Journal article icon

Journal article

The infinitesimal model: definition, derivation, and implications

Abstract:
Our focus here is on the infinitesimal model. In this model, one or several quantitative traits are described as the sum of a genetic and a non-genetic component, the first being distributed within families as a normal random variable centred at the average of the parental genetic components, and with a variance independent of the parental traits. Thus, the variance that segregates within families is not perturbed by selection, and can be predicted from the variance components. This does not necessarily imply that the trait distribution across the whole population should be Gaussian, and indeed selection or population structure may have a substantial effect on the overall trait distribution. One of our main aims is to identify some general conditions on the allelic effects for the infinitesimal model to be accurate. We first review the long history of the infinitesimal model in quantitative genetics. Then we formulate the model at the phenotypic level in terms of individual trait values and relationships between individuals, but including different evolutionary processes: genetic drift, recombination, selection, mutation, population structure, ... We give a range of examples of its application to evolutionary questions related to stabilising selection, assortative mating, effective population size and response to selection, habitat preference and speciation. We provide a mathematical justification of the model as the limit as the number M of underlying loci tends to infinity of a model with Mendelian inheritance, mutation and environmental noise, when the genetic component of the trait is purely additive. We also show how the model generalises to include epistatic effects. We prove in particular that, within each family, the genetic components of the individual trait values in the current generation are indeed normally distributed with a variance independent of ancestral traits, up to an error of order 1/√M. Simulations suggest that in some cases the convergence may be as fast as 1/M.
Publication status:
Published
Peer review status:
Peer reviewed

Actions


Access Document


Files:
Publisher copy:
10.1016/j.tpb.2017.06.001

Authors


More by this author
Institution:
University of Oxford
Oxford college:
Magdalen College
Role:
Author


More from this funder
Funding agency for:
Etheridge, A
Grant:
EP/K034316/1


Publisher:
Elsevier
Journal:
Theoretical Population Biology More from this journal
Volume:
118
Pages:
50-73
Publication date:
2017-07-11
Acceptance date:
2017-06-02
DOI:
EISSN:
1096-0325
ISSN:
0040-5809


Keywords:
Pubs id:
pubs:698643
UUID:
uuid:20784bd5-c1bf-437f-aa9b-c6ccea10a508
Local pid:
pubs:698643
Source identifiers:
698643
Deposit date:
2017-06-07

Terms of use



Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP