Developmental validation of the ForenSeq MainstAY kit, MiSeq FGx sequencing system and ForenSeq Universal Analysis Software

Stephens, K; Barta, Richelle; Fleming, Keenan; Pérez, Juan Carlos Mendoza; Wu, Shan-Fu; Snedecor, June; Holt, Cydne; LaRue, Bobby; Budowle, Bruce

doi:10.1016/j.fsigen.2023.102851

Cited by 10 publications

(16 citation statements)

References 89 publications

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“…The growing use of next-generation sequencing technologies in the forensic fields, with the possibility of combining thousands of markers together, requires the development of new biostatistical frameworks scalable to a higher number of genetic markers [9]. Moreover, many commercially available NGS-based kits allow to combine STRs and other non-traditional markers, such as SNPs or INDELs [12][13][14][15][16][17]. In particular, SNPs have been increasingly appealing thanks to their technical features and informational power: their smaller amplicon size is crucial with samples of low quantity and poor quality (this is relevant since the majority of forensic analyses involves degraded DNA) [64] and they provide insight for predicting human appearance and the biogeographical origin of unknown sample donors or deceased/missing persons [65,66], thus ultimately resulting in new investigative leads.…”

Section: Discussionmentioning

confidence: 99%

“…Notably, the latest application of SNPs is investigative genetic genealogy where dense SNP data are jointly analysed to infer distant relationships (which in forensics indicate relatedness exceeding that of first cousins) [69]. For these reasons, an increasing number of commercial NGS-based kits have included X chromosomal SNPs and/or STRs to address complex kinship scenarios [14,18,[70][71][72][73][74][75][76]. Nevertheless, complex kinship cases relying on many and mixed types of X chromosomal genetic markers cannot be addressed using the previous implementations for the inference of recombination rates, which are used, albeit with limitations, for STR markers.…”

Section: Discussionmentioning

confidence: 99%

“…Over the last decade, use of sequencing-based techniques has become increasingly widespread in forensic genetics [8][9][10][11]. This brought back interest in other types of markers, especially SNPs, which can be analysed either in combination with STRs or alone [12][13][14][15][16][17]. Whilst more SNPs are necessary to reach the discrimination capacity of STRs, the possibility of genotyping large number of markers simultaneously from low quantities of input DNA or from degraded material has opened the floodgates to new forensic applications also based on SNPs, such as ancestry inference, DNA phenotyping and investigative genetic genealogy, the latter being specifically designed on dense SNP data [18][19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Recombulator-X: a fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics

Aneli

Fariselli

Chierto

et al. 2023

Preprint

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Background and Objective: Genetic markers (especially short tandem repeats or STRs) located on the X chromosome are a valuable resource to solve complex kinship cases in forensic genetics in addition or alternatively to autosomal STRs. Groups of tightly linked markers are combined into haplotypes, thus increasing the discriminating power of tests. However, this approach requires precise knowledge of the recombination rates between adjacent markers. Recombination rates vary across the human genome and cannot be automatically derived from linkage physical maps. The International Society of Forensic Genetics recommends that recombination rate estimation on the X chromosome is performed from pedigree genetic data while taking into account the confounding effect of mutations. However, the only existing implementations that satisfy these requirements have several drawbacks: they were never publicly released, they are very slow and/or need cluster-level hardware and strong computational expertise to use. In order to address these key concerns, we developed Recombulator-X, a new open-source Python tool. Methods: The most challenging issue, namely the running time, was addressed with dynamic programming techniques to greatly reduce the computational complexity of the algorithm, coupled with JIT compilation to further increase performance. We also extended the statistical framework from STR to any polymorphic marker. Results: Compared to the previous methods, Recombulator-X reduces the estimation times from weeks or months to less than one hour for typical datasets. Moreover, the estimation process, including preprocessing, has been streamlined and packaged into a simple command-line tool that can be run on a normal PC. Where previous approaches were limited to small panels of STR markers (up to 15), our tool can handle greater numbers (up to 100) of mixed STR and non-STR markers. Conclusions: In the genetic forensic community, state-of-the-art estimation methods for X chromosome recombination rates have seen limited usage due to the technical hurdles posed by previous implementations. Recombulator-X makes the process much simpler, faster and accessible to researchers without a computational background, hopefully spurring increased adoption of best practices. Moreover, it extends the estimation framework to larger panels of genetic markers (not only STRs), allowing analyses of sequencing-based data.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Recombulator-X: a fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics

Aneli

Fariselli

Chierto

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Both kits target 27 autosomal short tandem repeats (STRs) that include both CODIS and ESS core loci for international compatibility and 24 Y‐STRs that make‐up the minimum set required by the Y haplotype reference database, excluding DYS393 (YHRD, http://yhrd.org). Data generated with the ForenSeq™ DNA Signature Prep Kit also includes 7 X‐STRs, 94 identity single‐nucleotide polymorphisms (SNPs), and can include additional targets for investigative lead generation using phenotypic and biogeographical ancestry (BGA) SNPs [6–8].…”

Section: Introductionmentioning

confidence: 99%

An exploratory view into allelic drop‐out of sequenced autosomal STRs

Foley,

Koehler,

et al. 2024

Journal of Forensic Sciences

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As massively parallel sequencing is implemented in forensic genetics, an understanding of sequence data must accompany these advancements, that is, accurate modeling of data for proper statistical analysis. Allelic drop‐out, a common stochastic effect seen in genetic data, is often modeled in statistical analysis of STR results. This proof‐of‐concept study sequenced several serial dilutions of a standard sample ranging from 4 ng to 7.82 pg to evaluate allelic drop‐out trends on a select panel of autosomal STRs using the ForenSeq™ DNA Signature Prep Kit, Primer Set A on the Illumina MiSeq FGx. Parameters assessed included locus, profile, and run specific information. A majority of the allelic drop‐out occurred in DNA concentrations less than 31.25 pg. Statistical results indicated a need for locus‐specific modeling based on STR descriptors, like simple versus compound repeat patterns. No correlation was seen between average read count of scored alleles and allelic drop‐out at a locus. A statistical correlation was observed between the amount of allelic drop‐out and the starting amount of DNA in a sample, average read count of a sample, and total read count generated on a flow cell. This study supports using common allelic drop‐out factors used in fragment length analysis on sequenced STRs while including additional locus, sample, and run specific information. Results demonstrate multiple factors that can be considered when developing probability of allelic drop‐out models for sequenced autosomal STRs including locus‐specific analysis, total read count of a profile, and total read count sequenced on a flow cell.

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“…Over the last decade, use of sequencingbased techniques has become increasingly widespread in forensic genetics [8][9][10][11]. This brought back interest in other types of markers, especially SNPs, which can be analysed either in combination with STRs or alone [12][13][14][15][16][17]. Whilst more SNPs are necessary to reach the discrimination capacity of STRs, the possibility of genotyping large number of markers simultaneously from low quantities of input DNA or from degraded material has opened the floodgates to new forensic applications also based on SNPs, such as ancestry inference, DNA phenotyping and investigative genetic genealogy, the latter being specifically designed on dense SNP data [18][19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Recombulator-X: A fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics

Aneli,

Fariselli,

Chierto

et al. 2023

PLoS Comput Biol

View full text Add to dashboard Cite

Genetic markers (especially short tandem repeats or STRs) located on the X chromosome are a valuable resource to solve complex kinship cases in forensic genetics in addition or alternatively to autosomal STRs. Groups of tightly linked markers are combined into haplotypes, thus increasing the discriminating power of tests. However, this approach requires precise knowledge of the recombination rates between adjacent markers. The International Society of Forensic Genetics recommends that recombination rate estimation on the X chromosome is performed from pedigree genetic data while taking into account the confounding effect of mutations. However, implementations that satisfy these requirements have several drawbacks: they were never publicly released, they are very slow and/or need cluster-level hardware and strong computational expertise to use. In order to address these key concerns we developed Recombulator-X, a new open-source Python tool. The most challenging issue, namely the running time, was addressed with dynamic programming techniques to greatly reduce the computational complexity of the algorithm. Compared to the previous methods, Recombulator-X reduces the estimation times from weeks or months to less than one hour for typical datasets. Moreover, the estimation process, including preprocessing, has been streamlined and packaged into a simple command-line tool that can be run on a normal PC. Where previous approaches were limited to small panels of STR markers (up to 15), our tool can handle greater numbers (up to 100) of mixed STR and non-STR markers. In conclusion, Recombulator-X makes the estimation process much simpler, faster and accessible to researchers without a computational background, hopefully spurring increased adoption of best practices.

show abstract

Developmental validation of the ForenSeq MainstAY kit, MiSeq FGx sequencing system and ForenSeq Universal Analysis Software

Cited by 10 publications

References 89 publications

Recombulator-X: a fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics

Recombulator-X: a fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics

An exploratory view into allelic drop‐out of sequenced autosomal STRs

Recombulator-X: A fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics

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