<b>nadiv</b>: an R package to create relatedness matrices for estimating non‐additive genetic variances in animal models

Wolak, Matthew E.

doi:10.1111/j.2041-210x.2012.00213.x

Cited by 161 publications

(149 citation statements)

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“…Moreover, other methods such as profile likelihoods (Meyer, 2008; implemented in the 'proLik' function within the package NADIV, Wolak, 2012) are more accessible and can also improve our comprehension of a particular dataset limits (Houle and Meyer, 2015). As each study system is unique, in terms of pedigree structure, number of repeated measures per individual or potential causes of pedigree errors, it is difficult to predict the reliability of quantitative genetics estimates without testing it formally.…”

Section: Resultsmentioning

confidence: 99%

“…Simulation analyses are now widely accessible to anyone with minimal programming skills in R, for instance by using the 'phensim' function within the package PEDANTICS, the 'rbv' function within the package MCMCglmm (Hadfield, 2010) or the 'drfx' and the 'grfx' function within the package NADIV (Wolak, 2012). Moreover, other methods such as profile likelihoods (Meyer, 2008; implemented in the 'proLik' function within the package NADIV, Wolak, 2012) are more accessible and can also improve our comprehension of a particular dataset limits (Houle and Meyer, 2015).…”

Section: Resultsmentioning

confidence: 99%

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An assessment of the reliability of quantitative genetics estimates in study systems with high rate of extra-pair reproduction and low recruitment

Bourret

Garant

2016

Heredity

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Quantitative genetics approaches, and particularly animal models, are widely used to assess the genetic (co)variance of key fitness related traits and infer adaptive potential of wild populations. Despite the importance of precision and accuracy of genetic variance estimates and their potential sensitivity to various ecological and population specific factors, their reliability is rarely tested explicitly. Here, we used simulations and empirical data collected from an 11-year study on tree swallow (Tachycineta bicolor), a species showing a high rate of extra-pair paternity and a low recruitment rate, to assess the importance of identity errors, structure and size of the pedigree on quantitative genetic estimates in our dataset. Our simulations revealed an important lack of precision in heritability and genetic-correlation estimates for most traits, a low power to detect significant effects and important identifiability problems. We also observed a large bias in heritability estimates when using the social pedigree instead of the genetic one (deflated heritabilities) or when not accounting for an important cause of resemblance among individuals (for example, permanent environment or brood effect) in model parameterizations for some traits (inflated heritabilities). We discuss the causes underlying the low reliability observed here and why they are also likely to occur in other study systems. Altogether, our results re-emphasize the difficulties of generalizing quantitative genetic estimates reliably from one study system to another and the importance of reporting simulation analyses to evaluate these important issues.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

An assessment of the reliability of quantitative genetics estimates in study systems with high rate of extra-pair reproduction and low recruitment

Bourret

Garant

2016

Heredity

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“…where k and l represent the dam and sire of i, m and n the dam and sire of j, and u is the additive genetic relatedness between individuals noted in the subscripts (Wolak 2012). This approximation assumes no inbreeding and ignores any dominance connections through grandparents, which were both inconsequential given the structure of our pedigree.…”

Section: Statistical Analysesmentioning

confidence: 99%

“…In cases examining common environmental variance, the vector of random effects was related to individuals in proportion to a blocked identity matrix. To calculate the dominance relationship matrix, the nadiv package (Wolak 2012) approximates the coefficients of fraternity (D ij ) between individuals i and j by…”

Section: Statistical Analysesmentioning

confidence: 99%

“…The sparse numerator relationship matrix (A) was calculated and inverted within Wombat, whereas we calculated and inverted the dominance relationship matrix (D) and additive 3 additive epistasis matrix (AA) using the nadiv package (Wolak 2012) in R (R Core Team 2012). In cases examining common environmental variance, the vector of random effects was related to individuals in proportion to a blocked identity matrix.…”

Section: Statistical Analysesmentioning

confidence: 99%

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Dominance Genetic Variance for Traits Under Directional Selection inDrosophila serrata

Sztepanacz

Blows

2015

Genetics

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In contrast to our growing understanding of patterns of additive genetic variance in single-and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected.KEYWORDS genetic variance; animal model; dominance; fitness C HARACTERIZING the genetic basis of phenotypes and the form and resulting consequences of selection on these phenotypes is a major goal of evolutionary biology. Substantial effort has been devoted to estimating additive genetic variance in metric traits and fitness components (Falconer and Mackay 1996;Lynch and Walsh 1998), establishing that the majority of metric traits have additive genetic variance and a heritability in the range of 0.2-0.6 (Lynch and Walsh 1998). More recently, the necessity of examining multivariate patterns of additive genetic variance and selection has been emphasized (Walsh and Blows 2009) and shown to influence the multivariate response to selection in laboratory (e.g., McGuigan and Blows 2009;Hine et al. 2014) and natural populations (Clements et al. 2011;Morrissey et al. 2012). In particular, additive genetic variance in all single traits often does not equate to genetic variance in all multivariate trait combinations (Hine and Blows 2006;Blows 2007;Walsh and Blows 2009), and a response to selection in trait combinations with low levels of additive genetic variance may be stochastic in nature .In contrast to our growing und...

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Local adaptation mediates floral responses to water limitation in an annual wildflower

Suni

Ainsworth

Hopkins

2020

American J of Botany

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Premise Understanding how environmental stress affects the strength of mutualisms is critically important given observed and projected environmental changes. In particular, the frequency and duration of drought have been increasing worldwide. We investigated how water availability affects plant traits that mediate a pollination mutualism. Methods For butterfly‐pollinated Phlox drummondii, we determined how moisture availability affects flower size, nectar volume, and nectar sugar amount. Furthermore, we explored the role that local adaptation may play in responses to moisture availability by including plants collected from regions that differ in aridity. Finally, we determined whether responses of plant populations to selection may differ under drought by calculating heritability of traits under control and dry conditions. Results Flower size was generally smaller in dry plants than in control plants. Early in the treatment period, nectar volume and sugar were higher in dry plants than in control plants for plants from both arid and wetter regions. With prolonged dry treatment, nectar volume and sugar remained higher only in plants from the arid region. Heritability of floral traits was lower for water‐limited plants than for control plants. Conclusions Plant investment into pollination mutualisms under environmental stress may depend on the extent to which populations are already locally adapted to such conditions, suggesting that mutualism may remain strong, at least in arid regions. However, decreases in heritability under water‐limitation suggest that responses to selection imposed by pollinators may be low, even if drought‐adapted plants maintain production of rewards to pollinators.

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nadiv: an R package to create relatedness matrices for estimating non‐additive genetic variances in animal models

Cited by 161 publications

References 41 publications

An assessment of the reliability of quantitative genetics estimates in study systems with high rate of extra-pair reproduction and low recruitment

An assessment of the reliability of quantitative genetics estimates in study systems with high rate of extra-pair reproduction and low recruitment

Dominance Genetic Variance for Traits Under Directional Selection inDrosophila serrata

Local adaptation mediates floral responses to water limitation in an annual wildflower

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