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Archival tissues represent a rich resource for clinical genomic studies, particularly when coupled with comprehensive medical records. Use of these in next generation sequencing (NGS) is a priority. Nine formalin-fixed paraffin-embedded (FFPE) DNA extraction methods were evaluated using twelve FFPE samples of varying tissue types. Quality assessment included total yield, percent dsDNA, fragment analysis and multiplex PCR. After assessment, three tissue types from four FFPE DNA methods were selected for NGS downstream evaluation, targeted and whole exome sequencing. In addition, two low input library protocols were evaluated for WES. Analysis revealed average coverage across the target regions for WES was ~20-30X for all four FFPE DNA extraction methods. For the targeted panels, the highest molecular tag coverage was obtained with the Kingfisher FFPE extraction method. The genotype concordance was 99% for the commonly called variant positions between all four extraction methods with the targeted PCR NGS panel and 96% with WES. Assessing quality of extracted DNA aids in selecting the optimal NGS approach, and the choice of both DNA extraction and library preparation approaches can impact the performance of archival tissue in NGS.

Summary: Understanding the diversity of gastrointestinal (GI) immune cells, especially in the muscularis propria, is crucial for understanding their role in the maintenance of enteric neurons and smooth muscle and their contribution to GI motility. Here, we present a detailed protocol for isolating single immune cells from the human gastric muscularis propria. We describe steps for tissue preservation, dissection, and dissociation of the muscularis propria. We then detail procedures for magnetic sorting of CD45+ cells and single-cell RNA sequencing (scRNA-seq) analysis.For complete details on the use and execution of this protocol, please refer to Chikkamenahalli et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Cholesterol homeostasis is maintained through finely tuned mechanisms regulating intestinal absorption, hepatic biosynthesis and secretion as well as plasma clearance. Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a secreted enzyme of the serine protease family that reduces cellular uptake of plasma low-density lipoprotein (LDL) cholesterol by promoting LDL receptor (LDL-R) degradation. Species-specific positive selection has been noted in the LDLR promoter, leading to differential expression of LDLR among primates. Whether PCSK9 experienced significant selective pressure to maintain a functional relationship with its target protein, LDL-R, is unknown.We compiled the sequences of the coding regions of PCSK9 from 14 primate species in the clade of Hominoids, Old World monkeys and New World monkeys. To detect selective pressure at the protein level, the ratios of nonsynonymous/synonymous substitution rate (d(N)/d(S)) under different evolutionary models were calculated across the phylogeny of PCSK9. Maximum likelihood analyses of d(N)/d(S) ratios for the aligned coding region sequences among 14 primate species indicated that PCSK9 was subject to a strong functional constraint (i.e., purifying selection). However, positive selection was noted in the functional carboxyl-terminal (C-terminal) domain in many branches across the phylogeny, especially in the lineage leading to the orangutan. Furthermore, at least five positively selected amino acids were detected in this lineage using the branch-site model A. In a sliding-window analysis, several d(N)/d(S) peaks in the C-terminal domain in both the human and the orangutan branches were noted.These results suggest that among primates, differential selective pressure has shaped evolutionary patterns in the functional domains of PCSK9, an important regulator of cholesterol homeostasis.

ABSTRACTSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had an unprecedented impact on human health and highlights the need for genomic epidemiology studies to increase our understanding of virus evolution and spread and to inform policy decisions. We sequenced viral genomes from over 22,000 patient samples tested at Mayo Clinic Laboratories between 2020 and 2022 and used Bayesian phylodynamics to describe county and regional spread in Minnesota. The earliest calculated introduction into Minnesota was to Hennepin County from a domestic source around 22 January 2020; 6 weeks before the first confirmed case in the state. This led to the virus spreading to Northern Minnesota and, eventually, the rest of the state. International introductions were most abundant in Hennepin (home to the Minneapolis/St. Paul International Airport) totaling 45 (out of 107) over the 2-year period. Southern Minnesota counties were most common for domestic introductions, with 19 (out of 64), potentially driven by bordering states such as Iowa and Wisconsin as well as Illinois, which is nearby. Hennepin also was, by far, the most dominant source of in-state transmissions to other Minnesota locations (n = 772) over the 2-year period. We also analyzed the diversity of the location source of SARS-CoV-2 viruses in each county and noted the timing of state-wide policies as well as trends in clinical cases. Neither the number of clinical cases nor the major policy decisions, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, appeared to have an impact on virus diversity across each individual county.IMPORTANCEWe analyzed over 22,000 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes of patient samples tested at Mayo Clinic Laboratories during a 2-year period in the COVID-19 pandemic, which included Alpha, Delta, and Omicron variants of concern to examine the roles and relationships of Minnesota virus transmission. We found that Hennepin County, the most populous county, drove the transmission of SARS-CoV-2 viruses in the state after including the formation of earlier clades including 20A, 20C, and 20G, as well as variants of concern Alpha and Delta. We also found that Hennepin County was the source for most of the county-to-county introductions after an initial predicted introduction with the virus in early 2020 from an international source, while other counties acted as transmission “sinks.” In addition, major policies, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, did not appear to have an impact on virus diversity across individual counties.

Abstract How to identify follicular lymphoma (FL) patients with low disease burden but high risk for early progression is unclear. Building on a prior study demonstrating the early transformation of FLs with high variant allele frequency (VAF) BCL2 mutations at activation-induced cytidine deaminase (AICDA) sites, we examined 11 AICDA mutational targets, including BCL2, BCL6, PAX5, PIM1, RHOH, SOCS, and MYC, in 199 newly diagnosed grade 1 and 2 FLs. BCL2 mutations with VAF ≥20% occurred in 52% of cases. Among 97 FL patients who did not initially receive rituximab-containing therapy, nonsynonymous BCL2 mutations at VAF ≥20% were associated with increased transformation risk (HR 3.01, 95% CI 1.04–8.78, p = 0.043) and a trend toward shorter event-free survival (EFS, median 20 months with mutations versus 54 months without, p = 0.052). Other sequenced genes were less frequently mutated and did not increase the prognostic value of the panel. Across the entire population, nonsynonymous BCL2 mutations at VAF ≥20% were associated with decreased EFS (HR 1.55, 95% CI 1.02–2.35, p = 0.043 after correction for FLIPI and treatment) and decreased overall survival after median 14-year follow-up (HR 1.82, 95% CI 1.05–3.17, p = 0.034). Thus, high VAF nonsynonymous BCL2 mutations remain prognostic even in the chemoimmunotherapy era.

Abstract Background Formalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data. Methods We optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics. Results Samples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation 4). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.9 ng/ul and 2.08 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.82 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.848 in predicting QC status (pass/fail) of FFPE samples. Conclusions We provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.7 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis.

Abstract Background Benign breast disease (BBD) is a risk factor for breast cancer (BC); however, little is known about the genetic alterations present at the time of BBD diagnosis and how these relate to risk of incident BC. Methods A subset of a long-term BBD cohort was selected to examine DNA variation across three BBD groups (42 future estrogen receptor-positive (ER+) BC, 36 future estrogen receptor-negative (ER−) BC, and 42 controls cancer-free for at least 16 years post-BBD). DNA extracted from archival formalin fixed, paraffin-embedded (FFPE) tissue blocks was analyzed for presence of DNA alterations using a targeted panel of 93 BC-associated genes. To address artifacts frequently observed in FFPE tissues (e.g., C>T changes), we applied three filtering strategies based on alternative allele frequencies and nucleotide substitution context. Gene-level associations were performed using two types of burden tests and adjusted for clinical and technical covariates. Results After filtering, the variant frequency of SNPs in our sample was highly consistent with population allele frequencies reported in 1 KG/ExAC (0.986, p

Abstract Background Archived formalin fixed paraffin embedded (FFPE) samples are valuable clinical resources to examine clinically relevant morphology features and also to study genetic changes. However, DNA quality and quantity of FFPE samples are often sub-optimal, and resulting NGS-based genetics variant detections are prone to false positives. Evaluations of wet-lab and bioinformatics approaches are needed to optimize variant detection from FFPE samples. Results As a pilot study, we designed within-subject triplicate samples of DNA derived from paired FFPE and fresh frozen breast tissues to highlight FFPE-specific artifacts. For FFPE samples, we tested two FFPE DNA extraction methods to determine impact of wet-lab procedures on variant calling: QIAGEN QIAamp DNA Mini Kit (“QA”), and QIAGEN GeneRead DNA FFPE Kit (“QGR”). We also used negative-control (NA12891) and positive control samples (Horizon Discovery Reference Standard FFPE). All DNA sample libraries were prepared for NGS according to the QIAseq Human Breast Cancer Targeted DNA Panel protocol and sequenced on the HiSeq 4000. Variant calling and filtering were performed using QIAGEN Gene Globe Data Portal. Detailed variant concordance comparisons and mutational signature analysis were performed to investigate effects of FFPE samples compared to paired fresh frozen samples, along with different DNA extraction methods. In this study, we found that five times or more variants were called with FFPE samples, compared to their paired fresh-frozen tissue samples even after applying molecular barcoding error-correction and default bioinformatics filtering recommended by the vendor. We also found that QGR as an optimized FFPE-DNA extraction approach leads to much fewer discordant variants between paired fresh frozen and FFPE samples. Approximately 92% of the uniquely called FFPE variants were of low allelic frequency range ( T|G > A” mutational signature known to be representative of FFPE artifacts resulting from cytosine deamination. Based on control samples and FFPE-frozen replicates, we derived an effective filtering strategy with associated empirical false-discovery estimates. Conclusions Through this study, we demonstrated feasibility of calling and filtering genetic variants from FFPE tissue samples using a combined strategy with molecular barcodes, optimized DNA extraction, and bioinformatics methods incorporating genomics context such as mutational signature and variant allelic frequency.