Forensic DNA Phenotyping: a review on SNP Panels, Genotyping Techniques, and Prediction Models

Terrado-Ortuño, Nuria; MAY, Patrick

doi:10.1093/fsr/owae013

Télécharger

Article (Périodiques scientifiques)

Forensic DNA Phenotyping: a review on SNP Panels, Genotyping Techniques, and Prediction Models

Terrado-Ortuño, Nuria; MAY, Patrick

2024 • In Forensic Sciences Research, owae013

Peer reviewed vérifié par ORBi

Permalien
https://hdl.handle.net/10993/60574

DOI
10.1093/fsr/owae013

Documents (1)Envoyer vers Détails Statistiques Bibliographie Publications similaires

Documents

Texte intégral

owae013.pdf

Postprint Auteur (1.09 MB)

Licence Creative Commons - Transfert dans le Domaine Public

Télécharger

Tous les documents dans ORBilu sont protégés par une licence d'utilisation.

Envoyer vers

RIS BibTex APA Chicago Permalink X Linkedin

Détails

Mots-clés :

Forensic genetics; DNA phenotyping; Genotyping

Résumé :

[en] In the past few years, forensic DNA phenotyping has attracted a strong interest in the forensic research. Among the increasing publications, many have focused on testing the available panels to infer biogeographical ancestry on less represented populations and understanding the genetic mechanisms underlying externally visible characteristics. However, there are currently no publications that gather all the existing panels limited to forensic DNA phenotyping and discuss the main technical limitations of the technique. In this review, we performed a bibliographic search in Scopus database of phenotyping-related literature, which resulted in a total of 48, 43 and 15 panels for biogeographical ancestry, externally visible characteristics and both traits inference, respectively. Here we provide a list of commercial and non-commercial panels and the limitations regarding the lack of harmonization in terms of terminology (i.e., categorization and measurement of traits) and reporting, the lack of genetic knowledge and environment influence to select markers and develop panels, and the debate surrounding the selection of genotyping technologies and prediction models and algorithms. In conclusion, this review aims to be an updated guide and to present an overview of the current related literature.

Centre de recherche :

Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)

Précision sur le type de document :

Compte rendu

Disciplines :

Génétique & processus génétiques
Criminologie

Auteur, co-auteur :

Terrado-Ortuño, Nuria; Genome Analysis, Bioinformatics Core, Luxembourg Centre for Systems Biomedicine , Esch-sur-Alzette, Luxembourg

MAY, Patrick ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core ; Genome Analysis, Bioinformatics Core, Luxembourg Centre for Systems Biomedicine , Esch-sur-Alzette, Luxembourg

Co-auteurs externes :

Langue du document :

Anglais

Titre :

Forensic DNA Phenotyping: a review on SNP Panels, Genotyping Techniques, and Prediction Models

Date de publication/diffusion :

11 mars 2024

Titre du périodique :

Forensic Sciences Research

ISSN :

2096-1790

eISSN :

2471-1411

Maison d'édition :

Oxford University Press (OUP)

Volume/Tome :

owae013

Peer reviewed :

Peer reviewed vérifié par ORBi

Focus Area :

Law / European Law
Systems Biomedicine

Objectif de développement durable (ODD) :

4. Education de qualité

URL complémentaire :

https://academic.oup.com/fsr/advance-article/doi/10.1093/fsr/owae013/7625515

Intitulé du projet de recherche :

U-AGR-6005 - IAS CRIMTYP - ALLEGREZZA Silvia

Organisme subsidiant :

Institute of Advanced Studies
Unilu - University of Luxembourg

N° du Fonds :

U-AGR-6005

Subventionnement (détails) :

This work was supported by the Institute of Advanced Studies (University of Luxembourg) under an Audacity grant (AUDACITY-2020): Meet the Unknown: The Future of CRIMinal Forensic Genomics PhenoTYPing (CRIMTYP).

Disponible sur ORBilu :

depuis le 14 mars 2024

Statistiques

Nombre de vues

213 (dont 3 Unilu)

Nombre de téléchargements

135 (dont 0 Unilu)

Voir plus de statistiques

citations Scopus^®

citations Scopus^®
sans auto-citations

citations OpenAlex

Bibliographie

Jobling MA, Gill P. Encoded evidence: DNA in forensic analysis. Nat Rev Genet. 2004;5:739-751.
Walsh SJ. Recent advances in forensic genetics. Expert Rev Mol Diagn. 2004;4:31-40.
Daniel R, Walsh SJ. The continuing evolution of forensic DNA profiling-from STRs to SNPs. Aust J Forensic Sci. 2006;38: 59-74.
Butler JM, Coble MD, Vallone PM. STRs vs. SNPs: thoughts on the future of forensic DNA testing. Forensic Sci Med Pathol. 2007;3:200-205.
Jobling MA. Y-chromosomal SNP haplotype diversity in forensic analysis. Forensic Sci Int. 2001;118:158-162.
Matheson S. DNA phenotyping: snapshot of a criminal. Cell. 2016;166:1061-1064.
Schneider PM, Prainsack B, Kayser M. The use of forensic DNA phenotyping in predicting appearance and biogeographic ances-try. Dtsch Arztebl Int. 2019;116:873.
Tozzo P, Politi C, Delicati A, et al. External visible characteristics prediction through SNPs analysis in the forensic setting: a review. Front Biosci (Landmark Ed). 2021;26:828-850.
Kayser M. Forensic DNA phenotyping: DNA testing for exter-nally visible characteristics. In: Siegel JA, Saukko PJ, Houck MM,editors.EncyclopediaofForensicSciences.2nded.Waltham (MA): Academic Press; 2013. p. 369-374.
Kayser M,Schneider PM.DNA-based prediction of human exter-nally visible characteristics in forensics: motivations, scientific challenges, and ethical considerations. Forensic Sci Int Genet. 2009;3:154-161.
Canales SA. [Forensic DNA phenotyping: a promising tool to aid forensic investigation. Current situation]. J Leg Med. 2020;46: 183-190. Spanish.
Póspiech E, Teisseyre P, Mielniczuk J, et al. Predicting physical appearance from DNA data: towards genomic solutions. Genes. 2022;13:121.
Mehta B, Daniel R, Phillips C, et al. Forensically relevant SNaP-shot® assays for human DNA SNP analysis: a review. Int J Leg Med. 2016;131:21-37.
Pulker H, Lareu MV, Phillips C, et al. Finding genes that underlie physical traits of forensic interest using genetic tools. Forensic Sci Int Genet. 2007;1:100-104.
Kayser M, Forensic DNA. Phenotyping: predicting human appearance from crime scene material for investigative purposes. Forensic Sci Int Genet. 2015;18:33-48.
Stephan CN, Caple JM, Guyomarc'h P, et al. An overview of the latest developments in facial imaging. Forensic Sci Res. 2019;4: 10-28.
Haddrill PR.Developments in forensic DNA analysis.Emerg Top Life Sci. 2021;5:381-393.
Budowle B. SNP typing strategies. Forensic Sci Int. 2004;146: S139-S142.
Sobrino B,CarracedoA.SNP typing in forensicgenetics:a review. Methods Mol Biol. 2005;297:107-126.
Sobrino B, Brión M, Carracedo A. SNPs in forensic genetics: a review on SNP typing methodologies. Forensic Sci Int. 2005;154: 181-194.
Decorte R. Genetic identification in the 21st century-current status and future developments. Forensic Sci Int. 2010;201: 160-164.
Zietkiewicz E, Witt M, Daca P, et al. Current genetic method-ologies in the identification of disaster victims and in forensic analysis. J Appl Genet. 2011;53:41-60.
Kowalczyk M, Zawadzka E, Szewczuk D, et al. Molecular mark-ers used in forensic genetics. Med Sci Law 2018; 58:201-209.
Liu F, Wen B, Kayser M. Colorful DNA polymorphisms in humans. Semin Cell Dev Biol. 2013;24:562-575.
Gurkan C, Bulbul O, Kidd KK. Editorial: current and emerging trendsinhumanidentificationandmolecularanthropology.Front Genet. 2021;12:1041.
Oh CS,Shin DH,Hong JH,et al.Single-nucleotide polymorphism analyses on ABCC11, EDAR, FGFR2, and ABO genotypes of mummified people of the Joseon Dynasty, South Korea. Anthro-pol Sci. 2018;126:67-73.
Watherston J, McNevin D, Gahan ME, et al. Current and emerg-ing tools for the recovery of genetic information from post mortem samples: new directions for disaster victim identification. Forensic Sci Int Genet. 2018;37:270-282.
Ambers A, Bus MM, King JL, et al. Forensic genetic investigation of human skeletal remains recovered from the La Belle shipwreck. Forensic Sci Int. 2020;306:110050.
Bogdanowicz W, Allen M, Branicki W, et al. Genetic identifi-cation of putative remains of the famous astronomer Nicolaus Copernicus. Proc Natl Acad Sci U S A. 2009;106:12279-12282.
Kupiec T, Branicki W. Genetic examination of the putative skull of Jan Kochanowski reveals its female sex.Croat Med J.2011;52: 403-409.
King TE, Fortes GG, Balaresque P, et al. Identification of the remains of King Richard III. Nat Commun. 2014;5:1-8.
Zupanič PI. Identification of a Slovenian pre-war elite couple killed in the Second World War. Forensic Sci Int. 2021;327: 110994.
Sankar P. Forensic DNA phenotyping: continuity and change in the history of race, genetics, and policing. In: Wailoo K, Nelson A, Lee C, editors. Genetics and the unsettled past: the collision of DNA,race,and history.New Brunswick (NJ): Rutgers University Press; 2012. p. 104-113.
Atwood L, Raymond J, Sears A, et al. From identification to intelligence: an assessment of the suitability of forensic DNA phenotyping service providers for use in Australian law enforce-ment casework. Front Genet. 2021;11:1-11.
Hollard C,Keyser C,Delabarde T,et al.Case report: on the use of the HID-ion AmpliSeqTM ancestry panel in a real forensic case. Int J Leg Med. 2017;131:351-358.
Graham EAM. DNA reviews: predicting phenotype. Forensic Sci Med Pathol. 2008;4:196-199.
Lippert C, Sabatini R, Maher MC, et al. Identification of indi-viduals by trait prediction using whole-genome sequencing data. Proc Natl Acad Sci. 2017;114:10166-10171.
Butler JM, Reeder DJ. STRBase. USA: National Institute of Stan-dards and Technology. Available from: https://strbase-archive.ni st.gov/
Soundararajan U, Yun L, Shi M, et al. Minimal SNP overlap among multiple panels of ancestry informative markers argues for more international collaboration. Forensic Sci Int Genet. 2016;23:25-32.
Mehta BM. Genotyping Tools for Forensic DNA Phenotyp-ing: From Low-to High-Throughput [dissertation]. Canberra (Australia): University of Canberra; 2019.
Børsting C, Morling N. Next generation sequencing and its applications in forensic genetics. Forensic Sci Int Genet. 2015;18: 78-89.
Budowle B, van Daal A. Forensically relevant SNP classes. Biotechniques. 2008;44:603-610.
Kayser M, de Knijff P. Improving human forensics through advances in genetics, genomics and molecular biology. Nat Rev Genet. 2011;12:179-192.
Wells JD, Linville JG. Biology/DNA/Entomology: Overview. In: Siegel JA, Saukko PJ, Houck MM, editors. Encyclopedia of Forensic Sciences.2nd ed.Waltham (MA): Academic Press; 2013. p. 387-393.
Morelato M, Barash M, Blanes L, et al. Forensic science: current stateandperspectivebyagroupofearlycareerresearchers.Found Sci. 2016;22:799-825.
Pope S, Puch-Solis R. Interpretation of DNA data within the context of UK forensic science - investigation. Emerg Top Life Sci. 2021;5:395-404.
Frudakis TN. Molecular Photofitting: Predicting Ancestry and Phenotype Using DNA. Cambridge (MA): Academic Press Inc.; 2007.
Cheung EYY, Gahan ME, McNevin D. Predictive DNA analysis for biogeographical ancestry. Aust J Forensic Sci. 2018;50:1-8.
Phillips C. Forensic genetic analysis of bio-geographical ancestry. Forensic Sci Int Genet. 2015;18:49-65.
Tully G. Genotype versus phenotype: human pigmentation. Forensic Sci Int Genet. 2007;1:105-110.
Branicki W. Studies on predicting pigmentation phenotype for forensic purposes. Probl Forensic Sci. 2009;77:29-52.
Branicki W, Kayser M. Prediction of human pigmentation traits from DNA polymorphisms. eLS. 2015;1:1-10.
Wolinsky H. CSI on steroids: DNA-based phenotyping is helping police derive visual information from crime scene samples to aid in the hunt for suspects. EMBO Rep. 2015;16:782-786.
Dabas P, Jain S, Khajuria H, et al. Forensic DNA phenotyping: inferring phenotypic traits from crime scene DNA. J Forensic Leg Med. 2022;88:102351.
Tricco AC,Lillie E,Zarin W,et al.PRISMA extension for Scoping Reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018;169:467-473.
Kayser M. In reply. Dtsch Arztebl Int. 2020;117:269-270.
Al-Asfi M, McNevin D, Mehta B, et al. Assessment of the Preci-sion ID Ancestry Panel. Int J Leg Med. 2018;132:1581-1594.
Bulbul O,Speed WC,Gurkan C,et al.Improving ancestry distinc-tions among Southwest Asian populations.Forensic Sci Int Genet. 2018;35:14-20.
Lowe AL, Urquhart A, Foreman LA, et al. Inferring ethnic origin by means of an STR profile. Forensic Sci Int. 2001;119:17-22.
RowoldDJ,HerreraRJ.Inferringrecenthumanphylogeniesusing forensic STR technology. Forensic Sci Int. 2003;133:260-265.
Phillips C, Santos C, Fondevila M, et al. Inference of ancestry in forensic analysis I: autosomal ancestry-informative marker sets. Methods Mol Biol. 2016;1420:233-253.
Oldoni F, Kidd KK, Podini D. Microhaplotypes in forensic genet-ics. Forensic Sci Int Genet. 2019;38:54-69.
Kayser M. Forensic use of Y-chromosome DNA: a general overview. Hum Genet. 2017;136:621-635.
Kivisild T. Maternal ancestry and population history from whole mitochondrial genomes. Investigative Genet. 2015;6:3.
Prestes PR, Mitchell RJ, Daniel R, et al. Predicting biogeograph-ical ancestry in admixed individuals-values and limitations of using uniparental and autosomal markers. Aust J Forensic Sci. 2015;48:10-23.
Halder I, Shriver M, Thomas M, et al. A panel of ancestry informative markers for estimating individual biogeographical ancestry and admixture from four continents: utility and appli-cations. Hum Mutat. 2008;29:648-658.
Qu Y,Tran D,Ma W.Deep learning approach to biogeographical ancestry inference. Procedia Comput Sci. 2019;159:552-561.
Cheung EYY, Gahan ME, McNevin D. Prediction of biogeo-graphical ancestry from genotype: a comparison of classifiers. Int J Leg Med. 2017;131:901-912.
Parfenchyk MS, Kotava SA. The theoretical framework for the panels of DNA markers formation in the forensic determination of an individual ancestral origin. Russ J Genet. 2021;57:1-9.
Alladio E, Poggiali B, Cosenza G, et al. Multivariate statisti-cal approach and machine learning for the evaluation of bio-geographical ancestry inference in the forensic field. Sci Rep. 2022;12:1-17.
Thermo Fisher Scientific. Precision ID Ancestry Panel. Last revi-sion: 2022. Available from: https://www.thermofisher.com/order/catalog/product/A25642
Phillips C, Salas A, Sánchez JJ, et al. Inferring ancestral origin using a single multiplex assay of ancestry-informative marker SNPs. Forensic Sci Int Genet. 2007;1:273-280.
UniversidaddeSantiagodeCompostela.Snipperappsuiteversion 3.Lastrevision:April2024.Availablefrom:http://mathgene.usc.e s/snipper/
Phillips C, Aradas AF, Kriegel AK, et al. Eurasiaplex: a forensic SNP assay for differentiating European and South Asian ances-tries. Forensic Sci Int Genet. 2013;7:359-366.
Santos C, Phillips C, Fondevila M, et al. Pacifiplex: an ancestry-informative SNP panel centred on Australia and the Pacific region. Forensic Sci Int Genet. 2016;20:71-80.
Carvalho Gontijo C, Porras-Hurtado LG, Freire-Aradas A, et al. PIMA: a population informative multiplex for the Americas. Forensic Sci Int Genet. 2020;44:102200.
KiddKK,SpeedWC,PakstisAJ,etal.Progresstowardanefficient panel of SNPs for ancestry inference. Forensic Sci Int Genet. 2014;10:23-32.
Phillips C, Parson W, Lundsberg B, et al. Building a forensic ancestry panel from the ground up: the EUROFORGEN Global AIM-SNP set. Forensic Sci Int Genet. 2014;11:13-25.
Pereira V, Freire-Aradas A, Ballard D, et al. Development and validation of the EUROFORGEN NAME (North African and Middle Eastern) ancestry panel. Forensic Sci Int Genet. 2019;42: 260-267.
Branicki W, Brudnik U, Wojas-pelc A. Genetic prediction of pigmentary traits in forensic studies. Forensic Sci Int. 2005;64: 343-357.
Martinez-Cadenas C, Penãa-Chilet M, Ibarrola-Villava M, et al. Gender is a major factor explaining discrepancies in eye colour prediction based on HERC2/OCA2 genotype and the IrisPlex model. Forensic Sci Int Genet. 2013;7:453-460.
Pietroni C,Andersen JD,Johansen P,et al.The effect of gender on eye colour variation in European populations and an evaluation of the IrisPlex prediction model.Forensic Sci Int Genet.2014; 11: 1-6.
Walsh S, Liu F, Ballantyne KN, et al. IrisPlex: a sensitive DNA tool for accurate prediction of blue and brown eye colour in the absence of ancestry information. Forensic Sci Int Genet. 2011;5: 170-180.
GuptaV,SharmaVK.Skintyping:Fitzpatrickgradingandothers. Clin Dermatol. 2019;37:430-436.
Kukla-Bartoszek M, Póspiech E, Wózniak A, et al. DNA-based predictive models for the presence of freckles. Forensic Sci Int Genet. 2019;42:252-259.
Hernando B, Ibañez MV, Deserio-Cuesta JA, et al. Genetic deter-minants of freckle occurrence in the Spanish population: towards ephelides prediction from human DNA samples. Forensic Sci Int Genet. 2018;33:38-47.
Cho S, Lee EH, Kim H, et al. Validation of BMI genetic risk score and DNA methylation in a Korean population. Int J Leg Med. 2021;135:1201-1212.
Claes P, Hill H, Shriver MD. Toward DNA-based facial compos-ites: preliminary results and validation. Forensic Sci Int Genet. 2014;13:208-216.
Samuels BD, Aho R, Brinkley JF. et al. FaceBase 3: analytical tools and FAIR resources for craniofacial and dental research. Development. 2020;147:dev191213.
The International Visible Trait Genetics (VisiGen) Consortium [Internet].
Claes P, Liberton DK, Daniels K, et al. Modeling 3D facial shape from DNA. PLoS Genet. 2014;10:e1004224.
Phillips C, Barbaro A, Lareu MV, et al. Initial study of candidate genes on chromosome two for relative hand skill. Int Congr Ser. 2006;1288:798-800.
van Daal A. The genetic basis of human pigmentation. Forensic Sci Int Genet Suppl Ser. 2008;1:541-543.
Fridman C, Cardena MMSG, De A Lima F, et al. Is it possible to use forensic DNA phenotyping in Brazilian population? Forensic Sci Int Genet Suppl Ser. 2015;5:e378-e380.
de Araújo LF, de Toledo GF, Fridman C. SLC24A5 and ASIP as phenotypic predictors in Brazilian population for forensic purposes. Leg Med. 2015;17:261-266.
Andrade ES, Fracasso NCA, Strazza Júnior PS, et al. Associa-tions of OCA2-HERC2 SNPs and haplotypes with human pig-mentation characteristics in the Brazilian population. Leg Med. 2017;24:78-83.
Veltre V, de Angelis F, Biondi G, et al. Evaluation of skin-related variants in African ancestry populations and their role in personal identification. Forensic Sci Int Genet Suppl Ser. 2019;7: 172-174.
Andersen JD, Meyer OS, Simão F, et al. Skin pigmenta-tion and genetic variants in an admixed Brazilian population of primarily European ancestry. Int J Leg Med. 2020;134: 1569-1579.
Zaumsegel D,Rothschild MA,Schneider PM.SNPs for the analy-sis of human pigmentation genes-a comparative study. Forensic Sci Int Genet Suppl Ser. 2008;1:544-546.
Branicki W, Szczerbínska A, Brudnik U, et al. The OCA2 gene as a marker for eye colour prediction. Forensic Sci Int Genet Suppl Ser. 2008;1:536-537.
Andersen JD, Johansen P, Wulf HC, et al. Genetic variants and skin colour in Danes. Forensic Sci Int Genet Suppl Ser. 2011;3:e153-e154.
Andersen JD, Pietroni C, Johansen P, et al. Importance of non-synonymous OCA2 variants in human eye color prediction. Mol Genet Genomic Med. 2016;4:420-430.
deAFracassoNC,deAndradeES,CEVW,etal.Haplotypesfrom the SLC45A2 gene are associated with the presence of freckles and eye, hair and skin pigmentation in Brazil. Leg Med. 2017;25: 43-51.
Meyer OS, Lunn MMB, Garcia SL, et al. Association between brown eye colour in rs12913832:GG individuals and SNPs in TYR, TYRP1,and SLC24A4. PloS One. 2020;15:e0239131.
Andersen JD, Johansen P, Mogensen HS, et al. Eye colour and SNPs in Danes. Forensic Sci Int Genet Suppl Ser. 2011;3: e151-e152.
Salvo NM, Mathisen MG, Janssen K, et al. Experimental long-distance haplotyping of OCA2-HERC2 variants. Forensic Sci Int Genet Suppl Ser. 2022;8:188-190.
Yan J,Cao LP,Ye Y,et al.Association of melanocortin-1-receptor gene polymorphism with freckles in Chinese Han population. Forensic Sci Int Genet Suppl Ser. 2013;4:e320-e321.
Fridman C, Ferreira MA, Marano LA, et al. Analysis of genetic polymorphisms associated with the presence of freckles for phe-notypic prediction. Forensic Sci Int Genet Suppl Ser. 2022;8: 26-28.
Liu F, van der Lijn F, Schurmann C, et al. A genome-wide asso-ciation study identifies five loci influencing facial morphology in Europeans. PLoS Genet. 2012;8:e1002932.
Wang Q, Jin B, Luo X, et al. Association between BMP4 gene polymorphisms and eyelid traits in Chinese Han population. Forensic Sci Int Genet Suppl Ser. 2017;6:e355-e356.
LiL,WangQ,WuS,etal.Whatmakesyour"eyes"lookdifferent? Forensic Sci Int Genet Suppl Ser. 2019;7:105-106.
Jin B, Zhu J, Wang H, et al. A primary investigation on SNPs associated with eyelid traits of Chinese Han adults. Forensic Sci Int Genet Suppl Ser. 2015;5:e669-e670.
Wang Q, Jin B, Liu F, et al. DNA-based eyelid trait prediction in Chinese Han population. Int J Leg Med. 2021;135:1743-1752.
Xie M, Song F, Li J, et al. Characteristics of SNPs related with high myopia traits in Chinese Han population. Forensic Sci Int Genet Suppl Ser. 2017;6:e35-e36.
Póspiech E,Kukla-Bartoszek M,Karłowska-Pik J,et al.Exploring the possibility of predicting human head hair greying from DNA using whole-exome and targeted NGS data. BMC Genomics. 2020;21:1-18.
Adhikari K, Fontanil T, Cal S, et al. A genome-wide association scan in admixed Latin Americans identifies loci influencing facial and scalp hair features. Nat Commun. 2016;7:1-12.
Póspiech E,Chen Y,Kukla-Bartoszek M,et al.Towards broaden-ing forensic DNA phenotyping beyond pigmentation: improving the prediction of head hair shape from DNA. Forensic Sci Int Genet. 2018;37:241-251.
Jawad M, Adnan A, Rehman RA, et al. Evaluation of facial hair-associated SNPs: a pilot study on male Pakistani Punjabi population. Forensic Sci Med Pathol. 2022;19:293-302.
International Society of Genetic Genealogy Wiki. DNAPrint Genomics. Last revision: 2015. Available from: https://isogg.org/wiki/DNAPrint_Genomics
Walsh S,Liu F,Wollstein A,et al.The HIrisPlex system for simul-taneous prediction of hair and eye colour from DNA.Forensic Sci Int Genet. 2013;7:98-115.
Chaitanya L, Breslin K, Zuñiga S, et al. The HIrisPlex-S system for eye, hair and skin colour prediction from DNA: introduction and forensic developmental validation. Forensic Sci Int Genet. 2018;35:123-135.
Department of Genetic Identification of Erasmus MC. HIrisPlex-S Eye, Hair and Skin Colour DNA Phenotyping Webtool. Last revision: 2022. Available from: https://hirisplex.erasmusmc.nl/
Ruiz Y, Phillips C, Gomez-Tato A, et al. Further development of forensic eye color predictive tests. Forensic Sci Int Genet. 2013;7: 28-40.
Söchtig J, Phillips C, Maroñas O, et al. Exploration of SNP variants affecting hair colour prediction in Europeans. Int J Leg Med. 2015;129:963-975.
Maroñas O,Phillips C,Söchtig J,et al.Development of a forensic skincolourpredictivetest.ForensicSciIntGenet.2014;13:34-44.
Xavier C, de la Puente M, Mosquera-Miguel A, et al. Devel-opment and validation of the VISAGE AmpliSeq basic tool to predict appearance and ancestry from DNA. Forensic Sci Int Genet. 2020;48:102336.
Qiagen NV, Verogen Inc. ForenSeq DNA Signature Prep Kit. Last revision: 2022. Available from: https://verogen.com/products/fo renseq-dna-signature-prep-kit/
Keating B, Bansal AT, Walsh S, et al. First all-in-one diagnos-tic tool for DNA intelligence: genome-wide inference of bio-geographic ancestry, appearance, relatedness, and sex with the Identitas v1 Forensic Chip. Int J Leg Med. 2013;127:559-572.
Identitas. IDentify. Last revision: 2022. Available from: https://www.identitascorp.com/identify-advantages/
Parabon Nanolabs. DNA Phenotyping-Parabon® Snapshot® DNA Analysis Service. Last revision: 2024. Available from: https://snapshot.parabon-nanolabs.com/phenotyping
WienrothM.Governinganticipatorytechnologypractices.Foren-sic DNA phenotyping and the forensic genetics community in Europe. New Genet Soc. 2018;37:137-152.
Samuel G, Prainsack B. Forensic DNA phenotyping in Europe: views "on the ground"from those who have a professional stake in the technology. New Genetics and Society. 2018;38:119-141.
Koops BJ, Schellekens MHM. Forensic DNA phenotyping: regu-latory issues. Colum Sci & Tech. 2008;9:158-202.
Granja R, Machado H. Forensic DNA phenotyping and its poli-tics of legitimation and contestation: views of forensic geneticists in Europe. Soc Stud Sci. 2023;53:850-868.
Samuel G, Carmen Howard H, Cornel M, et al. A response to the forensic genetics policy initiative's report 'establishing best practice for forensic DNA databases'. Forensic Sci Int Genet. 2018;36:e19-e21.
Kidd JR, Friedlaender FR, Speed WC, et al. Analyses of a set of 128 ancestry informative single-nucleotide polymorphisms in a global set of 119 population samples. Investigative Genet. 2011;2:1.
Scientific Working Group on DNA Analysis Methods (SWG-DAM). Available from: https://www.swgdam.org/
Coquet M, Terrado-Ortuño N. Forensic DNA phenotyping: pri-vacy breach, bias reification, and the pitfalls of abstract assess-ments of rights. Int J Police Sci Manag. 2023;25:262-279.
Katsara MA, Branicki W, Walsh S, et al. Evaluation of supervised machine-learning methods for predicting appearance traits from DNA. Forensic Sci Int Genet. 2021;53:102507.
Mengel-From J, Børsting C, Sanchez JJ, et al. Human eye colour and HERC2, OCA2 and MATP. Forensic Sci Int Genet. 2010;4: 323-328.
Meyer OS, Børsting C, Andersen JD. Perception of blue and brown eye colours for forensic DNA phenotyping. Forensic Sci Int Genet Suppl Ser. 2019;7:476-477.
Póspiech E, Draus-Barini J, Kupiec T, et al. Prediction of eye color from genetic data using Bayesian approach. J Forensic Sci. 2012;57:880-886.
Dembinski GM,Picard CJ.Evaluation of the IrisPlex DNA-based eye color prediction assay in a United States population. Forensic Sci Int Genet. 2014;9:111-117.
Dario P, Mouriño H, Oliveira AR, et al. Assessment of IrisPlex-based multiplex for eye and skin color prediction with appli-cation to a Portuguese population. Int J Leg Med. 2015;129: 1191-1200.
Andersen JD, Johansen P, Harder S, et al. Genetic analyses of the human eye colours using a novel objective method for eye colour classification. Forensic Sci Int Genet. 2013;7:508-515.
WollsteinA,WalshS,LiuF,etal.Novelquantitativepigmentation phenotyping enhances genetic association, epistasis, and predic-tion of human eye colour. Sci Rep. 2017;7:1-11.
Salas A, Phillips C, Carracedo A. Ancestry vs physical traits: the search for ancestry informative markers (AIMs). Int J Leg Med. 2005;120:188-189.
Wendt FR, Churchill JD, Novroski NMM, et al. Genetic analysis oftheYavapainativeAmericansfromWest-CentralArizonausing the Illumina MiSeq FGxTM forensic genomics system. Forensic Sci Int Genet. 2016;24:18-23.
Rajeevan H, Soundararajan U, Pakstis AJ, et al. Introducing the Forensic Research/Reference on Genetics knowledge base, FROG-kb. Investigative Genet. 2012;3:18.
Kidd KK, Soundararajan U, Rajeevan H, et al. The redesigned Forensic Research/Reference on Genetics knowledge base, FROG-kb. Forensic Sci Int Genet. 2018;33:33-37.
Kersbergen P, van Duijn K, Kloosterman AD, et al. Developing a set of ancestry-sensitive DNA markers reflecting continental origins of humans. BMC Genet. 2009;10:69.
Giardina E, Pietrangeli I, Martínez-Labarga C, et al. Haplotypes in SLC24A5 gene as ancestry informative markers in different populations. Curr Genomics. 2008;9:110-114.
Póspiech E,Wojas-Pelc A,Walsh S,et al.The common occurrence of epistasis in the determination of human pigmentation and its impact on DNA-based pigmentation phenotype prediction. Forensic Sci Int Genet. 2014;11:64-72.
Branicki W, Liu F, van Duijn K, et al. Model-based prediction of human hair color using DNA variants. Hum Genet. 2011;129: 443-454.
Marcínska M, Póspiech E, Abidi S, et al. Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness. PloS One. 2015;10:e0127852.
Phillips C, Fondevila M, Lareau MV. A 34-plex autosomal SNP single base extension assay for ancestry investigations. Methods Mol Biol. 2012;830:109-126.
de la Puente M, Santos C, Fondevila M, et al. The Global AIMs Nano set: a 31-plex SNaPshot assay of ancestry-informative SNPs. Forensic Sci Int Genet. 2016;22:81-88.
Bardan F,Higgins D,Austin JJ.A mini-multiplex SNaPshot assay for the triage of degraded human DNA. Forensic Sci Int Genet. 2018;34:62-70.
Muro T, Iida R, Fujihara J, et al. Simultaneous determination of seven informative Y chromosome SNPs to differentiate East Asian, European, and African populations. Leg Med. 2011;13: 134-141.
Young JM, Martin B, Kanokwongnuwut P, et al. Detection of forensicidentificationandintelligenceSNPdatafromlatentDNA using three commercial MPS panels. Forensic Sci Int Genet Suppl Ser. 2019;7:864-865.
LiuF,HendriksAEJ,Ralf A,etal.CommonDNAvariantspredict tall stature in Europeans. Hum Genet. 2014;133:587-597.
Liu F, Zhong K, Jing X, et al. Update on the predictability of tall stature from DNA markers in Europeans. Forensic Sci Int Genet. 2019;42:8-13.
Rogalla U, Rychlicka E, Derenko MV, et al. Simple and cost-effective 14-loci SNP assay designed for differentiation of Euro-pean, East Asian and African samples. Forensic Sci Int Genet. 2015;14:42-49.
Póspiech E, Karłowska-Pik J, Marcínska M, et al. Evaluation of the predictive capacity of DNA variants associated with straight hair in Europeans. Forensic Sci Int Genet. 2015;19:280-288.
Liu F, Hamer MA, Heilmann S, et al. Prediction of male-pattern baldness from genotypes. Eur J Hum Genet. 2015;24:895-902.
Qu Y, Tran D, Martinez-Marroquin E. Biogeographical Ancestry Inference from Genotype: A Comparison of Ancestral Informa-tive SNPs and Genome-wide SNPs. In: Proceedings of the 2020 IEEE Symposium series on computational intelligence (SSCI); 2020 Dec 1-4; Canberra. 2020. p. 64-70.
Jin XY, Wei YY, Lan Q, et al. A set of novel SNP loci for differ-entiating continental populations and three Chinese populations. PeerJ. 2019;7:e6508.
Truelsen DM, Farzad MS, Mogensen HS, et al. Typing of two Middle Eastern populations with the precision ID ancestry panel. Forensic Sci Int Genet Suppl Ser. 2017;6:e301-e302.
Daniel R, Sanchez JJ, Nassif NT, et al. SNPs associated with physicaltraits:avaluabletoolfortheinferenceofbiogeographical ancestry. Forensic Sci Int Genet Suppl Ser. 2008;1:538-540.
Poetsch M, Blöhm R, Harder M, et al. Prediction of people's origin from degraded DNA-presentation of SNP assays and calculation of probability. Int J Leg Med. 2013;127:347-357.
Gu Y, Yun L, Zhang L, et al. The potential forensic utility of two single nucleotide polymorphisms in predicting biogeographical ancestry. Forensic Sci Int Genet Suppl Ser. 2011;3:e105-e106.
Soejima M, Koda Y. Population differences of two coding SNPs in pigmentation-related genes SLC24A5 and SLC45A2.Int J Leg Med. 2007;121:36-39.
WettonJH,TsangKW,KhanH.Inferringthepopulationoforigin of DNA evidence within the UK by allele-specific hybridization of Y-SNPs. Forensic Sci Int. 2005;152:45-53.
Yuasa I, Umetsu K, Watanabe G, et al. MATP polymorphisms in Germans and Japanese: the L374F mutation as a population marker for Caucasoids. Int J Leg Med. 2004;118:364-366.
Hunter P. Uncharted waters: next-generation sequencing and machine learning software allow forensic sicente to expand into phenotype prediction from DNA samples. EMBO Rep. 2018;19:e45810.
Caliebe A, Walsh S, Liu F, et al. Likelihood ratio and posterior odds in forensic genetics: two sides of the same coin. Forensic Sci Int Genet. 2017;28:203-210.
Albert FW, Kruglyak L. The role of regulatory variation in complex traits and disease. Nat Rev Genet. 2015;16:197-212.
Bradbury C, Köttgen A, Staubach F. Off-target phenotypes in forensic DNA phenotyping and biogeographic ancestry inference: a resource. Forensic Sci Int Genet. 2019;38:93-104.
Venables SJ, Mehta B, Daniel R, et al. Assessment of high resolution melting analysis as a potential SNP genotyp-ing technique in forensic casework. Electrophoresis. 2014;35: 3036-3043.
Ragazzo M, Puleri G, Errichiello V, et al. Evaluation of OpenAr-rayTM as a genotyping method for Forensic DNA phenotyping and human identification. Genes (Basel). 2021;12:1-10.
Mehta B, Daniel R, McNevin D. HRM and SNaPshot as alterna-tive forensic SNP genotyping methods. Forensic Sci Med Pathol. 2017;13:293-301.
Oh S, Kim J, Park S, et al. Prediction of Y haplogroup by polymerasechainreaction-reverseblothybridizationassay.Genes Genomics. 2019;41:297-304.
Lundsberg B, Johansen P, Børsting C, et al. Development and optimisation of five multiplex assays with 115 of the AIM SNPs from the EUROFORGEN AIMs set on the Sequenom® MassARRAY® system. Forensic Sci Int Genet Suppl Ser. 2013;4: e182-e183.
Hwa HL, Lin CP, Huang TY, et al. A panel of 130 autosomal single-nucleotide polymorphisms for ancestry assignment in five Asian populations and in Caucasians. Forensic Sci Med Pathol. 2017;13:177-187.
Ribeiro J, Pereira V, Kondili A, et al. Typing of 111 ancestry informative markers in an Albanian population. Forensic Sci Int Genet Suppl Ser. 2015;5:e124-e125.
Ren P, Liu J, Zhao H, et al. Construction of a rapid microfluidic-based SNP genotyping (MSG) chip for ancestry inference. Foren-sic Sci Int Genet. 2019;41:145-151.
Daniel R, Santos C, Phillips C, et al. A SNaPshot of next genera-tion sequencing for forensic SNP analysis. Forensic Sci Int Genet. 2015;14:50-60.
Mehta B,Daniel R,Phillips C,et al.Massively parallel sequencing of customised forensically informative SNP panels on the MiSeq. Electrophoresis. 2016;37:2832-2840.
Breslin K, Wills B, Ralf A, et al. HIrisPlex-S system for eye, hair, and skin color prediction from DNA: massively parallel sequencing solutions for two common forensically used plat-forms. Forensic Sci Int Genet. 2019;43:102152.
Yang Y, Xie B, Yan J. Application of next-generation sequencing technology in forensic science. Genomics Proteomics Bioinfor-matics. 2014;12:190-197.
Ambers AD, Churchill JD, King JL, et al. More comprehensive forensic genetic marker analyses for accurate human remains identification using massively parallel DNA sequencing. BMC Genomics. 2016;17:21-30.
Jäger AC, Alvarez ML, Davis CP, et al. Developmental validation of the MiSeq FGx forensic genomics system for targeted next generation sequencing in forensic DNA casework and database laboratories. Forensic Sci Int Genet. 2017;28:52-70.
Turchi C, Onofri V, Melchionda F, et al. Development of a foren-sic DNA phenotyping panel using massive parallel sequencing. Forensic Sci Int Genet Suppl Ser. 2019;7:177-179.
Melchionda F, Silvestrini B, Robino C, et al. Development and validationofMPS-basedsystemforhumanappearanceprediction in challenging forensic samples. Genes (Basel). 2022;13:1688.
Young JM, Power D, Kanokwongnuwut P, et al. Ancestry and phenotype predictions from touch DNA using massively parallel sequencing. Int J Leg Med. 2021;135:81-89.
Ralf A, Kayser M. Investigative DNA analysis of two-person mixed crime scene trace in a murder case. Forensic Sci Int Genet. 2021;54:102557.
Diepenbroek M, Bayer B, Anslinger K. Pushing the boundaries: forensic DNA phenotyping challenged by single-cell sequencing. Genes (Basel). 2021;12:1362.
Kukla-Bartoszek M, Teisseyre P, Póspiech E, et al. Searching for improvements in predicting human eye colour from DNA. Int J Leg Med. 2021;135:2175-2187.
Cheung EYY, Gahan ME, McNevin D. Prediction of biogeo-graphical ancestry in admixed individuals.Forensic Sci Int Genet. 2018;36:104-111.
Katsara MA, Branicki W, Póspiech E, et al. Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modelling of human appearance traits. Forensic Sci Int Genet. 2021;50:102412.
Kastelic V, Drobnič K. A single-nucleotide polymorphism (SNP) multiplex system: the association of five SNPs with human eye and hair color in the Slovenian population and comparison using a Bayesian network and logistic regression model. Croat Med J. 2012;53:401-408.
Zaorska K, Zawierucha P, Nowicki M. Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches. Hum Genet. 2019;138:635-647.
Zidkova A, Horinek A, Stenzl V, et al. Application of multifactor dimensionality reduction analysis and Bayesian networks for eye color and ancestry prediction for forensic purposes in the Czech Republic. Forensic Sci Int Genet Suppl Ser. 2013;4:e322-e323.
Pfaffelhuber P, Rohde A. A central limit theorem concerning uncertainty in estimates of individual admixture. Theor Popul Biol. 2022;148:28-39.
Bulbul O, Filoglu G, Zorlu T, et al. Inference of biogeograph-ical ancestry across central regions of Eurasia. Int J Leg Med. 2016;130:73-79.
PóspiechE,Draus-BariniJ,KupiecT,etal.Gene-geneinteractions contribute to eye colour variation in humans. J Hum Genet. 2011;56:447-455.
Palmal S, Adhikari K, Mendoza-Revilla J, et al. Prediction of eye, hair and skin colour in Latin Americans. Forensic Sci Int Genet. 2021;53:102517.
Salvoro C, Faccinetto C, Zucchelli L, et al. Performance of four models for eye color prediction in an Italian population sample. Forensic Sci Int Genet. 2019;40:192-200.
Meyer OS, Salvo NM, Kjærbye A, et al. Prediction of eye colour in Scandinavians using the EyeColour 11 (EC11) SNP set. Genes (Basel). 2021;12:821.
CaliebeA,HarderM,SchuettR,etal.Themorethemerrier?How a few SNPs predict pigmentation phenotypes in the Northern German population. Eur J Hum Genet. 2015;24:739-747.
Pfaffelhuber P, Sester-Huss E, Baumdicker F, et al. Inference of recent admixture using genotype data. Forensic Sci Int Genet. 2022;56:102593.
Walsh S, Wollstein A, Liu F, et al. DNA-based eye colour pre-diction across Europe with the IrisPlex system. Forensic Sci Int Genet. 2012;6:330-340.
Caliebe A, Krawczak M, Kayser M. Predictive values in foren-sic DNA phenotyping are not necessarily prevalence-dependent. Forensic Sci Int Genet. 2018;33:e7-e8.
Pereira V, Mogensen HS, Børsting C, et al. Evaluation of the Precision ID ancestry panel for crime case work: a SNP typing assay developed for typing of 165 ancestral informative markers. Forensic Sci Int Genet. 2017;28:138-145.
Hussing C, Huber C, Bytyci R, et al. Sequencing of 231 forensic genetic markers using the MiSeq FGxTM forensic genomics system-anevaluationoftheassayandsoftware.ForensicSciRes. 2018;3:111-123.
Brión M, Sanchez JJ, Balogh K, et al. Analysis of 29 Y-chromosome SNPs in a single multiplex useful to predict the geographic origin of male lineages. Int Congr Ser. 2006;1288: 13-15.
Brión M, Sanchez JJ, Balogh K, et al. Introduction of a sin-gle nucleotide polymorphism-based 'major Y-chromosome hap-logroup typing kit' suitable for predicting the geographical origin of male lineages. Electrophoresis. 2005;26:4411-4420.
Lessig R, Edelmann J, Thiele K, et al. Results of Y-SNP typing in three different populations. Forensic Sci Int Genet Suppl Ser. 2008;1:219-221.
Brión M, Sobrino B, Blanco-Verea A, et al. Hierarchical analysis of 30 Y-chromosome SNPs in European populations. Int J Leg Med. 2005;119:10-15.
Onofri V, Alessandrini F, Turchi C, et al. Development of mul-tiplex PCRs for evolutionary and forensic applications of 37 human Y chromosome SNPs. Forensic Sci Int. 2006;157:23-35.
Bouakaze C, Keyser C, Amory S, et al. First successful assay of Y-SNP typing by SNaPshot minisequencing on ancient DNA. Int J Leg Med. 2007;121:493-499.
Chiurillo MA, Lander N, Rojas M, et al. Development of Y-SNP typing assay for forensic application in Venezuelan population. Forensic Sci Int Genet Suppl Ser. 2009;2:444-445.
Noveski P, Trivodalieva S, Efremov GD, et al. Y chromosome single nucleotide polymorphisms typing by SNaPshot MINISE-QUENCING. Balk J Med Genet. 2010;13:9-16.
van Oven M, Ralf A, Kayser M. An efficient multiplex genotyping approach for detecting the major worldwide human Y-chromosome haplogroups. Int J Leg Med. 2011;125: 879-885.
Ralf A, van Oven M, Montiel González D, et al. Forensic Y-SNP analysis beyond SNaPshot: high-resolution Y-chromosomal haplogrouping from low quality and quantity DNA using ion AmpliSeqandtargetedmassivelyparallelsequencing.ForensicSci Int Genet. 2019;41:93-106.
McNevin D, Bate A, Daniel R, et al. A preliminary mitochondrial DNA SNP genotyping assay for inferring genealogy.Aust J Foren-sic Sci. 2011;43:39-51.
van Oven M, Vermeulen M, Kayser M. Multiplex genotyping system for efficient inference of matrilineal genetic ancestry with continental resolution. Investigative Genet. 2011;2:6.
Ballantyne KN, van Oven M, Ralf A, et al. MtDNA SNP multi-plexes for efficient inference of matrilineal genetic ancestry within Oceania. Forensic Sci Int Genet. 2012;6:425-436.
Chaitanya L, van Oven M, Weiler N, et al. Developmental validation of mitochondrial DNA genotyping assays for adept matrilineal inference of biogeographic ancestry at a continental level. Forensic Sci Int Genet. 2014;11:39-51.
Palencia-Madrid L, Vinueza-Espinosa D, Baeta M, et al. Val-idation of a 52-mtSNP minisequencing panel for haplogroup classification of forensic DNA samples.Int J Leg Med.2020;134: 929-936.
Daniel R, Walsh SJ, Piper A. Investigation of single-nucleotide polymorphisms associated with ethnicity. Int Congr Ser. 2006; 1288:79-81.
Fondevila M,Phillips C,Santos C,et al.Revision of the SNPforID 34-plex forensic ancestry test: assay enhancements, standard reference sample genotypes and extended population studies. Forensic Sci Int Genet. 2013;7:63-74.
Phillips C, Fondevila M, Vallone PM, et al. Characterization of U.S. population samples using a 34plex ancestry informa-tive SNP multiplex. Forensic Sci Int Genet Suppl Ser. 2011;3: e182-e183.
Khodjet-El-Khil H, Fadhlaoui-Zid K, Cherni L, et al. Genetic analysis of the SNPforID 34-plex ancestry informative SNP panel in Tunisian and Libyan populations. Forensic Sci Int Genet. 2011;5:e45-e47.
Prestes PR, Mitchell RJ, Santos C, et al. The SNPforID 34-plex- its ability to infer level of admixture in individuals. Forensic Sci Int Genet Suppl Ser. 2013;4:e13-e14.
Santos C,Fondevila M,Ballard D,et al.Forensic ancestry analysis with two capillary electrophoresis ancestry informative marker (AIM)panels:resultsofacollaborativeEDNAPexercise.Forensic Sci Int Genet. 2015;19:56-67.
Gomes C, Fondevila M, Palomo-Díez S, et al. Phenotyping the ancient world: the physical appearance and ancestry of very degraded samples from a chalcolithic human remains. Forensic Sci Int Genet Suppl Ser. 2017;6:e484-e486.
Daniel R, Sanchez JJ, Nassif NT, et al. Partial forensic validation of a 16plex SNP assay for the inference of biogeographical ancestry. Forensic Sci Int Genet Suppl Ser. 2009;2:477-478.
Eduardoff M, Gross TE, Santos C, et al. Interlaboratory evalu-ation of the EUROFORGEN Global ancestry-informative SNP panel by massively parallel sequencing using the ion PGM™. Forensic Sci Int Genet. 2016;23:178-189.
Bulbul O, Filoglu G. Development of a SNP panel for predicting biogeographical ancestry and phenotype using massively parallel sequencing. Electrophoresis. 2018;39:2743-2751.
Daca-Roszak P, Pfeifer A, Zebracka-Gala J, et al. EurEAs_Gplex-a new SNaPshot assay for continental population discrimination and gender identification. Forensic Sci Int Genet. 2016;20:89-100.
Bulbul O, Cherni L, Khodjet-El-Khil H, et al. Evaluating a subset of ancestry informative SNPs for discriminating among South-west Asian and circum-Mediterranean populations. Forensic Sci Int Genet. 2016;23:153-158.
Li CX, Pakstis AJ, Jiang L, et al. A panel of 74 AISNPs: improved ancestry inference within Eastern Asia. Forensic Sci Int Genet. 2016;23:101-110.
Yuasa I, Akane A, Yamamoto T, et al. Japaneseplex: a forensic SNP assay for identification of Japanese people using Japanese-specific alleles. Leg Med. 2018;33:17-22.
Freire-Aradas A, Ruiz Y, Phillips C, et al. Exploring iris colour prediction and ancestry inference in admixed populations of South America. Forensic Sci Int Genet. 2014;13:3-9.
GrossTE,ZaumsegelD,RothschildMA,etal.Combinedanalysis of two different ancestry informative assays using SNPs and Indels in Eurasian populations. Forensic Sci Int: Genet Suppl. 2013;4:e25-e26.
Phillips C, McNevin D, Kidd KK, et al. MAPlex-a massively parallel sequencing ancestry analysis multiplex for Asia-Pacific populations. Forensic Sci Int Genet. 2019;42:213-226.
Cheung EYY, Phillips C, Eduardoff M, et al. Performance of ancestry-informative SNP and microhaplotype markers. Forensic Sci Int Genet. 2019;43:102141.
Xavier C, de la Puente M, Phillips C, et al. Forensic evaluation of the Asia Pacific ancestry-informative MAPlex assay. Forensic Sci Int Genet. 2020;48:102344.
Espregueira Themudo G, Smidt Mogensen H, Børsting C, et al. Frequencies of HID-ion AmpliSeq ancestry panel markers among Greenlanders. Forensic Sci Int Genet. 2016;24:60-64.
García O, Ajuriagerra JA, Alday A, et al. Frequencies of the precision ID ancestry panel markers in Basques using the ion torrent PGM™ platform. Forensic Sci Int Genet. 2017;31: e1-e4.
Nakanishi H, Pereira V, Børsting C, et al. Analysis of mainland Japanese and Okinawan Japanese populations using the precision ID ancestry panel. Forensic Sci Int Genet. 2018;33:106-109.
Wang Z, He G, Luo T, et al. Massively parallel sequencing of 165 ancestry informative SNPs in two Chinese Tibetan-Burmese minority ethnicities. Forensic Sci Int Genet. 2018;34:141-147.
Pereira V, Santangelo R, Børsting C, et al. Evaluation of the Precision of ancestry inferences in South American admixed populations. Front Genet. 2020;11:966.
Xie T, Shen C, Liu C, et al. Ancestry inference and admix-ture component estimations of Chinese Kazak group based on 165 AIM-SNPs via NGS platform. J Hum Genet. 2020;65: 461-468.
He G, Liu J, Wang M, et al. Massively parallel sequencing of 165 ancestry-informative SNPs and forensic biogeographical ancestry inferenceinthreeSouthernChineseSinitic/Tai-Kadaipopulations. Forensic Sci Int Genet. 2021;52:102475.
Cooley AM, Meiklejohn KA, Damaso N, et al. Performance comparison of massively parallel sequencing (MPS) instruments using single-nucleotide polymorphism (SNP) panels for ancestry. SLAS Technol. 2021;26:103-112.
Shan MA,Meyer OS,Refn M,et al.Analysis of skin pigmentation and genetic ancestry in three subpopulations from Pakistan: Punjabi, Pashtun, and Baloch. Genes (Basel). 2021;12:733.
Jin S, Chase M, Henry M, et al. Implementing a biogeographic ancestry inference service for forensic casework. Electrophoresis. 2018;39:2757-2765.
Mogensen HS, Tvedebrink T, Børsting C, et al. Ancestry predic-tion efficiency of the software GenoGeographer using a z-score method and the ancestry informative markers in the Precision ID ancestry panel. Forensic Sci Int Genet. 2020;44:102154.
Walsh S, Lindenbergh A, Zuniga SB, et al. Developmental valida-tion of the IrisPlex system: determination of blue and brown iris colour for forensic intelligence. Forensic Sci Int Genet. 2011;5: 464-471.
Chaitanya L, Walsh S, Andersen JD, et al. Collaborative EDNAP exercise on the IrisPlex system for DNA-based pre-diction of human eye colour. Forensic Sci Int Genet. 2014;11: 241-251.
Prestes PR, Mitchell RJ, Daniel R, et al. Evaluation of the IrisPlex system in admixed individuals. Forensic Sci Int Genet Suppl Ser. 2011;3:e283-e284.
Purps J, Geppert M, Nagy M, et al. Evaluation of the IrisPlex eye colour prediction tool in a German population sample. Forensic Sci Int Genet Suppl Ser. 2011;3:e202-e203.
Pneuman A, Budimlija ZM, Caragine T, et al. Verification of eye and skin color predictors in various populations. Leg Med. 2012;14:78-83.
Martinez-Cadenas C,Peña-Chilet M,Llorca-Cardeñosa MJ,et al. Gender and eye colour prediction discrepancies: a reply to criti-cisms. Forensic Sci Int Genet. 2014;9:e7-e9.
Liu F, Walsh S, Kayser M. Of sex and IrisPlex eye colour predic-tion: a reply to Martinez-Cadenas et al. Forensic Sci Int Genet. 2014;9:e5-e6.
Póspiech E, Karłowska-Pik J, Ziemkiewicz B, et al. Further evi-dence for population specific differences in the effect of DNA markers and gender on eye colour prediction in forensics. Int J Leg Med. 2016;130:923-934.
Yun L, Gu Y, Rajeevan H, et al. Application of six IrisPlex SNPs and comparison of two eye color prediction systems in diverse Eurasia populations. Int J Leg Med. 2014;128:447-453.
Bulbul O, Zorlu T, Filoglu G. Prediction of human eye colour using highly informative phenotype SNPs (PISNPs). Aus J Foren-sic Sci. 2018;52:27-37.
Al-Rashedi NAM, Mandal AM, ALObaidi LA. Eye color predic-tion using the IrisPlex system: a limited pilot study in the Iraqi population. Egypt J Forensic Sci. 2020;10:1-6.
Liu F, van Duijn K, Vingerling JR, et al. Eye color and the prediction of complex phenotypes from genotypes. Curr Biol. 2009;19:R192-R193.
Kastelic V, Póspiech E, Draus-Barini J, et al. Prediction of eye color in the Slovenian population using the IrisPlex SNPs. Croat Med J. 2013;54:381-386.
Paparazzo E, Gozalishvili A, Lagani V, et al. A new approach to broaden the range of eye colour identifiable by IrisPlex in DNA phenotyping. Sci Rep. 2022;12:1-10.
AllwoodJS,HarbisonSA.SNPmodeldevelopmentforthepredic-tionofeyecolourinNewZealand.ForensicSciIntGenet.2013;7: 444-452.
Shapturenko MN, Vakula SI, Kandratsiuk AV, et al. HERC2 (rs12913832) and OCA2 (rs1800407) genes polymorphisms in relation to iris color variation in Belarusian population. Forensic Sci Int Genet Suppl Ser. 2019;7:331-332.
Alghamdi J, Amoudi M, Kassab AC, et al. Eye color prediction usingsinglenucleotidepolymorphismsinSaudipopulation.Saudi J Biol Sci. 2019;26:1607-1612.
Walsh S, Kayser M. A practical guide to the HIrisPlex system: simultaneous prediction of eye and hair color from DNA. Meth-ods Mol Biol. 2016;1420:213-231.
Draus-Barini J, Walsh S, Póspiech E, et al. Bona fide colour: DNA prediction of human eye and hair colour from ancient and contemporaryskeletalremains.InvestigativeGenet.2013;4:1-15.
Walsh S, Chaitanya L, Clarisse L, et al. Developmental validation of the HIrisPlex system: DNA-based eye and hair colour pre-diction for forensic and anthropological usage. Forensic Sci Int Genet. 2014;9:150-161.
Chaitanya L, Pajnič IZ, Walsh S, et al. Bringing colour back after 70 years: predicting eye and hair colour from skeletal remains of World War II victims using the HIrisPlex system. Forensic Sci Int Genet. 2017;26:48-57.
ZupaničPI.IdentificationofaSlovenianprewarelitecouplekilled in the Second World War. Forensic Sci Int. 2021;327:110994.
Kukla-Bartoszek M, Póspiech E, Spólnicka M, et al. Investigating the impact of age-depended hair colour darkening during child-hood on DNA-based hair colour prediction with the HIrisPlex system. Forensic Sci Int Genet. 2018;36:26-33.
Carratto TMT, Marcorin L, do Valle-Silva G, et al. Prediction of eye and hair pigmentation phenotypes using the HIrisPlex system in a Brazilian admixed population sample. Int J Leg Med. 2021;135:1329-1339.
Grimes EA, Noake PJ, Dixon L, et al. Sequence polymorphism in the human melanocortin 1 receptor gene as an indicator of the red hair phenotype. Forensic Sci Int. 2001;122:124-129.
Branicki W, Kupiec T, Wolánska-Nowak P, et al. Determination of forensically relevant SNPs in the MC1R gene. Int Congr Ser. 2006;1288:816-818.
Branicki W, Brudnik U, Kupiec T, et al. Determination of pheno-type associated SNPs in the MC1R gene. J Forensic Sci. 2007;52: 349-354.
Branicki W, Wolánska-Nowak P, Brudnik U, et al. Forensic application of a rapid test for red hair colour prediction and sex determination. Z Zagadnien Nauk Sadowych. 2007;69:37-51.
Marano LA, Andersen JD, Goncalves FT, et al. Evaluation of HIrisplex-S system markers for eye,skin and hair color prediction in an admixed Brazilian population. Forensic Sci Int Genet Suppl Ser. 2019;7:427-428.
Carratto TMT, Marcorin L, Debortoli G, et al. Evaluation of the HIrisPlex-S system in a Brazilian population sample. Forensic Sci Int Genet Suppl Ser. 2019;7:794-796.
Kukla-BartoszekM,SzargutM,PóspiechE,etal.Thechallengeof predicting human pigmentation traits in degraded bone samples with the MPS-based HIrisPlex-S system. Forensic Sci Int Genet. 2020;47:102301.
Chen Y, Branicki W, Walsh S, et al. The impact of correlations between pigmentation phenotypes and underlying genotypes on genetic prediction of pigmentation traits. Forensic Sci Int Genet. 2021;50:102395.
Gentile F, Cherubini A, Colloca D, et al. Evaluation of PyroMark Q48 autoprep with HIrisPlex-S in an Italian population sample. Forensic Sci Int Genet Suppl Ser. 2022;8:308-310.
Valenzuela RK, Henderson MS, Walsh MH, et al. Predicting phenotype from genotype: normal pigmentation. J Forensic Sci. 2010;55:315-322.
Spichenok O, Budimlija ZM, Mitchell AA,et al. Prediction of eye and skin color in diverse populations using seven SNPs. Forensic Sci Int Genet. 2011;5:472-478.
Hart KL, Kimura SL, Mushailov V, et al. Improved eye-and skin-color prediction based on 8 SNPs. Croat Med J. 2013;54: 248-256.
Mushailov V, Rodriguez SA, Budimlija ZM, et al. Assay develop-ment and validation of an 8-SNP multiplex test to predict eye and skin coloration. J Forensic Sci. 2015;60:990-1000.
LimS,YounJP,HongS,etal.CustomizedmultiplexingSNPpanel for Korean-specific DNA phenotyping in forensic applications. Genes Genomics. 2017;39:723-732.
Liu F, Chen Y, Zhu G, et al. Meta-analysis of genome-wide asso-ciation studies identifies 8 novel loci involved in shape variation of human head hair. Hum Mol Genet. 2018;27:559-575.
Póspiech E, Karłowska-Pik J, Kukla-Bartoszek M, et al. Overlap-ping association signals in the genetics of hair-related phenotypes in humans and their relevance to predictive DNA analysis.Foren-sic Sci Int Genet. 2022;59:102693.
Fagertun J, Wolffhechel K, Pers TH, et al. Predicting facial char-acteristics from complex polygenic variations. Forensic Sci Int Genet. 2015;19:263-268.
Qiao L, Yang Y, Fu P, et al. Genome-wide variants of Eurasian facial shape differentiation and a prospective model of DNA based face prediction. J Genet Genomics. 2018;45:419-432.
Noreen S, Ballard D, Mehmood T, et al. Evaluation of loci to predict ear morphology using two SNaPshot assays. Forensic Sci Med Pathol. 2022;19:335-356.
Hussing C, Børsting C, Mogensen HS, et al. Testing of the Illumina® ForenSeq™ kit. Forensic Sci Int Genet Suppl Ser. 2015;5:e449-e450.
Churchill JD, Schmedes SE, King JL, et al. Evaluation of the Illumina® Beta version ForenSeq™ DNA signature prep kit for use in genetic profiling. Forensic Sci Int Genet. 2016;20:20-29.
Churchill JD, Novroski NMM, King JL, et al. Population and performance analyses of four major populations with Illumina's FGx forensic genomics system. Forensic Sci Int Genet. 2017;30: 81-92.
Silvia AL, Shugarts N, Smith J. A preliminary assessment of the ForenSeq™ FGx system: next generation sequencing of an STR and SNP multiplex. Int J Leg Med. 2017;131:73-86.
Sidstedt M, Junker K, Forsberg C, et al. In-house validation of MPS-based methods in a forensic laboratory. Forensic Sci Int Genet Suppl Ser. 2019;7:635-636.
Sharma V, Jani K, Khosla P, et al. Evaluation of ForenSeq™ signature prep kit B on predicting eye and hair coloration as well as biogeographical ancestry by using Universal Analysis Soft-ware (UAS) and available web-tools. Electrophoresis. 2019;40: 1353-1364.
Frégeau CJ. Validation of the Verogen ForenSeq™ DNA signa-ture prep kit/primer mix B for phenotypic and biogeographical ancestry predictions using the micro MiSeq® flow cells. Forensic Sci Int Genet. 2021;53:102533.
Salvo NM,JanssenK,KirsebomMK,etal.Predicting eyeand hair colour in a Norwegian population using Verogen's ForenSeq™ DNA signature prep kit. Forensic Sci Int Genet. 2022;56: 102620.
Weisz NA, Roberts KA, Hardy WR. Reliability of phenotype estimation and extended classification of ancestry using decedent samples. Int J Leg Med. 2021;135:2221-2233.
Barbaríc L, Horjan-Zanki I. Challenges in the recovery of the genetic data from human remains found on the Western Balkan migration route. Int J Leg Med. 2022;137:181-193.
Frégeau CJ. A multiple predictive tool approach for phenotypic and biogeographical ancestry inferences. Can Soc Forensic Sci J. 2021;55:71-99.
Junker K, Staadig A, Sidstedt M, et al. Phenotype prediction accuracy-aSwedishperspective.ForensicSciIntGenetSupplSer. 2019;7:384-386.
Magdalena M, Wróbel M, Parys-Proszek A, et al. Evaluation of the performance of the beta version of the ForenSeq DNA signature prep kit on the MiSeq FGx forensic genomics system. Forensic Sci Int Genet Suppl Ser. 2019;7:585-586.
Guo F, Yu J, Zhang L, et al. Massively parallel sequencing of forensic STRs and SNPs using the Illumina® ForenSeq™ DNA signature prep kit on the MiSeq FGx™ forensic genomics system. Forensic Sci Int Genet. 2017;31:135-148.
Ramani A, Wong Y, Tan SZ, et al. Ancestry prediction in Singa-porepopulationsamplesusingtheIlluminaForenSeqkit.Forensic Sci Int Genet. 2017;31:171-179.
Bouakaze C, Keyser C, Crubézy E, et al. Pigment phenotype and biogeographical ancestry from ancient skeletal remains: infer-ences from multiplexed autosomal SNP analysis. Int J Leg Med. 2009;123:315-325.
Butler K, Peck M, Hart J, et al. Molecular "eyewitness": forensic predictionofphenotypeandancestry.ForensicSciIntGenetSuppl Ser. 2011;3:e498-e499.
Castel C, Piper A. Development of a SNP multiplex assay for the inference of biogeographical ancestry and pigmenta-tion phenotype. Forensic Sci Int Genet Suppl Ser. 2011;3: e411-e412.
Gettings KB,Lai R,Johnson JL,et al.A 50-SNP assay for biogeo-graphic ancestry and phenotype prediction in the U.S.population. Forensic Sci Int Genet. 2014;8:101-108.
Bulbul O, Filoglu G, Altuncul H, et al. A SNP multiplex for the simultaneous prediction of biogeographic ancestry and pigmentation type. Forensic Sci Int Genet Suppl Ser. 2011;3: e500-e501.
Palencia-Madrid L, Xavier C, de la Puente M, et al. Evaluation of the VISAGE basic tool for appearance and ancestry prediction using PowerSeq chemistry on the MiSeq FGx system. Genes. 2020;11:708.
de la Puente M, Ruiz-Ramírez J, Ambroa-Conde A, et al. Devel-opment and evaluation of the ancestry informative marker panel of the VISAGE basic tool. Genes. 2021;12:1284.
Xavier C, de la Puente M, Sidstedt M, et al. Evaluation of the VISAGE basic tool for appearance and ancestry inference using ForenSeq® chemistry on the MiSeq FGx® system. Forensic Sci Int Genet. 2022;58:102675.
Diepenbroek M, Bayer B, Schwender K, et al. Evaluation of the ion AmpliSeq™ PhenoTrivium panel: MPS-based assay for ances-try and phenotype predictions challenged by casework samples. Genes. 2020;11:1398.
Rauf S, Austin JJ, Higgins D, et al. Unveiling forensically rel-evant biogeographic, phenotype and Y-chromosome SNP vari-ation in Pakistani ethnic groups using a customized hybridisa-tion enrichment forensic intelligence panel. PloS One. 2022;17: e0264125.
Fesenko DO, Ivanovsky ID, Ivanov PL, et al. A biochip for genotyping polymorphisms associated with eye, hair, skin color, ABO blood group, sex, Y chromosome core haplogroup, and its application to study the Slavic population. Mol Biol. 2022;56: 780-799.