GraphBin2: Refined and Overlapped Binning of Metagenomic Contigs Using Assembly Graphs

Metagenomic sequencing allows us to study structure, diversity and ecology in microbial communities without the necessity of obtaining pure cultures. In many metagenomics studies, the reads obtained from metagenomics sequencing are first assembled into longer contigs and these contigs are then binned into clusters of contigs where contigs in a cluster are expected to come from the same species. As different species may share common sequences in their genomes, one assembled contig may belong to multiple species. However, existing tools for contig binning only support non-overlapped binning, i.e., each contig is assigned to at most one bin (species). In this paper, we introduce GraphBin2 which refines the binning results obtained from existing tools and, more importantly, is able to assign contigs to multiple bins. GraphBin2 uses the connectivity and coverage information from assembly graphs to adjust existing binning results on contigs and to infer contigs shared by multiple species. Experimental results on both simulated and real datasets demonstrate that GraphBin2 not only improves binning results of existing tools but also supports to assign contigs to multiple bins

Book reviews

Teaching/Communication/Extension/Profession,

Safeguarding community-centred global health research during crises

Global health researchers encounter challenges in conducting research during crises, including pandemics, natural disasters and humanitarian conflicts.1 2 External crises often arise without prior notice and disrupt well-planned research. It is difficult to continue research activities under these circumstances, particularly when researchers and communities are at risk.3 Furthermore, community engagement and involvement (CEI), a crucial element in decolonised global health research,4 can become particularly difficult, as the community members’ primary focus may be on survival and acquiring basic needs, which must be a priority above commitment and participation in research. Conducting research in a context of crisis imposes concerns about ethical, credible and equitable research.5 6 The COVID-19 pandemic had a significant impact on global health research, particularly in low-income and middle-income countries (LMICs). Both funding acquisition and scholarly output in LMICs were affected.2 Collaborative research relied on virtual communication platforms, and alternative data collection mechanisms, such as online questionnaires and telephone interviews. However, the validity, reliability and generalisability of such datasets are still subject to extensive discussion.7 Populations without reliable internet access and electronic devices were often excluded from participation, which further exacerbated social inequity, particularly in disadvantaged rural communities.8 9 Here, we share the experience of the Sri Lankan team of the multicountry global health research programme ECLIPSE. We highlight three aspects that will inform the global scientific community in safeguarding research during crises: (1) positioning the research within the crisis context; (2) using CEI for ongoing research and (3) innovating methods and moving beyond the virtual mode

Comprehensive evaluation of a prospective Australian patient cohort with suspected genetic kidney disease undergoing clinical genomic testing: a study protocol

Introduction: Recent advances in genomic technology have allowed better delineation of renal conditions, the identification of new kidney disease genes and subsequent targets for therapy. To date, however, the utility of genomic testing in a clinically ascertained, prospectively recruited kidney disease cohort remains unknown. The aim of this study is to explore the clinical utility and cost-effectiveness of genomic testing within a national cohort of patients with suspected genetic kidney disease who attend multidisciplinary renal genetics clinics. Methods and Analysis: This is a prospective observational cohort study performed at 16 centres throughout Australia. Patients will be included if they are referred to one of the multidisciplinary renal genetics clinics and are deemed likely to have a genetic basis to their kidney disease by the multidisciplinary renal genetics team. The expected cohort consists of 360 adult and paediatric patients recruited by December 2018 with ongoing validation cohort of 140 patients who will be recruited until June 2020. The primary outcome will be the proportion of patients who receive a molecular diagnosis via genomic testing (diagnostic rate) compared with usual care. Secondary outcomes will include change in clinical diagnosis following genomic testing, change in clinical management following genomic testing and the cost-effectiveness of genomic testing compared with usual care. Ethics and Dissemination: The project has received ethics approval from the Melbourne Health Human Research Ethics Committee as part of the Australian Genomics Health Alliance protocol: HREC/16/MH/251. All participants will provide written informed consent for data collection and to undergo clinically relevant genetic/genomic testing. The results of this study will be published in peer-reviewed journals and will also be presented at national and international conferences.Kushani Jayasinghe, Zornitza Stark, Chirag Patel, Amali Mallawaarachchi, Hugh McCarthy, Randall Faull, Aron Chakera, Madhivanan Sundaram, Matthew Jose, Peter Kerr, You Wu, Louise Wardrop, Ilias Goranitis, Stephanie Best, Melissa Martyn, Catherine Quinlan, Andrew J Mallet

Introme accurately predicts the impact of coding and noncoding variants on gene splicing, with clinical applications

Predicting the impact of coding and noncoding variants on splicing is challenging, particularly in non-canonical splice sites, leading to missed diagnoses in patients. Existing splice prediction tools are complementary but knowing which to use for each splicing context remains difficult. Here, we describe Introme, which uses machine learning to integrate predictions from several splice detection tools, additional splicing rules, and gene architecture features to comprehensively evaluate the likelihood of a variant impacting splicing. Through extensive benchmarking across 21,000 splice-altering variants, Introme outperformed all tools (auPRC: 0.98) for the detection of clinically significant splice variants. Introme is available at https://github.com/CCICB/introme .Patricia J. Sullivan, Velimir Gayevskiy, Ryan L. Davis, Marie Wong, Chelsea Mayoh, Amali Mallawaarachchi, Yvonne Hort, Mark J. McCabe, Sarah Beecroft, Matilda R. Jackson, Peer Arts, Andrew Dubowsky, Nigel Laing, Marcel E. Dinger, Hamish S. Scott, Emily Oates, Mark Pinese, and Mark J. Cowle

Clinical spectrum, prognosis and estimated prevalence of DNAJB11-kidney disease

Monoallelic mutations of DNAJB11 were recently described in seven pedigrees with atypical clinical presentations of autosomal dominant polycystic kidney disease. DNAJB11 encodes one of the main cofactors of the endoplasmic reticulum chaperon BiP, a heat-shock protein required for efficient protein folding and trafficking. Here we conducted an international collaborative study to better characterize the DNAJB11-associated phenotype. Thirteen different loss-of-function variants were identified in 20 new pedigrees (54 affected individuals) by targeted next-generation sequencing, whole-exome sequencing or whole-genome sequencing. Amongst the 77 patients (27 pedigrees) now in total reported, 32 reached end stage kidney disease (range, 55-89 years, median age 75); without a significant difference between males and females. While a majority of patients presented with non-enlarged polycystic kidneys, renal cysts were inconsistently identified in patients under age 45. Vascular phenotypes, including intracranial aneurysms, dilatation of the thoracic aorta and dissection of a carotid artery were present in four pedigrees. We accessed Genomics England 100,000 genomes project data, and identified pathogenic variants of DNAJB11 in nine of 3934 probands with various kidney and urinary tract disorders. The clinical diagnosis was cystic kidney disease for eight probands and nephrocalcinosis for one proband. No additional pathogenic variants likely explaining the kidney disease were identified. Using the publicly available GnomAD database, DNAJB11 genetic prevalence was calculated at 0.85/10.000 individuals. Thus, establishing a precise diagnosis in atypical cystic or interstitial kidney disease is crucial, with important implications in terms of follow-up, genetic counseling, prognostic evaluation, therapeutic management, and for selection of living kidney donors

Expression and Function of Osteopontin in Vascular Adventitial Fibroblasts and Pathological Vascular Remodeling

Osteopontin is known to play important roles in various diseases including vascular disorders. However, little is known about its expression and function in vascular adventitial fibroblasts. Adventitial fibroblasts have been shown to play a key role in pathological vascular remodeling associating with various vascular disorders. In this study, we measured activation of Osteopontin and its biological functions in cultured adventitial fibroblasts and injured rat carotid injury arteries induced by balloon angioplasty. Our results showed that angiotensin II and aldosterone increased Osteopontin expression in adventitial fibroblasts in a time- and concentration-dependent manner. MAPKs and AP-1 pathways were involved in Osteopontin upregulation. In addition, Adventitial fibroblast migration stimulated by Angiotensin II and aldosterone required OPN expression. Perivascular delivery of antisense oligonucleotide for Osteopontin suppressed neointimal formation post-injury. We concluded that upregulation of Osteopontin expression in adventitial fibroblasts might be important in the pathogenesis of vascular remodeling after arterial injury

Public Preferences for Forest Ecosystem Management in Japan with Emphasis on Species Diversity

We carried out online choice experiments (CE) to investigate what value Japanese individuals assign to rare versus familiar species in forest ecosystem, and to determine how preference heterogeneity arises. CE attributes comprised a forestry charge as the price attribute and rare versus familiar species of animals or plants as the good to be valued. Species numbers in a 5 km-mesh forest area were evaluated without the use of species names to focus purely on responses to numerical changes. Positional effects were also tested to validate results regarding alternatives and attributes other than the price attribute. A random parameter logit model was adopted to capture preferences for species diversity. After confirming that no positional effects existed, we found that (1) rare animals were valued more highly than rare plants, (2) familiar plants were assigned a positive value, but familiar animals were not assigned significant value at the mean parameter estimate, and (3) preference heterogeneities existed for all species. The sources of preference heterogeneity were analyzed with a latent class model having principal components of environmental attitudes. The influence of such attitudes was shown to be significant and suggested that attention should be paid to belief systems rather than solely demographics