A classifier for the SNP-based inference of ancestry.
Ancestral inference from DNA could serve as an important adjunct for both standard and future human identity testing procedures. However, current STR methods for the inference of ancestral affiliation have inherent statistical and technical limitations. In an effort to identify bi-allelic markers that can be used to infer ancestral affiliation from DNA, we screened 211 SNPs in the human pigmentation and xenobiotic metabolism genes. Allele frequencies of 56 SNPs (most from pigmentation genes) were dramatically different between groups of unrelated individuals of Asian, African, and European descent, and both observed and simulated log likelihood ratios revealed that the markers were of exceptional value for ancestral inference. Log likelihood ratios of the multilocus estimates of biological ancestry (EAE/EBA) ranged from 7 to 10, which are on par with the best of the STR batteries yet described. A linear classification method was developed for incorporating these SNPs into a classifier model that was 99, 98, and 100% accurate for identifying individuals of European, African, and Asian descent, respectively. The methods and markers we describe are therefore an important first step for the development of a practical multiplex test for the inference of ancestry in a forensics setting.
Frudakis
Tony
T
DNAPrint Genomics, Inc., 900 Cocoanut Ave, Sarasota, FL 34236, USA. tfrudakis@dnaprint.com
Venkateswarlu
K
K
Thomas
Matthew J
MJ
Gaskin
Zach
Z
Ginjupalli
Siva
S
Gunturi
Sitarama
S
Ponnuswamy
Viswanathan
V
Natarajan
Sivamiani
S
Nachimuthu
Ponnuswamy Kolathupalayam
PK
D000465:Algorithms; D004247:DNA / Q000302:isolation & purification*; D016172:DNA Fingerprinting / Q000379:methods; D005787:Gene Frequency; D005819:Genetic Markers; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D020641:Polymorphism, Single Nucleotide; D044469:Racial Groups / Q000235:genetics*; D017422:Sequence Analysis, DNA
D005819:Genetic Markers; D004247:DNA