We describe an open source, portable, JavaScript-based genome browser, JBrowse, that can be used to navigate genome annotations over the web. JBrowse helps preserve the user's sense of location by avoiding discontinuous transitions, instead offering smoothly animated panning, zooming, navigation, and track selection. Unlike most existing genome browsers, where the genome is rendered into images on the webserver and the role of the client is restricted to displaying those images, JBrowse distributes work between the server and client and therefore uses significantly less server overhead than previous genome browsers. We report benchmark results empirically comparing server-and client-side rendering strategies, review the architecture and design considerations of JBrowse, and describe a simple wiki plug-in that allows users to upload and share annotation tracks.[The JBrowse source code (freely licensed), live demonstrations, mailing list, documentation, bug-tracking, and virtual machine images are available at http://jbrowse.org/.]In a genome, spatial relationships often indicate functional relationships. A genome browser (Stein et al. 2002;Kent et al. 2003;Stalker et al. 2004) visually conveys the spatial relationships between different pieces of genomic data, helping users form hypotheses about their functional relationships. Current mainstream web-based genome browsers help users understand the genomic data within a given region, but hinder the further development of that understanding by requiring users to navigate to other regions page-by-page. These discontinuous page transitions impair the user's intuitive understanding of which genomic locus they are viewing and how the displayed data points relate to one another.A genome browser also allows a researcher to visually compare and correlate information from several different sources (Cline and Kent 2009); as such, it is a tool for evaluating multiple forms of evidence, looking at interesting biological cases, linking out to more detailed sources of information, such as genomic databases, communicating information to collaborators visually, preparing publication figures, and more. The availability of many genome browsers via the web allows scores of researchers to immediately dive into the data without the overhead of installing, configuring, or maintaining software, as well as provides the ability to link with a myriad of other web-based sources of information.Most current web-based genome browsers are implemented using the Common Gateway Interface (CGI) protocol, which provides a mechanism for a web server to generate a web page to send to the user. For example, GBrowse (Stein et al. 2002), a genome browser commonly used for model organism databases, consists of a set of Perl scripts and libraries stationed on the server side. These scripts query a server-side database of genomic features, render the HTML and graphics files needed to display a region of the genome, and transmit them to the browser along with HTML form-based navigation controls. To scroll the...

Previous efforts to determine structures of non-coding RNA (ncRNA) probed only one RNA at a time with enzymes and chemicals, using gel electrophoresis to identify reactive positions. To accelerate RNA structure inference, we have developed FragSeq, a high-throughput RNA structure probing method that uses high-throughput RNA sequencing on fragments generated by nuclease P1, which specifically cleaves single stranded nucleic acids. In experiments probing the entire mouse nuclear transcriptome, we show that we can accurately and simultaneously map single-stranded regions (ssRNA) in multiple ncRNAs with known structure. We carried out probing in two cell types to demonstrate reproducibility. We also identified and experimentally validated structured regions in ncRNAs never previously probed.

Although diabetes results in part from a deficiency of normal pancreatic beta cells, inducing human beta cells to regenerate is difficult. Reasoning that insulinomas hold the “genomic recipe” for beta cell expansion, we surveyed 38 human insulinomas to obtain insights into therapeutic pathways for beta cell regeneration. An integrative analysis of whole-exome and RNA-sequencing data was employed to extensively characterize the genomic and molecular landscape of insulinomas relative to normal beta cells. Here, we show at the pathway level that the majority of the insulinomas display mutations, copy number variants and/or dysregulation of epigenetic modifying genes, most prominently in the polycomb and trithorax families. Importantly, these processes are coupled to co-expression network modules associated with cell proliferation, revealing candidates for inducing beta cell regeneration. Validation of key computational predictions supports the concept that understanding the molecular complexity of insulinoma may be a valuable approach to diabetes drug discovery.

ObjectiveWe previously reported a characterisation of the hepatocellular carcinoma (HCC) immune contexture and described an immune-specific class. We now aim to further delineate the immunogenomic classification of HCC to incorporate features that explain responses/resistance to immunotherapy.DesignWe performed RNA and whole-exome sequencing, T-cell receptor (TCR)-sequencing, multiplex immunofluorescence and immunohistochemistry in a novel cohort of 240 HCC patients and validated our results in other cohorts comprising 660 patients.ResultsOur integrative analysis led to define: (1) the inflamed class of HCC (37%), which includes the previously reported immune subclass (22%) and a new immune-like subclass (15%) with high interferon signalling, cytolytic activity, expression of immune-effector cytokines and a more diverse T-cell repertoire. A 20-gene signature was able to capture ~90% of these tumours and is associated with response to immunotherapy. Proteins identified in liquid biopsies recapitulated the inflamed class with an area under the ROC curve (AUC) of 0.91; (2) The intermediate class, enriched in TP53 mutations (49% vs 29%, p=0.035), and chromosomal losses involving immune-related genes and; (3) the excluded class, enriched in CTNNB1 mutations (93% vs 27%, p<0.001) and PTK2 overexpression due to gene amplification and promoter hypomethylation. CTNNB1 mutations outside the excluded class led to weak activation of the Wnt-βcatenin pathway or occurred in HCCs dominated by high interferon signalling and type I antigen presenting genes.ConclusionWe have characterised the immunogenomic contexture of HCC and defined inflamed and non-inflamed tumours. Two distinct CTNNB1 patterns associated with a differential role in immune evasion are described. These features may help predict immune response in HCC.

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BackgroundHigh-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA) represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools.Methods and FindingsTumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT) scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival.ConclusionsDetection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic dilemma and a potential critical inflection point in precision medicine. This study suggests that the use of personalized ctDNA biomarkers in gynecologic cancers can identify the presence of residual tumor while also more dynamically predicting response to treatment relative to currently used serum and imaging studies. Of particular interest, ctDNA was an independent predictor of survival in patients with ovarian and endometrial cancers. Earlier recognition of disease persistence and/or recurrence and the ability to stratify into better and worse outcome groups through ctDNA surveillance may open the window for improved survival and quality and life in these cancers.

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Colorectal cancer remains a leading source of cancer mortality worldwide. Initial response is often followed by emergent resistance that is poorly responsive to targeted therapies, reflecting currently undruggable cancer drivers such as KRAS and overall genomic complexity. Here, we report a novel approach to developing a personalized therapy for a patient with treatment-resistant metastatic KRAS-mutant colorectal cancer. An extensive genomic analysis of the tumor’s genomic landscape identified nine key drivers. A transgenic model that altered orthologs of these nine genes in the Drosophila hindgut was developed; a robotics-based screen using this platform identified trametinib plus zoledronate as a candidate treatment combination. Treating the patient led to a significant response: Target and nontarget lesions displayed a strong partial response and remained stable for 11 months. By addressing a disease’s genomic complexity, this personalized approach may provide an alternative treatment option for recalcitrant disease such as KRAS-mutant colorectal cancer.