Carolyn R. Steffen

Developmental validation of the PowerPlex® Fusion 6C System

The PowerPlex(®) Fusion 6C System is a 27-locus, six-dye, multiplex that includes all markers in the expanded CODIS core loci and increases overlap with STR database standards throughout the world. Additionally, it contains two, rapidly mutating, Y-STRs and is capable of both casework and database workflows, including direct amplification. A multi-laboratory developmental validation study was performed on the PowerPlex(®) Fusion 6C System. Here, we report the results of that study which followed SWGDAM guidelines and includes data for: species specificity, sensitivity, stability, precision, reproducibility and repeatability, case-type samples, concordance, stutter, DNA mixtures, and PCR-based procedures. Where appropriate we report data from both extracted DNA samples and direct amplification samples from various substrates and collection devices. Samples from all studies were separated on both Applied Biosystems 3500 series and 6-dye capable 3130 series Genetic Analyzers and data is reported for each. Together, the data validate the design and demonstrate the performance of the PowerPlex(®) Fusion 6C System.

D5S2500 is an ambiguously characterized STR: Identification and description of forensic microsatellites in the genomics age

In the process of establishing short tandem repeat (STR) sequence variant nomenclature guidelines in anticipation of expanded forensic multiplexes for massively parallel sequencing (MPS), it was discovered that the STR D5S2500 has multiple positions and genomic characteristics reported. This ambiguity is because the marker named D5S2500 consists of two different microsatellites forming separate components in the capillary electrophoresis multiplexes of Qiagens HDplex (Hilden, Germany) and AGCU ScienTechs non-CODIS STR 21plex (Wuxi, Jiangsu, China). This study outlines the genomic details used to identify each microsatellite and reveals the D5S2500 marker in HDplex has the correctly assigned STR name, while the D5S2500 marker in the AGCU 21plex, closely positioned a further 1643 nucleotides in the human reference sequence, is an unnamed microsatellite. The fact that the D5S2500 marker has existed as two distinct STR loci undetected for almost ten years, even with reported discordant genotypes for the standard control DNA, underlines the need for careful scrutiny of the genomic properties of forensic STRs, as they become adapted for sequence analysis with MPS systems. We make the recommendation that precise chromosome location data must be reported for any forensic marker under development but not in common use, so that the genomic characteristics of the locus are validated to the same level of accuracy as its allelic variation and forensic performance. To clearly differentiate each microsatellite, we propose the name D5S2800 be used to identify the Chromosome-5 STR in the AGCU 21plex.

Developmental validation of QIAGEN Investigator® 24plex QS Kit and Investigator® 24plex GO! Kit: Two 6-dye multiplex assays for the extended CODIS core loci

The original CODIS database based on 13 core STR loci has been overwhelmingly successful for matching suspects with evidence. In order to increase the power of discrimination, reduce the possibility of adventitious matches, and expand global data sharing, the CODIS Core Loci Working Group determined the expansion of the CODIS core loci to 20 STR plus three additional highly recommended loci (SE33, DY391, Amelogenin) Hares, 2015, 2012 [1,2]. The QIAGEN Investigator 24plex QS and Investigator 24plex GO! Kits are 6-dye multiplex assays that contain all markers of the expanded 23 CODIS core loci along with a unique internal performance control that is co-amplified with the STR markers. The Quality Sensor generates additional information for quality control and performance checks. Investigator 24plex QS is designed for purified DNA from casework and reference samples, whereas 24plex GO! is dedicated to direct amplification of reference samples, like blood or buccal cells on FTA or swabs. A developmental validation study was performed on both assays. Here, we report the results of this study which followed the recommendations of the European Network of Forensic Science Institutes (ENFSI) [3] and the Revised Validation Guidelines of the Scientific Working Group on DNA Analysis Methods (SWGDAM) [4]. Data included are for PCR-based procedures e.g. reaction conditions, effects of PCR annealing temperature variations, amplification cycles or cyclers, sensitivity (also in the context of the Quality Sensor), performance with simulated inhibition, stability and efficiency, precision, reproducibility, mixture study, concordance, stutter, species specificity, and case-type samples. The validation results demonstrate that the Investigator 24plex QS and Investigator 24plex GO! Kits are robust and reliable identification assays as required for forensic DNA typing in forensic casework analysis and databasing.

Low-template DNA: A single DNA analysis or two replicates?

This study investigates the following two questions: (1) Should the DNA analyst concentrate the DNA extract into a single amplification or should he/she split it up to do two replicates? (2) Given the electropherogram obtained from a first analysis, is it worthwhile for the DNA analyst to invest in obtaining a second replicate? A decision-theoretic approach addresses these questions by quantitatively expressing the expected net gain (ENG) of each DNA analysis of interest. The results indicate that two replicates generally have a greater ENG than a single DNA analysis for DNA quantities capable of producing two replicates having an average allelic peak height as low as 43rfu. This supports the position that two replicates increase the information content with regard to a single analysis.

Accurate Digital Polymerase Chain Reaction Quantification of Challenging Samples Applying Inhibitor-Tolerant DNA Polymerases

Digital PCR (dPCR) enables absolute quantification of nucleic acids by partitioning of the sample into hundreds or thousands of minute reactions. By assuming a Poisson distribution for the number of DNA fragments present in each chamber, the DNA concentration is determined without the need for a standard curve. However, when analyzing nucleic acids from complex matrixes such as soil and blood, the dPCR quantification can be biased due to the presence of inhibitory compounds. In this study, we evaluated the impact of varying the DNA polymerase in chamber-based dPCR for both pure and impure samples using the common PCR inhibitor humic acid (HA) as a model. We compared the TaqMan Universal PCR Master Mix with two alternative DNA polymerases: ExTaq HS and Immolase. By using Bayesian modeling, we show that there is no difference among the tested DNA polymerases in terms of accuracy of absolute quantification for pure template samples, i.e., without HA present. For samples containing HA, there were great differences in performance: the TaqMan Universal PCR Master Mix failed to correctly quantify DNA with more than 13 pg/nL HA, whereas Immolase (1 U) could handle up to 375 pg/nL HA. Furthermore, we found that BSA had a moderate positive effect for the TaqMan Universal PCR Master Mix, enabling accurate quantification for 25 pg/nL HA. Increasing the amount of DNA polymerase from 1 to 5 U had a strong effect for ExTaq HS, elevating HA-tolerance four times. We also show that the average Cq values of positive reactions may be used as a measure of inhibition effects, e.g., to determine whether or not a dPCR quantification result is reliable. The statistical models developed to objectively analyze the data may also be applied in quality control. We conclude that the choice of DNA polymerase in dPCR is crucial for the accuracy of quantification when analyzing challenging samples.

Corrigendum to ‘U.S. Population Data for 29 Autosomal STR Loci’ [Forensic Sci. Int. Genet. 7 (2013) e82–e83]

In 2013, we reported the genotypes and allele frequencies for 1036 unrelated samples in the U.S. population using capillary electrophoresis (CE) [1]. Since then, multiplex STR assays designed for sequencing technologies have become available, and we have re-analyzed our set of 1036 samples to determine sequence-based allele frequencies (manuscript in preparation). As a quality control for this sequence data and to evaluate back-compatibility, the calculated length-based genotypes from the sequence data were compared to the 2013 published CE genotypes. This comparison resulted in a list of differences which were further evaluated via sequenceand CE-data review. Instances in which the difference was not attributable to the sequencing assay were further evaluated with additional CE-based genotyping. This evaluation has resulted in revisions to the 2013 publication [1], detailed below. We have categorized the reasons for revisions as: (1) polymerase chain reaction (PCR) primer design differences, (2) change in the reporting of tri-alleles, (3) laboratory error, and (4) data analysis error. In summary, revisions have been made for a total of 13 STR loci, four of which are U.S. core loci (D5S818, D7S820, D13S317, and TPOX). The remaining nine loci are D6S1043, F13A01, F13B, FESFPS, LPL, Penta C, Penta D, Penta E, and SE33. The revisions affect 12 separate samples in the 1036 data set (12/1036 = 1.16%) and are summarized in Table 1. The distribution of revisions among the four populations is as follows: four African American samples (4/342 = 1.12%), three Caucasian samples (3/361 = 0.83%), four Hispanic samples (4/236 = 1.69%), and one Asian sample (1/97 = 1.03%). The revisions affect 37 genotypes out of 30,044 total genotypes (37/30,044 = 0.123%), not including the change in reporting of tri-alleles. The tri-allelic genotypes detected at TPOX (9, 10, 11) and Penta D (11, 14, 15) were reported as bi-allelic in 2013 (TPOX reported as 9, 11 and Penta D reported as 11, 14). In the revised data set, these genotypes have been removed. This change not only impacts the frequencies of the removed alleles, but also results in a sample number change at these loci: TPOX revised global n = 1035 and revised African American n = 341; Penta D revised global n = 1035 and revised Hispanic n = 235. Any change in sample number results in a change in all allele frequencies at the affected locus/population. A detailed presentation illustrating each of the revisions can be found at http://strbase.nist.gov/NISTpop.htm. Tables 2a–2d provides a summary of the revisions by population, locus, and specific allele(s) affected: original, revised, and the difference of revised − original. The maximum change in allele frequency by population was as follows 0.15% (African American), 0.28% (Caucasian), 0.71% (Hispanic), 1.0% (Asian). The greatest overall single change of 1.0% was observed for the 11 allele at D7S820 in the Asian population (n = 97). Similar to the 2015 Federal Bureau of Investigation (FBI) allele frequency revisions [2,3], empirical comparisons of random match probabilities (RMP) calculated from the original allele frequencies and the revised allele frequencies were performed on 100 randomly generated profiles for the two populations where U.S. core loci have been affected (African American and Asian). Comparisons were based on the original 13 U.S. core loci, as the expanded loci were not affected by the allele frequency changes. The random profiles were generated using DNA Profile Builder software (http://www.nucfs.ac.uk/dna-profilebuilder/) using the allele frequencies from the NIST original. RMP calculations for the 100 random profiles were generated with the LSAM (Laboratory Statistical Analysis Module) software (Future Technologies Inc., Fairfax, VA) using a theta correction of 0.01 for homozygous loci. Since the corrections only affected markers in the original 13 U.S. core loci, we only calculated statistics on these markers. The differences in the African American population RMP calculations were within 1.0004fold and the differences in the Asian population RMP calculations were within 1.3262-fold. This falls within a 2-fold change in RMP (comparable to the FBI’s analysis [3]) and well within the 10-fold difference expected by using a different set of allele frequencies for that population as suggested by previous studies and the National Research Council [4–7], as shown in Fig. 1 and Table 3. RMP scenarios were calculated for each population assuming homozygosity at the affected loci and using a theta correction of 0.01. The analysis was performed to understand the scope of the “worst case” effect of the revisions. The bounds of less rare and more rare RMPs as a function of commonly used STR kits are tabulated in Supplemental Table 1. Using the Asian population as an example, RMPs of 1.22 fold less rare and 1.61 fold more rare were calculated for the loci contained

Development of NIST standard reference material 2373: Genomic DNA standards for HER2 measurements

NIST standard reference material (SRM) 2373 was developed to improve the measurements of the HER2 gene amplification in DNA samples. SRM 2373 consists of genomic DNA extracted from five breast cancer cell lines with different amounts of amplification of the HER2 gene. The five components are derived from the human cell lines SK-BR-3, MDA-MB-231, MDA-MB-361, MDA-MB-453, and BT-474. The certified values are the ratios of the HER2 gene copy numbers to the copy numbers of selected reference genes DCK, EIF5B, RPS27A, and PMM1. The ratios were measured using quantitative polymerase chain reaction and digital PCR, methods that gave similar ratios. The five components of SRM 2373 have certified HER2 amplification ratios that range from 1.3 to 17.7. The stability and homogeneity of the reference materials were shown by repeated measurements over a period of several years. SRM 2373 is a well characterized genomic DNA reference material that can be used to improve the confidence of the measurements of HER2 gene copy number.

Expected net gain data of low-template DNA analyses

Low-template DNA analyses are affected by stochastic effects which can produce a configuration of peaks in the electropherogram (EPG) that is different from the genotype of the DNA׳s donor. A probabilistic and decision-theoretic model can quantify the expected net gain (ENG) of performing a DNA analysis by the difference between the expected value of information (EVOI) and the cost of performing the analysis. This article presents data on the ENG of performing DNA analyses of low-template DNA for a single amplification, two replicate amplifications, and for a second replicate amplification given the result of a first analysis. The data were obtained using amplification kits AmpFlSTR Identifiler Plus and Promega׳s PowerPlex 16 HS, an ABI 3130xl genetic sequencer, and Applied Biosystem׳s GeneMapper ID-X software. These data are supplementary to an original research article investigating whether a forensic DNA analyst should perform a single DNA analysis or two replicate analyses from a decision-theoretic point of view, entitled “Low-template DNA: a single DNA analysis or two replicates?” (Gittelson et al., 2016) [1].

Sequence-based US population data for the SE33 locus

A set of 1036 U.S. Population Samples were sequenced using the Illumina ForenSeq DNA Signature Prep Kit. This sample set has been highly characterized using a variety of marker systems for human identification. The FASTQ files obtained from a ForenSeq DNA Signature Prep Kit experiment include several STR loci that are not reported in the associated software. These include SE33, DXS8377, DXS10148, DYS456, and DYS461. The sequence variation within the autosomal STR marker SE33 was evaluated using a customized bioinformatic approach to identify and characterize the locus in the 1036 data set. The analysis identified 53 unique alleles by length and 264 by sequence. An additional 10 alleles were detected when selected extended flanking regions were examined to resolve discordances. Allele frequencies and SE33 sequence motif patterns are reported for the 1036 data set. The comparison of numerical allele calls derived from sequence data to the allele calls obtained from commercial capillary electrophoresis‐based STR typing kits resulted in 100% concordance, after manual data review and confirmation sequencing of three flanking region deletions. The analysis of this data set involved significant manual sequence curation and information support from length‐based genotypes to ensure high confidence in the sequence‐based allele calls. The challenges of interpreting the sequence data for SE33 consisted of high sequence noise, allele‐size dependent variance in coverage, and heterozygote imbalance. As allele length increased, sequence depth of coverage and quality decreased at the terminal end. Accordingly, heterozygous genotype imbalance increased in proportion to increased distance between alleles.

Sequence-based U.S. population data for 27 autosomal STR loci

This manuscript reports Short Tandem Repeat (STR) sequence-based allele frequencies for 1036 samples across 27 autosomal STR loci: D1S1656, TPOX, D2S441, D2S1338, D3S1358, D4S2408, FGA, D5S818, CSF1PO, D6S1043, D7S820, D8S1179, D9S1122, D10S1248, TH01, vWA, D12S391, D13S317, Penta E, D16S539, D17S1301, D18S51, D19S433, D20S482, D21S11, Penta D, and D22S1045. Sequence data were analyzed by two bioinformatic pipelines and all samples have been evaluated for concordance with alleles derived from CE-based analysis at all loci. Each reported sequence includes high-quality flanking sequence and is properly formatted according to the most recent guidance of the International Society for Forensic Genetics. In addition, GenBank accession numbers are reported for each sequence, and associated records are available in the STRSeq BioProject (https://www.ncbi.nlm.nih.gov/bioproject/380127). The D3S1358 locus demonstrates the greatest average increase in heterozygosity across populations (approximately 10 percentage points). Loci demonstrating average increase in heterozygosity from 10 to 5 percentage points include (in descending order) D9S1122, D13S317, D8S1179, D21S11, D5S818, D12S391, and D2S441. The remaining 19 loci each demonstrate less than 5 percentage point increase in average heterozygosity. Discussion includes the utility of this data in understanding traditional CE results, such as informing stutter models and understanding migration challenges, and considerations for population sampling strategies in light of the marked increase in rare alleles for several of the sequence-based STR loci. This NIST 1036 data set is expected to support the implementation of STR sequencing forensic casework by providing high-confidence sequence-based allele frequencies for the same sample set which are already the basis for population statistics in many U.S. forensic laboratories.