Journal Article

Integrated analysis of sequence evolution and population history using hypervariable compound haplotypes

Emma J. Rogers, Angela C. Shone, Santos Alonso, Celia A. May and John A.L. Armour

in Human Molecular Genetics

Volume 9, issue 18, pages 2675-2681
Published in print November 2000 | ISSN: 0964-6906
Published online November 2000 | e-ISSN: 1460-2083 | DOI:
Integrated analysis of sequence evolution and population history using hypervariable compound haplotypes

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We have examined compound haplotypes from a highly informative region of human chromosome 16, in which information from the rapid evolution of a highly unstable minisatellite is integrated with data on the longer-term evolution of this segment from 10 flanking substitutional polymorphisms. Combined with sequence data from non-human primates, analysis of relationships between these compound haplotypes allows the reconstruction of a rooted network of the evolutionary pathways between them. Most relationships can be explained via simple substitutional mutations, although the origins of some haplotypes involve recurrent events at a hotspot for substitutional mutation and/or gene conversion. For compound haplotypes including the minisatellite array, the network found in a range of world-wide populations constitutes a highly informative data set for the analysis of population history (437 different compound haplotypes were discriminated among 658 studied). Since the mutation rates and processes of the minisatellite array are known from direct studies, ages for individual lineages have been estimated using associated minisatellite diversity. These analyses suggest that the higher information content and sampling depth of these compound haplotypes may allow more precise calibration of lineage ages than is possible using coalescent analysis of DNA sequence. Using this method we have dated the oldest Eurasian lineage as 52 000–66 000 years and the oldest European specific lineage as 37 600–56 200 years.

Journal Article.  4286 words.  Illustrated.

Subjects: Genetics and Genomics

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