RNA viruses, like SARS-CoV-2, depend on their RNA-dependent RNA polymerases (RdRp) for replication, which is error prone. Monitoring replication errors is crucial for understanding the virus\'s evolution. Current methods lack the precision to detect rare de novo RNA mutations, particularly in low-input samples such as those from patients. Here we introduce a targeted accurate RNA consensus sequencing method (tARC-seq) to accurately determine the mutation frequency and types in SARS-CoV-2, both in cell culture and clinical samples. Our findings show an average of 2.68 × 10-5 de novo errors per cycle with a C > T bias that cannot be solely attributed to APOBEC editing. We identified hotspots and cold spots throughout the genome, correlating with high or low GC content, and pinpointed transcription regulatory sites as regions more susceptible to errors. tARC-seq captured template switching events including insertions, deletions and complex mutations. These insights shed light on the genetic diversity generation and evolutionary dynamics of SARS-CoV-2.

To improve the accuracy and the cost-efficiency of next-generation sequencing in ultralow-frequency mutation detection, we developed the Paired-End and Complementary Consensus Sequencing (PECC-Seq), a PCR-free duplex consensus sequencing approach. PECC-Seq employed shear points as endogenous barcodes to identify consensus sequences from the overlap in the shortened, complementary DNA strand-derived paired-end reads for sequencing error correction. With the high accuracy of PECC-Seq, we identified the characteristic base substitution errors introduced by the end-repair process of mechanical fragmentation-based library preparations, which were prominent at the terminal 7 bp of the library fragments in the 5\'-NpCpA-3\' and 5\'-NpCpT-3\' trinucleotide context. As demonstrated at the human genome scale (TK6 cells), after removing these potential end-repair artifacts from the terminal 7 bp, PECC-Seq could reduce the sequencing error frequency to mid-10-7 with a relatively low sequencing depth. For TA base pairs, the background error rate could be suppressed to mid-10-8. In mutagen-treated (6 μg/mL methyl methanesulfonate or 12 μg/mL N-nitroso-N-ethylurea) TK6, increases in mutagen treatment-related mutant frequencies could be detected, indicating the potential of PECC-Seq in detecting genome-wide ultra-rare mutations. In addition, our finding on the patterns of end-repair artifacts may provide new insights into further reducing technical errors not only for PECC-Seq, but also for other next-generation sequencing techniques.

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Purpose: Colorectal cancers are classified as right/left-sided based on whether they occur before/after the splenic flexure, with established differences in molecular subtypes and outcomes. However, it is unclear if this division is optimal and whether precise tumor location provides further information.Experimental Design: In 1,876 patients with colorectal cancer, we compared mutation prevalence and overall survival (OS) according to side and location. Consensus molecular subtype (CMS) was compared in a separate cohort of 608 patients.Results: Mutation prevalence differed by side and location for TP53, KRAS, BRAFV600, PIK3CA, SMAD4, CTNNB1, GNAS, and PTEN Within left- and right-sided tumors, there remained substantial variations in mutation rates. For example, within right-sided tumors, RAS mutations decreased from 70% for cecal, to 43% for hepatic flexure location (P = 0.0001), while BRAFV600 mutations increased from 10% to 22% between the same locations (P < 0.0001). Within left-sided tumors, the sigmoid and rectal region had more TP53 mutations (P = 0.027), less PIK3CA (P = 0.0009), BRAF (P = 0.0033), or CTNNB1 mutations (P < 0.0001), and less MSI (P < 0.0001) than other left-sided locations. Despite this, a left/right division preceding the transverse colon maximized prognostic differences by side and transverse colon tumors had K-modes mutation clustering that appeared more left than right sided. CMS profiles showed a decline in CMS1 and CMS3 and rise in CMS2 prevalence moving distally.Conclusions: Current right/left classifications may not fully recapitulate regional variations in tumor biology. Specifically, the sigmoid-rectal region appears unique and the transverse colon is distinct from other right-sided locations. Clin Cancer Res; 24(5); 1062-72. ©2017 AACRSee related commentary by Dienstmann, p. 989.

A long-standing question of human immunodeficiency virus (HIV) genetic variation and evolution has been whether differences exist in mutation rate and/or mutation spectra among HIV types (i.e., HIV-1 versus HIV-2) and among HIV groups (i.e., HIV-1 groups M-P and HIV-2 groups A-H) and HIV-1 Group M subtypes (i.e., subtypes A-D, F-H, and J-K). To address this, we developed a new single-strand consensus sequencing assay for the determination of HIV mutation frequencies and spectra using the Illumina sequencing platform. This assay enables parallel and standardized comparison of HIV mutagenesis among various viral vectors with lower background error than traditional methods of Illumina library preparation. We found significant differences in viral mutagenesis between HIV types but intriguingly no significant differences among HIV-1 Group M subtypes. More specifically, HIV-1 exhibited higher transition frequencies than HIV-2, due mostly to single G-to-A mutations and (to a lesser extent) G-to-A hypermutation. These data suggest that HIV-2 RT exhibits higher fidelity during viral replication, and taken together, these findings demonstrate that HIV type but not subtype significantly affects viral mutation frequencies and spectra. These differences may inform antiviral and vaccine strategies.

The mutation rate on the Y-chromosome matters for estimating the time-to-the-most-recent-common-ancestor (TMRCA, i.e. haplogroup age) in population genetics, as well as for forensic, medical, and genealogical studies. Large-scale sequencing efforts have produced several independent estimates of Y-SNP mutation rates. Genealogical, or pedigree, rates tend to be slightly faster than evolutionary rates obtained from ancient DNA or calibrations using dated (pre)historical events. It is, therefore, suggested to report TMRCAs using an envelope defined by the average aDNA-based rate and the average pedigree-based rate. The current estimate of the \"envelope rate\" is 0.75-0.89 substitutions per billion base pairs per year. The available Y-SNP mutation rates can be applied to high-coverage data from the entire X-degenerate region, but other datasets may demand recalibrated rates. While a consensus on Y-SNP rates is approaching, the debate on Y-STR rates has continued for two decades, because multiple genealogical rates were consistent with each other but three times faster than the single evolutionary estimate. Applying Y-SNP and Y-STR rates to the same haplogroups recently helped to clarify the issue. Genealogical and evolutionary STR rates typically provide lower and upper bounds of the \"true\" (SNP-based) age. The genealogical rate often-but not always-works well for haplogroups less than 7000 years old. The evolutionary rate, although calibrated using recent events, inflates ages of young haplogroups and deflates the age of the entire Y-chromosomal tree, but often provides reasonable estimates for intermediate ages (old haplogroups). Future rate estimates and accumulating case studies should further clarify the Y-SNP rates.

To develop evidence-based guideline recommendations through a systematic review of the literature to establish standard molecular biomarker testing of colorectal cancer (CRC) tissues to guide epidermal growth factor receptor (EGFR) therapies and conventional chemotherapy regimens.
The American Society for Clinical Pathology, College of American Pathologists, Association for Molecular Pathology, and American Society of Clinical Oncology convened an expert panel to develop an evidence-based guideline to establish standard molecular biomarker testing and guide therapies for patients with CRC. A comprehensive literature search that included more than 4,000 articles was conducted.
Twenty-one guideline statements were established.
Evidence supports mutational testing for EGFR signaling pathway genes, since they provide clinically actionable information as negative predictors of benefit to anti-EGFR monoclonal antibody therapies for targeted therapy of CRC. Mutations in several of the biomarkers have clear prognostic value. Laboratory approaches to operationalize CRC molecular testing are presented. Key Words: Molecular diagnostics; Gastrointestinal; Histology; Genetics; Oncology.

BACKGROUND: Enrichment of loci by DNA hybridization-capture, followed by high-throughput sequencing, is an important tool in modern genetics. Currently, the most common targets for enrichment are the protein coding exons represented by the consensus coding DNA sequence (CCDS). The CCDS, however, excludes many actual or computationally predicted coding exons present in other databases, such as RefSeq and Vega, and non-coding functional elements such as untranslated and regulatory regions. The number of variants per base pair (variant density) and our ability to interrogate regions outside of the CCDS regions is consequently less well understood.
RESULTS: We examine capture sequence data from outside of the CCDS regions and find that extremes of GC content that are present in different subregions of the genome can reduce the local capture sequence coverage to less than 50% relative to the CCDS. This effect is due to biases inherent in both the Illumina and SOLiD sequencing platforms that are exacerbated by the capture process. Interestingly, for two subregion types, microRNA and predicted exons, the capture process yields higher than expected coverage when compared to whole genome sequencing. Lastly, we examine the variation present in non-CCDS regions and find that predicted exons, as well as exonic regions specific to RefSeq and Vega, show much higher variant densities than the CCDS.
CONCLUSIONS: We show that regions outside of the CCDS perform less efficiently in capture sequence experiments. Further, we show that the variant density in computationally predicted exons is more than 2.5-times higher than that observed in the CCDS.