Acetylation of PHF5A Modulates Stress Responses and Colorectal Carcinogenesis through Alternative Splicing-Mediated Upregulation of KDM3A.

Alternative pre-mRNA-splicing-induced post-transcriptional gene expression regulation is one of the pathways for tumors maintaining proliferation rates accompanying the malignant phenotype under stress. Here, we uncover a list of hyperacetylated proteins in the context of acutely reduced Acetyl-CoA levels under nutrient starvation. PHF5A, a component of U2 snRNPs, can be acetylated at lysine 29 in response to multiple cellular stresses, which is dependent on p300. PHF5A acetylation strengthens the interaction among U2 snRNPs and affects global pre-mRNA splicing pattern and extensive gene expression. PHF5A hyperacetylation-induced alternative splicing stabilizes KDM3A mRNA and promotes its protein expression. Pathologically, PHF5A K29 hyperacetylation and KDM3A upregulation axis are correlated with poor prognosis of colon cancer. Our findings uncover a mechanism of an anti-stress pathway through which acetylation on PHF5A promotes the cancer cells' capacity for stress resistance and consequently contributes to colon carcinogenesis.

OPIA: an open archive of plant images and related phenotypic traits.

High-throughput plant phenotype acquisition technologies have been extensively utilized in plant phenomics studies, leading to vast quantities of images and image-based phenotypic traits (i-traits) that are critically essential for accelerating germplasm screening, plant diseases identification and biotic & abiotic stress classification. Here, we present the Open Plant Image Archive (OPIA, https://ngdc.cncb.ac.cn/opia/), an open archive of plant images and i-traits derived from high-throughput phenotyping platforms. Currently, OPIA houses 56 datasets across 11 plants, comprising a total of 566 225 images with 2 417 186 labeled instances. Notably, it incorporates 56 i-traits of 93 rice and 105 wheat cultivars based on 18 644 individual RGB images, and these i-traits are further annotated based on the Plant Phenotype and Trait Ontology (PPTO) and cross-linked with GWAS Atlas. Additionally, each dataset in OPIA is assigned an evaluation score that takes account of image data volume, image resolution, and the number of labeled instances. More importantly, OPIA is equipped with useful tools for online image pre-processing and intelligent prediction. Collectively, OPIA provides open access to valuable datasets, pre-trained models, and phenotypic traits across diverse plants and thus bears great potential to play a crucial role in facilitating artificial intelligence-assisted breeding research.

The P10K database: a data portal for the protist 10 000 genomes project.

Protists, a highly diverse group of microscopic eukaryotic organisms distinct from fungi, animals and plants, exert crucial roles within the earth's biosphere. However, the genomes of only a small fraction of known protist species have been published and made publicly accessible. To address this constraint, the Protist 10 000 Genomes Project (P10K) was initiated, implementing a specialized pipeline for single-cell genome/transcriptome assembly, decontamination and annotation of protists. The resultant P10K database (https://ngdc.cncb.ac.cn/p10k/) serves as a comprehensive platform, collating and disseminating genome sequences and annotations from diverse protist groups. Currently, the P10K database has incorporated 2959 genomes and transcriptomes, including 1101 newly sequenced datasets by P10K and 1858 publicly available datasets. Notably, it covers 45% of the protist orders, with a significant representation (53% coverage) of ciliates, featuring nearly a thousand genomes/transcriptomes. Intriguingly, analysis of the unique codon table usage among ciliates has revealed differences compared to the NCBI taxonomy system, suggesting a need to revise the codon tables used for these species. Collectively, the P10K database serves as a valuable repository of genetic resources for protist research and aims to expand its collection by incorporating more sequenced data and advanced analysis tools to benefit protist studies worldwide.

Lineage-specific genes are clustered with HET-domain genes and respond to environmental and genetic manipulations regulating reproduction in Neurospora.

Lineage-specific genes (LSGs) have long been postulated to play roles in the establishment of genetic barriers to intercrossing and speciation. In the genome of Neurospora crassa, most of the 670 Neurospora LSGs that are aggregated adjacent to the telomeres are clustered with 61% of the HET-domain genes, some of which regulate self-recognition and define vegetative incompatibility groups. In contrast, the LSG-encoding proteins possess few to no domains that would help to identify potential functional roles. Possible functional roles of LSGs were further assessed by performing transcriptomic profiling in genetic mutants and in response to environmental alterations, as well as examining gene knockouts for phenotypes. Among the 342 LSGs that are dynamically expressed during both asexual and sexual phases, 64% were detectable on unusual carbon sources such as furfural, a wildfire-produced chemical that is a strong inducer of sexual development, and the structurally-related furan 5-hydroxymethyl furfural (HMF). Expression of a significant portion of the LSGs was sensitive to light and temperature, factors that also regulate the switch from asexual to sexual reproduction. Furthermore, expression of the LSGs was significantly affected in the knockouts of adv-1 and pp-1 that regulate hyphal communication, and expression of more than one quarter of the LSGs was affected by perturbation of the mating locus. These observations encouraged further investigation of the roles of clustered lineage-specific and HET-domain genes in ecology and reproduction regulation in Neurospora, especially the regulation of the switch from the asexual growth to sexual reproduction, in response to dramatic environmental conditions changes.

McAN: a novel computational algorithm and platform for constructing and visualizing haplotype networks.

Haplotype networks are graphs used to represent evolutionary relationships between a set of taxa and are characterized by intuitiveness in analyzing genealogical relationships of closely related genomes. We here propose a novel algorithm termed McAN that considers mutation spectrum history (mutations in ancestry haplotype should be contained in descendant haplotype), node size (corresponding to sample count for a given node) and sampling time when constructing haplotype network. We show that McAN is two orders of magnitude faster than state-of-the-art algorithms without losing accuracy, making it suitable for analysis of a large number of sequences. Based on our algorithm, we developed an online web server and offline tool for haplotype network construction, community lineage determination, and interactive network visualization. We demonstrate that McAN is highly suitable for analyzing and visualizing massive genomic data and is helpful to enhance the understanding of genome evolution. Availability: Source code is written in C/C++ and available at https://github.com/Theory-Lun/McAN and https://ngdc.cncb.ac.cn/biocode/tools/BT007301 under the MIT license. Web server is available at https://ngdc.cncb.ac.cn/bit/hapnet/. SARS-CoV-2 dataset are available at https://ngdc.cncb.ac.cn/ncov/. Contact: songshh@big.ac.cn (Song S), zhaowm@big.ac.cn (Zhao W), baoym@big.ac.cn (Bao Y), zhangzhang@big.ac.cn (Zhang Z), ybxue@big.ac.cn (Xue Y).

LncBook 2.0: integrating human long non-coding RNAs with multi-omics annotations.

LncBook, a comprehensive resource of human long non-coding RNAs (lncRNAs), has been used in a wide range of lncRNA studies across various biological contexts. Here, we present LncBook 2.0 (https://ngdc.cncb.ac.cn/lncbook), with significant updates and enhancements as follows: (i) incorporation of 119 722 new transcripts, 9632 new genes, and gene structure update of 21 305 lncRNAs; (ii) characterization of conservation features of human lncRNA genes across 40 vertebrates; (iii) integration of lncRNA-encoded small proteins; (iv) enrichment of expression and DNA methylation profiles with more biological contexts and (v) identification of lncRNA-protein interactions and improved prediction of lncRNA-miRNA interactions. Collectively, LncBook 2.0 accommodates a high-quality collection of 95 243 lncRNA genes and 323 950 transcripts and incorporates their abundant annotations at different omics levels, thereby enabling users to decipher functional significance of lncRNAs in different biological contexts.

Brain Catalog: a comprehensive resource for the genetic landscape of brain-related traits.

A broad range of complex phenotypes are related to dysfunctions in brain (hereafter referred to as brain-related traits), including various mental and behavioral disorders and diseases of the nervous system. These traits in general share overlapping symptoms, pathogenesis, and genetic components. Here, we present Brain Catalog (https://ngdc.cncb.ac.cn/braincatalog), a comprehensive database aiming to delineate the genetic components of more than 500 GWAS summary statistics datasets for brain-related traits from multiple aspects. First, Brain Catalog provides results of candidate causal variants, causal genes, and functional tissues and cell types for each trait identified by multiple methods using comprehensive annotation datasets (58 QTL datasets spanning 6 types of QTLs). Second, Brain Catalog estimates the SNP-based heritability, the partitioning heritability based on functional annotations, and genetic correlations among traits. Finally, through bidirectional Mendelian randomization analyses, Brain Catalog presents inference of risk factors that are likely causal to each trait. In conclusion, Brain Catalog presents a one-stop shop for the genetic components of brain-related traits, potentially serving as a valuable resource for worldwide researchers to advance the understanding of how GWAS signals may contribute to the biological etiology of brain-related traits.

GWAS Atlas: an updated knowledgebase integrating more curated associations in plants and animals.

GWAS Atlas (https://ngdc.cncb.ac.cn/gwas/) is a manually curated resource of genome-wide genotype-to-phenotype associations for a wide range of species. Here, we present an updated implementation of GWAS Atlas by curating and incorporating more high-quality associations, with significant improvements and advances over the previous version. Specifically, the current release of GWAS Atlas incorporates a total of 278,109 curated genotype-to-phenotype associations for 1,444 different traits across 15 species (10 plants and 5 animals) from 830 publications and 3,432 studies. A collection of 6,084 lead SNPs of 439 traits and 486 experiment-validated causal variants of 157 traits are newly added. Moreover, 1,056 trait ontology terms are newly defined, resulting in 1,172 and 431 terms for Plant Phenotype and Trait Ontology and Animal Phenotype and Trait Ontology, respectively. Additionally, it is equipped with four online analysis tools and a submission platform, allowing users to perform data analysis and data submission. Collectively, as a core resource in the National Genomics Data Center, GWAS Atlas provides valuable genotype-to-phenotype associations for a diversity of species and thus plays an important role in agronomic trait study and molecular breeding.

Cell Taxonomy: a curated repository of cell types with multifaceted characterization.

Single-cell studies have delineated cellular diversity and uncovered increasing numbers of previously uncharacterized cell types in complex tissues. Thus, synthesizing growing knowledge of cellular characteristics is critical for dissecting cellular heterogeneity, developmental processes and tumorigenesis at single-cell resolution. Here, we present Cell Taxonomy (https://ngdc.cncb.ac.cn/celltaxonomy), a comprehensive and curated repository of cell types and associated cell markers encompassing a wide range of species, tissues and conditions. Combined with literature curation and data integration, the current version of Cell Taxonomy establishes a well-structured taxonomy for 3,143 cell types and houses a comprehensive collection of 26,613 associated cell markers in 257 conditions and 387 tissues across 34 species. Based on 4,299 publications and single-cell transcriptomic profiles of ∼3.5 million cells, Cell Taxonomy features multifaceted characterization for cell types and cell markers, involving quality assessment of cell markers and cell clusters, cross-species comparison, cell composition of tissues and cellular similarity based on markers. Taken together, Cell Taxonomy represents a fundamentally useful reference to systematically and accurately characterize cell types and thus lays an important foundation for deeply understanding and exploring cellular biology in diverse species.

MethBank 4.0: an updated database of DNA methylation across a variety of species.

DNA methylation, as the most intensively studied epigenetic mark, regulates gene expression in numerous biological processes including development, aging, and disease. With the rapid accumulation of whole-genome bisulfite sequencing data, integrating, archiving, analyzing, and visualizing those data becomes critical. Since its first publication in 2015, MethBank has been continuously updated to include more DNA methylomes across more diverse species. Here, we present MethBank 4.0 (https://ngdc.cncb.ac.cn/methbank/), which reports an increase of 309% in data volume, with 1449 single-base resolution methylomes of 23 species, covering 236 tissues/cell lines and 15 biological contexts. Value-added information, such as more rigorous quality evaluation, more standardized metadata, and comprehensive downstream annotations have been integrated in the new version. Moreover, expert-curated knowledge modules of featured differentially methylated genes associated with biological contexts and methylation analysis tools have been incorporated as new components of MethBank. In addition, MethBank 4.0 is equipped with a series of new web interfaces to browse, search, and visualize DNA methylation profiles and related information. With all these improvements, we believe the updated MethBank 4.0 will serve as a fundamental resource to provide a wide range of data services for the global research community.

HGD: an integrated homologous gene database across multiple species.

Homology is fundamental to infer genes' evolutionary processes and relationships with shared ancestry. Existing homolog gene resources vary in terms of inferring methods, homologous relationship and identifiers, posing inevitable difficulties for choosing and mapping homology results from one to another. Here, we present HGD (Homologous Gene Database, https://ngdc.cncb.ac.cn/hgd), a comprehensive homologs resource integrating multi-species, multi-resources and multi-omics, as a complement to existing resources providing public and one-stop data service. Currently, HGD houses a total of 112 383 644 homologous pairs for 37 species, including 19 animals, 16 plants and 2 microorganisms. Meanwhile, HGD integrates various annotations from public resources, including 16 909 homologs with traits, 276 670 homologs with variants, 398 573 homologs with expression and 536 852 homologs with gene ontology (GO) annotations. HGD provides a wide range of omics gene function annotations to help users gain a deeper understanding of gene function.

Unraveling Reactivity Differences: Room-Temperature Ring-Opening Metathesis Polymerization (ROMP) versus Frontal ROMP.

In this study, we explore the distinct reactivity patterns between frontal ring-opening metathesis polymerization (FROMP) and room-temperature solventless ring-opening metathesis polymerization (ROMP). Despite their shared mechanism, we find that FROMP is less sensitive to inhibitor concentration than room-temperature ROMP. By increasing the initiator-to-monomer ratio for a fixed inhibitor/initiator quantity, we find reduction in the ROMP background reactivity at room temperature (i.e., increased resin pot life). At elevated temperatures where inhibitor dissociation prevails, accelerated frontal polymerization rates are observed because of the concentrated presence of the initiator. Surprisingly, the strategy of employing higher initiator loading enhances both pot life and front speeds, which leads to FROMP rates exceeding prior reported values by over 5 times. This counterintuitive behavior is attributed to an increase in the proximity of the inhibitor to the initiator within the bulk resin and to whether the temperature favors coordination or dissociation of the inhibitor. A rapid method was developed for assessing resin pot life, and a straightforward model for active initiator behavior was established. Modified resin systems enabled direct ink writing of robust thermoset structures at rates much faster than previously possible.

Systematic calibration of epitranscriptomic maps using a synthetic modification-free RNA library.

Recent years have witnessed rapid progress in the field of epitranscriptomics. Functional interpretation of the epitranscriptome relies on sequencing technologies that determine the location and stoichiometry of various RNA modifications. However, contradictory results have been reported among studies, bringing the biological impacts of certain RNA modifications into doubt. Here, we develop a synthetic RNA library resembling the endogenous transcriptome but without any RNA modification. By incorporating this modification-free RNA library into established mapping techniques as a negative control, we reveal abundant false positives resulting from sequence bias or RNA structure. After calibration, precise and quantitative mapping expands the understanding of two representative modification types, N6-methyladenosine (m6A) and 5-methylcytosine (m5C). We propose that this approach provides a systematic solution for the calibration of various RNA-modification mappings and holds great promise in epitranscriptomic studies.

Discovery of a potent and selective covalent threonine tyrosine kinase (TTK) inhibitor.

Threonine tyrosine kinase (TTK) is a critical component of the spindle assembly checkpoint and plays a pivotal role in mitosis. TTK has been identified as a potential therapeutic target for human cancers. Here, we describe our design, synthesis and evaluation of a class of covalent TTK inhibitors, exemplified by 16 (SYL1073). Compound 16 potently inhibits TTK kinase with an IC50 of 0.016 µM and displays improved selectivity in a panel of kinases. Mass spectrometry analysis reveals that 16 covalently binds to the C604 cysteine residue in the hinge region of the TTK kinase domain. Furthermore, 16 achieves strong potency in inhibiting the growth of various human cancer cell lines, outperforming its relative reversible inhibitor, and eliciting robust downstream effects. Taken together, compound 16 provides a valuable lead compound for further optimization toward the development of drug for treatment of human cancers.

CompoDynamics: a comprehensive database for characterizing sequence composition dynamics.

Sequence compositions of nucleic acids and proteins have significant impact on gene expression, RNA stability, translation efficiency, RNA/protein structure and molecular function, and are associated with genome evolution and adaptation across all kingdoms of life. Therefore, a devoted resource of sequence compositions and associated features is fundamentally crucial for a wide range of biological research. Here, we present CompoDynamics (https://ngdc.cncb.ac.cn/compodynamics/), a comprehensive database of sequence compositions of coding sequences (CDSs) and genomes for all kinds of species. Taking advantage of the exponential growth of RefSeq data, CompoDynamics presents a wealth of sequence compositions (nucleotide content, codon usage, amino acid usage) and derived features (coding potential, physicochemical property and phase separation) for 118 689 747 high-quality CDSs and 34 562 genomes across 24 995 species. Additionally, interactive analytical tools are provided to enable comparative analyses of sequence compositions and molecular features across different species and gene groups. Collectively, CompoDynamics bears the great potential to better understand the underlying roles of sequence composition dynamics across genes and genomes, providing a fundamental resource in support of a broad spectrum of biological studies.

LncRNAWiki 2.0: a knowledgebase of human long non-coding RNAs with enhanced curation model and database system.

LncRNAWiki, a knowledgebase of human long non-coding RNAs (lncRNAs), has been rapidly expanded by incorporating more experimentally validated lncRNAs. Since it was built based on MediaWiki as its database system, it fails to manage data in a structured way and is ineffective to support systematic exploration of lncRNAs. Here we present LncRNAWiki 2.0 (https://ngdc.cncb.ac.cn/lncrnawiki), which is significantly improved with enhanced database system and curation model. In LncRNAWiki 2.0, all contents are organized in a structured manner powered by MySQL/Java and curators are able to submit/edit annotations based on the curation model that includes a wider range of annotation items. Moreover, it is equipped with popular online tools to help users identify lncRNAs with potentially important functions, and provides more user-friendly web interfaces to facilitate data curation, retrieval and visualization. Consequently, LncRNAWiki 2.0 incorporates a total of 2512 lncRNAs and 106 242 associations for disease, function, drug, interacting partner, molecular signature, experimental sample, CRISPR design, etc., thus providing a comprehensive and up-to-date resource of functionally annotated lncRNAs in human.

LIRBase: a comprehensive database of long inverted repeats in eukaryotic genomes.

Small RNAs (sRNAs) constitute a large portion of functional elements in eukaryotic genomes. Long inverted repeats (LIRs) can be transcribed into long hairpin RNAs (hpRNAs), which can further be processed into small interfering RNAs (siRNAs) with vital biological roles. In this study, we systematically identified a total of 6 619 473 LIRs in 424 eukaryotic genomes and developed LIRBase (https://venyao.xyz/lirbase/), a specialized database of LIRs across different eukaryotic genomes aiming to facilitate the annotation and identification of LIRs encoding long hpRNAs and siRNAs. LIRBase houses a comprehensive collection of LIRs identified in a wide range of eukaryotic genomes. In addition, LIRBase not only allows users to browse and search the identified LIRs in any eukaryotic genome(s) of interest available in GenBank, but also provides friendly web functionalities to facilitate users to identify LIRs in user-uploaded sequences, align sRNA sequencing data to LIRs, perform differential expression analysis of LIRs, predict mRNA targets for LIR-derived siRNAs, and visualize the secondary structure of candidate long hpRNAs encoded by LIRs. As demonstrated by two case studies, collectively, LIRBase bears the great utility for systematic investigation and characterization of LIRs and functional exploration of potential roles of LIRs and their derived siRNAs in diverse species.

BrainBase: a curated knowledgebase for brain diseases.

Brain is the central organ of the nervous system and any brain disease can seriously affect human health. Here we present BrainBase (https://ngdc.cncb.ac.cn/brainbase), a curated knowledgebase for brain diseases that aims to provide a whole picture of brain diseases and associated genes. Specifically, based on manual curation of 2768 published articles along with information retrieval from several public databases, BrainBase features comprehensive collection of 7175 disease-gene associations spanning a total of 123 brain diseases and linking with 5662 genes, 16 591 drug-target interactions covering 2118 drugs/chemicals and 623 genes, and five types of specific genes in light of expression specificity in brain tissue/regions/cerebrospinal fluid/cells. In addition, considering the severity of glioma among brain tumors, the current version of BrainBase incorporates 21 multi-omics datasets, presents molecular profiles across various samples/conditions and identifies four groups of glioma featured genes with potential clinical significance. Collectively, BrainBase integrates not only valuable curated disease-gene associations and drug-target interactions but also molecular profiles through multi-omics data analysis, accordingly bearing great promise to serve as a valuable knowledgebase for brain diseases.

EWAS Open Platform: integrated data, knowledge and toolkit for epigenome-wide association study.

Epigenome-Wide Association Study (EWAS) has become a standard strategy to discover DNA methylation variation of different phenotypes. Since 2018, we have developed EWAS Atlas and EWAS Data Hub to integrate a growing volume of EWAS knowledge and data, respectively. Here, we present EWAS Open Platform (https://ngdc.cncb.ac.cn/ewas) that includes EWAS Atlas, EWAS Data Hub and the newly developed EWAS Toolkit. In the current implementation, EWAS Open Platform integrates 617 018 high-quality EWAS associations from 910 publications, covering 51 phenotypes, 275 diseases and 104 environmental factors. It also provides well-normalized DNA methylation array data and the corresponding metadata from 115 852 samples, which involve 707 tissues, 218 cell lines and 528 diseases. Taking advantage of integrated knowledge and data in EWAS Atlas and EWAS Data Hub, EWAS Open Platform equips with EWAS Toolkit, a powerful one-stop site for EWAS enrichment, annotation, and knowledge network construction and visualization. Collectively, EWAS Open Platform provides open access to EWAS knowledge, data and toolkit and thus bears great utility for a broader range of relevant research.