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Library preparation protocols for most sequencing technologies involve PCR amplification of the template DNA, which open the possibility that a given template DNA molecule is sequenced multiple times. Reads arising from this phenomenon, known as PCR duplicates, inflate the cost of sequencing and can jeopardize the reliability of affected experiments. Despite the pervasiveness of this artefact, our understanding of its causes and of its impact on downstream statistical analyses remains essentially empirical. Here, we develop a general quantitative model of amplification distortions in sequencing data sets, which we leverage to investigate the factors controlling the occurrence of PCR duplicates. We show that the PCR duplicate rate is determined primarily by the ratio between library complexity and sequencing depth, and that amplification noise (including in its dependence on the number of PCR cycles) only plays a secondary role for this artefact. We confirm our predictions using new and published RAD‐seq libraries and provide a method to estimate library complexity and amplification noise in any data set containing PCR duplicates. We discuss how amplification‐related artefacts impact downstream analyses, and in particular genotyping accuracy. The proposed framework unites the numerous observations made on PCR duplicates and will be useful to experimenters of all sequencing technologies where DNA availability is a concern. [ABSTRACT FROM AUTHOR]

Single-cell sequencing has gained popularity in recent years. Despite its numerous applications, single-cell DNA sequencing data is highly error-prone due to technical biases arising from uneven sequencing coverage, allelic dropout, and amplification error. With these artifacts, the identification of somatic genomic variants becomes a challenging task, and over the years, several methods have been developed explicitly for this type of data. Single-cell variant callers implement distinct strategies, make different use of the data, and typically result in many discordant calls when applied to real data. Here, we review current approaches for single-cell variant calling, emphasizing single nucleotide variants. We highlight their potential benefits and shortcomings to help users choose a suitable tool for their data at hand.

DNA profiles generated by different STR kits may show different alleles for identical amplified loci. This well‐known phenomenon affects the smooth transition of data generated by new STR kits to a database or casework laboratory or cross‐laboratory comparison of STR profiles. As in other DNA databases throughout the world, it has become clear that the number of the analyzed loci should be expanded for a variety of reasons, such as partial profiles resulting from low copy‐number DNA template or degraded samples, working with mixtures or when prevalence of familial inbreeding. In the course of introducing a new STR kit, VeriFiler™ Express (Applied Biosystems, Foster City, CA, USA), we compared genotyping data of 1568 samples amplified by the VeriFiler™ Express with the data generated on the same samples by the Powerplex™ ESI FAST (Promega, Madison WI, USA) kit. Discordance was noted in 20 samples (1.27%), 14 (0.89%) of them showing allele dropout mismatch and six (0.38%) showing an additional fixed‐size third allele. These rates are well above the reported rates of 0.4% for this kit. Since correct genotyping and accurate consistent allele assignment is of paramount importance, it seems timely to recommend for DNA laboratories and genetic‐match search systems to take these possible inconsistencies into account. [ABSTRACT FROM AUTHOR]

Genotyping complex multigene families in novel systems is particularly challenging. Target primers frequently amplify simultaneously multiple loci leading to high PCR and sequencing artefacts such as chimeras and allele amplification bias. Most genotyping pipelines have been validated in nonmodel systems whereby the real genotype is unknown and the generation of artefacts may be highly repeatable. Further hindering accurate genotyping, the relationship between artefacts and genotype complexity (i.e. number of alleles per genotype) within a PCR remains poorly described. Here, we investigated the latter by experimentally combining multiple known major histocompatibility complex (MHC) haplotypes of a model organism (chicken, Gallus gallus, 43 artificial genotypes with 2–13 alleles per amplicon). In addition to well‐defined 'optimal' primers, we simulated a nonmodel species situation by designing 'cross‐species' primers based on sequence data from closely related Galliform species. We applied a novel open‐source genotyping pipeline (ACACIA; https://gitlab.com/psc%5fsantos/ACACIA), and compared its performance with another, previously published pipeline (AmpliSAS). Allele calling accuracy was higher when using ACACIA (98.5% versus 97% and 77.8% versus 75% for the 'optimal' and 'cross‐species' data sets, respectively). Systematic allele dropout of three alleles owing to primer mismatch in the 'cross‐species' data set explained high allele calling repeatability (100% when using ACACIA) despite low accuracy, demonstrating that repeatability can be misleading when evaluating genotyping workflows. Genotype complexity was positively associated with nonchimeric artefacts, chimeric artefacts (nonlinearly by levelling when amplifying more than 4–6 alleles) and allele amplification bias. Our study exemplifies and demonstrates pitfalls researchers should avoid to reliably genotype complex multigene families. [ABSTRACT FROM AUTHOR]

Huntington disease (HD) is an autosomal dominant disease characterized by motor, behavioral, and cognitive symptoms, caused by the pathological expansion of more than 35 CAG/CAA repeats in the HTT gene. We describe the phenotype of a patient compatible with HD. Several family members were reported as affected, and a paternal cousin and his daughter carried 39 and 42 CAG/CAA. HD genetic testing in proband showed homozygosity for a 14 CAG/CAA allele. Considering the phenotype and family history, HTT gene sequence was performed, revealing heterozygosity for the c.51C>G variant that changes the last nucleotide before the CAG tract, causing misannealing of forward primer (HD344) and dropout of the expanded allele. Polymerase chain reaction (PCR) analysis performed with an alternative forward primer demonstrated a 41 CAG/CAA allele. The c.51C>G variant was not detected in the affected cousin, thus suggesting a de novo occurrence. The lack of biological samples from the proband father and grandmother prevented further investigations to establish in which family member the variant occurred. These data indicate that patients presenting HD phenotype, and homozygous for a normal HTT CAG/CAA allele should be thoroughly evaluated for the presence of a genetic variant, even de novo, within the repeat region that may hamper genetic diagnosis. [ABSTRACT FROM AUTHOR]

Abstract Background The current literature on single cell genomic analyses on the DNA level is conflicting regarding requirements for cell quality, amplification success rates, allelic dropouts and resolution, lacking a systematic comparison of multiple cell input down to the single cell. We hypothesized that such a correlation assay would provide an approach to address the latter issues, utilizing the leukemic cell line OCI-AML3 with a known set of genetic aberrations. Results By analyzing single and multiple cell replicates (2 to 50 cells) purified by micromanipulation and serial dilution we stringently assessed the signal-to-noise ratio (SNR) from single as well as a discrete number of cells based on a multiple displacement amplification method, with whole exome sequencing as signal readout. In this setting, known OCI-AML3 mutations as well as large copy number alterations could be identified, adding to the current knowledge of cytogenetic status. The presence of DNMT3A R882C, NPM1 W288 fs and NRAS Q61L was consistent, in spite of uneven allelic read depths. In contrast, at the level of single cells, we observed that one-third to half of all variants were not reproduced in the replicate sample, and this allelic mismatch displayed an exponential function of cell input. Large signature duplications were discernible from 5 cells, whereas deletions were visible down to the single cell. Thus, even under highly optimized conditions, single cell whole genome amplification and interpretation must be taken with considerable caution, given that allelic change is frequent and displays low SNR. Allelic noise is rapidly alleviated with increased cell input, and the SNR is doubled from 2 to 50 cells. Conclusions In conclusion, we demonstrate noisy allele distributions, when analyzing genetic aberrations within single cells relative to multiple cells. Based on the presented data we recommend that single cell analyses should include replicate cell dilution assays for a given setup for relative assessment of procedure-specific SNR to ensure that the resolution supports the specific hypotheses.

Our capacity to study individual cells has enabled a new level of resolution for understanding complex biological systems such as multicellular organisms or microbial communities. Not surprisingly, several methods have been developed in recent years with a formidable potential to investigate the somatic evolution of single cells in both healthy and pathological tissues. However, single-cell sequencing data can be quite noisy due to different technical biases, so inferences resulting from these new methods need to be carefully contrasted. Here, I introduce CellCoal, a software tool for the coalescent simulation of single-cell sequencing genotypes. CellCoal simulates the history of single-cell samples obtained from somatic cell populations with different demographic histories and produces single-nucleotide variants under a variety of mutation models, sequencing read counts, and genotype likelihoods, considering allelic imbalance, allelic dropout, amplification, and sequencing errors, typical of this type of data. CellCoal is a flexible tool that can be used to understand the implications of different somatic evolutionary processes at the single-cell level, and to benchmark dedicated bioinformatic tools for the analysis of single-cell sequencing data. CellCoal is available at https://github.com/dapogon/cellcoal. [ABSTRACT FROM AUTHOR]

Epithelial ovarian cancer (EOC) is a leading cause of cancer mortality among women but unfortunately is usually not diagnosed until advanced stage. Early detection of EOC is of paramount importance to improve outcomes. Liquid biopsy of circulating tumor cells (CTCs) is emerging as one of the promising biomarkers for early detection of solid tumors. However, discrepancies in terms of oncogenomics (i.e., different genetic defects detected) between the germline, primary tumor, and liquid biopsy are a serious concern and may adversely affect downstream cancer management. Here, we illustrate the potential and pitfalls of CTCs by presenting two patients of Stage I EOC. We successfully isolated and recovered CTCs by a silicon-based nanostructured microfluidics system, the automated Cell RevealTM. We examined the genomics of CTCs as well as the primary tumor and germline control (peripheral blood mononuclear cells) by whole exome sequencing. Different signatures were then investigated by comparisons of identified mutation loci distinguishing those that may only arise in the primary tumor or CTCs. A novel model is proposed to test if the highly variable allele frequencies, between primary tumor and CTCs results, are due to allele dropout in plural CTCs or tumor heterogeneity. This proof-of-principle study provides a strategy to elucidate the possible cause of genomic discrepancy between the germline, primary tumor, and CTCs, which is helpful for further large-scale use of such technology to be integrated into clinical management protocols.

The article offers information on the significant allelic dropout phenomenon of Oncomine BRCA Research Assay on Ion Torrent S5. Topics discussed include information on the use of the disease-associated genetic testing in clinical practice; discussions on the evaluation of the performance of the Oncomine BRCA Research Assay and false-negative sequence variations on BRCA1 gene due to allelic dropout phenomenon.

Background: The current literature on single cell genomic analyses on the DNA level is conflicting regarding requirements for cell quality, amplification success rates, allelic dropouts and resolution, lacking a systematic comparison of multiple cell input down to the single cell. We hypothesized that such a correlation assay would provide an approach to address the latter issues, utilizing the leukemic cell line OCI-AML3 with a known set of genetic aberrations. Results: By analyzing single and multiple cell replicates (2 to 50 cells) purified by micromanipulation and serial dilution we stringently assessed the signal-to-noise ratio (SNR) from single as well as a discrete number of cells based on a multiple displacement amplification method, with whole exome sequencing as signal readout. In this setting, known OCI-AML3 mutations as well as large copy number alterations could be identified, adding to the current knowledge of cytogenetic status. The presence of DNMT3A R882C, NPM1 W288 fs and NRAS Q61L was consistent, in spite of uneven allelic read depths. In contrast, at the level of single cells, we observed that one-third to half of all variants were not reproduced in the replicate sample, and this allelic mismatch displayed an exponential function of cell input. Large signature duplications were discernible from 5 cells, whereas deletions were visible down to the single cell. Thus, even under highly optimized conditions, single cell whole genome amplification and interpretation must be taken with considerable caution, given that allelic change is frequent and displays low SNR. Allelic noise is rapidly alleviated with increased cell input, and the SNR is doubled from 2 to 50 cells. Conclusions: In conclusion, we demonstrate noisy allele distributions, when analyzing genetic aberrations within single cells relative to multiple cells. Based on the presented data we recommend that single cell analyses should include replicate cell dilution assays for a given setup for relative assessment of procedure-specific SNR to ensure that the resolution supports the specific hypotheses. [ABSTRACT FROM AUTHOR]

Crime scene traces of various types are routinely sent to forensic laboratories for analysis, generally with the aim of addressing questions about the source of the trace. The laboratory may choose to analyse the samples in different ways depending on the type and quality of the sample, the importance of the case and the cost and performance of the available analysis methods. Theoretically well-founded guidelines for the choice of analysis method are, however, lacking in most situations. In this paper, it is shown how such guidelines can be created using Bayesian decision theory. The theory is applied to forensic DNA analysis, showing how the information from the initial qPCR analysis can be utilized. It is assumed the alternatives for analysis are using a standard short tandem repeat (STR) DNA analysis assay, using the standard assay and a complementary assay, or the analysis may be cancelled following quantification. The decision is based on information about the DNA amount and level of DNA degradation of the forensic sample, as well as case circumstances and the cost for analysis. Semi-continuous electropherogram models are used for simulation of DNA profiles and for computation of likelihood ratios. It is shown how tables and graphs, prepared beforehand, can be used to quickly find the optimal decision in forensic casework. [ABSTRACT FROM AUTHOR]

Abstract: The trade‐offs of using single‐digest vs. double‐digest restriction site‐associated DNA sequencing (RAD‐seq) protocols have been widely discussed. However, no direct empirical comparisons of the two methods have been conducted. Here, we sampled a single population of Gulf pipefish (Syngnathus scovelli) and genotyped 444 individuals using RAD‐seq. Sixty individuals were subjected to single‐digest RAD‐seq (sdRAD‐seq), and the remaining 384 individuals were genotyped using a double‐digest RAD‐seq (ddRAD‐seq) protocol. We analysed the resulting Illumina sequencing data and compared the two genotyping methods when reads were analysed either together or separately. Coverage statistics, observed heterozygosity, and allele frequencies differed significantly between the two protocols, as did the results of selection components analysis. We also performed an in silico digestion of the Gulf pipefish genome and modelled five major sources of bias: PCR duplicates, polymorphic restriction sites, shearing bias, asymmetric sampling (i.e., genotyping fewer individuals with sdRAD‐seq than with ddRAD‐seq) and higher major allele frequencies. This combination of approaches allowed us to determine that polymorphic restriction sites, an asymmetric sampling scheme, mean allele frequencies and to some extent PCR duplicates all contribute to different estimates of allele frequencies between samples genotyped using sdRAD‐seq versus ddRAD‐seq. Our finding that sdRAD‐seq and ddRAD‐seq can result in different allele frequencies has implications for comparisons across studies and techniques that endeavour to identify genomewide signatures of evolutionary processes in natural populations. [ABSTRACT FROM AUTHOR]

Background Hereditary breast and ovarian cancer is characterized by mutations in BRCA1 or BRCA2 genes and PCR-based screening techniques, such as capillary sequencing and next-generation sequencing ( NGS), are considered gold standard methods for detection of pathogenic mutations in these genes. Single-nucleotide polymorphisms ( SNPs) constitute a vast source of variation in the human genome and represent a risk for misdiagnosis in genetic testing, since the presence of a SNP in primer-annealing sites may cause false negative results due to allele dropout. However, few reports are available and the frequency of this phenomenon in diagnostic assays remains unknown. Methods and Results In this article, we investigated the causes of a false negative capillary sequencing result in BRCA1 involving a mother-daughter dyad. Using several molecular strategies, including different DNA polymerases, primer redesign, allele-specific PCR and NGS, we established that the initial misdiagnosis was caused by a SNP located in the primer-annealing region, leading to allele dropout of the mutated allele. Conclusion Assuming that this problem can also occur in any PCR-based method that are widely used in diagnostic settings, the clinical report presented here draws attention for one of the limitations of genetic testing in general, for which medical and laboratory communities need to be aware. [ABSTRACT FROM AUTHOR]

Double-digested RADseq (dd RADseq) is a NGS methodology that generates reads from thousands of loci targeted by restriction enzyme cut sites, across multiple individuals. To be statistically sound and economically optimal, a dd RADseq experiment has a preliminary design stage that needs to consider issues related to the selection of enzymes, particular features of the genome of the focal species, possible modifications to the library construction protocol, coverage needed to minimize missing data, and the potential sources of error that may impact upon the coverage. We present ddradseqtools, a software package to help dd RADseq experimental design by (i) the generation of in silico double-digested fragments; (ii) the construction of modified dd RADseq libraries using adapters with either one or two indexes and degenerate base regions ( DBRs) to quantify PCR duplicates; and (iii) the initial steps of the bioinformatics preprocessing of reads. ddradseqtools generates single-end ( SE) or paired-end ( PE) reads that may bear SNPs and/or indels. The effect of allele dropout and PCR duplicates on coverage is also simulated. The resulting output files can be submitted to pipelines of alignment and variant calling, to allow the fine-tuning of parameters. The software was validated with specific tests for the correct operability of the program. The correspondence between in silico settings and parameters from dd RADseq in vitro experiments was assessed to provide guidelines for the reliable performance of the software. ddradseqtools is cost-efficient in terms of execution time, and can be run on computers with standard CPU and RAM configuration. [ABSTRACT FROM AUTHOR]

Background Angelman syndrome (AS) is a neurological disorder caused by genetic defects of the chromosome region 15q11-q13; some 70–80% of cases are due to deletions of the maternal allele, as the paternal copy is imprinted. Design and methods A maternal deletion at D15S986 was reported in a suspected case of AS; this marker is located in intron 2 of the ATP10C gene, which has been implicated in the development of AS. A segment of ~ 830 bp, including this marker and the primers used in routine genetic test, was cloned and sequenced. Results A single nucleotide deletion (named ATP10C*c.760+3808delA, GenBank accession number HQ856823 ) was detected in the middle of the forward primer, leading to allele dropout. A large European population sample (N = 363) was typed, and the detected variant was characterized as a novel polymorphism, with allele frequencies of 0.882 (TAT allele) and 0.118 (T-T allele). Conclusions An alternative primer set was developed, for which the segregation pattern of D15S986 in the proband extended family was normal. It can replace the currently used set. [ABSTRACT FROM AUTHOR]

Forensic DNA analysis applying PCR enables profiling of minute biological samples. Enhanced analysis conditions can be applied to further push the limit of detection, coming with the risk of visualising artefacts and allele imbalances. We have evaluated the consecutive increase of PCR cycles from 30 to 35 to investigate the limitations of low-template (LT) DNA analysis, applying the short tandem repeat (STR) analysis kit PowerPlex ESX 16. Mock crime scene DNA extracts of four different quantities (from around 8–84 pg) were tested. All PCR products were analysed using 5, 10 and 20 capillary electrophoresis (CE) injection seconds. Bayesian models describing allele dropout patterns, allele peak heights and heterozygote balance were developed to assess the overall improvements in EPG quality with altered PCR/CE settings. The models were also used to evaluate the impact of amplicon length, STR marker and fluorescent label on the risk for allele dropout. The allele dropout probability decreased for each PCR cycle increment from 30 to 33 PCR cycles. Irrespective of DNA amount, the dropout probability was not affected by further increasing the number of PCR cycles. For the 42 and 84 pg samples, mainly complete DNA profiles were generated applying 32 PCR cycles. For the 8 and 17 pg samples, the allele dropouts decreased from 100% using 30 cycles to about 75% and 20%, respectively. The results for 33, 34 and 35 PCR cycles indicated that heterozygote balance and stutter ratio were mainly affected by DNA amount, and not directly by PCR cycle number and CE injection settings. We found 32 and 33 PCR cycles with 10 CE injection seconds to be optimal, as 34 and 35 PCR cycles did not improve allele detection and also included CE saturation problems. We find allele dropout probability differences between several STR markers. Markers labelled with the fluorescent dyes CXR-ET (red in electropherogram) and TMR-ET (shown as black) generally have higher dropout risks compared with those labelled with JOE (green) and fluorescein (blue). Overall, the marker D10S1248 has the lowest allele dropout probability and D8S1179 the highest. The marker effect is mainly pronounced for 30–32 PCR cycles. Such effects would not be expected if the amplification efficiencies were identical for all markers. Understanding allele dropout risks and the variability in peak heights and balances is important for correct interpretation of forensic DNA profiles. [ABSTRACT FROM AUTHOR]

Puritz et al. provide a review of several RADseq methodological approaches in response to our 'Population Genomic Data Analysis' workshop (Sept 2013) review (Andrews & Luikart 2014). We agree with Puritz et al. on the importance for researchers to thoroughly understand RADseq library preparation and data analysis when choosing an approach for answering their research questions. Some of us are currently using multiple RADseq protocols, and we agree that the different methods may offer advantages in different cases. Our workshop review did not intend to provide a thorough review of RADseq because the workshop covered a broad range of topics within the field of population genomics. Similarly, neither the response of Puritz et al. nor our comments here provide sufficient space to thoroughly review RADseq. Nonetheless, here we address some key points that we find unclear or potentially misleading in their evaluation of techniques. [ABSTRACT FROM AUTHOR]

Duchenne muscular dystrophy (DMD) is an X-linked recessive neuromuscular disease caused by mutation in the DMD gene. A 38-year-old woman was referred to our hospital with her son who was diagnosed with DMD. Multiplex PCR failed to detect DMD mutations in the affected child. The female carrier underwent preimplantation genetic diagnosis by linkage analysis and gender determination. Eight embryos were biopsied after in vitro fertilization. Two healthy embryos determined both as females (E1 and E3) were transferred. Although the paternal allele was absent in E3, it was considered to be a result of allele dropout for the STR-49 marker. Surprisingly, a female and a male baby were delivered at 38 gestational weeks, suggesting that E3 was a male embryo with the allele dropout occurring at the SRY gene. Exon 2 duplication was detected in the DMD patient and the carrier mother using next-generation sequencing and multiple ligation-dependent probe amplification. Next, we verified the duplication of exon 2 by real-time PCR, using a special primer at 3′ of intron 1, very close to exon 2. Finally, we confirmed that both newborns inherited the normal allele, using quantitative real-time PCR and linkage analysis. © 2014 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Abstract: Background: PCR-based technology is indispensable for genetic diagnosis. On the other hand, allele dropout is one significant cause of genotyping errors. Most allele dropout mechanisms are related to annealing failure caused by single nucleotide variant (SNV) situated inside the primer sequences. Here, we demonstrate a novel allele dropout mechanism caused by a non-primer-binding-site SNV. Methods: We demonstrate that the apparent homozygosity of NM_000137.1(FAH):c.1035_1037del was caused by allele dropout. Results: The non-primer-binding-site SNV causes a strong secondary hairpin structure formation of the PCR products and leads to amplification failure. SNV check of the primer sequences per se during primer design is not adequate to avoid allele dropout. Conclusions: The next-generation primer design software should analyze the secondary structure of primers and template sequence taking SNV in both sequences into account in order to avoid genotyping errors. [Copyright &y& Elsevier]

Inexpensive short-read sequencing technologies applied to reduced representation genomes is revolutionizing genetic research, especially population genetics analysis, by allowing the genotyping of massive numbers of single-nucleotide polymorphisms ( SNP) for large numbers of individuals and populations. Restriction site-associated DNA ( RAD) sequencing is a recent technique based on the characterization of genomic regions flanking restriction sites. One of its potential drawbacks is the presence of polymorphism within the restriction site, which makes it impossible to observe the associated SNP allele (i.e. allele dropout, ADO). To investigate the effect of ADO on genetic variation estimated from RAD markers, we first mathematically derived measures of the effect of ADO on allele frequencies as a function of different parameters within a single population. We then used RAD data sets simulated using a coalescence model to investigate the magnitude of biases induced by ADO on the estimation of expected heterozygosity and FST under a simple demographic model of divergence between two populations. We found that ADO tends to overestimate genetic variation both within and between populations. Assuming a mutation rate per nucleotide between 10−9 and 10−8, this bias remained low for most studied combinations of divergence time and effective population size, except for large effective population sizes. Averaging FST values over multiple SNPs, for example, by sliding window analysis, did not correct ADO biases. We briefly discuss possible solutions to filter the most problematic cases of ADO using read coverage to detect markers with a large excess of null alleles. [ABSTRACT FROM AUTHOR]

The molecular genetic analysis of microdissected cells by laser, a method for selecting a starting material of pure DNA or RNA uncontaminated. Our study focuses on technical pre-PCR (polymerase chain reaction) for the amplification of DNA from a single cell (leukocyte) isolated from human blood after laser microdissection and aims to optimize the yield of DNA extracted of this cell to be amplified without errors and provide reliable genetic analyzes. This study has allowed us to reduce the duration of cell lysis in order to perform the step of expanding genomic PEP (primer extension preamplification) directly after lysis the same day and the quality of genomic amplification and eliminate purification step of the product PEP, step with a risk of contamination and risk of loss of genetic material related to manipulation. This approach has shown that the combination of at least 3 STR (short tandem repeat) markers for genetic analysis of single cell improves the efficiency and accuracy of PCR and minimizes the loss of allele (allele drop out; ADO). This protocol can be applied to large scale and an effective means suitable for genetic testing for molecular diagnostic from isolated single cell (cancerous - fetal). [ABSTRACT FROM AUTHOR]

Abstract: DNA sequence variation is known to exist in and around the repeat region of short tandem repeat (STR) loci used in human identity testing. While the vast majority of STR alleles measured in forensic DNA laboratories worldwide type as “normal” alleles compared with STR kit allelic ladders, a number of variant alleles have been reported. In addition, a sequence difference at a polymerase chain reaction (PCR) primer binding site in the DNA template can cause allele drop-out (i.e., a “null” or “silent” allele) with one set of primers and not with another. Our group at the National Institute of Standards and Technology (NIST) has been sequencing variant and null alleles supplied by forensic labs and cataloging this information on the NIST STRBase website for the past decade. The PCR primer sequences and strategy used for our STR allele sequencing work involving 23 autosomal STRs and 17 Y-chromosome STRs are described along with the results from 111 variant and 17 null alleles. [Copyright &y& Elsevier]

Abstract: To evaluate the accuracy of SBT protocols for HLA-C and to better understand the HLA-C polymorphism in Chinese, 1795 unrelated CMDP donors were typed at exons 2, 3, and 4 of the HLA-C gene using the Atria commercial kit. Of the study subjects, 1768 showed conclusive typing results, whereas the other 27 showed inconclusive results. Subsequent full-length cloning and haplotype sequencing showed that 11 of the 27 inconclusive results could be explained by the presence of nine novel alleles identified: Cw*0130, 0624, 070206, 075602, 0766, 0767, 0820, 0821, and 0827. These novel alleles were generated by a total of 10 coding-region substitutions, eight of them being located in the antigen-binding groove. Cw*0766 and Cw*075602 were detected three and two times, respectively, in the 1795 donors. The other 16 inconclusive samples were retested by SBT using our in-house PCR primers; all of them were found to carry Cw*0706, which dropped out in exons 2 and 3 in the initial PCR using the commercial primers amplifying from 5′ UTR to intron 3. Our results showed the importance of the full-length genomic sequence and intronic SNPs for the development of more accurate SBT. The allele distribution and novel alleles detected in this study also provide further insights into the HLA-C polymorphism in the Chinese Han population. [Copyright &y& Elsevier]

Objective: To evaluate trends and outcomes from preimplantation genetic diagnosis (PGD) cycles. Design: Retrospective data review. Setting: A reference laboratory specializing in the provision of PGD services. Patient(s): One hundred sixty-two patients at risk of transmitting a serious monogenic disorder to their children. Intervention(s): In vitro fertilization and PGD. Main Outcome Measure(s): Results of PGD cycles. Result(s): Two hundred twenty-four PGD cycles were referred by 59 different IVF centers. Forty-six different disorders were diagnosed, including several not previously diagnosed at the preimplantation stage. Cystic fibrosis was the most common reason for referral (73 cases). A diagnosis was obtained for 84.4% of tested embryos, with results available 6 to 36 hours from sample receipt. Only 10.7% of cycles had no transfer. The pregnancy rate per cycle with ET was 43.4%. Conclusion(s): Unlike previous reports of multiple PGD cycles, all of the cases in this study involved shipping of biopsied cells to a specialist reference laboratory for diagnosis. This approach, sometimes referred to as “transport PGD,” accounts for the vast majority of PGD cycles in the United States. Preimplantation genetic diagnosis was shown to be an effective alternative to prenatal diagnosis for patients with an ethical or a religious objection to pregnancy termination and for infertile patients carrying a genetic disorder. Demand for this service at our center doubled in each of the last 4 years. Pregnancy rates per ET were encouraging, almost half of all patients undergoing their first PGD cycle achieving a birth or ongoing pregnancy. [Copyright &y& Elsevier]

Mutation of primer site for genotyping by polymerase chain reaction (PCR) may cause allele dropout and other genotyping failures. Primary hyperoxaluria type 2 (PH2) is a rare inherited disease caused by overproduction of endogenous oxalate due to mutations in the glyoxylate/hydroxypyruvate reductase (GRHPR) gene. Here, to avoid allele dropout and primer annealing to multiple sites, and given the discrepancy in intron length between GRHPR gene data, we updated the primers used in the sequence assay of the GRHPR gene. These redesigned primers show potential in reducing detection failure of GRHPR mutations. In addition, we performed a single nucleotide polymorphism (SNP) linkage analysis of the GRHPR gene using direct sequencing with PCR amplification of specific alleles (DS-PASA). Using this technique, we sequenced four common SNPs between intron E and exon 6, which show linkage disequilibrium (LD) consisting of three types of haplotypes, similar to data from the HapMap SNP database. [ABSTRACT FROM AUTHOR]

Abstract: We experienced a difficult case of TH01 typing. Instability of TH01 allele 9.3 was observed using GenePrint STR System TH01. Allele dropout was observed when an AmpFℓSTR Profiler Kit was subsequently used for confirmation of the TH01 type. Use of the PowerPlex 16 System made it possible to detect allele 9.3. As a result of sequencing, a single point mutation (G-to-A transition) located 37 bases upstream of the first TCAT motif of the repeat region was identified as the cause of the allele dropout during use of the AmpFℓSTR Profiler Kit. This mutation was located at the 3′ end of the forward primers of the AmpFℓSTR Profiler Kit and GenePrint STR System TH01. [Copyright &y& Elsevier]

DNA extracted from hair or faeces shows increasing promise for censusing populations whose individuals are difficult to locate. To date, the main problem with this approach has been that genotyping errors are common. If these errors are not identified, counting genotypes is likely to overestimate the number of individuals in a population. Here, we describe an algorithm that uses maximum likelihood estimates of genotyping error rates to calculate the evidence that samples came from the same individual. We test this algorithm with a hypothetical model of genotyping error and show that this algorithm works well with substantial rates of genotyping error and reasonable amounts of data. Additional work is necessary to develop statistical models of error in empirical data. [ABSTRACT FROM AUTHOR]

Epithelial ovarian cancer (EOC) is a leading cause of cancer mortality among women but unfortunately is usually not diagnosed until advanced stage. Early detection of EOC is of paramount importance to improve outcomes. Liquid biopsy of circulating tumor cells (CTCs) is emerging as one of the promising biomarkers for early detection of solid tumors. However, discrepancies in terms of oncogenomics (i.e., different genetic defects detected) between the germline, primary tumor, and liquid biopsy are a serious concern and may adversely affect downstream cancer management. Here, we illustrate the potential and pitfalls of CTCs by presenting two patients of Stage I EOC. We successfully isolated and recovered CTCs by a silicon-based nanostructured microfluidics system, the automated Cell RevealTM. We examined the genomics of CTCs as well as the primary tumor and germline control (peripheral blood mononuclear cells) by whole exome sequencing. Different signatures were then investigated by comparisons of identified mutation loci distinguishing those that may only arise in the primary tumor or CTCs. A novel model is proposed to test if the highly variable allele frequencies, between primary tumor and CTCs results, are due to allele dropout in plural CTCs or tumor heterogeneity. This proof-of-principle study provides a strategy to elucidate the possible cause of genomic discrepancy between the germline, primary tumor, and CTCs, which is helpful for further large-scale use of such technology to be integrated into clinical management protocols. [ABSTRACT FROM AUTHOR]

Abstract: In humans, Surfactant Protein A exists as two highly homologous genetic isoforms, SFTPA1 and SFTPA2. Mutations in these two genes are associated with idiopathic pulmonary fibrosis (IPF) and lung cancer. We have developed a Sanger DNA sequencing assay which utilizes long-range PCR to detect mutations in these two genes. [Copyright &y& Elsevier]

Abstract: Allele typing performed using the original components of the AmpFlSTR Identifiler kit led to unbalanced peak heights and allele dropouts. However, allele typing was completely successful when substituting the QIAGEN Multiplex PCR Master Mix for the AmpFlSTR PCR Reaction Mix of the Identifiler kit. The successful range for allele typing was 250pg to 1.5ng of DNA. The running times for PCR amplification were reduced by about 30min from the original protocol. [Copyright &y& Elsevier]

Abstract: The use of expert systems to interpret short tandem repeat (STR) DNA profiles in forensic, medical and ancient DNA applications is becoming increasingly prevalent as high-throughput analytical systems generate large amounts of data that are time-consuming to process. With special reference to low copy number (LCN) applications we use a graphical model to simulate stochastic variation associated with the entire DNA process starting with extraction of sample, followed by the processing associated with preparation of a PCR reaction mix, and PCR itself. Each part of the process is modelled with input efficiency parameters. Then, the key output parameters that define the characteristics of a DNA profile are derived—namely heterozygous balance (Hb) and the probability of allelic dropout p(D). [Copyright &y& Elsevier]

Our capacity to study individual cells has enabled a new level of resolution for understanding complex biological systems such as multicellular organisms or microbial communities. Not surprisingly, several methods have been developed in recent years with a formidable potential to investigate the somatic evolution of single cells in both healthy and pathological tissues. However, single-cell sequencing data can be quite noisy due to different technical biases, so inferences resulting from these new methods need to be carefully contrasted. Here, I introduce CellCoal, a software tool for the coalescent simulation of single-cell sequencing genotypes. CellCoal simulates the history of single-cell samples obtained from somatic cell populations with different demographic histories and produces single-nucleotide variants under a variety of mutation models, sequencing read counts, and genotype likelihoods, considering allelic imbalance, allelic dropout, amplification, and sequencing errors, typical of this type of data. CellCoal is a flexible tool that can be used to understand the implications of different somatic evolutionary processes at the single-cell level, and to benchmark dedicated bioinformatic tools for the analysis of single-cell sequencing data. CellCoal is available at https://github.com/dapogon/cellcoal., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)