Evaluate 11 Plex SNPs of the MC1R Gene for Eye Color Prediction using the SNaPshot Technique in an Iranian Population

Authors

  • Hassan Zamanifar PhD in Molecular Genetics, Research Assistant Department of Genetics, Rey Payam Noor University
  • Alireza Rafati PhD in Medical Biotechnology, Research Assistant, Department of Medical Biotechnology and Molecular Medicine, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences,Tehran, Iran, PhD in Medical Biotechnology, Research Assistant Department of Medical Genetics, Sirjan School of Medical Sciences, Sirjan, Iran
  • Sara Hekmatshoar PhD in Medical Biotechnology, Research Assistant Department of Medical Genetics, Sirjan School of Medical Sciences, Sirjan, Iran
  • Sayed Mostafa Hosseini MSc of Genetics, Student, Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran

DOI:

https://doi.org/10.37506/dy17mj74

Keywords:

Hair color,, Eye color, MC1R, Iranian Population, SNaPshot

Abstract

The most ambitious DNA phenotyping goal is forecasting a full face from a DNA sample. Over the last decade, GWAS and successive predictive analyses have discovered a multitude of EVC-predictive SNPs and predictive models, most particularly for human pigmentation features. IrisPlex, the first forensic eye color prediction system, was designed mainly to differentiate between blue and brown eyes, and its evolved version, the HirisPlex-S DNA testing method, predicts eye, hair, and skin color based on DNA traces. 59 DNA samples were examined using the Multiplex SnaPshot kit (Applied Biosystems) for the simultaneous detection of 11 SNPs (rs1805005, rs885479, rs11547464, rs185008, rs1805006, rs1805007, rs1805009, rs2228479, rs1110400) taken from a large-scale GWAS research. This study adopted the genotype identification of 11 Hirisplex system markers as a prediction model of eye color and hair color. Some of these variants (rs11547464, rs885479, rs1805005, rs2228479) were found to be relevant for anticipating eye and hair color, whereas others (rs1805008, rs1805006, rs1805007, rs1805009, rs1110400, Y1520CH, N29insA) were observed to be unacceptable because of low variation. The statistical data illustrated a substantial level of agreement between the statistical model and the actual eye color of the participants.

Author Biographies

  • Hassan Zamanifar, PhD in Molecular Genetics, Research Assistant Department of Genetics, Rey Payam Noor University

    PhD in Molecular Genetics, Research Assistant Department of Genetics, Rey Payam Noor University

  • Alireza Rafati, PhD in Medical Biotechnology, Research Assistant, Department of Medical Biotechnology and Molecular Medicine, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences,Tehran, Iran, PhD in Medical Biotechnology, Research Assistant Department of Medical Genetics, Sirjan School of Medical Sciences, Sirjan, Iran

    PhD in Medical Biotechnology, Research Assistant, Department of Medical Biotechnology and Molecular Medicine, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences,Tehran, Iran, PhD in Medical Biotechnology, Research Assistant Department of Medical Genetics, Sirjan School of Medical Sciences, Sirjan, Iran

  • Sara Hekmatshoar, PhD in Medical Biotechnology, Research Assistant Department of Medical Genetics, Sirjan School of Medical Sciences, Sirjan, Iran
    • PhD in Medical Biotechnology, Research Assistant Department of Medical Genetics, Sirjan School of Medical Sciences, Sirjan, Iran
  • Sayed Mostafa Hosseini, MSc of Genetics, Student, Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran

    MSc of Genetics, Student, Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran

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Published

2026-04-23

How to Cite

Evaluate 11 Plex SNPs of the MC1R Gene for Eye Color Prediction using the SNaPshot Technique in an Iranian Population. (2026). Indian Journal of Forensic Medicine & Toxicology, 20(2), 52-59. https://doi.org/10.37506/dy17mj74