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Cheng K, Bright JA, Kelly H, Liu YY, Lin MH, Kruijver M, Taylor D, Buckleton J. Developmental validation of STRmix™ NGS, a probabilistic genotyping tool for the interpretation of autosomal STRs from forensic profiles generated using NGS. Forensic Sci Int Genet 2023; 62:102804. [PMID: 36370677 DOI: 10.1016/j.fsigen.2022.102804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/04/2022] [Accepted: 11/07/2022] [Indexed: 11/09/2022]
Abstract
We describe the developmental validation of the probabilistic genotyping software - STRmix™ NGS - developed for the interpretation of forensic DNA profiles containing autosomal STRs generated using next generation sequencing (NGS) also known as massively parallel sequencing (MPS) technologies. Developmental validation was carried out in accordance with the Scientific Working Group on DNA Analysis Methods (SWGDAM) Guidelines for the Validation of Probabilistic Genotyping Systems and the International Society for Forensic Genetics (ISFG) recommendations and included sensitivity and specificity testing, accuracy, precision, and the interpretation of case-types samples. The results of developmental validation demonstrate the appropriateness of the software for the interpretation of profiles developed using NGS technology.
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Affiliation(s)
- Kevin Cheng
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland 1142, New Zealand.
| | - Jo-Anne Bright
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland 1142, New Zealand
| | - Hannah Kelly
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland 1142, New Zealand
| | - Yao-Yuan Liu
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland 1142, New Zealand
| | - Meng-Han Lin
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland 1142, New Zealand
| | - Maarten Kruijver
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland 1142, New Zealand
| | - Duncan Taylor
- Forensic Science SA, GPO Box 2790, Adelaide, SA 5001, Australia
| | - John Buckleton
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland 1142, New Zealand
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Development and validation of a novel 133-plex forensic STR panel (52 STRs and 81 Y-STRs) using single-end 400 bp massive parallel sequencing. Int J Legal Med 2021; 136:447-464. [PMID: 34741666 DOI: 10.1007/s00414-021-02738-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/25/2021] [Indexed: 12/15/2022]
Abstract
Short tandem repeats (STRs) are the preferred genetic markers in forensic DNA analysis, routinely measured by capillary electrophoresis (CE) method based on the fragment length features. While, the massive parallel sequencing (MPS) technology could simultaneously target a large number of intriguing forensic STRs, bypassing the intrinsic limitations of amplicon size separation and accessible fluorophores in CE, which is efficient and promising for enabling the identification of forensic biological evidence. Here, we developed a novel MPS-based Forensic Analysis System Multiplecues SetB Kit of 133-plex forensic STR markers (52 STRs and 81 Y-STRs) and one Y-InDel (M175) based on multiplex PCR and single-end 400 bp sequencing strategy. This panel was subjected to developmental validation studies according to the SWGDAM Validation Guidelines. Approximately 2185 MPS-based reactions using 6 human DNA standards and 8 male donors were conducted for substrate studies (filter paper, gauze, cotton swab, four different types of FTA cards, peripheral venous blood, saliva, and exfoliated cells), sensitivity studies (from 2 ng down to 0.0625 ng), mixture studies (two-person DNA mixtures), PCR inhibitor studies (seven commonly encountered PCR inhibitors), species specificity studies (11 non-human species), and repeatability studies. Results of concordance studies (413 Han males and 6 human DNA standards) generated by STRait Razor and in-house Python scripts indicated 99.98% concordance rate in STR calling relative to CE for STRs between 41,900 genotypes at 100 STR markers. Moreover, the limitations of present studies, the nomenclature rules and forensic MPS applications were also described. In conclusion, the validation studies based on ~ 2200 MPS-based and ~ 2500 CE-based DNA profiles demonstrated that the novel MPS-based panel meets forensic DNA quality assurance guidelines with robust, reliable, and reproducible performance on samples of various quantities and qualities, and the STR nomenclature rules should be further regulated to integrate the inconformity between MPS-based and CE-based methods.
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Interpretation of DNA data within the context of UK forensic science - evaluation. Emerg Top Life Sci 2021; 5:405-413. [PMID: 34027985 PMCID: PMC8760892 DOI: 10.1042/etls20200340] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 04/24/2021] [Accepted: 05/04/2021] [Indexed: 12/30/2022]
Abstract
Forensic DNA provides a striking contribution to the provision of justice worldwide. It has proven to be crucial in the investigative phase of an unsolved crime where a suspect needs to be identified, e.g. from a DNA database search both nationally and internationally. It is also a powerful tool in the assignment of evidential weight to the comparison of a profile of a person of interest and a crime scene profile. The focus of this document is the evaluation of autosomal profiles for criminal trials in the UK. A separate review covers investigation and evaluation of Y-STR profiles, investigation using autosomal profiles, kinship analysis, body identification and Forensic Genetic Genealogy investigations. In less than 40 years, forensic DNA profiling has developed from a specialist technique to everyday use. Borrowing on advances in genome typing technology, forensic DNA profiling has experienced a substantial increase in its sensitivity and informativeness. Alongside this development, novel interpretation methodologies have also been introduced. This document describes the state of the art and future advances in the interpretation of forensic DNA data.
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Cheng K, Lin MH, Moreno L, Skillman J, Hickey S, Cuenca D, Hudlow WR, Just R, Bright JA, Buckleton J, Curran JM. Modeling allelic analyte signals for aSTRs in NGS DNA profiles. J Forensic Sci 2021; 66:1234-1245. [PMID: 33599286 DOI: 10.1111/1556-4029.14685] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 01/18/2021] [Accepted: 01/19/2021] [Indexed: 11/27/2022]
Abstract
We describe an adaption of Bright et al.'s work modeling peak height variability in CE-DNA profiles to the modeling of allelic aSTR (autosomal short tandem repeats) read counts from NGS-DNA profiles, specifically for profiles generated from the ForenSeq™ DNA Signature Prep Kit, DNA Primer Mix B. Bright et al.'s model consists of three key components within the estimation of total allelic product-template, locus-specific amplification efficiencies, and degradation. In this work, we investigated the two mass parameters-template and locus-specific amplification efficiencies-and used MLE (maximum likelihood estimation) and MCMC (Markov chain Monte Carlo) methods to obtain point estimates to calculate the total allelic product. The expected read counts for alleles were then calculated after proportioning some of the expected stutter product from the total allelic product. Due to preferential amplicon selection introduced by the sample purification beads, degradation is difficult to model from the aSTR outputs alone. Improved modeling of the locus-specific amplification efficiencies may mask the effects of degradation. Whilst this model could be improved by introducing locus specific variances in addition to locus specific priors, our results demonstrate the suitability of adapting Bright et al.'s allele peak height model for NGS-DNA profiles. This model could be incorporated into continuous probabilistic interpretation approaches for mixed DNA profiles.
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Affiliation(s)
- Kevin Cheng
- Institute of Environmental Science and Research Limited, Auckland, New Zealand.,Department of Statistics, University of Auckland, Auckland, New Zealand
| | - Meng-Han Lin
- Institute of Environmental Science and Research Limited, Auckland, New Zealand
| | - Lilliana Moreno
- DNA Support Unit, Federal Bureau of Investigation Laboratory, Quantico, VA, USA
| | - Jessica Skillman
- Washington D.C. Department of Forensic Sciences, Washington, DC, USA
| | - Stephanie Hickey
- Washington D.C. Department of Forensic Sciences, Washington, DC, USA
| | - Daniela Cuenca
- California Department of Justice, Jan Bashinski DNA Laboratory, Richmond, CA, USA
| | - William R Hudlow
- California Department of Justice, Jan Bashinski DNA Laboratory, Richmond, CA, USA
| | - Rebecca Just
- DNA Support Unit, Federal Bureau of Investigation Laboratory, Quantico, VA, USA.,National Biodefense Analysis and Countermeasures Center, Fort Detrick, MD, USA
| | - Jo-Anne Bright
- Institute of Environmental Science and Research Limited, Auckland, New Zealand
| | - John Buckleton
- Institute of Environmental Science and Research Limited, Auckland, New Zealand.,Department of Statistics, University of Auckland, Auckland, New Zealand
| | - James M Curran
- Department of Statistics, University of Auckland, Auckland, New Zealand
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King JL, Woerner AE, Mandape SN, Kapema KB, Moura-Neto RS, Silva R, Budowle B. STRait Razor Online: An enhanced user interface to facilitate interpretation of MPS data. Forensic Sci Int Genet 2021; 52:102463. [PMID: 33493821 DOI: 10.1016/j.fsigen.2021.102463] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 11/06/2020] [Accepted: 12/29/2020] [Indexed: 12/17/2022]
Abstract
Since 2013, STRait Razor has enabled analysis of massively parallel sequencing (MPS) data from various marker systems such as short tandem repeats, single nucleotide polymorphisms, insertion/deletions, and mitochondrial DNA. In this paper, STRait Razor Online (SRO), available at https://www.unthsc.edu/straitrazor, is introduced as an interactive, Shiny-based user interface for primary analysis of MPS data and secondary analysis of STRait Razor haplotype pileups. This software can be accessed from any common browser via desktop, tablet, or smartphone device. SRO is available also as a standalone application and open-source R script available at https://github.com/ExpectationsManaged/STRaitRazorOnline. The local application is capable of batch processing of both fastq files and primary analysis output. Processed batches generate individual report folders and summary reports at the locus- and haplotype-level in a matter of minutes. For example, the processing of data from ∼700 samples generated with the ForenSeq Signature Preparation Kit from allsequences.txt to a final table can be performed in ∼40 min whereas the Excel-based workbooks can take 35-60 h to compile a subset of the tables generated by SRO. To facilitate analysis of single-source, reference samples, a preliminary triaging system was implemented that calls potential alleles and flags loci suspected of severe heterozygote imbalance. When compared to published, manually curated data sets, 98.72 % of software-assigned allele calls without manual interpretation were consistent with curated data sets, 0.99 % loci were presented to the user for interpretation due to heterozygote imbalance, and the remaining 0.29 % of loci were inconsistent due to the analytical thresholds used across the studies.
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Affiliation(s)
- Jonathan L King
- Center for Human Identification, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA.
| | - August E Woerner
- Center for Human Identification, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA; Department of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA
| | - Sammed N Mandape
- Center for Human Identification, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA
| | - Kapema Bupe Kapema
- Center for Human Identification, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA
| | | | - Rosane Silva
- Instituto de Biofisica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Bruce Budowle
- Center for Human Identification, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA; Department of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA
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