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Genetic interactions matter more in less-optimal environments: a Focused Review of “Phenotype uniformity in combined-stress environments has a different genetic architecture than in single-stress treatments” (Makumburage and Stapleton, 2011)
An increase in the distribution of data points indicates the presence of genetic or environmental modifiers. Mapping of the genetic control of the spread of points, the uniformity, allows us to allocate genetic difference in point distribution to adjacent, cis effects or to independently segregating...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4127526/ https://www.ncbi.nlm.nih.gov/pubmed/25157259 http://dx.doi.org/10.3389/fpls.2014.00384 |
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author | Landers, Dustin A. Stapleton, Ann E. |
author_facet | Landers, Dustin A. Stapleton, Ann E. |
author_sort | Landers, Dustin A. |
collection | PubMed |
description | An increase in the distribution of data points indicates the presence of genetic or environmental modifiers. Mapping of the genetic control of the spread of points, the uniformity, allows us to allocate genetic difference in point distribution to adjacent, cis effects or to independently segregating, trans genetic effects. Our genetic architecture-mapping experiment elucidated the “environmental context specificity” of modifiers, the number and effect size of positive and negative alleles important for uniformity in single and combined stress, and the extent of additivity in estimated allele effects in combined stress environments. We found no alleles for low uniformity in combined stress treatments in the maize mapping population we examined. The major advances in this research area since early 2011 have been in improved methods for modeling of distributions and means and detection of important loci. Double hierarchical general linear models and, more recently, a likelihood ratio formulation have been developed to better model and estimate the genetic and environmental effects in populations. These new methods have been applied to real data sets by the method authors and we now encourage additional development of the software and wider application of the methods. We also propose that simulations of genetic regulatory network models to examine differences in uniformity and systematic exploration of models using shared simulations across communities of researchers would be constructive avenues for developing further insight into the genetic mechanisms of variation control. |
format | Online Article Text |
id | pubmed-4127526 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-41275262014-08-25 Genetic interactions matter more in less-optimal environments: a Focused Review of “Phenotype uniformity in combined-stress environments has a different genetic architecture than in single-stress treatments” (Makumburage and Stapleton, 2011) Landers, Dustin A. Stapleton, Ann E. Front Plant Sci Plant Science An increase in the distribution of data points indicates the presence of genetic or environmental modifiers. Mapping of the genetic control of the spread of points, the uniformity, allows us to allocate genetic difference in point distribution to adjacent, cis effects or to independently segregating, trans genetic effects. Our genetic architecture-mapping experiment elucidated the “environmental context specificity” of modifiers, the number and effect size of positive and negative alleles important for uniformity in single and combined stress, and the extent of additivity in estimated allele effects in combined stress environments. We found no alleles for low uniformity in combined stress treatments in the maize mapping population we examined. The major advances in this research area since early 2011 have been in improved methods for modeling of distributions and means and detection of important loci. Double hierarchical general linear models and, more recently, a likelihood ratio formulation have been developed to better model and estimate the genetic and environmental effects in populations. These new methods have been applied to real data sets by the method authors and we now encourage additional development of the software and wider application of the methods. We also propose that simulations of genetic regulatory network models to examine differences in uniformity and systematic exploration of models using shared simulations across communities of researchers would be constructive avenues for developing further insight into the genetic mechanisms of variation control. Frontiers Media S.A. 2014-08-11 /pmc/articles/PMC4127526/ /pubmed/25157259 http://dx.doi.org/10.3389/fpls.2014.00384 Text en Copyright © 2014 Landers and Stapleton. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Landers, Dustin A. Stapleton, Ann E. Genetic interactions matter more in less-optimal environments: a Focused Review of “Phenotype uniformity in combined-stress environments has a different genetic architecture than in single-stress treatments” (Makumburage and Stapleton, 2011) |
title | Genetic interactions matter more in less-optimal environments: a Focused Review of “Phenotype uniformity in combined-stress environments has a different genetic architecture than in single-stress treatments” (Makumburage and Stapleton, 2011) |
title_full | Genetic interactions matter more in less-optimal environments: a Focused Review of “Phenotype uniformity in combined-stress environments has a different genetic architecture than in single-stress treatments” (Makumburage and Stapleton, 2011) |
title_fullStr | Genetic interactions matter more in less-optimal environments: a Focused Review of “Phenotype uniformity in combined-stress environments has a different genetic architecture than in single-stress treatments” (Makumburage and Stapleton, 2011) |
title_full_unstemmed | Genetic interactions matter more in less-optimal environments: a Focused Review of “Phenotype uniformity in combined-stress environments has a different genetic architecture than in single-stress treatments” (Makumburage and Stapleton, 2011) |
title_short | Genetic interactions matter more in less-optimal environments: a Focused Review of “Phenotype uniformity in combined-stress environments has a different genetic architecture than in single-stress treatments” (Makumburage and Stapleton, 2011) |
title_sort | genetic interactions matter more in less-optimal environments: a focused review of “phenotype uniformity in combined-stress environments has a different genetic architecture than in single-stress treatments” (makumburage and stapleton, 2011) |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4127526/ https://www.ncbi.nlm.nih.gov/pubmed/25157259 http://dx.doi.org/10.3389/fpls.2014.00384 |
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