Analysis of 17 STR data on 5362 southern Portuguese individuals—an update on reference database

• Published in: Forensic science international : genetics Vol. 21; pp. e10 - e12
• Main Authors: Cabezas Silva, Raquel, Ribeiro, Teresa, Lucas, Isabel, Porto, Maria João, Costa Santos, Jorge, Dario, Paulo
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ireland Ltd 01.03.2016
• Subjects: Databases, Genetic; Forensic Genetics - methods; Gene Frequency; Genetic Variation; Genetics, Population - methods; Humans; Identifiler; Microsatellite Repeats; Pathology; Phylogeny; Polymerase Chain Reaction; Population data update; Population genetics; Portugal; Powerplex® 16; Reference Values; Identifiler; Powerplex ® 16; Population genetics; Portugal; Population data update; Powerplex® 16; Identifiler(®); Powerplex(®) 16
• ISSN: 1872-4973; 1878-0326
• DOI: 10.1016/j.fsigen.2015.11.007

ABSTRACT The main objective of this work consisted of the updating of allele frequencies and other relevant forensic parameters for the 17 autosomal STR loci provided by the combination of the two types of kits used routinely in our laboratory casework: AmpF/STR Identifiler® and the Powerplex® 16 Systems. This aim was of significant importance, given that the last study on these kits within the southern Portuguese population dates back to 2006, and, as a consequence, it was necessary to correct the deviation caused by population evolution over the last ten years so that they might be better applied to our forensic casework. For this reason genetic data from 5362 unrelated Caucasian Portuguese individuals from the south of Portugal who were involved in paternity testing casework from 2005 to 2014 was used. Of all the markers, TPOX proved to be the least polymorphic, and Penta E the most. Secondly, this up-to-date southern Portuguese population was compared not only with the northern and central Portuguese populations, but also with that of southern Portugal in 2006, along with populations from Spain, Italy, Greece, Romania, Morocco, Angola and Korea in order to infer information about the relatedness of these respective populations, and the variation of the southern Portuguese population over time.