The complex genetic architecture of shoot growth natural variation in Arabidopsis thaliana
One of the main outcomes of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, inte...
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Published in | PLoS genetics Vol. 15; no. 4; p. e1007954 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Public Library of Science
22.04.2019
Public Library of Science (PLoS) |
Subjects | |
Online Access | Get full text |
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Summary: | One of the main outcomes of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, interactions with the genetic background, environment or age. Linkage or association mapping strategies will be more or less sensitive to this complexity, so that we still have an unclear picture of its extent. By combining high-throughput phenotyping under two environmental conditions with classical QTL mapping approaches in multiple Arabidopsis thaliana segregating populations as well as advanced near isogenic lines construction and survey, we have attempted to improve our understanding of quantitative phenotypic variation. Integrative traits such as those related to vegetative growth used in this work (highlighting either cumulative growth, growth rate or morphology) all showed complex and dynamic genetic architecture with respect to the segregating population and condition. The more resolutive our mapping approach, the more complexity we uncover, with several instances of QTLs visible in near isogenic lines but not detected with the initial QTL mapping, indicating that our phenotyping accuracy was less limiting than the mapping resolution with respect to the underlying genetic architecture. In an ultimate approach to resolve this complexity, we intensified our phenotyping effort to target specifically a 3Mb-region known to segregate for a major quantitative trait gene, using a series of selected lines recombined every 100kb. We discovered that at least 3 other independent QTLs had remained hidden in this region, some with trait- or condition-specific effects, or opposite allelic effects. If we were to extrapolate the figures obtained on this specific region in this particular cross to the genome- and species-scale, we would predict hundreds of causative loci of detectable phenotypic effect controlling these growth-related phenotypes. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Current address: GQE Le Moulon, INRA, Univ. Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, Gif-sur-Yvette, France Current address: Saskatoon Research and Development Centre, Agriculture and Agri-Food Canada, Saskatoon, SK, Canada Current address: Institute of Plant Breeding and Genetic Resources ELGO-DEMETER, Thermi, Thessaloniki, Greece / Department of Comparative Development and Genetics, Max Planck Institute for Plant Breeding Research, Cologne, Germany Current address: CIRAD, UMR AGAP, Montpellier, France Current address: Institute of Plant Science, Bern University, Bern, Switzerland The authors have declared that no competing interests exist. |
ISSN: | 1553-7404 1553-7390 1553-7404 |
DOI: | 10.1371/journal.pgen.1007954 |