The extent to which prokaryotic evolution has been influenced by horizontal gene transfer (HGT) and therefore might be more of a network than a tree is unclear. Here we use supertree methods to ask whether a definitive prokaryotic phylogenetic tree exists and whether it can be confidently inferred using orthologous genes. We analysed an 11-taxon dataset spanning the deepest divisions of prokaryotic relationships, a 10-taxon dataset spanning the relatively recent gamma-proteobacteria and a 61-taxon dataset spanning both, using species for which complete genomes are available. Congruence among gene trees spanning deep relationships is not better than random. By contrast, a strong, almost perfect phylogenetic signal exists in gamma-proteobacterial genes. Deep-level prokaryotic relationships are difficult to infer because of signal erosion, systematic bias, hidden paralogy and/or HGT. Our results do not preclude levels of HGT that would be inconsistent with the notion of a prokaryotic phylogeny. This approach will help decide the extent to which we can say that there is a prokaryotic phylogeny and where in the phylogeny a cohesive genomic signal exists.
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http://dx.doi.org/10.1098/rspb.2004.2864 | DOI Listing |
Biology (Basel)
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Key Laboratory of Oceanic and Polar Fisheries, Ministry of Agriculture and Rural Affairs, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China.
To evaluate and compare the effectiveness of prediction models for Argentine squid trawling grounds in the Southwest Atlantic high seas based on vessel position and fishing log data, this study used AIS datasets and fishing log datasets from fishing seasons spanning 2019-2024 (December to June each year). Using a spatial resolution of 0.1° × 0.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
January 2025
Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Yunlin, Taiwan.
Background: In medical education, enhancing thinking skills is vital. The Virtual Diagnosis and Treatment Platform (VP) refines medical students' diagnostic abilities through interactive patient interviews (simulated patient interactions). By analyzing the questions asked during these interviews, the VP evaluates students' aptitude in medical history inquiries, offering insights into their thinking capabilities.
View Article and Find Full Text PDFSci Data
January 2025
Yale University, Department of Anthropology, 10 Sachem Street, New Haven, CT, 06511, USA.
The diverse, highly endemic flora and fauna of Madagascar make it a priority for research and conservation. Lemurs, the island's endemic primates, exhibit a distinctive array of biological, behavioral and demographic traits. Research on these species contributes to significant theoretical issues, including the evolution of mammalian life histories and social systems.
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January 2025
Yunnan Provincial Key Laboratory of Animal Nutrition and Feed Science, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, China.
Compared with leaner breeds, local Chinese pig breeds have distinct intestinal microbial, as determined by metagenomic techniques, and the interactions between oral microorganisms and their hosts are also gradually being clarified. However, the high host genome content means that few metagenome-based oral microbiomes have been reported. Here, we combined dilution-based metagenomic sequencing and binning approaches to extract the microbial genomes from the oral microbiomes of Tibetan and Duroc pigs.
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Department of Health, Sport and Bioscience. University of East London, Water Lane, Stratford E15 4LZ, United Kingdom. Electronic address:
The interplay of biotic and abiotic factors driving Ixodes ricinus abundance trends are not fully understood. Machine learning (ML) approaches are being increasingly used to explore this and predict future abundance patterns of this species, however, the studies focusing on this to date have had limitations (including short study duration, limited sample size, narrow geographical range and use of a single ML model). This study was undertaken to address these limitations by applying 11 predictive ML models (across three data clustering techniques) to a large I.
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