Project description:Somatic genome rearrangements are thought to play important roles in cancer development. We optimized a long span paired-end-tag (PET) sequencing approach using 10 Kb genomic DNA inserts to study human genome structural variations (SVs). The use of 10 Kb insert size allows the identification of breakpoints within repetitive or homology containing regions of a few Kb in size and results in a higher physical coverage compared to small insert libraries with the same sequencing effort. We have applied this approach to comprehensively characterize the SVs of 15 cancer and 2 non-cancer genomes and used a filtering approach to strongly enrich for somatic SVs in the cancer genomes. Our analyses revealed that most inversions, deletions, and insertions are germline SVs, whereas tandem duplications, unpaired inversions, inter-chromosomal translocations, and complex rearrangements are overrepresented among somatic rearrangements in cancer genomes. We demonstrate that the quantitative and connective nature of DNA-PET data is precise in delineating the genealogy of complex rearrangement events, we observe signatures which are compatible with breakage-fusion-bridge cycles, and discover that large duplications are among the initial rearrangements that trigger genome instability for extensive amplification in epithelial cancers. Structural variations of 15 human cancer samples and 2 human normal samples were identified by long span paired-end sequencing
Project description:We developed a computational framework that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression. We demonstrate the utility of this framework using a melanoma dataset. Our analysis correctly identified known drivers of melanoma and predicted multiple novel tumor dependencies. Two dependencies, TBC1D16 and RAB27A, confirmed empirically, suggest that abnormal regulation of protein trafficking contributes to proliferation in melanoma. Together, these results demonstrate the ability of integrative Bayesian approaches to identify novel candidate drivers with biological, and possibly therapeutic, importance in cancer.
Project description:We performed whole-genome sequencing of 42 paired tumor/normal EPD genomes and analyzed somatically acquired single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes
Project description:We performed whole-genome sequencing of 37 paired tumor/normal OS genomes and analyzed somatically acquired single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes
Project description:We performed whole-genome sequencing of 42 paired tumor/normal LGG genomes and analyzed somatically acquired single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes
Project description:We performed whole-genome sequencing of 13 paired tumor/normal Rhabdomyosarcoma genomes and analyzed somatically acquired single nucleotide variations SNVs, insertion/deletions, structural variations and copy number variations in the cancer genomes
Project description:We developed a computational framework that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression. We demonstrate the utility of this framework using a melanoma dataset. Our analysis correctly identified known drivers of melanoma and predicted multiple novel tumor dependencies. Two dependencies, TBC1D16 and RAB27A, confirmed empirically, suggest that abnormal regulation of protein trafficking contributes to proliferation in melanoma. Together, these results demonstrate the ability of integrative Bayesian approaches to identify novel candidate drivers with biological, and possibly therapeutic, importance in cancer. Effects of knockdown of two genes -TBC1D16 and RAB27A - were tested on four cell lines each, each of them with two different hairpins. As a control, we used a hairping targeting GFP. shGFP experiments were done in biological duplicates or more. The second WM1976-shGFP sample was identified as an outlier by a PCA analysis and was excluded from our analysis.
Project description:The Pan-Cancer Analysis of Whole Genomes (PCAWG) study is an international collaboration to identify common patterns of mutation in more than 2,800 cancer whole genomes from the International Cancer Genome Consortium. Building upon previous work which examined cancer coding regions, this project is exploring the nature and consequences of somatic and germline variations in both coding and non-coding regions, with specific emphasis on cis-regulatory sites, non-coding RNAs, and large-scale structural alterations. Read more on the <a href=\"https://dcc.icgc.org/pcawg\" target=\"_blank\">project website</a>.<br>This is a subset featuring RNA-seq transcription profiling data of 27 cancer subtypes in 19 tissues. Some donors have matched normal tissue. As general reference, a subset of normal tissue samples from the GTEx project were included in this experiment.
Project description:The Pan-Cancer Analysis of Whole Genomes (PCAWG) study is an international collaboration to identify common patterns of mutation in more than 2,800 cancer whole genomes from the International Cancer Genome Consortium. Building upon previous work which examined cancer coding regions, this project is exploring the nature and consequences of somatic and germline variations in both coding and non-coding regions, with specific emphasis on cis-regulatory sites, non-coding RNAs, and large-scale structural alterations. Read more on the <a href=\"https://dcc.icgc.org/pcawg\" target=\"_blank\">project website</a>.<br>This is a subset featuring RNA-seq transcription profiling data of 27 cancer subtypes in 19 tissues. Some donors have matched normal tissue.<br>This is the alternative view of the experiment for Expression Atlas to show gene expression per donor.
Project description:Structural variation has played an important role in the evolutionary restructuring of human and great ape genomes. We generated approximately 10-fold genomic sequence coverage from a western lowland gorilla and integrated these data into a physical and cytogenetic framework to develop a comprehensive view of structural variation. We discovered and validated over 7,665 structural changes within the gorilla lineage including sequence resolution of inversions, deletions, duplications and retrotranspositions. A comparison with human and other ape genomes shows that the gorilla genome has been subjected to the highest rate of segmental duplication. We show that both the gorilla and chimpanzee genomes have experienced independent yet parallel patterns of structural mutation that have not occurred in humans, including the formation of subtelomeric heterochromatic caps, the hyperexpansion of segmental duplications and bursts of retroviral integrations. Our analysis suggests that the chimpanzee and gorilla genomes are structurally more derived than either orangutan or human. all combinations of human, chimpanzee and gorilla are used in 2 different arrayCGH designs. First, a standard 2.1 was used to detected CNVs, and second, we used a custom designed arrayCGH to validate gorilla specific duplications and deletions