Maximum Likelihood Estimation of Genetic Parameters in Life-History Studies Using the `Animal Model'

Knott, Sara; Sibly, Richard M.; Smith, Robert H.; Møller, H.

doi:10.2307/2390099

Cited by 69 publications

(60 citation statements)

References 18 publications

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“…To partition the phenotypic variance (V P ) and estimate variance components and heritability, we used a restricted maximum likelihood (REML) mixed-model known as ''the animal model'' (42,43), implemented in the software ASREML (44). The analysis combines pedigree information with phenotypic records to break down individual phenotypes in a sum of fixed and random effects.…”

Section: Methodsmentioning

confidence: 99%

Quantitative genetics of age at reproduction in wild swans: Support for antagonistic pleiotropy models of senescence

Charmantier

Perrins

McCleery

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

148

158

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Why do individuals stop reproducing after a certain age, and how is this age determined? The antagonistic pleiotropy theory for the evolution of senescence predicts that increased early-life performance should be accompanied by earlier (or faster) senescence. Hence, an individual that has started to breed early should also lose its reproductive capacities early. We investigate here the relationship between age at first reproduction (AFR) and age at last reproduction (ALR) in a free-ranging mute swan (Cygnus olor) population monitored for 36 years. Using multivariate analyses on the longitudinal data, we show that both traits are strongly selected in opposite directions. Analysis of the phenotypic covariance between these characters shows that individuals vary in their inherent quality, such that some individuals have earlier AFR and later ALR than expected. Quantitative genetic pedigree analyses show that both traits possess additive genetic variance but also that AFR and ALR are positively genetically correlated. Hence, although both traits display heritable variation and are under opposing directional selection, their evolution is constrained by a strong evolutionary tradeoff. These results are consistent with the theory that increased early-life performance comes with faster senescence because of genetic tradeoffs.evolutionary tradeoff ͉ genetic correlation ͉ heritability ͉ mute swan ͉ aging T he decline in reproductive performance in organisms of old ages is one component of the evolutionary paradox of aging (1). Aging, or senescence, is the drop in survival and͞or fertility probabilities in old individuals. It is often witnessed in laboratory conditions (e.g., see refs. 2-4) and, more rarely, in nature (5-7). For evolutionary biologists, the evolution of decreased performance and increased mortality with age, which should at first sight be counterselected, is a puzzle. The solution to this puzzle lies in the weaker force of natural selection for older individuals in age-structured populations (8), which allows for the evolution of aging.Two main genetic processes have been proposed as causal mechanisms underlying the evolution of senescence. The first assumes an accumulation of late-acting deleterious mutations as a result of weak selection late in life (referred to as the mutation accumulation theory) (1, 8). Alternatively, aging can be promoted by the active selection of alleles with late deleterious effects but beneficial effects early in life, when selection is strongest (9). This latter theory, known as the antagonistic pleiotropy (AP) theory of aging, can be considered an optimality theory (10) because the evolution of senescence is explained by fitness maximized by good performance early in life, at the expense of performance later. This type of pleiotropic effect is best illustrated in physiological or ecological tradeoffs such as that occurring between reproduction and survival. Indeed this theory has at times been called the ''tradeoff'' model (11). However, an important facet of the AP theory is ...

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Section: Methodsmentioning

confidence: 99%

Quantitative genetics of age at reproduction in wild swans: Support for antagonistic pleiotropy models of senescence

Charmantier

Perrins

McCleery

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

148

158

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“…where y was a vector of phenotypic values, b and a were vectors of fixed and random effects, e was a vector of residual values, and X and Z were the corresponding design matrices (16,27).…”

Section: Morphometric Traits (Vii) Birth Weightmentioning

confidence: 99%

Heritability of fitness in a wild mammal population

Kruuk

Clutton‐Brock

Slate

et al. 2000

Proc. Natl. Acad. Sci. U.S.A.

442

436

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Classical population genetics theory predicts that selection should deplete heritable genetic variance for fitness. We show here that, consistent with this prediction, there was a negative correlation between the heritability of a trait and its association with fitness in a wild population of red deer (Cervus elaphus) and there was no evidence of significant heritability of total fitness. However, the decline in heritability was caused, at least in part, by increased levels of residual variance in longevity and, hence, in total fitness: in this population, longevity is known to be heavily influenced by environmental factors. Other life history traits that were not associated with longevity, such as average annual breeding success, had higher heritabilities. Coefficients of additive genetic variance differed markedly between traits, but highly skewed measures, such as male breeding success, generally had greater coefficients of variance than morphometric traits. Finally, there were significant maternal effects in a range of traits, particularly for females.

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“…It also partitions phenotypic variance of a quantitative character into its additive genetic and other fixed and random components such as common environment (Meyer 1989). Furthermore, by exploiting all relationships between individuals in a pedigree, they are considerably more powerful than the conventional models used in estimating quantitative genetic parameters (Knott et al 1995;Lynch and Walsh 1998). Thus, in contrast to earlier studies of the inheritance of sexually selected traits in birds, the animal model approach allowed us to separate additive genetic from environmental effects.…”

Section: Animal Model and Heritability Analysismentioning

confidence: 99%

“…We first quantified the contributions of additive genetic (heritable) effects relative to environmental effects, and estimated the genetic correlation between the forehead and wing patch areas using a pedigree analysis procedure based on restricted maximumlikelihood (REML) estimators and a mixed ''animal'' model (Knott et al 1995;Lynch and Walsh 1998). These techniques make maximum use of information in multigenerational pedigrees and produce less biased estimates of genetic variability than traditional parent-offspring or full-sibling analyses (e.g.…”

mentioning

confidence: 99%

“…These techniques make maximum use of information in multigenerational pedigrees and produce less biased estimates of genetic variability than traditional parent-offspring or full-sibling analyses (e.g. Knott et al 1995;Lynch and Walsh 1998). We then used the winter NAO index to define environmental quality and estimated heritability and components of variance of these characters under both favorable and unfavorable environmental conditions.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Climatic and Temporal Effects on the Expression of Secondary Sexual Characters: Genetic and Environmental Components

Garant¹,

Sheldon²,

Gustafsson³

2004

Evolution

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Abstract. Despite great interest in sexual selection, relatively little is known in detail about the genetic and environmental determinants of secondary sexual characters in natural populations. Such information is important for determining the way in which populations may respond to sexual selection. We report analyses of genetic and largescale environmental components of phenotypic variation of two secondary sexual plumage characters (forehead and wing patch size) in the collared flycatcher Ficedula albicollis over a 22-year period. We found significant heritability for both characters but little genetic covariance between the two. We found a positive association between forehead patch size and a large-scale climatic index, the North Atlantic Oscillation (NAO) index, but not for wing patch. This pattern was observed in both cross-sectional and longitudinal data suggesting that the population response to NAO index can be explained as the result of phenotypic plasticity. Heritability of forehead patch size for old males, calculated under favorable conditions (NAO index Ն median), was greater than that under unfavorable conditions (NAO index Ͻ median). These changes occurred because there were opposing changes in additive genetic variance (V A ) and residual variance (V R ) under favorable and unfavorable conditions, with V A increasing and V R decreasing in good environments. However, no such effect was detected for young birds, or for wing patch size in either age class. In addition to these environmental effects on both phenotypic and genetic variances, we found evidence for a significant decrease of forehead patch size over time in older birds. This change appears to be caused by a change in the sign of viability selection on forehead patch size, which is associated with a decline in the breeding value of multiple breeders. Our data thus reveal complex patterns of environmental influence on the expression of secondary sexual characters, which may have important implications for understanding selection and evolution of these characters.

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Maximum Likelihood Estimation of Genetic Parameters in Life-History Studies Using the `Animal Model'

Cited by 69 publications

References 18 publications

Quantitative genetics of age at reproduction in wild swans: Support for antagonistic pleiotropy models of senescence

Quantitative genetics of age at reproduction in wild swans: Support for antagonistic pleiotropy models of senescence

Heritability of fitness in a wild mammal population

Climatic and Temporal Effects on the Expression of Secondary Sexual Characters: Genetic and Environmental Components

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