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 (PCA). We show that the common FST index of genetic differentiation between populations can be viewed as the proportion of variance explained by the principal components. Considering 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) considering 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 (3×). 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 noncoding 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). An additional analysis of European data shows that a genome scan based on PCA retrieves classical examples of local adaptation even when there are no well-defined populations. PCA-based statistics, implemented in the PCAdapt R package and the PCAdapt fast open-source software, retrieve well-known signals of human adaptation, which is encouraging for future whole-genome sequencing project, especially when defining populations is difficult.
Detecting Genomic Signatures of Natural Selection with Principal Component Analysis: Application to the 1000 Genomes Data
N. Duforet-Frebourg,Keurcien Luu,G. Laval,Eric Bazin,M. Blum
Published 2015 in Molecular biology and evolution
ABSTRACT
PUBLICATION RECORD
- Publication year
2015
- Venue
Molecular biology and evolution
- Publication date
2015-04-08
- Fields of study
Biology, Medicine
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
CITATION MAP
EXTRACTION MAP
CLAIMS
CONCEPTS
- 1000 genomes data (phase 1)
The human whole-genome sequence dataset from the first phase of the 1000 Genomes Project used as the study's main application data.
Aliases: 1000 Genomes phase 1, 1000 Genomes Project phase 1
- fst index
A population-differentiation statistic used here as a reference for explaining variance across principal components.
Aliases: FST, F_ST
- innate immune system
The host defense pathway category whose beta-defensin-related genes are discussed as a polygenic adaptation signal.
Aliases: innate immunity
- lipid metabolism
The metabolic pathway category whose fatty-acid omega-oxidation component is discussed as a polygenic adaptation signal.
Aliases: fatty acid omega oxidation
- local adaptation
Adaptation driven by selection in specific environments or populations that leaves locus-specific genetic signals.
Aliases: local adaptation signals
- pcadapt
The R package and open-source software implementing the PCA-based statistics described in the abstract.
Aliases: PCAdapt R package, PCAdapt fast open-source software
- positive selection
Selection that increases the frequency of advantageous genetic variants and can create detectable genomic signatures.
Aliases: selection
- principal component analysis
A multivariate method that summarizes genetic variation into orthogonal components used here to scan the genome.
Aliases: PCA
REFERENCES
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