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Open access resources for genome-wide association mapping in rice

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 variet...

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Autores principales: 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-Falcão, Paula R., Leung, Hei, Ebana, Kowaru, Yano, Masahiro, Eizenga, Georgia, McClung, Anna, Mezey, Jason
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4742900/
https://www.ncbi.nlm.nih.gov/pubmed/26842267
http://dx.doi.org/10.1038/ncomms10532
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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-Falcão, Paula R.
Leung, Hei
Ebana, Kowaru
Yano, Masahiro
Eizenga, Georgia
McClung, Anna
Mezey, Jason
author_facet 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-Falcão, Paula R.
Leung, Hei
Ebana, Kowaru
Yano, Masahiro
Eizenga, Georgia
McClung, Anna
Mezey, Jason
author_sort McCouch, Susan R.
collection PubMed
description 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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spelling pubmed-47429002016-03-04 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-Falcão, Paula R. Leung, Hei Ebana, Kowaru Yano, Masahiro Eizenga, Georgia McClung, Anna Mezey, Jason Nat Commun Article 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. Nature Publishing Group 2016-02-04 /pmc/articles/PMC4742900/ /pubmed/26842267 http://dx.doi.org/10.1038/ncomms10532 Text en Copyright © 2016, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
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-Falcão, Paula R.
Leung, Hei
Ebana, Kowaru
Yano, Masahiro
Eizenga, Georgia
McClung, Anna
Mezey, Jason
Open access resources for genome-wide association mapping in rice
title Open access resources for genome-wide association mapping in rice
title_full Open access resources for genome-wide association mapping in rice
title_fullStr Open access resources for genome-wide association mapping in rice
title_full_unstemmed Open access resources for genome-wide association mapping in rice
title_short Open access resources for genome-wide association mapping in rice
title_sort open access resources for genome-wide association mapping in rice
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4742900/
https://www.ncbi.nlm.nih.gov/pubmed/26842267
http://dx.doi.org/10.1038/ncomms10532
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