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PLoS One. 2018 Apr 23;13(4):e0195491. doi: 10.1371/journal.pone.0195491. eCollection 2018.

Estimating genetic kin relationships in prehistoric populations.

Author information

1
Uppsala University, Evolutionary Biology Centre, Department of Organismal Biology, Norbyvägen 18C, SE-752 36 Uppsala, Sweden.
2
Uppsala University, SciLifeLab, Norbyvägen 18C, SE-752 36 Uppsala, Sweden.

Abstract

Archaeogenomic research has proven to be a valuable tool to trace migrations of historic and prehistoric individuals and groups, whereas relationships within a group or burial site have not been investigated to a large extent. Knowing the genetic kinship of historic and prehistoric individuals would give important insights into social structures of ancient and historic cultures. Most archaeogenetic research concerning kinship has been restricted to uniparental markers, while studies using genome-wide information were mainly focused on comparisons between populations. Applications which infer the degree of relationship based on modern-day DNA information typically require diploid genotype data. Low concentration of endogenous DNA, fragmentation and other post-mortem damage to ancient DNA (aDNA) makes the application of such tools unfeasible for most archaeological samples. To infer family relationships for degraded samples, we developed the software READ (Relationship Estimation from Ancient DNA). We show that our heuristic approach can successfully infer up to second degree relationships with as little as 0.1x shotgun coverage per genome for pairs of individuals. We uncover previously unknown relationships among prehistoric individuals by applying READ to published aDNA data from several human remains excavated from different cultural contexts. In particular, we find a group of five closely related males from the same Corded Ware culture site in modern-day Germany, suggesting patrilocality, which highlights the possibility to uncover social structures of ancient populations by applying READ to genome-wide aDNA data. READ is publicly available from https://bitbucket.org/tguenther/read.

PMID:
29684051
PMCID:
PMC5912749
DOI:
10.1371/journal.pone.0195491
[Indexed for MEDLINE]
Free PMC Article

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