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Background: Next generation sequencing has a potential to revolutionize the management of cancer patients within the framework of precision oncology. Nevertheless, lack of standardization decelerated entering of the technology into the clinical testing space. Here we dissected a number of common problems of NGS diagnostics in oncology and introduced ways they can be resolved.Methods: DNA was extracted from 26 formalin fixed paraffin embedded (FFPE) specimens and processed with the TrueSeq Amplicon Cancer Panel (Illumina Inc, San Diego, California) targeting 48 cancer-related genes and sequenced in single run. Sequencing data were comparatively analyzed by several bioinformatics pipelines.Results: Libraries yielded sufficient coverage to detect even low prevalent mutations. We found that the number of FFPE sequence artifacts significantly correlates with pre-normalization concentration of libraries (rank correlation -0.81; p < 1e-10), thus, contributing to sample-specific variant detection cut-offs. Surprisingly, extensive validation of EGFR mutation calls by a combination of aligners and variant callers resulted in identification of two false negatives and one false positive that were due to complexity of underlying genomic change, confirmed by Sanger sequencing. Additionally, the study of the non-EGFR amplicons revealed 33 confirmed unique mutations in 17 genes, with TP53 being the most frequently mutated. Clinical relevance of these finding is discussed.Conclusions: Reporting of entire mutational spectrum revealed by targeted sequencing is questionable, at least until the clinically-driven guidelines on reporting of somatic mutations are established. The standardization of sequencing protocols, especially their data analysis components, requires assay-, disease-, and, in many cases, even sample-specific customization that could be performed only in cooperation with clinicians. [ABSTRACT FROM AUTHOR]

Background: The assessment of cell-free circulating DNA fragments, also known as a "liquid biopsy" of the patient's plasma, is an important source for the discovery and subsequent non-invasive monitoring of cancer and other pathological conditions. Although the nucleosome-guided fragmentation patterns of cell-free DNA (cfDNA) have not yet been studied in detail, non-random representation of cfDNA sequencies may reflect chromatin features in the tissue of origin at gene-regulation level. Results: In this study, we investigated the association between epigenetic landscapes of human tissues evident in the patterns of cfDNA in plasma by deep sequencing of human cfDNA samples. We have demonstrated that baseline characteristics of cfDNA fragmentation pattern are in concordance with the ones corresponding to cell lines-derived. To identify the loci differentially represented in cfDNA fragment, we mapped the transcription start sites within the sequenced cfDNA fragments and tested for association of these genomic coordinates with the relative strength and the patterns of gene expressions. Preselected sets of house-keeping and tissue specific genes were used as models for actively expressed and silenced genes. Developed measure of gene regulation was able to differentiate these two sets based on sequencing coverage near gene transcription start site. Conclusion: Experimental outcomes suggest that cfDNA retains characteristics previously noted in genome-wide analysis of chromatin structure, in particular, in MNase-seq assays. Thus far the analysis of the DNA fragmentation pattern may aid further developing of cfDNA based biomarkers for a variety of human conditions. [ABSTRACT FROM AUTHOR]

Background: The liver plays a central role in the maintenance of homeostasis and health in general. However, there is substantial inter-individual variation in hepatic gene expression, and although numerous genetic factors have been identified, less is known about the epigenetic factors. Results: By analyzing the methylomes and transcriptomes of 14 fetal and 181 adult livers, we identified 657 differentially methylated genes with adult-specific expression, these genes were enriched for transcription factor binding sites of HNF1A and HNF4A. We also identified 1,000 genes specific to fetal liver, which were enriched for GATA1, STAT5A, STAT5B and YY1 binding sites. We saw strong liver-specific effects of single nucleotide polymorphisms on both methylation levels (28,447 unique CpG sites (meQTL)) and gene expression levels (526 unique genes (eQTL)), at a false discovery rate (FDR) < 0.05. Of the 526 unique eQTL associated genes, 293 correlated significantly not only with genetic variation but also with methylation levels. The tissue-specificities of these associations were analyzed in muscle, subcutaneous adipose tissue and visceral adipose tissue. We observed that meQTL were more stable between tissues than eQTL and a very strong tissue-specificity for the identified associations between CpG methylation and gene expression. Conclusions: Our analyses generated a comprehensive resource of factors involved in the regulation of hepatic gene expression, and allowed us to estimate the proportion of variation in gene expression that could be attributed to genetic and epigenetic variation, both crucial to understanding differences in drug response and the etiology of liver diseases. [ABSTRACT FROM AUTHOR]

Publisher Correction to: BMC Bioinformatics (2021) 22:290 https://doi.org/10.1186/s12859-021-... Following the publication of the original article [[1]], the authors identified missing additional files and references. Publisher Correction to: TrancriptomeReconstructoR: data-driven annotation of complex transcriptomes The file describes an example pipeline for de novo calling of gene and transcript models by TranscriptomeReconstructoR, as well as detailed description of the algorithm. [Extracted from the article]