2012 journal article

Association genetics of the loblolly pine (Pinus taeda, Pinaceae) metabolome

NEW PHYTOLOGIST, 193(4), 890–902.

By: A. Eckert *, J. Wegrzyn *, W. Cumbie n, B. Goldfarb n, D. Huber *, V. Tolstikov *, O. Fiehn *, D. Neale *

author keywords: association genetics; forest trees; loblolly pine (Pinus taeda); metabolome; natural selection; single nucleotide polymorphisms (SNPs)
MeSH headings : Bayes Theorem; Gene Frequency; Genetic Association Studies; Genetics, Population; Metabolome; Models, Genetic; Pinus taeda / genetics; Pinus taeda / metabolism; Polymorphism, Single Nucleotide; Southeastern United States
TL;DR: Standard association genetic methods are used to correlate 3563 single nucleotide polymorphisms (SNPs) to concentrations of 292 metabolites measured in a single loblolly pine (Pinus taeda) association population, highlighting the importance of multi-SNP models to association mapping and the implications for association mapping in forest trees. (via Semantic Scholar)
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15. Life on Land (Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018

The metabolome of a plant comprises all small molecule metabolites, which are produced during cellular processes. The genetic basis for metabolites in nonmodel plants is unknown, despite frequently observed correlations between metabolite concentrations and stress responses. A quantitative genetic analysis of metabolites in a nonmodel plant species is thus warranted. Here, we use standard association genetic methods to correlate 3563 single nucleotide polymorphisms (SNPs) to concentrations of 292 metabolites measured in a single loblolly pine (Pinus taeda) association population. A total of 28 single locus associations were detected, representing 24 and 20 unique SNPs and metabolites, respectively. Multilocus Bayesian mixed linear models identified 2998 additional associations for a total of 1617 unique SNPs associated to 255 metabolites. These SNPs explained sizeable fractions of metabolite heritabilities when considered jointly (56.6% on average) and had lower minor allele frequencies and magnitudes of population structure as compared with random SNPs. Modest sets of SNPs (n = 1-23) explained sizeable portions of genetic effects for many metabolites, thus highlighting the importance of multi-SNP models to association mapping, and exhibited patterns of polymorphism consistent with being linked to targets of natural selection. The implications for association mapping in forest trees are discussed.