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Reconstruction of target genomes from sequence data produced by instruments that are agnostic as to the species-of-origin may be confounded by contaminant DNA. Whether introduced during sample processing or through co-extraction alongside the target DNA, if insufficient care is taken during the assembly process, the final assembled genome may be a mixture of data from several species. Such assemblies can confound sequence-based biological inference and, when deposited in public databases, may be included in downstream analyses by users unaware of underlying problems. We present BlobToolKit, a software suite to aid researchers in identifying and isolating non-target data in draft and publicly available genome assemblies. BlobToolKit can be used to process assembly, read and analysis files for fully reproducible interactive exploration in the browser-based Viewer. BlobToolKit can be used during assembly to filter non-target DNA, helping researchers produce assemblies with high biological credibility. We have been running an automated BlobToolKit pipeline on eukaryotic assemblies publicly available in the International Nucleotide Sequence Data Collaboration and are making the results available through a public instance of the Viewer at https://blobtoolkit.genomehubs.org/view. We aim to complete analysis of all publicly available genomes and then maintain currency with the flow of new genomes. We have worked to embed these views into the presentation of genome assemblies at the European Nucleotide Archive, providing an indication of assembly quality alongside the public record with links out to allow full exploration in the Viewer.

A planetary-scale understanding of the ocean ecosystem, particularly in light of climate change, is crucial. Here, we review the work of Tara Oceans, an international, multidisciplinary project to assess the complexity of ocean life across comprehensive taxonomic and spatial scales. Using a modified sailing boat, the team sampled plankton at 210 globally distributed sites at depths down to 1,000 m. We describe publicly available resources of molecular, morphological and environmental data, and discuss how an ecosystems biology approach has expanded our understanding of plankton diversity and ecology in the ocean as a planetary, interconnected ecosystem. These efforts illustrate how global-scale concepts and data can help to integrate biological complexity into models and serve as a baseline for assessing ecosystem changes and the future habitability of our planet in the Anthropocene epoch.The schooner Tara sailed 140,000 km across the global oceans to sample diverse marine ecosystems and plankton communities. In the Review, members of the Tara Oceans project highlight how resulting data can be used for an integrated understanding of ocean biology.

Standards for sequencing the microbial 'uncultivated majority', namely bacterial and archaeal single-cell genome sequences, and genome sequences from metagenomic datasets, are proposed. We present two standards developed by the Genomic Standards Consortium (GSC) for reporting bacterial and archaeal genome sequences. Both are extensions of the Minimum Information about Any (x) Sequence (MIxS). The standards are the Minimum Information about a Single Amplified Genome (MISAG) and the Minimum Information about a Metagenome-Assembled Genome (MIMAG), including, but not limited to, assembly quality, and estimates of genome completeness and contamination. These standards can be used in combination with other GSC checklists, including the Minimum Information about a Genome Sequence (MIGS), Minimum Information about a Metagenomic Sequence (MIMS), and Minimum Information about a Marker Gene Sequence (MIMARKS). Community-wide adoption of MISAG and MIMAG will facilitate more robust comparative genomic analyses of bacterial and archaeal diversity.

Open access to sequence data is a cornerstone of biology and biodiversity research, but has created tension under the United Nations Convention on Biological Diversity (CBD). Policy decisions could compromise research and development, unless a practical multilateral solution is implemented. Ensuring international benefit-sharing from sequence data without jeopardising open sharing is a major obstacle for the Convention on Biological Diversity and other UN negotiations. Here, the authors propose a solution to address the concerns of both developing countries and life scientists.

A vast and rich body of information has grown up as a result of the world's enthusiasm for 'omics technologies. Finding ways to describe and make available this information that maximise its usefulness has become a major effort across the 'omics world. At the heart of this effort is the Genomic Standards Consortium (GSC), an open-membership organization that drives community-based standardization activities, Here we provide a short history of the GSC, provide an overview of its range of current activities, and make a call for the scientific community to join forces to improve the quality and quantity of contextual information about our public collections of genomes, metagenomes, and marker gene sequences.

Due to the constantly increasing number of mutations in the SARS-CoV-2 genome, concerns have emerged over the possibility of decreased diagnostic accuracy of reverse transcription-polymerase chain reaction (RT-PCR), the gold standard diagnostic test for SARS-CoV-2. We propose an analysis pipeline to discover genomic variations overlapping the target regions of commonly used PCR primer sets. We provide the list of these mutations in a publicly available format based on a dataset of more than 1.2 million SARS-CoV-2 samples. Our approach distinguishes among mutations possibly having a damaging impact on PCR efficiency and ones anticipated to be neutral in this sense. Samples are categorized as “prone to misclassification” vs. “likely to be correctly detected” by a given PCR primer set based on the estimated effect of mutations present. Samples susceptible to misclassification are generally present at a daily rate of 2% or lower, although particular primer sets seem to have compromised performance when detecting Omicron samples. As different variant strains may temporarily gain dominance in the worldwide SARS-CoV-2 viral population, the efficiency of a particular PCR primer set may change over time, therefore constant monitoring of variations in primer target regions is highly recommended.

The role of the Arctic Ocean ecosystem in climate regulation may depend on the responses of marine microorganisms to environmental change. We applied genome-resolved metagenomics to 41 Arctic seawater samples, collected at various depths in different seasons during the Tara Oceans Polar Circle expedition, to evaluate the ecology, metabolic potential and activity of resident bacteria and archaea. We assembled 530 metagenome-assembled genomes (MAGs) to form the Arctic MAGs catalogue comprising 526 species. A total of 441 MAGs belonged to species that have not previously been reported and 299 genomes showed an exclusively polar distribution. Most Arctic MAGs have large genomes and the potential for fast generation times, both of which may enable adaptation to a copiotrophic lifestyle in nutrient-rich waters. We identified 38 habitat generalists and 111 specialists in the Arctic Ocean. We also found a general prevalence of 14 mixotrophs, while chemolithoautotrophs were mostly present in the mesopelagic layer during spring and autumn. We revealed 62 MAGs classified as key Arctic species, found only in the Arctic Ocean, showing the highest gene expression values and predicted to have habitat-specific traits. The Artic MAGs catalogue will inform our understanding of polar microorganisms that drive global biogeochemical cycles. Using genome-resolved metagenomics for 41 Arctic seawater samples, this ecogenomic analysis of 530 metagenome-assembled genomes (MAGs) from the polar Arctic Ocean reveals uncultured Arctic bacterial and archaeal MAGs, their gene expression patterns, habitat preferences and metabolic potential.

Depression, cardiovascular diseases and diabetes are among the major non-communicable diseases, leading to significant disability and mortality worldwide. These diseases may share environmental and genetic determinants associated with multimorbid patterns. Stressful early-life events are among the primary factors associated with the development of mental and physical diseases. However, possible causative mechanisms linking early life stress (ELS) with psycho-cardio-metabolic (PCM) multi-morbidity are not well understood. This prevents a full understanding of causal pathways towards the shared risk of these diseases and the development of coordinated preventive and therapeutic interventions. This paper describes the study protocol for EarlyCause, a large-scale and inter-disciplinary research project funded by the European Union's Horizon 2020 research and innovation programme. The project takes advantage of human longitudinal birth cohort data, animal studies and cellular models to test the hypothesis of shared mechanisms and molecular pathways by which ELS shapes an individual's physical and mental health in adulthood. The study will research in detail how ELS converts into biological signals embedded simultaneously or sequentially in the brain, the cardiovascular and metabolic systems. The research will mainly focus on four biological processes including possible alterations of the epigenome, neuroendocrine system, inflammatome, and the gut microbiome. Life-course models will integrate the role of modifying factors as sex, socioeconomics, and lifestyle with the goal to better identify groups at risk as well as inform promising strategies to reverse the possible mechanisms and/or reduce the impact of ELS on multi-morbidity development in high-risk individuals. These strategies will help better manage the impact of multi-morbidity on human health and the associated risk.

Understanding the myriad pathways by which antimicrobial-resistance genes (ARGs) spread across biomes is necessary to counteract the global menace of antimicrobial resistance. We screened 17939 assembled metagenomic samples covering 21 biomes, differing in sequencing quality and depth, unevenly across 46 countries, 6 continents, and 14 years (2005-2019) for clinically crucial ARGs, mobile colistin resistance ( mcr ), carbapenem resistance (CR), and (extended-spectrum) beta-lactamase (ESBL and BL) genes. These ARGs were most frequent in human gut, oral and skin biomes, followed by anthropogenic (wastewater, bioreactor, compost, food), and natural biomes (freshwater, marine, sediment). Mcr-9 was the most prevalent mcr gene, spatially and temporally; bla OXA-233 and bla TEM-1 were the most prevalent CR and BL/ESBL genes, but bla GES-2 and bla TEM-116 showed the widest distribution. Redundancy analysis and Bayesian analysis showed ARG distribution was non-random and best-explained by potential host genera and biomes, followed by collection year, anthropogenic factors and collection countries. Preferential ARG occurrence, and potential transmission, between characteristically similar biomes indicate strong ecological boundaries. Our results provide a high-resolution global map of ARG distribution and importantly, identify checkpoint biomes wherein interventions aimed at disrupting ARGs dissemination are likely to be most effective in reducing dissemination and in the long term, the ARG global burden. An extensive metagenomic analysis investigates the global distribution of antimicrobial resistance genes over different biomes, which are primarily influenced by host genera and environment rather than geographic or anthropogenic factors.

The success of environmental DNA (eDNA) approaches for species detection has revolutionized biodiversity monitoring and distribution mapping. Targeted eDNA amplification approaches, such as quantitative PCR, have improved our understanding of species distribution, and metabarcoding‐based approaches have enabled biodiversity assessment at unprecedented scales and taxonomic resolution. eDNA datasets, however, are often scattered across repositories with inconsistent formats, varying access restrictions, and inadequate metadata; this limits their interoperation, reuse, and overall impact. Adopting FAIR (Findable, Accessible, Interoperable, and Reusable) data practices with eDNA data can transform the monitoring of biodiversity and individual species and support data‐driven biodiversity management across broad scales. FAIR practices remain underdeveloped in the eDNA community, partly due to gaps in adapting existing vocabularies, such as Darwin Core (DwC) and Minimum Information about any (x) Sequence (MIxS), to eDNA‐specific needs and workflows. To address these challenges, we propose a comprehensive FAIR eDNA (FAIRe) Metadata Checklist, which integrates existing data standards and introduces new terms tailored to eDNA workflows. Metadata are systematically linked to both raw data (e.g., metabarcoding sequences, Ct/Cq values of targeted qPCR assays) and derived biological observations (e.g., Amplicon Sequence Variant (ASV)/Operational Taxonomic Unit (OTU) tables, species presence/absence). Along with formatting guidelines, tools, templates, and example datasets, we introduce a standardized, ready‐to‐use approach for FAIR eDNA practices. Through broad collaboration, we seek to integrate these guidelines into established biodiversity and molecular data standards, promote journal data policies, and foster user‐driven improvements and uptake of FAIR practices among eDNA data producers. In proposing this standardized approach and developing a long‐term plan with key databases and data standard organizations, the goal is to enhance accessibility, maximize reuse, and elevate the scientific impact of these valuable biodiversity data resources. Environmental DNA (eDNA) has emerged as a transformative tool for biodiversity monitoring and species detection, yet inconsistent metadata practices hinder data interoperability and reuse. To address these challenges, we present the comprehensive FAIR eDNA (FAIRe) guidelines and metadata checklist, supported by practical tools and multi‐disciplinary collaborations, to advance the adoption of FAIR (Findable, Accessible, Interoperable, and Reusable) principles in eDNA workflows.