Cargando…

Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters

BACKGROUND: Grain size is one of the key factors determining yield and quality in rice. A large number of genes are involved in the regulation of grain size parameters such as grain length and grain width. Different alleles of these genes have different impacts on the grain size traits under their c...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Chan-Mi, Park, Jonghwa, Kim, Backki, Seo, Jeonghwan, Lee, Gileung, Jang, Su, Koh, Hee-Jong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4627975/
https://www.ncbi.nlm.nih.gov/pubmed/26519289
http://dx.doi.org/10.1186/s12284-015-0066-1
_version_ 1782398356124860416
author Lee, Chan-Mi
Park, Jonghwa
Kim, Backki
Seo, Jeonghwan
Lee, Gileung
Jang, Su
Koh, Hee-Jong
author_facet Lee, Chan-Mi
Park, Jonghwa
Kim, Backki
Seo, Jeonghwan
Lee, Gileung
Jang, Su
Koh, Hee-Jong
author_sort Lee, Chan-Mi
collection PubMed
description BACKGROUND: Grain size is one of the key factors determining yield and quality in rice. A large number of genes are involved in the regulation of grain size parameters such as grain length and grain width. Different alleles of these genes have different impacts on the grain size traits under their control. However, the combined influence of multiple alleles of different genes on grain size remains to be investigated. Six key genes known to influence grain size were investigated in this study: GS3, GS5, GS6, GW2, qSW5/GW5, and GW8/OsSPL16. Allele and grain measurement data were used to develop a regression equation model that can be used for molecular breeding of rice with desired grain characteristics. RESULTS: A total of 215 diverse rice germplasms, which originated from or were developed in 28 rice-consuming countries, were used in this study. Genotyping analysis demonstrated that a relatively small number of allele combinations were preserved in the diverse population and that these allele combinations were significantly associated with differences in grain size. Furthermore, in several cases, variation at a single gene was sufficient to influence grain size, even when the alleles of other genes remained constant. The data were used to develop a regression equation model for prediction of rice grain size, and this was tested using data from a further 34 germplasms. The model was significantly correlated with three of the four grain size-related traits examined in this study. CONCLUSION: Rice grain size is strongly influenced by specific combinations of alleles from six different genes. A regression equation model developed from allele and grain measurement data can be used in rice breeding programs for the development of new rice varieties with desired grain size and shape. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12284-015-0066-1) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4627975
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Springer US
record_format MEDLINE/PubMed
spelling pubmed-46279752015-11-05 Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters Lee, Chan-Mi Park, Jonghwa Kim, Backki Seo, Jeonghwan Lee, Gileung Jang, Su Koh, Hee-Jong Rice (N Y) Original Article BACKGROUND: Grain size is one of the key factors determining yield and quality in rice. A large number of genes are involved in the regulation of grain size parameters such as grain length and grain width. Different alleles of these genes have different impacts on the grain size traits under their control. However, the combined influence of multiple alleles of different genes on grain size remains to be investigated. Six key genes known to influence grain size were investigated in this study: GS3, GS5, GS6, GW2, qSW5/GW5, and GW8/OsSPL16. Allele and grain measurement data were used to develop a regression equation model that can be used for molecular breeding of rice with desired grain characteristics. RESULTS: A total of 215 diverse rice germplasms, which originated from or were developed in 28 rice-consuming countries, were used in this study. Genotyping analysis demonstrated that a relatively small number of allele combinations were preserved in the diverse population and that these allele combinations were significantly associated with differences in grain size. Furthermore, in several cases, variation at a single gene was sufficient to influence grain size, even when the alleles of other genes remained constant. The data were used to develop a regression equation model for prediction of rice grain size, and this was tested using data from a further 34 germplasms. The model was significantly correlated with three of the four grain size-related traits examined in this study. CONCLUSION: Rice grain size is strongly influenced by specific combinations of alleles from six different genes. A regression equation model developed from allele and grain measurement data can be used in rice breeding programs for the development of new rice varieties with desired grain size and shape. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12284-015-0066-1) contains supplementary material, which is available to authorized users. Springer US 2015-10-30 /pmc/articles/PMC4627975/ /pubmed/26519289 http://dx.doi.org/10.1186/s12284-015-0066-1 Text en © Lee et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Lee, Chan-Mi
Park, Jonghwa
Kim, Backki
Seo, Jeonghwan
Lee, Gileung
Jang, Su
Koh, Hee-Jong
Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters
title Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters
title_full Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters
title_fullStr Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters
title_full_unstemmed Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters
title_short Influence of Multi-Gene Allele Combinations on Grain Size of Rice and Development of a Regression Equation Model to Predict Grain Parameters
title_sort influence of multi-gene allele combinations on grain size of rice and development of a regression equation model to predict grain parameters
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4627975/
https://www.ncbi.nlm.nih.gov/pubmed/26519289
http://dx.doi.org/10.1186/s12284-015-0066-1
work_keys_str_mv AT leechanmi influenceofmultigeneallelecombinationsongrainsizeofriceanddevelopmentofaregressionequationmodeltopredictgrainparameters
AT parkjonghwa influenceofmultigeneallelecombinationsongrainsizeofriceanddevelopmentofaregressionequationmodeltopredictgrainparameters
AT kimbackki influenceofmultigeneallelecombinationsongrainsizeofriceanddevelopmentofaregressionequationmodeltopredictgrainparameters
AT seojeonghwan influenceofmultigeneallelecombinationsongrainsizeofriceanddevelopmentofaregressionequationmodeltopredictgrainparameters
AT leegileung influenceofmultigeneallelecombinationsongrainsizeofriceanddevelopmentofaregressionequationmodeltopredictgrainparameters
AT jangsu influenceofmultigeneallelecombinationsongrainsizeofriceanddevelopmentofaregressionequationmodeltopredictgrainparameters
AT kohheejong influenceofmultigeneallelecombinationsongrainsizeofriceanddevelopmentofaregressionequationmodeltopredictgrainparameters