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Functional multi-locus QTL mapping of temporal trends in Scots pine wood traits.

ABSTRACT: Quantitative trait loci (QTL) mapping of wood properties in conifer species has focused on single time point measurements or on trait means based on heterogeneous wood samples (e.g., increment cores), thus ignoring systematic within-tree trends. In this study, functional QTL mapping was performed for a set of important wood properties in increment cores from a 17-yr-old Scots pine (Pinus sylvestris L.) full-sib family with the aim of detecting wood trait QTL for general intercepts (means) and for linear slopes by increasing cambial age. Two multi-locus functional QTL analysis approaches were proposed and their performances were compared on trait datasets comprising 2 to 9 time points, 91 to 455 individual tree measurements and genotype datasets of amplified length polymorphisms (AFLP), and single nucleotide polymorphism (SNP) markers. The first method was a multilevel LASSO analysis whereby trend parameter estimation and QTL mapping were conducted consecutively; the second method was our Bayesian linear mixed model whereby trends and underlying genetic effects were estimated simultaneously. We also compared several different hypothesis testing methods under either the LASSO or the Bayesian framework to perform QTL inference. In total, five and four significant QTL were observed for the intercepts and slopes, respectively, across wood traits such as earlywood percentage, wood density, radial fiberwidth, and spiral grain angle. Four of these QTL were represented by candidate gene SNPs, thus providing promising targets for future research in QTL mapping and molecular function. Bayesian and LASSO methods both detected similar sets of QTL given datasets that comprised large numbers of individuals.

SUBMITTER: Li Z

PROVIDER: S-EPMC4267932 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Functional traits have emerged as a key to understand species responses to environmental conditions. The concerted expression of multiple traits gives rise to the phenotype of each individual, which is the one interacting with the environment and evolving. However, patterns of trait covariation and how they vary in response to environmental conditions remain poorly understood, particularly at the intraspecific scale. Here, we have measured traits at different scales and in different organs, and analysed their covariation in a large number of conspecifics distributed in two contrasting environments. We expected significant correlations among traits, not only within clusters of traits as found in global, multispecies studies, but also among clusters, with more relationships within clusters, due to genetic constraints, and among clusters due to more coordinated phenotypes than community level, multispecies studies. We surveyed 100 Pinus sylvestris trees in a Mediterranean mountainous area distributed in two contrasting elevations. We measured 13 functional traits, in three clusters (leaf, stem and whole-plant traits), and analysed their variation and coordination. We found significant coordination among traits belonging to different clusters that reveals coordinated phenotypes. However, we found fewer correlations within trait clusters than initially expected. Trait correlation structures (number, intensity and type of correlations among traits) differed among individuals at different elevations. We observed more correlations within trait clusters at low elevation compared to those at high elevation. Moreover, the higher number of correlations among different trait clusters and the lower trait variation at the higher elevation suggests that variability decreases under more stressful conditions. Altogether, our results reveal that traits at intraspecific scale are coordinated in a broad network and not only within clusters of traits but also that this trait covariation is significantly affected by environmental conditions.

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Functional multi-locus QTL mapping of temporal trends in Scots pine wood traits.

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