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Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development
Most phenotypic variation present in natural populations is under polygenic control, largely determined by genetic variation at quantitative trait loci (QTLs). These genetic loci frequently interact with the environment, development, and each other, yet the importance of these interactions on the un...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2565841/ https://www.ncbi.nlm.nih.gov/pubmed/18949035 http://dx.doi.org/10.1371/journal.pgen.1000234 |
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author | Wentzell, Adam M. Boeye, Ian Zhang, Zhiyong Kliebenstein, Daniel J. |
author_facet | Wentzell, Adam M. Boeye, Ian Zhang, Zhiyong Kliebenstein, Daniel J. |
author_sort | Wentzell, Adam M. |
collection | PubMed |
description | Most phenotypic variation present in natural populations is under polygenic control, largely determined by genetic variation at quantitative trait loci (QTLs). These genetic loci frequently interact with the environment, development, and each other, yet the importance of these interactions on the underlying genetic architecture of quantitative traits is not well characterized. To better study how epistasis and development may influence quantitative traits, we studied genetic variation in Arabidopsis glucosinolate activation using the moderately sized Bayreuth×Shahdara recombinant inbred population, in terms of number of lines. We identified QTLs for glucosinolate activation at three different developmental stages. Numerous QTLs showed developmental dependency, as well as a large epistatic network, centered on the previously cloned large-effect glucosinolate activation QTL, ESP. Analysis of Heterogeneous Inbred Families validated seven loci and all of the QTL×DPG (days post-germination) interactions tested, but was complicated by the extensive epistasis. A comparison of transcript accumulation data within 211 of these RILs showed an extensive overlap of gene expression QTLs for structural specifiers and their homologs with the identified glucosinolate activation loci. Finally, we were able to show that two of the QTLs are the result of whole-genome duplications of a glucosinolate activation gene cluster. These data reveal complex age-dependent regulation of structural outcomes and suggest that transcriptional regulation is associated with a significant portion of the underlying ontogenic variation and epistatic interactions in glucosinolate activation. |
format | Text |
id | pubmed-2565841 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-25658412008-10-24 Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development Wentzell, Adam M. Boeye, Ian Zhang, Zhiyong Kliebenstein, Daniel J. PLoS Genet Research Article Most phenotypic variation present in natural populations is under polygenic control, largely determined by genetic variation at quantitative trait loci (QTLs). These genetic loci frequently interact with the environment, development, and each other, yet the importance of these interactions on the underlying genetic architecture of quantitative traits is not well characterized. To better study how epistasis and development may influence quantitative traits, we studied genetic variation in Arabidopsis glucosinolate activation using the moderately sized Bayreuth×Shahdara recombinant inbred population, in terms of number of lines. We identified QTLs for glucosinolate activation at three different developmental stages. Numerous QTLs showed developmental dependency, as well as a large epistatic network, centered on the previously cloned large-effect glucosinolate activation QTL, ESP. Analysis of Heterogeneous Inbred Families validated seven loci and all of the QTL×DPG (days post-germination) interactions tested, but was complicated by the extensive epistasis. A comparison of transcript accumulation data within 211 of these RILs showed an extensive overlap of gene expression QTLs for structural specifiers and their homologs with the identified glucosinolate activation loci. Finally, we were able to show that two of the QTLs are the result of whole-genome duplications of a glucosinolate activation gene cluster. These data reveal complex age-dependent regulation of structural outcomes and suggest that transcriptional regulation is associated with a significant portion of the underlying ontogenic variation and epistatic interactions in glucosinolate activation. Public Library of Science 2008-10-24 /pmc/articles/PMC2565841/ /pubmed/18949035 http://dx.doi.org/10.1371/journal.pgen.1000234 Text en Wentzell et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Wentzell, Adam M. Boeye, Ian Zhang, Zhiyong Kliebenstein, Daniel J. Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development |
title | Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development |
title_full | Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development |
title_fullStr | Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development |
title_full_unstemmed | Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development |
title_short | Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development |
title_sort | genetic networks controlling structural outcome of glucosinolate activation across development |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2565841/ https://www.ncbi.nlm.nih.gov/pubmed/18949035 http://dx.doi.org/10.1371/journal.pgen.1000234 |
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