arXiv:1504.04543 [q-bio.PE]
Detecting genomic signatures of natural selection with principal component analysis: application to the 1000 Genomes data
Nicolas Duforet-Frebourg et al.
(Submitted on 8 Apr 2015)
Large-scale genomic data offers the perspective to decipher the genetic architecture of natural selection. To characterize natural selection, various analytical methods for detecting candidate genomic regions have been developed. We propose to perform genome-wide scans of natural selection using principal component analysis. We show that the common Fst index of genetic differentiation between populations can be viewed as a proportion of variance explained by the principal components. Looking at the correlations between genetic variants and each principal component provides a conceptual framework to detect genetic variants involved in local adaptation without any prior definition of populations. To validate the PCA-based approach, we consider the 1000 Genomes data (phase 1) after removal of recently admixed individuals resulting in 850 individuals coming from Africa, Asia, and Europe. The number of genetic variants is of the order of 36 millions obtained with a low-coverage sequencing depth (3X). The correlations between genetic variation and each principal component provide well-known targets for positive selection (EDAR, SLC24A5, SLC45A2, DARC), and also new candidate genes (APPBPP2, TP1A1, RTTN, KCNMA, MYO5C) and non-coding RNAs. In addition to identifying genes involved in biological adaptation, we identify two biological pathways involved in polygenic adaptation that are related to the innate immune system (beta defensins) and to lipid metabolism (fatty acid omega oxidation). PCA-based statistics retrieve well-known signals of human adaptation, which is encouraging for future whole-genome sequencing project, especially in non-model species for which defining populations can be difficult. Genome scan based on PCA is implemented in the open-source and freely available PCAdapt software.
Link
bioRxiv http://dx.doi.org/10.1101/018143
Fast principal components analysis reveals independent evolution of ADH1B gene in Europe and East Asia
Kevin J Galinsky et al.
Principal components analysis (PCA) is a widely used tool for inferring population structure and correcting confounding in genetic data. We introduce a new algorithm, FastPCA, that leverages recent advances in random matrix theory to accurately approximate top PCs while reducing time and memory cost from quadratic to linear in the number of individuals, a computational improvement of many orders of magnitude. We apply FastPCA to a cohort of 54,734 European Americans, identifying 5 distinct subpopulations spanning the top 4 PCs. Using a new test for natural selection based on population differentiation along these PCs, we replicate previously known selected loci and identify three new signals of selection, including selection in Europeans at the ADH1B gene. The coding variant rs1229984 has previously been associated to alcoholism and shown to be under selection in East Asians; we show that it is a rare example of independent evolution on two continents.
Link
3 comments:
Just a note: It took some digging to figure out which allele of this SNP is the 'dangerous' one. The G or C allele (depending on reading frame) is the ancestral allele, which codes for normal breakdown of alcohol, plus higher 'bad' cholesterol. The derived A or T allele causes alcohol to be broken down more slowly, so a person who is homozygous for it could become drunk much more quickly, and run into problems like alcohol poisoning, plus they have less bad cholesterol. This is considered "good," because alcohol making one feel ill quicker reduces the risk of alcoholism, plus the derived allele also helps protect against cardiovascular disease.
Unfortunately for me, I have the plain Ancestral variants of both this, and the acetaldehyde quick breakdown gene, meaning I could in theory have a higher risk of becoming an alcoholic, as my paternal family tends to be.
This isn't independent evolution. It's Neanderthal descent. God, it is so hilarious to watch them scramble for answers.
@dwaggonerstr:This isn't independent evolution. It's Neanderthal descent
I don't think you understand what this paper is saying. The rs1229984 allele isn't widespread in Europe, it's found only in subpopulations and has very different frequencies and very different haplotypes to those found in East Asians. Whether the allele was originally introgressed from Neanderthals* or not isn't really relevant - it's subsequent increase in frequency in East Asians and in Europeans appears to be via different paths. Have a look at Supplementary Table 8 and you'll see what they're getting at.
* Do you have for this in the first place? I couldn't find any reference to Neanderthals being derived at this locus.
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