Abstract
Long non-coding RNAs (lncRNAs) have significant functions in a wide range of important biological processes. Although the number of known human lncRNAs has dramatically increased, they are ...poorly annotated, posing great challenges for better understanding their functional significance and elucidating their complex functioning molecular mechanisms. Here, we present LncBook (http://bigd.big.ac.cn/lncbook), a curated knowledgebase of human lncRNAs that features a comprehensive collection of human lncRNAs and systematic curation of lncRNAs by multi-omics data integration, functional annotation and disease association. In the present version, LncBook houses a large number of 270 044 lncRNAs and includes 1867 featured lncRNAs with 3762 lncRNA–function associations. It also integrates an abundance of multi-omics data from expression, methylation, genome variation and lncRNA–miRNA interaction. Also, LncBook incorporates 3772 experimentally validated lncRNA-disease associations and further identifies a total of 97 998 lncRNAs that are putatively disease-associated. Collectively, LncBook is dedicated to the integration and curation of human lncRNAs as well as their associated data and thus bears great promise to serve as a valuable knowledgebase for worldwide research communities.
Energy-efficient and reliable underwater acoustic communication attracts a lot of research due to special marine communication conditions with limited resources in underwater acoustic sensor networks ...(UASNs). In their final analysis, the existing studies focus on controlling redundant communication and route void that greatly influence UASNs' comprehensive performances. Most of them consider directional or omnidirectional transmission for partial optimization aspects, which still have many extra data loads and performance losses. This paper analyzes the main issue sources causing redundant communication in UASNs, and proposes a lightweight differentiated transmission to suppress extra communication to the greatest extent as well as balance energy consumption. First, the layered model employs layer ID to limit the scale of the data packet header, which does not need depth or location information. Second, the layered model, fuzzy-based model, random modeling and directional-omnidirectional differentiated transmission mode comb out the forwarders step by step to decrease needless duplicated forwarding. Third, forwarders are decided by local computation in nodes, which avoids exchanging controlling information among nodes. Simulation results show that our method can efficiently reduce the network load and improve the performance in terms of energy consumption balance, network lifetime, data conflict and network congestion, and data packet delivery ratio.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
In-depth profiling of genetic variations in the gut microbiome is highly desired for understanding its functionality and impacts on host health and disease. Here, by harnessing the long read ...advantage provided by Oxford Nanopore Technology (ONT), we characterize fine-scale genetic variations of structural variations (SVs) in hundreds of gut microbiomes from healthy humans. ONT long reads dramatically improve the quality of metagenomic assemblies, enable reliable detection of a large, expanded set of structural variation types (notably including large insertions and inversions). We find SVs are highly distinct between individuals and stable within an individual, representing gut microbiome fingerprints that shape strain-level differentiations in function within species, complicating the associations to metabolites and host phenotypes such as blood glucose. In summary, our study strongly emphasizes that incorporating ONT reads into metagenomic analyses expands the detection scope of genetic variations, enables profiling strain-level variations in gut microbiome, and their intricate correlations with metabolome.
SARS-CoV-2 is the cause of the current global pandemic of COVID-19; this virus infects multiple organs, such as the lungs and gastrointestinal tract. The microbiome in these organs, including the ...bacteriome and virome, responds to infection and might also influence disease progression and treatment outcome. In a cohort of 13 COVID-19 patients in Beijing, China, we observed that the gut virome and bacteriome in the COVID-19 patients were notably different from those of five healthy controls. We identified a bacterial dysbiosis signature by observing reduced diversity and viral shifts in patients, and among the patients, the bacterial/viral compositions were different between patients of different severities, although these differences are not entirely distinguishable from the effect of antibiotics. Severe cases of COVID-19 exhibited a greater abundance of opportunistic pathogens but were depleted for butyrate-producing groups of bacteria compared with mild to moderate cases. We replicated our findings in a mouse COVID-19 model, confirmed virome differences and bacteriome dysbiosis due to SARS-CoV-2 infection, and observed that immune/infection-related genes were differentially expressed in gut epithelial cells during infection, possibly explaining the virome and bacteriome dynamics. Our results suggest that the components of the microbiome, including the bacteriome and virome, are affected by SARS-CoV-2 infections, while their compositional signatures could reflect or even contribute to disease severity and recovery processes.
In the Internet of Vessels (IoV), it is difficult for any unmanned surface vessel (USV) to work as a coordinator to establish full communication connections (FCCs) among USVs due to the lack of ...communication connections and the complex natural environment of the sea surface. The existing solutions do not include the employment of some infrastructure to establish USVs’ intragroup FCC while relaying data. To address this issue, considering the high-dimension continuous action space and state space of USVs, we propose a multi-agent deep reinforcement learning framework strategized by unmanned aerial vehicles (UAVs). UAVs can evaluate and navigate the multi-USV cooperation and position adjustment to establish a FCC. When ensuring FCCs, we aim to improve the IoV’s performance by maximizing the USV’s communication range and movement fairness while minimizing their energy consumption, which cannot be explicitly expressed in a closed-form equation. We transform this problem into a partially observable Markov game and design a separate actor–critic structure, in which USVs act as actors and UAVs act as critics to evaluate the actions of USVs and make decisions on their movement. An information transition in UAVs facilitates effective information collection and interaction among USVs. Simulation results demonstrate the superiority of our framework in terms of communication coverage, movement fairness, and average energy consumption, and that it can increase communication efficiency by at least 10% compared to DDPG, with the highest exceeding 120% compared to other baselines.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
With the rapid development of underwater acoustic modem technology, underwater acoustic sensor networks (UWASNs) have more applications in long-term monitoring of the deployment area. In the ...underwater environment, the sensors are costly with limited energy. And acoustic communication medium poses new challenges, including high path loss, low bandwidth, and high energy consumption. Therefore, designing transmission mechanism to decrease energy consumption and to optimize the lifetime of UWASN becomes a significant task. This paper proposes a balance transmission mechanism, and divides the data transmission process into two phases. In the routing set-up phase, an efficient routing algorithm based on the optimum transmission distance is present to optimize the energy consumption of the UWASN. And then, a data balance transmission algorithm is introduced in the stable data transmission phase. The algorithm determines one-hop or multihop data transmission of the node to underwater sink according to the current energy level of adjacent nodes. Furthermore, detailed theoretical analysis evaluates the optimum energy levels in the UWASNs with different scales. The simulation results prove the efficiency of the BTM.
Abstract
The BIG Data Center at Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences provides freely open access to a suite of database resources in support of worldwide research ...activities in both academia and industry. With the vast amounts of omics data generated at ever-greater scales and rates, the BIG Data Center is continually expanding, updating and enriching its core database resources through big-data integration and value-added curation, including BioCode (a repository archiving bioinformatics tool codes), BioProject (a biological project library), BioSample (a biological sample library), Genome Sequence Archive (GSA, a data repository for archiving raw sequence reads), Genome Warehouse (GWH, a centralized resource housing genome-scale data), Genome Variation Map (GVM, a public repository of genome variations), Gene Expression Nebulas (GEN, a database of gene expression profiles based on RNA-Seq data), Methylation Bank (MethBank, an integrated databank of DNA methylomes), and Science Wikis (a series of biological knowledge wikis for community annotations). In addition, three featured web services are provided, viz., BIG Search (search as a service; a scalable inter-domain text search engine), BIG SSO (single sign-on as a service; a user access control system to gain access to multiple independent systems with a single ID and password) and Gsub (submission as a service; a unified submission service for all relevant resources). All of these resources are publicly accessible through the home page of the BIG Data Center at http://bigd.big.ac.cn.
Structural variants (SVs, including large‐scale insertions, deletions, inversions, and translocations) significantly impact the functions of genes in the microbial genome, and SVs in the microbiome ...are associated with diverse biological processes and human diseases. With the advancements in sequencing and bioinformatics technologies, increasingly, sequencing data and analysis tools are already being extensively utilized for microbiome SV analyses, leading to a higher demand for more dedicated SV analysis workflows. Moreover, due to the unique detection biases of various sequencing technologies, including short‐read sequencing (such as Illumina platforms) and long‐read sequencing (e.g., Oxford Nanopore and PacBio), SV discovery based on multiple platforms is necessary to comprehensively identify the wide variety of SVs. Here, we establish an integrated pipeline MetaSVs combining Nanopore long reads and Illumina short reads to analyze SVs in the microbial genomes from gut microbiome and further identify differential SVs that can be reflective of metabolic differences. Our pipeline provides researchers easy access to SVs and relevant metabolites in the microbial genomes without the requirement of specific technical expertise, which is particularly useful to researchers interested in metagenomic SVs but lacking sophisticated bioinformatic knowledge.
MetaSVs (https://github.com/Wlab518/SV_procedure) are a pipeline combining Nanopore long reads and Illumina short reads to analyze structural variants (SVs) in the microbial genomes and further identify differential SVs that can be reflective of metabolic differences. The pipeline integrates multiple software tools and its core mission consists of 13 steps, including the creation of soft links, quality control, and sequence statistics, removal of host reads, metagenome assembly and evaluation, extraction of high‐quality draft genomes (bins), and dereplication, species taxonomy and gene models of bins, detection and visualization of SVs, and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. MetaSVs provide researchers easy access to SVs and relevant metabolites in the microbial genomes without the requirement of specific technical expertise, which is particularly useful to researchers interested in metagenomic SVs but lacking sophisticated bioinformatic knowledge.
Highlights
A bioinformatic pipeline to integrate Nanopore long reads and Illumina short reads is provided, capable of conducting metagenomic structural variant (SV) analyses.
The detailed description of each step of the microbial SV pipeline is illustrated by a simplified example of the human gut microbiome.
This pipeline will help beginners learn how to conduct microbial SV analyses and enable experienced scientists to improve their efficiency.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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