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The development and use of a molecular model for soybean maturity groups

BACKGROUND: Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiat...

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Autores principales: Langewisch, Tiffany, Lenis, Julian, Jiang, Guo-Liang, Wang, Dechun, Pantalone, Vince, Bilyeu, Kristin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5450301/
https://www.ncbi.nlm.nih.gov/pubmed/28558691
http://dx.doi.org/10.1186/s12870-017-1040-4
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author Langewisch, Tiffany
Lenis, Julian
Jiang, Guo-Liang
Wang, Dechun
Pantalone, Vince
Bilyeu, Kristin
author_facet Langewisch, Tiffany
Lenis, Julian
Jiang, Guo-Liang
Wang, Dechun
Pantalone, Vince
Bilyeu, Kristin
author_sort Langewisch, Tiffany
collection PubMed
description BACKGROUND: Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiated and reproductive development proceeds. Therefore, soybean adaptation has been attributed to genetic changes and natural or artificial selection to optimize plant development in specific, narrow latitudinal ranges. In North America, these regions have been classified into twelve maturity groups (MG), with lower MG being shorter season than higher MG. Growing soybean lines not adapted to a particular environment typically results in poor growth and significant yield reductions. The objective of this study was to develop a molecular model for soybean maturity based on the alleles underlying the major maturity loci: E1, E2, and E3. RESULTS: We determined the allelic variation and diversity of the E maturity genes in a large collection of soybean landraces, North American ancestors, Chinese cultivars, North American cultivars or expired Plant Variety Protection lines, and private-company lines. The E gene status of accessions in the USDA Soybean Germplasm Collection with SoySNP50K Beadchip data was also predicted. We determined the E allelic combinations needed to adapt soybean to different MGs in the United States (US) and discovered a strong signal of selection for E genotypes released in North America, particularly the US and Canada. CONCLUSIONS: The E gene maturity model proposed will enable plant breeders to more effectively transfer traits into different MGs and increase the overall efficiency of soybean breeding in the US and Canada. The powerful yet simple selection strategy for increasing soybean breeding efficiency can be used alone or to directly enhance genomic prediction/selection schemes. The results also revealed previously unrecognized aspects of artificial selection in soybean imposed by soybean breeders based on geography that highlights the need for plant breeding that is optimized for specific environments. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12870-017-1040-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-54503012017-06-01 The development and use of a molecular model for soybean maturity groups Langewisch, Tiffany Lenis, Julian Jiang, Guo-Liang Wang, Dechun Pantalone, Vince Bilyeu, Kristin BMC Plant Biol Research Article BACKGROUND: Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiated and reproductive development proceeds. Therefore, soybean adaptation has been attributed to genetic changes and natural or artificial selection to optimize plant development in specific, narrow latitudinal ranges. In North America, these regions have been classified into twelve maturity groups (MG), with lower MG being shorter season than higher MG. Growing soybean lines not adapted to a particular environment typically results in poor growth and significant yield reductions. The objective of this study was to develop a molecular model for soybean maturity based on the alleles underlying the major maturity loci: E1, E2, and E3. RESULTS: We determined the allelic variation and diversity of the E maturity genes in a large collection of soybean landraces, North American ancestors, Chinese cultivars, North American cultivars or expired Plant Variety Protection lines, and private-company lines. The E gene status of accessions in the USDA Soybean Germplasm Collection with SoySNP50K Beadchip data was also predicted. We determined the E allelic combinations needed to adapt soybean to different MGs in the United States (US) and discovered a strong signal of selection for E genotypes released in North America, particularly the US and Canada. CONCLUSIONS: The E gene maturity model proposed will enable plant breeders to more effectively transfer traits into different MGs and increase the overall efficiency of soybean breeding in the US and Canada. The powerful yet simple selection strategy for increasing soybean breeding efficiency can be used alone or to directly enhance genomic prediction/selection schemes. The results also revealed previously unrecognized aspects of artificial selection in soybean imposed by soybean breeders based on geography that highlights the need for plant breeding that is optimized for specific environments. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12870-017-1040-4) contains supplementary material, which is available to authorized users. BioMed Central 2017-05-30 /pmc/articles/PMC5450301/ /pubmed/28558691 http://dx.doi.org/10.1186/s12870-017-1040-4 Text en © The Author(s). 2017 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Langewisch, Tiffany
Lenis, Julian
Jiang, Guo-Liang
Wang, Dechun
Pantalone, Vince
Bilyeu, Kristin
The development and use of a molecular model for soybean maturity groups
title The development and use of a molecular model for soybean maturity groups
title_full The development and use of a molecular model for soybean maturity groups
title_fullStr The development and use of a molecular model for soybean maturity groups
title_full_unstemmed The development and use of a molecular model for soybean maturity groups
title_short The development and use of a molecular model for soybean maturity groups
title_sort development and use of a molecular model for soybean maturity groups
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5450301/
https://www.ncbi.nlm.nih.gov/pubmed/28558691
http://dx.doi.org/10.1186/s12870-017-1040-4
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