Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Integrative Genomics Viewer

The SARS-CoV-2 pandemic affecting the human respiratory system severely challenges public health and urgently demands for increasing our understanding of COVID-19 pathogenesis, especially host factors facilitating virus infection and replication. SARS-CoV-2 was reported to enter cells via binding to ACE2, followed by its priming by TMPRSS2. Here, we investigate ACE2 and TMPRSS2 expression levels and their distribution across cell types in lung tissue (twelve donors, 39,778 cells) and in cells derived from subsegmental bronchial branches (four donors, 17,521 cells) by single nuclei and single cell RNA sequencing, respectively. While TMPRSS2 is strongly expressed in both tissues, in the subsegmental bronchial branches ACE2 is predominantly expressed in a transient secretory cell type. Interestingly, these transiently differentiating cells show an enrichment for pathways related to RHO GTPase function and viral processes suggesting increased vulnerability for SARS-CoV-2 infection. Our data provide a rich resource for future investigations of COVID-19 infection and pathogenesis.

https://www.embopress.org/doi/epdf/10.15252/embj.20105114

SARS-CoV-2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells.

Genomic instability pathways in colorectal cancer (CRC) have been extensively studied, but the role of retrotransposition in colorectal carcinogenesis remains poorly understood. Although retrotransposons are usually repressed, they become active in several human cancers, in particular those of the gastrointestinal tract. Here we characterize retrotransposon insertions in 202 colorectal tumor whole genomes and investigate their associations with molecular and clinical characteristics. We found highly variable retrotransposon activity among tumors and identified recurrent insertions in 15 known cancer genes. In approximately 1% of the cases we identified insertions in APC, likely to be tumor-initiating events. Insertions were positively associated with the CpG island methylator phenotype and the genomic fraction of allelic imbalance. Clinically, high number of insertions was independently associated with poor disease-specific survival.

/pdf/retrotransposon-insertions-can-initiate-colorectal-cancer-3occaiyjkc.pdf

Retrotransposon insertions can initiate colorectal cancer and are associated with poor survival

Microsatellite instability (MSI) leads to accumulation of an excessive number of mutations in the genome, mostly small insertions and deletions. MSI colorectal cancers (CRCs), however, also contain more point mutations than microsatellite‐stable (MSS) tumors, yet they have not been as comprehensively studied. To identify candidate driver genes affected by point mutations in MSI CRC, we ranked genes based on mutation significance while correcting for replication timing and gene expression utilizing an algorithm, MutSigCV. Somatic point mutation data from the exome kit‐targeted area from 24 exome‐sequenced sporadic MSI CRCs and respective normals, and 12 whole‐genome‐sequenced sporadic MSI CRCs and respective normals were utilized. The top 73 genes were validated in 93 additional MSI CRCs. The MutSigCV ranking identified several well‐established MSI CRC driver genes and provided additional evidence for previously proposed CRC candidate genes as well as shortlisted genes that have to our knowledge not been linked to CRC before. Two genes, SMARCB1 and STK38L , were also functionally scrutinized, providing evidence of a tumorigenic role, for SMARCB1 mutations in particular.

/pdf/comprehensive-evaluation-of-coding-region-point-mutations-in-5czbrpytt1.pdf

Comprehensive evaluation of coding region point mutations in microsatellite‐unstable colorectal cancer

7 Review of the literature 9 1 Cancer 9 1.1 Oncogenes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.2 Tumor suppressor genes . . . . . . . . . . . . . . . . . . . . . . . . 11 1.3 Genomic instability . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2 Genetic predisposition to cancer 12 2.1 Familial aggregation and heritability . . . . . . . . . . . . . . . . . 13 2.2 Linkage and association studies . . . . . . . . . . . . . . . . . . . . 13 2.3 Next-generation sequencing . . . . . . . . . . . . . . . . . . . . . . 16 2.4 Genetic testing for cancer risk . . . . . . . . . . . . . . . . . . . . . 17 3 Colorectal cancer 18 3.1 Epidemiologic and clinical aspects . . . . . . . . . . . . . . . . . . 18 3.2 Molecular pathogenesis . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.3 Hereditary colorectal cancer syndromes . . . . . . . . . . . . . . . 22 3.3.1 Lynch syndrome . . . . . . . . . . . . . . . . . . . . . . . . 23 3.3.2 Gastrointestinal polyposis syndromes . . . . . . . . . . . . . 24 3.3.3 Other hereditary syndromes . . . . . . . . . . . . . . . . . . 29 3.4 Moderate-penetrance variants . . . . . . . . . . . . . . . . . . . . . 32 3.5 Low-penetrance variants . . . . . . . . . . . . . . . . . . . . . . . . 33

Genetic predisposition to colorectal cancer in young patients and in the general population

Next-generation sequencing (NGS) is being routinely applied in life sciences and clinical practice, where the interpretation of the resulting massive data has become a critical challenge Computational workflows, such as the Broad GATK, have been established to take raw sequencing data and produce processed data for downstream analyses Consequently, results of these computationally demanding workflows, consisting of eg sequence alignment and variant calling, are increasingly being provided for customers by sequencing and bioinformatics facilities However, downstream variant analysis, whole-genome level in particular, has been lacking a multi-purpose tool, which could take advantage of rapidly growing genomic information and integrate genetic variant, sequence, genomic annotation and regulatory (eg ENCODE) data interactively and in a visual fashion Here we introduce a highly efficient and user-friendly software, BasePlayer (http://baseplayerfi), for biological discovery in large-scale NGS data BasePlayer enables tightly integrated comparative variant analysis and visualization of thousands of NGS data samples and millions of variants, with numerous applications in disease, regulatory and population genomics Although BasePlayer has been designed primarily for whole-genome and exome sequencing data, it is well-suited to various study settings, diseases and organisms by supporting standard and upcoming file formats BasePlayer transforms an ordinary desktop computer into a large-scale genomic research platform, enabling also a non-technical user to perform complex comparative variant analyses, population frequency filtering and genome level annotations under intuitive, scalable and highly-responsive user interface to facilitate everyday genetic research as well as the search of novel discoveries

/pdf/baseplayer-versatile-analysis-software-for-large-scale-1b4jjwchmg.pdf

BasePlayer: Versatile Analysis Software for Large-scale Genomic Variant Discovery

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BasePlayer: Versatile Analysis Software for Large-scale Genomic Variant Discovery