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An evolutionary perspective on epistasis and the missing heritability.

Hemani G, Knott S, Haley C - PLoS Genet. (2013)

Bottom Line: We propose that one reason that the problem of the "missing heritability" arises is because the additive genetic variation that is estimated to be contributing to the variance of a trait will most likely be an artefact of the non-additive variance that can be maintained over evolutionary time.We demonstrate that the perception of independent additive effects comprising the majority of the genetic architecture of complex traits is biased upwards and that the search for causal variants in complex traits under selection is potentially underpowered by parameterising for additive effects alone.Given dense SNP panels the detection of causal variants through genome-wide association studies may be improved by searching for epistatic effects explicitly.

View Article: PubMed Central - PubMed

Affiliation: The Roslin Institute and Royal (Dick) School of Veterinary Science, University of Edinburgh, Edinburgh, United Kingdom.

ABSTRACT
The relative importance between additive and non-additive genetic variance has been widely argued in quantitative genetics. By approaching this question from an evolutionary perspective we show that, while additive variance can be maintained under selection at a low level for some patterns of epistasis, the majority of the genetic variance that will persist is actually non-additive. We propose that one reason that the problem of the "missing heritability" arises is because the additive genetic variation that is estimated to be contributing to the variance of a trait will most likely be an artefact of the non-additive variance that can be maintained over evolutionary time. In addition, it can be shown that even a small reduction in linkage disequilibrium between causal variants and observed SNPs rapidly erodes estimates of epistatic variance, leading to an inflation in the perceived importance of additive effects. We demonstrate that the perception of independent additive effects comprising the majority of the genetic architecture of complex traits is biased upwards and that the search for causal variants in complex traits under selection is potentially underpowered by parameterising for additive effects alone. Given dense SNP panels the detection of causal variants through genome-wide association studies may be improved by searching for epistatic effects explicitly.

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Effect of LD on G-P map estimation.Different G-P maps of causal variants (rows of graphs) deterministically calculated from neighbouring SNPs in different levels of linkage disequilibrium (columns of graphs). All SNP and causal variant frequencies are set to 0.5. Rows 1–2: Canalisation; 3: ; 4: ; 5: .
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pgen-1003295-g003: Effect of LD on G-P map estimation.Different G-P maps of causal variants (rows of graphs) deterministically calculated from neighbouring SNPs in different levels of linkage disequilibrium (columns of graphs). All SNP and causal variant frequencies are set to 0.5. Rows 1–2: Canalisation; 3: ; 4: ; 5: .

Mentions: Figure 2b and Figure S6 show that although estimated genetic variance at observed SNPs decreases as LD with causal variants decreases, the estimated proportion of the variance that is additive actually increases. To illustrate this further Figure 3 shows how estimates of epistatic GP-maps change when LD is reduced, and two important biases can be shown.


An evolutionary perspective on epistasis and the missing heritability.

Hemani G, Knott S, Haley C - PLoS Genet. (2013)

Effect of LD on G-P map estimation.Different G-P maps of causal variants (rows of graphs) deterministically calculated from neighbouring SNPs in different levels of linkage disequilibrium (columns of graphs). All SNP and causal variant frequencies are set to 0.5. Rows 1–2: Canalisation; 3: ; 4: ; 5: .
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3585114&req=5

pgen-1003295-g003: Effect of LD on G-P map estimation.Different G-P maps of causal variants (rows of graphs) deterministically calculated from neighbouring SNPs in different levels of linkage disequilibrium (columns of graphs). All SNP and causal variant frequencies are set to 0.5. Rows 1–2: Canalisation; 3: ; 4: ; 5: .
Mentions: Figure 2b and Figure S6 show that although estimated genetic variance at observed SNPs decreases as LD with causal variants decreases, the estimated proportion of the variance that is additive actually increases. To illustrate this further Figure 3 shows how estimates of epistatic GP-maps change when LD is reduced, and two important biases can be shown.

Bottom Line: We propose that one reason that the problem of the "missing heritability" arises is because the additive genetic variation that is estimated to be contributing to the variance of a trait will most likely be an artefact of the non-additive variance that can be maintained over evolutionary time.We demonstrate that the perception of independent additive effects comprising the majority of the genetic architecture of complex traits is biased upwards and that the search for causal variants in complex traits under selection is potentially underpowered by parameterising for additive effects alone.Given dense SNP panels the detection of causal variants through genome-wide association studies may be improved by searching for epistatic effects explicitly.

View Article: PubMed Central - PubMed

Affiliation: The Roslin Institute and Royal (Dick) School of Veterinary Science, University of Edinburgh, Edinburgh, United Kingdom.

ABSTRACT
The relative importance between additive and non-additive genetic variance has been widely argued in quantitative genetics. By approaching this question from an evolutionary perspective we show that, while additive variance can be maintained under selection at a low level for some patterns of epistasis, the majority of the genetic variance that will persist is actually non-additive. We propose that one reason that the problem of the "missing heritability" arises is because the additive genetic variation that is estimated to be contributing to the variance of a trait will most likely be an artefact of the non-additive variance that can be maintained over evolutionary time. In addition, it can be shown that even a small reduction in linkage disequilibrium between causal variants and observed SNPs rapidly erodes estimates of epistatic variance, leading to an inflation in the perceived importance of additive effects. We demonstrate that the perception of independent additive effects comprising the majority of the genetic architecture of complex traits is biased upwards and that the search for causal variants in complex traits under selection is potentially underpowered by parameterising for additive effects alone. Given dense SNP panels the detection of causal variants through genome-wide association studies may be improved by searching for epistatic effects explicitly.

Show MeSH
Related in: MedlinePlus