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Launched in 2000 and held every year since, the Bioinformatics Open Source Conference (BOSC) is a volunteer-run meeting coordinated by the Open Bioinformatics Foundation (OBF) that covers open source software development and open science in bioinformatics. Most years, BOSC has been part of the Intelligent Systems for Molecular Biology (ISMB) conference, but in 2018, and again in 2020, BOSC partnered with the Galaxy Community Conference (GCC). This year’s combined BOSC + GCC conference was called the Bioinformatics Community Conference (BCC2020, bcc2020.github.io). Originally slated to take place in Toronto, Canada, BCC2020 was moved online due to COVID-19. The meeting started with a wide array of training sessions; continued with a main program of keynote presentations, talks, posters, Birds of a Feather, and more; and ended with four days of collaboration (CoFest). Efforts to make the meeting accessible and inclusive included very low registration fees, talks presented twice a day, and closed captioning for all videos. More than 800 people from 61 countries registered for at least one part of the meeting, which was held mostly in the Remo.co video-conferencing platform.

As reliable, efficient genome sequencing becomes more ubiquitous, the need for similarly reliable and efficient variant calling becomes increasingly important. The Genome Analysis Toolkit (GATK), maintained by the Broad Institute, is currently the widely accepted standard for variant calling software. However, alternative solutions may provide faster variant calling without sacrificing accuracy. One such alternative is Sentieon DNASeq, a toolkit analogous to GATK but built on a highly optimized backend. We evaluated the DNASeq single-sample variant calling pipeline in comparison to that of GATK. Our results confirm the near-identical accuracy of the two software packages, showcase perfect scalability and great speed from Sentieon, and describe computational performance considerations for the deployment of Sentieon DNASeq.

In telomerase-deficient yeast cells, like equivalent mammalian cells, telomeres shorten over many generations until a period of senescence/crisis is reached. After this, a small fraction of cells can escape senescence, principally using recombination-dependent mechanisms. To investigate the pathways that affect entry into and recovery from telomere-driven senescence, we combined a gene deletion disrupting telomerase (est1Δ) with the systematic yeast deletion collection and measured senescence characteristics in high-throughput assays. As expected, the vast majority of gene deletions showed no strong effects on entry into/exit from senescence. However, around 200 gene deletions behaving similarly to a rad52Δest1Δ archetype (rad52Δ affects homologous recombination) accelerated entry into senescence, and such cells often could not recover growth. A smaller number of strains similar to a rif1Δest1Δ archetype (rif1Δ affects proteins that bind telomeres) accelerated entry into senescence but also accelerated recovery from senescence. Our genome-wide analysis identifies genes that affect entry into and/or exit from telomere-initiated senescence and will be of interest to those studying telomere biology, replicative senescence, cancer, and ageing. Our dataset is complementary to other high-throughput studies relevant to telomere biology, genetic stability, and DNA damage responses.

Telomeres are specialized nucleoprotein structures, which protect chromosome ends and have been implicated in the ageing process. Telomere shortening has been shown to contribute to a persistent DNA damage response (DDR) during replicative senescence, the irreversible loss of division potential of somatic cells. Similarly, persistent DDR foci can be found in stress-induced senescence, although their nature is not understood. Here we show, using immuno-fluorescent in situ hybridization and ChIP, that up to half of the DNA damage foci in stress-induced senescence are located at telomeres irrespective of telomerase activity. Moreover, live-cell imaging experiments reveal that all persistent foci are associated with telomeres. Finally, we report an age-dependent increase in frequencies of telomere-associated foci in gut and liver of mice, occurring irrespectively of telomere length. We conclude that telomeres are important targets for stress in vitro and in vivo and this has important consequences for the ageing process.

The annotation of Systems Biology Markup Language (SBML) models with semantic terms has been supported for a number of years. The prevalence of such annotated models is growing, with repositories such as Biomodels.net and an increasing number of software tools supporting and encouraging their use and development. With the increasing use of semantic annotations in the context of systems biology modeling has come the realization that the current Core SBML specification defining their use contains limitations that reduce the scope of metadata that can be captured in such models. SBML Level 3 provides the facility to propose and develop optional extensions to the Core specification. One such extension is described here, with an initial proposal of an Annotation package. This proposal extends the current Core annotation specification to provide support for a richer set of semantic annotations while adhering more closely to the existing specification of Resource Description Framework (RDF).

To better understand telomere biology in budding yeast, we have performed systematic suppressor/enhancer analyses on yeast strains containing a point mutation in the essential telomere capping gene CDC13 (cdc13-1) or containing a null mutation in the DNA damage response and telomere capping gene YKU70 (yku70Δ). We performed Quantitative Fitness Analysis (QFA) on thousands of yeast strains containing mutations affecting telomere-capping proteins in combination with a library of systematic gene deletion mutations. To perform QFA, we typically inoculate 384 separate cultures onto solid agar plates and monitor growth of each culture by photography over time. The data are fitted to a logistic population growth model; and growth parameters, such as maximum growth rate and maximum doubling potential, are deduced. QFA reveals that as many as 5% of systematic gene deletions, affecting numerous functional classes, strongly interact with telomere capping defects. We show that, while Cdc13 and Yku70 perform complementary roles in telomere capping, their genetic interaction profiles differ significantly. At least 19 different classes of functionally or physically related proteins can be identified as interacting with cdc13-1, yku70Δ, or both. Each specific genetic interaction informs the roles of individual gene products in telomere biology. One striking example is with genes of the nonsense-mediated RNA decay (NMD) pathway which, when disabled, suppress the conditional cdc13-1 mutation but enhance the null yku70Δ mutation. We show that the suppressing/enhancing role of the NMD pathway at uncapped telomeres is mediated through the levels of Stn1, an essential telomere capping protein, which interacts with Cdc13 and recruitment of telomerase to telomeres. We show that increased Stn1 levels affect growth of cells with telomere capping defects due to cdc13-1 and yku70Δ. QFA is a sensitive, high-throughput method that will also be useful to understand other aspects of microbial cell biology., Author Summary Telomeres, specialized structures at the end of linear chromosomes, ensure that chromosome ends are not mistakenly treated as DNA double-strand breaks. Defects in the telomere cap contribute to ageing and cancer. In yeast, defects in telomere capping proteins can cause telomeres to behave like double-strand breaks. To better understand the telomere and responses to capping failure, we have combined a systematic yeast gene deletion library with mutations affecting important yeast telomere capping proteins, Cdc13 or Yku70. Quantitative Fitness Analysis (QFA) was used to accurately measure the fitness of thousands of different yeast strains containing telomere capping defects and additional deletion mutations. Interestingly, we find that many gene deletions suppress one type of telomere capping defect while enhancing another. Through QFA, we can begin to define the roles of different gene products in contributing to different aspects of the telomere cap. Strikingly, mutations in nonsense-mediated mRNA decay pathways, which degrade many RNA molecules, suppress the cdc13-1 defect while enhancing the yku70Δ defect. QFA is widely applicable and will be useful for understanding other aspects of yeast cell biology.

Medical imaging techniques such as MRI and CT can be used to retrieve 3D anatomical digital models in medical studies. However, imaging cannot be used as many times as needed due to cost and health issues. Deformation is an alternative approach to building 3D digital models, where thin-plate spline (TPS) based transformation has been commonly used. We have developed visualization software to show the TPS based transformation by morphing 3D models created from digital imaging. The programs are used to show the animated transformation to enhance the human perception of the changes in the 3D models.

Summary: Saint is a web application which provides a lightweight annotation integration environment for quantitative biological models. The system enables modellers to rapidly mark up models with biological information derived from a range of data sources. Availability and Implementation: Saint is freely available for use on the web at http://www.cisban.ac.uk/saint. The web application is implemented in Google Web Toolkit and Tomcat, with all major browsers supported. The Java source code is freely available for download at http://saint-annotate.sourceforge.net. The Saint web server requires an installation of libSBML and has been tested on Linux (32-bit Ubuntu 8.10 and 9.04). Contact: helpdesk@cisban.ac.uk; a.l.lister@ncl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Many questions that biologists want to answer using the information available from completely sequenced genomes are complex. A graphical environment allows users to visually explore and operate on a sequence. Sequence and annotation data exists in bewildering varieties of types and levels of detail. The graphical environment therefore needs to adapt to this variation to provide the user the best possible visual representation of genomic data in a given context. As more and more online tools and services become available for biologists, mediating software should also be able to integrate and link to them. The Bluejay browser is a Java-based visual environment for exploring biological sequences. Uniquely, Bluejay fully integrates existing gene expression software into a genomic context. Bluejay also differentiates itself from most form-based HTML sequence browsers because it: (i) is highly scalable so that it can visualize a wide range of genomic objects ranging from a large whole genome down to individual nucleotides by using data-transformational Web services; and (ii) dynamically discovers and provides links to disparate resources such as gene annotation data (via XLinks) and semantically- described biological Web Services (via the BioMOBY protocol).