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Spatially Explicit Models to Investigate Geographic Patterns in the Distribution of Forensic STRs

Authors :
Emmanuel I. Michalodimitrakis
Radim Brdicka
Aphrodite Loutradis
Andrea Novelletto
Carla Jodice
Andrea Finocchio
Nejat Akar
Francesco Messina
Publication Year :
2016
Publisher :
Cold Spring Harbor Laboratory, 2016.

Abstract

Human forensic STRs are used for individual identification but have been reported to have little power for inter-population analyses. Several methods have been developed which incorporate information on the spatial distribution of individuals to arrive at a description of the arrangement of diversity. We genotyped at 16 forensic STRs a large population sample obtained from many locations in Italy, Greece and Turkey, i.e. three countries seldom represented together in previous studies. Using spatial PCA on the full dataset, we detected patterns of population affinities in the area similar to those of genome-wide SNP and STR studies. Additionally, we devised objective criteria to reduce the overall complexity into reduced datasets. Independent spatially explicit methods applied to these latter datasets converged in showing that the extraction of information on long-to medium-range geographical trends and structuring from the overall diversity is possible. All analyses returned the picture of a background clinal variation, with regional discontinuities captured by each of the reduced datasets. These coincided with the main bodies of water, i.e. the Adriatic/Ionian and the Aegean Seas. High levels of gene flow were inferred within the main continental areas by coalescent simulations. These results are promising in a microevolutionary perspective, in view of the fast pace at which forensic data are being accumulated for many locales. It is foreseeable that this will allow the exploitation of an invaluable genotypic resource, assembled for other (forensic) purposes, to clarify important aspects in the formation of local gene pools.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....b208861e2e65e5f49b45ce9a46871791
Full Text :
https://doi.org/10.1101/051375