The extraordinary evolutionary history of the reticuloendotheliosis viruses

The reticuloendotheliosis viruses (REVs) comprise several closely related amphotropic retroviruses isolated from birds. These viruses exhibit several highly unusual characteristics that have not so far been adequately explained, including their extremely close relationship to mammalian retroviruses, and their presence as endogenous sequences within the genomes of certain large DNA viruses. We present evidence for an iatrogenic origin of REVs that accounts for these phenomena. Firstly, we identify endogenous retroviral fossils in mammalian genomes that share a unique recombinant structure with REVs—unequivocally demonstrating that REVs derive directly from mammalian retroviruses. Secondly, through sequencing of archived REV isolates, we confirm that contaminated Plasmodium lophurae stocks have been the source of multiple REV outbreaks in experimentally infected birds. Finally, we show that both phylogenetic and historical evidence support a scenario wherein REVs originated as mammalian retroviruses that were accidentally introduced into avian hosts in the late 1930s, during experimental studies of P. lophurae, and subsequently integrated into the fowlpox virus (FWPV) and gallid herpesvirus type 2 (GHV-2) genomes, generating recombinant DNA viruses that now circulate in wild birds and poultry. Our findings provide a novel perspective on the origin and evolution of REV, and indicate that horizontal gene transfer between virus families can expand the impact of iatrogenic transmission events

Genome maps across 26 human populations reveal population-specific patterns of structural variation.

Large structural variants (SVs) in the human genome are difficult to detect and study by conventional sequencing technologies. With long-range genome analysis platforms, such as optical mapping, one can identify large SVs (>2 kb) across the genome in one experiment. Analyzing optical genome maps of 154 individuals from the 26 populations sequenced in the 1000 Genomes Project, we find that phylogenetic population patterns of large SVs are similar to those of single nucleotide variations in 86% of the human genome, while ~2% of the genome has high structural complexity. We are able to characterize SVs in many intractable regions of the genome, including segmental duplications and subtelomeric, pericentromeric, and acrocentric areas. In addition, we discover ~60 Mb of non-redundant genome content missing in the reference genome sequence assembly. Our results highlight the need for a comprehensive set of alternate haplotypes from different populations to represent SV patterns in the genome

Mutational signatures in tumours induced by high and low energy radiation in Trp53 deficient mice.

Ionising radiation (IR) is a recognised carcinogen responsible for cancer development in patients previously treated using radiotherapy, and in individuals exposed as a result of accidents at nuclear energy plants. However, the mutational signatures induced by distinct types and doses of radiation are unknown. Here, we analyse the genetic architecture of mammary tumours, lymphomas and sarcomas induced by high (56Fe-ions) or low (gamma) energy radiation in mice carrying Trp53 loss of function alleles. In mammary tumours, high-energy radiation is associated with induction of focal structural variants, leading to genomic instability and Met amplification. Gamma-radiation is linked to large-scale structural variants and a point mutation signature associated with oxidative stress. The genomic architecture of carcinomas, sarcomas and lymphomas arising in the same animals are significantly different. Our study illustrates the complex interactions between radiation quality, germline Trp53 deficiency and tissue/cell of origin in shaping the genomic landscape of IR-induced tumours

Diversification of the Caenorhabditis heat shock response by Helitron transposable elements.

Heat Shock Factor 1 (HSF-1) is a key regulator of the heat shock response (HSR). Upon heat shock, HSF-1 binds well-conserved motifs, called Heat Shock Elements (HSEs), and drives expression of genes important for cellular protection during this stress. Remarkably, we found that substantial numbers of HSEs in multiple Caenorhabditis species reside within Helitrons, a type of DNA transposon. Consistent with Helitron-embedded HSEs being functional, upon heat shock they display increased HSF-1 and RNA polymerase II occupancy and up-regulation of nearby genes in C. elegans. Interestingly, we found that different genes appear to be incorporated into the HSR by species-specific Helitron insertions in C. elegans and C. briggsae and by strain-specific insertions among different wild isolates of C. elegans. Our studies uncover previously unidentified targets of HSF-1 and show that Helitron insertions are responsible for rewiring and diversifying the Caenorhabditis HSR

Transposable Elements, Inflammation, and Neurological Disease.

Transposable Elements (TE) are mobile DNA elements that can replicate and insert themselves into different locations within the host genome. Their propensity to self-propagate has a myriad of consequences and yet their biological significance is not well-understood. Indeed, retrotransposons have evaded evolutionary attempts at repression and may contribute to somatic mosaicism. Retrotransposons are emerging as potent regulatory elements within the human genome. In the diseased state, there is mounting evidence that endogenous retroelements play a role in etiopathogenesis of inflammatory diseases, with a disposition for both autoimmune and neurological disorders. We postulate that active mobile genetic elements contribute more to human disease pathogenesis than previously thought

Translocation and deletion breakpoints in cancer genomes are associated with potential non-B DNA-forming sequences

Gross chromosomal rearrangements (including translocations, deletions, insertions and duplications) are a hallmark of cancer genomes and often create oncogenic fusion genes. An obligate step in the generation of such gross rearrangements is the formation of DNA double-strand breaks (DSBs). Since the genomic distribution of rearrangement breakpoints is non-random, intrinsic cellular factors may predispose certain genomic regions to breakage. Notably, certain DNA sequences with the potential to fold into secondary structures [potential non-B DNA structures (PONDS); e.g. triplexes, quadruplexes, hairpin/cruciforms, Z-DNA and single-stranded looped-out structures with implications in DNA replication and transcription] can stimulate the formation of DNA DSBs. Here, we tested the postulate that these DNA sequences might be found at, or in close proximity to, rearrangement breakpoints. By analyzing the distribution of PONDS-forming sequences within ±500 bases of 19 947 translocation and 46 365 sequence-characterized deletion breakpoints in cancer genomes, we find significant association between PONDS-forming repeats and cancer breakpoints. Specifically, (AT)n, (GAA)n and (GAAA)n constitute the most frequent repeats at translocation breakpoints, whereas A-tracts occur preferentially at deletion breakpoints. Translocation breakpoints near PONDS-forming repeats also recur in different individuals and patient tumor samples. Hence, PONDS-forming sequences represent an intrinsic risk factor for genomic rearrangements in cancer genomes

Somatic retrotransposition in human cancer revealed by whole-genome and exome sequencing

Retrotransposons constitute a major source of genetic variation, and somatic retrotransposon insertions have been reported in cancer. Here, we applied TranspoSeq, a computational framework that identifies retrotransposon insertions from sequencing data, to whole genomes from 200 tumor/normal pairs across 11 tumor types as part of The Cancer Genome Atlas (TCGA) Pan-Cancer Project. In addition to novel germline polymorphisms, we find 810 somatic retrotransposon insertions primarily in lung squamous, head and neck, colorectal, and endometrial carcinomas. Many somatic retrotransposon insertions occur in known cancer genes. We find that high somatic retrotransposition rates in tumors are associated with high rates of genomic rearrangement and somatic mutation. Finally, we developed TranspoSeq-Exome to interrogate an additional 767 tumor samples with hybrid-capture exome data and discovered 35 novel somatic retrotransposon insertions into exonic regions, including an insertion into an exon of the PTEN tumor suppressor gene. The results of this large-scale, comprehensive analysis of retrotransposon movement across tumor types suggest that somatic retrotransposon insertions may represent an important class of structural variation in cancer.National Cancer Institute (U.S.) (grant U24CA143867)National Cancer Institute (U.S.) (grant U24CA126546

SomInaClust: detection of cancer genes based on somatic mutation patterns of inactivation and clustering

Background: With the advances in high throughput technologies, increasing amounts of cancer somatic mutation data are being generated and made available. Only a small number of (driver) mutations occur in driver genes and are responsible for carcinogenesis, while the majority of (passenger) mutations do not influence tumour biology. In this study, SomInaClust is introduced, a method that accurately identifies driver genes based on their mutation pattern across tumour samples and then classifies them into oncogenes or tumour suppressor genes respectively. Results: SomInaClust starts from the observation that oncogenes mainly contain mutations that, due to positive selection, cluster at similar positions in a gene across patient samples, whereas tumour suppressor genes contain a high number of protein-truncating mutations throughout the entire gene length. The method was shown to prioritize driver genes in 9 different solid cancers. Furthermore it was found to be complementary to existing similar-purpose methods with the additional advantages that it has a higher sensitivity, also for rare mutations (occurring in less than 1% of all samples), and it accurately classifies candidate driver genes in putative oncogenes and tumour suppressor genes. Pathway enrichment analysis showed that the identified genes belong to known cancer signalling pathways, and that the distinction between oncogenes and tumour suppressor genes is biologically relevant. Conclusions: SomInaClust was shown to detect candidate driver genes based on somatic mutation patterns of inactivation and clustering and to distinguish oncogenes from tumour suppressor genes. The method could be used for the identification of new cancer genes or to filter mutation data for further data-integration purposes