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To determine early somatic changes in high-grade serous ovarian cancer (HGSOC), we performed whole genome sequencing on a rare collection of 16 low stage HGSOCs. The majority showed extensive structural alterations (one had an ultramutated profile), exhibited high levels of p53 immunoreactivity, and harboured a TP53 mutation, deletion or inactivation. BRCA1 and BRCA2 mutations were observed in two tumors, with nine showing evidence of a homologous recombination (HR) defect. Combined Analysis with The Cancer Genome Atlas (TCGA) indicated that low and late stage HGSOCs have similar mutation and copy number profiles. We also found evidence that deleterious TP53 mutations are the earliest events, followed by deletions or loss of heterozygosity (LOH) of chromosomes carrying TP53, BRCA1 or BRCA2. Inactivation of HR appears to be an early event, as 62.5% of tumours showed a LOH pattern suggestive of HR defects. Three tumours with the highest ploidy had little genome-wide LOH, yet one of these had a homozygous somatic frame-shift BRCA2 mutation, suggesting that some carcinomas begin as tetraploid then descend into diploidy accompanied by genome-wide LOH. Lastly, we found evidence that structural variants (SV) cluster in HGSOC, but are absent in one ultramutated tumor, providing insights into the pathogenesis of low stage HGSOC.

The miRBase database aims to provide integrated interfaces to comprehensive microRNA sequence data, annotation and predicted gene targets. miRBase takes over functionality from the microRNA Registry and fulfils three main roles: the miRBase Registry acts as an independent arbiter of microRNA gene nomenclature, assigning names prior to publication of novel miRNA sequences. miRBase Sequences is the primary online repository for miRNA sequence data and annotation. miRBase Targets is a comprehensive new database of predicted miRNA target genes. miRBase is available at http://microrna.sanger.ac.uk/.

Ovarian cancer is a clinically and molecularly heterogeneous disease. The driving forces behind this variability are unknown. Here, we report wide variation in the expression of the DNA cytosine deaminase APOBEC3B, with elevated expression in the majority of ovarian cancer cell lines (three SDs above the mean of normal ovarian surface epithelial cells) and high-grade primary ovarian cancers. APOBEC3B is active in the nucleus of several ovarian cancer cell lines and elicits a biochemical preference for deamination of cytosines in 5′-TC dinucleotides. Importantly, examination of whole-genome sequence from 16 ovarian cancers reveals that APOBEC3B expression correlates with total mutation load as well as elevated levels of transversion mutations. In particular, high APOBEC3B expression correlates with C-to-A and C-to-G transversion mutations within 5′-TC dinucleotide motifs in early-stage high-grade serous ovarian cancer genomes, suggesting that APOBEC3B-catalyzed genomic uracil lesions are further processed by downstream DNA "repair" enzymes including error-prone translesion polymerases. These data identify a potential role for APOBEC3B in serous ovarian cancer genomic instability. Cancer Res; 73(24); 7222–31. ©2013 AACR.

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.

Summary The Tasmanian devil (Sarcophilus harrisii), the largest marsupial carnivore, is endangered due to a transmissible facial cancer spread by direct transfer of living cancer cells through biting. Here we describe the sequencing, assembly, and annotation of the Tasmanian devil genome and whole-genome sequences for two geographically distant subclones of the cancer. Genomic analysis suggests that the cancer first arose from a female Tasmanian devil and that the clone has subsequently genetically diverged during its spread across Tasmania. The devil cancer genome contains more than 17,000 somatic base substitution mutations and bears the imprint of a distinct mutational process. Genotyping of somatic mutations in 104 geographically and temporally distributed Tasmanian devil tumors reveals the pattern of evolution and spread of this parasitic clonal lineage, with evidence of a selective sweep in one geographical area and persistence of parallel lineages in other populations. PaperClip, Graphical Abstract Highlights ► Whole-genome sequences of the Tasmanian devil and two distant cancer subclones ► The Tasmanian devil cancer lineage originated recently in a female devil ► The devil cancer genome is relatively stable despite ongoing evolution ► Clonal divergence and geographic spread elucidated through patterns of mutation, Whole-genome sequences of the Tasmanian devil and two devil cancer subclones suggest that the cancer first arose from a female devil and that the clone has subsequently genetically diverged during its spread across Tasmania.

The human X chromosome has a unique biology that was shaped by its evolution as the sex chromosome shared by males and females. We have determined 99.3% of the euchromatic sequence of the X chromosome. Our analysis illustrates the autosomal origin of the mammalian sex chromosomes, the stepwise process that led to the progressive loss of recombination between X and Y, and the extent of subsequent degradation of the Y chromosome. LINE1 repeat elements cover one-third of the X chromosome, with a distribution that is consistent with their proposed role as way stations in the process of X-chromosome inactivation. We found 1,098 genes in the sequence, of which 99 encode proteins expressed in testis and in various tumour types. A disproportionately high number of mendelian diseases are documented for the X chromosome. Of this number, 168 have been explained by mutations in 113 X-linked genes, which in many cases were characterized with the aid of the DNA sequence.

Among bacteria, many species have synonymous codon usage patterns that have been influenced by natural selection for those codons that are translated more accurately and/or efficiently. However, in other species selection appears to have been ineffective. Here, we introduce a population genetics-based model for quantifying the extent to which selection has been effective. The approach is applied to 80 phylogenetically diverse bacterial species for which whole genome sequences are available. The strength of selected codon usage bias, S, is found to vary substantially among species; in 30% of the genomes examined, there was no significant evidence that selection had been effective. Values of S are highly positively correlated with both the number of rRNA operons and the number of tRNA genes. These results are consistent with the hypothesis that species exposed to selection for rapid growth have more rRNA operons, more tRNA genes and more strongly selected codon usage bias. For example, Clostridium perfringens, the species with the highest value of S, can have a generation time as short as 7 min.

Pseudomonas aeruginosa PA01 has a large (6.7 Mbp) genome with a high (67%) G 1 C content. Codon usage in this species is dominated by this compositional bias, with the average G 1 C content at synonymously variable third positions of codons being 83%. Nevertheless, there is some variation of synonymous codon usage among genes. The nature and causes of this variation were investigated using multivariate statistical analyses. Three trends were identified. The major source of variation was attributable to genes with unusually low G 1 C content that are probably due to horizontal transfer. A lesser trend among genes was associated with the preferential use of putatively translationally optimal codons in genes expressed at high levels. In addition, genes on the leading strand of replication were on average more G 1 T-rich. Our findings contradict the results of two previous analyses, and the reasons for the discrepancies are discussed. q 2002 Elsevier Science B.V. All rights reserved.

Chronic lymphocytic leukemia is characterized by relapse after treatment and chemotherapy resistance. Similarly, in other malignancies leukemia cells accumulate mutations during growth, forming heterogeneous cell populations that are subject to Darwinian selection and may respond differentially to treatment. There is therefore a clinical need to monitor changes in the subclonal composition of cancers during disease progression. Here, we use whole-genome sequencing to track subclonal heterogeneity in 3 chronic lymphocytic leukemia patients subjected to repeated cycles of therapy. We reveal different somatic mutation profiles in each patient and use these to establish probable hierarchical patterns of subclonal evolution, to identify subclones that decline or expand over time, and to detect founder mutations. We show that clonal evolution patterns are heterogeneous in individual patients. We conclude that genome sequencing is a powerful and sensitive approach to monitor disease progression repeatedly at the molecular level. If applied to future clinical trials, this approach might eventually influence treatment strategies as a tool to individualize and direct cancer treatment.

All cancers carry somatic mutations. A subset of these somatic alterations, termed driver mutations, confer selective growth advantage and are implicated in cancer development, whereas the remainder are passengers. Here we have sequenced the genomes of a malignant melanoma and a lymphoblastoid cell line from the same person, providing the first comprehensive catalogue of somatic mutations from an individual cancer. The catalogue provides remarkable insights into the forces that have shaped this cancer genome. The dominant mutational signature reflects DNA damage due to ultraviolet light exposure, a known risk factor for malignant melanoma, whereas the uneven distribution of mutations across the genome, with a lower prevalence in gene footprints, indicates that DNA repair has been preferentially deployed towards transcribed regions. The results illustrate the power of a cancer genome sequence to reveal traces of the DNA damage, repair, mutation and selection processes that were operative years before the cancer became symptomatic.

Network analysis transcends conventional pairwise approaches to data analysis as the context of components in a network graph can be taken into account. Such approaches are increasingly being applied to genomics data, where functional linkages are used to connect genes or proteins. However, while microarray gene expression datasets are now abundant and of high quality, few approaches have been developed for analysis of such data in a network context. We present a novel approach for 3-D visualisation and analysis of transcriptional networks generated from microarray data. These networks consist of nodes representing transcripts connected by virtue of their expression profile similarity across multiple conditions. Analysing genome-wide gene transcription across 61 mouse tissues, we describe the unusual topography of the large and highly structured networks produced, and demonstrate how they can be used to visualise, cluster, and mine large datasets. This approach is fast, intuitive, and versatile, and allows the identification of biological relationships that may be missed by conventional analysis techniques. This work has been implemented in a freely available open-source application named BioLayout Express 3D., Author Summary This paper describes a novel approach for analysis of gene expression data. In this approach, normalized gene expression data is transformed into a graph where nodes in the graph represent transcripts connected to each other by virtue of their coexpression across multiple tissues or samples. The graph paradigm has many advantages for such analyses. Graph clustering of the derived network performs extremely well in comparison to traditional pairwise schemes. We show that this approach is robust and able to accommodate large datasets such as the Genomics Institute of the Novartis Research Foundation mouse tissue atlas. The entire approach and algorithms are combined into a single open-source JAVA application that allows users to perform this analysis and further mining on their own data and to visualize the results interactively in 3-D. The approach is not limited to gene expression data but would also be useful for other complex biological datasets. We use the method to investigate the relationship between the phylogenetic age of transcripts and their tissue specificity.

Evidence is emerging that micro RNA (miRNA) is an important and potentially polymorphic regulatory layer for silencing gene expression in vivo. Knowledge of miRNA targeting may help to elucidate the function of many human genes in common diseases, providing a powerful target validation technology. Accurate in silico prediction of miRNA targets in mRNA is a critical capability, allowing effective evaluation of the impact of variation on the creation, strengthening, weakening and destruction of miRNA binding sites. Application of such analyses identifies thousands of single-nucleotide polymorphisms, which may potentially impact miRNA regulation of mRNA. The authors believe this information may offer a real opportunity to study miRNA function at a number of levels. First, sequence-focused analysis will help to define the functional boundaries of miRNA target binding. Second, one may be able to identify miRNA target variants in mRNA with a direct role in human disease, which may be valuable therapeutic targets.

Chromosome 17 is unusual among the human chromosomes in many respects. It is the largest human autosome with orthology to only a single mouse chromosome1, mapping entirely to the distal half of mouse chromosome 11. Chromosome 17 is rich in protein-coding genes, having the second highest gene density in the genome2,3. It is also enriched in segmental duplications, ranking third in density among the autosomes4. Here we report a finished sequence for human chromosome 17, as well as a structural comparison with the finished sequence for mouse chromosome 11, the first finished mouse chromosome. Comparison of the orthologous regions reveals striking differences. In contrast to the typical pattern seen in mammalian evolution5,6, the human sequence has undergone extensive intrachromosomal rearrangement, whereas the mouse sequence has been remarkably stable. Moreover, although the human sequence has a high density of segmental duplication, the mouse sequence has a very low density. Notably, these segmental duplications correspond closely to the sites of structural rearrangement, demonstrating a link between duplication and rearrangement. Examination of the main classes of duplicated segments provides insight into the dynamics underlying expansion of chromosome-specific, low-copy repeats in the human genome.

The finished sequence of human chromosome 20 comprises 59,187,298 base pairs (bp) and represents 99.4% of the euchromatic DNA. A single contig of 26 megabases (Mb) spans the entire short arm, and five contigs separated by gaps totalling 320 kb span the long arm of this metacentric chromosome. An additional 234,339 bp of sequence has been determined within the pericentromeric region of the long arm. We annotated 727 genes and 168 pseudogenes in the sequence. About 64% of these genes have a 5' and a 3' untranslated region and a complete open reading frame. Comparative analysis of the sequence of chromosome 20 to whole-genome shotgun-sequence data of two other vertebrates, the mouse Mus musculus and the puffer fish Tetraodon nigroviridis, provides an independent measure of the efficiency of gene annotation, and indicates that this analysis may account for more than 95% of all coding exons and almost all genes.

High throughput sequencing technologies open up a new dimension in cancer genomics by enabling the characterization of cancer genomes at base-pair resolution. To date, the majority of large-scale genomics projects rely on fresh-frozen biospecimens in their studies, which are difficult to obtain and often lack long-term clinical data. Unlike fresh-frozen samples, archived formalin-fixed paraffin-embedded (FFPE) tissues are more readily accessible, and are often associated with known clinical outcomes and more complete clinical annotations. However, sequencing library preparation methods need to be further optimized with regard to applicability to FFPE samples. To test whether next-generation sequencing technologies could overcome previously reported artifacts associated with formalin fixation and report accurate sequencing results, we compared whole-genome and targeted enrichment DNA sequencing data obtained from five FFPE tumor samples for which matching frozen tissues were available. We successfully generated sequencing libraries using 1 µg of genomic DNA as input material and a modified TruSeq™ sample preparation protocol. We designed a custom enrichment pool targeting exons from 215 cancer-related genes and utilized this pool to pull-down and sequence approximately 1.3 Mb region of the genome with an average 400x coverage depth to test if deep sequencing would improve validation of tumor-specific somatic mutations. We used the Illumina sequence analysis pipeline and the Windows-based second generation DNA sequencing software NextGENe® to analyze the data and identify sequence variations that are different from the human reference genome. CNV detection was overall higher among FFPE samples compared with fresh-frozen samples, demonstrating that tissue processing impacts sequencing data quality. We obtained good concordance in variant calls between matched FFPE and fresh-frozen samples. Discordant variant calls were mainly due to low depth of coverage in the regions where variant calls were made. Improvements to DNA sequencing methods for archived samples will significantly enhance cancer research and will result in more reliable prediction of individual cancer therapies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3179. doi:1538-7445.AM2012-3179

Background: MicroRNAs (miRNAs) are short RNAs of around 22 nucleotides that regulate gene expression. The primary transcripts of miRNAs contain double-stranded RNA and are therefore potential substrates for adenosine to inosine (A-to-I) RNA editing. Results: We have conducted a survey of RNA editing of miRNAs from ten human tissues by sequence comparison of PCR products derived from matched genomic DNA and total cDNA from the same individual. Six out of 99 (6%) miRNA transcripts from which data were obtained were subject to A-to-I editing in at least one tissue. Four out of seven edited adenosines were in the mature miRNA and were predicted to change the target sites in 3' untranslated regions. For a further six miRNAs, we identified A-to-I editing of transcripts derived from the opposite strand of the genome to the annotated miRNA. These miRNAs may have been annotated to the wrong genomic strand. Conclusion: Our results indicate that RNA editing increases the diversity of miRNAs and their targets, and hence may modulate miRNA function.