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Most cases of multidrug-resistant (MDR) tuberculosis (TB) are never diagnosed (328,300 of the ∼490,000 cases in 2016 were missed). The Xpert MTB/RIF assay detects resistance only to rifampin, despite ∼20% of rifampin-resistant cases being susceptible to isoniazid (a critical first-line drug). Consequently, many countries require further testing with the GenoType MTBDR plus assay. However, MTBDR plus is not recommended for use on smear-negative specimens, and thus, many specimens require culture-based drug susceptibility testing. Furthermore, MTBDR plus requires specialized expertise, lengthy hands-on time, and significant laboratory infrastructure and interpretation is not automated. To address these gaps, we evaluated the accuracy of the FluoroType MTBDR (FluoroType) assay. Sputa from 244 smear-positive and 204 smear-negative patients with presumptive TB (Xpert MTB positive, n = 343) were tested. Culture and MTBDR plus on isolates served as reference standards (for active TB and MDR-TB, respectively). Sanger sequencing and MTBDR plus , both of which were performed on sputa, were used to resolve discrepancies. The sensitivity of FluoroType for the detection of M. tuberculosis complex was 98% (95% confidence interval [CI], 95 to 99%) and 92% (95% CI, 84 to 96%) for smear-positive and smear-negative specimens, respectively (232/237 versus 90/98 specimens; P < 0.009). The sensitivity and specificity for smear-negative specimens were 100% and 97%, respectively, for rifampin resistance; 100% and 98%, respectively, for isoniazid resistance; and 100% and 100%, respectively, for MDR-TB. FluoroType identified 98%, 97%, and 97% of the rpoB , katG , and inhA promoter mutations, respectively. FluoroType has excellent sensitivity with sputa equivalent to that of MTBDR plus with the isolates and can provide rapid drug susceptibility testing for rifampin and isoniazid. In addition, the capacity of FluoroType to simultaneously identify virtually all mutations in the rpoB , katG , and inhA promoter may be useful for individualized treatment regimens., (Copyright © 2018 American Society for Microbiology.)

Background: Runs of homozygosity (ROH) islands are stretches of homozygous sequence in the genome of a large proportion of individuals in a population. Algorithms for the detection of ROH depend on the similarity of haplotypes. Coverage gaps and copy number variants (CNV) may result in incorrect identification of such similarity, leading to the detection of ROH islands where none exists. Misidentified hemizygous regions will also appear as homozygous based on sequence variation alone. Our aim was to identify ROH islands influenced by marker coverage gaps or CNV, using Illumina BovineHD BeadChip (777 K) single nucleotide polymorphism (SNP) data for Austrian Brown Swiss, Tyrol Grey and Pinzgauer cattle., Methods: ROH were detected using clustering, and ROH islands were determined from population inbreeding levels for each marker. CNV were detected using a multivariate copy number analysis method and a hidden Markov model. SNP coverage gaps were defined as genomic regions with intermarker distances on average longer than 9.24 kb. ROH islands that overlapped CNV regions (CNVR) or SNP coverage gaps were considered as potential artefacts. Permutation tests were used to determine if overlaps between CNVR with copy losses and ROH islands were due to chance. Diversity of the haplotypes in the ROH islands was assessed by haplotype analyses., Results: In Brown Swiss, Tyrol Grey and Pinzgauer, we identified 13, 22, and 24 ROH islands covering 26.6, 389.0 and 35.8 Mb, respectively, and we detected 30, 50 and 71 CNVR derived from CNV by using both algorithms, respectively. Overlaps between ROH islands, CNVR or coverage gaps occurred for 7, 14 and 16 ROH islands, respectively. About 37, 44 and 52% of the ROH islands coverage in Brown Swiss, Tyrol Grey and Pinzgauer, respectively, were affected by copy loss. Intersections between ROH islands and CNVR were small, but significantly larger compared to ROH islands at random locations across the genome, implying an association between ROH islands and CNVR. Haplotype diversity for reliable ROH islands was lower than for ROH islands that intersected with copy loss CNVR., Conclusions: Our findings show that a significant proportion of the ROH islands in the bovine genome are artefacts due to CNV or SNP coverage gaps.

Background: Molecular classification of tumour clonality is currently not evaluated in multiple invasive breast carcinomas, despite evidence suggesting common clonal origins. There is no consensus about which type of data (e.g. copy number, mutation, histology) and especially which statistical method is most suitable to distinguish clonal recurrences from independent primary tumours., Methods: Thirty-seven invasive breast tumour pairs were stratified according to laterality and time interval between the diagnoses of the two tumours. In a multi-omics approach, tumour clonality was analysed by integrating clinical characteristics (n = 37), DNA copy number (n = 37), DNA methylation (n = 8), gene expression microarray (n = 7), RNA sequencing (n = 3), and SNP genotyping data (n = 3). Different statistical methods, e.g. the diagnostic similarity index (SI), were used to classify the tumours as clonally related recurrences or independent primary tumours., Results: The SI and hierarchical clustering showed similar tendencies and the highest concordance with the other methods. Concordant evidence for tumour clonality was found in 46% (17/37) of patients. Notably, no association was found between the current clinical guidelines and molecular tumour features., Conclusions: A more accurate classification of clonal relatedness between multiple breast tumours may help to mitigate treatment failure and relapse by integrating tumour-associated molecular features, clinical parameters, and statistical methods. Guidelines need to be defined with exact thresholds to standardise clonality testing in a routine diagnostic setting.

Unlike agricultural crops, most forest species have not had millennia of improvement through phenotypic selection, but can contribute energy and material resources and possibly help alleviate climate change. Yield gains similar to those achieved in agricultural crops over millennia could be made in forestry species with the use of genomic methods in a much shorter time frame. Here we compare various methods of genomic prediction for eight traits related to foliar terpene yield in Eucalyptus polybractea , a tree grown predominantly for the production of Eucalyptus oil. The genomic markers used in this study are derived from shallow whole genome sequencing of a population of 480 trees. We compare the traditional pedigree-based additive best linear unbiased predictors (ABLUP), genomic BLUP (GBLUP), BayesB genomic prediction model, and a form of GBLUP based on weighting markers according to their influence on traits (BLUP|GA). Predictive ability is assessed under varying marker densities of 10,000, 100,000 and 500,000 SNPs. Our results show that BayesB and BLUP|GA perform best across the eight traits. Predictive ability was higher for individual terpene traits, such as foliar α-pinene and 1,8-cineole concentration (0.59 and 0.73, respectively), than aggregate traits such as total foliar oil concentration (0.38). This is likely a function of the trait architecture and markers used. BLUP|GA was the best model for the two biomass related traits, height and 1 year change in height (0.25 and 0.19, respectively). Predictive ability increased with marker density for most traits, but with diminishing returns. The results of this study are a solid foundation for yield improvement of essential oil producing eucalypts. New markets such as biopolymers and terpene-derived biofuels could benefit from rapid yield increases in undomesticated oil-producing species., (Copyright © 2018 Kainer et al.)

We describe a genetic map with a total of 381 bins of 616 genotyping by sequencing (GBS)-based SNP markers in a F 6 -F 8 recombinant inbred line (RIL) population of 393 individuals derived from crossing S. bicolor BTx623 to S. bicolor IS3620C, a guinea line substantially diverged from BTx623. Five segregation distorted regions were found with four showing enrichment for S. bicolor alleles, suggesting possible selection during formation of this RIL population. A quantitative trait locus (QTL) study with this number of individuals, tripled relative to prior studies of this cross, provided resources, validated previous findings, and demonstrated improved power to detect plant height and flowering time related QTL relative to other published studies. An unexpected low correlation between flowering time and plant height permitted us to separate QTL for each trait and provide evidence against pleiotropy. Ten non- random syntenic regions conferring QTL for the same trait suggest that those QTL may represent alleles at genes functioning in the same manner since the 96 million year ago genome duplication that created these syntenic relationships, while syntenic regions conferring QTL for different trait may suggest sub-functionalization after duplication. Collectively, this study provides resources for marker-assisted breeding, as well as a framework for fine mapping and subsequent cloning of major genes for important traits such as plant height and flowering time in sorghum., (Copyright © 2018 Kong et al.)

Rapid differentiation of wild-type measles virus from measles vaccine strains is crucial during a measles outbreak and in a measles elimination setting. A real-time reverse transcription-PCR (rRT-PCR) for the rapid detection of measles vaccine strains was developed with high specificity and sensitivity equivalent to that of traditional measles genotyping methods. The "stressed" minor groove binder-TaqMan probe design approach achieves specificity to vaccine strains only, without compromising sensitivity. This assay, without requiring sequence genotyping, has proved to be extremely useful in outbreak settings for over 4 years at the Regional Measles Reference Laboratory for the Western Pacific Region., (Copyright © 2018 Tran et al.)

Background: Germline and tumor pharmacogenomics impact drug responses, but germline markers less commonly guide oncology prescribing. The authors hypothesized that a critical number of clinically actionable germline pharmacogenomic associations exist, representing clinical implementation opportunities., Methods: In total, 125 oncology drugs were analyzed for positive germline pharmacogenomic associations in journals with impact factors ≥5. Studies were assessed for design and genotyping quality, clinically relevant outcomes, statistical rigor, and evidence of drug-gene effects. Associations from studies of high methodologic quality were deemed potentially clinically actionable, and translational summaries were written as point-of-care clinical decision support (CDS) tools and formally evaluated using the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument., Results: The authors identified germline pharmacogenomic results for 56 of 125 oncology drugs (45%) across 173 publications. Actionable associations were detected for 12 drugs, including 6 that had germline pharmacogenomic information within US Food and Drug Administration labels or published guidelines (capecitabine/fluorouracil/dihydropyrimidine dehydrogenase [DPYD], irinotecan/uridine diphosphate glucuronosyltransferase family 1 member A1 [UGT1A1], mercaptopurine/thioguanine/thiopurine S-methyltransferase [TPMT], tamoxifen/cytochrome P450 [CYP] family 2 subfamily D member 6 [CYP2D6]), and 6 others were novel (asparaginase/nuclear factor of activated T-cells 2 [NFATC2]/human leukocyte antigen D-related β1 [HLA-DRB1], cisplatin/acylphosphatase 2 [ACYP2], doxorubicin/adenosine triphosphate-binding cassette subfamily C member 2/Rac family small guanosine triphosphatase 2/neutrophil cytosolic factor 4 [ABCC2/RAC2/NCF4], lapatinib/human leukocyte antigen DQ α1 [HLA-DQA1], sunitinib/cytochrome P450 family 3 subfamily A member 5 [CYP3A5], vincristine/centrosomal protein 72 [CEP72]). By using AGREE II, the developed CDS summaries had high mean ± standard deviation scores (maximum score, 100) for scope and purpose (92.7 ± 5.1) and rigour of development (87.6 ± 7.4) and moderate yet robust scores for clarity of presentation (58.6 ± 25.1) and applicability (55.9 ± 24.6). The overall mean guideline quality score was 5.2 ± 1.0 (maximum score, 7). Germline pharmacogenomic CDS summaries for these 12 drugs were recommended for implementation., Conclusions: Several oncology drugs have actionable germline pharmacogenomic information, justifying their delivery through institutional pharmacogenomic implementations to determine clinical utility. Cancer 2018;124:3052-65. © 2018 American Cancer Society., (© 2018 American Cancer Society.)

Loop mediated isothermal amplification (LAMP) assay is sensitive, prompt, high throughput and field deployable technique for nucleic acid amplification under isothermal conditions. In this study, we have developed and optimized four different visualization methods of loop-mediated isothermal amplification (LAMP) assay to detect Pfcrt K76T mutants of P. falciparum and compared their important features for one-pot in-field applications. Even though all the four tested LAMP methods could successfully detect K76T mutants of P. falciparum, however considering the time, safety, sensitivity, cost and simplicity, the malachite green and HNB based methods were found more efficient. Among four different visual dyes uses to detect LAMP products accurately, hydroxynaphthol blue and malachite green could produce long stable color change and brightness in a close tube-based approach to prevent cross-contamination risk. Our results indicated that the LAMP offers an interesting novel and convenient best method for the rapid, sensitive, cost-effective, and fairly user friendly tool for detection of K76T mutants of P. falciparum and therefore presents an alternative to PCR-based assays. Based on our comparative analysis, better field based LAMP visualization method can be chosen easily for the monitoring of other important drug targets (Kelch13 propeller region)., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: The primary high-risk human papillomavirus (hrHPV) assays in the United States are the cobas (Roche) and the Aptima (Hologic). The cobas assay detects hrHPV by DNA analysis while the Aptima detects messenger RNA (mRNA) oncogenic transcripts. As the Aptima assay identifies oncogenic expression, it should have a lower rate of hrHPV and genotype detection., Methods: The Kaiser Permanente Regional Reference Laboratory in Denver, Colorado changed its hrHPV assay from the cobas to the Aptima assay. The rates of hrHPV detection and genotyping were compared over successive six-month periods., Results: The overall hrHPV detection rates by the two platforms were similar (9.5% versus 9.1%) and not statistically different. For genotyping, the HPV 16 rate by the cobas was 1.6% and by the Aptima it was 1.1%. These differences were statistically different with the Aptima detecting nearly one-third less HPV 16 infections. With the HPV 18 and HPV 18/45, there was a slightly higher detection rate of HPV 18/45 by the Aptima platform (0.5% versus 0.9%) and this was statistically significant., Conclusion: While HPV 16 represents a low percentage of hrHPV infections, it was detected significantly less by the Aptima assay compared to the cobas assay. This has been previously reported, although not highlighted. Given the test methodologies, one would expect the Aptima to detect less HPV 16. This difference appears to be mainly due to a significantly increased number of non-oncogenic HPV 16 infections detected by the cobas test as there were no differences in HPV 16 detection rates in the high-grade squamous intraepithelial lesions indicating that the two tests have similar sensitivities for oncogenic HPV 16., (© 2018 Wiley Periodicals, Inc.)

Background: ATCC HIV-1 drug resistance test kit was designed to detect HIV-1 drug resistance (HIVDR) mutations in the protease and reverse transcriptase genes for all HIV-1 group M subtypes and circulating recombinant forms. The test has been validated for both plasma and dried blood spot specimen types with viral load (VL) of ≥1000 copies/ml. We performed an in-country assessment on the kit to determine the genotyping sensitivity and its accuracy in detecting HIVDR mutations using plasma samples stored under suboptimal conditions., Methods: Among 572 samples with VL ≥1000 copies/ml that had been genotyped by ViroSeq assay, 183 were randomly selected, including 85 successful genotyped and 98 unsuccessful genotyped samples. They were tested with ATCC kits following the manufacturer's instructions. Sequence identity and HIVDR patterns were analysed with Stanford University HIV Drug Resistance HIVdb program., Results: Of the 183 samples, 127 (69.4%) were successfully genotyped by either method. While ViroSeq system genotyped 85/183 (46.5%) with median VL of 32,971 (IQR: 11,150-96,506) copies/ml, ATCC genotyped 115/183 (62.8%) samples with median VL of 23,068 (IQR: 7,397-86,086) copies/ml. Of the 98 unsuccessful genotyped samples with ViroSeq assay, 42 (42.9%) samples with lower median VL of 13,906 (IQR: 6,122-72,329) copies/ml were successfully genotyped using ATCC. Sequence identity analysis revealed that the sequences generated by both methods were >98% identical and yielded similar HIVDR profiles at individual patient level., Conclusion: This study confirms that ATCC kit showed greater sensitivity in genotyping plasma samples stored in suboptimal conditions experiencing frequent and prolonged power outage. Thus, it is more sensitive particularly for subtypes A and A/G HIV-1 in resource-limited settings., Competing Interests: The authors have declared that no competing interests exist.

Objective: A simple, non-invasive sample collection method is key for the integration of pharmacogenetics into clinical practice. The aim of this study was to gain samples for pharmacogenetic testing and evaluate the variation between dry-flocked and sponge-tipped buccal swabs in yield and quality of DNA isolated., Results: Thirty-one participants collected samples using dry-flocked swabs and sponge-tipped swabs. Samples were assessed for DNA yield, quality and genotyping performance on a qPCR OpenArray platform of 28 pharmacogenetic SNPs and a CYP2D6 TaqMan copy number variant. DNA from sponge-tipped swabs had a significantly greater yield compared to DNA collected with dry-flocked swabs (p = 4.4 × 10 -7 ). Moreover, highest genotyping call rates across all assays and highest CNV confidence scores were observed in DNA samples collected from sponge-tipped swabs (97% vs. 54% dry-flocked swabs; 0.99 vs. 0.88 dry-flocked swabs, respectively). Sample collection using sponge-tipped swabs provides a DNA source of sufficient quantity and quality for pharmacogenetic variant detection using qPCR.

Genotyping-by-sequencing (GBS) potentially offers a cost-effective alternative for SNP discovery and genotyping. Here, we report the exploration of GBS in tetraploid potato. Both ApeKI and PstI/MspI enzymes were used for library preparation on eight diverse potato genotypes. ApeKI yielded more markers than PstI/MspI but provided a lower read coverage per marker, resulting in more missing data and limiting effective genotyping to the tetraploid mode. We then assessed the accuracy of these SNPs by comparison with SolCAP data (5824 data points in diploid mode and 3243 data points in tetraploid mode) and found the match rates between genotype calls was 90.4% and 81.3%, respectively. Imputation of missing data did not prove very accurate because of incomplete haplotype discovery, suggesting caution in setting the allowance for missing data. To further assess the quality of GBS-derived data, a genome-wide association analysis was performed for flower color on 318 clones (with ApeKI). A strong association signal on chromosome 2 was obtained with the most significant SNP located in the middle of the dihydroflavonol 4-reductase (DFR) gene. We conclude that an appropriate choice of enzyme for GBS library preparation makes it possible to obtain high-quality SNPs in potato and will be helpful for marker-assisted genomics.

Background: Accurate and internationally comparable human papillomavirus (HPV) DNA detection and typing services are essential for HPV vaccine research and surveillance., Objectives: This study assessed the proficiency of different HPV typing services offered routinely in laboratories worldwide., Study Design: The HPV Laboratory Network (LabNet) has designed international proficiency panels that can be regularly issued. The HPV genotyping proficiency panels of 2013 and 2014 contained 43 and 41 coded samples, respectively, composed of purified plasmids of sixteen HPV types (HPV 6, 11, 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68a and 68b) and 3 extraction controls. Proficient typing was defined as detection in both single and multiple infections of 50 International Units of HPV 16 and HPV 18 and 500 genome equivalents for the other 14 HPV types, with at least 97% specificity., Results: Ninety-six laboratories submitted 136 datasets in 2013 and 121 laboratories submitted 148 datasets in 2014. Thirty-four different HPV genotyping assays were used, notably Linear Array, HPV Direct Flow-chip, GenoFlow HPV array, Anyplex HPV 28, Inno-LiPa, and PGMY-CHUV assays. A trend towards increased sensitivity and specificity was observed. In 2013, 59 data sets (44%) were 100% proficient compared to 86 data sets (59%) in 2014. This is a definite improvement compared to the first proficiency panel, issued in 2008, when only 19 data sets (26%) were fully proficient., Conclusion: The regularly issued global proficiency program has documented an ongoing worldwide improvement in comparability and reliability of HPV genotyping services., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objectives: In a recent publication, we reported the successful use of tetra primer-amplification refractory mutation system based polymerase chain reaction (T-ARMS-PCR) for genotyping of rs445709131-SNP responsible for the bovine leukocyte adhesion deficiency (BLAD) in cattle. The SNP is characterized by higher GC content of the surrounding region, hence, the previous protocol utilized dimethyl sulfoxide as PCR enhancer. Here, the reaction cocktail was modified with the use of thermostable strand displacement polymerase (SD polymerase) instead of commonly used Taq DNA Polymerase. The amplification efficiency, reaction sensitivity, specificity, and need of PCR enhancer in reactions containing SD polymerase and Taq polymerase were compared., Results: T-ARMS-PCR assay is influenced by multiple factors for the correct genotyping necessitating extensive optimization at the initial stages. The described modification enabled generation of all amplicons by 25 cycles whereas the assay with Taq polymerase needed a minimum of 35 cycles. The modified assay amplified all amplicons at a wider range of annealing temperature (50-60 °C), without the addition of dimethyl sulfoxide. The replacement of Taq polymerase with SD polymerase may be beneficial in the T-ARMS assay for development of user-friendly, faster assay which is less affected by the reaction and cyclic conditions.

Background: Human rhinoviruses (RVs) are increasingly associated with severe disease of the respiratory tract. Multiple studies highlighted the clinical significance of different RV species; RV-C is linked to asthma exacerbations and increased disease severity in children, whereas RV-B seems to correlate with milder disease., Objectives: Current typing strategies for differentiation of RV species are time consuming and require extensive equipment. Here we present a novel genotyping tool to discriminate RV species A, B and C., Study Design: The method encompasses a VP4/VP2 polymerase chain reaction (PCR), followed by hybridization of the product on a macro array with probes covering RV-A, B, and C, produced by Chipron as custom array. Validation was performed with respiratory specimens submitted for diagnostic evaluation to the Academic Medical Center. A selection of RV PCR-positive samples genotyped based on VP4/VP2 sequencing was evaluated. Diagnostic performance was tested on respiratory samples positive for RV in an in-house multiplex respiratory PCR from January 2016 to January 2017. In-house primers and additional genotype-specific primers were used for sequencing to investigate array-negative and array-double-positive samples., Results: The majority of samples pretyped RVs (n = 135) were classified correctly, except for one that was assigned RV-C instead of RV-A, and 3 samples tested negative. The array gave four double-positive results; the presence of more than one genotype was confirmed in two samples. In 173/187 (92.5%) RV-positive tested patient samples from 2016, the test resulted in a designated species. RV species A was identified in 109 specimens (58.3%), RV-B in 26 (13.9%), and RV-C in 56 (29.9%) samples. Sequencing of the probe region of 14 (7.6%) negative samples revealed up to 3 mismatches to the probes for 12 samples; in 2 cases no PCR product was generated. Notably, in 18 samples the chip detected more than one species, of which 16 were confirmed by sequencing., Discussion: The Chipron LCD RV array provides a fast and highly sensitive method for discrimination between rhinovirus species, and has the power to detect dual infections., (Copyright © 2017. Published by Elsevier B.V.)

Background: Circulating tumour DNA (ctDNA) is considered to have a high potential for future management of malignancies. This pilot external quality assessment (EQA) scheme aimed to address issues of analytical quality in this new area of laboratory diagnostics., Methods: The EQA scheme consisted of three 2-mL EDTA-plasma samples spiked with fragmented genomic DNA with a mutant allele frequency ranging from 0% to 10% dedicated to the analysis of nine known sequence variations in KRAS codon 12/13 and of BRAF V600E. Laboratories reported: (1) time elapsed for processing, (2) storage temperatures, (3) methods for extraction and quantification, (4) genotyping methodologies and (5) results., Results: Specimens were sent to 42 laboratories from 10 European countries; 72.3% reported to isolate cell-free DNA (cfDNA) manually, 62.5% used the entire plasma volume for cfDNA isolation and 38.5% used >10% of cfDNA extracted for downstream genotyping. Of the methods used for quantification, PicoGreen demonstrated the lowest coefficient of variation (33.7%). For genotyping, 11 different methods were reported with the highest error rate observed for Sanger sequencing and the lowest for highly sensitive approaches like digital PCR. In total, 197 genotypes were determined with an overall error rate of 6.09%., Conclusions: This pilot EQA scheme illustrates the current variability in multiple phases of cfDNA processing and analysis of ctDNA resulting in an overall error rate of 6.09%. The areas with the greatest variance and clinical impact included specimen volume, cfDNA quantification method, and preference of genotyping platform. Regarding quality assurance, there is an urgent need for harmonisation of procedures and workflows.

The identification of the mutation causing Huntington's disease (HD) has led to the generation of a large number of mouse models. These models are used to further enhance our understanding of the mechanisms underlying the disease, as well as investigating and identifying therapeutic targets for this disorder. Here we review the transgenic, knock-in mice commonly used to model HD, as well those that have been generated to study specific disease mechanisms. We then provide a brief overview of the importance of standardizing the use of HD mice and describe brief protocols used for genotyping the mouse models used within the Bates Laboratory.

Evidence strongly indicates that extended RAS testing should be undertaken in mCRC patients, prior to prescribing anti-EGFR therapies. With more laboratories implementing testing, the requirement for External Quality Assurance schemes increases, thus ensuring high standards of molecular analysis. Data was analysed from 15 United Kingdom National External Quality Assessment Service (UK NEQAS) for Molecular Genetics Colorectal cancer external quality assurance (EQA) schemes, delivered between 2009 and 2016. Laboratories were provided annually with nine colorectal tumour samples for genotyping. Information on methodology and extent of testing coverage was requested, and scores given for genotyping, interpretation and clerical accuracy. There has been a sixfold increase in laboratory participation (18 in 2009 to 108 in 2016). For RAS genotyping, fewer laboratories now use Roche cobas®, pyrosequencing and Sanger sequencing, with more moving to next generation sequencing (NGS). NGS is the most commonly employed technology for BRAF and PIK3CA mutation screening. KRAS genotyping errors were seen in ≤10% laboratories, until the 2014-2015 scheme, when there was an increase to 16.7%, corresponding to a large increase in scheme participants. NRAS genotyping errors peaked at 25.6% in the first 2015-2016 scheme but subsequently dropped to below 5%. Interpretation and clerical accuracy scores have been consistently good throughout. Within this EQA scheme, we have observed that the quality of molecular analysis for colorectal cancer has continued to improve, despite changes in the required targets, the volume of testing and the technologies employed. It is reassuring to know that laboratories clearly recognise the importance of participating in EQA schemes.

High resolution melting analysis (HRMA) is a single-tube method, which can be carried out rapidly as an additional step following real-time quantitative PCR (qPCR). The method enables the differentiation of genetic variation (down to single nucleotide polymorphisms) in amplified DNA fragments without sequencing. HRMA has previously been adopted to determine variability in the amplified genes of a number of organisms. However, only one work to date has focused on pathogenic parasites-nematodes from the genus Trichinella. In this study, we employed a qPCR-HRMA assay specifically targeting two sequential gene fragments-cytochrome c oxidase subunit I (COI) and expansion segment V (ESV), in order to differentiate 37 single L1 muscle larvae samples of eight Trichinella species. We show that qPCR-HRMA based on the mitochondrial COI gene allows differentiation between the sequences of PCR products of the same length. This simple, rapid and reliable method can be used to identify at the species level single larvae of eight Trichinella taxa.

ABO genotyping is used in several disciplines, including transfusion, transplantation, human evolution, and forensic medicine. Detection of single nucleotide polymorphisms (SNPs) on a locus is a common way to identify different genotypes. In this study we developed a strategy for ABO genotyping, which can rapidly and efficiently detect SNPs. DNA fragments containing 4 SNPs in the ABO gene (c.261delG, c.297A > G, c.1009A > G, and c.1061delC) were amplified using individually and multiplexed polymerase chain reaction (PCR)-based methods and subsequently genotyped by high-resolution melting (HRM) analysis. Human blood ABO genotypes from 92 samples were successfully determined by HRM analysis. A total of 14 genotypes (A/A, A/O01, A/O02, A201/O01, A205/O01, B/B, B/O01, B/O02, A/B, A201/B, A205/B, O01/O01, O02/O02, O01/O02) were identified by analysis of the 4 SNPs of interest in this study. The results suggest that the present HRM assay is a reliable and rapid method for ABO blood type genotyping and it may offer an alternative to traditional genotyping methods., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background: Herpes Simplex Virus (HSV) drug resistance is a significant public health concern among immunocompromised individuals. Phenotypic assays are considered the gold standard method for detecting HSV drug resistance. However, plaque reduction assays (PRAs) are technically demanding, often with long turnaround times of up to four weeks. In contrast, genotypic tests can be performed within a few days., Objectives: The development and coordination of the first European External Quality Assessment (EQA) study to evaluate phenotypic and genotypic methods used for HSV drug resistance testing in specialised reference laboratories., Study Design: Four HSV-1 or HSV-2 strains with different antiviral susceptibility profiles were isolated from clinical samples. Isolates were quantified by qPCR, and aliquoted in culture medium. One isolate was distributed at two dilutions to help assess assay sensitivity. The panel was distributed to five European centres with a six-week deadline for the return of phenotypic and genotypic results, together with clinical reports., Results: Four out of five participating labs returned results by the deadline. Limited results were later available from the fifth lab. Phenotypic and genotypic data were largely, but not completely, concordant. An unusual resistance profile shown by one of the samples was explained by the detection of a mixed virus population after extensive further investigation by one of the centres., Conclusions: Discordant clinical outputs reflecting the diversity of phenotypic methodologies demonstrated the utility of this exercise. With emerging genotypic technologies looking to supplant phenotyping, there is a need for curated public databases, accessible interpretation tools and standardised control materials for quality management. By establishing a network of testing laboratories, we hope that this EQA scheme will facilitate ongoing progress in this area., (Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.)

The European Commision (EC) recently approved osimertinib for the treatment of adult patients with locally advanced or metastatic non-small-cell lung cancer (NSCLC) harboring EGFR T790M mutations. Besides tissue-based testing, blood samples containing cell-free circulating tumor DNA (ctDNA) can be used to interrogate T790M status. Herein, we describe the conditions and results of a round robin trial (RRT) for T790M mutation testing in NSCLC tissue specimens and peripheral blood samples spiked with cell line DNA mimicking tumor-derived ctDNA. The underlying objectives of this two-staged external quality assessment (EQA) approach were (a) to evaluate the accuracy of T790M mutations testing across multiple centers and (b) to investigate if a liquid biopsy-based testing for T790M mutations in spiked blood samples is feasible in routine diagnostic. Based on a successfully completed internal phase I RRT, an open RRT for EGFR T790M mutation testing in tumor tissue and blood samples was initiated. In total, 48 pathology centers participated in the EQA. Of these, 47 (97.9%) centers submitted their analyses within the pre-defined time frame and 44 (tissue), respectively, 40 (plasma) successfully passed the test. The overall success rates in the RRT phase II were 91.7% (tissue) and 83.3% (blood), respectively. Thirty-eight out of 48 participants (79.2%) successfully passed both parts of the RRT. The RRT for blood-based EGFR testing initiated in Germany is, to the best of our knowledge, the first of his kind in Europe. In summary, our results demonstrate that blood-based genotyping for EGFR resistance mutations can be successfully integrated in routine molecular diagnostics complementing the array of molecular methods already available at pathology centers in Germany.

Haplotype plays a vital role in diverse fields; however, the sequencing technologies cannot resolve haplotype directly. Pioneers demonstrated several approaches to resolve haplotype in the early years, which was extensively reviewed. Since then, numerous methods have been developed recently that have significantly improved phasing performance. Here, we review experimental methods that have emerged mainly over the past five years, and categorize them into five classes according to their maximum scale of contiguity: (i) encapsulation, (ii) 3D structure capture and construction, (iii) compartmentalization, (iv) fluorography, (v) long-read sequencing. Several subsections of certain methods are attached to each class as instances. We also discuss the relative advantages and disadvantages of different classes and make comparisons among representative methods of each class., Competing Interests: The authors declare no conflict of interest.

Inferring relatedness from genomic data is an essential component of genetic association studies, population genetics, forensics, and genealogy. While numerous methods exist for inferring relatedness, thorough evaluation of these approaches in real data has been lacking. Here, we report an assessment of 12 state-of-the-art pairwise relatedness inference methods using a data set with 2485 individuals contained in several large pedigrees that span up to six generations. We find that all methods have high accuracy (92-99%) when detecting first- and second-degree relationships, but their accuracy dwindles to <43% for seventh-degree relationships. However, most identical by descent (IBD) segment-based methods inferred seventh-degree relatives correct to within one relatedness degree for >76% of relative pairs. Overall, the most accurate methods are Estimation of Recent Shared Ancestry (ERSA) and approaches that compute total IBD sharing using the output from GERMLINE and Refined IBD to infer relatedness. Combining information from the most accurate methods provides little accuracy improvement, indicating that novel approaches, such as new methods that leverage relatedness signals from multiple samples, are needed to achieve a sizeable jump in performance., (Copyright © 2017 Ramstetter et al.)

Motivation: Principal component analysis (PCA) is a crucial step in quality control of genomic data and a common approach for understanding population genetic structure. With the advent of large genotyping studies involving hundreds of thousands of individuals, standard approaches are no longer feasible. However, when the full decomposition is not required, substantial computational savings can be made., Results: We present FlashPCA2, a tool that can perform partial PCA on 1 million individuals faster than competing approaches, while requiring substantially less memory., Availability and Implementation: https://github.com/gabraham/flashpca ., Contact: gad.abraham@unimelb.edu.au., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com)

Background: The WHO European Region (EUR) has adopted the goal of eliminating measles and rubella but individual countries perform differently in achieving this goal. Measles virus spread across the EUR by mobile groups has recently led to large outbreaks in the insufficiently vaccinated resident population. As an instrument for monitoring the elimination process and verifying the interruption of endemic virus transmission, molecular surveillance has to provide valid and representative data. Irrespective of the country's specific situation, it is required to ensure the functionality of the laboratory surveillance that is supported by the WHO Global Measles and Rubella Laboratory Network., Aims: To investigate whether the molecular surveillance in the EUR is adequate for the challenges in the elimination phase, we addressed the quality assurance of molecular data, the continuity and intensity of molecular monitoring, and the analysis of transmission chains., Sources: Published articles, the molecular External Quality Assessment Programme of the WHO, the Centralized Information System for Infectious Diseases of the WHO EUR and the WHO Measles and Rubella Nucleotide Surveillance databases served as information sources., Content: Molecular proficiency testing conducted by the WHO in 2016 has shown that the expertise for measles and rubella virus genotyping exists in all parts of the EUR. The analysis of surveillance data reported nationally to the WHO in 2013-2016 has revealed some countries with outbreaks but not sufficiently representative molecular data. Long-lasting supranational MV transmission chains were identified., Implications: A more systematic molecular monitoring and recording of the transmission pattern for the whole EUR could help to create a meaningful picture of the elimination process., (Copyright © 2017 European Society of Clinical Microbiology and Infectious Diseases. All rights reserved.)

Motivation: Accurate identification of genotypes is an essential part of the analysis of genomic data, including in identification of sequence polymorphisms, linking mutations with disease and determining mutation rates. Biological and technical processes that adversely affect genotyping include copy-number-variation, paralogous sequences, library preparation, sequencing error and reference-mapping biases, among others., Results: We modeled the read depth for all data as a mixture of Dirichlet-multinomial distributions, resulting in significant improvements over previously used models. In most cases the best model was comprised of two distributions. The major-component distribution is similar to a binomial distribution with low error and low reference bias. The minor-component distribution is overdispersed with higher error and reference bias. We also found that sites fitting the minor component are enriched for copy number variants and low complexity regions, which can produce erroneous genotype calls. By removing sites that do not fit the major component, we can improve the accuracy of genotype calls., Availability and Implementation: Methods and data files are available at https://github.com/CartwrightLab/WuEtAl2017/ (doi:10.5281/zenodo.256858)., Contact: cartwright@asu.edu., Supplementary Information: Supplementary data is available at Bioinformatics online., (© The Author(s) 2017. Published by Oxford University Press.)

Background: To date, genome-scale analyses in the domestic horse have been limited by suboptimal single nucleotide polymorphism (SNP) density and uneven genomic coverage of the current SNP genotyping arrays. The recent availability of whole genome sequences has created the opportunity to develop a next generation, high-density equine SNP array., Results: Using whole genome sequence from 153 individuals representing 24 distinct breeds collated by the equine genomics community, we cataloged over 23 million de novo discovered genetic variants. Leveraging genotype data from individuals with both whole genome sequence, and genotypes from lower-density, legacy SNP arrays, a subset of ~5 million high-quality, high-density array candidate SNPs were selected based on breed representation and uniform spacing across the genome. Considering probe design recommendations from a commercial vendor (Affymetrix, now Thermo Fisher Scientific) a set of ~2 million SNPs were selected for a next-generation high-density SNP chip (MNEc2M). Genotype data were generated using the MNEc2M array from a cohort of 332 horses from 20 breeds and a lower-density array, consisting of ~670 thousand SNPs (MNEc670k), was designed for genotype imputation., Conclusions: Here, we document the steps taken to design both the MNEc2M and MNEc670k arrays, report genomic and technical properties of these genotyping platforms, and demonstrate the imputation capabilities of these tools for the domestic horse.

Genetic sequencing ("genotyping") plays a critical role in the modern clinical management of HIV infection. This virus evolves rapidly within patients because of its error-prone reverse transcriptase and short generation time. Consequently, HIV variants with mutations that confer resistance to one or more antiretroviral drugs can emerge during sub-optimal treatment. There are now multiple HIV drug resistance interpretation algorithms that take the region of the HIV genome encoding the major drug targets as inputs; expert use of these algorithms can significantly improve to clinical outcomes in HIV treatment. Next-generation sequencing has the potential to revolutionize HIV resistance genotyping by lowering the threshold that rare but clinically significant HIV variants can be detected reproducibly, and by conferring improved cost-effectiveness in high-throughput scenarios. In this review, we discuss the relative merits and challenges of deploying the Illumina MiSeq instrument for clinical HIV genotyping., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Epidermal growth factor receptor (EGFR) mutations have been used as the strongest predictor of effectiveness of treatment with EGFR tyrosine kinase inhibitors (TKIs). Three most common EGFR mutations (L858R, exon 19 deletion, and T790M) are known to be major selection markers for EGFR-TKIs therapy. Here, we developed a multiplex picodroplet digital PCR (ddPCR) assay to detect 3 common EGFR mutations in 1 reaction. Serial-dilution experiments with genomic DNA harboring EGFR mutations revealed linear performance, with analytical sensitivity ~0.01% for each mutation. All 33 EGFR-activating mutations detected in formalin-fixed paraffin-embedded (FFPE) tissue samples by the conventional method were also detected by this multiplex assay. Owing to the higher sensitivity, an additional mutation (T790M; including an ultra-low-level mutation, <0.1%) was detected in the same reaction. Regression analysis of the duplex assay and multiplex assay showed a correlation coefficient (R 2 ) of 0.9986 for L858R, 0.9844 for an exon 19 deletion, and 0.9959 for T790M. Using ddPCR, we designed a multiplex ultrasensitive genotyping platform for 3 common EGFR mutations. Results of this proof-of-principle study on clinical samples indicate clinical utility of multiplex ddPCR for screening for multiple EGFR mutations concurrently with an ultra-rare pretreatment mutation (T790M)., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

Motivation: Large genomic datasets combining genotype and sequence data, such as for expression quantitative trait loci (eQTL) detection, require perfect matching between both data types., Results: We described here MBV (Match BAM to VCF); a method to quickly solve sample mislabeling and detect cross-sample contamination and PCR amplification bias., Availability and Implementation: MBV is implemented in C ++ as an independent component of the QTLtools software package, the binary and source codes are freely available at https://qtltools.github.io/qtltools/ ., Contact: olivier.delaneau@unige.ch or emmanouil.dermitzakis@unige.ch., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com)

Standardization of the methods for extraction of DNA from sand flies is essential for obtaining high efficiency during subsequent molecular analyses, such as the new sequencing methods. Information obtained using these methods may contribute substantially to taxonomic, evolutionary, and eco-epidemiological studies. The aim of the present study was to standardize and compare two methods for the extraction of genomic DNA from sand flies for obtaining DNA in sufficient quantities for next-generation sequencing. Sand flies were collected from the municipalities of Campo Grande, Camapuã, Corumbá and Miranda, state of Mato Grosso do Sul, Brazil. Three protocols using a silica column-based commercial kit (ReliaPrep™ Blood gDNA Miniprep System kit, Promega ® ), and three protocols based on the classical phenol-chloroform extraction method (Uliana et al., 1991), were compared with respect to the yield and quality of the extracted DNA. DNA was quantified using a Qubit 2.0 fluorometer. The presence of sand fly DNA was confirmed by PCR amplification of the IVS6 region (constitutive gene), followed by electrophoresis on a 1.5% agarose gel. A total of 144 male specimens were analyzed, 72 per method. Significant differences were observed between the two methods tested. Protocols 2 and 3 of phenol-chloroform extraction presented significantly better performance than all commercial kit extraction protocols tested. For phenol-chloroform extraction, protocol 3 presented significantly better performance than protocols 1 and 2. The IVS6 region was detected in 70 of 72 (97.22%) samples extracted with phenol, including all samples for protocols 2 and 3. This is the first study on the standardization of methods for the extraction of DNA from sand flies for application to next-generation sequencing, which is a promising tool for entomological and molecular studies of sand flies., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Selecting and validating reference genes are the first steps in studying gene expression by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR). The present study aimed to evaluate the stability of five reference genes for the purpose of normalization when studying gene expression in various cultivars of Prunus persica with different chilling requirements. Flower bud tissues of nine peach genotypes from Embrapa's peach breeding program with different chilling requirements were used, and five candidate reference genes based on the RT-qPCR that were useful for studying the relative quantitative gene expression and stability were evaluated using geNorm, NormFinder, and bestKeeper software packages. The results indicated that among the genes tested, the most stable genes to be used as reference genes are Act and UBQ10. This study is the first survey of the stability of reference genes in peaches under chilling stress and provides guidelines for more accurate RT-qPCR results.

Background: This paper describes a method, called AlphaSeqOpt, for the allocation of sequencing resources in livestock populations with existing phased genomic data to maximise the ability to phase and impute sequenced haplotypes into the whole population., Methods: We present two algorithms. The first selects focal individuals that collectively represent the maximum possible portion of the haplotype diversity in the population. The second allocates a fixed sequencing budget among the families of focal individuals to enable phasing of their haplotypes at the sequence level. We tested the performance of the two algorithms in simulated pedigrees. For each pedigree, we evaluated the proportion of population haplotypes that are carried by the focal individuals and compared our results to a variant of the widely-used key ancestors approach and to two haplotype-based approaches. We calculated the expected phasing accuracy of the haplotypes of a focal individual at the sequence level given the proportion of the fixed sequencing budget allocated to its family., Results: AlphaSeqOpt maximises the ability to capture and phase the most frequent haplotypes in a population in three ways. First, it selects focal individuals that collectively represent a larger portion of the population haplotype diversity than existing methods. Second, it selects focal individuals from across the pedigree whose haplotypes can be easily phased using family-based phasing and imputation algorithms, thus maximises the ability to impute sequence into the rest of the population. Third, it allocates more of the fixed sequencing budget to focal individuals whose haplotypes are more frequent in the population than to focal individuals whose haplotypes are less frequent. Unlike existing methods, we additionally present an algorithm to allocate part of the sequencing budget to the families (i.e. immediate ancestors) of focal individuals to ensure that their haplotypes can be phased at the sequence level, which is essential for enabling and maximising subsequent sequence imputation., Conclusions: We present a new method for the allocation of a fixed sequencing budget to focal individuals and their families such that the final sequenced haplotypes, when phased at the sequence level, represent the maximum possible portion of the haplotype diversity in the population that can be sequenced and phased at that budget.

Single nucleotide polymorphisms (SNPs) carried in calpain (CAPN1), calpastatin (CAST), and leptin (LEP) genes are associated with meat tenderness. Due to the economic importance of this meat quality attribute, the development of fast, reliable, and affordable methods to identify bovine carriers of favorable alleles is of great importance for genetic improvement. Currently, PCR-RFLP is accepted as the standard gold method for genotyping SNPs associated with meat tenderness. But these SNPs can be detected by other techniques as high-resolution melting (HRM) analysis - a post-PCR method - that offers several advantages and has great application potential in the meat industry. In this study, we standardized, validated, and compared the performance of PCR-HRM to that of PCR-RFLP in genotyping bovine SNPs associated with meat tenderness: CAPN4751, CAPN316, CAST2959, CAST282, LEPE2FB, and LEPE2JW. We analyzed genotypes of a total of 380 bovines, 110 Bos taurus and 270 Bos indicus. Results obtained with PCR-HRM were consistent with those found by PCR-RLFP. Furthermore, HRM was found to be highly sensitive, and our results confirmed the repeatability (intra-assay precision) and reproducibility (inter-assay precision) of this assay. An internal control for endonuclease activity was created using site-directed mutagenesis to generate an additional enzymatic restriction point useful to discriminate SNP alleles. Our results show that PCR-HRM is an efficient method that produces reliable and rapid results. However, should be had in account that the method of DNA extraction, the quality and quantity of DNA, analyst-related variations, and primer design may generate challenges for allele discrimination.

Background: Haplotype reconstruction (phasing) is an essential step in many applications, including imputation and genomic selection. The best phasing methods rely on both familial and linkage disequilibrium (LD) information. With whole-genome sequence (WGS) data, relatively small samples of reference individuals are generally sequenced due to prohibitive sequencing costs, thus only a limited amount of familial information is available. However, reference individuals have many relatives that have been genotyped (at lower density). The goal of our study was to improve phasing of WGS data by integrating familial information from haplotypes that were obtained from a larger genotyped dataset and to quantify its impact on imputation accuracy., Results: Aligning a pre-phased WGS panel [~5 million single nucleotide polymorphisms (SNPs)], which is based on LD information only, to a 50k SNP array that is phased with both LD and familial information (called scaffold) resulted in correctly assigning parental origin for 99.62% of the WGS SNPs, their phase being determined unambiguously based on parental genotypes. Without using the 50k haplotypes as scaffold, that value dropped as expected to 50%. Correctly phased segments were on average longer after alignment to the genotype phase while the number of switches decreased slightly. Most of the incorrectly assigned segments, and subsequent switches, were due to singleton errors. Imputation from 50k SNP array to WGS data with improved phasing had a marginal impact on imputation accuracy (measured as r 2 ), i.e. on average, 90.47% with traditional techniques versus 90.65% with pre-phasing integrating familial information. Differences were larger for SNPs located in chromosome ends and rare variants. Using a denser WGS panel (~13 millions SNPs) that was obtained with traditional variant filtering rules, we found similar results although performances of both phasing and imputation accuracy were lower., Conclusions: We present a phasing strategy for WGS data, which indirectly integrates familial information by aligning WGS haplotypes that are pre-phased with LD information only on haplotypes obtained with genotyping data, with both LD and familial information and on a much larger population. This strategy results in very few mismatches with the phase obtained by Mendelian segregation rules. Finally, we propose a strategy to further improve phasing accuracy based on haplotype clusters obtained with genotyping data.

Hundreds of thousands of individuals have been genotyped in the past decades using genotyping arrays, representing both a valuable data resource for future biomedical research and a substantial investment in human genetic research. However, novel chip designs and their altered sets of single-nucleotide polymorphisms (SNPs) pose the question of how well established data resources, such as large samples of healthy controls genotyped on legacy arrays, can be combined with newer samples genotyped on those novel arrays using genotype imputation. We exemplarily investigated this question based on genotype data of 30 European and 30 African unrelated samples from the 1000 Genomes project and on markers present on two legacy SNP arrays, namely Affymetrix's Human SNP 6.0 and Illumina's 550k array, and three newer arrays, namely two Axiom arrays from Affymetrix and an OmniExpress array from Illumina. We cross-compared the imputation accuracy as well as efficacy and assessed genotype concordance among these arrays. Although the accuracy of genotype prediction was uniformly high across all arrays, the imputation efficacy, that is, the proportion of successfully imputed markers, differed considerably between array combinations in both sample sets, with legacy arrays showing a trend towards lower efficacy values compared with newer arrays when serving as imputation basis. We conclude that, given the substantial losses of markers covered by the legacy arrays, the re-genotyping of existing samples sets, in particular those of healthy population controls, would be a worthwhile endeavor to secure their continued use in the future.

Background: Genomic prediction using high-density (HD) marker genotypes is expected to lead to higher prediction accuracy, particularly for more heterogeneous multi-breed and crossbred populations such as those in sheep and beef cattle, due to providing stronger linkage disequilibrium between single nucleotide polymorphisms and quantitative trait loci controlling a trait. The objective of this study was to evaluate a possible improvement in genomic prediction accuracy of production traits in Australian sheep breeds based on HD genotypes (600k, both observed and imputed) compared to prediction based on 50k marker genotypes. In particular, we compared improvement in prediction accuracy of animals that are more distantly related to the reference population and across sheep breeds., Methods: Genomic best linear unbiased prediction (GBLUP) and a Bayesian approach (BayesR) were used as prediction methods using whole or subsets of a large multi-breed/crossbred sheep reference set. Empirical prediction accuracy was evaluated for purebred Merino, Border Leicester, Poll Dorset and White Suffolk sire breeds according to the Pearson correlation coefficient between genomic estimated breeding values and breeding values estimated based on a progeny test in a separate dataset., Results: Results showed a small absolute improvement (0.0 to 8.0% and on average 2.2% across all traits) in prediction accuracy of purebred animals from HD genotypes when prediction was based on the whole dataset. Greater improvement in prediction accuracy (1.0 to 12.0% and on average 5.2%) was observed for animals that were genetically lowly related to the reference set while it ranged from 0.0 to 5.0% for across-breed prediction. On average, no significant advantage was observed with BayesR compared to GBLUP.

Motivation: Variant calling from next-generation sequencing (NGS) data is susceptible to false positive calls due to sequencing, mapping and other errors. To better distinguish true from false positive calls, we present a method that uses genotype array data from the sequenced samples, rather than public data such as HapMap or dbSNP, to train an accurate classifier using Random Forests. We demonstrate our method on a set of variant calls obtained from 642 African-ancestry genomes from the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA), sequenced to high depth (30X)., Results: We have applied our classifier to compare call sets generated with different calling methods, including both single-sample and multi-sample callers. At a False Positive Rate of 5%, our method determines true positive rates of 97.5%, 95% and 99% on variant calls obtained using Illuminas single-sample caller CASAVA, Real Time Genomics multisample variant caller, and the GATK UnifiedGenotyper, respectively. Since NGS sequencing data may be accompanied by genotype data for the same samples, either collected concurrent to sequencing or from a previous study, our method can be trained on each dataset to provide a more accurate computational validation of site calls compared to generic methods. Moreover, our method allows for adjustment based on allele frequency (e.g. a different set of criteria to determine quality for rare versus common variants) and thereby provides insight into sequencing characteristics that indicate call quality for variants of different frequencies., Availability and Implementation: Code is available on Github at: https://github.com/suyashss/variant&#95;validation., Contacts: suyashs@stanford.edu or mtaub@jhsph.edu., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2016. Published by Oxford University Press.)

Background: The number of teats in pigs is related to a sow's ability to rear piglets to weaning age. Several studies have identified genes and genomic regions that affect teat number in swine but few common results were reported. The objective of this study was to identify genetic factors that affect teat number in pigs, evaluate the accuracy of genomic prediction, and evaluate the contribution of significant genes and genomic regions to genomic broad-sense heritability and prediction accuracy using 41,108 autosomal single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing on 2936 Duroc boars., Results: Narrow-sense heritability and dominance heritability of teat number estimated by genomic restricted maximum likelihood were 0.365 ± 0.030 and 0.035 ± 0.019, respectively. The accuracy of genomic predictions, calculated as the average correlation between the genomic best linear unbiased prediction and phenotype in a tenfold validation study, was 0.437 ± 0.064 for the model with additive and dominance effects and 0.435 ± 0.064 for the model with additive effects only. Genome-wide association studies (GWAS) using three methods of analysis identified 85 significant SNP effects for teat number on chromosomes 1, 6, 7, 10, 11, 12 and 14. The region between 102.9 and 106.0 Mb on chromosome 7, which was reported in several studies, had the most significant SNP effects in or near the PTGR2, FAM161B, LIN52, VRTN, FCF1, AREL1 and LRRC74A genes. This region accounted for 10.0% of the genomic additive heritability and 8.0% of the accuracy of prediction. The second most significant chromosome region not reported by previous GWAS was the region between 77.7 and 79.7 Mb on chromosome 11, where SNPs in the FGF14 gene had the most significant effect and accounted for 5.1% of the genomic additive heritability and 5.2% of the accuracy of prediction. The 85 significant SNPs accounted for 28.5 to 28.8% of the genomic additive heritability and 35.8 to 36.8% of the accuracy of prediction., Conclusions: The three methods used for the GWAS identified 85 significant SNPs with additive effects on teat number, including SNPs in a previously reported chromosomal region and SNPs in novel chromosomal regions. Most significant SNPs with larger estimated effects also had larger contributions to the total genomic heritability and accuracy of prediction than other SNPs.

Accurate human leukocyte antigen (HLA) genotyping is critical in studies involving the immune system. Several algorithms to estimate HLA genotypes from whole-exome data were developed. We compared the accuracy of seven algorithms, including Optitype, Polysolver and PHLAT, as well as investigated patterns and possible causes of miscalls using 12 clinical samples and 961 individuals from the 1000 Genomes Project. Optitype showed the highest accuracy of 97.2% for HLA class I alleles at the second field resolution, followed by 94.0% in Polysolver and 85.6% in PHLAT. In Optitype, 34 (21.1%) of 161 miscalls were across different serological types, and common miscalls were HLA-A*26:01 to HLA-A*25:01, HLA-B*45:01 to HLA-B*44:15 and HLA-C*08:02 to HLA-C*05:01 with error rates of 4.1%, 10.0% and 4.1%, respectively. In Polysolver, 193 (55.9%) of 345 miscalls occurred across different serological alleles, and a specific pattern of genotyping error from HLA-A*25:01 to HLA-A*26:01 was observed in 93.3% of HLA-A*25:01 carriers, due to dropping of HLA-A*25:01 sequence reads during the extraction process of HLA reads. In PHLAT, 147 (59.8%) of 246 miscalls in HLA-A were due to erroneous assignment of multiple alleles to either HLA-A*01:22 or HLA-A*01:81. These results suggest that careful considerations needed to be taken when using exome-based HLA class I genotyping data and applying these results in clinical settings.

The rpoB gene codes for the RNA polymerase β subunit, which is the target of rifampicin, an essential drug in the treatment of tuberculosis and other mycobacterial infections. This gene is present in all bacteria, but its length and nucleotide sequence vary between bacterial species, including mycobacteria. Mutations in the rpoB gene alter the structure of this protein and cause drug resistance. To describe the resistance-associated mutations, the scientific and medical communities have been using, since 1993, a numbering system based on the Escherichia coli sequence annotation. Using E. coli reference for describing mutations in mycobacteria leads to misunderstandings, particularly with the increasing use of whole genome sequencing, which brought an alternative numbering system based on the Mycobacterium tuberculosis rpoB sequence. We propose using a consensus numbering system for the reporting of resistance mutations based on the reference genomes from the species interrogated (such as strain H37Rv for M. tuberculosis). This manuscript provides the necessary figures and tables allowing researchers, microbiologists and clinicians to easily convert other annotation systems into one common language., (Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Tumor tissues were potential resources in cancer susceptibility studies. To assess the genotyping concordance between tumor tissues and peripheral blood, we conducted this study in a large sample size and genome-wide scale. Genome-wide genotypes of human colon adenocarcinoma (COAD) retrieved from The Cancer Genome Atlas (TCGA) was analyzed. A total of 387 pairs of matched fresh frozen tumor tissues and peripheral blood samples passed the quality control processes. High concordant rate (94.85% with no-calls and 97.89% without no-calls) was found between tumor tissues and peripheral blood. The discordant rate raised with the increase of heterozygote rate, and the tendency was statistically significant. The total missing rate was 3.10%. We also verified 14 susceptibility SNPs and the average genotyping concordant rate was 97.42%. These findings suggest that majority of SNPs could be accurately genotyped using DNA isolated from tumor tissues., (Copyright © 2017 Elsevier Inc. All rights reserved.)

CE equipment detects and deconvolutes mixtures containing up to six fluorescently labeled DNA fragments. This deconvolution is done by the collection software that requires a spectral calibration file. The calibration file is used to adjust for the overlap that occurs between the emission spectra of fluorescence dyes. All commercial genotyping and sequencing kits require the installation of a corresponding matrix standard to generate a calibration file. Due to the differences in emission spectrum overlap between fluorescent dyes, the application of existing commercial matrix standards to the electrophoretic separation of DNA labeled with other fluorescent dyes can yield undesirable results. Currently, the number of fluorescent dyes available for oligonucleotide labeling surpasses the availability of commercial matrix standards. Therefore, in this study we developed and evaluated a customized matrix standard using ATTO 633, ATTO 565, ATTO 550, ATTO Rho6G, and 6-FAM dyes for which no commercial matrix standard is available. We highlighted the potential genotyping errors of using an incorrect matrix standard by evaluating the relative performance of our custom dye set using six matrix standards. The specific performance of two genotyping kits (UniQTyper™ Y-10 version 1.0 and PowerPlex® Y23 System) was also evaluated using their specific matrix standards. The procedure we followed for the construction of our custom dye matrix standard can be extended to other fluorescent dyes., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Background: DNA-based predictions for hard-to-measure production traits hold great promise for selective breeding programs. DNA pooling might provide a cheap genomic approach to use phenotype data from commercial flocks which are commonly group-mated with parentage unknown. This study on sheep explores if genomic breeding values for stud sires can be estimated from genomic relationships that were obtained from pooled DNA in combination with phenotypes from commercial progeny., Methods: Phenotypes used in this study were categorical data. Blood was pooled strategically aiming at even pool sizes and within sex and phenotype category. A hybrid genomic relationship matrix was constructed relating pools to sires. This matrix was used to determine the contribution of sires to each of the pools and therefore phenotype category by using a simple regression approach. Genomic breeding values were also estimated using the hybrid genomic relationship matrix., Results: We demonstrated that, using pooled DNA, the genetic performance of sires can be illustrated as their contribution to phenotype categories and can be expressed as a regression coefficient. Genomic estimated breeding values for sires were equivalent to the regression coefficients and are a commonly used industry tool., Conclusions: Genotyping of DNA from pooled biological samples offers a cheap method to link phenotypic information from commercial production animals to the breeding population and can be turned into information on the genetic value of stud sires for traits that cannot be measured in the stud environment.

As an example of optimizing population-specific genotyping assays using a whole-genome sequence reference set, we detail the approach that followed to design the Axiom-NL array which is characterized by an improved imputation backbone based on the Genome of the Netherlands (GoNL) reference sequence and, compared with earlier arrays, a more comprehensive inclusion of SNPs on chromosomes X, Y, and the mitochondria. Common variants on the array were selected to be compatible with the Illumina Psych Array and the Affymetrix UK Biobank Axiom array. About 3.5% of the array (23 977 markers) represents SNPs from the GWAS catalog, including SNPs at FTO, APOE, Ion-channels, killer-cell immunoglobulin-like receptors, and HLA. Around 26 000 markers associated with common psychiatric disorders are included, as well as 6705 markers suggested to be associated with fertility and twinning. The platform can thus be used for risk profiling, detection of new variants, as well as ancestry determination. Results of coverage tests in 249 unrelated subjects with GoNL-based sequence data show that after imputation with 1000G as a reference, the median concordance between original and imputed genotypes is above 98%. The median imputation quality R 2 for MAF thresholds of 0.001, 0.01, 0.05, and >0.05 are 0.05, 0.28, 0.80, 0.99, respectively, for the 1000G imputed SNPs, with a similar quality for the autosomes and X chromosome, showing a good genome-wide coverage for association studies after imputation.

We report our results of 1000 diagnostic WES cases based on 2819 sequenced samples from 54 countries with a wide phenotypic spectrum. Clinical information given by the requesting physicians was translated to HPO terms. WES processes were performed according to standardized settings. We identified the underlying pathogenic or likely pathogenic variants in 307 families (30.7%). In further 253 families (25.3%) a variant of unknown significance, possibly explaining the clinical symptoms of the index patient was identified. WES enabled timely diagnosing of genetic diseases, validation of causality of specific genetic disorders of PTPN23, KCTD3, SCN3A, PPOX, FRMPD4, and SCN1B, and setting dual diagnoses by detecting two causative variants in distinct genes in the same patient. We observed a better diagnostic yield in consanguineous families, in severe and in syndromic phenotypes. Our results suggest that WES has a better yield in patients that present with several symptoms, rather than an isolated abnormality. We also validate the clinical benefit of WES as an effective diagnostic tool, particularly in nonspecific or heterogeneous phenotypes. We recommend WES as a first-line diagnostic in all cases without a clear differential diagnosis, to facilitate personal medical care., Competing Interests: DT, AMBA, MERW, JK, KKK, AM, OP, MCdC, CB, KW, RS, JMGA, OB, SK, NN, MW, RAJ are employed at Centogene AG; AR has financial holdings in Centogene AG; WE, MTAR, AAR, WAT, AAlo, MAB, and MA are employees at King Abdulaziz Medical city; AAlh is employee at Prince Sultan Military Medical City; NAS is employee at Johns Hopkins Aramco hospital.

Objective: Prompt genotyping of Mycobacterium tuberculosis (M. tuberculosis) is crucial for improving molecular epidemiological investigation of tuberculosis (TB)., Methods: We performed a retrospective study to evaluate the use of 24 loci MIRU-VNTR (mycobacterial interspersed repetitive unit-variable number of tandem-repeat) directly on 135 clinical samples from 84 TB patients., Results: There was a direct correlation between genotyping on clinical samples by MIRU-VNTR and bacterial load (P = 0.001). VNTR loci were amplified successfully for 41.5% of the clinical samples (19-24 loci), 32.6% (13-18 loci), 23.7% (7-12 loci) and 2.2% (1-6 loci). Loci of 2401, 577, 2996 and 154 had the highest power to show the mixed strains infection in clinical samples., Conclusions: Direct MIRU-VNTR is partially successful in complete genotyping of M. tuberculosis strains. On the other hand, detection of polyclonal infection is undoubtedly reliable based on the direct MIRU-VNTR., (Copyright © 2016 Elsevier Ltd. All rights reserved.)