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https://hdl.handle.net/1959.11/52870
Title: | Marker-Based Quantitative Genetics in the Wild?: The Heritability and Genetic Correlation of Chemical Defenses in Eucalyptus |
Contributor(s): | Andrew, R L (author) ; Peakall, R (author); Wallis, I R (author); Wood, J T (author); Knight, E J (author); Foley, W J (author) |
Publication Date: | 2005-12-01 |
Open Access: | Yes |
DOI: | 10.1534/genetics.105.042952![Open Access Link](/web/OA.png) |
Handle Link: | https://hdl.handle.net/1959.11/52870 |
Abstract: | | Marker-based methods for estimating heritability and genetic correlation in the wild have attracted interest because traditional methods may be impractical or introduce bias via G × E effects, mating system variation, and sampling effects. However, they have not been widely used, especially in plants. A regression-based approach, which uses a continuous measure of genetic relatedness, promises to be particularly appropriate for use in plants with mixed-mating systems and overlapping generations. Using this method, we found significant narrow-sense heritability of foliar defense chemicals in a natural population of Eucalyptus melliodora. We also demonstrated a genetic basis for the phenotypic correlation underlying an ecological example of conditioned flavor aversion involving different biosynthetic pathways. Our results revealed that heritability estimates depend on the spatial scale of the analysis in a way that offers insight into the distribution of genetic and environmental variance. This study is the first to successfully use a marker-based method to measure quantitative genetic parameters in a tree. We suggest that this method will prove to be a useful tool in other studies and offer some recommendations for future applications of the method.
Publication Type: | Journal Article |
Source of Publication: | Genetics, 171(4), p. 1989-1998 |
Publisher: | Genetics Society of America |
Place of Publication: | United States of America |
ISSN: | 1943-2631 0016-6731 |
Fields of Research (FoR) 2020: | 310207 Statistical and quantitative genetics 310399 Ecology not elsewhere classified 310599 Genetics not elsewhere classified |
Socio-Economic Objective (SEO) 2020: | 280102 Expanding knowledge in the biological sciences |
Peer Reviewed: | Yes |
HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
Appears in Collections: | Journal Article School of Environmental and Rural Science
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