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An elimination database is an essential component of a laboratory’s quality assurance program. Laboratory elimination databases are standard in forensic DNA laboratories and are considered best practice for the detection and control of human DNA contamination. However, developing elimination database procedures that are fit for use with next generation sequencing (NGS) assays requires consideration of several new factors, including 1) STR genotyping results that not only include the repeat allele, but also the allele sequence, and 2) assays that simultaneously type multiple marker systems. Manual entry of NGS-based elimination profiles into a database file is impractical: the process would be time consuming and highly prone to transcription errors. Moreover, it is not feasible to manually compare NGS sequences from an unknown sample to any number of profiles in an elimination database on a routine basis.
To address these issues, we have designed a workflow for semi-automated generation of an NGS-based laboratory elimination database, and comparisons of identity-informative markers from an unknown sample to the database using probabilistic genotyping software. For application to typing results produced using the ForenSeq DNA Signature Prep Kit (Verogen, Inc.), a custom script was developed to extract marker data from ForenSeq Universal Analysis Software reports and populate a locked elimination database master file that is automatically versioned each time new profiles are added. From the master file, the script generates separate, versioned output files containing the autosomal STR and identity-informative SNP profiles. The output files are compatible with STRmix (NicheVision) and EuroForMix, respectively, and are used to compare an unknown sample profile to the elimination database using the database search function in each software.
The complete workflow addresses the new factors associated with using NGS for forensic DNA testing, and at the same time achieves multiple quality assurance aims: easy and reliable development of a secure elimination database without manual transcription, versioned files for traceback, and error-free comparisons between unknown samples and database profiles using NGS data. The approach and procedures should be of interest to laboratories that are considering implementing NGS for forensic DNA testing.
Disclaimers: This work was funded under Contract No. HSHQDC-15-C-00064, awarded by the DHS S&T to NBACC, a DHS federal laboratory operated by BNBI. Views and conclusions contained herein are those of the authors and should not be interpreted to represent policies, expressed or implied, of the DHS or S&T. This manuscript has been authored by BNBI under Contract No. HSHQDC-15-C-00064 with the DHS. The US Government retains and the publisher, by accepting the article for publication, acknowledges that the USG retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for USG purposes. Views and conclusions contained herein are those of the authors and should not be interpreted to represent policies, expressed or implied, of the DHS.
An elimination database is an essential component of a laboratory’s quality assurance program. Laboratory elimination databases are standard in forensic DNA laboratories and are considered best practice for the detection and control of human DNA contamination. However, developing elimination database procedures that are fit for use with next generation sequencing (NGS) assays requires consideration of several new factors, including 1) STR genotyping results that not only include the repeat allele, but also the allele sequence, and 2) assays that simultaneously type multiple marker systems. Manual entry of NGS-based elimination profiles into a database file is impractical: the process would be time consuming and highly prone to transcription errors. Moreover, it is not feasible to manually compare NGS sequences from an unknown sample to any number of profiles in an elimination database on a routine basis.
To address these issues, we have designed a workflow for semi-automated generation of an NGS-based laboratory elimination database, and comparisons of identity-informative markers from an unknown sample to the database using probabilistic genotyping software. For application to typing results produced using the ForenSeq DNA Signature Prep Kit (Verogen, Inc.), a custom script was developed to extract marker data from ForenSeq Universal Analysis Software reports and populate a locked elimination database master file that is automatically versioned each time new profiles are added. From the master file, the script generates separate, versioned output files containing the autosomal STR and identity-informative SNP profiles. The output files are compatible with STRmix (NicheVision) and EuroForMix, respectively, and are used to compare an unknown sample profile to the elimination database using the database search function in each software.
The complete workflow addresses the new factors associated with using NGS for forensic DNA testing, and at the same time achieves multiple quality assurance aims: easy and reliable development of a secure elimination database without manual transcription, versioned files for traceback, and error-free comparisons between unknown samples and database profiles using NGS data. The approach and procedures should be of interest to laboratories that are considering implementing NGS for forensic DNA testing.
Disclaimers: This work was funded under Contract No. HSHQDC-15-C-00064, awarded by the DHS S&T to NBACC, a DHS federal laboratory operated by BNBI. Views and conclusions contained herein are those of the authors and should not be interpreted to represent policies, expressed or implied, of the DHS or S&T. This manuscript has been authored by BNBI under Contract No. HSHQDC-15-C-00064 with the DHS. The US Government retains and the publisher, by accepting the article for publication, acknowledges that the USG retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for USG purposes. Views and conclusions contained herein are those of the authors and should not be interpreted to represent policies, expressed or implied, of the DHS.
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