Open access resources for genome-wide association mapping in rice

McCouch, Susan R., Wright, Mark H., Tung, Chih-Wei, Maron, Lyza G., McNally, Kenneth L., Fitzgerald, Melissa, Singh, Namrata, DeClerck, Genevieve, Agosto-Perez, Francisco, Korniliev, Pavel, Greenberg, Anthony J., Naredo, Ma. Elizabeth B., Mercado, Sheila Mae Q., Harrington, Sandra E., Shi, Yuxin, Branchini, Darcy A., Kuser-Falcao, Paula R., Leung, Hei, Ebana, Kowaru, Yano, Masahiro, Eizenga, Georgia, McClung, Anna and Mezey, Jason (2016) Open access resources for genome-wide association mapping in rice. Nature Communications, 7 1-13. doi:10.1038/ncomms10532


Author McCouch, Susan R.
Wright, Mark H.
Tung, Chih-Wei
Maron, Lyza G.
McNally, Kenneth L.
Fitzgerald, Melissa
Singh, Namrata
DeClerck, Genevieve
Agosto-Perez, Francisco
Korniliev, Pavel
Greenberg, Anthony J.
Naredo, Ma. Elizabeth B.
Mercado, Sheila Mae Q.
Harrington, Sandra E.
Shi, Yuxin
Branchini, Darcy A.
Kuser-Falcao, Paula R.
Leung, Hei
Ebana, Kowaru
Yano, Masahiro
Eizenga, Georgia
McClung, Anna
Mezey, Jason
Title Open access resources for genome-wide association mapping in rice
Journal name Nature Communications   Check publisher's open access policy
ISSN 2041-1723
Publication date 2016-02-04
Year available 2016
Sub-type Article (original research)
DOI 10.1038/ncomms10532
Open Access Status DOI
Volume 7
Start page 1
End page 13
Total pages 13
Place of publication London, United Kingdom
Publisher Nature Publishing Group
Collection year 2017
Language eng
Abstract 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.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
School of Agriculture and Food Sciences
 
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