ArticleEuropean journal of human genetics : EJHG2025
A genetic perspective on the recent demographic history of Ireland and Britain.
Article in European journal of human genetics : EJHG, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- What's new in April's EJHG?European journal of human genetics : EJHG · 2025Article
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11 authors.
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Abstract
While subtle yet discrete clusters of genetic identity across Ireland and Britain have been identified, their recent demographic history is unclear. Using genotype data from 6574 individuals with associated regional Irish or British ancestry, we identified genetic communities by applying Leiden community detection. Using haplotype segments segregated by length as proxy for time, we inferred regional Irish and British demographic histories. Using a subset of Irish participants, we provide genealogical context by estimating the enrichment/depletion of surnames within the Irish genetic communities. Through patterns of haplotype sharing, we find evidence of recent population bottlenecks in Orcadian, Manx and Welsh genetic communities. We observed temporal changes in genetic affinities within and between genetic communities in Ireland and Britain. Structure in Ireland is subtler compared to neighbouring British communities, with the Irish groups sharing relatively more short haplotype segments. In addition, we detected varying degrees of genetic isolation in peripheral Irish and British genetic communities across different time periods. Further, we observe a stable migration corridor between north-east Ireland and south-west Scotland while there is a recent migration barrier between south-east and west Ireland. Genealogical analysis of surnames in Ireland reflects history-Anglo-Norman surnames are enriched in the Wexford community while Scottish and Gallowglass surnames were enriched in the Ulster community. Using these new insights into the regional demographic history of Ireland and Britain across different time periods, we hope to understand the driving forces of rare allele frequencies and disease risk association within these populations.
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