Molecular evaluation of genetic diversity and association studies in rice (Oryza sativa L.) View Full Text


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Article Info

DATE

2012-04-13

AUTHORS

C. VANNIARAJAN, K. K. VINOD, ANDY PEREIRA

ABSTRACT

In the present study, we tested rice genotypes that included un(der)exploited landraces of Tamil Nadu along with indica and japonica test cultivars to ascertain their genetic diversity structure. Highly polymorphic microsatellite markers were used for generating marker segregation data. A novel measure, allele discrimination index, was used to determine subpopulation differentiation power of each marker. Phenotypic data were collected for yield and component traits. Pattern of molecular differentiation separated indica and japonica genotypes; indica genotypes had two subpopulations within. Landraces were found to have indica genome, but formed a separate subgroup with low linkage disequilibrium. The landraces further separated into distinct group in both hierarchical clustering analysis using neighbour-joining method as well as in the model based population structure analysis. Japonica and the remaining indica cultivars formed two other distinct groups. Linkage disequilibrium observed in the whole population was considerably reduced in subpopulations. Low linkage disequilibrium of landforms suggests their narrow adaptation in local geographical niche. Many population specific alleles could be identified particularly for japonica cultivars and landraces. Association analysis revealed nine marker–trait associations with three agronomic traits, of which 67% were previously reported. Although the testing landraces together with known cultivars had permitted genome-wide association mapping, the experiment offers scope to study more landraces collected from the entire geographical region for drawing more reliable information. More... »

PAGES

9-19

References to SciGraph publications

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  • 1985-08. Variation in some agronomically important characters in a germplasm collection of beet (Beta vulgaris L.) in EUPHYTICA
  • 2010-10-24. Genome-wide association studies of 14 agronomic traits in rice landraces in NATURE GENETICS
  • 2008-12-09. Trait identification and QTL validation for reproductive stage drought resistance in rice using selective genotyping of near flowering RILs in EUPHYTICA
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s12041-012-0146-6

    DOI

    http://dx.doi.org/10.1007/s12041-012-0146-6

    DIMENSIONS

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/22546822


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    43 schema:description In the present study, we tested rice genotypes that included un(der)exploited landraces of Tamil Nadu along with indica and japonica test cultivars to ascertain their genetic diversity structure. Highly polymorphic microsatellite markers were used for generating marker segregation data. A novel measure, allele discrimination index, was used to determine subpopulation differentiation power of each marker. Phenotypic data were collected for yield and component traits. Pattern of molecular differentiation separated indica and japonica genotypes; indica genotypes had two subpopulations within. Landraces were found to have indica genome, but formed a separate subgroup with low linkage disequilibrium. The landraces further separated into distinct group in both hierarchical clustering analysis using neighbour-joining method as well as in the model based population structure analysis. Japonica and the remaining indica cultivars formed two other distinct groups. Linkage disequilibrium observed in the whole population was considerably reduced in subpopulations. Low linkage disequilibrium of landforms suggests their narrow adaptation in local geographical niche. Many population specific alleles could be identified particularly for japonica cultivars and landraces. Association analysis revealed nine marker–trait associations with three agronomic traits, of which 67% were previously reported. Although the testing landraces together with known cultivars had permitted genome-wide association mapping, the experiment offers scope to study more landraces collected from the entire geographical region for drawing more reliable information.
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