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. 2010 Mar 1;55(2):315-22.
doi: 10.1111/j.1556-4029.2009.01317.x. Epub 2010 Feb 11.

Predicting phenotype from genotype: normal pigmentation

Robert K Valenzuela  1 , Miquia S Henderson, Monica H Walsh, Nanibaa' A Garrison, Jessica T Kelch, Orit Cohen-Barak, Drew T Erickson, F John Meaney, J Bruce Walsh, Keith C Cheng, Shosuke Ito, Kazumasa Wakamatsu, Tony Frudakis, Matthew Thomas, Murray H Brilliant
Affiliations

Predicting phenotype from genotype: normal pigmentation

Robert K Valenzuela et al. J Forensic Sci. .

Abstract

Genetic information in forensic studies is largely limited to CODIS data and the ability to match samples and assign them to an individual. However, there are circumstances, in which a given DNA sample does not match anyone in the CODIS database, and no other information about the donor is available. In this study, we determined 75 SNPs in 24 genes (previously implicated in human or animal pigmentation studies) for the analysis of single- and multi-locus associations with hair, skin, and eye color in 789 individuals of various ethnic backgrounds. Using multiple linear regression modeling, five SNPs in five genes were found to account for large proportions of pigmentation variation in hair, skin, and eyes in our across-population analyses. Thus, these models may be of predictive value to determine an individual's pigmentation type from a forensic sample, independent of ethnic origin.

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Conflict of interest statement

Conflict of Interest Statement

Dr. Tony Frudakis is and Dr. Matthew Thomas was an employee and shareholder of a company, DNAPrint, which performs forensic DNA analysis.

Figures

FIG. 1
FIG. 1
Flow diagram of method for determining three-SNP multiple linear regression models.
FIG. 2
FIG. 2
Three-SNP multiple linear regression (MLR) models for four pigmentation traits across populations. In each panel, the horizontal-axis depicts all 9880 combinations of significant SNPs in a three-SNP MLR model (i.e., 40 choose 3). The vertical-axis is the R2 value for each model. The three SNPs that occurred most frequently in the models with the highest R2 values are indicated by the colored bar insets. Each model contained rs16891982 (SLC45A2) in red. (A) Hair total melanin’s second and third SNPs were rs1426654 (SLC24A5) in green, and rs12913832 (HERC2) in blue, model R2 value of 76.3%. (B) Natural log of hair melanin ratio’s second and third SNPs were rs1426654 (SLC24A5) and rs1805007 (MC1R) in black, model R2 value of 43.2%. (C) Skin reflectance’s second and third SNPs were rs1426654 (SLC24A5) and rs2424984 (ASIP) in brown, model R2 value of 45.7%. (D) Eye color’s SNP was rs12913832 (HERC2) in blue, model R2 value of 74.8%. The second and third SNPs rs16891982 (SLC45A2) and rs1426654 (SLC24A5) only marginally increased the model R2 value to 76.4%.
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