Zika vector transmission risk in temperate Australia: a vector competence study

Background: Zika virus is an emerging pathogen of global importance. It has been responsible for recent outbreaks in the Americas and in the Pacific region. This study assessed five different mosquito species from the temperate climatic zone in Australia and included Aedes albopictus as a potentially invasive species. Methods: Mosquitoes were orally challenged by membrane feeding with Zika virus strain of Cambodia 2010 origin, belonging to the Asian clade. Virus infection and dissemination were assessed by quantitative PCR on midgut and carcass after dissection. Transmission was assessed by determination of cytopathogenic effect of saliva (CPE) on Vero cells, followed by determination of 50% tissue culture infectious dose (TCID50) for CPE positive samples. Additionally, the presence of Wolbachia endosymbiont infection was assessed by qPCR and standard PCR. Results: Culex mosquitoes were found unable to present Zika virus in saliva, as demonstrated by molecular as well as virological methods. Aedes aegypti, was used as a positive control for Zika infection and showed a high level of virus infection, dissemination and transmission. Local Aedes species, Ae. notoscriptus and, to a lesser degree, Ae. camptorhynchus were found to expel virus in their saliva and contained viral nucleic acid within the midgut. Molecular assessment identified low or no dissemination for these species, possibly due to low virus loads. Ae. albopictus from Torres Strait islands origin was shown as an efficient vector. Cx quinquefasciatus was shown to harbour Wolbachia endosymbionts at high prevalence, whilst no Wolbachia was found in Cx annulirostris. The Australian Ae. albopictus population was shown to harbour Wolbachia at high frequency. Conclusions: The risk of local Aedes species triggering large Zika epidemics in the southern parts of Australia is low. The potentially invasive Ae. albopictus showed high prevalence of virus in the saliva and constitutes a potential threat if this mosquito species becomes established in mainland Australia. Complete risk analysis of Zika transmission in the temperate zone would require an assessment of the impact of temperature on Zika virus replication within local and invasive mosquito species

RNASeq Analysis of Aedes albopictus Mosquito Midguts after Chikungunya Virus Infection

Chikungunya virus (CHIKV) is an emerging pathogen around the world and causes significant morbidity in patients. A single amino acid mutation in the envelope protein of CHIKV has led to a shift in vector preference towards Aedes albopictus. While mosquitoes are known to mount an antiviral immune response post-infection, molecular interactions during the course of infection at the tissue level remain largely uncharacterised. We performed whole transcriptome analysis on dissected midguts of Aedes albopictus infected with CHIKV to identify differentially expressed genes. For this, RNA was extracted at two days post-infection (2-dpi) from pooled midguts. We initially identified 25 differentially expressed genes (p-value < 0.05) when mapped to a reference transcriptome. Further, multiple differentially expressed genes were identified from a custom de novo transcriptome, which was assembled using the reads that did not align with the reference genome. Thirteen of the identified transcripts, possibly involved in immunity, were validated by qRT-PCR. Homologues of seven of these genes were also found to be significantly upregulated in Aedes aegypti midguts 2 dpi, indicating a conserved mechanism at play. These results will help us to characterise the molecular interaction between Aedes albopictus and CHIKV and can be utilised to reduce the impact of this viral infection

Additional file 1: Figure S1. of PathOS: a decision support system for reporting high throughput sequencing of cancers in clinical diagnostic laboratories

PathOSAnalysisWorkflow.pdf: Schematic of the typical data analysis workflow from sequencer to diagnostic pathology report. (PDF 65 kb

The repertoire of mutational signatures in human cancer

Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature 1. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium 2 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we characterized mutational signatures using 84,729,690 somatic mutations from 4,645 whole-genome and 19,184 exome sequences that encompass most types of cancer. We identified 49 single-base-substitution, 11 doublet-base-substitution, 4 clustered-base-substitution and 17 small insertion-and-deletion signatures. The substantial size of our dataset, compared with previous analyses 3–15, enabled the discovery of new signatures, the separation of overlapping signatures and the decomposition of signatures into components that may represent associated—but distinct—DNA damage, repair and/or replication mechanisms. By estimating the contribution of each signature to the mutational catalogues of individual cancer genomes, we revealed associations of signatures to exogenous or endogenous exposures, as well as to defective DNA-maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes that contribute to the development of human cancer

Integrative pathway enrichment analysis of multivariate omics data

Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations

Divergent mutational processes distinguish hypoxic and normoxic tumours

Many primary tumours have low levels of molecular oxygen (hypoxia), and hypoxic tumours respond poorly to therapy. Pan-cancer molecular hallmarks of tumour hypoxia remain poorly understood, with limited comprehension of its associations with specific mutational processes, non-coding driver genes and evolutionary features. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumour types, we quantify hypoxia in 1188 tumours spanning 27 cancer types. Elevated hypoxia associates with increased mutational load across cancer types, irrespective of underlying mutational class. The proportion of mutations attributed to several mutational signatures of unknown aetiology directly associates with the level of hypoxia, suggesting underlying mutational processes for these signatures. At the gene level, driver mutations in TP53, MYC and PTEN are enriched in hypoxic tumours, and mutations in PTEN interact with hypoxia to direct tumour evolutionary trajectories. Overall, hypoxia plays a critical role in shaping the genomic and evolutionary landscapes of cancer

Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer

Chromatin is folded into successive layers to organize linear DNA. Genes within the same topologically associating domains (TADs) demonstrate similar expression and histone-modification profiles, and boundaries separating different domains have important roles in reinforcing the stability of these features. Indeed, domain disruptions in human cancers can lead to misregulation of gene expression. However, the frequency of domain disruptions in human cancers remains unclear. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumor types, we analyzed 288,457 somatic structural variations (SVs) to understand the distributions and effects of SVs across TADs. Notably, SVs can lead to the fusion of discrete TADs, and complex rearrangements markedly change chromatin folding maps in the cancer genomes. Notably, only 14% of the boundary deletions resulted in a change in expression in nearby genes of more than twofold

Genomic footprints of activated telomere maintenance mechanisms in cancer

Cancers require telomere maintenance mechanisms for unlimited replicative potential. They achieve this through TERT activation or alternative telomere lengthening associated with ATRX or DAXX loss. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we dissect whole-genome sequencing data of over 2500 matched tumor-control samples from 36 different tumor types aggregated within the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium to characterize the genomic footprints of these mechanisms. While the telomere content of tumors with ATRX or DAXX mutations (ATRX/DAXXtrunc) is increased, tumors with TERT modifications show a moderate decrease of telomere content. One quarter of all tumor samples contain somatic integrations of telomeric sequences into non-telomeric DNA. This fraction is increased to 80% prevalence in ATRX/DAXXtrunc tumors, which carry an aberrant telomere variant repeat (TVR) distribution as another genomic marker. The latter feature includes enrichment or depletion of the previously undescribed singleton TVRs TTCGGG and TTTGGG, respectively. Our systematic analysis provides new insight into the recurrent genomic alterations associated with telomere maintenance mechanisms in cancer

Patterns of somatic structural variation in human cancer genomes

AbstractA key mutational process in cancer is structural variation, in which rearrangements delete, amplify or reorder genomic segments that range in size from kilobases to whole chromosomes1–7. Here we develop methods to group, classify and describe somatic structural variants, using data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumour types8. Sixteen signatures of structural variation emerged. Deletions have a multimodal size distribution, assort unevenly across tumour types and patients, are enriched in late-replicating regions and correlate with inversions. Tandem duplications also have a multimodal size distribution, but are enriched in early-replicating regions—as are unbalanced translocations. Replication-based mechanisms of rearrangement generate varied chromosomal structures with low-level copy-number gains and frequent inverted rearrangements. One prominent structure consists of 2–7 templates copied from distinct regions of the genome strung together within one locus. Such cycles of templated insertions correlate with tandem duplications, and—in liver cancer—frequently activate the telomerase gene TERT. A wide variety of rearrangement processes are active in cancer, which generate complex configurations of the genome upon which selection can act

A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns

In cancer, the primary tumour’s organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA