scholarly journals Genomic basis for RNA alterations revealed by whole-genome analyses of 27 cancer types

2017 ◽  
Author(s):  
◽  
Claudia Calabrese ◽  
Natalie R. Davidson ◽  
Nuno A. Fonseca ◽  
Yao He ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Specific Expression ◽  
Alu Elements ◽  
Cancer Types ◽  
Genome Analyses ◽  
Gene Alterations

AbstractWe present the most comprehensive catalogue of cancer-associated gene alterations through characterization of tumor transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes project. Using matched whole-genome sequencing data, we attributed RNA alterations to germline and somatic DNA alterations, revealing likely genetic mechanisms. We identified 444 associations of gene expression with somatic non-coding single-nucleotide variants. We found 1,872 splicing alterations associated with somatic mutation in intronic regions, including novel exonization events associated with Alu elements. Somatic copy number alterations were the major driver of total gene and allele-specific expression (ASE) variation. Additionally, 82% of gene fusions had structural variant support, including 75 of a novel class called “bridged” fusions, in which a third genomic location bridged two different genes. Globally, we observe transcriptomic alteration signatures that differ between cancer types and have associations with DNA mutational signatures. Given this unique dataset of RNA alterations, we also identified 1,012 genes significantly altered through both DNA and RNA mechanisms. Our study represents an extensive catalog of RNA alterations and reveals new insights into the heterogeneous molecular mechanisms of cancer gene alterations.

scholarly journals Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing

2018 ◽  
Author(s):  
Isidro Cortés-Ciriano ◽  
June-Koo Lee ◽  
Ruibin Xi ◽  
Dhawal Jain ◽  
Youngsook L. Jung ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Human Cancer ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
End Joining ◽  
Cancer Types ◽  
Non Homologous End Joining

SummaryChromothripsis is a newly discovered mutational phenomenon involving massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in cancer suggest that chromothripsis may be far more common than initially inferred from low resolution DNA copy number data. Here, we analyze the patterns of chromothripsis across 2,658 tumors spanning 39 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of >50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy number states, a considerable fraction of the events involves multiple chromosomes as well as additional structural alterations. In addition to non-homologous end-joining, we detect signatures of replicative processes and templated insertions. Chromothripsis contributes to oncogene amplification as well as to inactivation of genes such as mismatch-repair related genes. These findings show that chromothripsis is a major process driving genome evolution in human cancer.

scholarly journals A simplified workflow for the analysis of whole-genome sequencing data from Pristionchus pacificus mutant lines

2020 ◽  
Author(s):  
Christian Rödelsperger
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Model Organism ◽  
Model Systems ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Pristionchus Pacificus ◽  
Mutant Lines

AbstractNematodes are attractive model systems to understand the genetic basis of various biological processes ranging from development to complex behaviors. In particular, mutagenesis experiments combined with whole-genome sequencing has been proven as one of the most effective methods to identify core players of multiple biological pathways. To enable experimentalists to apply such integrative genetic and bioinformatic analysis in the case of the satellite model organism Pristionchus pacificus, I present a simplified workflow for the analysis of whole-genome data from mutant lines and corresponding mapping panels. Individual components are based on well-maintained and widely used software packages and are extended by 50 lines of code for the analysis and visualization of allele frequencies. The effectiveness of this workflow is demonstrated by an application to recently generated data of a P. pacificus mutant line, where it reduced the number of candidate mutations from an initial set of 3,500 single nucleotide variants to ten.

scholarly journals Somatic mutation landscape reveals differential variability of cell-of-origin for primary liver cancer

2019 ◽  
Author(s):  
Kyungsik Ha ◽  
Masashi Fujita ◽  
Rosa Karlić ◽  
Sungmin Yang ◽  
Yujin Hoshida ◽  
...  
Keyword(s):  
Liver Cancer ◽  
Progenitor Cells ◽  
Genome Sequencing ◽  
Primary Liver Cancer ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Cell Of Origin ◽  
Sequencing Data ◽  
Liver Cancers ◽  
Cancer Types

AbstractBackgroundPrimary liver tissue cancers display consistent increase in global disease burden and mortality. Identification of cell-of-origins for primary liver cancers would be a necessity to expand options for designing relevant therapeutics and preventive medicine for these cancer types. Previous reports on cell-of-origin for primary liver cancers was mainly from animal studies, and integrative research utilizing human specimen data was poorly established.MethodsWe analyzed a whole-genome sequencing data set for a total of 363 tumor and progenitor tissues along with 423 normal tissue epigenomic marks to predict the cell-of-origin for primary liver cancer subtypes.ResultsDespite the mixed histological features, the predicted cell-of-origin for mixed hepatocellular carcinoma / intrahepatic cholangiocarcinoma were uniformly predicted as a hepatocytic origin. Individual sample-level prediction revealed differential level of cell-of-origin heterogeneity depending on the primary liver cancer types, with more heterogeneity observed in intrahepatic cholangiocarcinomas. Additional analyses on the whole genome sequencing data of hepatic progenitor cells suggest these progenitor cells might not a direct cell-of-origin for liver cancers.ConclusionsThese results provide novel insights on the heterogeneous nature and potential contributors of cell-of-origin predictions for primary liver cancers.

scholarly journals Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes

2018 ◽  
Author(s):  
Stefan C. Dentro ◽  
Ignaty Leshchiner ◽  
Kerstin Haase ◽  
Maxime Tarabichi ◽  
Jeff Wintersinger ◽  
...  
Keyword(s):  
Tumor Heterogeneity ◽  
Human Cancer ◽  
Driver Mutations ◽  
Whole Genome Sequencing Data ◽  
Tumor Evolution ◽  
Driver Gene ◽  
Cancer Type ◽  
Whole Genome ◽  
Sequencing Data ◽  
Cancer Types

SUMMARYIntra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin and drivers of ITH across cancer types are poorly understood. To address this question, we extensively characterize ITH across whole-genome sequences of 2,658 cancer samples, spanning 38 cancer types. Nearly all informative samples (95.1%) contain evidence of distinct subclonal expansions, with frequent branching relationships between subclones. We observe positive selection of subclonal driver mutations across most cancer types, and identify cancer type specific subclonal patterns of driver gene mutations, fusions, structural variants and copy-number alterations, as well as dynamic changes in mutational processes between subclonal expansions. Our results underline the importance of ITH and its drivers in tumor evolution, and provide an unprecedented pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data.

What can go wrong in the non-coding genome and how to interpret whole genome sequencing data

2021 ◽  
Vol 33 (2) ◽  
pp. 121-131
Author(s):  
Heiko Krude ◽  
Stefan Mundlos ◽  
Nancy Christine Øien ◽  
Robert Opitz ◽  
Markus Schuelke
Keyword(s):  
Molecular Mechanisms ◽  
Mutation Detection ◽  
Genetic Diseases ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Triplet Repeats ◽  
Routine Diagnostics ◽  
Disease Mechanisms ◽  
Whole Exome

Abstract Whole exome sequencing discovers causative mutations in less than 50 % of rare disease patients, suggesting the presence of additional mutations in the non-coding genome. So far, non-coding mutations have been identified in less than 0.2 % of individuals with genetic diseases listed in the ClinVar database and exhibit highly diverse molecular mechanisms. In contrast to our capability to sequence the whole genome, our ability to discover and functionally confirm such non-coding mutations is lagging behind severely. We discuss the problems and present examples of confirmed mutations in deep intronic sequences, non-coding triplet repeats, enhancers, and larger structural variants and highlight their proposed disease mechanisms. Finally, we discuss the type of data that would be required to establish non-coding mutation detection in routine diagnostics.

scholarly journals Selective and mechanistic sources of recurrent rearrangements across the cancer genome

2017 ◽  
Author(s):  
Jeremiah A Wala ◽  
Ofer Shapira ◽  
Yilong Li ◽  
David Craft ◽  
Steven E Schumacher ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Cancer Genome ◽  
Whole Genome Sequencing Data ◽  
Open Chromatin ◽  
Whole Genome ◽  
Tumor Type ◽  
Sequencing Data ◽  
Specific Expression ◽  
Order Of Magnitude

AbstractCancer cells can acquire profound alterations to the structure of their genomes, including rearrangements that fuse distant DNA breakpoints. We analyze the distribution of somatic rearrangements across the cancer genome, using whole-genome sequencing data from 2,693 tumor-normal pairs. We observe substantial variation in the density of rearrangement breakpoints, with enrichment in open chromatin and sites with high densities of repetitive elements. After accounting for these patterns, we identify significantly recurrent breakpoints (SRBs) at 52 loci, including novel SRBs near BRD4 and AKR1C3. Taking into account both loci fused by a rearrangement, we observe different signatures resembling either single breaks followed by strand invasion or two separate breaks that become joined. Accounting for these signatures, we identify 90 pairs of loci that are significantly recurrently juxtaposed (SRJs). SRJs are primarily tumor-type specific and tend to involve genes with tissue-specific expression. SRJs were frequently associated with disruption of topology-associated domains, juxtaposition of enhancer elements, and increased expression of neighboring genes. Lastly, we find that the power to detect SRJs decreases for short rearrangements, and that reliable detection of all driver SRJs will require whole-genome sequencing data from an order of magnitude more cancer samples than currently available.

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