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Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice
Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits durin...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Pub. Group
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4214417/ https://www.ncbi.nlm.nih.gov/pubmed/25295980 http://dx.doi.org/10.1038/ncomms6087 |
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author | Yang, Wanneng Guo, Zilong Huang, Chenglong Duan, Lingfeng Chen, Guoxing Jiang, Ni Fang, Wei Feng, Hui Xie, Weibo Lian, Xingming Wang, Gongwei Luo, Qingming Zhang, Qifa Liu, Qian Xiong, Lizhong |
author_facet | Yang, Wanneng Guo, Zilong Huang, Chenglong Duan, Lingfeng Chen, Guoxing Jiang, Ni Fang, Wei Feng, Hui Xie, Weibo Lian, Xingming Wang, Gongwei Luo, Qingming Zhang, Qifa Liu, Qian Xiong, Lizhong |
author_sort | Yang, Wanneng |
collection | PubMed |
description | Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits. |
format | Online Article Text |
id | pubmed-4214417 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Nature Pub. Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-42144172014-11-13 Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice Yang, Wanneng Guo, Zilong Huang, Chenglong Duan, Lingfeng Chen, Guoxing Jiang, Ni Fang, Wei Feng, Hui Xie, Weibo Lian, Xingming Wang, Gongwei Luo, Qingming Zhang, Qifa Liu, Qian Xiong, Lizhong Nat Commun Article Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits. Nature Pub. Group 2014-10-08 /pmc/articles/PMC4214417/ /pubmed/25295980 http://dx.doi.org/10.1038/ncomms6087 Text en Copyright © 2014, 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 Yang, Wanneng Guo, Zilong Huang, Chenglong Duan, Lingfeng Chen, Guoxing Jiang, Ni Fang, Wei Feng, Hui Xie, Weibo Lian, Xingming Wang, Gongwei Luo, Qingming Zhang, Qifa Liu, Qian Xiong, Lizhong Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice |
title | Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice |
title_full | Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice |
title_fullStr | Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice |
title_full_unstemmed | Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice |
title_short | Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice |
title_sort | combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4214417/ https://www.ncbi.nlm.nih.gov/pubmed/25295980 http://dx.doi.org/10.1038/ncomms6087 |
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