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Review Article | Open Access

Advances in forensic DNA phenotyping

Caixia Li1,C, Hao Zhang1,§, Chao Liu2( ), Lan Hu1( )
Key Laboratory of Forensic Genetics, Beijing Engineering Research Center of Crime Scene Evidence Examination, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing 100038, China
State Key Laboratory of Bioactive Molecules and Druggability Assessment, Guangdong Basic Research Center of Excellence for Natural Bioactive Molecules and Discovery of Innovative Drugs, Jinan University, Guangzhou 510632, China

§The first two authors contributed equally to this paper.

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Abstract

Forensic DNA phenotyping (FDP) refers to a suite of technologies that infer phenotypic information from the genetic material of biological samples. These technologies play a critical role in criminal investigations. This review systematically summarizes recent advances in four key areas: biogeographical ancestry inference, forensic genetic genealogy, appearance prediction, and age prediction. We discuss the underlying genetic principles, current methodological approaches, major achievements, persistent challenges, and outline directions for future research to bridge the gap between forensic DNA phenotyping technologies and operational casework.

Keywords

forensic geneticsforensic DNA phenotypingbiogeographical ancestryforensic genetic genealogy

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Forensic Science Advances
Volume 1 Issue 1,
October 2026
Pages 33-40
DOI: 10.26599/FSA.2026.9750002

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Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

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Cite this article:
Li C, Zhang H, Liu C, et al. Advances in forensic DNA phenotyping. Forensic Science Advances, 2026, 1(1): 33-40. https://doi.org/10.26599/FSA.2026.9750002

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Received: 29 July 2026
Revised: 21 August 2026
Accepted: 24 August 2026
Published: 30 October 2026
© The Editorial Office of Forensic Science Advances 2026. Published by Tsinghua University Press

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License (CC BY-NC-ND 4.0). See https://creativecommons.org/licenses/by-nc-nd/4.0/.