The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

The Gene Ontology resource (GO; http://geneontology.org) provides structured, computable knowledge regarding the functions of genes and gene products. Founded in 1998, GO has become widely adopted in the life sciences, and its contents are under continual improvement, both in quantity and in quality. Here, we report the major developments of the GO resource during the past two years. Each monthly release of the GO resource is now packaged and given a unique identifier (DOI), enabling GO-based analyses on a specific release to be reproduced in the future. The molecular function ontology has been refactored to better represent the overall activities of gene products, with a focus on transcription regulator activities. Quality assurance efforts have been ramped up to address potentially out-of-date or inaccurate annotations. New evidence codes for high-throughput experiments now enable users to filter out annotations obtained from these sources. GO-CAM, a new framework for representing gene function that is more expressive than standard GO annotations, has been released, and users can now explore the growing repository of these models. We also provide the ‘GO ribbon’ widget for visualizing GO annotations to a gene; the widget can be easily embedded in any web page.

The Gene Ontology Resource: 20 years and still GOing strong

Snakemake is a workflow engine that provides a readable Python-based workflow definition language and a powerful execution environment that scales from single-core workstations to compute clusters without modifying the workflow. It is the first system to support the use of automatically inferred multiple named wildcards (or variables) in input and output filenames.

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Snakemake--a scalable bioinformatics workflow engine.

The PubMLST.org website hosts a collection of open-access, curated databases that integrate population sequence data with provenance and phenotype information for over 100 different microbial species and genera.  Although the PubMLST website was conceived as part of the development of the first multi-locus sequence typing (MLST) scheme in 1998 the software it uses, the Bacterial Isolate Genome Sequence database (BIGSdb, published in 2010), enables PubMLST to include all levels of sequence data, from single gene sequences up to and including complete, finished genomes.  Here we describe developments in the BIGSdb software made from publication to June 2018 and show how the platform realises microbial population genomics for a wide range of applications.  The system is based on the gene-by-gene analysis of microbial genomes, with each deposited sequence annotated and curated to identify the genes present and systematically catalogue their variation.  Originally intended as a means of characterising isolates with typing schemes, the synthesis of sequences and records of genetic variation with provenance and phenotype data permits highly scalable (whole genome sequence data for tens of thousands of isolates) means of addressing a wide range of functional questions, including: the prediction of antimicrobial resistance; likely cross-reactivity with vaccine antigens; and the functional activities of different variants that lead to key phenotypes.  There are no limitations to the number of sequences, genetic loci, allelic variants or schemes (combinations of loci) that can be included, enabling each database to represent an expanding catalogue of the genetic variation of the population in question.  In addition to providing web-accessible analyses and links to third-party analysis and visualisation tools, the BIGSdb software includes a RESTful application programming interface (API) that enables access to all the underlying data for third-party applications and data analysis pipelines.

Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications.

1. Weinstein, J.N. et al. Nat. Genet. 45, 1113–1120 (2013). 2. Zhang, J. et al. Database. http://dx.doi.org/10.1093/ database/bar026 (2011) 3. Siva, N. Lancet 385, 103–104 (2015). 4. McKenna, A. et al. Genome Res. 20, 1297–1303 (2010). 5. UNC Bioinformatics. TCGA mRNA-seq pipeline for UNC data. https://webshare.bioinf.unc.edu/public/ mRNAseq_TCGA/UNC_mRNAseq_summary.pdf (2013). 6. Albrecht, M., Michael, A., Patrick, D., Peter, B. & Douglas, T. in Proceedings of the 1st ACM SIGMOD Workshop on Scalable Workflow Execution Engines and Technologies (SWEET ’12) 1. ACM (Association of Computing Machinery. http://dx.doi. org/10.1145/2443416.2443417 (2012). 7. Bernhardsson, E. & Frieder, E. Luigi. Github https:// github.com/spotify/luigi (2016). 8. Goecks, J., Nekrutenko, A. & Taylor, J. Genome Biol. 11, R86 (2010). 9. UCSC. Xena http://xena.ucsc.edu (2016). comprehensive analyses. Further, it means that results can be reproduced using the original computation’s set of tools and parameters. If we had run the original TCGA best-practices RNA-seq pipeline with one sample per node, it would have cost ~$800,000. Through the use of efficient algorithms (STAR and Kallisto) and Toil, we were able to reduce the final cost to $26,071 (Supplementary Note 9). We have demonstrated the utility of Toil by creating one of the single largest, consistently analyzed, public human RNA-seq expression repositories, which we hope the community will find useful.

Nextflow enables reproducible computational workflows

A person’s germline genome strongly influences their risk of developing cancer. Yet the molecular mechanisms linking the host genome to the specific somatic molecular phenotypes of individual cancers are largely unknown. We quantified the relationships between germline polymorphisms and somatic mutational features in prostate cancer. Across 1,991 prostate tumors, we identified 23 co-occurring germline and somatic events in close 2D or 3D spatial genomic proximity, affecting 10 cancer driver genes. These driver quantitative trait loci (dQTLs) overlap active regulatory regions, and shape the tumor epigenome, transcriptome and proteome. Some dQTLs are active in multiple cancer types, and information content analyses imply hundreds of undiscovered dQTLs. Specific dQTLs explain at least 16.7% ancestry-biases in rates of TMPRSS2-ERG gene fusions and 67.3% of ancestry-biases in rates of FOXA1 point mutations. These data reveal extensive influences of common germline variation on somatic mutational landscapes.

/pdf/germline-determinants-of-the-prostate-tumor-genome-mlod9wrq.pdf

Germline determinants of the prostate tumor genome


 Purpose Circulating tumour DNA (ctDNA) analysis has demonstrated utility for diagnostic and prognostic applications in many cancer types, including metastatic prostate cancer. However, localised prostate cancer yields relatively low levels of ctDNA and therefore it has been difficult to detect in this context using conventional methods. We aimed to assess the limits of detection of ctDNA in localised prostate cancer by leveraging thousands of patient-specific mutations per case with the high-sensitivity INVAR method, and to test the hypothesis that ctDNA detection is associated with high risk disease. Experimental Procedures A total of 128 individuals with clinically localised prostate cancer at the time of sample collection were selected from cohorts in Australia (n=48) and the UK (n=80). Additionally, 27 healthy individuals without prostate cancer were included as negative controls. Primary tumour tissue and matched bloods from all cases were whole genome sequenced (WGS) and somatic variants were called using pipelines from the Pan Prostate Cancer Group. Plasma cell-free DNA (cfDNA) samples from cases and controls were profiled using custom targeted sequencing panels, with saturating coverage of patient-specific mutations identified by WGS. We assessed ctDNA detection in cases using the highly sensitive INVAR pipeline, that leverages consensus read sequencing alignments, background error modelling and integration of signals across thousands of patient-specific variants. Biochemical recurrence and metastasis-free survival curves were used to assess the relationship between ctDNA detection and disease progression. Results We analysed pre-treatment blood plasma ctDNA in a large cohort of localised prostate cancer patients, using error-suppressed targeted sequencing of over 280k patient-specific mutations. To comprehensively assess ctDNA mutation analysis in this context, we combined signals across the maximum number of genome-wide patient specific mutations and leveraged an established analysis pipeline (INVAR) that corrects for background error rates and calculates a global integrated mutant allele fraction. ctDNA was detected in 9.3% of localised prostate cancer patients. In cases where ctDNA was detected we found significant associations with biochemical recurrence (p=0.01) and shorter metastasis-free survival (p < 0.0001). Conclusions Our study provides clear insights into the required analytical sensitivity and potential utility of ctDNA mutation analysis in localised prostate cancer. We found that mutation-based ctDNA detection rates were low in localised prostate cancer (<10% cases), but in ctDNA positive cases there was a significant association with relapse after surgical intervention alone. This raises the potential for including ctDNA detection as an additional tool for patient stratification in future neo/adjuvant treatment trials aiming to assess the impact of treatment escalation in men at high risk of relapse with current standard of care treatment alone.
 Citation Format: Bernard J. Pope, Gahee Park, Edmund Lau, Jelena Belic, Radoslaw Lach, Anne George, Patrick McCoy, Anne Nguyen, Corrina Grima, Chol-hee Jung, Emma-Jane Ditter, Hui Zhao, David Wedge, Rosalind A Eeles, Daniel Brewer, Andy G. Lynch, Harveer Dev, Christopher M Hovens, Vincent J. Gnanpragasam, Nitzan Rosenfeld, Niall M. Corcoran, Charles E. Massie. Ultra-sensitive detection of circulating tumour DNA enriches for patients with higher risk disease in clinically localised prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr PR012.

Abstract PR012: Ultra-sensitive detection of circulating tumour DNA enriches for patients with higher risk disease in clinically localised prostate cancer

Constitutional biological processes involve the generation of DNA double-strand breaks (DSBs). The production of such breaks and their subsequent resolution are also highly relevant to neurodegenerative diseases and cancer, in which extensive DNA fragmentation has been described Stephens et al. (2011), Blondet et al. (2001). Tchurikov et al. Tchurikov et al. (2011, 2013) have reported previously that frequent sites of DSBs occur in chromosomal domains involved in the co-ordinated expression of genes. This group report that hot spots of DSBs in human HEK293T cells often coincide with H3K4me3 marks, associated with active transcription Kravatsky et al. (2015) and that frequent sites of DNA double-strand breakage are likely to be relevant to cancer genomics Tchurikov et al. (2013, 2016) . Recently, they applied a RAFT (rapid amplification of forum termini) protocol that selects for blunt-ended DSB sites and mapped these to the human genome within defined co-ordinate 'windows'. In this paper, we re-analyse public RAFT data to derive sites of DSBs at the single-nucleotide level across the built genome for human HEK293T cells (https://figshare.com/s/35220b2b79eaaaf64ed8). This refined mapping, combined with accessory ENCODE data tracks and ribosomal DNA-related sequence annotations, will likely be of value for the design of clinically relevant targeted assays such as those for cancer susceptibility, diagnosis, treatment-matching and prognostication.

https://minerva-access.unimelb.edu.au/bitstream/handle/11343/261026/PMC5133665.pdf

Bernard J. Pope

Papers

Germline determinants of the prostate tumor genome

Abstract PR012: Ultra-sensitive detection of circulating tumour DNA enriches for patients with higher risk disease in clinically localised prostate cancer

Single nucleotide-level mapping of DNA double-strand breaks in human HEK293T cells.