DNA Data Bank of Japan at work on genome sequence data.

We at the DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) have recently begun receiving, processing and releasing EST and genome sequence data submitted by various Japanese genome projects. The data include those for human, Arabidopsis thaliana, rice, nematode, Synechocystis sp. and Escherichia coli. Since the quantity of data is very large, we organized teams to conduct preliminary discussions with project teams about data submission and handling for release to the public. We also developed a mass submission tool to cope with a large quantity of data. In addition, to provide genome data on WWW, we developed a genome information system using Java. This system (http://mol.genes.nig.ac.jp/ecoli/) can in theory be used for any genome sequence data. These activities will facilitate processing of large quantities of EST and genome data.     

dbCNS: A New Database for Conserved Noncoding Sequences

We developed dbCNS (http://yamasati.nig.ac.jp/dbcns), a new database for conserved noncoding sequences (CNSs). CNSs exist in many eukaryotes and are assumed to be involved in protein expression control. Version 1 of dbCNS, introduced here, includes a powerful and precise CNS identification pipeline for multiple vertebrate genomes. Mutations in CNSs may induce morphological changes and cause genetic diseases. For this reason, many vertebrate CNSs have been identified, with special reference to primate genomes. We integrated ∼6.9 million CNSs from many vertebrate genomes into dbCNS, which allows users to extract CNSs near genes of interest using keyword searches. In addition to CNSs, dbCNS contains published genome sequences of 161 species. With purposeful taxonomic sampling of genomes, users can employ CNSs as queries to reconstruct CNS alignments and phylogenetic trees, to evaluate CNS modifications, acquisitions, and losses, and to roughly identify species with CNSs having accelerated substitution rates. dbCNS also produces links to dbSNP for searching pathogenic single-nucleotide polymorphisms in human CNSs. Thus, dbCNS connects morphological changes with genetic diseases. A test analysis using 38 gnathostome genomes was accomplished within 30 s. dbCNS results can evaluate CNSs identified by other stand-alone programs using genome-scale data.     

Mammalian Mitochondrial ncRNA Database

Mammalian Mitochondrial ncRNA is a web-based database, which provides specific information on non-coding RNA in mammals. This database includes easy searching, comparing with BLAST and retrieving information on predicted structure and its function about mammalian ncRNAs.

Availability

The database is available for free at http://www.iitm.ac.in/bioinfo/mmndb/     

Genomic Target Database (GTD): A database of potential targets in human pathogenic bacteria

A Genomic Target Database (GTD) has been developed having putative genomic drug targets for human bacterial pathogens. The selected pathogens are either drug resistant or vaccines are yet to be developed against them. The drug targets have been identified using subtractive genomics approaches and these are subsequently classified into

1. Drug targets in pathogen specific unique metabolic pathways,
2. Drug targets in host-pathogen common metabolic pathways, and
3. Membrane localized drug targets.

HTML code is used to link each target to its various properties and other available public resources. Essential resources and tools for subtractive genomic analysis, sub-cellular localization, vaccine and drug designing are also mentioned. To the best of authors knowledge, no such database (DB) is presently available that has listed metabolic pathways and membrane specific genomic drug targets based on subtractive genomics. Listed targets in GTD are readily available resource in developing drug and vaccine against the respective pathogen, its subtypes, and other family members. Currently GTD contains 58 drug targets for four pathogens. Shortly, drug targets for six more pathogens will be listed.

Availability

GTD is available at IIOAB website http://www.iioab.webs.com/GTD.htm. It can also be accessed at http://www.iioabdgd.webs.com.GTD is free for academic research and non-commercial use only. Commercial use is strictly prohibited without prior permission from IIOAB.     

SiBIC: A Web Server for Generating Gene Set Networks Based on Biclusters Obtained by Maximal Frequent Itemset Mining

Detecting biclusters from expression data is useful, since biclusters are coexpressed genes under only part of all given experimental conditions. We present a software called SiBIC, which from a given expression dataset, first exhaustively enumerates biclusters, which are then merged into rather independent biclusters, which finally are used to generate gene set networks, in which a gene set assigned to one node has coexpressed genes. We evaluated each step of this procedure: 1) significance of the generated biclusters biologically and statistically, 2) biological quality of merged biclusters, and 3) biological significance of gene set networks. We emphasize that gene set networks, in which nodes are not genes but gene sets, can be more compact than usual gene networks, meaning that gene set networks are more comprehensible. SiBIC is available at http://utrecht.kuicr.kyoto-u.ac.jp:8080/miami/faces/index.jsp.     

Predicted Enhanced Human Propensity of Current Avian-Like H1N1 Swine Influenza Virus from China

Influenza A virus (IAV) subtypes against which little or no pre-existing immunity exists in humans represent a serious threat to global public health. Monitoring of IAV in animal hosts is essential for early and rapid detection of potential pandemic IAV strains to prevent their spread. Recently, the increased pandemic potential of the avian-like swine H1N1 IAV A/swine/Guangdong/104/2013 has been suggested. The virus is infectious in humans and the general population seems to lack neutralizing antibodies against this virus. Here we present an in silico analysis that shows a strong human propensity of this swine virus further confirming its pandemic potential. We suggest mutations which would further enhance its human propensity. We also propose conserved antigenic determinants which could serve as a component of a prepandemic vaccine. The bioinformatics tool, which can be used to further monitor the evolution of swine influenza viruses towards a pandemic virus, are described here and are made publically available (http://www.vin.bg.ac.rs/180/tools/iav_mon.php; http://www.biomedprotection.com/iav_mon.php).     

Exploiting SNP Correlations within Random Forest for Genome-Wide Association Studies

The primary goal of genome-wide association studies (GWAS) is to discover variants that could lead, in isolation or in combination, to a particular trait or disease. Standard approaches to GWAS, however, are usually based on univariate hypothesis tests and therefore can account neither for correlations due to linkage disequilibrium nor for combinations of several markers. To discover and leverage such potential multivariate interactions, we propose in this work an extension of the Random Forest algorithm tailored for structured GWAS data. In terms of risk prediction, we show empirically on several GWAS datasets that the proposed T-Trees method significantly outperforms both the original Random Forest algorithm and standard linear models, thereby suggesting the actual existence of multivariate non-linear effects due to the combinations of several SNPs. We also demonstrate that variable importances as derived from our method can help identify relevant loci. Finally, we highlight the strong impact that quality control procedures may have, both in terms of predictive power and loci identification. Variable importance results and T-Trees source code are all available at www.montefiore.ulg.ac.be/~botta/ttrees/ and github.com/0asa/TTree-source respectively.     

The Effect of Preoperative Oral Carbohydrate or Oral Rehydration Solution on Postoperative Quality of Recovery: A Randomized,Controlled Clinical Trial

Background

Numerous studies have demonstrated the beneficial effects of preoperative administration of oral carbohydrate (CHO) or oral rehydration solution (ORS). However, the effects of preoperative CHO or ORS on postoperative quality of recovery after anesthesia remain unclear. Consequently, the purpose of the current study was to evaluate the effect of preoperative CHO or ORS on patient recovery, using the Quality of Recovery 40 questionnaire (QoR-40).

Methods

This prospective, randomized, controlled clinical trial included American Society of Anesthesiologists (ASA) physical status 1 and 2 adult patients, who were scheduled to undergo a surgical procedure of body surface. Subjects were randomized to one of the three groups: 1) preoperative CHO group, 2) preoperative ORS group, and 3) control group. The primary outcome was the global QoR-40 administered 24 h after surgery. Intraoperative use of vasopressor, intraoperative body temperature changes, and postoperative nausea and vomiting (PONV) were also evaluated.

Results

We studied 134 subjects. The median [interquartile range (IQR)] global QoR-40 scores 24 h after the surgery were 187 [177–197], 186 [171–200], and 184 [171–198] for the CHO, ORS, and control groups, respectively (p = 0.916). No significant differences existed between the groups regarding intraoperative vasopressor use during the surgery (p = 0.475).

Conclusions

Results of the current study indicated that the preoperative administration of either CHO or ORS did not improve the quality of recovery in patients undergoing minimally invasive body surface surgery.

Trial Registration

www.umin.ac.jp UMIN000009388 https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr.cgi?function=brows&action=brows&type=summary&recptno=R000011029&language=E     

PDBsum extras: SARS‐CoV‐2 and AlphaFold models

The PDBsum web server provides structural analyses of the entries in the Protein Data Bank (PDB). Two recent additions are described here. The first is the detailed analysis of the SARS‐CoV‐2 virus protein structures in the PDB. These include the variants of concern, which are shown both on the sequences and 3D structures of the proteins. The second addition is the inclusion of the available AlphaFold models for human proteins. The pages allow a search of the protein against existing structures in the PDB via the Sequence Annotated by Structure (SAS) server, so one can easily compare the predicted model against experimentally determined structures. The server is freely accessible to all at http://www.ebi.ac.uk/pdbsum.     

MetaMetaDB: A Database and Analytic System for Investigating Microbial Habitability

MetaMetaDB (http://mmdb.aori.u-tokyo.ac.jp/) is a database and analytic system for investigating microbial habitability, i.e., how a prokaryotic group can inhabit different environments. The interaction between prokaryotes and the environment is a key issue in microbiology because distinct prokaryotic communities maintain distinct ecosystems. Because 16S ribosomal RNA (rRNA) sequences play pivotal roles in identifying prokaryotic species, a system that comprehensively links diverse environments to 16S rRNA sequences of the inhabitant prokaryotes is necessary for the systematic understanding of the microbial habitability. However, existing databases are biased to culturable prokaryotes and exhibit limitations in the comprehensiveness of the data because most prokaryotes are unculturable. Recently, metagenomic and 16S rRNA amplicon sequencing approaches have generated abundant 16S rRNA sequence data that encompass unculturable prokaryotes across diverse environments; however, these data are usually buried in large databases and are difficult to access. In this study, we developed MetaMetaDB (Meta-Metagenomic DataBase), which comprehensively and compactly covers 16S rRNA sequences retrieved from public datasets. Using MetaMetaDB, users can quickly generate hypotheses regarding the types of environments a prokaryotic group may be adapted to. We anticipate that MetaMetaDB will improve our understanding of the diversity and evolution of prokaryotes.     

Plasmid Construction Using Recombination Activity in the Fission Yeast Schizosaccharomyces pombe

Background

Construction of plasmids is crucial in modern genetic manipulation. As of now, the common method for constructing plasmids is to digest specific DNA sequences with restriction enzymes and to ligate the resulting DNA fragments with DNA ligase. Another potent method to construct plasmids, known as gap-repair cloning (GRC), is commonly used in the budding yeast Saccharomyces cerevisiae. GRC makes use of the homologous recombination activity that occurs within the yeast cells. Due to its flexible design and efficiency, GRC has been frequently used for constructing plasmids with complex structures as well as genome-wide plasmid collections. Although there have been reports indicating GRC feasibility in the fission yeast Schizosaccharomyces pombe, this species is not commonly used for GRC as systematic studies of reporting GRC efficiency in S. pombe have not been performed till date.

Methodology/Principal Findings

We investigated GRC efficiency in S. pombe in this study. We first showed that GRC was feasible in S. pombe by constructing a plasmid that contained the LEU2 auxotrophic marker gene in vivo and showed sufficient efficiency with short homology sequences (>25 bp). No preference was shown for the sequence length from the cut site in the vector plasmid. We next showed that plasmids could be constructed in a proper way using 3 DNA fragments with 70% efficiency without any specific selections being made. The GRC efficiency with 3 DNA fragments was dramatically increased >95% in lig4Δ mutant cell, where non-homologous end joining is deficient. Following this approach, we successfully constructed plasmid vectors with leu1+, ade6+, his5+, and lys1+ markers with the low-copy stable plasmid pDblet as a backbone by applying GRC in S. pombe.

Conclusions/Significance

We concluded that GRC was sufficiently feasible in S. pombe for genome-wide gene functional analysis as well as for regular plasmid construction. Plasmids with different markers constructed in this research are available from NBRP-yeast (http://yeast.lab.nig.ac.jp/).     

EMu: probabilistic inference of mutational processes and their localization in the cancer genome

The spectrum of mutations discovered in cancer genomes can be explained by the activity of a few elementary mutational processes. We present a novel probabilistic method, EMu, to infer the mutational signatures of these processes from a collection of sequenced tumors. EMu naturally incorporates the tumor-specific opportunity for different mutation types according to sequence composition. Applying EMu to breast cancer data, we derive detailed maps of the activity of each process, both genome-wide and within specific local regions of the genome. Our work provides new opportunities to study the mutational processes underlying cancer development. EMu is available at http://www.sanger.ac.uk/resources/software/emu/.     

GHOSTX: An Improved Sequence Homology Search Algorithm Using a Query Suffix Array and a Database Suffix Array

DNA sequences are translated into protein coding sequences and then further assigned to protein families in metagenomic analyses, because of the need for sensitivity. However, huge amounts of sequence data create the problem that even general homology search analyses using BLASTX become difficult in terms of computational cost. We designed a new homology search algorithm that finds seed sequences based on the suffix arrays of a query and a database, and have implemented it as GHOSTX. GHOSTX achieved approximately 131–165 times acceleration over a BLASTX search at similar levels of sensitivity. GHOSTX is distributed under the BSD 2-clause license and is available for download at http://www.bi.cs.titech.ac.jp/ghostx/. Currently, sequencing technology continues to improve, and sequencers are increasingly producing larger and larger quantities of data. This explosion of sequence data makes computational analysis with contemporary tools more difficult. We offer this tool as a potential solution to this problem.