Prediction of Eye Colour in Scandinavians Using the EyeColour 11 (EC11) SNP Set.
DNA phenotyping
eye colour
forensic genetics
pigmentation
rs12913832
Journal
Genes
ISSN: 2073-4425
Titre abrégé: Genes (Basel)
Pays: Switzerland
ID NLM: 101551097
Informations de publication
Date de publication:
27 05 2021
27 05 2021
Historique:
received:
12
05
2021
revised:
20
05
2021
accepted:
25
05
2021
entrez:
2
6
2021
pubmed:
3
6
2021
medline:
16
9
2021
Statut:
epublish
Résumé
Description of a perpetrator's eye colour can be an important investigative lead in a forensic case with no apparent suspects. Herein, we present 11 SNPs (Eye Colour 11-EC11) that are important for eye colour prediction and eye colour prediction models for a two-category reporting system (blue and brown) and a three-category system (blue, intermediate, and brown). The EC11 SNPs were carefully selected from 44 pigmentary variants in seven genes previously found to be associated with eye colours in 757 Europeans (Danes, Swedes, and Italians). Mathematical models using three different reporting systems: a quantitative system (PIE-score), a two-category system (blue and brown), and a three-category system (blue, intermediate, brown) were used to rank the variants. SNPs with a sufficient mean variable importance (above 0.3%) were selected for EC11. Eye colour prediction models using the EC11 SNPs were developed using leave-one-out cross-validation (LOOCV) in an independent data set of 523 Norwegian individuals. Performance of the EC11 models for the two- and three-category system was compared with models based on the IrisPlex SNPs and the most important eye colour locus, rs12913832. We also compared model performances with the IrisPlex online tool (IrisPlex Web). The EC11 eye colour prediction models performed slightly better than the IrisPlex and rs12913832 models in all reporting systems and better than the IrisPlex Web in the three-category system. Three important points to consider prior to the implementation of eye colour prediction in a forensic genetic setting are discussed: (1) the reference population, (2) the SNP set, and (3) the reporting strategy.
Identifiants
pubmed: 34071952
pii: genes12060821
doi: 10.3390/genes12060821
pmc: PMC8227851
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Références
PLoS One. 2020 Sep 11;15(9):e0239131
pubmed: 32915910
Curr Biol. 2009 Mar 10;19(5):R192-3
pubmed: 19278628
Forensic Sci Int Genet. 2014 Mar;9:111-7
pubmed: 24528589
Forensic Sci Int Genet. 2018 Jul;35:123-135
pubmed: 29753263
Forensic Sci Int Genet. 2019 May;40:192-200
pubmed: 30884346
Am J Hum Genet. 2008 Feb;82(2):424-31
pubmed: 18252222
Front Genet. 2021 Jan 12;11:568701
pubmed: 33510767
Hum Genet. 2008 Mar;123(2):177-87
pubmed: 18172690
Bioinformatics. 2005 Jan 15;21(2):263-5
pubmed: 15297300
Forensic Sci Int Genet. 2012 May;6(3):330-40
pubmed: 21813346
Forensic Sci Int Genet. 2017 May;28:138-145
pubmed: 28273506
Genome Res. 2012 Mar;22(3):446-55
pubmed: 22234890
Forensic Sci Int Genet. 2013 Jan;7(1):28-40
pubmed: 22709892
Forensic Sci Int Genet. 2020 Jan;44:102154
pubmed: 31670023
Forensic Sci Int Genet. 2013 Jan;7(1):98-115
pubmed: 22917817
Hum Genet. 2017 Jul;136(7):847-863
pubmed: 28500464
Forensic Sci Int Genet. 2013 Sep;7(5):508-15
pubmed: 23948321
Forensic Sci Int Genet. 2011 Jun;5(3):170-80
pubmed: 20457092
Theor Popul Biol. 2018 Mar;120:1-10
pubmed: 29278682
Mol Genet Genomic Med. 2016 Mar 11;4(4):420-30
pubmed: 27468418
Forensic Sci Int Genet. 2015 Sep;18:33-48
pubmed: 25716572
Forensic Sci Int Genet. 2014 Jul;11:1-6
pubmed: 24631691