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Background : Forensic investigative genetic genealogy (FIGG) has developed rapidly in recent years and is considered a novel tool for crime investigation. However, crime scene samples are often of low quality and quantity and are challenging to analyze. Deciding which approach should be used for kinship inference in forensic practice remains a troubling problem for investigators. Methods : In this study, we selected four popular approaches-KING, IBS, TRUFFLE, and GERMLINE-comprising one method of moment (MoM) estimator and three identical by descent (IBD) segment-based tools and compared their performance at varying numbers of SNPs and levels of genotyping errors using both simulated and real family data. We also explored the possibility of making robust kinship inferences for samples with ultra-high genotyping errors by integrating MoM and the IBD segment-based methods. Results : The results showed that decreasing the number of SNPs had little effect on kinship inference when no fewer than 164 K SNPs were used for all four approaches. However, as the number decreased further, decreased efficiency was observed for the three IBD segment-based methods. Genotyping errors also had a significant effect on kinship inference, especially when they exceeded 1%. In contrast, MoM was much more robust to genotyping errors. Furthermore, the combination of the MoM and the IBD segment-based methods showed a higher overall accuracy, indicating its potential to improve the tolerance to genotyping errors. Conclusions : In conclusion, this study shows that different approaches have unique characteristics and should be selected for different scenarios. More importantly, the integration of the MoM and the IBD segment-based methods can improve the robustness of kinship inference and has great potential for applications in forensic practice.

The MiniMUGA genotyping array is a popular tool for genetic quality control of laboratory mice and genotyping samples from most experimental crosses involving laboratory strains, particularly for reduced complexity crosses. The content of the production version of the MiniMUGA array is fixed; however, there is the opportunity to improve the array's performance and the associated report's usefulness by leveraging thousands of samples genotyped since the initial description of MiniMUGA. Here, we report our efforts to update and improve marker annotation, increase the number and the reliability of the consensus genotypes for classical inbred strains and substrains, and increase the number of constructs reliably detected with MiniMUGA. In addition, we have implemented key changes in the informatics pipeline to identify and quantify the contribution of specific genetic backgrounds to the makeup of a given sample, remove arbitrary thresholds, include the Y Chromosome and mitochondrial genome in the ideogram, and improve robust detection of the presence of commercially available substrains based on diagnostic alleles. Finally, we have updated the layout of the report to simplify the interpretation and completeness of the analysis and added a section summarizing the ideogram in table format. These changes will be of general interest to the mouse research community and will be instrumental in our goal of improving the rigor and reproducibility of mouse-based biomedical research., Competing Interests: Conflicts of interest The authors have no conflict of interest to declare. None of the authors have a financial relationship with Neogen Inc. apart from the service contracts listed above., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.)

Considering polygenic risk scores (PRSs) in individual risk prediction is increasingly implemented in genetic testing for hereditary breast cancer (BC) based on next-generation sequencing (NGS). To calculate individual BC risks, the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) with the inclusion of the BCAC 313 or the BRIDGES 306 BC PRS is commonly used. The PRS calculation depends on accurately reproducing the variant allele frequencies (AFs) and, consequently, the distribution of PRS values anticipated by the algorithm. Here, the 324 loci of the BCAC 313 and the BRIDGES 306 BC PRS were examined in population-specific database gnomAD and in real-world data sets of five centers of the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC), to determine whether these expected AFs can be reproduced by NGS-based genotyping. Four PRS loci were non-existent in gnomAD v3.1.2 non-Finnish Europeans, further 24 loci showed noticeably deviating AFs. In real-world data, between 11 and 23 loci were reported with noticeably deviating AFs, and were shown to have effects on final risk prediction. Deviations depended on the sequencing approach, variant caller and calling mode (forced versus unforced) employed. Therefore, this study demonstrates the necessity to apply quality assurance not only in terms of sequencing coverage but also observed AFs in a sufficiently large cohort, when implementing PRSs in a routine diagnostic setting. Furthermore, future PRS design should be guided by the technical reproducibility of expected AFs across commonly used genotyping methods, especially NGS, in addition to the observed effect sizes., (© 2024. The Author(s).)

Importance: Four molluscum contagiosum virus (MOCV) genotypes (MOCV1-4) and four subtype variants were partially characterized using restriction enzyme profiling in the 1980s/1990s, but complete genome sequences of only MOCV1 and MOCV2 are available. The evolutionary pathways whereby genotypes/subtype variants with unavailable sequences emerged and whether all MOCVs can be detected using current diagnostic approaches remain unclear. We fully characterized 47 novel complete MOCV genomes, including the first complete MOCV3 genome, expanding the number of fully characterized genomes to 66. For reliably classifying the novel non-MOCV1/2 genomes, we developed and validated a framework for matching sequence-derived restriction maps with those defining MOCV subtypes in pioneering studies. Six phylogenetic subgroups (PG1-6) were identified, PG5 representing a novel MOCV2 subtype. The phylogenetic subgroups diverged from the prototype lineages following large-scale recombination events and hinted at partial sequence content of MOCV4 and direction of recombinant transfer in the events spawning PG5 and yet undetected MOCV1vb variant., Competing Interests: The authors declare no conflict of interest.

Array technology to genotype single-nucleotide variants (SNVs) is widely used in genome-wide association studies (GWAS), clinical diagnostics, and linkage studies. Arrays have undergone a tremendous growth in both number and content over recent years making a comprehensive comparison all the more important. We have compared 28 genotyping arrays on their overall content, genome-wide coverage, imputation quality, presence of known GWAS loci, mtDNA variants and clinically relevant genes (i.e., American College of Medical Genetics (ACMG) actionable genes, pharmacogenetic genes, human leukocyte antigen (HLA) genes and SNV density). Our comparison shows that genome-wide coverage is highly correlated with the number of SNVs on the array but does not correlate with imputation quality, which is the main determinant of GWAS usability. Average imputation quality for all tested arrays was similar for European and African populations, indicating that this is not a good criterion for choosing a genotyping array. Rather, the additional content on the array, such as pharmacogenetics or HLA variants, should be the deciding factor. As the research question of a study will in large part determine which class of genes are of interest, there is not just one perfect array for all different research questions. This study can thus help as a guideline to determine which array best suits a study's requirements., (© 2021. The Author(s).)

Objectives: Genotyping of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been instrumental in monitoring viral evolution and transmission during the pandemic. The quality of the sequence data obtained from these genotyping efforts depends on several factors, including the quantity/integrity of the input material, the technology, and laboratory-specific implementation. The current lack of guidelines for SARS-CoV-2 genotyping leads to inclusion of error-containing genome sequences in genomic epidemiology studies. We aimed to establish clear and broadly applicable recommendations for reliable virus genotyping., Methods: We established and used a sequencing data analysis workflow that reliably identifies and removes technical artefacts; such artefacts can result in miscalls when using alternative pipelines to process clinical samples and synthetic viral genomes with an amplicon-based genotyping approach. We evaluated the impact of experimental factors, including viral load and sequencing depth, on correct sequence determination., Results: We found that at least 1000 viral genomes are necessary to confidently detect variants in the SARS-CoV-2 genome at frequencies of ≥10%. The broad applicability of our recommendations was validated in over 200 clinical samples from six independent laboratories. The genotypes we determined for clinical isolates with sufficient quality cluster by sampling location and period. Our analysis also supports the rise in frequencies of 20A.EU1 and 20A.EU2, two recently reported European strains whose dissemination was facilitated by travel during the summer of 2020., Conclusions: We present much-needed recommendations for the reliable determination of SARS-CoV-2 genome sequences and demonstrate their broad applicability in a large cohort of clinical samples., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Inadequate sensitivity has been the primary limitation for implementing high-throughput sequencing for studies of tick-borne agents. Here we describe the development of TBDCapSeq, a sequencing assay that uses hybridization capture probes that cover the complete genomes of the eleven most common tick-borne agents found in the United States. The probes are used for solution-based capture and enrichment of pathogen nucleic acid followed by high-throughput sequencing. We evaluated the performance of TBDCapSeq to surveil samples that included human whole blood, mouse tissues, and field-collected ticks. For Borrelia burgdorferi and Babesia microti, the sensitivity of TBDCapSeq was comparable and occasionally exceeded the performance of agent-specific quantitative PCR and resulted in 25 to > 10,000-fold increase in pathogen reads when compared to standard unbiased sequencing. TBDCapSeq also enabled genome analyses directly within vertebrate and tick hosts. The implementation of TBDCapSeq could have major impact in studies of tick-borne pathogens by improving detection and facilitating genomic research that was previously unachievable with standard sequencing approaches.

Cryptosporidiosis is ranked sixth in the list of the most important food-borne parasites globally, and it is an important contributor to mortality in infants and the immunosuppressed. Recently, the number of genome sequences available for this parasite has increased drastically. The majority of the sequences are derived from population studies of Cryptosporidium parvum and Cryptosporidium hominis , the most important species causing disease in humans. Work with this parasite is challenging since it lacks an optimal, prolonged, in vitro culture system, which accurately reproduces the in vivo life cycle. This obstacle makes the cloning of isolates nearly impossible. Thus, patient isolates that are sequenced represent a population or, at times, mixed infections. Oocysts, the lifecycle stage currently used for sequencing, must be considered a population even if the sequence is derived from single-cell sequencing of a single oocyst because each oocyst contains four haploid meiotic progeny (sporozoites). Additionally, the community does not yet have a set of universal markers for strain typing that are distributed across all chromosomes. These variables pose challenges for population studies and require careful analyses to avoid biased interpretation. This review presents an overview of existing population studies, challenges, and potential solutions to facilitate future population analyses.

The article highlighted the problem of meat cattle genetic defects. The aim was the development of DNA tests for some genetic defects diagnostics, the determination of the animal carriers and their frequencies tracking in time. The 1490 DNA samples from the Aberdeen Angus ( n = 701), Hereford ( n = 385), Simmental ( n = 286) and Belgian Blue ( n = 118) cattle have been genotyped on the genetic defects by newly created and earlier developed DNA tests based on AS-PCR and PCR-RFLP methods. The Aberdeen Angus cattle genotyping has revealed 2.38 ± 0.31% AMC-cows and 1.67 ± 0.19 % AMC-bulls, 0.65 ± 0.07% DDC-cows and 0.90 ± 0.10% DDC-bulls. The single animals among the Hereford cattle were carriers of MSUD and CWH (on 0.27 ± 0.05%), ICM and HY (on 0.16 ± 0.03%). The Simmental cattle were free from OS. All Belgian Blue livestock were M1- and 0.84%-CMD1-carriers. The different ages Aberdeen Angus cattle genotyping has shown the tendency of the AMC- and DDC frequencies to increase in the later generations. The statistically significant increase of DDC of 1.17% in the cows' population born in 2019 compared to those born in 2015 allows concluding the further development of the DNA analysis-based measures preventing the manifestation of the genetic anomalies in meat cattle herds is necessary.

Microsatellite DNA analysis is a powerful tool for assessing population genetics. The main aim of this study was to assess the genetic potential of the peregrine falcon population covered by the restitution program. We characterized individuals from breeders that set their birds for release into the wild and birds that have been reintroduced in previous years. This was done using a well-known microsatellite panel designed for the peregrine falcon containing 10 markers. We calculated the genetic distance between individuals and populations using the UPGMA (unweighted pair group method with arithmetic mean) method and then performed a Principal Coordinates Analysis (PCoA) and constructed phylogenetic trees, to visualize the results. In addition, we used the Bayesian clustering method, assuming 1-15 hypothetical populations, to find the model that best fit the data. Units were segregated into groups regardless of the country of origin, and the number of alleles and observed heterozygosity were different in different breeding groups. The wild and captive populations were grouped independent of the original population.

Artemia is an industrially important genus used in aquaculture as a nutritious diet for fish and as an aquatic model organism for toxicity tests. However, despite the significance of Artemia, genomic research remains incomplete and knowledge on its genomic characteristics is insufficient. In particular, Artemia franciscana of North America has been widely used in fisheries of other continents, resulting in invasion of native species. Therefore, studies on population genetics and molecular marker development as well as morphological analyses are required to investigate its population structure and to discriminate closely related species. Here, we used the Illumina Hi-Seq platform to estimate the genomic characteristics of A. franciscana through genome survey sequencing (GSS). Further, simple sequence repeat (SSR) loci were identified for microsatellite marker development. The predicted genome size was ∼867 Mb using K-mer (a sequence of k characters in a string) analysis (K = 17), and heterozygosity and duplication rates were 0.655 and 0.809%, respectively. A total of 421467 SSRs were identified from the genome survey assembly, most of which were dinucleotide motifs with a frequency of 77.22%. The present study will be a useful basis in genomic and genetic research for A. franciscana., (© 2021 The Author(s).)

We developed microsatellite markers for Appasus japonicus (Heteroptera: Belostomatidae). This belostomatid bug is distributed in East Asia (Japanese Archipelago, Korean Peninsula and mainland China) and often listed as an endangered species in the Red List or the Red Data Book at the national and local level in Japan. Here, we describe twenty novel polymorphic microsatellite loci developed for A. japonicus, and marker suitability was evaluated using 56 individuals from four A. japonicus populations (Nagano, Hiroshima and Yamaguchi prefectures, Japan, and Chungcheongnam-do, Korea). The number of alleles per locus ranged from 1 to 12 (mean = 2.5), and the average observed and expected heterozygosity and fixation index per locus were 0.270, 0.323 and 0.153, respectively. In addition, a population structure analysis was conducted using the software STRUCTURE, and its result suggested that the 20 markers described here will be useful for investigating the genetic structure of A. japonicus populations, which should contribute to population genetics studies of this species.

Errors in genotype calling can have perverse effects on genetic analyses, confounding association studies, and obscuring rare variants. Analyses now routinely incorporate error rates to control for spurious findings. However, reliable estimates of the error rate can be difficult to obtain because of their variance between studies. Most studies also report only a single estimate of the error rate even though genotypes can be miscalled in more than one way. Here, we report a method for estimating the rates at which different types of genotyping errors occur at biallelic loci using pedigree information. Our method identifies potential genotyping errors by exploiting instances where the haplotypic phase has not been faithfully transmitted. The expected frequency of inconsistent phase depends on the combination of genotypes in a pedigree and the probability of miscalling each genotype. We develop a model that uses the differences in these frequencies to estimate rates for different types of genotype error. Simulations show that our method accurately estimates these error rates in a variety of scenarios. We apply this method to a dataset from the whole-genome sequencing of owl monkeys (Aotus nancymaae) in three-generation pedigrees. We find significant differences between estimates for different types of genotyping error, with the most common being homozygous reference sites miscalled as heterozygous and vice versa. The approach we describe is applicable to any set of genotypes where haplotypic phase can reliably be called and should prove useful in helping to control for false discoveries., (© The Author(s) 2020. Published by Oxford University Press on behalf of Genetics Society of America. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objectives: Accurate assays for hepatitis C virus (HCV) quantitation and genotyping are important for the management of HCV infection. In this study, we evaluated the performance of cobas HCV and cobas HCV GT assays (Roche) for HCV quantitation and genotyping on the cobas 4800 System., Methods: We compared the performance of the cobas HCV assays with another commercial system (Abbott m 2000) using a panel of well-characterized patient samples and proficiency testing samples., Results: The limit-of-detection of the cobas HCV assay in our center was higher (15 IU/mL) than the manufacturer claim (9.2 IU/mL). The assay showed high analytical specificity, accuracy, precision, and linearity. Performance was congruent with the RealTi m e HCV assay (Abbott). For genotyping, the cobas HCV GT assay only showed moderate agreement with the RealTi m e HCV Genotype II assay (kappa = 0.550). The cobas assay outperformed the RealTi m e assay for typing HCV genotypes 1b and 6 (p = 0.033)., Conclusion: Our results confirm that the cobas 4800 System is a reliable platform for HCV quantitation and genotyping. The cobas HCV GT assay is a good choice for genotype 1b/6 endemic areas in east Asia, clearly outperforming the RealTi m e HCV Genotype II assay.

The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of X O and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research., (Copyright © 2020 by the Genetics Society of America.)

Background: The SureX HPV genotyping test (SureX HPV test), which targets the human papillomavirus (HPV) E6/E7 genes was compared with the Cobas 4800 and Venus HPV tests for detecting 14 high-risk HPV (HR-HPV) types in clinical referral and follow-up patients to evaluate its value for cervical cancer screening., Methods: Two different populations were enrolled in the study. The first population comprised 185 cases and was used for comparing the SureX HPV test (Health, China) with the Cobas 4800 test (Roche, USA). The second population comprised 290 cases and was used for comparing the SureX HPV test (Health, China) with the Venus HPV test (Zhijiang, China). Polymerase chain reaction (PCR) sequencing was performed for further confirmation of discordant results., Results: In the first population, the overall agreement rate was 95.6% for 14 high-risk HPV types. Eight discordant cases were confirmed by PCR sequencing, which showed that the agreement rates were 75.0% between the SureX HPV test and PCR sequencing and 25.0% between the Cobas 4800 test and PCR sequencing (P < 0.01). In the second population, the overall agreement rate was 95.5%. Thirteen discordant cases were confirmed by PCR sequencing, which showed that the agreement rates were 76.9% between the SureX HPV test and PCR sequencing and 23.1% between the Venus HPV test and PCR sequencing (P < 0.01). With cervical intraepithelial neoplasia grade 2+ (CIN2+) as the reference standard, the sensitivity values of the SureX HPV test and the Venus HPV test were 93.5% and 92.0%, (P > 0.05), while the specificity values were 43.3% and 46.7%, respectively (P > 0.05)., Conclusion: The SureX HPV test had good consistency with both the Cobas 4800 and Venus HPV tests for 14 HR-HPV types. In addition, it avoided some false negatives and false positives. Therefore, the SureX HPV test can be used for cervical cancer screening.

Male-to-female sex reversal in horses is a developmental disorder in which phenotypic females have a male genetic constitution. Male-to-female sex reversal is the second most common genetic sex abnormality, after X chromosome monosomy. All male-to-female sex reversal cases studied to date have been found to be infertile. Therefore, a screening test is particularly useful in laboratories doing DNA genotyping in horses. Our laboratory has tested > 209,000 horses for parentage using a panel of microsatellite markers and the sex marker gene amelogenin ( AMEL ). Suspect XY sex reversal cases are reported females with a male profile by AMEL testing. After routine genotyping, 49 cases were detected and further tested using the sex-determining region Y ( SRY ) gene, confirming the XY SRY -negative genotype of suspect sex reversal cases. When some inconsistencies arose in the initial result, a molecular panel of X- and Y-linked markers was analyzed for these samples. Of the 49 cases, 33 were confirmed as XY SRY -negative. The remaining 16 cases were identified as false-positives as a result of anomalies of AMEL testing in horses.

Pharmacogenomics is rapidly assuming an integral part in modern health care. Still, its broad applicability relies on the feasibility of performing pharmacogenomic testing in all clinical settings, including in remote areas or resource-limited settings with budget restrictions. In this study, we describe the development and feasibility of rapid and reliable pharmacogenomics assays using a portable molecular biology laboratory, namely the 2MoBiL (Mobile Molecular Biology Laboratory). More precisely, we demonstrate that the genotyping of rs4149056, located within SLCO1B1 , can be efficiently and reliably performed using the 2MoBiL portable laboratory and conventional benchtop laboratory equipment and a gold standard genotyping method (KASP assay) as directly comparable methodologies. Taking into account the compact size of 2MoBiL, which directly and positively impacts on its portability, and the high accuracy achieved, we conclude that the 2MoBiL-based genotyping method is warranted for further studies in clinical practices at remote areas and resource-limited as well as time-constrained planetary health settings. To contextualize the broader and potential future applications of 2MoBiL, we emphasize that genotyping of a limited set of clinically relevant single-nucleotide polymorphisms is often a common endpoint of genomics and pharmacogenomics discovery and translational research pipeline. Hence, rapid genotyping by 2MoBiL can be an essential catalyst for global implementation of pharmacogenomics and personalized medicine in the clinic. The Clinical Trial Registration number is NCT03093818.

The glycoprotein encoded by the ACKR1 gene expresses the Duffy blood group antigens and is a receptor for malaria parasites. We recently described 18 long-range ACKR1 alleles in an autochthonous population of a malaria endemic region. Extending this work, we sequenced the gene in a 53-sample repository established by the US Food and Drug Administration (FDA) as reference reagents for blood group genotyping. The FDA samples have been characterized for 19 genes; however, long-range haplotype information for these genes, including ACKR1, was lacking. We used a hybrid approach, novel for this type of gene, to characterize ACKR1 by combining two next-generation sequencing technologies, the short-read massively parallel sequencing and the long-read nanopore sequencing. The expedient integration of data from both next-generation sequencing systems were necessary and sufficient to allow determination of all 25 long-range ACKR1 alleles found in the 53 samples accurately. All 25 alleles identified in our current FDA cohort were novel and, unexpectedly, none had been observed among the 18 alleles in our previous study. The alleles will be useful for validation, calibration, and proficiency testing of red cell genotyping. The lack of any overlap between the ACKR1 alleles in the two studies documents differences in mutation rate and recombination frequency among populations. The exact haplotype and their interethnic or interpopulation dissimilarities can influence disease susceptibility and therapy., (Published by Elsevier Inc.)

With the widespread use of single nucleotide variants generated through mutagenesis screens and genome editing technologies, there is pressing need for an efficient and low-cost strategy to genotype single nucleotide substitutions. We have developed a rapid and inexpensive method for detection of point mutants through optimization of SuperSelective (SS) primers for end-point PCR in Caenorhabditis elegans Each SS primer consists of a 5' "anchor" that hybridizes to the template, followed by a noncomplementary "bridge," and a "foot" corresponding to the target allele. The foot sequence is short, such that a single mismatch at the terminal 3' nucleotide destabilizes primer binding and prevents extension, enabling discrimination of different alleles. We explored how length and sequence composition of each SS primer segment affected selectivity and efficiency in various genetic contexts in order to develop simple rules for primer design that allow for differentiation between alleles over a broad range of annealing temperatures. Manipulating bridge length affected amplification efficiency, while modifying the foot sequence altered discriminatory power. Changing the anchor position enabled SS primers to be used for genotyping in regions with sequences that are challenging for standard primer design. After defining primer design parameters, we demonstrated the utility of SS primers for genotyping crude C. elegans lysates, suggesting that this approach could also be used for SNP mapping and screening of CRISPR mutants. Further, since SS primers reliably detect point mutations, this method has potential for broad application in all genetic systems., (Copyright © 2020 by the Genetics Society of America.)

Background: Homologous sex chromosomes can differentiate over time because recombination is suppressed in the region of the sex determining locus, leading to the accumulation of repeats, progressive loss of genes that lack differential influence on the sexes and sequence divergence on the hemizygous homolog. Divergence in the non-recombining regions leads to the accumulation of Y or W specific sequence useful for developing sex-linked markers. Here we use in silico whole-genome subtraction to identify putative sex-linked sequences in the scincid lizard Bassiana duperreyi which has heteromorphic XY sex chromosomes., Results: We generated 96.7 × 10 9 150 bp paired-end genomic sequence reads from a XY male and 81.4 × 10 9 paired-end reads from an XX female for in silico whole genome subtraction to yield Y enriched contigs. We identified 7 reliable markers which were validated as Y chromosome specific by polymerase chain reaction (PCR) against a panel of 20 males and 20 females., Conclusions: The sex of B. duperreyi can be reversed by low temperatures (XX genotype reversed to a male phenotype). We have developed sex-specific markers to identify the underlying genotypic sex and its concordance or discordance with phenotypic sex in wild populations of B. duperreyi. Our pipeline can be applied to isolate Y or W chromosome-specific sequences of any organism and is not restricted to sequence residing within single-copy genes. This study greatly improves our knowledge of the Y chromosome in B. duperreyi and will enhance future studies of reptile sex determination and sex chromosome evolution.

STRidER, the STRs for Identity ENFSI Reference Database, is a curated, freely publicly available online allele frequency database, quality control (QC) and software platform for autosomal Short Tandem Repeats (STRs) developed under the endorsement of the International Society for Forensic Genetics. Continuous updates comprise additional STR loci and populations in the frequency database and many further STR-related aspects. One significant innovation is the autosomal STR data QC provided prior to publication of datasets. Such scrutiny was lacking previously, leaving QC to authors, reviewers and editors, which led to an unacceptably high error rate in scientific papers. The results from scrutinizing 184 STR datasets containing >177,000 individual genotypes submitted in the first two years of STRidER QC since 2017 revealed that about two-thirds of the STR datasets were either being withdrawn by the authors after initial feedback or rejected based on a conservative error rate. Almost no error-free submissions were received, which clearly shows that centralized QC and data curation are essential to maintain the high-quality standard required in forensic genetics. While many errors had minor impact on the resulting allele frequencies, multiple error categories were commonly found within single datasets. Several datasets contained serious flaws. We discuss the factors that caused the errors to draw the attention to redundant pitfalls and thus contribute to better quality of autosomal STR datasets and allele frequency reports.

Background: Individuals whose copies of the survival motor neuron 1 (SMN1) gene exist on the same chromosome are considered silent carriers for spinal muscular atrophy (SMA). Conventional screening for SMA only determines SMN1 copy number without any information regarding how those copies are arranged. A single nucleotide variant (SNV) rs143838139 is highly linked with the silent carrier genotype, so testing for this SNV can more accurately assess risk to a patient of having an affected child., Methods: Using a custom-designed SNV-specific Taqman genotyping assay, we determined and validated a model for silent-carrier detection in the laboratory., Results: An initial cohort of 21 pilot specimens demonstrated results that were 100% concordant with a reference laboratory method; this cohort was utilized to define the reportable range. An additional 177 specimens were utilized for a broader evaluation of clinical validity and reproducibility. Allelic-discrimination analysis demonstrated tight clustering of genotype groupings and excellent reproducibility, with a coefficient of variation for all genotypes ranging from 1% to 4%., Conclusion: The custom-developed Taqman SNV genotyping assay we tested provides a rapid, accurate, and cost-effective method for routine SMA silent-carrier screening and considerably improves detection rates of residual risk for SMA carriers., (© American Society for Clinical Pathology 2019. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Giardia intestinalis is an intestinal protozoan most commonly found in humans. It has been grouped into 8 assemblages (A-H). Markers such as the glutamate dehydrogenase gene, triose phosphate isomerase and beta-giardin (β-giardin) have been widely used for genotyping. In addition, different genetic targets have been proposed as a valuable alternative to assess diversity and genetics of this microorganism. Thus, our objective was to evaluate new markers for the study of the diversity and intra-taxa genetic structure of G. intestinalis in silico and in DNA obtained from stool samples. We analysed nine constitutive genes in 80 complete genome sequences and in a group of 24 stool samples from Colombia. Allelic diversity was evaluated by locus and for the concatenated sequence of nine loci that could discriminate up to 53 alleles. Phylogenetic reconstructions allowed us to identify AI, AII and B assemblages. We found evidence of intra- and inter-assemblage recombination events. Population structure analysis showed genetic differentiation among the assemblages analysed.

In this study, we aimed to assess the value of genotyping DNA pools as a strategy to generate accurate and cost-effective genomic estimated breeding values (GEBV) of sires in multi-sire mating systems. In order to do that, we used phenotypic records of 2,436 Australian Angus cattle from 174 sires, including yearling weight (YWT; N = 1,589 records), coat score (COAT; N = 2,026 records), and Meat Standards Australia marbling score (MARB; N = 1,304 records). Phenotypes were adjusted for fixed effects and age at measurement and pools of 2, 5, 10, 15, 20, and 25 animals were explored. Pools were created either by phenotype or at random. When pools were created at random, 10 replicates were examined to provide a measure of sampling variation. The relative accuracy of each pooling strategy was measured by the Pearson correlation coefficient between the sire's GEBV with pooled progeny and the GEBV using individually genotyped progeny. Random pools allow the computation of sire GEBV that are, on average, moderately correlated (i.e., r > 0.5 at pool sizes [PS] ≤ 10) with those obtained without pooling. However, for pools assigned at random, the difference between the best and the worst relative accuracy obtained out of the 10 replicates was as high as 0.41 for YWT, 0.36 for COAT, and 0.61 for MARB. This uncertainty associated with the relative accuracy of GEBV makes randomly assigning animals to pools an unreliable approach. In contrast, pooling by phenotype allowed the estimation of sires' GEBV with a relative accuracy ≥ 0.9 at PS < 10 for all three phenotypes. Moreover, even with larger PS, the lowest relative accuracy obtained was 0.88 (YWT, PS = 20). In agreement with results using simulated data, we conclude that pooling by phenotype is a robust approach to implementing genomic evaluation using commercial herd data, and PS larger than 10 individuals can be considered., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Recent studies have used genome-wide single-nucleotide polymorphisms (SNPs) to investigate relationships among various Jewish populations and their non-Jewish historical neighbors, often focusing on small subsets of populations from a limited geographic range or relatively small samples within populations. Here, building on the significant progress that has emerged from genomic SNP studies in the placement of Jewish populations in relation to non-Jewish populations, we focus on population structure among Jewish populations. In particular, we examine Jewish population-genetic structure in samples that span much of the historical range of Jewish populations in Europe, the Middle East, North Africa, and South Asia. Combining 429 newly genotyped samples from 29 Jewish and 3 non-Jewish populations with previously reported genotypes on Jewish and non-Jewish populations, we investigate variation in 2789 individuals from 114 populations at 486,592 genome-wide autosomal SNPs. Using multidimensional scaling analysis, unsupervised model-based clustering, and population trees, we find that, genetically, most Jewish samples fall into four major clusters that largely represent four culturally defined groupings, namely the Ashkenazi, Mizrahi, North African, and Sephardi subdivisions of the Jewish population. We detect high-resolution population structure, including separation of the Ashkenazi and Sephardi groups and distinctions among populations within the Mizrahi and North African groups. Our results refine knowledge of Jewish population-genetic structure and contribute to a growing understanding of the distinctive genetic ancestry evident in closely related but historically separate Jewish communities.

Phasing is the process of inferring haplotypes from genotype data. Efficient algorithms and associated software for accurate phasing in pedigrees are needed, especially for populations lacking reference panels of sequenced individuals. We present a novel method for phasing genotypes from whole-genome sequence data in pedigrees, called PULSAR (Phasing Using Lineage Specific Alleles/Rare variants). The method is based on the property that alleles specific to a single founding chromosome within a pedigree are highly informative for identifying haplotypes that are shared identical by descent. Simulation studies are used to assess the performance of PULSAR with various pedigree sizes and structures, and the effect of genotyping errors and the presence of nonsequenced individuals is investigated. In pedigrees with complete sequencing and realistic genotyping error rates, PULSAR correctly phases >99.9% of heterozygous genotypes, excluding sites at which all individuals are heterozygous, and does so with a switch error rate frequently below 10 -4 . PULSAR is highly accurate, capable of genotype error correction and imputation, and computationally competitive with alternative phasing software applicable to pedigrees. Our method has the significant advantage of not requiring reference panels that are essential for other population-based phasing algorithms. A software implementation of PULSAR is freely available.

Background: The androgen receptor (AR) is a nuclear receptor, encoded by the AR gene on the X chromosome. Within the first exon of the AR gene, two short tandem repeats (STR), CAG and GGC, are a source of polymorphism in the population. Therefore, high-throughput methods for screening AR, such as next-generation sequencing (NGS), are sought after; however, data generated by NGS are limited by the availability of bioinformatics tools. Here, we evaluated the accuracy of the bioinformatics tool HipSTR in detecting and quantify CAG repeats within the AR gene., Method: The AR gene of 228 infertile men was sequenced using NGSgene panel. Data generated were analyzed with HipSTR to detect CAG repeats. The accuracy was compared with the results obtained with Sanger., Results: We found that HipSTR was more accurate than Sanger in genotyping normal karyotype men (46,XY), however, it was more likely to misidentify homozygote genotypes in men with Klinefelter syndrome (47,XXY)., Conclusion: Our findings show that the bioinformatics tool HipSTR is 100% accurate in detecting and assessing AR CAG repeats in infertile men (46,XY) as well as in men with low-level mosaicism., (© 2020 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.)

While genotyping studies are scavenging for suitable samples to analyze, large serum collections are currently left unused as they are assumed to provide insufficient amounts of DNA for array-based genotyping. Long-term stored serum is considered to be difficult to genotype since preanalytical treatments and storage effects on DNA yields are not well understood. Successful genotyping of such samples has the potential to activate large biobanks for future genome-wide association studies (GWAS). We aimed to evaluate genotyping of ultralow amounts of DNA from samples stored up to 45 years in the Janus Serum Bank with two commercially available platforms. 64 samples, with various preanalytical treatments, were genotyped on the Axiom Array from Thermo Fisher Scientific and a subset of 24 samples with slightly higher yield were genotyped on the HumanCoreExome array from Illumina. Our results showed that about 80% of the serum samples produced call rates with the Axiom arrays that would be satisfactory in GWAS. The mean DNA yield was 5.8 ng as measured with PicoGreen, 3-6% of recommended yield. The failed samples had on average lower input amounts of DNA. All serum samples genotyped on the HumanCoreExome with a standard and FFPE protocol produced GWAS satisfactory call rates, with mean 97.57% and 98.35% call rates, respectively. The mean yield was 10.65 ng, 6% of the recommendations. Successful array-based genotyping of ultralow DNA yields from serum samples stored up to 45 years is possible. These results demonstrate the potential to activate large serum biobank collections for future studies.

Background: Genetic polymorphisms at 23 short tandem repeat (STR) loci were investigated in 1,215 Jining Han individuals from Jining city, Shandong province, eastern China., Methods: We used population genetic data of 23 autosomal STR loci included in the Huaxia Platinum system to evaluate 1,215 unrelated Chinese Han individuals in the Jining Han population. Allele frequencies and forensic parameters of the STR loci were determined and genetic relationships among the Jining Han and other Chinese populations were evaluated., Results: In total, we observed 321 alleles, with frequencies ranging from 0.00041 to 0.52222. The combined discrimination power and probability of excluding paternity were 0.99999999999999999999999999919 and 0.99999999962, respectively. No deviations from HWE were observed at any loci. Population comparisons showed that the Xinjiang groups (Uyghur and Kazakh) and the Mongolian and Tibetan groups were isolated, while the Jining Han population clustered together with other populations, except the Guizhou Han population., Conclusion: This study demonstrated that 23 autosomal STR loci included in the Huaxia Platinum system are highly polymorphic and suitable for personal forensic identification and paternity testing in this population., (© 2020 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.)

Coriander (Coriandrum sativum L.) is an aromatic herb, widely used as a spice and is of great pharmaceutical interest. Despite high medicinal and economic value, there is a dearth of genomic information about profiling as well as the expressed sequence-based genic markers. In this study, transcriptome was sequenced from seeds, leaves, and flower for gene mining and identification of SSR markers. A total of 9746 SSR containing loci were identified, the most abundant type of SSR identified were the di-nucleotide repeat motifs (45.5%), followed by tri- (34.6%), tetra- (4.5%), penta- (1.5%) and hexanucleotide repeats (1%). A total of 3795 primers were designed, out of which 120 randomly selected were validated in 14 accessions of coriander cultivated in India. The current study provides useful information about preliminary transcriptome sketch and genic markers, which can be useful in breeding and genetic diversity estimation of coriander., Competing Interests: Declaration of Competing Interest None of the authors have any financial or personal relationships that could inappropriately influence or bias the content of the research paper., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The antiplatelet agent clopidogrel, a prodrug that requires bioactivation through the cytochrome P450 2C19 (CYP2C19) enzyme, is commonly prescribed post-percutaneous coronary intervention (PCI). Genetic variation in CYP2C19 contributes to individual variability in clopidogrel response, and can lead to adverse cardiovascular events. Incorporating CYP2C19 testing during routine clinical care helps identify high-risk patients, and provides the opportunity for pharmacotherapeutic interventions in the early post-PCI period. The Spartan RX CYP2C19 System has emerged as an optimal genotyping assay for use in clinical care due to ease of use, utilization of buccal swabs, and rapid turnaround time. However, workflow constraints related to sample collection and processing, storage, time, and personnel were encountered when integrating testing into clinical care. To improve clinical workflow and successfully implement CYP2C19 genotyping at our institution, we validated the Spartan RX System to return genotype utilizing blood samples. Our Molecular Diagnostic Laboratory tested 26 known reference materials and both blood and buccal swab samples from 23 patients and volunteers using the Spartan RX Assay. Genotype results were 100% concordant between DNA from blood and buccal swabs for all patients or volunteers, and consistent with expected results for the 26 reference materials. For reproducibility, three samples were tested in at least four separate runs, with all resulting genotypes in agreement between runs. Post-validation, the laboratory began offering CYP2C19 testing during clinical care. DNA extracted from blood can serve as a genomic DNA source for the Spartan RX Assay. Alteration of the methodology allowed for clinical implementation to support genotype-guided therapy., (© 2019 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

Plant growth and development are largely regulated by non-coding RNAs (ncRNA); thus ncRNA based markers would be rewarding in molecular breeding. In the present study, for the first time we developed total 623 ncRNA based SSRs including 119 microRNASSRs (miRNASSRs) and 504 long non-coding RNASSRs (lncRNASSRs) distributed across 12 Capsicum chromosomes. Out of 623 ncRNASSRs, 120 (including 60 each miRNASSRs and lncRNASSRs) were used for genotyping of 96 Capsicum accessions belonging to C. annuum, C. chinense and C. frutescens; and 75% SSRs were polymorphic. Model-based and distance-based cluster analyses identified three species specific clusters, i.e. cluster-I (C. annuum), cluster-II (C. frutescens) and cluster-III (C. chinense); therefore, these SSRs may have a potential role to play in interspecific Capsicum breeding. Tissue specific expression of SSR containing ncRNAs and versatile functions of their targets suggested the usefulness of SSRs for mapping of genes/QTLs and breeding of wide range of traits in Capsicum., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Hematopoietic stem cells (HSCs) are functionally and genetically diverse and this diversity decreases with age and disease. Numerous systems have been developed to quantify HSC diversity by genetic barcoding, but no framework has been established to empirically validate barcode sequences. Here we have developed an analytical framework, Selection of informative Amplicon Barcodes from Experimental Replicates (SABER), that identifies barcodes that are unique among a large set of experimental replicates. Amplicon barcodes were sequenced from the blood of 56 adult zebrafish divided into training and validation sets. Informative barcodes were identified and samples with a high fraction of informative barcodes were chosen by bootstrapping. There were 4.2 ± 1.8 barcoded HSC clones per sample in the training set and 3.5 ± 2.1 in the validation set (p = 0.3). SABER reproducibly quantifies functional HSCs and can accommodate a wide range of experimental group sizes. Future large-scale studies aiming to understand the mechanisms of HSC clonal evolution will benefit from this new approach to identifying informative amplicon barcodes.

Detecting and estimating DNA sample contamination are important steps to ensure high-quality genotype calls and reliable downstream analysis. Existing methods rely on population allele frequency information for accurate estimation of contamination rates. Correctly specifying population allele frequencies for each individual in early stage of sequence analysis is impractical or even impossible for large-scale sequencing centers that simultaneously process samples from multiple studies across diverse populations. On the other hand, incorrectly specified allele frequencies may result in substantial bias in estimated contamination rates. For example, we observed that existing methods often fail to identify 10% contaminated samples at a typical 3% contamination exclusion threshold when genetic ancestry is misspecified. Such an incomplete screening of contaminated samples substantially inflates the estimated rate of genotyping errors even in deeply sequenced genomes and exomes. We propose a robust statistical method that accurately estimates DNA contamination and is agnostic to genetic ancestry of the intended or contaminating sample. Our method integrates the estimation of genetic ancestry and DNA contamination in a unified likelihood framework by leveraging individual-specific allele frequencies projected from reference genotypes onto principal component coordinates. Our method can also be used for estimating genetic ancestries, similar to LASER or TRACE , but simultaneously accounting for potential contamination. We demonstrate that our method robustly estimates contamination rates and genetic ancestries across populations and contamination scenarios. We further demonstrate that, in the presence of contamination, genetic ancestry inference can be substantially biased with existing methods that ignore contamination, while our method corrects for such biases., (© 2020 Zhang et al.; Published by Cold Spring Harbor Laboratory Press.)

Background: Short tandem repeats (STRs) are essential genetic markers for forensic applications and population estimations; thus the population genetics of STR loci have been extensively studied and discussed., Methods: In the present study, we detected 21 autosomal noncombined DNA index system (non-CODIS) STR loci in a Chinese Han population from Shanghai, calculated their forensic parameters and analyzed their genetic relationships with reported reference populations in mainland China., Results: A total of 173 alleles were observed, with corresponding allele frequencies from 0.0020 to 0.5512. The cumulative power of discrimination (CPD) and the cumulative probability of exclusion (CPE) values of the 21 STR loci were 0.999999999999999999997337058271 and 0.99999953732495, respectively. The results of interpopulation differentiation, phylogenetic, multidimensional scaling, and structure analyses indicated a closer genetic relationship of the studied population with Han populations from other regions of China than with other populations., Conclusions: The 21 STR loci exhibited high genetic polymorphism in the studied Shanghai&#95;Han population and could be used for forensic applications and population genetic studies., (© 2019 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.)

Background: Individual identification is one of the most important tasks in the field of forensic genetics. Insertion/Deletion (InDel) polymorphism marker has been a promising marker for individual identification. However, a part of InDel loci in commonly used commercial kit show low polymorphisms in Chinese populations., Methods: We evaluated a panel of 35 InDel loci constructed previously for individual identifications in Hui group. Subsequently, population data of three Chinese populations from 1,000 Genomes Project database were used to evaluate individual identification performance of these 35 InDels. Forensic parameters, such as heterozygosity, power of exclusion, match probability and power of discrimination, were calculated to evaluate the forensic efficiency of these loci in Hui group. The heatmap of insertion allelic frequencies, Nei's genetic distances, pairwise fixation index values, principal component analyses and admixture analyses were used to analyze the genetic differentiations and structure between Hui group and other populations., Results: In studied Hui group, besides rs3054057, polymorphism information content values of the remaining loci were greater than 0.3. Values of expected heterozygosity of these loci were close to 0.5. The combined power of discrimination and power of exclusion values were 0.99999999999999659609 and 0.998682, respectively. Analyses of population genetics revealed that Chinese Hui group had closer genetic relationships with East Asian populations than other intercontinental populations., Conclusion: The forensic statistical analyses revealed these loci showed relatively high genetic polymorphisms in Chinese Hui group, and could be served as a useful tool for individual identifications in Hui group. Population genetic evaluations indicated that Chinese Hui group had close genetic relationships with East Asian populations., (© 2019 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.)

Background: Accurately identifying single-nucleotide polymorphisms (SNPs) from bacterial sequencing data is an essential requirement for using genomics to track transmission and predict important phenotypes such as antimicrobial resistance. However, most previous performance evaluations of SNP calling have been restricted to eukaryotic (human) data. Additionally, bacterial SNP calling requires choosing an appropriate reference genome to align reads to, which, together with the bioinformatic pipeline, affects the accuracy and completeness of a set of SNP calls obtained. This study evaluates the performance of 209 SNP-calling pipelines using a combination of simulated data from 254 strains of 10 clinically common bacteria and real data from environmentally sourced and genomically diverse isolates within the genera Citrobacter, Enterobacter, Escherichia, and Klebsiella., Results: We evaluated the performance of 209 SNP-calling pipelines, aligning reads to genomes of the same or a divergent strain. Irrespective of pipeline, a principal determinant of reliable SNP calling was reference genome selection. Across multiple taxa, there was a strong inverse relationship between pipeline sensitivity and precision, and the Mash distance (a proxy for average nucleotide divergence) between reads and reference genome. The effect was especially pronounced for diverse, recombinogenic bacteria such as Escherichia coli but less dominant for clonal species such as Mycobacterium tuberculosis., Conclusions: The accuracy of SNP calling for a given species is compromised by increasing intra-species diversity. When reads were aligned to the same genome from which they were sequenced, among the highest-performing pipelines was Novoalign/GATK. By contrast, when reads were aligned to particularly divergent genomes, the highest-performing pipelines often used the aligners NextGenMap or SMALT, and/or the variant callers LoFreq, mpileup, or Strelka., (© The Author(s) 2020. Published by Oxford University Press.)

Individuals within a species can exhibit vast variation in copy number of repetitive DNA elements. This variation may contribute to complex traits such as lifespan and disease, yet it is only infrequently considered in genotype-phenotype associations. Although the possible importance of copy number variation is widely recognized, accurate copy number quantification remains challenging. Here, we assess the technical reproducibility of several major methods for copy number estimation as they apply to the large repetitive ribosomal DNA array (rDNA). rDNA encodes the ribosomal RNAs and exists as a tandem gene array in all eukaryotes. Repeat units of rDNA are kilobases in size, often with several hundred units comprising the array, making rDNA particularly intractable to common quantification techniques. We evaluate pulsed-field gel electrophoresis, droplet digital PCR, and Nextera-based whole genome sequencing as approaches to copy number estimation, comparing techniques across model organisms and spanning wide ranges of copy numbers. Nextera-based whole genome sequencing, though commonly used in recent literature, produced high error. We explore possible causes for this error and provide recommendations for best practices in rDNA copy number estimation. We present a resource of high-confidence rDNA copy number estimates for a set of S. cerevisiae and C. elegans strains for future use. We furthermore explore the possibility for FISH-based copy number estimation, an alternative that could potentially characterize copy number on a cellular level., (Copyright © 2020 Morton et al.)

This study compared imputation from lower-density commercial and customized panels to high-density panels and a combined panel (Illumina and Affymetrix) in Nelore beef cattle. Additionally, linkage disequilibrium and haplotype block conformation were estimated in individual high-density panels and compared with corresponding values in the combined panel after imputation. Overall, 814 animals were genotyped using BovineHD BeadChip (IllumHD), and 93 of these animals were also genotyped using the Axion Genome-Wide BOS 1 Array Plate (AffyHD). In general, customization considering linkage disequilibrium and minor allele frequency had the highest accuracies. The IllumHD panel had higher values of linkage disequilibrium for short distances between SNPs than AffyHD and the combined panel. The combined panel had an increased number of small haplotype blocks. The use of a combined panel is recommended due to its increased density and number of haplotype blocks, which in turn increase the probability of a marker being close to a quantitative trait locus of interest. Considering common SNPs between IllumHD and AffyHD for the customization of a low-density panel increases the imputation accuracy for IllumHD, AffyHD and the combined panel.

Short tandem repeat (STR) profiling has been routinely used in kinship testing since the introduction of commercial kits in the mid-1990s. While 15 to 23 STR loci normally give definitive results in simple kinship testing, additional loci are sometimes required to resolve complex cases. The SureID 23comp Human Identification Kit, recently released by Health Gene Technologies (China), multiplexes amelogenin and 22 autosomal STRs, 17 of which are non-CODIS STRs. This enables the profiling of 38-40 loci when used in conjunction with widely used commercial kits. In this study, the kit was evaluated for kinship applications as a supplementary STR kit following the minimum criteria for validation recommended by the European Network of Forensic Science Institutes (ENFSI) and the Scientific Working Group on DNA Analysis Methods (SWGDAM) using 500 samples. Performance was comparable with other commercial kits demonstrating: repeatability and reproducibility; precision (maximum s.d. 0.1048 nt); accuracy, all alleles were within ±0.41 nt compared to the actual sizes; heterozygous peak balances at all loci >68%; stutter ratios ranged from 3.8% to 16.15%; full profiles were generated with 125 pg DNA (95.12% of alleles at 62 pg),; and we found 100% concordance over 5 common STRs with the GlobalFiler kit.

The success of next-generation sequencing depends on the accuracy of variant calls. Few objective protocols exist for QC following variant calling from whole genome sequencing (WGS) data. After applying QC filtering based on Genome Analysis Tool Kit (GATK) best practices, we used genotype discordance of eight samples that were sequenced twice each to evaluate the proportion of potentially inaccurate variant calls. We designed a QC pipeline involving hard filters to improve replicate genotype concordance, which indicates improved accuracy of genotype calls. Our pipeline analyzes the efficacy of each filtering step. We initially applied this strategy to well-characterized variants from the ClinVar database, and subsequently to the full WGS dataset. The genome-wide biallelic pipeline removed 82.11% of discordant and 14.89% of concordant genotypes, and improved the concordance rate from 98.53% to 99.69%. The variant-level read depth filter most improved the genome-wide biallelic concordance rate. We also adapted this pipeline for triallelic sites, given the increasing proportion of multiallelic sites as sample sizes increase. For triallelic sites containing only SNVs, the concordance rate improved from 97.68% to 99.80%. Our QC pipeline removes many potentially false positive calls that pass in GATK, and may inform future WGS studies prior to variant effect analysis.

Background/aims: To evaluate the HCV RNA genotyping and HDV RNA tests that are performed in molecular microbiology laboratories in Turkey as part of a national external quality assessment programme, MOTAKK (Moleküler Tanıda Kalite Kontrol) (English translation: Quality control in molecular diagnostics)., Materials and Methods: Plasmas having different HCV RNA genotypes were used to prepare HCV genotype control sera. The HDV RNA main stock was prepared from patients with chronic delta hepatitis who had a significant amount of viral load detected, as per the WHO reference materials on viral load studies that were compiled for the purpose of developing HDV RNA control sera. Samples with different viral loads were prepared from this main stock by dilution. The prepared controls were delivered to the registered laboratories. The laboratories carried out the relevant tests and entered their results via the MOTAKK web page. External quality assessment (EQA) reports of the participants were uploaded to the website as well., Results: In total, there were 23 participating laboratories, out of which 20 exclusively performed HCV genotyping, and 15 and 16 only performed HDV RNA in 2015 and 2016, respectively. The success rate of the results of the HCV genotype was 56-96% in 2015 and 30-95% in 2016. The tube with a 30% success rate had a recombinant type of HCV, therefore, it could not be detected in most of the laboratories. The HDV RNA results were evaluated qualitatively. Accordingly, HDV RNA detection rates of participant laboratories were 71-100% in 2015 and 50-100% in 2016., Conclusion: This study was the first national external quality control program in Turkey regarding HCV RNA genotyping and HDV RNA in the field of molecular microbiology, and it was implemented successfully.

Testing for Hardy-Weinberg equilibrium (HWE) is an important component in almost all analyses of population genetic data. Genetic markers that violate HWE are often treated as special cases; for example, they may be flagged as possible genotyping errors, or they may be investigated more closely for evolutionary signatures of interest. The presence of population structure is one reason why genetic markers may fail a test of HWE. This is problematic because almost all natural populations studied in the modern setting show some degree of structure. Therefore, it is important to be able to detect deviations from HWE for reasons other than structure. To this end, we extend statistical tests of HWE to allow for population structure, which we call a test of "structural HWE." Additionally, our new test allows one to automatically choose tuning parameters and identify accurate models of structure. We demonstrate our approach on several important studies, provide theoretical justification for the test, and present empirical evidence for its utility. We anticipate the proposed test will be useful in a broad range of analyses of genome-wide population genetic data., (Copyright © 2019 Hao and Storey.)

Pharmacogenetic testing increasingly is available from clinical and research laboratories. However, only a limited number of quality control and other reference materials currently are available for the complex rearrangements and rare variants that occur in the CYP2D6 gene. To address this need, the Division of Laboratory Systems, CDC-based Genetic Testing Reference Material Coordination Program, in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Cell Repositories (Camden, NJ), has characterized 179 DNA samples derived from Coriell cell lines. Testing included the recharacterization of 137 genomic DNAs that were genotyped in previous Genetic Testing Reference Material Coordination Program studies and 42 additional samples that had not been characterized previously. DNA samples were distributed to volunteer testing laboratories for genotyping using a variety of commercially available and laboratory-developed tests. These publicly available samples will support the quality-assurance and quality-control programs of clinical laboratories performing CYP2D6 testing., (Copyright © 2019 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)

Conservation initiatives are now more crucial than ever-over a million plant and animal species are at risk of extinction over the coming decades. The genetic management of threatened species held in insurance programs is recommended; however, few are taking advantage of the full range of genomic technologies available today. Less than 1% of the 13505 species currently listed as threated by the International Union for Conservation of Nature (IUCN) have a published genome. While there has been much discussion in the literature about the importance of genomics for conservation, there are limited examples of how having a reference genome has changed conservation management practice. The Tasmanian devil ( Sarcophilus harrisii ), is an endangered Australian marsupial, threatened by an infectious clonal cancer devil facial tumor disease (DFTD). Populations have declined by 80% since the disease was first recorded in 1996. A reference genome for this species was published in 2012 and has been crucial for understanding DFTD and the management of the species in the wild. Here we use the Tasmanian devil as an example of how a reference genome has influenced management actions in the conservation of a species.

Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Genotype imputation, where missing genotypes can be computationally imputed, is an essential tool in genomic analysis ranging from genome wide associations to phenotype prediction. Traditional genotype imputation methods are typically based on haplotype-clustering algorithms, hidden Markov models (HMMs), and statistical inference. Deep learning-based methods have been recently reported to suitably address the missing data problems in various fields. To explore the performance of deep learning for genotype imputation, in this study, we propose a deep model called a sparse convolutional denoising autoencoder (SCDA) to impute missing genotypes. We constructed the SCDA model using a convolutional layer that can extract various correlation or linkage patterns in the genotype data and applying a sparse weight matrix resulted from the L 1 regularization to handle high dimensional data. We comprehensively evaluated the performance of the SCDA model in different scenarios for genotype imputation on the yeast and human genotype data, respectively. Our results showed that SCDA has strong robustness and significantly outperforms popular reference-free imputation methods. This study thus points to another novel application of deep learning models for missing data imputation in genomic studies.