Detecting Maternal-Effect Loci by Statistical Cross-Fostering

Wolf, Jason B.; Cheverud, James M.

doi:10.1534/genetics.111.136440

Cited by 15 publications

(16 citation statements)

References 61 publications

(103 reference statements)

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“…Our unpublished results, however, show that the DGE and the IGE on family members are fully confounded in this situation. A potential solution may come from cross-fostering strategies, where genetically unrelated individuals are combined into the litter nursed by a (foster) mother (for example, Bouwman et al, 2010;Wolf and Cheverud, 2012). In such data, a set of familiar individuals contains variation in pair-wise relatedness, so that direct effects and indirect effects on relatives can probably be distinguished.…”

Section: Estimating Igesmentioning

confidence: 99%

The quantitative genetics of indirect genetic effects: a selective review of modelling issues

2013

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Indirect genetic effects (IGE) occur when the genotype of an individual affects the phenotypic trait value of another conspecific individual. IGEs can have profound effects on both the magnitude and the direction of response to selection. Models of inheritance and response to selection in traits subject to IGEs have been developed within two frameworks; a trait-based framework in which IGEs are specified as a direct consequence of individual trait values, and a variance-component framework in which phenotypic variance is decomposed into a direct and an indirect additive genetic component. This work is a selective review of the quantitative genetics of traits affected by IGEs, with a focus on modelling, estimation and interpretation issues. It includes a discussion on variance-component vs trait-based models of IGEs, a review of issues related to the estimation of IGEs from field data, including the estimation of the interaction coefficient W (psi), and a discussion on the relevance of IGEs for response to selection in cases where the strength of interaction varies among pairs of individuals. An investigation of the trait-based model shows that the interaction coefficient W may deviate considerably from the corresponding regression coefficient when feedback occurs. The increasing research effort devoted to IGEs suggests that they are a widespread phenomenon, probably particularly in natural populations and plants. Further work in this field should considerably broaden our understanding of the quantitative genetics of inheritance and response to selection in relation to the social organisation of populations.

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Section: Estimating Igesmentioning

confidence: 99%

The quantitative genetics of indirect genetic effects: a selective review of modelling issues

2013

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“…Analogously, the additive maternal effect genotypic value, a m , , is half the difference between the mean phenotypes of the offspring of A 1 A 1 and A 2 A 2 mothers, while the dominance maternal effect genotypic value, d m , is defined as the deviation of the average offspring phenotype of heterozygous mothers from the average of the offspring means of homozygous mothers, in the absence of direct effects (cf. Wolf and Cheverud ). The offspring phenotypes as a function of these genetic effects are summarized in Table .…”

Section: The Modelmentioning

confidence: 96%

“…The effects of the locus are summarized using two classic parameters, the additive ( a ) and dominance ( d ) genotypic values or effects (see Falconer and Mackay ). Following Wolf and Cheverud (), we define the direct and maternal effects of the locus in an idealized scenario where each is measured in the absence of the other effect. We take this approach (of defining each in the absence of the other) because, in the traditional quantitative genetic approach, direct, and maternal effects are partially confounded due to relatedness (i.e., the fact that some genotypes of mothers can only produce a subset of possible offspring genotypes; e.g., A 1 A 1 mothers cannot have A 2 A 2 offspring).…”

Section: The Modelmentioning

confidence: 99%

“…We take this approach (of defining each in the absence of the other) because, in the traditional quantitative genetic approach, direct, and maternal effects are partially confounded due to relatedness (i.e., the fact that some genotypes of mothers can only produce a subset of possible offspring genotypes; e.g., A 1 A 1 mothers cannot have A 2 A 2 offspring). Our definitions of direct and maternal effects are therefore equivalent to the values that one might recover through cross‐fostering, where offspring genotypes are randomized across maternal genotypes (Wolf and Cheverud ). We use the subscripts “ o ” and “ m ” to indicate direct (“offspring”) and maternal effects, respectively.…”

Section: The Modelmentioning

confidence: 99%

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Evolutionary genetics of maternal effects

Wolf

Wade

2016

Evolution

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Maternal genetic effects (MGEs), where genes expressed by mothers affect the phenotype of their offspring, are important sources of phenotypic diversity in a myriad of organisms. We use a single-locus model to examine how MGEs contribute patterns of heritable and non-heritable variation and influence evolutionary dynamics in randomly mating and inbreeding populations. We elucidate the influence of MGEs by examining the offspring genotype-phenotype relationship, which determines how MGEs affect evolutionary dynamics in response to selection on offspring phenotypes. This approach reveals important results that are not apparent from classic quantitative genetic treatments of MGEs. We show that additive and dominance MGEs make different contributions to evolutionary dynamics and patterns of variation, which are differentially affected by inbreeding. Dominance MGEs make the offspring genotype-phenotype relationship frequency dependent, resulting in the appearance of negative frequency-dependent selection, while additive MGEs contribute a component of parent-of-origin dependent variation. Inbreeding amplifies the contribution of MGEs to the additive genetic variance and, therefore enhances their evolutionary response. Considering evolutionary dynamics of allele frequency change on an adaptive landscape, we show that this landscape differs from the mean fitness surface, and therefore, under some condition, fitness peaks can exist but not be ‘available’ to the evolving population.

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“…There is abundant empirical evidence for the role of maternal genetic factors acting in the womb that affect body size and growth (Ernst et al, 2000; Rhees et al, 1999; Cowley et al, 1989; Brumby, 1960; Atchley et al, 1991; Walton and Hammond, 1938), but no phenotypic variation in an F2 intercross can be attributed to maternal genetic effects because all the mothers are genetically identical F1 hybrids of the two parental strains. Maternal-effect QTLs for growth and body size have been detected in advanced intercross generations (Wolf and Cheverud, 2012; Wolf et al, 2002; Wolf et al, 2011). Their discoveries illustrate how QTLs that affect the maternal-age associated risk of congenital heart disease can be found.…”

Section: An Unbiased Genetic Approach To the Maternal Effects On Omentioning

confidence: 99%

Transgenerational cardiology: One way to a baby's heart is through the mother

Jay

Akhirome

Magnan

et al. 2016

Molecular and Cellular Endocrinology

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Despite decades of progress, congenital heart disease remains a major cause of mortality and suffering in children and young adults. Prevention would be ideal, but formidable biological and technical hurdles face any intervention that seeks to target the main causes, genetic mutations in the embryo. Other factors, however, significantly modify the total risk in individuals who carry mutations. Investigation of these factors could lead to an alternative approach to prevention. To define the risk modifiers, our group has taken an “experimental epidemiologic” approach via inbred mouse strain crosses. The original intent was to map genes that modify an individual’s risk of heart defects caused by an Nkx2-5 mutation. During the analysis of >2000 Nkx2-5+/− offspring from one cross we serendipitously discovered a maternal-age associated risk, which also exists in humans. Reciprocal ovarian transplants between young and old mothers indicate that the incidence of heart defects correlates with the age of the mother and not the oocyte, which implicates a maternal pathway as the basis of the risk. The quantitative risk varies between strain backgrounds, so maternal genetic polymorphisms determine the activity of a factor or factors in the pathway. Most strikingly, voluntary exercise by the mother mitigates the risk. Therefore, congenital heart disease can in principle be prevented by targeting a maternal pathway even if the embryo carries a causative mutation. Further mechanistic insight is necessary to develop an intervention that could be implemented on a broad scale, but the physiology of maternal-fetal interactions, aging, and exercise are notoriously complex and undefined. This suggests that an unbiased genetic approach would most efficiently lead to the relevant pathway. A genetic foundation would lay the groundwork for human studies and clinical trials.

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Detecting Maternal-Effect Loci by Statistical Cross-Fostering

Cited by 15 publications

References 61 publications

The quantitative genetics of indirect genetic effects: a selective review of modelling issues

The quantitative genetics of indirect genetic effects: a selective review of modelling issues

Evolutionary genetics of maternal effects

Transgenerational cardiology: One way to a baby's heart is through the mother

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