Open access resources for genome-wide association mapping in rice

被引：0
作者：
Susan R. McCouch
Mark H. Wright
Chih-Wei Tung
Lyza G. Maron
Kenneth L. McNally
Melissa Fitzgerald
Namrata Singh
Genevieve DeClerck
Francisco Agosto-Perez
Pavel Korniliev
Anthony J. Greenberg
Ma. Elizabeth B. Naredo
Sheila Mae Q. Mercado
Sandra E. Harrington
Yuxin Shi
Darcy A. Branchini
Paula R. Kuser-Falcão
Hei Leung
Kowaru Ebana
Masahiro Yano
Georgia Eizenga
Anna McClung
Jason Mezey
机构：
[1] School of Integrative Plant Sciences,Department of Biological Statistics and Computational Biology
[2] Plant Breeding and Genetics section,undefined
[3] Cornell University,undefined
[4] Cornell University,undefined
[5] International Rice Research Institute,undefined
[6] School of Food Science,undefined
[7] University of Queensland,undefined
[8] Transnational Learning Center,undefined
[9] Cornell University,undefined
[10] National Institute of Agrobiological Sciences,undefined
[11] USDA–ARS Dale Bumpers National Rice Research Center,undefined
[12] Present address: Department of Genetics,undefined
[13] Stanford School of Medicine,undefined
[14] Stanford,undefined
[15] California 94305,undefined
[16] USA,undefined
[17] Present address: Department of Agronomy,undefined
[18] National Taiwan University,undefined
[19] 106 Taipei,undefined
[20] Taiwan,undefined
[21] Present address: Mann Library,undefined
[22] Cornell University,undefined
[23] Ithaca,undefined
[24] New York 14850,undefined
[25] USA,undefined
[26] Present address: Embrapa Agriculture Informatics,undefined
[27] 13083-886 Campinas,undefined
[28] Brazil.,undefined
来源：
Nature Communications | / 7卷
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摘要：
Increasing food production is essential to meet the demands of a growing human population, with its rising income levels and nutritional expectations. To address the demand, plant breeders seek new sources of genetic variation to enhance the productivity, sustainability and resilience of crop varieties. Here we launch a high-resolution, open-access research platform to facilitate genome-wide association mapping in rice, a staple food crop. The platform provides an immortal collection of diverse germplasm, a high-density single-nucleotide polymorphism data set tailored for gene discovery, well-documented analytical strategies, and a suite of bioinformatics resources to facilitate biological interpretation. Using grain length, we demonstrate the power and resolution of our new high-density rice array, the accompanying genotypic data set, and an expanded diversity panel for detecting major and minor effect QTLs and subpopulation-specific alleles, with immediate implications for rice improvement.
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