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20 results for “Heritability estimation”
Accurate and Efficient Estimation of Local Heritability using Summary Statistics and LD Matrix -- Demo datasets for the HEELS tutorials
<p>We introduced a new estimator for local heritability, "HEELS", which attains comparable statistical efficiency as the REML estimator (such as those produced by GCTA and BOLT-REML) but only requires summary-level statistics – Z-scores from marginal association tests and the empirical LD. Our method has been implemented into an open-source Python-based command line tool. </p> <p>The datasets released here can be downloaded to test the two main functions of our software package: 1) estimating local heritability; 2) computing the low-dimensional representation of the LD matrix. They are meant to accompany the HEELS tutorials we have posted onto the wiki pages of our github repository: https://github.com/huilisabrina/HEELS/wiki.</p> <p> </p>
Data from: Is pairing with a relative heritable? estimating female and male genetic contributions to the degree of biparental inbreeding in song sparrows (Melospiza melodia)
The degree of inbreeding expressed within populations can profoundly shape evolutionary dynamics. The degree to which individuals inbreed is frequently assumed to evolve in response to selection, for example resulting from inbreeding depression. Such evolutionary responses require additive genetic variance (VA) in the degree to which individuals inbreed. However, the magnitude of VA in the degree of biparental inbreeding has never been estimated. We devised a quantitative genetic model to estimate sex-specific VA in the degree to which individuals inbreed, while accounting for effects of individuals' own coefficients of inbreeding and genetic effects stemming from immigration. We applied this model to the degree of inbreeding expressed through social pairing in free-living song sparrows (Melospiza melodia). VA estimates for both sexes appreciably exceeded zero and the cross-sex genetic covariance was strongly positive, creating substantial total VA in the degree of inbreeding. Our analyses also revealed inbreeding depression in the degree of inbreeding such that more inbred individuals paired with closer relatives, and immigrant effects such that individuals with greater genomic contributions from immigrants paired with more distant relatives. We thereby demonstrate that the degree of biparental inbreeding can show substantial VA in nature and might consequently evolve in response to selection.
Data from: Heritability estimates from genome wide relatedness matrices in wild populations: application to a passerine, using a small sample size
Genomic developments have empowered the investigation of heritability in wild populations directly from genome wide relatedness matrices (GRM). Such GRM based approaches can in particular be used to improve or substitute approaches based on social pedigree (PED-social). However, measuring heritability from GRM in the wild has not been widely applied yet, especially using small samples and in non-model species. Here, we estimated heritability for four quantitative traits (tarsus length, wing length, bill length and body mass), using PED-social and a pedigree corrected by genetic data (PED-corrected) and GRM from a small sample (n = 494) of blue tits from natural populations in Corsica genotyped at nearly 50,000 filtered SNPs derived from RAD-seq. We also measured genetic correlations among traits and we performed chromosome partitioning. Heritability estimates were slightly higher when using GRM compared to PED-social, and PED-corrected yielded intermediate values, suggesting a minor underestimation of heritability in PED-social due to incorrect pedigree links, including extra-pair paternity, and to lower information content than the GRM. Genetic correlations among traits were similar between PED-social and GRM but credible intervals were very large in both cases, suggesting a lack of power for this small dataset. Although a positive linear relationship was found between the number of genes per chromosomes and the chromosome heritability for tarsus length, chromosome partitioning similarly showed a lack of power for the three other traits. We discuss the usefulness and limitations of the quantitative genetic inferences based on genomic data in small samples from wild populations.
Data from: The influence of nonrandom extra-pair paternity on heritability estimates derived from wild pedigrees
Quantitative genetic analysis is often fundamental for understanding evolutionary processes in wild populations. Avian populations provide a model system due to the relative ease of inferring relatedness amongst individuals through observation. However, extra-pair paternity (EPP) creates erroneous links within the social pedigree. Previous work has suggested this causes minor underestimation of heritability if paternal misassignment is random and hence not influenced by the trait being studied. Nevertheless, much literature suggests numerous traits are associated with EPP and the accuracy of heritability estimates for such traits remains unexplored. We show analytically how non-random pedigree errors can influence heritability estimates. Then, combining empirical data from a large great tit (Parus major) pedigree with simulations, we assess how heritability estimates derived from social pedigrees change depending on the mode of the relationship between EPP and the focal trait. We show that the magnitude of the underestimation is typically small (<15%). Hence, our analyses suggest that quantitative genetic inference from pedigrees derived from observations of social relationships are relatively robust; our approach also provides a widely-applicable method for assessing the consequences of non-random EPP.
Quantifying heritability and estimating evolutionary potential in the wild when individuals that share genes also share environments
<p>Accurate heritability estimates for fitness-related traits are required to predict an organism's ability to respond to global change. Heritability estimates are theoretically expected to be inflated if, due to limited dispersal, individuals that share genes are also likely to share similar environments. However, if relatives occupy similar environments due, at least partly, to genetic variation for habitat selection, then accounting for environmental similarity in quantitative genetic models may result in diminished heritability estimates in wild populations. This potential issue has been pointed out in the literature, but has not been evaluated by empirical studies.<br><br>Here, we investigate whether environmental similarity among individuals can be partly explained by genetic variation for habitat selection, and how this link potentially blurs estimates for heritability in fitness-related traits.<br><br>Using intensive GPS-monitoring, we quantified home-range habitat composition for 293 roe deer inhabiting a heterogeneous landscape to assess environmental similarity. To investigate if environmental similarity might harbour genetic variation, we combined genome-wide data in a quantitative genetic framework to evaluate genetic variation for home-range habitat composition, which is partly the result of habitat selection at settlement. Finally, we explored how environmental similarity affects heritability estimates for behaviours related to the risk avoidance-resource acquisition trade-off (i.e. being in open habitat, distance to roads) and proxies of individual performance (i.e. body mass, hind foot length). We found substantial heritability for home-range habitat composition, with estimates ranging from 0.40 (proportion of meadows) to 0.85 (proportion of refuge habitat). Accounting for similarity in habitat composition between relatives decreased the heritability estimates for both behavioural and morphological traits (reduction ranging from 55% to 100% and from 22% to 41%, respectively). As a consequence, only half of these heritability estimates remained significantly different from zero.<br><br>Our results show that similar genotypes occupy similar environments, which could lead to heritable variation being incorrectly attributed to environmental effects. To accurately distinguish the sources of phenotypic variation and predict the ability of organisms to respond to global change, it is necessary to develop quantitative genetic studies investigating the mechanisms underpinning environmental similarity among relatives.</p>
Pedigree and phenotypic variables used for estimation of heritability of sand lizard badge size and condition
<p><span>Sexual selection on fitness-determining traits should theoretically erode genetic variance and lead to low heritability. However, many sexually selected traits maintain significant phenotypic and additive genetic variance, with explanations for this "lek paradox" including genic capture due to condition-dependence, and breaks on directional selection due to environmental sources of variance including maternal effects. Here we investigate genetic and environmental sources of variance in the intrasexually selected green badge of the sand lizard (<em>Lacerta agilis</em>). The badge functions as a cue to male fighting ability in this species, and male-male interactions determine mate acquisition. Using animal models on a pedigree including three generations of males measured over an extensive nine year field study, we partition phenotypic variance in both badge size and body condition into additive genetic, maternal, and permanent environmental effects experienced by an individual over its lifespan. Heritability of badge size was 0.33 with a significant estimate of underlying additive genetic variance. Body condition was strongly environmentally determined in this species and does not show either significant additive genetic variance or heritability. Neither badge size nor body condition were responsive to maternal effects. We propose that the lack of additive genetic variance and heritability of body condition makes it unlikely that genic capture mechanisms maintains additive genetic variance for badge size. That said, genic capture was originally proposed for male traits under female choice, not agonistic selection. If developmental pathways generating variance in body condition, and/or the covarying secondary sex trait, differ between inter- and intrasexual selection, or the rate at which their additive genetic variance or covariance is depleted, future work may show whether genic capture is largely restricted to intersexual selection processes.</span></p>
Quantifying heritability and estimating evolutionary potential in the wild when individuals that share genes also share environments
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Data from: Is pairing with a relative heritable? estimating female and male genetic contributions to the degree of biparental inbreeding in song sparrows (Melospiza melodia)
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Data from: The influence of nonrandom extra-pair paternity on heritability estimates derived from wild pedigrees
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Pedigree and phenotypic variables used for estimation of heritability of sand lizard badge size and condition
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Data from: Heritability estimates from genome wide relatedness matrices in wild populations: application to a passerine, using a small sample size
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Data from: RAD‐sequencing for estimating genomic relatedness matrix‐based heritability in the wild: a case study in roe deer
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Estimating heritability in honeybees: comparison of three major methods based on empirical and simulated datasets
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Data for "Accurate Estimation of Marker-Associated Genetic Variance and Heritability in Complex Trait Analyses"
<p>This data is associated with the manuscript titled "Accurate Estimation of Marker-Associated Genetic Variance and Heritability in Complex Trait Analyses".</p> <p>9 files are contained. These files contain the summary statistics from the linear mixed model analyses in the simulations</p> <p>data_fig1a - all data for recreating Figure 1A</p> <p>data_fig1b - all data for recreating Figure 1B</p> <p>data_fig1c - all data for recreating Figure 1C</p> <p>data_fig1d - all data for recreating Figure 1D</p> <p>data_fig1e - all data for recreating Figure 1E</p> <p>data_fig1f - all data for recreating Figure 1F</p> <p>data_fig2 - all data for recreating Figure 2</p> <p>data_fig3 - all data for recreating Figure 3</p> <p>data_fig4 - all data for recreating Figure 4</p>
Data from: Multilocus estimation of selfing and its heritability
We describe a new method of estimating the selfing rate (S) in a mixed mating population based on a population structure approach that accounts for possible intergenerational correlation in selfing rate, giving rise to an estimate of the upper limit for heritability of selfing rate (h^2). A correlation between generations in selfing rate is shown to affect one- and two-locus probabilities of identity by descent. Conventional estimates of selfing rate based on a population structure approach are positively biased by intergenerational correlation in selfing. Multilocus genotypes of individuals are used to give maximum-likelihood estimates of S and h^2 in the presence of scoring artifacts. Our multilocus estimation of selfing rate and its heritability (MESH) method was tested with simulated data for a range of conditions. Selfing rate estimates from MESH have low bias and root mean squared error, while estimates of the heritability of selfing rate have more uncertainty. Increasing the number of individuals in a sample helps to reduce bias and root mean squared error more than increasing the number of loci of sampled individuals. Improved estimates of selfing rate, as well as estimates of its heritability, can be obtained with this method, although a large number of loci and individuals are needed to achieve best results.
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: Shared spatial effects on quantitative genetic parameters: accounting for spatial autocorrelation and home range overlap reduces estimates of heritability in wild red deer
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Data from: Partial genotyping at polymorphic markers can improve heritability estimates in sibling groups
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Data from: Multilocus estimation of selfing and its heritability
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Data from: Accounting for female space sharing in St. Kilda Soay sheep (Ovis aries) results in little change in heritability estimates
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