Dataset Information

Barcoding sponges: an overview based on comprehensive sampling.

ABSTRACT: BACKGROUND: Phylum Porifera includes ?8,500 valid species distributed world-wide in aquatic ecosystems ranging from ephemeral fresh-water bodies to coastal environments and the deep-sea. The taxonomy and systematics of sponges is complicated, and morphological identification can be both time consuming and erroneous due to phenotypic convergence and secondary losses, etc. DNA barcoding can provide sponge biologists with a simple and rapid method for the identification of samples of unknown taxonomic membership. The Sponge Barcoding Project (www.spongebarcoding.org), the first initiative to barcode a non-bilaterian metazoan phylum, aims to provide a comprehensive DNA barcode database for Phylum Porifera. METHODOLOGY/PRINCIPAL FINDINGS: ?7,400 sponge specimens have been extracted, and amplification of the standard COI barcoding fragment has been attempted for approximately 3,300 museum samples with ?25% mean amplification success. Based on this comprehensive sampling, we present the first report on the workflow and progress of the sponge barcoding project, and discuss some common pitfalls inherent to the barcoding of sponges. CONCLUSION: A DNA-barcoding workflow capable of processing potentially large sponge collections has been developed and is routinely used for the Sponge Barcoding Project with success. Sponge specific problems such as the frequent co-amplification of non-target organisms have been detected and potential solutions are currently under development. The initial success of this innovative project have already demonstrated considerable refinement of sponge systematics, evaluating morphometric character importance, geographic phenotypic variability, and the utility of the standard barcoding fragment for Porifera (despite its conserved evolution within this basal metazoan phylum).

SUBMITTER: Vargas S

PROVIDER: S-EPMC3389008 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Barcoding sponges: an overview based on comprehensive sampling.

Vargas Sergio S Schuster Astrid A Sacher Katharina K Büttner Gabrielle G Schätzle Simone S Läuchli Benjamin B Hall Kathryn K Hooper John N A JN Erpenbeck Dirk D Wörheide Gert G

PloS one 20120703 7

<h4>Background</h4>Phylum Porifera includes ∼8,500 valid species distributed world-wide in aquatic ecosystems ranging from ephemeral fresh-water bodies to coastal environments and the deep-sea. The taxonomy and systematics of sponges is complicated, and morphological identification can be both time consuming and erroneous due to phenotypic convergence and secondary losses, etc. DNA barcoding can provide sponge biologists with a simple and rapid method for the identification of samples of unknown ...[more]

PMID: 22802937

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Project description:OBJECTIVES:To explore the scope of the published literature on computer-tailoring, considering both the development and the evaluation aspects, with the aim of identifying and categorising main approaches and detecting research gaps, tendencies and trends. SETTING:Original researches from any country and healthcare setting. PARTICIPANTS:Patients or health consumers with any health condition regardless of their specific characteristics. METHOD:A systematic scoping review was undertaken based on the York's five-stage framework outlined by Arksey and O'Malley. Five leading databases were searched: PubMed, Scopus, Science Direct, EBSCO and IEEE for articles published between 1990 and 2017. Tailoring concept was investigated for three aspects: system design, information delivery and evaluation. Both quantitative (ie, frequencies) and qualitative (ie, theme analysis) methods have been used to synthesis the data. RESULTS:After reviewing 1320 studies, 360 articles were identified for inclusion. Two main routes were identified in tailoring literature including public health research (64%) and computer science research (17%). The most common facets used for tailoring were sociodemographic (73 %), target behaviour status (59%) and psycho-behavioural determinants (56%), respectively. The analysis showed that only 13% of the studies described the tailoring algorithm they used, from which two approaches revealed: information retrieval (12%) and natural language generation (1%). The systematic mapping of the delivery channel indicated that nearly half of the articles used the web (57%) to deliver the tailored information; printout (19%) and email (10%) came next. Analysis of the evaluation approaches showed that nearly half of the articles (53%) used an outcome-based approach, 44% used process evaluation and 3% assessed cost-effectiveness. CONCLUSIONS:This scoping review can inform researchers to identify the methodological approaches of computer tailoring. Improvements in reporting and conduct are imperative. Further research on tailoring methodology is warranted, and in particular, there is a need for a guideline to standardise reporting.

Project description:Eight years after DNA barcoding was formally proposed on a large scale, CO1 sequences are rapidly accumulating from around the world. While studies to date have mostly targeted local or regional species assemblages, the recent launch of the global iBOL project (International Barcode of Life), highlights the need to understand the effects of geographical scale on Barcoding's goals. Sampling has been central in the debate on DNA Barcoding, but the effect of the geographical scale of sampling has not yet been thoroughly and explicitly tested with empirical data. Here, we present a CO1 data set of aquatic predaceous diving beetles of the tribe Agabini, sampled throughout Europe, and use it to investigate how the geographic scale of sampling affects 1) the estimated intraspecific variation of species, 2) the genetic distance to the most closely related heterospecific, 3) the ratio of intraspecific and interspecific variation, 4) the frequency of taxonomically recognized species found to be monophyletic, and 5) query identification performance based on 6 different species assignment methods. Intraspecific variation was significantly correlated with the geographical scale of sampling (R-square = 0.7), and more than half of the species with 10 or more sampled individuals (N = 29) showed higher intraspecific variation than 1% sequence divergence. In contrast, the distance to the closest heterospecific showed a significant decrease with increasing geographical scale of sampling. The average genetic distance dropped from > 7% for samples within 1 km, to < 3.5% for samples up to > 6000 km apart. Over a third of the species were not monophyletic, and the proportion increased through locally, nationally, regionally, and continentally restricted subsets of the data. The success of identifying queries decreased with increasing spatial scale of sampling; liberal methods declined from 100% to around 90%, whereas strict methods dropped to below 50% at continental scales. The proportion of query identifications considered uncertain (more than one species < 1% distance from query) escalated from zero at local, to 50% at continental scale. Finally, by resampling the most widely sampled species we show that even if samples are collected to maximize the geographical coverage, up to 70 individuals are required to sample 95% of intraspecific variation. The results show that the geographical scale of sampling has a critical impact on the global application of DNA barcoding. Scale-effects result from the relative importance of different processes determining the composition of regional species assemblages (dispersal and ecological assembly) and global clades (demography, speciation, and extinction). The incorporation of geographical information, where available, will be required to obtain identification rates at global scales equivalent to those in regional barcoding studies. Our result hence provides an impetus for both smarter barcoding tools and sprouting national barcoding initiatives-smaller geographical scales deliver higher accuracy.

Project description:OBJECTIVES:Occupational injuries and diseases are a huge public health problem and cause extensive suffering and loss of productivity. Nevertheless, many occupational health and safety (OHS) guidelines are still not based on the best available evidence. In the last decade, numerous systematic reviews on behavioural, relational and mixed interventions to reduce occupational injuries and diseases have been carried out, but a comprehensive synopsis is yet missing. The aim of this overview of reviews is to provide a comprehensive basis to inform evidence-based decision-making about interventions in the field of OHS. METHODS:We conducted an overview of reviews. We searched MEDLINE (Ovid), the Cochrane Library (Wiley), epistemonikos.org and Scopus (Elsevier) for relevant systematic reviews published between January 2008 and June 2018. Two authors independently screened abstracts and full-text publications and determined the risk of bias of the included systematic reviews with the ROBIS (Risk of Bias in Systematic Reviews) tool. RESULTS:We screened 2287 abstracts and 200 full-texts for eligibility. Finally, we included 25 systematic reviews with a low risk of bias for data synthesis and analysis. We identified systematic reviews on the prevention of occupational injuries, musculoskeletal, skin and lung diseases, occupational hearing impairment and interventions without specific target diseases. Several interventions led to consistently positive results on individual diseases; other interventions did not show any effects, or the studies are contradictory. We provide detailed results on all included interventions. DISCUSSION:To our knowledge, this is the first comprehensive overview of behavioural, relational and mixed interventions and their effectiveness in preventing occupational injuries and diseases. It provides policymakers with an important basis for making evidence-based decisions on interventions in this field. PROSPERO REGISTRATION NUMBER:CRD42018100341.

Dataset Information

Barcoding sponges: an overview based on comprehensive sampling.

Publications

Barcoding sponges: an overview based on comprehensive sampling.

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