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- Next-generation sequencing (NGS) is a technology being used by many laboratories to test for inherited disorders and tumor mutations. This technology is new for many practicing pathologists, who may not be familiar with the uses, methodology, and limitations of NGS. - To familiarize pathologists with several aspects of NGS, including current and expanding uses; methodology including wet bench aspects, bioinformatics, and interpretation; validation and proficiency; limitations; and issues related to the integration of NGS data into patient care. - The review is based on peer-reviewed literature and personal experience using NGS in a clinical setting at a major academic center. - The clinical applications of NGS will increase as the technology, bioinformatics, and resources evolve to address the limitations and improve quality of results. The challenge for clinical laboratories is to ensure testing is clinically relevant, cost-effective, and can be integrated into clinical care.

Thanks to high-throughput sequencing technologies, genome sequencing has become a common component in nearly all aspects of viral research; thus, we are experiencing an explosion in both the number of available genome sequences and the number of institutions producing such data. However, there are currently no common standards used to convey the quality, and therefore utility, of these various genome sequences. Here, we propose five “standard” categories that encompass all stages of viral genome finishing, and we define them using simple criteria that are agnostic to the technology used for sequencing. We also provide genome finishing recommendations for various downstream applications, keeping in mind the cost-benefit trade-offs associated with different levels of finishing. Our goal is to define a common vocabulary that will allow comparison of genome quality across different research groups, sequencing platforms, and assembly techniques.

Seq-Well provides similar scale and data quality to massively parallel, droplet-based single-cell RNA-seq methods in an easy to use, inexpensive and portable microwell format compatible with low-input samples. Single-cell RNA-seq can precisely resolve cellular states, but applying this method to low-input samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively parallel single-cell RNA-seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semipermeable membrane, enabling efficient cell lysis and transcript capture. We use Seq-Well to profile thousands of primary human macrophages exposed to Mycobacterium tuberculosis .

DNA sequencing continues to decrease in cost with the Illumina HiSeq2000 generating up to 600 Gb of paired-end 100 base reads in a ten-day run. Here we present a protocol for community amplicon sequencing on the HiSeq2000 and MiSeq Illumina platforms, and apply that protocol to sequence 24 microbial communities from host-associated and free-living environments. A critical question as more sequencing platforms become available is whether biological conclusions derived on one platform are consistent with what would be derived on a different platform. We show that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons.

We present, on behalf of EuroGentest and the European Society of Human Genetics, guidelines for the evaluation and validation of next-generation sequencing (NGS) applications for the diagnosis of genetic disorders. The work was performed by a group of laboratory geneticists and bioinformaticians, and discussed with clinical geneticists, industry and patients’ representatives, and other stakeholders in the field of human genetics. The statements that were written during the elaboration of the guidelines are presented here. The background document and full guidelines are available as supplementary material. They include many examples to assist the laboratories in the implementation of NGS and accreditation of this service. The work and ideas presented by others in guidelines that have emerged elsewhere in the course of the past few years were also considered and are acknowledged in the full text. Interestingly, a few new insights that have not been cited before have emerged during the preparation of the guidelines. The most important new feature is the presentation of a ‘rating system’ for NGS-based diagnostic tests. The guidelines and statements have been applauded by the genetic diagnostic community, and thus seem to be valuable for the harmonization and quality assurance of NGS diagnostics in Europe.

Core Ideas An R package that performs Next Generation Sequencing Bulk Segregant Analysis was developed. Two methods for analysis are provided: QTL‐seq and G’. The QTLseqr package is quick and produces publication quality figures and tables. Next‐Generation Sequencing Bulk Segregant Analysis (NGS‐BSA) is efficient in detecting quantitative trait loci (QTL). Despite the popularity of NGS‐BSA and the R statistical platform, no R packages are currently available for NGS‐BSA. We present QTLseqr, an R package for NGS‐BSA that identifies QTL using two statistical approaches: QTL‐seq and G’. These approaches use a simulation method and a tricube smoothed G statistic, respectively, to identify and assess statistical significance of QTL. QTLseqr can import and filter SNP data, calculate SNP distributions, relative allele frequencies, G’ values, and log10 (p‐values), enabling identification and plotting of QTL. The source code is available at https://github.com/bmansfeld/QTLseqr.

Next-generation DNA sequencing (NGS) has progressed enormously over the past decade, transforming genomic analysis and opening up many new opportunities for applications in clinical microbiology laboratories. The impact of NGS on microbiology has been revolutionary, with new microbial genomic sequences being generated daily, leading to the development of large databases of genomes and gene sequences. The ability to analyze microbial communities without culturing organisms has created the ever-growing field of metagenomics and microbiome analysis and has generated significant new insights into the relation between host and microbe. The medical literature contains many examples of how this new technology can be used for infectious disease diagnostics and pathogen analysis. The implementation of NGS in medical practice has been a slow process due to various challenges such as clinical trials, lack of applicable regulatory guidelines, and the adaptation of the technology to the clinical environment. In April 2015, the American Academy of Microbiology (AAM) convened a colloquium to begin to define these issues, and in this document, we present some of the concepts that were generated from these discussions.

Next-generation sequencing (NGS) data are used for both clinical care and clinical research. DNA sequence variants identified using NGS are often returned to patients/participants as part of clinical or research protocols. The current standard of care is to validate NGS variants using Sanger sequencing, which is costly and time-consuming. We performed a large-scale, systematic evaluation of Sanger-based validation of NGS variants using data from the ClinSeq® project. We first used NGS data from 19 genes in 5 participants, comparing them to high-throughput Sanger sequencing results on the same samples, and found no discrepancies among 234 NGS variants. We then compared NGS variants in 5 genes from 684 participants against data from Sanger sequencing. Of over 5800 NGS-derived variants, 19 were not validated by Sanger data. Using newly designed sequencing primers, Sanger sequencing confirmed 17 of the NGS variants, and the remaining 2 variants had low quality scores from exome sequencing. Overall, we measured a validation rate of 99.965% for NGS variants using Sanger sequencing, which was higher than many existing medical tests that do not necessitate orthogonal validation. A single round of Sanger sequencing is more likely to incorrectly refute a true-positive variant from NGS than to correctly identify a false-positive variant from NGS. Validation of NGS-derived variants using Sanger sequencing has limited utility, and best practice standards should not include routine orthogonal Sanger validation of NGS variants.

Sequencing 16S rRNA gene fragments has become a fundamental tool for understanding the diversity of microbial communities and the factors that affect their diversity. Due to technical challenges, it is common to observe wide variation in the number of sequences that are collected from different samples within the same study. However, the diversity metrics used by microbial ecologists are sensitive to differences in sequencing effort. Therefore, tools are needed to control for the uneven levels of sequencing. This simulation-based analysis shows that despite a longstanding controversy, rarefaction is the most robust approach to control for uneven sequencing effort. The controversy started because of confusion over the definition of rarefaction and violation of assumptions that are made by methods that have been borrowed from other fields. Microbial ecologists should use rarefaction.

Microsatellites, or simple sequence repeats (SSRs), are one of the most informative and multi-purpose genetic markers exploited in plant functional genomics. However, the discovery of SSRs and development using traditional methods are laborious, time-consuming, and costly. Recently, the availability of high-throughput sequencing technologies has enabled researchers to identify a substantial number of microsatellites at less cost and effort than traditional approaches. Illumina is a noteworthy transcriptome sequencing technology that is currently used in SSR marker development. Although 454 pyrosequencing datasets can be used for SSR development, this type of sequencing is no longer supported. This review aims to present an overview of the next generation sequencing, with a focus on the efficient use of de novo transcriptome sequencing (RNA-Seq) and related tools for mining and development of microsatellites in plants.