MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased ∼1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.

MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. This study describes an update of the miRTarBase (http://miRTarBase.mbc.nctu.edu.tw/) that provides information about experimentally validated miRNA-target interactions (MTIs). The latest update of the miRTarBase expanded it to identify systematically Argonaute-miRNA-RNA interactions from 138 crosslinking and immunoprecipitation sequencing (CLIP-seq) data sets that were generated by 21 independent studies. The database contains 4966 articles, 7439 strongly validated MTIs (using reporter assays or western blots) and 348 007 MTIs from CLIP-seq. The number of MTIs in the miRTarBase has increased around 7-fold since the 2014 miRTarBase update. The miRNA and gene expression profiles from The Cancer Genome Atlas (TCGA) are integrated to provide an effective overview of this exponential growth in the miRNA experimental data. These improvements make the miRTarBase one of the more comprehensively annotated, experimentally validated miRNA-target interactions databases and motivate additional miRNA research efforts.

MicroRNAs (miRNAs) are small non-coding RNA molecules capable of negatively regulating gene expression to control many cellular mechanisms. The miRTarBase database (http://mirtarbase.mbc.nctu.edu.tw/) provides the most current and comprehensive information of experimentally validated miRNA-target interactions. The database was launched in 2010 with data sources for >100 published studies in the identification of miRNA targets, molecular networks of miRNA targets and systems biology, and the current release (2013, version 4) includes significant expansions and enhancements over the initial release (2010, version 1). This article reports the current status of and recent improvements to the database, including (i) a 14-fold increase to miRNA-target interaction entries, (ii) a miRNA-target network, (iii) expression profile of miRNA and its target gene, (iv) miRNA target-associated diseases and (v) additional utilities including an upgrade reminder and an error reporting/user feedback system.

ARS-CoV-2 was first detected in December 2019, leading to a pandemic with an estimated 5-6% mortality rate 1. Akin to SARS-CoV-1, the causative agent of the 2003 SARS outbreak, this is an enveloped betacoronavirus with protrusions of large trimeric 'spike' proteins. Receptor binding domains (RBDs) located at the tips of these spikes facilitate host cell entry via interaction with angiotensin-converting enzyme 2 (ACE2) 2. Spikes are type I transmembrane glycoproteins, formed from a single polypeptide, which transitions into a post-fusion state via cleavage into S1 (N-terminal) and S2 (C-terminal) chains following receptor binding or trypsin treatment 3. In the pre-fusion state, the apical RBD (~22 kDa) is folded down, enshrouded by the N-terminal domain (NTD) of the spike so that the receptor binding site is inaccessible until, it is assumed, an RBD stochastically swings upwards to present the ACE2 binding site 4-7. ACE2 interaction locks the RBD in the 'up' conformation, which drives conversion to the post-fusion form where the S2 subunit engages the host membrane while dispensing with S1 4,5. Neutralizing human monoclonal antibodies (mAbs) that recognize the ACE2 receptor binding site for SARS-CoV-1 and SARS-CoV-2 are generally not cross-reactive between the two viruses and are susceptible to escape mutation 8-12. Indeed, a natural mutation (Y495N) has already been identified at this site (GISAID 13 : accession ID: EPI_ISL_429783 Wienecke-Baldacchino et al.). By contrast, the CR3022 antibody (derived from a SARS-CoV-1-infected patient) cross-reacts strongly with SARS-CoV-2 (see Methods and Fig. 1) and has been shown to recognize a cryptic, conserved footprint on the RBD distinct from the binding epitope of

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

Longan (Dimocarpus longan Lour.), an important subtropical fruit in the family Sapindaceae, is grown in more than 10 countries. Longan is an edible drupe fruit and a source of traditional medicine with polyphenol-rich traits. Tree size, alternate bearing, and witches' broom disease still pose serious problems. To gain insights into the genomic basis of longan traits, a draft genome sequence was assembled. The draft genome (about 471.88 Mb) of a Chinese longan cultivar, “Honghezi,” was estimated to contain 31 007 genes and 261.88 Mb of repetitive sequences. No recent whole-genome-wide duplication event was detected in the genome. Whole-genome resequencing and analysis of 13 cultivated D. longan accessions revealed the extent of genetic diversity. Comparative transcriptome studies combined with genome-wide analysis revealed polyphenol-rich and pathogen resistance characteristics. Genes involved in secondary metabolism, especially those from significantly expanded (DHS, SDH, F3΄H, ANR, and UFGT) and contracted (PAL, CHS, and F3΄5΄H) gene families with tissue-specific expression, may be important contributors to the high accumulation levels of polyphenolic compounds observed in longan fruit. The high number of genes encoding nucleotide-binding site leucine-rich repeat (NBS-LRR) and leucine-rich repeat receptor-like kinase proteins, as well as the recent expansion and contraction of the NBS-LRR family, suggested a genomic basis for resistance to insects, fungus, and bacteria in this fruit tree. These data provide insights into the evolution and diversity of the longan genome. The comparative genomic and transcriptome analyses provided information about longan-specific traits, particularly genes involved in its polyphenol-rich and pathogen resistance characteristics.

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BPC 157 promotes angiogenesis in CAM assay and tube formation assay. BPC 157 accelerates the blood flow recovery and vessel number in rats with hind limb ischemia. BPC 157 up-regulates VEGFR2 expression in rats with hind limb ischemia and endothelial cell culture. BPC 157 promotes VEGFR2 internalization in association with VEGFR2-Akt-eNOS activation.