The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
Mark Kirkpatrick - One of the best experts on this subject based on the ideXlab platform.
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up hill down dale Quantitative Genetics of curvaceous traits
Philosophical Transactions of the Royal Society B, 2005Co-Authors: K Meyer, Mark KirkpatrickAbstract:‘Repeated’ measurements for a trait and individual, taken along some continuous scale such as time, can be thought of as representing points on a curve, where both means and covariances along the trajectory can change, gradually and continually. Such traits are commonly referred to as ‘function-valued’ (FV) traits. This review shows that standard Quantitative genetic concepts extend readily to FV traits, with individual statistics, such as estimated breeding values and selection response, replaced by corresponding curves, modelled by respective functions. Covariance functions are introduced as the FV equivalent to matrices of covariances. Considering the class of functions represented by a regression on the continuous covariable, FV traits can be analysed within the linear mixed model framework commonly employed in Quantitative Genetics, giving rise to the so-called random regression model. Estimation of covariance functions, either indirectly from estimated covariances or directly from the data using restricted maximum likelihood or Bayesian analysis, is considered. It is shown that direct estimation of the leading principal components of covariance functions is feasible and advantageous. Extensions to multi-dimensional analyses are discussed.
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Quantitative Genetics and the evolution of reaction norms
Evolution, 1992Co-Authors: Richard Gomulkiewicz, Mark KirkpatrickAbstract:We extend methods of Quantitative Genetics to studies of the evolution of reaction norms defined over continuous environments. Our models consider both spatial variation (hard and soft selection) and temporal variation (within a generation and between generations). These different forms of environmental variation can produce different evolutionary trajectories even when they favor the same optimal reaction norm. When genetic constraints limit the types of evolutionary changes available to a reaction norm, different forms of environmental variation can also produce different evolutionary equilibria. The methods and models presented here provide a framework in which empiricists may determine whether a reaction norm is optimal and, if it is not, to evaluate hypotheses for why it is not.
Wolfgang Forstmeier - One of the best experts on this subject based on the ideXlab platform.
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Quantitative Genetics and fitness consequences of neophilia in zebra finches
Behavioral Ecology, 2011Co-Authors: Holger Schielzeth, Elisabeth Bolund, Bart Kempenaers, Wolfgang ForstmeierAbstract:Consistent between-individual differences in context-general behavioral traits (often called personality traits) are particularly interesting for behavioral ecologists because they might show unexpected cross-context correlations and explain maladaptive behavior. In order to understand their evolutionary significance, it is relevant to know the heritability of these traits and how they relate to reproductive success. This might give insights into selective processes that maintain variation as well as into potential trade-offs. We scored approach to novel objects of 530 captive zebra finches in a familiar environment. Scores were highly repeatable and showed substantial additive genetic variation. We measured reproductive success, promiscuity, and extrapair paternity rates under aviary conditions and calculated linear and nonlinear selection differentials based on fertilization success as well as effects on chick-rearing success of pairs. Approach to novel objects had little influence on these components of reproductive success. However, we found that the social environment (manipulated operational sex ratios) influenced the correlation between approach to a novel object and the proportion of extrapair paternity. We also found that the sex ratio manipulation affected measures of the intensity of sexual selection. Both effects were stronger in males than in females. We conclude that despite the lack of differences in overall reproductive success, approach to novel objects reflects variation in reproductive strategies. Key words: behavioral syndromes, extrapair paternity, fitness landscapes, mating preferences, operational sex ratio, reproductive success, sexual selection, temperament. [Behav Ecol]
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Quantitative Genetics and behavioural correlates of digit ratio in the zebra finch
Proceedings of The Royal Society B: Biological Sciences, 2005Co-Authors: Wolfgang ForstmeierAbstract:A recent study on a captive zebra finch population suggested that variation in digit ratio (i.e. the relative length of the second to the fourth toe) might be an indicator of the action of sex steroids during embryo development, as is widely assumed for human digits. Zebra finch digit ratio was found to vary with offspring sex, laying order of eggs within a clutch, and to predict aspects of female mating behaviour. Hence, it was proposed that the measurement of digit ratio would give insights into how an individual's behaviour is shaped by its maternal environment. Studying 500 individuals of a different zebra finch population I set out to: (1) determine the proximate causes of variation in digit ratio by means of Quantitative Genetics and (2) to search for phenotypic and genetic correlations between digit ratio, sexual behaviour and aspects of fitness. In contrast to the earlier study, I found no sexual dimorphism in digit ratio and no effect of either laying order or experimentally altered hatching order on digit ratio. Instead, I found that variation in digit ratio was almost entirely additive genetic, with heritability estimates ranging from 71 to 84%. The rearing environment (from egg deposition to independence) explained an additional 5–6% of the variation in digit ratio, but there was no indication of any maternal effects transmitted through the egg. I found highly significant phenotypic correlations (and genetic correlations of similar size) between digit ratio and male song rate (positive correlation) as well as between digit ratio and female hopping activity in a choice chamber (negative correlation). Rather surprisingly, the strength of these correlations differed significantly between subsequent generations of the same population, illustrating how quickly such correlations can appear and disappear probably due to genotype–environment interactions.
Lars Ronnegard - One of the best experts on this subject based on the ideXlab platform.
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a novel generalized ridge regression method for Quantitative Genetics
Genetics, 2013Co-Authors: Xia Shen, Moudud Alam, Freddy Fikse, Lars RonnegardAbstract:As the molecular marker density grows, there is a strong need in both genome-wide association studies and genomic selection to fit models with a large number of parameters. Here we present a computationally efficient generalized ridge regression (RR) algorithm for situations in which the number of parameters largely exceeds the number of observations. The computationally demanding parts of the method depend mainly on the number of observations and not the number of parameters. The algorithm was implemented in the R package bigRR based on the previously developed package hglm . Using such an approach, a heteroscedastic effects model ( HEM ) was also developed, implemented, and tested. The efficiency for different data sizes were evaluated via simulation. The method was tested for a bacteria-hypersensitive trait in a publicly available Arabidopsis data set including 84 inbred lines and 216,130 SNPs. The computation of all the SNP effects required
Allen J Moore - One of the best experts on this subject based on the ideXlab platform.
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the Quantitative Genetics and coevolution of male and female reproductive traits
Evolution, 2010Co-Authors: Rhonda R Snook, Leonardo D Bacigalupe, Allen J MooreAbstract:Studies of experimental sexual selection have tested the effect of variation in the intensity of sexual selection on male investment in reproduction, particularly sperm. However, in several species, including Drosophila pseudoobscura, no sperm response to experimental evolution has occurred. Here, we take a Quantitative Genetics approach to examine whether genetic constraints explain the limited evolutionary response. We quantified direct and indirect genetic variation, and genetic correlations within and between the sexes, in experimental populations of D. pseudoobscura. We found that sperm number may be limited by low heritability and evolvability whereas sperm quality (length) has moderate V A and CV A but does not evolve. Likewise, the female reproductive tract, suggested to drive the evolution of sperm, did not respond to experimental sexual selection even though there was sufficient genetic variation. The lack of genetic correlations between the sexes supports the opportunity for sexual conflict over investment in sperm by males and their storage by females. Our results suggest no absolute constraint arising from a lack of direct or indirect genetic variation or patterns of genetic covariation. These patterns show why responses to experimental evolution are hard to predict, and why research on genetic variation underlying interacting reproductive traits is needed.
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the Quantitative Genetics of sex differences in parenting
Proceedings of the National Academy of Sciences of the United States of America, 2008Co-Authors: Craig A Walling, Per T Smiseth, Clare E Stamper, Allen J MooreAbstract:Sex differences in parenting are common in species where both males and females provide care. Although there is a considerable body of game and optimality theory for why the sexes should differ in parental care, Genetics can also play a role, and no study has examined how genetic influences might influence differences in parenting. We investigated the extent that genetic variation influenced differences in parenting, whether the evolution of differences could be constrained by shared genetic influences, and how sex-specific patterns of genetic variation underlying parental care might dictate which behaviors are free to evolve in the burying beetle Nicrophorus vespilloides. Females provided more direct care than males but did not differ in levels of indirect care or the number of offspring they were willing to rear. We found low to moderate levels of heritability and evolvability for all 3 parenting traits in both sexes. Intralocus sexual conflict was indicated by moderately strong intersex genetic correlations, but these were not so strong as to represent an absolute constraint to the evolution of sexual dimorphism in care behavior. Instead, the pattern of genetic correlations between parental behaviors showed sex-specific tradeoffs. Thus, differences in the genetic correlations between parental traits within a sex create sex-specific lines of least evolutionary resistance, which in turn produce the specific patterns of sex differences in parental care. Our results therefore suggest a mechanism for the evolution of behavioral specialization during biparental care if uniparental and biparental care behaviors share the same genetic influences.
Xia Shen - One of the best experts on this subject based on the ideXlab platform.
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a novel generalized ridge regression method for Quantitative Genetics
Genetics, 2013Co-Authors: Xia Shen, Moudud Alam, Freddy Fikse, Lars RonnegardAbstract:As the molecular marker density grows, there is a strong need in both genome-wide association studies and genomic selection to fit models with a large number of parameters. Here we present a computationally efficient generalized ridge regression (RR) algorithm for situations in which the number of parameters largely exceeds the number of observations. The computationally demanding parts of the method depend mainly on the number of observations and not the number of parameters. The algorithm was implemented in the R package bigRR based on the previously developed package hglm . Using such an approach, a heteroscedastic effects model ( HEM ) was also developed, implemented, and tested. The efficiency for different data sizes were evaluated via simulation. The method was tested for a bacteria-hypersensitive trait in a publicly available Arabidopsis data set including 84 inbred lines and 216,130 SNPs. The computation of all the SNP effects required
