-9837-9

    DOI

    http://dx.doi.org/10.1007/s11032-013-9837-9

    DIMENSIONS

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