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The Genetic Architecture Of Maize Height

Height is one of the most heritable and easily measured traits in maize (Zea mays L.). Given a pedigree or estimates of the genomic identity-by-state among related plants, height is also accurately predictable. But, mapping alleles explaining natural variation in maize height remains a formidable ch...

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Autores principales: Peiffer, Jason A., Romay, Maria C., Gore, Michael A., Flint-Garcia, Sherry A., Zhang, Zhiwu, Millard, Mark J., Gardner, Candice A. C., McMullen, Michael D., Holland, James B., Bradbury, Peter J., Buckler, Edward S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Genetics Society of America 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3982682/
https://www.ncbi.nlm.nih.gov/pubmed/24514905
http://dx.doi.org/10.1534/genetics.113.159152
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author Peiffer, Jason A.
Romay, Maria C.
Gore, Michael A.
Flint-Garcia, Sherry A.
Zhang, Zhiwu
Millard, Mark J.
Gardner, Candice A. C.
McMullen, Michael D.
Holland, James B.
Bradbury, Peter J.
Buckler, Edward S.
author_facet Peiffer, Jason A.
Romay, Maria C.
Gore, Michael A.
Flint-Garcia, Sherry A.
Zhang, Zhiwu
Millard, Mark J.
Gardner, Candice A. C.
McMullen, Michael D.
Holland, James B.
Bradbury, Peter J.
Buckler, Edward S.
author_sort Peiffer, Jason A.
collection PubMed
description Height is one of the most heritable and easily measured traits in maize (Zea mays L.). Given a pedigree or estimates of the genomic identity-by-state among related plants, height is also accurately predictable. But, mapping alleles explaining natural variation in maize height remains a formidable challenge. To address this challenge, we measured the plant height, ear height, flowering time, and node counts of plants grown in >64,500 plots across 13 environments. These plots contained >7300 inbreds representing most publically available maize inbreds in the United States and families of the maize Nested Association Mapping (NAM) panel. Joint-linkage mapping of quantitative trait loci (QTL), fine mapping in near isogenic lines (NILs), genome-wide association studies (GWAS), and genomic best linear unbiased prediction (GBLUP) were performed. The heritability of maize height was estimated to be >90%. Mapping NAM family-nested QTL revealed the largest explained 2.1 ± 0.9% of height variation. The effects of two tropical alleles at this QTL were independently validated by fine mapping in NIL families. Several significant associations found by GWAS colocalized with established height loci, including brassinosteroid-deficient dwarf1, dwarf plant1, and semi-dwarf2. GBLUP explained >80% of height variation in the panels and outperformed bootstrap aggregation of family-nested QTL models in evaluations of prediction accuracy. These results revealed maize height was under strong genetic control and had a highly polygenic genetic architecture. They also showed that multiple models of genetic architecture differing in polygenicity and effect sizes can plausibly explain a population’s variation in maize height, but they may vary in predictive efficacy.
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spelling pubmed-39826822014-04-10 The Genetic Architecture Of Maize Height Peiffer, Jason A. Romay, Maria C. Gore, Michael A. Flint-Garcia, Sherry A. Zhang, Zhiwu Millard, Mark J. Gardner, Candice A. C. McMullen, Michael D. Holland, James B. Bradbury, Peter J. Buckler, Edward S. Genetics Investigations Height is one of the most heritable and easily measured traits in maize (Zea mays L.). Given a pedigree or estimates of the genomic identity-by-state among related plants, height is also accurately predictable. But, mapping alleles explaining natural variation in maize height remains a formidable challenge. To address this challenge, we measured the plant height, ear height, flowering time, and node counts of plants grown in >64,500 plots across 13 environments. These plots contained >7300 inbreds representing most publically available maize inbreds in the United States and families of the maize Nested Association Mapping (NAM) panel. Joint-linkage mapping of quantitative trait loci (QTL), fine mapping in near isogenic lines (NILs), genome-wide association studies (GWAS), and genomic best linear unbiased prediction (GBLUP) were performed. The heritability of maize height was estimated to be >90%. Mapping NAM family-nested QTL revealed the largest explained 2.1 ± 0.9% of height variation. The effects of two tropical alleles at this QTL were independently validated by fine mapping in NIL families. Several significant associations found by GWAS colocalized with established height loci, including brassinosteroid-deficient dwarf1, dwarf plant1, and semi-dwarf2. GBLUP explained >80% of height variation in the panels and outperformed bootstrap aggregation of family-nested QTL models in evaluations of prediction accuracy. These results revealed maize height was under strong genetic control and had a highly polygenic genetic architecture. They also showed that multiple models of genetic architecture differing in polygenicity and effect sizes can plausibly explain a population’s variation in maize height, but they may vary in predictive efficacy. Genetics Society of America 2014-04 2014-02-10 /pmc/articles/PMC3982682/ /pubmed/24514905 http://dx.doi.org/10.1534/genetics.113.159152 Text en Copyright © 2014 by the Genetics Society of America Available freely online through the author-supported open access option.
spellingShingle Investigations
Peiffer, Jason A.
Romay, Maria C.
Gore, Michael A.
Flint-Garcia, Sherry A.
Zhang, Zhiwu
Millard, Mark J.
Gardner, Candice A. C.
McMullen, Michael D.
Holland, James B.
Bradbury, Peter J.
Buckler, Edward S.
The Genetic Architecture Of Maize Height
title The Genetic Architecture Of Maize Height
title_full The Genetic Architecture Of Maize Height
title_fullStr The Genetic Architecture Of Maize Height
title_full_unstemmed The Genetic Architecture Of Maize Height
title_short The Genetic Architecture Of Maize Height
title_sort genetic architecture of maize height
topic Investigations
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3982682/
https://www.ncbi.nlm.nih.gov/pubmed/24514905
http://dx.doi.org/10.1534/genetics.113.159152
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