Standardization and quality management in next-generation sequencing

Biostatistical Aspects of Whole Genome Sequencing Studies: Preprocessing and Quality Control

Rapid advances in high-throughput DNA sequencing technologies have enabled large-scale whole genome sequencing (WGS) studies. Before performing association analysis between phenotypes and genotypes, preprocessing and quality control (QC) of the raw sequence data need to be performed. Because many biostatisticians have not been working with WGS data so far, we first sketch Illumina's short-read sequencing technology. Second, we explain the general preprocessing pipeline for WGS studies. Third, we provide an overview of important QC metrics, which are applied to WGS data: on the raw data, after mapping and alignment, after variant calling, and after multisample variant calling. Fourth, we illustrate the QC with the data from the GENEtic SequencIng Study Hamburg-Davos (GENESIS-HD), a study involving more than 9000 human whole genomes. All samples were sequenced on an Illumina NovaSeq 6000 with an average coverage of 35× using a PCR-free protocol. For QC, one genome in a bottle (GIAB) trio was sequenced in four replicates, and one GIAB sample was successfully sequenced 70 times in different runs. Fifth, we provide empirical data on the compression of raw data using the DRAGEN original read archive (ORA). The most important quality metrics in the application were genetic similarity, sample cross-contamination, deviations from the expected Het/Hom ratio, relatedness, and coverage. The compression ratio of the raw files using DRAGEN ORA was 5.6:1, and compression time was linear by genome coverage. In summary, the preprocessing, joint calling, and QC of large WGS studies are feasible within a reasonable time, and efficient QC procedures are readily available.

Recommendations for reporting tissue and circulating tumour (ct)DNA next-generation sequencing results in non-small cell lung cancer

Non-small cell lung cancer is a heterogeneous disease and molecular characterisation plays an important role in its clinical management. Next-generation sequencing-based panel testing enables many molecular alterations to be interrogated simultaneously, allowing for comprehensive identification of actionable oncogenic drivers (and co-mutations) and appropriate matching of patients with targeted therapies. Despite consensus in international guidelines on the importance of broad molecular profiling, adoption of next-generation sequencing varies globally. One of the barriers to its successful implementation is a lack of accepted standards and guidelines specifically for the reporting and clinical annotation of next-generation sequencing results. Based on roundtable discussions between pathologists and oncologists, we provide best practice recommendations for the reporting of next-generation sequencing results in non-small cell lung cancer to facilitate its use and enable easy interpretation for physicians. These are intended to complement existing guidelines related to the use of next-generation sequencing (solid and liquid). Here, we discuss next-generation sequencing workflows, the structure of next-generation sequencing reports, and our recommendations for best practice thereof. The aim of these recommendations and considerations is ultimately to ensure that reports are fully interpretable, and that the most appropriate treatment options are selected based on robust molecular profiles in well-defined reports.

Assessment of the Impact of Preanalytical DNA Integrity on the Genome Data Quality

Many molecular approaches have been employed for the quality control (QC) of biobanked DNA samples. Since 2003, the National Biobank of Korea (NBK) has provided various studies with over half a million quality-controlled genomic DNA samples using conventional agarose gel electrophoresis and spectrophotometry. We assessed the postanalytical genomic data quality of DNA samples (n = 41) with a different range of the DNA quality index such as genomic quality number (GQN) for developing an evidence-based best practice for DNA quality criteria. We examined the quality indices of three different platforms, including single nucleotide polymorphism arrays, methylation arrays, and next-generation sequencing, using the same DNA samples (n = 41) of different quality, ranging from 4.0 to 10.0 values of the GQN. Our data analysis revealed that higher GQN value and/or double-stranded DNA concentration resulted in higher quality genomic data. In addition, all the analyzed DNA samples successfully generated good-quality genomic data. This study provides a guide for the QC of biobanked DNA samples for genomic analysis platforms.

An assessment of AcquireX and Compound Discoverer software 3.3 for non-targeted metabolomics

We used the Exploris 240 mass spectrometer for non-targeted metabolomics on Saccharomyces cerevisiae strain BY4741 and tested AcquireX software for increasing the number of detectable compounds and Compound Discoverer 3.3 software for identifying compounds by MS2 spectral library matching. AcquireX increased the number of potentially identifiable compounds by 50% through six iterations of MS2 acquisition. On the basis of high-scoring MS2 matches made by Compound Discoverer, there were 483 compounds putatively identified from nearly 8000 candidate spectra. Comparisons to 20 amino acid standards, however, revealed instances whereby compound matches could be incorrect despite strong scores. Situations included the candidate with the top score not being the correct compound, matching the same compound at two different chromatographic peaks, assigning the highest score to a library compound much heavier than the mass for the parent ion, and grouping MS2 isomers to a single parent ion. Because the software does not calculate false positive and false discovery rates at these multiple levels where such errors can propagate, we conclude that manual examination of findings will be required post software analysis. These results will interest scientists who may use this platform for metabolomics research in diverse disciplines including medical science, environmental science, and agriculture.

Operationalizing Quality Assurance for Clinical Illumina Somatic Next-Generation Sequencing Pipelines

Quality assurance (QA) is essential for precision oncology workflows, in particular in the clinical setting. However, because of numerous variations in laboratory and bioinformatics pipelines, QA practices remain non-standardized, are often ad hoc, and are lacking longitudinal tracking. A selected review of existing software was performed for quality control of Illumina next-generation sequencing data, focusing specifically on generalizable tools that can be integrated into any bioinformatics workflow to easily develop a QA workflow with longitudinal tracking. Although all implementations need to be integrated, validated, and iterated upon to suit individual operations, providing a base suite of options will enable better validation and use of QA in clinical somatic mutation testing for workflows using Illumina next-generation sequencing and beyond.

Recent Advances and Techniques for Identifying Novel Antibacterial Targets

BACKGROUND

With the emergence of drug-resistant bacteria, the development of new antibiotics is urgently required. Target-based drug discovery is the most frequently employed approach for the drug development process. However, traditional drug target identification techniques are costly and time-consuming. As research continues, innovative approaches for antibacterial target identification have been developed which enabled us to discover drug targets more easily and quickly.

METHODS

In this review, methods for finding drug targets from omics databases have been discussed in detail including principles, procedures, advantages, and potential limitations. The role of phage-driven and bacterial cytological profiling approaches is also discussed. Moreover, current article demonstrates the advancements being made in the establishment of computational tools, machine learning algorithms, and databases for antibacterial target identification.

RESULTS

Bacterial drug targets successfully identified by employing these aforementioned techniques are described as well.

CONCLUSION

The goal of this review is to attract the interest of synthetic chemists, biologists, and computational researchers to discuss and improve these methods for easier and quicker development of new drugs.

Cancer treatment comes to age: from one-size-fits-all to next-generation sequencing (NGS) technologies

Cancer is one of the leading causes of death worldwide and one of the greatest challenges in extending life expectancy. The paradigm of one-size-fits-all medicine has already given way to the stratification of patients by disease subtypes, clinical characteristics, and biomarkers (stratified medicine). The introduction of next-generation sequencing (NGS) in clinical oncology has made it possible to tailor cancer patient therapy to their molecular profiles. NGS is expected to lead the transition to precision medicine (PM), where the right therapeutic approach is chosen for each patient based on their characteristics and mutations. Here, we highlight how the NGS technology facilitates cancer treatment. In this regard, first, precision medicine and NGS technology are reviewed, and then, the NGS revolution in precision medicine is described. In the sequel, the role of NGS in oncology and the existing limitations are discussed. The available databases and bioinformatics tools and online servers used in NGS data analysis are also reviewed. The review ends with concluding remarks.

A comprehensive assessment of exome capture methods for RNA sequencing of formalin-fixed and paraffin-embedded samples

RNA-Seq analysis of Formalin-Fixed and Paraffin-Embedded (FFPE) samples has emerged as a highly effective approach and is increasingly being used in clinical research and drug development. However, the processing and storage of FFPE samples are known to cause extensive degradation of RNAs, which limits the discovery of gene expression or gene fusion-based biomarkers using RNA sequencing, particularly methods reliant on Poly(A) enrichment. Recently, researchers have developed an exome targeted RNA-Seq methodology that utilizes biotinylated oligonucleotide probes to enrich RNA transcripts of interest, which could overcome these limitations. Nevertheless, the standardization of this experimental framework, including probe designs, sample multiplexing, sequencing read length, and bioinformatic pipelines, remains an essential requirement. In this study, we conducted a comprehensive comparison of three main commercially available exome capture kits and evaluated key experimental parameters, to provide the overview of the advantages and limitations associated with the selection of library preparation protocols and sequencing platforms. The results provide valuable insights into the best practices for obtaining high-quality data from FFPE samples.

Key aspects defining the development and implementation of a regional genomic surveillance strategy for the Eastern Mediterranean Region

The COVID-19 pandemic highlighted the critical role of pathogen sequencing in making informed public health decisions. Initially, the Eastern Mediterranean Region faced limitations in sequencing capacity. However, with robust WHO and stakeholder support, the situation significantly improved. By 2022, COVID-19 sequencing was underway in 22 out of 23 regional countries, with varying throughput and capacity. Notably, three genomic hubs were established in Oman, UAE, and Morocco, playing a key role in providing expanded genomics training and support across the region. While primarily for COVID-19 surveillance, this sequencing capacity offers an opportunity to integrate genomic surveillance into existing networks. This integration can enable early detection and response to high-threat pathogens with pandemic potential. To advance this, WHO/EMRO collaborated with stakeholders to formulate the Eastern Mediterranean Regional Genomic Surveillance Strategy for Emerging Pathogens of Pandemic Concern. Consultative meetings with regional and international genomic surveillance experts identified strategy focal points, key partners, priority pathogens, and implementation steps. As the strategy awaits member states' ratification in Q4 2023, this manuscript outlines pivotal facets defined by member states and the strategic document's key deliverables and opportunities. These efforts aim to yield a substantial positive impact within the region.

Why is there no service to support taxonomy?

Increasing complexity and specialisation of modern sciences has led to increasingly collaborative publications, as well as the involvement of commercial services. Modern integrative taxonomy likewise depends on many lines of evidence and is increasingly complex, but the trend of collaboration lags and various attempts at 'turbo taxonomy' have been unsatisfactory. We are developing a taxonomic service in the Senckenberg Ocean Species Alliance to provide fundamental data for new species descriptions. This will also function as a hub to connect a global network of taxonomists, assembling an alliance of scientists working on potential new species to tackle both the extinction and inclusion crises we face today. The current rate of new species descriptions is simply too slow; the discipline is often dismissed as old fashioned, and there is a crisis level need for taxonomic descriptions to come to grips with the scale of Anthropocene biodiversity loss. Here, we envision how the process of describing and naming species would benefit from a service supporting the acquisition of descriptive data. Also see the video abstract here: https://youtu.be/E8q3KJor_F8.

Blood taken immediately after fatal resuscitation attempts yields higher quality DNA for genetic studies as compared to autopsy samples

BACKGROUND

The out-of-hospital cardiac arrest (OHCA) in the young may be associated with a genetic predisposition which is relevant even for genetic counseling of relatives. The identification of genetic variants depends on the availability of intact genomic DNA. DNA from autopsy may be not available due to low autopsy frequencies or not suitable for high-throughput DNA sequencing (NGS). The emergency medical service (EMS) plays an important role to save biomaterial for subsequent molecular autopsy. It is not known whether the DNA integrity of samples collected by the EMS is better suited for NGS than autopsy specimens.

MATERIAL AND METHODS

DNA integrity was analyzed by standardized protocols. Fourteen blood samples collected by the EMS and biomaterials from autopsy were compared. We collected 172 autopsy samples from different tissues and blood with postmortem intervals of 14-168 h. For comparison, DNA integrity derived from blood stored under experimental conditions was checked against autopsy blood after different time intervals.

RESULTS

DNA integrity and extraction yield were higher in EMS blood compared to any autopsy tissue. DNA stability in autopsy specimens was highly variable and had unpredictable quality. In contrast, collecting blood samples by the EMS is feasible and delivered comparably the highest DNA integrity.

CONCLUSIONS

Isolation yield and DNA integrity from blood samples collected by the EMS is superior in comparison to autopsy specimens. DNA from blood samples collected by the EMS on scene is stable at room temperature or even for days at 4 °C. We conclude that the EMS personnel should always save a blood sample of young fatal OHCA cases died on scene to enable subsequent genetic analysis.

Amplicon Sequencing Minimal Information (ASqMI): Quality and Reporting Guidelines for Actionable Calls in Biodefense Applications

BACKGROUND

Accurate, high-confidence data is critical for assessing potential biothreat incidents. In a biothreat event, false-negative and -positive results have serious consequences. Worst case scenarios can result in unnecessary shutdowns or fatalities at an exorbitant monetary and psychological cost, respectively. Quantitative PCR assays for agents of interest have been successfully used for routine biosurveillance. Recently, there has been increased impetus for adoption of amplicon sequencing (AS) for biosurveillance because it enables discrimination of true positives from near-neighbor false positives, as well as broad, simultaneous detection of many targets in many pathogens in a high-throughput scheme. However, the high sensitivity of AS can lead to false positives. Appropriate controls and workflow reporting can help address these challenges.

OBJECTIVES

Data reporting standards are critical to data trustworthiness. The standards presented herein aim to provide a framework for method quality assessment in biodetection.

METHODS

We present a set of standards, Amplicon Sequencing Minimal Information (ASqMI), developed under the auspices of the AOAC INTERNATIONAL Stakeholder Program on Agent Detection Assays for making actionable calls in biosurveillance applications. In addition to the first minimum information guidelines for AS, we provide a controls checklist and scoring scheme to assure AS run quality and assess potential sample contamination.

RESULTS

Adoption of the ASqMI guidelines will improve data quality, help track workflow performance, and ultimately provide decision makers confidence to trust the results of this new and powerful technology.

CONCLUSION

AS workflows can provide robust, confident calls for biodetection; however, due diligence in reporting and controls are needed. The ASqMI guideline is the first AS minimum reporting guidance document that also provides the means for end users to evaluate their workflows to improve confidence.

HIGHLIGHTS

Standardized reporting guidance for actionable calls is critical to ensuring trustworthy data.

Pharmacogenomics in practice: a review and implementation guide

Considerable efforts have been exerted to implement Pharmacogenomics (PGx), the study of interindividual variations in DNA sequence related to drug response, into routine clinical practice. In this article, we first briefly describe PGx and its role in improving treatment outcomes. We then propose an approach to initiate clinical PGx in the hospital setting. One should first evaluate the available PGx evidence, review the most relevant drugs, and narrow down to the most actionable drug-gene pairs and related variant alleles. This is done based on data curated and evaluated by experts such as the pharmacogenomics knowledge implementation (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC), as well as drug regulatory authorities such as the US Food and Drug Administration (FDA) and European Medicinal Agency (EMA). The next step is to differentiate reactive point of care from preemptive testing and decide on the genotyping strategy being a candidate or panel testing, each of which has its pros and cons, then work out the best way to interpret and report PGx test results with the option of integration into electronic health records and clinical decision support systems. After test authorization or testing requirements by the government or drug regulators, putting the plan into action involves several stakeholders, with the hospital leadership supporting the process and communicating with payers, the pharmacy and therapeutics committee leading the process in collaboration with the hospital laboratory and information technology department, and healthcare providers (HCPs) ordering the test, understanding the results, making the appropriate therapeutic decisions, and explaining them to the patient. We conclude by recommending some strategies to further advance the implementation of PGx in practice, such as the need to educate HCPs and patients, and to push for more tests' reimbursement. We also guide the reader to available PGx resources and examples of PGx implementation programs and initiatives.

Navigating bottlenecks and trade-offs in genomic data analysis

Genome sequencing and analysis allow researchers to decode the functional information hidden in DNA sequences as well as to study cell to cell variation within a cell population. Traditionally, the primary bottleneck in genomic analysis pipelines has been the sequencing itself, which has been much more expensive than the computational analyses that follow. However, an important consequence of the continued drive to expand the throughput of sequencing platforms at lower cost is that often the analytical pipelines are struggling to keep up with the sheer amount of raw data produced. Computational cost and efficiency have thus become of ever increasing importance. Recent methodological advances, such as data sketching, accelerators and domain-specific libraries/languages, promise to address these modern computational challenges. However, despite being more efficient, these innovations come with a new set of trade-offs, both expected, such as accuracy versus memory and expense versus time, and more subtle, including the human expertise needed to use non-standard programming interfaces and set up complex infrastructure. In this Review, we discuss how to navigate these new methodological advances and their trade-offs.

The DNA integrity number and concentration are useful parameters for successful comprehensive genomic profiling test for cancer using formalin‐fixed paraffin embedded tissue

The acquisition of high-quality biospecimens and the appropriate handling of these materials are indispensable for successful clinical sequencing. We developed a cancer clinical sequencing system targeting 160 cancer genes: PleSSision-Rapid. Through the PleSSision-Rapid system, we have analyzed DNA quality evaluated by DIN (DNA integrity number) with 1329 formalin-fixed paraffin embedded (FFPE) samples including 477 prospectively collected tissues for genomic test (P) and 852 archival samples after routine pathological diagnosis (A1/A2). As a result, the samples with more than DIN 2.1 was 92.0% (439/477) in prospectively collected sample (P), while it was 85.6% (332/388) and 76.7% (356/464) in two types of archival samples (A1/A2). We performed the PleSSision-Rapid sequence using the samples with over DIN 2.1 and DNA concentration >10 ng/μL with which we were able to construct a DNA library, and the probability of sequence success was almost equivalent during all types of specimen processing, at 90.7% (398/439) in (P), 92.5% (307/332) in (A1) and 90.2% (321/356) in (A2), respectively. Our result indicated the clinical benefit to prepare the prospective collection of FFPE materials for indisputable clinical sequence, and that DIN ≥ 2.1 would be a solid parameter for sample preparation of comprehensive genomic profiling tests.

GenoPipe: identifying the genotype of origin within (epi)genomic datasets

Confidence in experimental results is critical for discovery. As the scale of data generation in genomics has grown exponentially, experimental error has likely kept pace despite the best efforts of many laboratories. Technical mistakes can and do occur at nearly every stage of a genomics assay (i.e., cell line contamination, reagent swapping, tube mislabelling, etc.) and are often difficult to identify post-execution. However, the DNA sequenced in genomic experiments contains certain markers (e.g., indels) encoded within and can often be ascertained forensically from experimental datasets. We developed the Genotype validation Pipeline (GenoPipe), a suite of heuristic tools that operate together directly on raw and aligned sequencing data from individual high-throughput sequencing experiments to characterize the underlying genome of the source material. We demonstrate how GenoPipe validates and rescues erroneously annotated experiments by identifying unique markers inherent to an organism’s genome (i.e., epitope insertions, gene deletions, and SNPs).

Integrating Cutting-Edge Methods to Oral Cancer Screening, Analysis, and Prognosis

Oral cancer (OC) has become a significant barrier to health worldwide due to its high morbidity and mortality rates. OC is among the most prevalent types of cancer that affect the head and neck region, and the overall survival rate at 5 years is still around 50%. Moreover, it is a multifactorial malignancy instigated by genetic and epigenetic variabilities, and molecular heterogeneity makes it a complex malignancy. Oral potentially malignant disorders (OPMDs) are often the first warning signs of OC, although it is challenging to predict which cases will develop into malignancies. Visual oral examination and histological examination are still the standard initial steps in diagnosing oral lesions; however, these approaches have limitations that might lead to late diagnosis of OC or missed diagnosis of OPMDs in high-risk individuals. The objective of this review is to present a comprehensive overview of the currently used novel techniques viz., liquid biopsy, next-generation sequencing (NGS), microarray, nanotechnology, lab-on-a-chip (LOC) or microfluidics, and artificial intelligence (AI) for the clinical diagnostics and management of this malignancy. The potential of these novel techniques in expanding OC diagnostics and clinical management is also reviewed.

From Samples to Germline and Somatic Sequence Variation: A Focus on Next-Generation Sequencing in Melanoma Research

Next-generation sequencing (NGS) applications have flourished in the last decade, permitting the identification of cancer driver genes and profoundly expanding the possibilities of genomic studies of cancer, including melanoma. Here we aimed to present a technical review across many of the methodological approaches brought by the use of NGS applications with a focus on assessing germline and somatic sequence variation. We provide cautionary notes and discuss key technical details involved in library preparation, the most common problems with the samples, and guidance to circumvent them. We also provide an overview of the sequence-based methods for cancer genomics, exposing the pros and cons of targeted sequencing vs. exome or whole-genome sequencing (WGS), the fundamentals of the most common commercial platforms, and a comparison of throughputs and key applications. Details of the steps and the main software involved in the bioinformatics processing of the sequencing results, from preprocessing to variant prioritization and filtering, are also provided in the context of the full spectrum of genetic variation (SNVs, indels, CNVs, structural variation, and gene fusions). Finally, we put the emphasis on selected bioinformatic pipelines behind (a) short-read WGS identification of small germline and somatic variants, (b) detection of gene fusions from transcriptomes, and (c) de novo assembly of genomes from long-read WGS data. Overall, we provide comprehensive guidance across the main methodological procedures involved in obtaining sequencing results for the most common short- and long-read NGS platforms, highlighting key applications in melanoma research.

Metagenomic and genomic characterization of heavy metal tolerance and resistance genes in the rhizosphere microbiome of Avicennia germinans in a semi-arid mangrove forest in the tropics

Mangroves are often exposed to heavy metals that accumulate in the food chain, generate toxicity to mangrove plants and affect microbial diversity. This study determined the abundance of genes associated with resistance and tolerance to heavy metals in the rhizosphere microbiome of Avicennia germinans from a semi-arid mangrove of La Guajira-Colombia by metagenomics and genomics approach. Twenty-eight genes associated with tolerance and 49 genes related to resistance to heavy metals were detected. Genes associated with tolerance and resistance to Cu, especially cusA and copA, were the most abundant. The highest number of genes for tolerance and resistance were for Zn and Co, respectively. The isolate Vibrio fluvialis showed the ability to tolerate Cu, Ni, Zn, and Cd. This work used a complementary approach of metagenomics and genomics to characterize the potential of mangrove microorganisms to tolerate and resist heavy metals and the influence of salinity on their abundance.

Tackling the translational challenges of multi-omics research in the realm of European personalised medicine: A workshop report

Personalised medicine (PM) presents a great opportunity to improve the future of individualised healthcare. Recent advances in -omics technologies have led to unprecedented efforts characterising the biology and molecular mechanisms that underlie the development and progression of a wide array of complex human diseases, supporting further development of PM. This article reflects the outcome of the 2021 EATRIS-Plus Multi-omics Stakeholder Group workshop organised to 1) outline a global overview of common promises and challenges that key European stakeholders are facing in the field of multi-omics research, 2) assess the potential of new technologies, such as artificial intelligence (AI), and 3) establish an initial dialogue between key initiatives in this space. Our focus is on the alignment of agendas of European initiatives in multi-omics research and the centrality of patients in designing solutions that have the potential to advance PM in long-term healthcare strategies.

A Comprehensive Review of Performance of Next-Generation Sequencing Platforms

Background

Next-generation sequencing methods have been developed and proposed to investigate any query in genomics or clinical activity involving DNA. Technical advancement in these sequencing methods has enhanced sequencing volume to several billion nucleotides within a very short time and low cost. During the last few years, the usage of the latest DNA sequencing platforms in a large number of research projects helped to improve the sequencing methods and technologies, thus enabling a wide variety of research/review publications and applications of sequencing technologies.

Objective

The proposed study is aimed at highlighting the most fast and accurate NGS instruments developed by various companies by comparing output per hour, quality of the reads, maximum read length, reads per run, and their applications in various domains. This will help research institutions and biological/clinical laboratories to choose the sequencing instrument best suited to their environment. The end users will have a general overview about the history of the sequencing technologies, latest developments, and improvements made in the sequencing technologies till now.

Results

The proposed study, based on previous studies and manufacturers' descriptions, highlighted that in terms of output per hour, Nanopore PromethION outperformed all sequencers. BGI was on the second position, and Illumina was on the third position.

Conclusion

The proposed study investigated various sequencing instruments and highlighted that, overall, Nanopore PromethION is the fastest sequencing approach. BGI and Nanopore can beat Illumina, which is currently the most popular sequencing company. With respect to quality, Ion Torrent NGS instruments are on the top of the list, Illumina is on the second position, and BGI DNB is on the third position. Secondly, memory- and time-saving algorithms and databases need to be developed to analyze data produced by the 3rd- and 4th-generation sequencing methods. This study will help people to adopt the best suited sequencing platform for their research work, clinical or diagnostic activities.

Consistent count region-copy number variation (CCR-CNV): an expandable and robust tool for clinical diagnosis of copy number variation at the exon level using next-generation sequencing data

PURPOSE

Despite the importance of exonic copy number variations (CNVs) in human genetic diseases, reliable next-generation sequencing-based methods for detecting them are unavailable. We developed an expandable and robust exonic CNV detection tool called consistent count region (CCR)-CNV.

METHODS

In total, about 1000 samples of the truth set were used for validating CCR-CNV. We compared CCR-CNV performance with 2 well-known CNV tools. Finally, to overcome the limitations of CCR-CNV, we devised a combined approach.

RESULTS

The mean sensitivity and specificity of CCR-CNV alone were above 95%, which was superior to that of other CNV tools, such as DECoN and Atlas-CNV. However, low covered region and positive predictive value and high false discovery rate act as obstacles to its use in clinical settings. The combined approach showed much improved performance than CCR-CNV alone.

CONCLUSION

In this study, we present a novel diagnostic tool that allows the identification of exonic CNVs with high confidence using various reagents and clinical next-generation sequencing platforms. We validated this method using the largest multiple ligation-dependent probe amplification-confirmed data set, including sufficient copy normal control data. The approach, combined with existing CNV tools, allows the implementation of CCR-CNV in clinical settings.

Building up a clinical microbiota profiling: a quality framework proposal

Extensive characterization of the human microbiota has revealed promising relationships between microbial composition and health or disease, generating interest in biomarkers derived from microbiota profiling. However, microbiota complexity and technical challenges strongly influencing the results limit the generalization of microbiota profiling and question its clinical utility. In addition, no quality management scheme has been adapted to the specificities of microbiota profiling, notably due to the heterogeneity in methods and results. In this review, we discuss possible adaptation of classical quality management tools routinely used in diagnostic laboratories to microbiota profiling and propose a specific framework. Multiple quality controls are needed to cover all steps, from sampling to data processing. Standard operating procedures, primarily developed for wet lab analyses, must be adapted to the use of bioinformatic tools. Finally, requirements for test validation and proficiency testing must take into account expected discrepancies in results due to the heterogeneity of the processes. The proposed quality management framework should support the implementation of routine microbiota profiling by clinical laboratories to support patient care. Furthermore, its use in research laboratories would improve publication reproducibility as well as transferability of methods and results to routine practice.

Endophytic bacterial community diversity in two citrus cultivars with different citrus canker disease resistance

The selective infection of Xanthomonas citri pv. citri (Xcc) to citrus cultivars is universally known, but the relationship between endophytic bacteria and the resistance of host variety to canker disease remains unclear. In this study, endophytic bacterial populations of two citrus cultivars-the resistant satsuma mandarin and the susceptible Newhall navel orange-were analyzed through high-throughput sequencing. The results showed that endophytic bacterial community of satsuma mandarin was more abundant than that of Newhall navel orange. In addition, bacterial abundance was the highest in the spring samples, followed by that in summer and winter samples, in both the varieties. In all samples, the predominant phyla were Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes; the major genera were Bacillus and Stenotrophomonas, and the main species was Bacillus subtilis. According to the analysis of the predominant bacteria in the two citrus cultivars, B. subtilis with potential antagonistic characteristics against Xcc existed universally in all samples. However, the susceptible Newhall navel oranges were abundant in Bacillus subtilis and had a relatively large number of canker-causing cooperative bacteria such as Stenotrophomonas. The results suggested that endophytic bacterial community of the two citrus cultivars had some differences based on the season or plant tissue, and these differences were mainly in the quantity of bacteria, affecting citrus canker disease occurrence. In conclusion, the differences in endophytic bacteria on citrus cultivars might be related to host resistance or susceptibility to citrus canker disease.

Handling of targeted amplicon sequencing data focusing on index hopping and demultiplexing using a nested metabarcoding approach in ecology

High-throughput sequencing platforms are increasingly being used for targeted amplicon sequencing because they enable cost-effective sequencing of large sample sets. For meaningful interpretation of targeted amplicon sequencing data and comparison between studies, it is critical that bioinformatic analyses do not introduce artefacts and rely on detailed protocols to ensure that all methods are properly performed and documented. The analysis of large sample sets and the use of predefined indexes create challenges, such as adjusting the sequencing depth across samples and taking sequencing errors or index hopping into account. However, the potential biases these factors introduce to high-throughput amplicon sequencing data sets and how they may be overcome have rarely been addressed. On the example of a nested metabarcoding analysis of 1920 carabid beetle regurgitates to assess plant feeding, we investigated: (i) the variation in sequencing depth of individually tagged samples and the effect of library preparation on the data output; (ii) the influence of sequencing errors within index regions and its consequences for demultiplexing; and (iii) the effect of index hopping. Our results demonstrate that despite library quantification, large variation in read counts and sequencing depth occurred among samples and that the sequencing error rate in bioinformatic software is essential for accurate adapter/primer trimming and demultiplexing. Moreover, setting an index hopping threshold to avoid incorrect assignment of samples is highly recommended.

Statistical guidelines for quality control of next-generation sequencing techniques

More and more next-generation sequencing (NGS) data are made available every day. However, the quality of this data is not always guaranteed. Available quality control tools require profound knowledge to correctly interpret the multiplicity of quality features. Moreover, it is usually difficult to know if quality features are relevant in all experimental conditions. Therefore, the NGS community would highly benefit from condition-specific data-driven guidelines derived from many publicly available experiments, which reflect routinely generated NGS data. In this work, we have characterized well-known quality guidelines and related features in big datasets and concluded that they are too limited for assessing the quality of a given NGS file accurately. Therefore, we present new data-driven guidelines derived from the statistical analysis of many public datasets using quality features calculated by common bioinformatics tools. Thanks to this approach, we confirm the high relevance of genome mapping statistics to assess the quality of the data, and we demonstrate the limited scope of some quality features that are not relevant in all conditions. Our guidelines are available at https://cbdm.uni-mainz.de/ngs-guidelines.

Analysis of mitochondrial regulatory transcripts in publicly available datasets with validation in placentae from pre-term, post-term and fetal growth restriction pregnancies

INTRODUCTION

The human placenta has a defined lifespan and placental aging is a key feature as pregnancy progresses. Placental aging and mitochondrial dysfunction are known to play a key role in pregnancy pathophysiology. Premature aging of the placenta has also been linked with placental dysfunction resulting in poor fetal development and premature birth.

METHODS

The expression of key mitochondrial-related genes were analysed in a series of publicly available databases then expression changes were validated in placental samples collected from term, pre-term, post-term pregnancies and pregnancies complicated by fetal growth restriction (FGR). Gene and protein expression levels of MFN1, MFN2, TFAM, TOMM20, OPA3 and SIRT4 were measured in placental tissues via qPCR and western blotting.

RESULTS

Initial analysis found that key mitochondrial transcripts related to biogenesis, bioenergetics and mitophagy clustered by pregnancy trimester. A refined list of 13 mitochondrial-related genes were investigated in additional external datasets of pregnancy complications. In the new cohort, protein expression of MFN1 was decreased in FGR and MFN2 is decreased in post-term placenta. Analysis of placental tissues revealed that TOMM20 gene and protein expression was altered in FGR and post-term placenta.

DISCUSSION

MFN1 and MFN2 play a major role in mitochondrial dynamics, and alterations in these markers have been highlighted in early unexplained miscarriage. TOMM20 is an importer protein that plays a major role in mitophagy and changes have also been identified in age-related diseases. Significant changes in MFN1, MFN2 and TOMM20 indicate that mitochondrial regulators play a critical role in placental aging and placental pathophysiology.

Human Papillomavirus Detection by Whole-Genome Next-Generation Sequencing: Importance of Validation and Quality Assurance Procedures

Next-generation sequencing (NGS) yields powerful opportunities for studying human papillomavirus (HPV) genomics for applications in epidemiology, public health, and clinical diagnostics. HPV genotypes, variants, and point mutations can be investigated in clinical materials and described in previously unprecedented detail. However, both the NGS laboratory analysis and bioinformatical approach require numerous steps and checks to ensure robust interpretation of results. Here, we provide a step-by-step review of recommendations for validation and quality assurance procedures of each step in the typical NGS workflow, with a focus on whole-genome sequencing approaches. The use of directed pilots and protocols to ensure optimization of sequencing data yield, followed by curated bioinformatical procedures, is particularly emphasized. Finally, the storage and sharing of data sets are discussed. The development of international standards for quality assurance should be a goal for the HPV NGS community, similar to what has been developed for other areas of sequencing efforts including microbiology and molecular pathology. We thus propose that it is time for NGS to be included in the global efforts on quality assurance and improvement of HPV-based testing and diagnostics.

TMB or not TMB as a biomarker: That is the question

Immune checkpoint inhibitors (ICIs) have revolutionized the landscape of therapeutic options for many cancers. These treatments have demonstrated improved efficacy and often a more favourable toxicity profile compared to standard cytotoxic chemotherapy. There are considerable differences among responders, with some patients experiencing durable long-term disease control and even remission. Given this variability, determining a proper biomarker to select patients for ICI therapy has become increasingly important. The only biomarker proven to be predictive of overall survival benefit with ICI therapy is PD-L1 expression level measured by immunohistochemistry. Several attempts have been made to identify different predictive biomarkers. One of the most intriguing and divisive is tumor mutational burden (TMB). TMB represents the number of mutations per megabase (Mut/Mb) of DNA that were sequenced in a specific cancer. With a higher number of mutations detected, and consequentially an increase in the number neo-epitopes, then it is more likely that one or more of those neo-antigens could be immunogenic and trigger a T cell response. Initially, TMB was identified as a biomarker for ICIs in melanoma and subsequent studies suggested a possible clinical role for TMB in non-small cell lung cancer. The initial data were not confirmed in a prospective study assessing OS as the primary endpoint. Recently, the FDA has approved pembrolizumab in all cancers with a TMB > 10Mut/Mb[12] based on findings from the phase 2 KEYNOTE-158. Much criticism has emerged about this pan-cancer approval, in particular about the use of TMB as biomarker to select patients. Here we review the data about the importance and role of TMB as possible pan-cancer one-size-fits-all biomarker. We highlight the strengths and intrinsic limitations of such a complex biomarker and its adoption in the daily practice.

Building a Quality Management System in a Core Facility: A Genomics Core Case Study

Core facilities are key resources supporting the academic research enterprise, providing access to innovative and essential technologies and expertise. Given the constraints placed on core facilities as recharge centers and the ever-changing research environment, an important competitive differentiator that can support rigorous and reproducible approaches in core labs is the implementation of a quality management system (QMS). This paper describes a systematic approach to building a QMS in a genomics core facility at the University of North Carolina School of Medicine. This model is based on principles of the International Organization for Standardization 9001 system with initiatives focused on process mapping, training (communication, customer service, performance management, development of standard operating procedures, and quality audits), root cause analysis, visual control boards, mock quality audits, and continuous improvement through metrics tracking and "voice of the customer" exercises. The goal of this paper is to share practical step-by-step recommendations and outcomes of this core facility QMS that are generally applicable to academic core facilities, regardless of technical focus. Application of these good laboratory practice principles will foster "competitiveness through compliance" and promote outstanding interdisciplinary research between academic cores and their nonacademic pharmaceutical and federal research partners. Additionally, implementation of the QMS qualified this core to apply for federally funded contracts, thereby diversifying its types of projects and sources of revenue.

The ethics of genomic medicine: redefining values and norms in the UK and France

This paper presents a joint position of the UK-France Genomics and Ethics Network (UK-FR GENE), which has been set up to reflect on the ethical and social issues arising from the integration of genomics into routine clinical care in the UK and France. In 2018, the two countries announced enhanced cooperation between their national strategies, Genomics England and Plan France Médecine Génomique 2025, which offers a unique opportunity to study the impact of genomic medicine and relevant policies in different national contexts. The paper provides first insights into the two national strategies and the norms, values and principles at stake in each country. It discusses the impact of genomic medicine on established relationships and existing regulations, and examines its effects on solidarity and trust in public healthcare systems. Finally, it uses the social contract as an analytical lens to explore and redefine the balance between individual rights and collective duties in the context of genomic medicine. This paper leads to three key observations: (1) despite each country's strategy being at a different stage of implementation, the two countries face similar ethical issues; (2) each country tries to solve these issues by (re-)defining individual rights and collective duties in its own way; (3) the social contract presents a useful tool to analyse the ways the UK and France address the ethical challenges raised by genomics. This overview lays the groundwork for future in-depth comparison, and drive collaborative research, between the UK and France.

Molecular Phylogeny and Evolution of Amazon Parrots in the Greater Antilles

Amazon parrots (Amazona spp.) colonized the islands of the Greater Antilles from the Central American mainland, but there has not been a consensus as to how and when this happened. Today, most of the five remaining island species are listed as endangered, threatened, or vulnerable as a consequence of human activity. We sequenced and annotated full mitochondrial genomes of all the extant Amazon parrot species from the Greater Antillean (A. leucocephala (Cuba), A. agilis, A. collaria (both from Jamaica), A. ventralis (Hispaniola), and A. vittata (Puerto Rico)), A. albifrons from mainland Central America, and A. rhodocorytha from the Atlantic Forest in Brazil. The assembled and annotated mitogenome maps provide information on sequence organization, variation, population diversity, and evolutionary history for the Caribbean species including the critically endangered A. vittata. Despite the larger number of available samples from the Puerto Rican Parrot Recovery Program, the sequence diversity of the A. vittata population in Puerto Rico was the lowest among all parrot species analyzed. Our data support the stepping-stone dispersal and speciation hypothesis that has started approximately 3.47 MYA when the ancestral population arrived from mainland Central America and led to diversification across the Greater Antilles, ultimately reaching the island of Puerto Rico 0.67 MYA. The results are presented and discussed in light of the geological history of the Caribbean and in the context of recent parrot evolution, island biogeography, and conservation. This analysis contributes to understating evolutionary history and empowers subsequent assessments of sequence variation and helps design future conservation efforts in the Caribbean.

The Role of the Pathologist in the Next-Generation Era of Tumor Molecular Characterization

Current pathology practice is being shaped by the increasing complexity of modern medicine, in particular of precision oncology, and major technological advances. In the "next-generation technologies era", the pathologist has become the person responsible for the integration and interpretation of morphologic and molecular information and for the delivery of critical answers to diagnostic, prognostic and predictive queries, acquiring a prominent position in the molecular tumor boards.

Whole-genome sequencing data of Kazakh individuals

Objectives

Kazakhstan is a Central Asian crossroad of European and Asian populations situated along the way of the Great Silk Way. The territory of Kazakhstan has historically been inhabited by nomadic tribes and today is the multi-ethnic country with the dominant Kazakh ethnic group. We sequenced and analyzed the whole-genomes of five ethnic healthy Kazakh individuals with high coverage using next-generation sequencing platform. This whole-genome sequence data of healthy Kazakh individuals can be a valuable reference for biomedical studies investigating disease associations and population-wide genomic studies of ethnically diverse Central Asian region.

Data description

Blood samples have been collected from five ethnic healthy Kazakh individuals living in Kazakhstan. The genomic DNA was extracted from blood and sequenced. Sequencing was performed on Illumina HiSeq2000 next-generation sequencing platform. We sequenced and analyzed the whole-genomes of ethnic Kazakh individuals with the coverage ranging from 26 to 32X. Ranging from 98.85 to 99.58% base pairs were totally mapped and aligned on the human reference genome GRCh37 hg19. Het/Hom and Ts/Tv ratios for each whole genome ranged from 1.35 to 1.49 and from 2.07 to 2.08, respectively. Sequencing data are available in the National Center for Biotechnology Information SRA database under the accession number PRJNA374772.

The International Collaboration for Cancer Classification and Research

Gaps in the translation of research findings to clinical management have been recognized for decades. They exist for the diagnosis as well as the management of cancer. The international standards for cancer diagnosis are contained within the World Health Organization (WHO) Classification of Tumours, published by the International Agency for Research on Cancer (IARC) and known worldwide as the WHO Blue Books. In addition to their relevance to individual patients, these volumes provide a valuable contribution to cancer research and surveillance, fulfilling an important role in scientific evidence synthesis and international standard setting. However, the multidimensional nature of cancer classification, the way in which the WHO Classification of Tumours is constructed, and the scientific information overload in the field pose important challenges for the translation of research findings to tumour classification and hence cancer diagnosis. To help address these challenges, we have established the International Collaboration for Cancer Classification and Research (IC3 R) to provide a forum for the coordination of efforts in evidence generation, standard setting and best practice recommendations in the field of tumour classification. The first IC3 R meeting, held in Lyon, France, in February 2019, gathered representatives of major institutions involved in tumour classification and related fields to identify and discuss translational challenges in data comparability, standard setting, quality management, evidence evaluation and copyright, as well as to develop a collaborative plan for addressing these challenges.

Analyzing Low-Level mtDNA Heteroplasmy-Pitfalls and Challenges from Bench to Benchmarking

Massive parallel sequencing technologies are promising a highly sensitive detection of low-level mutations, especially in mitochondrial DNA (mtDNA) studies. However, processes from DNA extraction and library construction to bioinformatic analysis include several varying tasks. Further, there is no validated recommendation for the comprehensive procedure. In this study, we examined potential pitfalls on the sequencing results based on two-person mtDNA mixtures. Therefore, we compared three DNA polymerases, six different variant callers in five mixtures between 50% and 0.5% variant allele frequencies generated with two different amplification protocols. In total, 48 samples were sequenced on Illumina MiSeq. Low-level variant calling at the 1% variant level and below was performed by comparing trimming and PCR duplicate removal as well as six different variant callers. The results indicate that sensitivity, specificity, and precision highly depend on the investigated polymerase but also vary based on the analysis tools. Our data highlight the advantage of prior standardization and validation of the individual laboratory setup with a DNA mixture model. Finally, we provide an artificial heteroplasmy benchmark dataset that can help improve somatic variant callers or pipelines, which may be of great interest for research related to cancer and aging.

Impact of DNA integrity on the success rate of tissue-based next-generation sequencing: Lessons from nationwide cancer genome screening project SCRUM-Japan GI-SCREEN

In the nationwide cancer genome screening project SCRUM-Japan GI-SCREEN, 2590 archival formalin-fixed paraffin-embedded (FFPE) tumor tissues from 19 institutions were analyzed with two tissue-based next-generation sequencing (NGS) panels at the Clinical Laboratory Improvement Amendments (CLIA)-certified College of American Pathologists (CAP)-accredited central laboratory. The Oncomine Cancer Research Panel (OCP; 143 genes) succeeded in producing validated results for only 68.3% of the samples (%OCP-success). CE-IVD (25 genes) succeeded in 45.9% of the OCP-failed samples, leading to an overall NGS success (%combined-success) rate as high as 82.9%. Among 2573 samples, the DNA-integrity (ΔCt )-high (ΔCt  < 4.4, n = 1253) samples showed significantly higher %OCP- and %combined-success rates (90.2% and 97.4%, respectively) than the DNA-integrity-intermediate (4.4 < ΔCt  < 6.3, n = 911; 68.9% and 88.7%) and DNA-integrity-low ones (ΔCt  > 6.3 or polymerase chain reaction-failed, n = 409; 5.6% and 24.7%). Other factors associated with NGS success included the FFPE-sample storage period (<4 years), the specimen type (surgical) and the primary tumor site (colorectal). Multivariable analysis revealed DNA integrity as the factor with the strongest independent association with NGS success, although it was suggested that other institution-specific factors contribute to the discordance of inter-institutional NGS success rates. Our results emphasize the importance of DNA quality in FFPE samples for NGS tests and the impact of DNA integrity on quality monitoring of pathology specimens for achieving successful NGS.

A novel prognostic two-gene signature for triple negative breast cancer

The absence of a robust risk stratification tool for triple negative breast cancer (TNBC) underlies imprecise and nonselective treatment of these patients with cytotoxic chemotherapy. This study aimed to interrogate transcriptomes of TNBC resected samples using next generation sequencing to identify novel biomarkers associated with disease outcomes. A subset of cases (n = 112) from a large, well-characterized cohort of primary TNBC (n = 333) were subjected to RNA-sequencing. Reads were aligned to the human reference genome (GRCH38.83) using the STAR aligner and gene expression quantified using HTSEQ. We identified genes associated with distant metastasis-free survival and breast cancer-specific survival by applying supervised artificial neural network analysis with gene selection to the RNA-sequencing data. The prognostic ability of these genes was validated using the Breast Cancer Gene-Expression Miner v4. 0 and Genotype 2 outcome datasets. Multivariate Cox regression analysis identified a prognostic gene signature that was independently associated with poor prognosis. Finally, we corroborated our results from the two-gene prognostic signature by their protein expression using immunohistochemistry. Artificial neural network identified two gene panels that strongly predicted distant metastasis-free survival and breast cancer-specific survival. Univariate Cox regression analysis of 21 genes common to both panels revealed that the expression level of eight genes was independently associated with poor prognosis (p < 0.05). Adjusting for clinicopathological factors including patient's age, grade, nodal stage, tumor size, and lymphovascular invasion using multivariate Cox regression analysis yielded a two-gene prognostic signature (ACSM4 and SPDYC), which was associated with poor prognosis (p < 0.05) independent of other prognostic variables. We validated the protein expression of these two genes, and it was significantly associated with patient outcome in both independent and combined manner (p < 0.05). Our study identifies a prognostic gene signature that can predict prognosis in TNBC patients and could potentially be used to guide the clinical management of TNBC patients.

Twelve quick steps for genome assembly and annotation in the classroom

Eukaryotic genome sequencing and de novo assembly, once the exclusive domain of well-funded international consortia, have become increasingly affordable, thus fitting the budgets of individual research groups. Third-generation long-read DNA sequencing technologies are increasingly used, providing extensive genomic toolkits that were once reserved for a few select model organisms. Generating high-quality genome assemblies and annotations for many aquatic species still presents significant challenges due to their large genome sizes, complexity, and high chromosome numbers. Indeed, selecting the most appropriate sequencing and software platforms and annotation pipelines for a new genome project can be daunting because tools often only work in limited contexts. In genomics, generating a high-quality genome assembly/annotation has become an indispensable tool for better understanding the biology of any species. Herein, we state 12 steps to help researchers get started in genome projects by presenting guidelines that are broadly applicable (to any species), sustainable over time, and cover all aspects of genome assembly and annotation projects from start to finish. We review some commonly used approaches, including practical methods to extract high-quality DNA and choices for the best sequencing platforms and library preparations. In addition, we discuss the range of potential bioinformatics pipelines, including structural and functional annotations (e.g., transposable elements and repetitive sequences). This paper also includes information on how to build a wide community for a genome project, the importance of data management, and how to make the data and results Findable, Accessible, Interoperable, and Reusable (FAIR) by submitting them to a public repository and sharing them with the research community.

Next Generation Sequencing and Bioinformatics Analysis of Family Genetic Inheritance

Mendelian and complex genetic trait diseases continue to burden and affect society both socially and economically. The lack of effective tests has hampered diagnosis thus, the affected lack proper prognosis. Mendelian diseases are caused by genetic mutations in a singular gene while complex trait diseases are caused by the accumulation of mutations in either linked or unlinked genomic regions. Significant advances have been made in identifying novel diseases associated mutations especially with the introduction of next generation and third generation sequencing. Regardless, some diseases are still without diagnosis as most tests rely on SNP genotyping panels developed from population based genetic analyses. Analysis of family genetic inheritance using whole genomes, whole exomes or a panel of genes has been shown to be effective in identifying disease-causing mutations. In this review, we discuss next generation and third generation sequencing platforms, bioinformatic tools and genetic resources commonly used to analyze family based genomic data with a focus on identifying inherited or novel disease-causing mutations. Additionally, we also highlight the analytical, ethical and regulatory challenges associated with analyzing personal genomes which constitute the data used for family genetic inheritance.

German-Wide Interlaboratory Study Compares Consistency, Accuracy and Reproducibility of Whole-Genome Short Read Sequencing

We compared the consistency, accuracy and reproducibility of next-generation short read sequencing between ten laboratories involved in food safety (research institutes, state laboratories, universities and companies) from Germany and Austria. Participants were asked to sequence six DNA samples of three bacterial species (Campylobacter jejuni, Listeria monocytogenes and Salmonella enterica) in duplicate, according to their routine in-house sequencing protocol. Four different types of Illumina sequencing platforms (MiSeq, NextSeq, iSeq, NovaSeq) and one Ion Torrent sequencing instrument (S5) were involved in the study. Sequence quality parameters were determined for all data sets and centrally compared between laboratories. SNP and cgMLST calling were performed to assess the reproducibility of sequence data collected for individual samples. Overall, we found Illumina short read data to be more accurate (higher base calling accuracy, fewer miss-assemblies) and consistent (little variability between independent sequencing runs within a laboratory) than Ion Torrent sequence data, with little variation between the different Illumina instruments. Two laboratories with Illumina instruments submitted sequence data with lower quality, probably due to the use of a library preparation kit, which shows difficulty in sequencing low GC genome regions. Differences in data quality were more evident after assembling short reads into genome assemblies, with Ion Torrent assemblies featuring a great number of allele differences to Illumina assemblies. Clonality of samples was confirmed through SNP calling, which proved to be a more suitable method for an integrated data analysis of Illumina and Ion Torrent data sets in this study.

The regulatory landscape of precision oncology laboratory medicine in the United States - Perspective on the past 5 years and considerations for future regulation

The regulatory landscape for precision oncology in the United States is complicated, with multiple governmental regulatory agencies with different scopes of jurisdiction. Several regulatory proposals have been introduced since the Food and Drug Administration released a draft guidance to regulate laboratory-developed tests in 2014. Key aspects of the most recent proposals and discussion of central arguments related to the regulation of precision oncology laboratory tests provides insight to stakeholders for future discussions related to regulation of laboratory tests.

Regional sequence expansion or collapse in heterozygous genome assemblies

High levels of heterozygosity present a unique genome assembly challenge and can adversely impact downstream analyses, yet is common in sequencing datasets obtained from non-model organisms. Here we show that by re-assembling a heterozygous dataset with variant parameters and different assembly algorithms, we are able to generate assemblies whose protein annotations are statistically enriched for specific gene ontology categories. While total assembly length was not significantly affected by assembly methodologies tested, the assemblies generated varied widely in fragmentation level and we show local assembly collapse or expansion underlying the enrichment or depletion of specific protein functional groups. We show that these statistically significant deviations in gene ontology groups can occur in seemingly high-quality assemblies, and result from difficult-to-detect local sequence expansion or contractions. Given the unpredictable interplay between assembly algorithm, parameter, and biological sequence data heterozygosity, we highlight the need for better measures of assembly quality than N50 value, including methods for assessing local expansion and collapse.

In the genomic era, genomes must be reconstructed from fragments using computational methods, or assemblers. How do we know that a new genome assembly is correct? This is important because errors in assembly can lead to downstream problems in gene predictions and these inaccurate results can contaminate databases, affecting later comparative studies. A particular challenge occurs when a diploid organism inherits two highly divergent genome copies from its parents. While it is widely appreciated that this type of data is difficult for assemblers to handle properly, here we show that the process is prone to more errors than previously appreciated. Specifically, we document examples of regional expansion and collapse, affecting downstream gene prediction accuracy, but without changing the overall genome assembly size or other metrics of accuracy. Our results suggest that assembly evaluation methods should be altered to identify whether regional expansions and collapses are present in the genome assembly.

Microbiome Diagnostics

BACKGROUND

During the past decade, breakthroughs in sequencing technology and computational biology have provided the basis for studies of the myriad ways in which microbial communities ("microbiota") in and on the human body influence human health and disease. In almost every medical specialty, there is now a growing interest in accurate and replicable profiling of the microbiota for use in diagnostic and therapeutic application.

CONTENT

This review provides an overview of approaches, challenges, and considerations for diagnostic applications borrowing from other areas of molecular diagnostics, including clinical metagenomics. Methodological considerations and evolving approaches for microbiota profiling from mitochondrially encoded 16S rRNA-based amplicon sequencing to metagenomics and metatranscriptomics are discussed. To improve replicability, at least the most vulnerable steps in testing workflows will need to be standardized and continuous efforts needed to define QC standards. Challenges such as purity of reagents and consumables, improvement of reference databases, and availability of diagnostic-grade data analysis solutions will require joint efforts across disciplines and with manufacturers.

SUMMARY

The body of literature supporting important links between the microbiota at different anatomic sites with human health and disease is expanding rapidly and therapeutic manipulation of the intestinal microbiota is becoming routine. The next decade will likely see implementation of microbiome diagnostics in diagnostic laboratories to fully capitalize on technological and scientific advances and apply them in routine medical practice.

Evaluation of DNA and RNA quality from archival formalin-fixed paraffin-embedded tissue for next-generation sequencing - Retrospective study in Japanese single institution

Genetic analysis on formalin-fixed paraffin-embedded (FFPE) tissue specimens has become a mainstream method, from conventional direct sequencing to comprehensive analysis using next-generation sequencing (NGS). In this study, we evaluated the quality of DNA and RNA extracted from FFPE sections, derived from surgical specimens of different tumor types. Electrophoresis was performed using a 4200 TapeStation to evaluate DNA and RNA fragmentation. DNA Ct values were higher and significantly increased over a period of 4 years compared with those from cell lines or frozen tissues. The RNA integrity number equivalent (RIN) ranged from 1 to 4.1 and DV200 ranged from 7.3 to 81%. Twelve of the 108 cases were analyzed by NGS using the AmpliSeq Cancer HotSpot Panel v2 on a Miniseq system. A sufficient number of reads and coverage were obtained in all cases. Our results revealed that NGS analysis was sufficient for FFPE-derived DNA within 4 years of preservation. Conversely, approximately 20% of the RNA derived from FFPE within 4 years from the collection could be inappropriate for gene analysis based on RIN and DV200. It was suggested that FFPE would be adequate for genetic analysis, although it is desirable to store frozen specimens for the tumor tissues to be subjected to genetic analysis.

Quality Control of Next-Generation Sequencing-Based HIV-1 Drug Resistance Data in Clinical Laboratory Information Systems Framework

Next-generation sequencing (NGS) in HIV drug resistance (HIVDR) testing has the potential to improve both clinical and public health settings, however it challenges the normal operations of quality management systems to be more flexible due to its complexity, massive data generation, and rapidly evolving protocols. While guidelines for quality management in NGS data have previously been outlined, little guidance has been implemented for NGS-based HIVDR testing. This document summarizes quality control procedures for NGS-based HIVDR testing laboratories using a laboratory information systems (LIS) framework. Here, we focus in particular on the quality control measures applied on the final sequencing product aligned with the recommendations from the World Health Organization HIV Drug Resistance Laboratory Network.