Applications of massively parallel sequencing in forensic genetics

Carratto, Thássia Mayra Telles; Moraes, Vitor Matheus Soares; Recalde, Tamara Soledad Frontanilla; Oliveira, Maria Luiza Guimarães de; Teixeira Mendes-Junior, Celso

doi:10.1590/1678-4685-GMB-2022-0077

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Young Brazilian Geneticists - Special Issue • Genet. Mol. Biol. 45 (3 Suppl 1) • 2022 • https://doi.org/10.1590/1678-4685-GMB-2022-0077 copy

Applications of massively parallel sequencing in forensic genetics

Authorship SCIMAGO INSTITUTIONS RANKINGS

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.

Keywords:
Next-Generation Sequencing (NGS); DNA analysis; RNA analysis; methylation; genetic polymorphisms

Panel	Manufacturer	Number and types of markers	Chromosomes	Recommended input DNA	Purposes
ForenSeq DNA Signature Prep Kit	Verogen	Mix A: Amelogenin + 58 STRs + 94 SNPs Mix B: mix A + 78 SNPs	Autosomes Y-chromosome X-chromosome	1 ng, with sensitivity as low as 62.5 pg	Human identification Mixture deconvolution Eye and hair color prediction Biogeographical ancestry inference
Precision ID Identity	Applied Biosystems	124 SNPs	Autosomes Y-chromosome	100 pg	Human identification
Precision ID Global Filer NGS STR v2		35 STRs	Autosomes Y-chromosome X-chromosome	125 pg	Human identification Mixture deconvolution
Precision ID Ancestry		165 SNPs	Autosomes	125 pg	Biogeographical ancestry inference
Precision ID mtDNA Control Region		1.2 kb control region	mtDNA	2 pg	Maternal lineage identification Maternal biogeographical ancestry inference
Ion AmpliSeq DNA Phenotyping		23 SNPs + 1 InDel	Autosomes	1 ng	Eye and hair color prediction
Ion AmpliSeq HID Y-SNP Research v1		859 SNPs	Y-chromosome	1 ng, with right haplogroup determination down to 25 pg	Paternal lineage identification Paternal biogeographical ancestry inference
Ion AmpliSeq VISAGE-Basic Tool Research		152 SNPs + 1 InDel	Autosomes	1 ng, with full profile recovery down to 100 pg	Eye, hair and skin color prediction Biogeographical ancestry inference
Ion AmpliSeq PhenoTrivium		319 SNPs + 1 InDel	Autosomes Y-chromosome	1 ng, with reliable predictions for phenotypes down to 25 pg	Eye, hair and skin color prediction Biogeographical ancestry inference Paternal lineage identification Paternal biogeographical ancestry
Ion AmpliSeq MH 74 Plex Research		74 microhaplotypes	Autosomes	1 ng, with sensitivity as low as 50 pg	Mixture deconvolution Biogeographical ancestry inference

	Tissue/body fluid identified	NGS Platform	Number of markers	Number of samples	Study
mRNA	blood, semen, vaginal secretion, menstrual blood, and saliva	MiSeq System (Illumina®)	33	232	Hanson et al. 2018Hanson E, Ingold S, Haas C and Ballantyne J (2018) Messenger RNA biomarker signatures for forensic body fluid identification revealed by targeted RNA sequencing. Forensic Sci Int Genet 34:206-221.
	blood, semen, vaginal secretion, menstrual blood, and saliva	MiSeq System (Illumina®)	33	197	Dørum et al. 2018Dørum G, Ingold S, Hanson E, Ballantyne J, Snipen L and Haas C (2018) Predicting the origin of stains from next generation sequencing mRNA data. Forensic Sci Int Genet 34:37-48.
	nasal mucosa	MiSeq FGx System (Illumina®)	2	12	Chirnside et al. 2020Chirnside O, Lemalu A and Fleming R (2020) Identification of nasal mucosa markers for forensic mRNA body fluid determination. Forensic Sci Int Genet 48:102317.
	blood, semen, vaginal secretion, menstrual blood, saliva, and skin	MiSeq System (Illumina®)	35	63	Ingold et al. 2020Ingold S, Dørum G, Hanson E, Ballantyne J and Haas C (2020) Assigning forensic body fluids to donors in mixed body fluids by targeted RNA/DNA deep sequencing of coding region SNPs. Int J Legal Med 134:473-485.
microRNA	blood, semen, vaginal fluid, menstrual blood, saliva, urine, feces, and sweat	HiSeq System (Illumina®)	6	20	Seashols-Williams et al., 2016Seashols-Williams S, Lewis C, Calloway C, Peace N, Harrison A, Hayes-Nash C, Fleming S, Wu Q and Zehner ZE (2016) High-throughput miRNA sequencing and identification of biomarkers for forensically relevant biological fluids. Electrophoresis 37:2780-2788.
	blood and saliva	Ion PGM™ System (Thermo Fisher Scientific)	25	10	Wang et al. 2016Wang Z, Zhou D, Cao Y, Hu Z, Zhang S, Bian Y, Hou Y and Li C (2016) Characterization of microRNA expression profiles in blood and saliva using the Ion Personal Genome Machine ® System (Ion PGMTM System). Forensic Sci Int Genet 20:140-146.
	blood, semen, vaginal secretion, menstrual blood, saliva, and skin	HiSeq and NextSeq (Illumina®)	9	119	Dørum et al., 2019Dørum G, Ingold S, Hanson E, Ballantyne J, Russo G, Aluri S, Snipen L and Haas C (2019) Predicting the origin of stains from whole miRNome massively parallel sequencing data. Forensic Sci Int Genet 40:131-139.
DNA methylation	blood, semen, saliva, and epithelial tissue	PyroMark Q24 (Qiagen)	4	42	Madi et al., 2012Madi T, Balamurugan K, Bombardi R, Duncan G and McCord B (2012) The determination of tissue-specific DNA methylation patterns in forensic biofluids using bisulfite modification and pyrosequencing. Electrophoresis 33:1736-1745.
	blood, semen, vaginal secretion, and saliva	PSQ HS 96A System (Biotage)	8	80	Park et al., 2014Park J-L, Kwon O-H, Kim JH, Yoo H-S, Lee H-C, Woo K-M, Kim S-Y, Lee S-H and Kim YS (2014) Identification of body fluid-specific DNA methylation markers for use in forensic science. Forensic Sci Int Genet 13:147-153.
	blood, seminal fluid, vaginal secretions, and buccal swabs	PyroMark Q24 (Qiagen)	4	89	Alghanim et al., 2020Alghanim H, Balamurugan K and McCord B (2020) Development of DNA methylation markers for sperm, saliva and blood identification using pyrosequencing and qPCR/HRM. Anal Biochem 611:113933.
	saliva	MiSeq FGx System (Illumina®)	18	65	Watanabe et al., 2022Watanabe K, Taniguchi K, Toyomane K and Akutsu T (2022) A new approach for forensic analysis of saliva-containing body fluid mixtures based on SNPs and methylation patterns of nearby CpGs. Forensic Sci Int Genet 56:102624.
Microbiome profiling	vaginal secretion, saliva and skin	Ion PGM™ System	16S rRNA gene	110	Díez López et al. 2019Díez López C, Vidaki A, Ralf A, Montiel González D, Radjabzadeh D, Kraaij R, Uitterlinden AG, Haas C, Lao O and Kayser M (2019) Novel taxonomy-independent deep learning microbiome approach allows for accurate classification of different forensically relevant human epithelial materials. Forensic Sci Int Genet 41:72-82.
Microbiome profiling	blood, semen, vaginal fluid, menstrual blood, saliva, and skin	MiSeq System (Illumina®)	16S rRNA gene	70	Dobay et al., 2019Dobay A, Haas C, Fucile G, Downey N, Morrison HG, Kratzer A and Arora N (2019) Microbiome-based body fluid identification of samples exposed to indoor conditions. Forensic Sci Int Genet 40:105-113.

Relationship	Average % DNA Shared	Range
Identical Twin	100%	-
Parent/Child	50%*	-
Full Sibling	50%	38%-61%
Grandparent/Grandchild, Aunt or Uncle/Niece or Nephew, Half Sibling	25%	17%-34%
1st Cousin, Great-grandparent/Great-grandchild, Great-Uncle or Aunt/ Great Nephew or Niece	12.5%	4%-23%
1st Cousin Once Removed Half 1st Cousin	6.25%	2%-11.5%
2nd Cousin	3.13%	2%-6%
3rd Cousin	0.78%	0%-2.2%

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E-mail: editor@gmb.org.br

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to Celso Teixeira Mendes-Junior. Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Av. Bandeirantes, 3900, 14040-901, Ribeirão Preto, SP, Brazil. E-mail address: ctmendes@ffclrp.usp.br.