Drought mitigation by thinning:Benefits from the stem to the stand along 15 years of experimental rainfall exclusion in a holm oak coppice

International audienc

Common garden experiments in the genomic era : new perspectives and opportunities

PdV was supported by a doctoral studentship from the French Ministère de la Recherche et de l’Enseignement Supérieur. OEG was supported by the Marine Alliance for Science and Technology for Scotland (MASTS)The study of local adaptation is rendered difficult by many evolutionary confounding phenomena (e.g. genetic drift and demographic history). When complex traits are involved in local adaptation, phenomena such as phenotypic plasticity further hamper evolutionary biologists to study the complex relationships between phenotype, genotype and environment. In this perspective paper, we suggest that the common garden experiment, specifically designed to deal with phenotypic plasticity has a clear role to play in the study of local adaptation, even (if not specifically) in the genomic era. After a quick review of some high-throughput genotyping protocols relevant in the context of a common garden, we explore how to improve common garden analyses with dense marker panel data and recent statistical methods. We then show how combining approaches from population genomics and genome-wide association studies with the settings of a common garden can yield to a very efficient, thorough and integrative study of local adaptation. Especially, evidence from genomic (e.g. genome scan) and phenotypic origins constitute independent insights into the possibility of local adaptation scenarios, and genome-wide association studies in the context of a common garden experiment allow to decipher the genetic bases of adaptive traits.PostprintPeer reviewe

AdditiveValues

Untreated file generated by the simulation model that contains the additive genetic values and phenotypic values of the simulated parental population. First column = ID; second column = additive value; third column = phenotypic valu

Data from: Partial genotyping at polymorphic markers can improve heritability estimates in sibling groups

Accurate estimates of heritability (h²) are necessary to assess adaptive responses of populations and evolution of fitness-related traits in changing environments. For plants, h² estimates generally rely on maternal progeny designs, assuming that offspring are either half-sibs or unrelated. However, plant mating systems often depart from half-sib assumptions, this can bias h² estimates. Here, we investigate how to accurately estimate h² in non-model species through the analysis of sibling designs with a moderate genotyping effort. We performed simulations to investigate how microsatellite marker information available for only a subset of offspring can improve h² estimates based on maternal progeny designs in presence of non-random mating, inbreeding in the parental population or maternal effects. We compared the basic family method, considering or not adjustments based on average relatedness coefficients, and methods based on the animal model. The animal model was used with average relatedness information, or with hybrid relatedness information: associating one-generation pedigree and family assumptions, or associating one-generation pedigree and average relatedness coefficients. Our results highlighted that methods using marker-based relatedness coefficients performed as well as pedigree-based methods in presence of non-random mating (i.e. unequal male reproductive contributions, selfing), offering promising prospects to investigate in situ heritabilities in natural populations. In presence of maternal effects, only the use of pairwise relatednesses through pedigree information improved the accuracy of h² estimates. In that case the amount of father-related offspring in the sibling design is the most critical. Overall, we showed that the method using both one-generation pedigree and average relatedness coefficients was the most robust to various ecological scenarios

Data from: Partial genotyping at polymorphic markers can improve heritability estimates in sibling groups

Accurate estimates of heritability (h²) are necessary to assess adaptive responses of populations and evolution of fitness-related traits in changing environments. For plants, h² estimates generally rely on maternal progeny designs, assuming that offspring are either half-sibs or unrelated. However, plant mating systems often depart from half-sib assumptions, this can bias h² estimates. Here, we investigate how to accurately estimate h² in non-model species through the analysis of sibling designs with a moderate genotyping effort. We performed simulations to investigate how microsatellite marker information available for only a subset of offspring can improve h² estimates based on maternal progeny designs in presence of non-random mating, inbreeding in the parental population or maternal effects. We compared the basic family method, considering or not adjustments based on average relatedness coefficients, and methods based on the animal model. The animal model was used with average relatedness information, or with hybrid relatedness information: associating one-generation pedigree and family assumptions, or associating one-generation pedigree and average relatedness coefficients. Our results highlighted that methods using marker-based relatedness coefficients performed as well as pedigree-based methods in presence of non-random mating (i.e. unequal male reproductive contributions, selfing), offering promising prospects to investigate in situ heritabilities in natural populations. In presence of maternal effects, only the use of pairwise relatednesses through pedigree information improved the accuracy of h² estimates. In that case the amount of father-related offspring in the sibling design is the most critical. Overall, we showed that the method using both one-generation pedigree and average relatedness coefficients was the most robust to various ecological scenarios

GenotypeOffspring_N4

genotyping at the 13 microsatellite markers (presented in Gauzere et al. 2013 Molecular Ecology) for a subset of offspring per family sampled from plot N

Pedigree File

the pedigree file, refering to the identity of the individual("ID"), its mother ("MotherID") and its father ("FatherID") when it has been assigne

Data from: Using partial genotyping to estimate the genetic and maternal determinants of adaptive traits in a progeny trial of Fagus sylvatica

Understanding the determinants of phenotypic variation is critical to evaluate the ability of traits to evolve in a changing environment. In trees, the genetic component of the phenotypic variance is most often estimated based on maternal progeny tests. However, the lack of knowledge about the paternal relatedness hampers the accurate estimation of additive genetic and maternal effects. Here, we investigate how different methods accounting for paternal relatedness allow the estimation of heritability and maternal determinants of adaptive traits in a natural population of Fagus sylvatica L., presenting non-random mating. Twelve potentially adaptive functional traits were measured in 60 maternal families in a nursery. We genotyped a subset of offspring and of all the potentially reproductive adults in the population at 13 microsatellite markers to infer paternal relationships and to estimate average relatedness within and between maternal families. This relatedness information was then used in family and animal models to estimate the components of phenotypic variance. All the studied traits displayed significant genetic variance and moderate heritability. Maternal effects were detected for the diameter increment, stem volume and bud burst. Comparison of family and animal models showed that unbalanced mating system led to only slight departures from maternal family assumptions in the progeny trial. However, neglecting the significant maternal effects led to an overestimation of the heritability. Overall, we highlighted the usefulness of relatedness pattern analyses using polymorphic molecular markers to accurately analyse tree sibling designs

LoisellePaternalCoefficients

Untreated file generated by the simulation model that contains the pairwise individual paternal relatedness coefficients estimated based on the Loiselle approach (matrix format

PhiACoefficients

Untreated file generated by the simulation model that contains the pairwise individual kinship coefficients estimated based on the simulated pedigree (matrix format