The HIrisPlex-S system for eye, hair and skin colour prediction from DNA: Introduction and forensic developmental validation
Open accessAbstract
Forensic DNA Phenotyping (FDP), i.e. the prediction of human externally visible traits from DNA, has become a fast growing subfield within forensic genetics due to the intelligence information it can provide from DNA traces. FDP outcomes can help focus police investigations in search of unknown perpetrators, who are generally unidentifiable with standard DNA profiling. Therefore, we previously developed and forensically validated the IrisPlex DNA test system for eye colour prediction and the HIrisPlex system for combined eye and hair colour prediction from DNA traces. Here we introduce and forensically validate the HIrisPlex-S DNA test system (S for skin) for the simultaneous prediction of eye, hair, and skin colour from trace DNA. This FDP system consists of two SNaPshot-based multiplex assays targeting a total of 41 SNPs via a novel multiplex assay for 17 skin colour predictive SNPs and the previous HIrisPlex assay for 24 eye and hair colour predictive SNPs, 19 of which also contribute to skin colour prediction. The HIrisPlex-S system further comprises three statistical prediction models, the previously developed IrisPlex model for eye colour prediction based on 6 SNPs, the previous HIrisPlex model for hair colour prediction based on 22 SNPs, and the recently introduced HIrisPlex-S model for skin colour prediction based on 36 SNPs. In the forensic developmental validation testing, the novel 17-plex assay performed in full agreement with the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, as previously shown for the 24-plex assay. Sensitivity testing of the 17-plex assay revealed complete SNP profiles from as little as 63 pg of input DNA, equalling the previously demonstrated sensitivity threshold of the 24-plex HIrisPlex assay. Testing of simulated forensic casework samples such as blood, semen, saliva stains, of inhibited DNA samples, of low quantity touch (trace) DNA samples, and of artificially degraded DNA samples as well as concordance testing, demonstrated the robustness, efficiency, and forensic suitability of the new 17-plex assay, as previously shown for the 24-plex assay. Finally, we provide an update to the publically available HIrisPlex website https://hirisplex.erasmusmc.nl/, now allowing the estimation of individual probabilities for 3 eye, 4 hair, and 5 skin colour categories from HIrisPlex-S input genotypes. The HIrisPlex-S DNA test represents the first forensically validated tool for skin colour prediction, and reflects the first forensically validated tool for simultaneous eye, hair and skin colour prediction from DNA.
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Skin color was associated with cognitive ability in monoracial African-Americans (Model 1b).
“Skin color (assessed genetically with the highly accurate predictor [79,93] was associated with cognitive ability (Model 1b, Table 5), but made no significant incremental contribution when ancestry was also in the model (Model 2, Table 5).”
From Global Ancestry and Cognitive Ability (2019) · cites this paper as [79]
Skin color made no significant incremental contribution to cognitive ability when ancestry was also in the model.
“Skin color (assessed genetically with the highly accurate predictor [79,93] was associated with cognitive ability (Model 1b, Table 5), but made no significant incremental contribution when ancestry was also in the model (Model 2, Table 5).”
From Global Ancestry and Cognitive Ability (2019) · cites this paper as [79]
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BackgroundMethodInfluentialExtensive pedigrees reveal the social organization of a Neolithic community
Rivollat, M., Rohrlach, A. B., Ringbauer, H., Childebayeva, A., Mendisco, F., Barquera, R., Szolek, A., Roy, M. L., Colleran, H., Tuke, J., et al. (2023) · Nature · doi:10.1038/s41586-023-06350-8 · Cited by 108 · see citing works
“We investigated genotypes of 72 SNPs associated with phenotypes of interest in all individuals 42,63 , including the HIris-Plex-S SNPs to predict the pigmentation of skin, eyes and hair 64–66 .”
Bronze and Iron Age population movements underlie Xinjiang population history
Kumar, V., Wang, W., Zhang, J., Wang, Y., Ruan, Q., JianJun, Y., Wu, X., Hu, X., Wu, X., Guo, W., et al. (2022) · Science · doi:10.1126/science.abk1534 · Cited by 111 · see citing works
Self-citationDevelopments in forensic DNA analysis
Haddrill, P. (2021) · Emerging Topics in Life Sciences · doi:10.1042/etls20200304 · Cited by 83 · see citing works
Genetic ancestry changes in Stone to Bronze Age transition in the East European plain
Saag, L., Vasilyev, S., Varul, L., Kosorukova, N., Gerasimov, D., Oshibkina, S., Griffith, S. J., Solnik, A., Saag, L., D'Atanasio, E., et al. (2020) · Science Advances · doi:10.1101/2020.07.02.184507 · Cited by 77
Breslin, K., Wills, B., Ralf, A., García, M. V., Kukla-Bartoszek, M., Pośpiech, E., Freire-Aradas, A., Xavier, C., Ingold, S., de la Puente, M., et al. (2019) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2019.102152 · Cited by 73
Self-citationThe genomic history of the Aegean palatial civilizations
Clemente, F., Unterländer, M., Dolgova, O., Amorim, C. E. G., Coroado-Santos, F., Neuenschwander, S., Ganiatsou, E., Dávalos, D. I. C., Anchieri, L., Michaud, F., et al. (2021) · Cell · doi:10.1016/j.cell.2021.03.039 · Cited by 77 · see citing works
“We compared our dataset with the 41 SNPs published as HIrisPlex-S (Chaitanya et al., 2018;Walsh et al., 2017) and found an overlap of 30 SNPs (Table S1, ‘‘Nuclear capture’’ tab).”
ResultXavier, C., de la Puente, M., Mosquera-Miguel, A., Freire-Aradas, A., Kalamara, V., Vidaki, A., Gross, T., Revoir, A., Pośpiech, E., Kartasińska, E., et al. (2020) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2020.102336 · Cited by 67 · see citing works
“Recently, a non-commercial MPS application of the HIrisPlex-S SNP panel for simultaneous prediction of eye, hair and skin color was published [25] for both the AmpliSeq-based Ion S5 System (Thermo Fisher Scientific) as well as the MiSeq FGx (Illumina) MPS platforms.”
MethodSelf-citationA genetic probe into the ancient and medieval history of Southern Europe and West Asia
Lazaridis, I., Alpaslan-Roodenberg, S., Acar, A., Açıkkol, A., Agelarakis, A. P., Aghikyan, L., Akyüz, U., Andreeva, D., Andrijašević, G., Antonović, D., et al. (2022) · Science · doi:10.1126/science.abq0755 · Cited by 127 · see citing works
Self-citationMalmström, H., Günther, T., Svensson, E., Juras, A., Fraser, M., Munters, A. R., Pospieszny, Ł., Tõrv, M., Lindström, J., Götherström, A., et al. (2019) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2019.1528 · Cited by 105 · see citing works
“Ancestry and admixture were assessed using principal component analyses, unsupervised ADMIXTURE [41], and admixture proportions were estimated using ADMIXTOOLS’ qpWave and qpAdm [1,44], and phenotypic variation was investigated [61,62].”
MethodWatherston, J., McNevin, D., Gahan, M., Bruce, D., & Ward, J. (2018) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2018.08.016 · Cited by 63 · see citing works
Villalba‐Mouco, V., Caravatti, C. O., Herrada, C. R., Childebayeva, A., Rohrlach, A. B., Fregeiro, M. I., Beltrán, E. C., Felipe, C. V., Aron, F., Himmel, M., et al. (2021) · Science Advances · doi:10.1126/sciadv.abi7038 · Cited by 87 · see citing works
Saupe, T., Montinaro, F., Scaggion, C., Carrara, N., Kivisild, T., D’Atanasio, E., Hui, R., Solnik, A., Lebrasseur, O., Larson, G., et al. (2021) · Current Biology · doi:10.1016/j.cub.2021.04.022 · Cited by 61 · see citing works
“HIrisPlex-S Chaitanya et al.(89) and Walsh et al.”
Skin colour and vitamin D: An update
Hänel, A., & Carlberg, C. (2020) · Experimental Dermatology · doi:10.1111/exd.14142 · Cited by 76 · see citing works
Naqvi, S., Hoskens, H., Wilke, F., Weinberg, S. M., Shaffer, J. R., Walsh, S., Shriver, M. D., Wysocka, J., & Claes, P. D. (2022) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-120121-102607 · Cited by 52 · see citing works
“The simultaneous prediction of eye, hair, and skin color has already been validated forensically (20).”
BackgroundSelf-citationInterpol review of forensic biology and forensic DNA typing 2016-2019
Butler, J., & Willis, S. M. (2020) · Forensic Science International: Synergy · doi:10.1016/j.fsisyn.2019.12.002 · Cited by 53 · see citing works
McCord, B., Gauthier, Q., Cho, S., Roig, M. N., Gibson-Daw, G. C., Young, B., Taglia, F., Zapico, S. C., Mariot, R., Lee, S. B., et al. (2018) · Analytical Chemistry · doi:10.1021/acs.analchem.8b05318 · Cited by 52 · see citing works
Population Genetics and Signatures of Selection in Early Neolithic European Farmers
Childebayeva, A., Rohrlach, A. B., Barquera, R., Rivollat, M., Aron, F., Szolek, A., Kohlbacher, O., Nicklisch, N., Alt, K. W., Gronenborn, D., et al. (2022) · Molecular Biology and Evolution · doi:10.1093/molbev/msac108 · Cited by 49 · see citing works
“We determined genotype likelihoods for a select number of SNPs associated with genetic adaptation, including lactase persistence, metabolic adaptation, among others, as well as SNPs associated with phenotypic traits as determined by the H-IrisplexS platform (Walsh et al. 2014; Chaitanya et al. 2018) (supplementary fig.”
Xavier, C., Eduardoff, M., Bertoglio, B., Amory, C., Berger, C., Casas-Vargas, A., Pallua, J., & Parson, W. (2021) · Genes · doi:10.3390/genes12020146 · Cited by 50 · see citing works
Seguin‐Orlando, A., Donat, R., Sarkissian, C. S. I. D., Southon, J. R., Thèves, C., Manen, C., Tchérémissinoff, Y., Crubézy, É., Shapiro, B., Deleuze, J., et al. (2021) · Current Biology · doi:10.1016/j.cub.2020.12.015 · Cited by 53 · see citing works
DNA-based predictive models for the presence of freckles
Kukla‐Bartoszek, M., Pośpiech, E., Woźniak, A., Boroń, M., Karłowska-Pik, J., Teisseyre, P., Zubańska, M., Bronikowska, A., Grzybowski, T., Płoski, R., et al. (2019) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2019.07.012 · Cited by 46 · see citing works
Self-citationAbuabara, K., You, Y., Margolis, D., Hoffmann, T., Risch, N., & Jorgenson, E. (2019) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2019.06.044 · Cited by 44 · see citing works
True colors: A literature review on the spatial distribution of eye and hair pigmentation
Katsara, M., & Nothnagel, M. (2019) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2019.01.001 · Cited by 42 · see citing works
East Anglian early Neolithic monument burial linked to contemporary Megaliths
Scheib, C., Hui, R., D'Atanasio, E., Wohns, A., Inskip, S., Rose, A. K., Cessford, C., O'Connell, T., Robb, J., Evans, C., et al. (2019) · Annals of Human Biology · doi:10.1080/03014460.2019.1623912 · Cited by 41 · see citing works
A review of the potential of the MinION™ single‐molecule sequencing system for forensic applications
Plesivkova, D., Richards, R., & Harbison, S. (2018) · WIREs Forensic Science · doi:10.1002/wfs2.1323 · Cited by 41 · see citing works
Diepenbroek, M., Bayer, B., Schwender, K., Schiller, R., Lim, J., Lagacé, R., & Anslinger, K. (2020) · Genes · doi:10.3390/genes11121398 · Cited by 40 · see citing works
“Observations about the weak amplification rate of rs1470608 have been previously reported in the development of the SNapShot and MPS versions of the HIrisPlex-S (HPS) Panel [11,17,56].”
MethodInfluentialUncovering Forensic Evidence: A Path to Age Estimation through DNA Methylation
Castagnola, M. J., Medina-Paz, F., & Zapico, S. C. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25094917 · Cited by 52 · see citing works
“Examples include the extensively researched study of single nucleotide polymorphisms (SNPs) predictive for eye, hair, skin color, and biogeographical ancestry [35,36], which has become the most accurate and widely used in Forensic DNA Phenotyping.”
BackgroundGenetic ancestry plays a central role in population pharmacogenomics
Yang, H., Chen, C., Lin, Y., & Chu, S. (2021) · Communications Biology · doi:10.1038/s42003-021-01681-6 · Cited by 51 · see citing works
DNA phenotyping: current application in forensic science
Marano, L. A., & Fridman, C. (2019) · Research and Reports in Forensic Medical Science · doi:10.2147/rrfms.s164090 · Cited by 36 · see citing works
“Taking into account this evolutionary obstacle, a global prediction model was developed based on 36 markers distributed among 16 pigmentation genes.(17) This model was created taking into account three (light, dark, dark–black) or five (very pale, pale, intermediate, dark, dark–black) skin tones, obtaining prediction…”
How to choose sets of ancestry informative markers: A supervised feature selection approach
Pfaffelhuber, P., Grundner-Culemann, F., Lipphardt, V., & Baumdicker, F. (2019) · bioRxiv · doi:10.1101/759464 · Cited by 36
The diverse genetic origins of a Classical period Greek army
Reitsema, L. J., Mittnik, A., Kyle, B., Catalano, G., Fabbri, P. F., Kazmi, A. C. S., Reinberger, K. L., Sìneo, L., Vassallo, S., Bernardos, R. L., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2205272119 · Cited by 82 · see citing works
Population Replacement in Early Neolithic BritainPreprint
Brace, S., Diekmann, Y., Booth, T. J., Faltyskova, Z., Rohland, N., Mallick, S., Ferry, M., Michel, M., Oppenheimer, J., Broomandkhoshbacht, N., et al. (2018) · bioRxiv · doi:10.1101/267443 · Cited by 35 · see citing works
Self-citationEvaluation of supervised machine-learning methods for predicting appearance traits from DNA.
Katsara, M., Branicki, W., Walsh, S., Kayser, M., & Nothnagel, M. (2021) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2021.102507 · Cited by 33 · see citing works
Self-citationGlobal Ancestry and Cognitive Ability
Lasker, J., Pesta, B. J., Fuerst, J. G. R., & Kirkegaard, E. O. W. (2019) · Psych · doi:10.3390/psych1010034 · Cited by 32 · see citing works
“Skin color (assessed genetically with the highly accurate predictor [79,93] was associated with cognitive ability (Model 1b, Table 5), but made no significant incremental contribution when ancestry was also in the model (Model 2, Table 5).”
BackgroundMethodGenomic ancestry and social dynamics of the last hunter-gatherers of Atlantic France
Simões, L. G., Peyroteo-Stjerna, R., Marchand, G., Bernhardsson, C., Vialet, A., Chetty, D., Alaçamlı, E., Edlund, H., Bouquin, D., Dina, C., et al. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2310545121 · Cited by 26 · see citing works
“S system (66).”
Genetic history of Cambridgeshire before and after the Black Death
Hui, R., Scheib, C., D'Atanasio, E., Inskip, S., Cessford, C., Biagini, S. A., Wohns, A., Ali, M. Q. A., Griffith, S. J., Solnik, A., et al. (2024) · Science Advances · doi:10.1126/sciadv.adi5903 · Cited by 32 · see citing works
Palencia-Madrid, L., Xavier, C., de la Puente, M., Hohoff, C., Phillips, C., Kayser, M., & Parson, W. (2020) · Genes · doi:10.3390/genes11060708 · Cited by 32 · see citing works
Self-citationHopman, R., & M'charek, A. (2020) · BioSocieties · doi:10.1057/s41292-020-00190-9 · Cited by 32 · see citing works
Xavier, C., de la Puente, M., Mosquera-Miguel, A., Freire-Aradas, A., Kalamara, V., Ralf, A., Revoir, A., Gross, T., Schneider, P. M., Ames, C., et al. (2022) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2022.102779 · Cited by 29 · see citing works
Self-citationPopulation relationships based on 170 ancestry SNPs from the combined Kidd and Seldin panels
Pakstis, A., Speed, W. C., Soundararajan, U., Rajeevan, H., Kidd, J., Li, H., & Kidd, K. (2019) · Scientific Reports · doi:10.1038/s41598-019-55175-x · Cited by 29 · see citing works
Xavier, C., de la Puente, M., Sidstedt, M., Junker, K., Minawi, A., Unterländer, M., Chantrel, Y., Laurent, F.-X., Delest, A., Hohoff, C., et al. (2022) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2022.102675 · Cited by 28 · see citing works
Self-citationMolecular markers used in forensic genetics
Kowalczyk, M., Zawadzka, E., Szewczuk, D., Gryzińska, M., & Jakubczak, A. (2018) · Medicine, Science and the Law · doi:10.1177/0025802418803852 · Cited by 28
Exploring nanotechnology in forensic investigations: Techniques, innovations, and future prospects
Ullah, M. F., Khan, Y., Khan, M. I., Abdullaeva, B., & Waqas, M. (2024) · Sensing and Bio-Sensing Research · doi:10.1016/j.sbsr.2024.100674 · Cited by 27
Bulbul, O., & Filoglu, G. (2018) · Electrophoresis · doi:10.1002/elps.201800243 · Cited by 27 · see citing works
Revisiting informed consent in forensic genomics in light of current technologies and the times
Budowle, B., & Sajantila, A. (2023) · Zeitschrift für Rechtsmedizin · doi:10.1007/s00414-023-02947-w · Cited by 26 · see citing works
“[43] (see appendix 5 FAQs) require that informed consent cover that the donor understands and agrees that the sample may be searched in national and non-national databases.”
BackgroundKivisild, T., Saag, L., Hui, R., Biagini, S. A., Pankratov, V., D’Atanasio, E., Pagani, L., Saag, L., Rootsi, S., Mägi, R., et al. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.07.012 · Cited by 25 · see citing works
de Bruin, D. D. S. H., Haagmans, M. A., van der Gaag, K. J., Hoogenboom, J., Weiler, N., Tesi, N., Salazar, A., Zhang, Y.-R., Holstege, H., Reinders, M., et al. (2024) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2024.103154 · Cited by 25
Self-citationExternal visible characteristics prediction through SNPs analysis in the forensic setting: a review.
Tozzo, P., Politi, C., Delicati, A., Gabbin, A., & Caenazzo, L. (2021) · Frontiers in Bioscience · doi:10.52586/4991 · Cited by 25 · see citing works
“rs2378249 ASIP/PIGU 20 Hair colour [37, 49]”
Kukla-Bartoszek, M., Szargut, M., Pośpiech, E., Diepenbroek, M., Zielińska, G., Jarosz, A., Piniewska-Róg, D., Arciszewska, J., Cytacka, S., Spólnicka, M., et al. (2020) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2020.102301 · Cited by 25 · see citing works
Self-citationForensic DNA phenotyping: Inferring phenotypic traits from crime scene DNA
Dabas, P., Jain, S. G., Khajuria, H., & Nayak, B. P. (2022) · Journal of Forensic and Legal Medicine · doi:10.1016/j.jflm.2022.102351 · Cited by 22 · see citing works
Salvo, N. M., Janssen, K., Kirsebom, M. K., Meyer, O. S., Berg, T., & Olsen, G. (2021) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2021.102620 · Cited by 24 · see citing works
Performance of four models for eye color prediction in an Italian population sample.
Salvoro, C., Faccinetto, C., Zucchelli, L., Porto, M., Marino, A., Occhi, G., Campos, G. D. L., & Vazza, G. (2019) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2019.03.008 · Cited by 24 · see citing works
Mandape, S. N., Budowle, B., Mittelman, K., & Mittelman, D. (2024) · Croatian Medical Journal · doi:10.3325/cmj.2024.65.249 · Cited by 23 · see citing works
“Since then, the capability of phenotypic SNPs to identify markers directly related to traits has progressed in their utility to predict visible traits, such as facial shape, skin pigmentation, eye color, hair color, baldness, and freckles, to name a few (78-81).”
Gerber, D., Szeifert, B., Székely, O., Egyed, B., Gyuris, B., Giblin, J. I., Horváth, A., Köhler, K., Kulcsár, G., Kustár, Á., et al. (2023) · Molecular Biology and Evolution · doi:10.1093/molbev/msad182 · Cited by 24 · see citing works
“For inferring pigmentation of the studied individuals, we used the HIrisPlex (Chaitanya et al., 2018) system supplemented with further variants obtained from SNPedia database (Cariaso and Lennon, 2012).”
MethodPredicting Physical Appearance from DNA Data—Towards Genomic Solutions
Pośpiech, E., Teisseyre, P., Mielniczuk, J., & Branicki, W. (2022) · Genes · doi:10.3390/genes13010121 · Cited by 24 · see citing works
“The IrisPlex tool for the genotyping and prediction of eye colour evolved to HIrisPlex [106] and finally to the HIrisPlex-S tool [109], which were developed based on the same strategy as IrisPlex.”
MethodSelf-citationFrom flesh to bones: Multi‐omics approaches in forensic science
Procopio, N., & Bonicelli, A. (2024) · Proteomics · doi:10.1002/pmic.202200335 · Cited by 23 · see citing works
“Similarly, but using the HIrisPlex system, Chaitanya et al. analysed the SNPs profiles for 49 samples originated from bones or teeth from the World War II and obtained and eye and hair color predictions from all the skeletal samples analysed [342].”
MethodNortheastern Asian and Jomon-related genetic structure in the Three Kingdoms period of Gimhae, Korea
Gelabert, P., Blažytė, A., Chang, Y., Fernandes, D., Jeon, S., Hong, J. G., Yoon, J., Ko, Y., Oberreiter, V., Cheronet, O., et al. (2022) · Current Biology · doi:10.1016/j.cub.2022.06.004 · Cited by 22 · see citing works
Pushing the Boundaries: Forensic DNA Phenotyping Challenged by Single-Cell Sequencing
Diepenbroek, M., Bayer, B., & Anslinger, K. (2021) · Genes · doi:10.3390/genes12091362 · Cited by 22 · see citing works
“Furthermore, skin color is the most complex phenotypic trait to predict, and incomplete profiles make it even more difficult [34,35].”
BackgroundStephens, K., Barta, R., Fleming, K., Pérez, J. C., Wu, S., Snedecor, J., Holt, C., LaRue, B., & Budowle, B. (2023) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2023.102851 · Cited by 21 · see citing works
Gross, T., Fleckhaus, J., & Schneider, P. (2021) · Zeitschrift für Rechtsmedizin · doi:10.1007/s00414-021-02569-0 · Cited by 21
Prediction of eye, hair and skin colour in Latin Americans.
Palmal, S., Adhikari, K., Mendoza-Revilla, J., Fuentes-Guajardo, M., de Cerqueira, C. C. S., Bonfante, B., Chacón-Duque, J., Sohail, A., Hurtado, M., Villegas, V., et al. (2021) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2021.102517 · Cited by 21 · see citing works
“…studies on prediction of pigmentation traits, exploiting GWAS findings, focused on eye colour [20–23] and these analyses were subsequently extended to hair [24,25] and skin [26]. r As a result, sets of SNPs have now been proposed for the simultaneous prediction of eye, hair and skin colour[27,28].”
Optimizing the genetic prediction of the eye and hair color for North Eurasian populations
Balanovska, E., Lukianova, E., Kagazezheva, J., Maurer, A., Leybova, N., Agdzhoyan, A., Gorin, I., Petrushenko, V., Zhabagin, M., Pylev, V., et al. (2020) · BMC Genomics · doi:10.1186/s12864-020-06923-1 · Cited by 21 · see citing works
Forensic DNA phenotyping: a review on SNP panels, genotyping techniques, and prediction models
Terrado-Ortuño, N., & May, P. (2024) · Forensic Sciences Research · doi:10.1093/fsr/owae013 · Cited by 19 · see citing works
Staadig, A., Hedman, J., & Tillmar, A. (2023) · Genes · doi:10.3390/genes14040818 · Cited by 20 · see citing works
“The phenotype and ancestry informative markers have previously been identified and found to be informative [53,59,60].”
BackgroundMeyer, O., Lunn, M. M. B., Garcia, S. L., Kjærbye, A. B., Morling, N., Børsting, C., & Andersen, J. D. (2020) · PLoS ONE · doi:10.1371/journal.pone.0239131 · Cited by 20 · see citing works
“rs1126809 has previously been used as a marker for skin pigmentation [5, 44, 45].”
A review of the method and validation of the MiSeq FGx™ Forensic Genomics Solution
England, R., & Harbison, S. (2019) · WIREs Forensic Science · doi:10.1002/wfs2.1351 · Cited by 20 · see citing works
Ragazzo, M., Puleri, G., Errichiello, V., Manzo, L., Luzzi, L., Potenza, S., Strafella, C., Peconi, C., Nicastro, F., Caputo, V., et al. (2021) · Genes · doi:10.3390/genes12020221 · Cited by 19 · see citing works
“The HIrisPlex-S panel and the related software were previously validated elsewhere [16,19].”
BackgroundMethodOpening up forensic DNA phenotyping: the logics of accuracy, commonality and valuing
Hopman, R. (2020) · doi:10.1080/14636778.2020.1755638 · Cited by 19
“And indeed in 2012 and 2017 additional tests for eye- and hair color respectively were legalized, with skin color to be added in the near future (Chaitanya et al. 2018). Within the Dutch forensic context, I move from the research lab where researchers are working on the discovery of biomarkers that affect physical app…”
BackgroundOff-target phenotypes in forensic DNA phenotyping and biogeographic ancestry inference: A resource
Bradbury, C., Köttgen, A., & Staubach, F. (2018) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2018.10.010 · Cited by 20 · see citing works
Resutik, P., Aeschbacher, S., Krützen, M., Kratzer, A., Haas, C., Phillips, C., & Arora, N. (2023) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2023.102850 · Cited by 16 · see citing works
Advancement in Human Face Prediction Using DNA
Alshehhi, A., Almarzooqi, A., Alhammadi, K., Werghi, N., Tay, G. K., & AlSafar, H. S. (2023) · Genes · doi:10.3390/genes14010136 · Cited by 18 · see citing works
Searching for improvements in predicting human eye colour from DNA
Kukla-Bartoszek, M., Teisseyre, P., Pośpiech, E., Karłowska-Pik, J., Zieliński, P., Woźniak, A., Boroń, M., Dąbrowski, M., Zubańska, M., Jarosz, A., et al. (2021) · Zeitschrift für Rechtsmedizin · doi:10.1007/s00414-021-02645-5 · Cited by 16 · see citing works
Self-citationPrediction of Eye Colour in Scandinavians Using the EyeColour 11 (EC11) SNP Set
Meyer, O., Salvo, N. M., Kjærbye, A. B., Kjersem, M., Andersen, M. M., Sørensen, E., Ullum, H., Janssen, K., Morling, N., Børsting, C., et al. (2021) · Genes · doi:10.3390/genes12060821 · Cited by 16 · see citing works
Carratto, T. M. T., Marcorin, L., Valle-Silva, G. D., de Oliveira, M. D., Donadi, E., Simões, A., Castelli, E., & Mendes-Junior, C. (2021) · Zeitschrift für Rechtsmedizin · doi:10.1007/s00414-021-02554-7 · Cited by 16 · see citing works
“The HIrisPlex-S system was developed to predict skin color based on 36 SNPs, in addition to the previous models for eye and hair color prediction [39, 40].”
MethodLasisi, T. (2021) · American Journal of Physical Anthropology · doi:10.1002/ajpa.24264 · Cited by 16 · see citing works
“Davenport and Davenport (1907), for instance, claimed that “blue/grey and brown suffice”, the DNA phenotyping tool HIrisPlex-S claims to be able to predict eye color as being blue brown or “intermediate” (Chaitanya et al., 2018), and a recent genome-wide association study (GWAS) on admixed Latin Americans used the cat…”
BackgroundInfluentialChen, Y., Branicki, W., Walsh, S., Nothnagel, M., Kayser, M., & Liu, F. (2020) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2020.102395 · Cited by 15 · see citing works
Self-citationNimbkar, P. H., & Bhatt, V. D. (2022) · Forensic Science International · doi:10.1016/j.forsciint.2022.111352 · Cited by 15
Forensic DNA phenotyping: A promising tool to aid forensic investigation. Current situation
Serrano, A. C. (2020) · Revista Española de Medicina Legal · doi:10.1016/j.remle.2020.01.002 · Cited by 15 · see citing works
Marano, L. A., Andersen, J. D., Gonçalves, F., Garcia, A. L., & Fridman, C. (2019) · doi:10.1016/j.fsigss.2019.10.038 · Cited by 15
Forensic genetic investigation of human skeletal remains recovered from the La Belle shipwreck.
Ambers, A., Bus, M., King, J., Jones, B. M., Durst, J., Bruseth, J., Gill-King, H., & Budowle, B. (2019) · Forensic Science International · doi:10.1016/j.forsciint.2019.110050 · Cited by 15 · see citing works
Investigating the genetic architecture of eye colour in a Canadian cohort
Lona‐Durazo, F., Thakur, R., Pairo‐Castineira, E., Funderburk, K. M., Zhang, T., Kovacs, M. A., Choi, J., Jackson, I. J., Brown, K. M., & Parra, E. J. (2022) · iScience · doi:10.1016/j.isci.2022.104485 · Cited by 14 · see citing works
A review of scientific research in defensive cyberspace operation tools and technologies
Goethals, P., & Hunt, M. E. (2019) · Journal of Cyber Security Technology · doi:10.1080/23742917.2019.1601889 · Cited by 14 · see citing works
A review on the role of emerging revolutionary nanotechnology in forensic investigations
Tambo, F., & Ablateye, D. N. O. (2020) · doi:10.31018/jans.v12i4.2415 · Cited by 14
“However, eye, hair and skin color from DNA can be predicted using HirisPlex-S systems which in conjunction with SNP genotyping achieve essentially useful accuracies and have been validated for forensic analysis (Wirken et al., 2018).”
BackgroundPilli, E., Palamenghi, A., & Cattaneo, C. (2025) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.15398 · Cited by 14 · see citing works
Sobral, A. F., Dinis‐Oliveira, R. J., & Barbosa, D. J. (2024) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2024.103163 · Cited by 14 · see citing works
Melchionda, F., Silvestrini, B., Robino, C., Bini, C., Fattorini, P., Martínez-Labarga, C., Angelis, F. D., Tagliabracci, A., & Turchi, C. (2022) · Genes · doi:10.3390/genes13101688 · Cited by 13 · see citing works
“The 41 SNPs of HirisPlex-S systems [2] were analysed in this study.”
BackgroundMethodInfluentialAt the beginnings of the funerary Megalithism in Iberia at Campo de Hockey necropolis
Vila, E. V., Bonilla, M. D., Morell, B., Olalde, Í., Muñoz, L. P. S.-B., Bella, S. D., Emslie, S. D., Martín, S. B., Salvador, Á. R., Fernández-Sánchez, D., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-13014-6 · Cited by 14 · see citing works
Wendt, F. R., Pathak, G. A., & Polimanti, R. (2022) · Nature Communications · doi:10.1038/s41467-022-35423-x · Cited by 12 · see citing works
Ravasini, F., Kabral, H., Solnik, A., de Gennaro, L., Montinaro, F., Hui, R., Delpino, C., Finocchi, S., Giroldini, P., Mei, O., et al. (2024) · Genome biology · doi:10.1186/s13059-024-03430-4 · Cited by 9 · see citing works
Life history and ancestry of the late Upper Palaeolithic infant from Grotta delle Mura, Italy
Higgins, O. A., Modi, A., Cannariato, C., Diroma, M. A., Lugli, F., Ricci, S., Zaro, V., Vai, S., Vazzana, A., Romandini, M., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-51150-x · Cited by 12 · see citing works
“Based on data from the 41 SNPs in the HIrisPlex-S panel 51 , the infantmostlikelyhadblueeyes,darkskinandcurlydarkbrown/almost black hair (Supplementary Data 23).”
- Authors
- Chaitanya, L., Breslin, K., Zuñiga, S., Wirken, L., Pośpiech, E., Kukla-Bartoszek, M., Sijen, T., Knijff, P. D., Liu, F., Branicki, W., Kayser, M., & Walsh, S.
- Affiliations
- Erasmus MC (NL)
- Indiana University – Purdue University Indianapolis (US)
- Leiden University Medical Center (NL)
- Jagiellonian University (PL)
- Netherlands Forensic Institute (NL)
- Chinese Academy of Sciences (CN)
- Corresponding author
- Kayser, Manfred
- Walsh, Susan
- ORCID
- Venue
- Forensic Science International: Genetics
- Publisher
- Elsevier BV
- Published
- 2018-07
- Volume
- 35
- Pages
- 123-135
- ISSN
- 1872-4973 (ISSN-L)
- OpenAlex
- W2796803633
- Cited by
- 335
- References
- 58
- Citations by year
- 2026: 48 · 2025: 37 · 2024: 42 · 2023: 45 · 2022: 51 · 2021: 39 · 2020: 33 · 2019: 30 · 2018: 9
- FWCI
- 16.98
- Type
- journal article
- Language
- en
- Open access
- green
- ruj.uj.edu.pl
- Licence
- Locations
- Forensic Science International Genetics (publishedVersion)
- PubMed (publishedVersion)
- Homo Politicus (Academy of Humanities and Economics in Lodz) (submittedVersion, cc-by-nc-nd)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- IUScholarWorks (Indiana University) (submittedVersion)
- Purdue University Indianapolis (Indiana University) (submittedVersion)
- Funders
- Indiana University-Purdue University Indianapolis
- Fundacja na rzecz Nauki Polskiej
- National Institute of Justice (2014-DN-BX-K031)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- trace DNA, degraded DNA, statistical forecasting models, suspect identification, genotype probabilities
- MeSH terms
- Animals, DNA, Eye Color, Hair Color, Humans, Phenotype, Skin Pigmentation, Species Specificity, Reproducibility of Results, Polymerase Chain Reaction, Polymorphism, Single Nucleotide, Forensic Genetics, Genotyping Techniques
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