Applications of Massively Parallel Sequencing in Forensic Genetics

Overview

Journal Genet Mol Biol

Specialty Genetics

Date 2022 Sep 19

PMID 36121926

Authors

Thassia Mayra Telles Carratto

Vitor Matheus Soares Moraes

Tamara Soledad Frontanilla Recalde

Maria Luiza Guimaraes de Oliveira

Celso Teixeira Mendes-Junior

Affiliations

Soon will be listed here.

Abstract

Massively parallel sequencing, also referred to as next-generation sequencing, has positively changed DNA analysis, allowing further advances in genetics. Its capability of dealing with low quantity/damaged samples makes it an interesting instrument for forensics. The main advantage of MPS is the possibility of analyzing simultaneously thousands of genetic markers, generating high-resolution data. Its detailed sequence information allowed the discovery of variations in core forensic short tandem repeat loci, as well as the identification of previous unknown polymorphisms. Furthermore, different types of markers can be sequenced in a single run, enabling the emergence of DIP-STRs, SNP-STR haplotypes, and microhaplotypes, which can be very useful in mixture deconvolution cases. In addition, the multiplex analysis of different single nucleotide polymorphisms can provide valuable information about identity, biogeographic ancestry, paternity, or phenotype. DNA methylation patterns, mitochondrial DNA, mRNA, and microRNA profiling can also be analyzed for different purposes, such as age inference, maternal lineage analysis, body-fluid identification, and monozygotic twin discrimination. MPS technology also empowers the study of metagenomics, which analyzes genetic material from a microbial community to obtain information about individual identification, post-mortem interval estimation, geolocation inference, and substrate analysis. This review aims to discuss the main applications of MPS in forensic genetics.

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References

Naue J, Hoefsloot H, Mook O, Rijlaarsdam-Hoekstra L, van der Zwalm M, Henneman P . Chronological age prediction based on DNA methylation: Massive parallel sequencing and random forest regression. Forensic Sci Int Genet. 2017; 31:19-28. DOI: 10.1016/j.fsigen.2017.07.015. View

Teschendorff A, West J, Beck S . Age-associated epigenetic drift: implications, and a case of epigenetic thrift?. Hum Mol Genet. 2013; 22(R1):R7-R15. PMC: 3782071. DOI: 10.1093/hmg/ddt375. View

Dorum G, Ingold S, Hanson E, Ballantyne J, Snipen L, Haas C . Predicting the origin of stains from next generation sequencing mRNA data. Forensic Sci Int Genet. 2018; 34:37-48. DOI: 10.1016/j.fsigen.2018.01.001. View

Li H, Bi R, Fan Y, Wu Y, Tang Y, Li Z . mtDNA Heteroplasmy in Monozygotic Twins Discordant for Schizophrenia. Mol Neurobiol. 2016; 54(6):4343-4352. DOI: 10.1007/s12035-016-9996-x. View

Kulstein G, Schacker U, Wiegand P . Old meets new: Comparative examination of conventional and innovative RNA-based methods for body fluid identification of laundered seminal fluid stains after modular extraction of DNA and RNA. Forensic Sci Int Genet. 2018; 36:130-140. DOI: 10.1016/j.fsigen.2018.06.017. View

Jager A, Alvarez M, Davis C, Guzman E, Han Y, Way L . 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. DOI: 10.1016/j.fsigen.2017.01.011. View

Zhang X, Shen C, Jin X, Guo Y, Xie T, Zhu B . Developmental validations of a self-developed 39 AIM-InDel panel and its forensic efficiency evaluations in the Shaanxi Han population. Int J Legal Med. 2021; 135(4):1359-1367. DOI: 10.1007/s00414-021-02600-4. View

Breslin K, Wills B, Ralf A, Ventayol Garcia M, Kukla-Bartoszek M, Pospiech E . HIrisPlex-S system for eye, hair, and skin color prediction from DNA: Massively parallel sequencing solutions for two common forensically used platforms. Forensic Sci Int Genet. 2019; 43:102152. DOI: 10.1016/j.fsigen.2019.102152. View

Alghanim H, Balamurugan K, McCord B . Development of DNA methylation markers for sperm, saliva and blood identification using pyrosequencing and qPCR/HRM. Anal Biochem. 2020; 611:113933. DOI: 10.1016/j.ab.2020.113933. View

10.

Oldoni F, Castella V, Hall D . A novel set of DIP-STR markers for improved analysis of challenging DNA mixtures. Forensic Sci Int Genet. 2015; 19:156-164. DOI: 10.1016/j.fsigen.2015.07.012. View

11.

Wu S, Kim T, Wu X, Scherler K, Baxter D, Wang K . Circulating MicroRNAs and Life Expectancy Among Identical Twins. Ann Hum Genet. 2016; 80(5):247-56. PMC: 5757377. DOI: 10.1111/ahg.12160. View

12.

Zbiec-Piekarska R, Spolnicka M, Kupiec T, Parys-Proszek A, Makowska Z, Paleczka A . Development of a forensically useful age prediction method based on DNA methylation analysis. Forensic Sci Int Genet. 2015; 17:173-179. DOI: 10.1016/j.fsigen.2015.05.001. View

13.

Dobay A, Haas C, Fucile G, Downey N, Morrison H, Kratzer A . Microbiome-based body fluid identification of samples exposed to indoor conditions. Forensic Sci Int Genet. 2019; 40:105-113. DOI: 10.1016/j.fsigen.2019.02.010. View

14.

Zhang J, Wang M, Qi X, Shi L, Zhang J, Zhang X . Predicting the postmortem interval of burial cadavers based on microbial community succession. Forensic Sci Int Genet. 2021; 52:102488. DOI: 10.1016/j.fsigen.2021.102488. View

15.

Abecasis G, Auton A, Brooks L, DePristo M, Durbin R, Handsaker R . An integrated map of genetic variation from 1,092 human genomes. Nature. 2012; 491(7422):56-65. PMC: 3498066. DOI: 10.1038/nature11632. View

16.

Schmedes S, Woerner A, Novroski N, Wendt F, King J, Stephens K . Targeted sequencing of clade-specific markers from skin microbiomes for forensic human identification. Forensic Sci Int Genet. 2017; 32:50-61. DOI: 10.1016/j.fsigen.2017.10.004. View

17.

Weber J, Baxter D, Zhang S, Huang D, Huang K, Lee M . The microRNA spectrum in 12 body fluids. Clin Chem. 2010; 56(11):1733-41. PMC: 4846276. DOI: 10.1373/clinchem.2010.147405. View

18.

Lan Q, Shen C, Jin X, Guo Y, Xie T, Chen C . Distinguishing three distinct biogeographic regions with an in-house developed 39-AIM-InDel panel and further admixture proportion estimation for Uyghurs. Electrophoresis. 2019; 40(11):1525-1534. DOI: 10.1002/elps.201800448. View

19.

. The Integrative Human Microbiome Project. Nature. 2019; 569(7758):641-648. PMC: 6784865. DOI: 10.1038/s41586-019-1238-8. View

20.

Wang Z, Zhou D, Cao Y, Hu Z, Zhang S, Bian Y . Characterization of microRNA expression profiles in blood and saliva using the Ion Personal Genome Machine(®) System (Ion PGM™ System). Forensic Sci Int Genet. 2015; 20:140-146. DOI: 10.1016/j.fsigen.2015.10.008. View