Statistical genetics and evolution of quantitative traits
By Richard A. Neher, Boris I. Shraiman. 2011
101 citations recorded by the source corpus.
The distribution and heritability of many traits depends on numerous loci in the genome. In general, the astronomical number of possible genotypes makes the system with large numbers of loci difficult to describe. Multilocus evolution, however, greatly simplifies in the limit of weak selection and frequent recombination. In this limit, populations rapidly reach quasilinkage equilibrium (QLE) in which the dynamics of the full genotype distribution, including correlations between alleles at different loci, can be parametrized by the allele frequencies. This review provides a simplified exposition of the concept and mathematics of QLE which is central to the statistical description of genotypes in sexual populations. Key results of quantitative genetics such as the generalized Fisher's ``fundamental theorem,'' along with Wright's adaptive landscape, are shown to emerge within QLE from the dynamics of the genotype distribution. This is followed by a discussion under what circumstances QLE is applicable, and what the breakdown of QLE implies for the population structure and the dynamics of selection. Understanding the fundamental aspects of multilocus evolution obtained through simplified models may be helpful in providing conceptual and computational tools to address the challenges arising in the studies of complex quantitative phenotypes of practical interest.
Subfields: Ecology, Evolution, Behavior and Systematics, Genetics, Public Health, Environmental and Occupational Health
View Paper: https://www.semanticscholar.org/paper/7fcd621b9b580128ccc617c63c502375c07dbc17
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Citations in the corpus
- Genetic Draft, Selective Interference, and Population Genetics of Rapid Adaptation (2013, methodology): “…to be universal to populations in which individual lineages are amplified while they diversify and is found in facultatively sexual populations (Neher and Shraiman, 2011b), asexual populations adapting by small steps, as well as populations in a dynamic balance between deleterious and…”
- Nonequilibrium physics in biology (2019, methodology): “…(115) VA = 2 ∑ i Ci(wi − w)2 represents the total gametic variance from natural selection and VR = −2 ∑ i ∑ Q,Q 6=∅,L wirQDi,Q represents the epistatic ga- metic variance from the linkage disequilibrium of the loci((Ewens, 2004; Neher and Shraiman, 2011; Rice, 2004; Svirezhev and Passekov, 1990)).”
- Inferring fitness landscapes by regression produces biased estimates of epistasis (2014, background): “In the case of a population with large diversity and no well-defined reference sequence, the reference-free parameterization with ± 1 may be more appropriate, with β0 then denoting the inferred average fitness (57, 62).”