| Literature DB >> 29658972 |
Diana María Hohl1,2, Brenda Bezus1, Julia Ratowiecki3, Cecilia Inés Catanesi1,4.
Abstract
The aim of this work was to describe the phenotypic and genotypic variability related to iris color for the population of Buenos Aires province (Argentina), and to assess the usefulness of current methods of analysis for this country. We studied five Single Nucleotide Polymorphisms (SNPs) included in the IrisPlex kit, in 118 individuals, and we quantified eye color with Digital Iris Analysis Tool. The markers fit Hardy-Weinberg equilibrium for the whole sample, but not for rs12913832 within the group of brown eyes (LR=8.429; p=0.004). We found a remarkable association of HERC2 rs12913832 GG with blue color (p < 0.01) but the other markers did not show any association with iris color. The results for the Buenos Aires population differ from those of other populations of the world for these polymorphisms (p < 0,01). The differences we found might respond to the admixed ethnic composition of Argentina; therefore, methods of analysis used in European populations should be carefully applied when studying the population of Argentina. These findings reaffirm the importance of this investigation in the Argentinian population for people identification based on iris color.Entities:
Year: 2018 PMID: 29658972 PMCID: PMC5901501 DOI: 10.1590/1678-4685-GMB-2017-0175
Source DB: PubMed Journal: Genet Mol Biol ISSN: 1415-4757 Impact factor: 1.771
Figure 1Histogram of distribution of iris color variation. X axis: PIE-score (Pixel Index of the Eye) ranged from -1 to 1 (i.e. from brown to blue, respectively). Y axis: Number of individuals with each PIE-score value.
Genotypic frequencies for five markers related to eye color. n: sample size.
| Marker | Genotype | Blue eyes | Brown eyes | Population frequency |
|---|---|---|---|---|
| rs12913832 | AA | 0.0000 ± 0.0000 | 0.47826 ± 0.05207 | 0.38261 ± 0.04532 |
| n=115 | AG | 0.17391 ± 0.07903 | 0.48913 ± 0.05212 | 0.42609 ± 0.04611 |
| GG | 0.82608 ± 0.07903 | 0.03261 ± 0.01851 | 0.19130 ± 0.03668 | |
| rs12203592 | CC | 0.78261 ± 0.08601 | 0.84783 ± 0.03745 | 0.83478 ± 0.03463 |
| n=115 | CT | 0.17391 ± 0.07903 | 0.13043 ± 0.03511 | 0.13913 ± 0.03227 |
| TT | 0.04348 ± 0.04252 | 0.02174 ± 0.01520 | 0.02609 ± 0.01486 | |
| rs12896399 | GG | 0.47619 ± 0.10899 | 0.46914 ± 0.05545 | 0.47059 ± 0.04942 |
| n=102 | GT | 0.28571 ± 0.09858 | 0.41975 ± 0.05484 | 0.39216 ± 0.048342 |
| TT | 0.23810 ± 0.09294 | 0.11111 ± 0.03492 | 0.137250.03407 | |
| rs16891982 | CC | 0.00000 ± 0.00000 | 0.04396 ± 0.02149 | 0.03509 ± 0.01723 |
| n=114 | CG | 0.30435 ± 0.09594 | 0.32967 ± 0.04928 | 0.32456 ± 0.04385 |
| GG | 0.69565 ± 0.09594 | 0.62637 ± 0.05071 | 0.64035 ± 0.04495 | |
| rs1393350 | AA | 0.08696 ± 0.05875 | 0.07692 ± 0.02793 | 0.07895 ± 0.02526 |
| n=114 | AG | 0.47826 ± 0.10416 | 0.26374 ± 0.04619 | 0.30702 ± 0.04320 |
| GG | 0.43478 ± 0.10337 | 0.65934 ± 0.04968 | 0.61403 ± 0.04560 |
Results from median regression. REF: reference variable, sd: standard deviation, IC95: 95% confidence interval. *: removed from the analysis for being unrepresentative.
| Marker | Genotype | Coefficient | sd | P-value | IC95 |
|---|---|---|---|---|---|
| rs12913832 | AA | REF | REF | REF | REF |
| AG | 0.02 | 0.08 | 0.77 | [(-0.13) – 0.18] | |
| GG | 1.82 | 0.1 | < 0.01 | [1.62 – 2.01] | |
| rs12203592 | CC | REF | REF | REF | REF |
| CT | 0.03 | 0.1 | 0.8 | [(-0.17) – 0.23] | |
| TT | * | * | * | * | |
| rs12896399 | GG | REF | REF | REF | REF |
| GT | -0.02 | 0.08 | 0.83 | [(-0.17) – 0.14] | |
| TT | 0.04 | 0.11 | 0.7 | [(-0.17) – 0.26] | |
| rs16891982 | CC | * | * | * | * |
| CG | 0.02 | 0.08 | 0.83 | [(-0.14) – 0.18] | |
| GG | REF | REF | REF | REF | |
| rs1393350 | AA | 0 | 0.13 | 0.98 | [(-0.26) – 0.25] |
| AG | 0.01 | 0.08 | 0.85 | [(-0.14) – 0.17] | |
| GG | REF | REF | REF | REF |
Fst values obtained from interpopulation comparison. *p=0.00000. All values are significative, except for **p=0.01802 ± 0.0121.
| Buenos Aires | Africa | America | Europe | East Asia | |
|---|---|---|---|---|---|
| Buenos Aires | 0 | ||||
| Africa | 0.28325* | 0 | |||
| America | 0.11023* | 0.17090* | 0 | ||
| Europe | 0.20880* | 0.52826* | 0.38470* | 0 | |
| East Asia | 0.21005* | 0.15482* | 0.02330** | 0.50612* | 0 |
Most probable K (in bold letter) of the Structure analysis shown above. Performed with Structure Harvester
| K | Reps | Mean LnP(K) | Stdev LnP(K) | Ln’(K) | Ln’’(K) | Delta K |
|---|---|---|---|---|---|---|
| 2 | 20 | -2198.195000 | 28.852738 | — | — | — |
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| 4 | 20 | -2269.855000 | 136.131942 | 134.525000 | 87.505000 | 0.642795 |
| 5 | 20 | -2222.835000 | 114.639555 | 47.020000 | — | — |
Figure 2Structure analysis of different populations: 1-African, 2-Native American, 3-East Asian, 4-European, 5-Buenos Aires. Each color represents an assumed ancestral population. Each individual is represented by a single vertical line divided into K segments of different colors.
Figure 3MDS matrix performed with Past. The distance among populations is calculated from Fst. Stress value=0.