Bayesian genome-wide association study of nut traits in Japanese chestnut View Full Text


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Article Info

DATE

2018-07-19

AUTHORS

Sogo Nishio, Takeshi Hayashi, Toshiya Yamamoto, Shingo Terakami, Hiroyoshi Iwata, Atsushi Imai, Norio Takada, Hidenori Kato, Toshihiro Saito

ABSTRACT

Japanese chestnut (Castanea crenata Sieb. et Zucc.) has a long juvenile phase, so breeders have to wait many years to evaluate nut traits. Molecular markers associated with genes of interest would accelerate selection in chestnut breeding programs. We evaluated five nut traits (nut harvest date, nut weight, pericarp splitting, insect infestation, and specific gravity) in 99 Japanese chestnut cultivars and selections. A wide range of phenotypic variation was observed for each of the traits, suggesting that the collection harbored sufficient genetic diversity for breeding. A Bayesian genome-wide association study was conducted using 162 simple sequence repeat markers and 741 single nucleotide polymorphism markers. To evaluate the potential of marker-assisted selection, we examined 12 molecular markers found to be associated with nut traits: 4 for nut harvest date, 4 for nut weight, 1 for pericarp splitting, and 3 for insect infestation. The percentages of phenotypic variance explained ranged from 4.8 to 37.1%. Although insect infestation showed only medium heritability (0.672), we obtained two quantitative trait loci (QTLs) with extremely high posterior probabilities (0.93 and 1.00). Out of the 12 molecular markers, 3 of the 4 markers for nut harvest time could be validated in a breeding population. Accuracies of genomic selection were extremely high for nut harvest date (0.841) and moderate for insect infestation (0.604), suggesting that genomic selection based on Bayesian regression would reduce the cost of phenotypic evaluation of these traits and possibly others. More... »

PAGES

99

References to SciGraph publications

  • 2008-06. Linkage disequilibrium — understanding the evolutionary past and mapping the medical future in NATURE REVIEWS GENETICS
  • 2013-10-10. Castanea sativa: genotype-dependent recovery from chestnut blight in TREE GENETICS & GENOMES
  • 2011-11-21. Chestnut in FRUIT BREEDING
  • 2011-09-01. Landscape genetic structure of chestnut (Castanea sativa Mill.) in Spain in TREE GENETICS & GENOMES
  • 2006-01-10. Linkage disequilibrium in cultivated grapevine, Vitis vinifera L in THEORETICAL AND APPLIED GENETICS
  • 2014-06-03. Use of population structure and parentage analyses to elucidate the spread of native cultivars of Japanese chestnut in TREE GENETICS & GENOMES
  • 2012-11-30. A transcriptome-based genetic map of Chinese chestnut (Castanea mollissima) and identification of regions of segmental homology with peach (Prunus persica) in TREE GENETICS & GENOMES
  • 2009-10-21. Linkage disequilibrium in wild French grapevine, Vitis vinifera L. subsp. silvestris in HEREDITY
  • 2013-01-31. A Bayesian method and its variational approximation for prediction of genomic breeding values in multiple traits in BMC BIOINFORMATICS
  • 2008-10-29. Role of genomics in the potential restoration of the American chestnut in TREE GENETICS & GENOMES
  • 2016-06-14. Estimation of loss of genetic diversity in modern Japanese cultivars by comparison of diverse genetic resources in Asian pear (Pyrus spp.) in BMC GENOMIC DATA
  • 2011-09-02. Towards genomic selection in apple (Malus ×domestica Borkh.) breeding programmes: Prospects, challenges and strategies in TREE GENETICS & GENOMES
  • 2010-01-22. EM algorithm for Bayesian estimation of genomic breeding values in BMC GENOMIC DATA
  • 2016-05-21. Association Mapping in Turkish Olive Cultivars Revealed Significant Markers Related to Some Important Agronomic Traits in BIOCHEMICAL GENETICS
  • 2014-04-30. Accuracy of genomic selection models in a large population of open-pollinated families in white spruce in HEREDITY
  • 2010-07-20. Genetic variation, population structure and linkage disequilibrium in peach commercial varieties in BMC GENOMIC DATA
  • 2012-03-16. Genetic diversity, linkage disequilibrium, and association mapping analyses of peach (Prunus persica) landraces in China in TREE GENETICS & GENOMES
  • 2010-01-27. A variational Bayes algorithm for fast and accurate multiple locus genome-wide association analysis in BMC BIOINFORMATICS
  • 2012-11-08. A physical map of the Chinese chestnut (Castanea mollissima) genome and its integration with the genetic map in TREE GENETICS & GENOMES
  • 2009-11-01. Phenotypic diversity and relationships of fruit quality traits in peach and nectarine [Prunus persica (L.) Batsch] breeding progenies in EUPHYTICA
  • 2013-01-12. Mapping and pedigree analysis of the gene that controls the easy peel pellicle trait in Japanese chestnut (Castanea crenata Sieb. et Zucc.) in TREE GENETICS & GENOMES
  • 2015-01-24. Current applications, challenges, and perspectives of marker-assisted seedling selection in Rosaceae tree fruit breeding in TREE GENETICS & GENOMES
  • 2013-04-16. Genetic and morphological characterization of chestnut (Castanea sativa Mill.) germplasm in Piedmont (north-western Italy) in TREE GENETICS & GENOMES
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    29 schema:description Japanese chestnut (Castanea crenata Sieb. et Zucc.) has a long juvenile phase, so breeders have to wait many years to evaluate nut traits. Molecular markers associated with genes of interest would accelerate selection in chestnut breeding programs. We evaluated five nut traits (nut harvest date, nut weight, pericarp splitting, insect infestation, and specific gravity) in 99 Japanese chestnut cultivars and selections. A wide range of phenotypic variation was observed for each of the traits, suggesting that the collection harbored sufficient genetic diversity for breeding. A Bayesian genome-wide association study was conducted using 162 simple sequence repeat markers and 741 single nucleotide polymorphism markers. To evaluate the potential of marker-assisted selection, we examined 12 molecular markers found to be associated with nut traits: 4 for nut harvest date, 4 for nut weight, 1 for pericarp splitting, and 3 for insect infestation. The percentages of phenotypic variance explained ranged from 4.8 to 37.1%. Although insect infestation showed only medium heritability (0.672), we obtained two quantitative trait loci (QTLs) with extremely high posterior probabilities (0.93 and 1.00). Out of the 12 molecular markers, 3 of the 4 markers for nut harvest time could be validated in a breeding population. Accuracies of genomic selection were extremely high for nut harvest date (0.841) and moderate for insect infestation (0.604), suggesting that genomic selection based on Bayesian regression would reduce the cost of phenotypic evaluation of these traits and possibly others.
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