Comparison of commercially available whole-genome sequencing kits for variant detection in circulating cell-free DNA

Identification of Somatic Mutations in Plasma Cell-Free DNA from Patients with Metastatic Oral Squamous Cell Carcinoma

The accurate diagnosis and treatment of oral squamous cell carcinoma (OSCC) requires an understanding of its genomic alterations. Liquid biopsies, especially cell-free DNA (cfDNA) analysis, are a minimally invasive technique used for genomic profiling. We conducted comprehensive whole-exome sequencing (WES) of 50 paired OSCC cell-free plasma with whole blood samples using multiple mutation calling pipelines and filtering criteria. Integrative Genomics Viewer (IGV) was used to validate somatic mutations. Mutation burden and mutant genes were correlated to clinico-pathological parameters. The plasma mutation burden of cfDNA was significantly associated with clinical staging and distant metastasis status. The genes TTN, PLEC, SYNE1, and USH2A were most frequently mutated in OSCC, and known driver genes, including KMT2D, LRP1B, TRRAP, and FLNA, were also significantly and frequently mutated. Additionally, the novel mutated genes CCDC168, HMCN2, STARD9, and CRAMP1 were significantly and frequently present in patients with OSCC. The mutated genes most frequently found in patients with metastatic OSCC were RORC, SLC49A3, and NUMBL. Further analysis revealed that branched-chain amino acid (BCAA) catabolism, extracellular matrix-receptor interaction, and the hypoxia-related pathway were associated with OSCC prognosis. Choline metabolism in cancer, O-glycan biosynthesis, and protein processing in the endoplasmic reticulum pathway were associated with distant metastatic status. About 20% of tumors carried at least one aberrant event in BCAA catabolism signaling that could possibly be targeted by an approved therapeutic agent. We identified molecular-level OSCC that were correlated with etiology and prognosis while defining the landscape of major altered events of the OSCC plasma genome. These findings will be useful in the design of clinical trials for targeted therapies and the stratification of patients with OSCC according to therapeutic efficacy.

Nematode mitochondrial metagenomics: A new tool for biodiversity analysis

DNA barcoding approaches have greatly increased our understanding of biodiversity on the planet, and metabarcoding is widely used for classifying members of the phylum Nematoda. However, loci typically utilized in metabarcoding studies are often unable to resolve closely related species or are unable to recover all taxa present in a sample due to inadequate PCR primer binding. Mitochondrial metagenomics (mtMG) is an alternative approach utilizing shotgun sequencing of total DNA to recover the mitochondrial genomes of all species present in samples. However, this approach requires a comprehensive reference database for identification and currently available mitochondrial sequences for nematodes are highly dominated by sequences from the order Rhabditida, and excludes many clades entirely. Here, we analysed the efficacy of mtMG for the recovery of nematode taxa and the generation of mitochondrial genomes. We first developed a curated reference database of nematode mitochondrial sequences and expanded it with 40 newly sequenced taxa. We then tested the mito-metagenomics approach using a series of nematode mock communities consisting of morphologically identified nematode species representing various feeding traits, life stages, and phylogenetic relationships. We were able to identify all but two species through the de novo assembly of COX1 genes. We were also able to recover additional mitochondrial protein coding genes (PCGs) for 23 of the 24 detected species including a full array of 12 PCGs from five of the species. We conclude that mtMG offers a potential for the effective recovery of nematode biodiversity but remains limited by the breadth of the reference database.

Methylated ccfDNA from plasma biomarkers of Alzheimer's disease using targeted bisulfite sequencing

Aim: Noninvasive biomarkers such as methylated ccfDNA from plasma could help to support the diagnosis of Alzheimer's disease (AD). Methods: A targeted sequencing protocol was developed to identify candidate biomarkers of AD in methylated ccfDNA extracted from plasma. Results: The authors identified differentially methylated CpGs, regions of which were the same as those identified in previous AD studies. Specifically, a differentially methylated CpG of the LHX2 gene previously identified in a plasma study of AD was replicated in the study. The MBP and DUSP22 regions have been identified in other brain studies of AD and in the authors' study. Conclusion: Although these biomarkers must be validated in other cohorts, methylated ccfDNA could be a relevant noninvasive biomarker in AD.

Massively parallel enrichment of low-frequency alleles enables duplex sequencing at low depth

The ability to assay large numbers of low-frequency mutations is useful in biomedicine, yet, the technical hurdles of sequencing multiple mutations at extremely high depth, with accuracy, limits their detection in clinical practice. Low-frequency mutations can typically be detected by increasing the sequencing depth, however this limits the number of loci that can be probed for simultaneously. Here, we report a technique to accurately track thousands of distinct mutations with minimal reads, termed MAESTRO (minor allele enriched sequencing through recognition oligonucleotides), which employs massively-parallel mutation enrichment to enable duplex sequencing to track up to 10,000 low-frequency mutations, yet requiring up to 100-fold less sequencing. We show that MAESTRO could inform the mutation validation of whole-exome sequencing and whole genome sequencing data from tumor samples, enable chimerism testing, and is suitable for the monitoring of minimal residual disease via liquid biopsies. MAESTRO may improve the breadth, depth, accuracy, and efficiency of sequencing-based mutational testing.

Massively-parallel mutation enrichment enables the tracking of up to 10,000 low-frequency mutations, via duplex sequencing, requiring up to 100-fold less sequencing depth.

Comparison of methods for isolation and quantification of circulating cell-free DNA from patients with endometriosis

RESEARCH QUESTION

Which is the optimal extraction method for isolating and quantifying circulating cell-free DNA (ccfDNA) from patients with endometriosis? Endometriosis is a common benign disease, associated with pain, infertility and reduced quality of life. Endometriosis is also a known risk factor for various cancers. Robust biomarkers for early detection and prediction of prognosis, however, are lacking. CcfDNA is an easy to obtain biomarker associated with prognosis of cancer patients and enables non-invasive analysis of somatic mutations. Recently, elevated levels of ccfDNA were detected in patients with endometriosis.

DESIGN

Two different ccfDNA extraction methods were compared: Maxwell RSC ccfDNA plasma kit (Maxwell) and QiAamp minElute ccfDNA mini kit (QIAamp). The ccfDNA and circulating mitochondrial DNA (mtDNA) quantities from 34 patients diagnosed with endometriosis were analysed. Fluorometric measurement and quantitative reverse transcription polymerase chain reaction (qRT-PCR) of short and long ALU and mtDNA fragments were used to quantiy ccfDNA.

RESULTS

The yield of ccfDNA isolated with the Maxwell method was significantly higher compared with the QIAamp method (P < 0.0001). Integrity of ccfDNA was significantly higher in the QIAamp isolate (P < 0.0001). Recovered mtDNA was not significantly different between both extraction methods used.

CONCLUSIONS

The choice of extraction method can significantly influence the ccfDNA output and integrity. Both methods, however, enabled isolation of sufficient ccfDNA for further downstream applications. With this approach, isolation of ccfDNA could enable the non-invasive detection and analysis of somatic mutation within endometriosis tissue.

Genomic diversity of Mycobacterium avium subsp. paratuberculosis: pangenomic approach for highlighting unique genomic features with newly constructed complete genomes

Mycobacterium avium subsp. paratuberculosis (MAP) is a causative agent of Johne’s disease, which is a chronic granulomatous enteropathy in ruminants. Determining the genetic diversity of MAP is necessary to understand the epidemiology and biology of MAP, as well as establishing disease control strategies. In the present study, whole genome-based alignment and comparative analysis were performed using 40 publicly available MAP genomes, including newly sequenced Korean isolates. First, whole genome-based alignment was employed to identify new genomic structures in MAP genomes. Second, the genomic diversity of the MAP population was described by pangenome analysis. A phylogenetic tree based on the core genome and pangenome showed that the MAP was differentiated into two major types (C- and S-type), which was in keeping with the findings of previous studies. However, B-type strains were discriminated from C-type strains. Finally, functional analysis of the pangenome was performed using three virulence factor databases (i.e., PATRIC, VFDB, and Victors) to predict the phenotypic diversity of MAP in terms of pathogenicity. Based on the results of the pangenome analysis, we developed a real-time PCR technique to distinguish among S-, B- and C-type strains. In conclusion, the results of our study suggest that the phenotypic differences between MAP strains can be explained by their genetic polymorphisms. These results may help to elucidate the diversity of MAP, extending from genomic features to phenotypic traits.