Clinical applications of precision oncology require accurate tests that can distinguish true cancer specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

A microcosm study in iron-limited waters of the northeast subarctic Pacific Ocean was conducted to examine how iron availability affects the frustule-related response of individual diatoms and thus the total quantity of silica precipitated by the community. New silica precipitated per cell was estimated using the fluorescent cell stain 2-(4-pyridyl)-5{[4-dimethylaminoethyl-aminocarbamoyl)-methoxy]phenyl}oxazole (PDMPO). Differences in new silica precipitation within a particular genus before and after iron enrichment were small compared to differences among genera, indicating that the quantity of total silica precipitated is particularly sensitive to community composition. Transcriptional patterns of genes encoding silicon transporters, aminopropyltransferases, chitin synthases, and a protein with uncharacterized function were measured in natural populations to identify indicators of the frustule-related responses of different genera to iron limitation. Transcripts associated with silicon transporters were the most readily detectable in three metatranscriptome datasets and were capable of resolving species composition shifts and physiological responses. Silicon transporter transcripts from a distinct phylogenetic clade were most abundant in the iron-limited community, and transcripts from a separate clade were more abundant in the community that bloomed after iron enrichment. Transcripts of the gene present in the ironlimited community were also more abundant in iron-limited laboratory cultures of Pseudo-nitzschia multiseries, suggesting that this gene plays a role in silicon uptake during iron limitation. The responses of individual cells, as detected in this study, determine how the community influences silicon cycling in iron-limited environments.

As CRISPR-based therapies enter the clinic, evaluation of safety remains a critical and active area of study. Here, we employ a clinical next generation sequencing (NGS) workflow to achieve high sequencing depth and detect ultra-low frequency variants across exons of genes associated with cancer, all exons, and genome wide. In three separate primary human hematopoietic stem and progenitor cell (HSPC) donors assessed in technical triplicates, we electroporated high-fidelity Cas9 protein targeted to three loci (AAVS1, HBB, and ZFPM2) and harvested genomic DNA at days 4 and 10. Our results demonstrate that clinically relevant delivery of high-fidelity Cas9 to primary HSPCs and ex vivo culture up to 10 days does not introduce or enrich for tumorigenic variants and that even a single SNP in a gRNA spacer sequence is sufficient to eliminate Cas9 off-target activity in primary, repair-competent human HSPCs.

The identification and classification of the non-haemolytic or viridans group of streptococci have long been recognised as difficult and unsatisfactory. Phenotypic and genotypic heterogeneity have resulted in ambiguous speciation, particularly with mutans streptococci and other oral streptococci. This study was done to determine whether random amplified polymorphic DNA (RAPD) analysis is useful to identify and even classify oral and other streptococci. DNA was prepared and purified from 25 strains of mutans streptococci including 11 reference strains of Streptococcus mutans, seven of S. sobrinus, three of S. rattus and one each of the four other species of the mutans group, together with 20 other reference species, mostly streptococci, and from 49 fresh isolates of mutans streptococci and of S. mutans from human saliva and dental plaque. DNA amplification was primed with each of three arbitrarily selected primers nine or 10 nucleotides in length. The amplified DNA fragments (amplicons) obtained were compared by agarose gel electrophoresis. Species-and strain-specific RAPD fingerprints were obtained not only from pure genomic DNA, but also from the supernates of crude cellular or colony extracts. Pending the analysis of numerous other strains, the data suggest that RAPD may be of value: (i) to distinguish the species S. mutans and S. sobrinus from each other and potentially from other species of oral streptococci, (ii) to differentiate and possibly classify oral streptococci and (iii) as a valuable tool in mutans streptococci epidemiology and transmission studies, by virtue of its rapidity, efficiency and reproducibility in generating genetic fingerprints of streptococcal isolates.

Background The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples. Results We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy. Conclusions A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.