N6-methyladenine DNA modification in Drosophila.

DNA N(6)-methyladenine (6mA) modification is commonly found in microbial genomes and plays important functions in regulating numerous biological processes in bacteria. However, whether 6mA occurs and what its potential roles are in higher-eukaryote cells remain unknown. Here, we show that 6mA is present in Drosophila genome and that the 6mA modification is dynamic and is regulated by the Drosophila Tet homolog, DNA 6mA demethylase (DMAD), during embryogenesis. Importantly, our biochemical assays demonstrate that DMAD directly catalyzes 6mA demethylation in vitro. Further genetic and sequencing analyses reveal that DMAD is essential for development and that DMAD removes 6mA primarily from transposon regions, which correlates with transposon suppression in Drosophila ovary. Collectively, we uncover a DNA modification in Drosophila and describe a potential role of the DMAD-6mA regulatory axis in controlling development in higher eukaryotes.

RIC-seq for global in situ profiling of RNA-RNA spatial interactions.

Highly structured RNA molecules usually interact with each other, and associate with various RNA-binding proteins, to regulate critical biological processes. However, RNA structures and interactions in intact cells remain largely unknown. Here, by coupling proximity ligation mediated by RNA-binding proteins with deep sequencing, we report an RNA in situ conformation sequencing (RIC-seq) technology for the global profiling of intra- and intermolecular RNA-RNA interactions. This technique not only recapitulates known RNA secondary structures and tertiary interactions, but also facilitates the generation of three-dimensional (3D) interaction maps of RNA in human cells. Using these maps, we identify noncoding RNA targets globally, and discern RNA topological domains and trans-interacting hubs. We reveal that the functional connectivity of enhancers and promoters can be assigned using their pairwise-interacting RNAs. Furthermore, we show that CCAT1-5L-a super-enhancer hub RNA-interacts with the RNA-binding protein hnRNPK, as well as RNA derived from the MYC promoter and enhancer, to boost MYC transcription by modulating chromatin looping. Our study demonstrates the power and applicability of RIC-seq in discovering the 3D structures, interactions and regulatory roles of RNA.

The Augmented R-Loop Is a Unifying Mechanism for Myelodysplastic Syndromes Induced by High-Risk Splicing Factor Mutations.

Mutations in several general pre-mRNA splicing factors have been linked to myelodysplastic syndromes (MDSs) and solid tumors. These mutations have generally been assumed to cause disease by the resultant splicing defects, but different mutations appear to induce distinct splicing defects, raising the possibility that an alternative common mechanism is involved. Here we report a chain of events triggered by multiple splicing factor mutations, especially high-risk alleles in SRSF2 and U2AF1, including elevated R-loops, replication stress, and activation of the ataxia telangiectasia and Rad3-related protein (ATR)-Chk1 pathway. We further demonstrate that enhanced R-loops, opposite to the expectation from gained RNA binding with mutant SRSF2, result from impaired transcription pause release because the mutant protein loses its ability to extract the RNA polymerase II (Pol II) C-terminal domain (CTD) kinase-the positive transcription elongation factor complex (P-TEFb)-from the 7SK complex. Enhanced R-loops are linked to compromised proliferation of bone-marrow-derived blood progenitors, which can be partially rescued by RNase H overexpression, suggesting a direct contribution of augmented R-loops to the MDS phenotype.

Adaptive Selection of Cis-regulatory Elements in the Han Chinese.

Cis-regulatory elements have an important role in human adaptation to the living environment. However, the lag in population genomic cohort studies and epigenomic studies, hinders the research in the adaptive analysis of cis-regulatory elements in human populations. In this study, we collected 4,013 unrelated individuals and performed a comprehensive analysis of adaptive selection of genome-wide cis-regulatory elements in the Han Chinese. In total, 12.34% of genomic regions are under the influence of adaptive selection, where 1.00% of enhancers and 2.06% of promoters are under positive selection, and 0.06% of enhancers and 0.02% of promoters are under balancing selection. Gene ontology enrichment analysis of these cis-regulatory elements under adaptive selection reveals that many positive selections in the Han Chinese occur in pathways involved in cell-cell adhesion processes, and many balancing selections are related to immune processes. Two classes of adaptive cis-regulatory elements related to cell adhesion were in-depth analyzed, one is the adaptive enhancers derived from neanderthal introgression, leads to lower hyaluronidase level in skin, and brings better performance on UV-radiation resistance to the Han Chinese. Another one is the cis-regulatory elements regulating wound healing, and the results suggest the positive selection inhibits coagulation and promotes angiogenesis and wound healing in the Han Chinese. Finally, we found that many pathogenic alleles, such as risky alleles of type 2 diabetes or schizophrenia, remain in the population due to the hitchhiking effect of positive selections. Our findings will help deepen our understanding of the adaptive evolution of genome regulation in the Han Chinese.

NPInter v5.0: ncRNA interaction database in a new era.

Noncoding RNAs (ncRNAs) play key regulatory roles in biological processes by interacting with other biomolecules. With the development of high-throughput sequencing and experimental technologies, extensive ncRNA interactions have been accumulated. Therefore, we updated the NPInter database to a fifth version to document these interactions. ncRNA interaction entries were doubled from 1 100 618 to 2 596 695 by manual literature mining and high-throughput data processing. We integrated global RNA-DNA interactions from iMARGI, ChAR-seq and GRID-seq, greatly expanding the number of RNA-DNA interactions (from 888 915 to 8 329 382). In addition, we collected different types of RNA interaction between SARS-CoV-2 virus and its host from recently published studies. Long noncoding RNA (lncRNA) expression specificity in different cell types from tumor single cell RNA-seq (scRNA-seq) data were also integrated to provide a cell-type level view of interactions. A new module named RBP was built to display the interactions of RNA-binding proteins with annotations of localization, binding domains and functions. In conclusion, NPInter v5.0 (http://bigdata.ibp.ac.cn/npinter5/) provides informative and valuable ncRNA interactions for biological researchers.

Characterizing mobile element insertions in 5675 genomes.

Mobile element insertions (MEIs) are a major class of structural variants (SVs) and have been linked to many human genetic disorders, including hemophilia, neurofibromatosis, and various cancers. However, human MEI resources from large-scale genome sequencing are still lacking compared to those for SNPs and SVs. Here, we report a comprehensive map of 36 699 non-reference MEIs constructed from 5675 genomes, comprising 2998 Chinese samples (∼26.2×, NyuWa) and 2677 samples from the 1000 Genomes Project (∼7.4×, 1KGP). We discovered that LINE-1 insertions were highly enriched in centromere regions, implying the role of chromosome context in retroelement insertion. After functional annotation, we estimated that MEIs are responsible for about 9.3% of all protein-truncating events per genome. Finally, we built a companion database named HMEID for public use. This resource represents the latest and largest genomewide study on MEIs and will have broad utility for exploration of human MEI findings.

piRBase: integrating piRNA annotation in all aspects.

Piwi-interacting RNAs are a type of small noncoding RNA that have various functions. piRBase is a manually curated resource focused on assisting piRNA functional analysis. piRBase release v3.0 is committed to providing more comprehensive piRNA related information. The latest release covers >181 million unique piRNA sequences, including 440 datasets from 44 species. More disease-related piRNAs and piRNA targets have been collected and displayed. The regulatory relationships between piRNAs and targets have been visualized. In addition to the reuse and expansion of the content in the previous version, the latest version has additional new content, including gold standard piRNA sets, piRNA clusters, piRNA variants, splicing-junction piRNAs, and piRNA expression data. In addition, the entire web interface has been redesigned to provide a better experience for users. piRBase release v3.0 is free to access, browse, search, and download at http://bigdata.ibp.ac.cn/piRBase.

Active retrotransposons help maintain pericentromeric heterochromatin required for faithful cell division.

Retrotransposons are populated in vertebrate genomes, and when active, are thought to cause genome instability with potential benefit to genome evolution. Retrotransposon-derived RNAs are also known to give rise to small endo-siRNAs to help maintain heterochromatin at their sites of transcription; however, as not all heterochromatic regions are equally active in transcription, it remains unclear how heterochromatin is maintained across the genome. Here, we address these problems by defining the origins of repeat-derived RNAs and their specific chromatin locations in Drosophila S2 cells. We demonstrate that repeat RNAs are predominantly derived from active gypsy elements and processed by Dcr-2 into small RNAs to help maintain pericentromeric heterochromatin. We also show in cultured S2 cells that synthetic repeat-derived endo-siRNA mimics are sufficient to rescue Dcr-2-deficiency-induced defects in heterochromatin formation in interphase and chromosome segregation during mitosis, demonstrating that active retrotransposons are required for stable genetic inheritance.

NONCODEV6: an updated database dedicated to long non-coding RNA annotation in both animals and plants.

NONCODE (http://www.noncode.org/) is a comprehensive database of collection and annotation of noncoding RNAs, especially long non-coding RNAs (lncRNAs) in animals. NONCODEV6 is dedicated to providing the full scope of lncRNAs across plants and animals. The number of lncRNAs in NONCODEV6 has increased from 548 640 to 644 510 since the last update in 2017. The number of human lncRNAs has increased from 172 216 to 173 112. The number of mouse lncRNAs increased from 131 697 to 131 974. The number of plant lncRNAs is 94 697. The relationship between lncRNAs in human and cancer were updated with transcriptome sequencing profiles. Three important new features were also introduced in NONCODEV6: (i) updated human lncRNA-disease relationships, especially cancer; (ii) lncRNA annotations with tissue expression profiles and predicted function in five common plants; iii) lncRNAs conservation annotation at transcript level for 23 plant species. NONCODEV6 is accessible through http://www.noncode.org/.

NPInter v4.0: an integrated database of ncRNA interactions.

Noncoding RNAs (ncRNAs) play crucial regulatory roles in a variety of biological circuits. To document regulatory interactions between ncRNAs and biomolecules, we previously created the NPInter database (http://bigdata.ibp.ac.cn/npinter). Since the last version of NPInter was issued, a rapidly growing number of studies have reported novel interactions and accumulated numerous high-throughput interactome data. We have therefore updated NPInter to its fourth edition in which are integrated 600 000 new experimentally identified ncRNA interactions. ncRNA-DNA interactions derived from ChIRP-seq data and circular RNA interactions have been included in the database. Additionally, disease associations were annotated to the interacting molecules. The database website has also been redesigned with a more user-friendly interface and several additional functional modules. Overall, NPInter v4.0 now provides more comprehensive data and services for researchers working on ncRNAs and their interactions with other biomolecules.

piRBase: a comprehensive database of piRNA sequences.

PIWI-interacting RNAs are a class of small RNAs that is most abundantly expressed in animal germline. Substantial research is going on to reveal the functions of piRNAs in the epigenetic and post-transcriptional regulation of transposons and genes. To collect and annotate these data, we developed piRBase, a database assisting piRNA functional study. Since its launch in 2014, piRBase has integrated 264 data sets from 21 organisms, and the number of collected piRNAs has reached 173 million. The latest piRBase release (v2.0, 2018) was more focused on the comprehensive annotation of piRNA sequences, as well as the increasing number of piRNAs. In addition, piRBase release v2.0 also contained the potential information of piRNA targets and disease related piRNA. All datasets in piRBase is free to access, and available for browse, search and bulk downloads at http://www.regulatoryrna.org/database/piRNA/.

SmProt: a database of small proteins encoded by annotated coding and non-coding RNA loci.

Small proteins is the general term for proteins with length shorter than 100 amino acids. Identification and functional studies of small proteins have advanced rapidly in recent years, and several studies have shown that small proteins play important roles in diverse functions including development, muscle contraction and DNA repair. Identification and characterization of previously unrecognized small proteins may contribute in important ways to cell biology and human health. Current databases are generally somewhat deficient in that they have either not collected small proteins systematically, or contain only predictions of small proteins in a limited number of tissues and species. Here, we present a specifically designed web-accessible database, small proteins database (SmProt, http://bioinfo.ibp.ac.cn/SmProt), which is a database documenting small proteins. The current release of SmProt incorporates 255 010 small proteins computationally or experimentally identified in 291 cell lines/tissues derived from eight popular species. The database provides a variety of data including basic information (sequence, location, gene name, organism, etc.) as well as specific information (experiment, function, disease type, etc.). To facilitate data extraction, SmProt supports multiple search options, including species, genome location, gene name and their aliases, cell lines/tissues, ORF type, gene type, PubMed ID and SmProt ID. SmProt also incorporates a service for the BLAST alignment search and provides a local UCSC Genome Browser. Additionally, SmProt defines a high-confidence set of small proteins and predicts the functions of the small proteins.

Dynamic-BM: multispecies Dynamic BodyMap database from temporal RNA-seq data.

Biological processes, especially developmental processes, are often dynamic. Previous BodyMap projects for human and mouse have provided researchers with portals to tissue-specific gene expression, but these efforts have not included dynamic gene expression patterns. Over the past few years, substantial progress in our understanding of the molecular mechanisms of protein-coding and long noncoding RNA (lncRNA) genes in development processes has been achieved through numerous time series RNA sequencing (RNA-seq) studies. However, none of the existing databases focuses on these time series data, thus rendering the exploration of dynamic gene expression patterns inconvenient. Here, we present Dynamic BodyMap (Dynamic-BM), a database for temporal gene expression profiles, obtained from 2203 time series of RNA-seq samples, covering >25 tissues from five species. Dynamic-BM has a user-friendly Web interface designed for browsing and searching the dynamic expression pattern of genes from different sources. It is an open resource for efficient data exploration, providing dynamic expression profiles of both protein-coding genes and lncRNAs to facilitate the generation of new hypotheses in developmental biology research. Additionally, Dynamic-BM includes a literature-based knowledgebase for lncRNAs associated with tissue development and a list of manually selected lncRNA candidates that may be involved in tissue development. Dynamic-BM is available at http://bioinfo.ibp.ac.cn/Dynamic-BM.

LncVar: a database of genetic variation associated with long non-coding genes.

MOTIVATION: Long non-coding RNAs (lncRNAs) are essential in many molecular pathways, and are frequently associated with disease but the mechanisms of most lncRNAs have not yet been characterized. Genetic variations, including single nucleotide polymorphisms (SNPs) and structural variations, are widely distributed in the genome, including lncRNA gene regions. As the number of studies on lncRNAs grows rapidly, it is necessary to evaluate the effects of genetic variations on lncRNAs. RESULTS: Here, we present LncVar, a database of genetic variation associated with long non-coding genes in six species. We collected lncRNAs from the NONCODE database, and evaluated their conservation. We systematically integrated transcription factor binding sites and m6A modification sites of lncRNAs and provided comprehensive effects of SNPs on transcription and modification of lncRNAs. We collected putatively translated open reading frames (ORFs) in lncRNAs, and identified both synonymous and non-synonymous SNPs in ORFs. We also collected expression quantitative trait loci of lncRNAs from the literature. Furthermore, we identified lncRNAs in CNV regions as prognostic biomarker candidates of cancers and predicted lncRNA gene fusion events from RNA-seq data from cell lines. The LncVar database can be used as a resource to evaluate the effects of the variations on the biological function of lncRNAs. AVAILABILITY AND IMPLEMENTATION: LncVar is available at http://bioinfo.ibp.ac.cn/LncVar CONTACT: rschen@ibp.ac.cnSupplementary information: Supplementary materials are available at Bioinformatics online.

BioCircos.js: an interactive Circos JavaScript library for biological data visualization on web applications.

UNLABELLED: We here present BioCircos.js, an interactive and lightweight JavaScript library especially for biological data interactive visualization. BioCircos.js facilitates the development of web-based applications for circular visualization of various biological data, such as genomic features, genetic variations, gene expression and biomolecular interactions. AVAILABILITY AND IMPLEMENTATION: BioCircos.js and its manual are freely available online at http://bioinfo.ibp.ac.cn/biocircos/ CONTACT: rschen@ibp.ac.cn SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Computational identification of piRNA targets on mouse mRNAs.

MOTIVATION: PIWI-interacting RNAs (piRNAs) are a class of small non-coding RNAs that are highly abundant in the germline. One important role of piRNAs is to defend genome integrity by guiding PIWI proteins to silence transposable elements (TEs), which have a high potential to cause deleterious effects on their host. The mechanism of piRNA-mediated post-transcriptional silencing was also observed to affect mRNAs, suggesting that piRNAs might play a broad role in gene expression regulation. However, there has been no systematic report with regard to how many protein-coding genes might be targeted and regulated by piRNAs. RESULTS: We trained a support vector machine classifier based on a combination of Miwi CLIP-Seq-derived features and position-derived features to predict the potential targets of piRNAs on mRNAs in the mouse. Reanalysis of a published microarray dataset suggested that the expression level of the 2587 protein-coding genes predicted as piRNA targets showed significant upregulation as a whole after abolishing the slicer activity of Miwi, supporting the conclusion that they are subject to piRNA-mediated regulation. AVAILABILITY AND IMPLEMENTATION: A web version of the method called pirnaPre as well as our results for browse is available at http://www.regulatoryrna.org/software/piRNA/piRNA_target_mRNA/index.php CONTACT: crs@sun5.ibp.ac.cn or heshunmin@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

[The Research Advance of the piRNA Function].

Piwi-interacting RNA (piRNA)is the largest class of small non-coding RNA,which usually expressed in germline cells.piRNA has a role in transposon silencing,and contributes to maintain ge-nome integrity.The C.elegans piRNA has a special role in a memory of previous gene expression.The discovery of piRNA in somatic cells and cancers showed the functional diversity of piRNA.In this article, we reviewed the piRNA's role in transposon,mRNA,lncRNA,DNA methylation and epigenetic regula-tion,and discussed the function of piRNA in cancers.

New insights into the fungal community from the raw genomic sequence data of fig wasp Ceratosolen solmsi.

BACKGROUND: To date, biologists have discovered a large amount of valuable information from assembled genomes, but the abundant microbial data that is hidden in the raw genomic sequence data of plants and animals is usually ignored. In this study, the richness and composition of fungal community were determined in the raw genomic sequence data of Ceratosolen solmsi (RGSD-CS). RESULTS: To avoid the interference from sequences of C. solmsi, the unmapped raw data (about 17.1%) was obtained by excluding the assembled genome of C. solmsi from RGSD-CS. Comparing two fungal reference datasets, internal transcribed spacer (ITS) and large ribosomal subunit (LSU) of rRNA, the ITS dataset discovered a more diverse fungal community and was therefore selected as the reference dataset for evaluating the fungal community based on the unmapped raw data. The threshold of 95% sequence identity revealed many more matched fungal reads and fungal richness in the unmapped raw data than those by identities above 95%. Based on the threshold of 95% sequence identity, the fungal community of RGSD-CS was primarily composed of Saccharomycetes (88.4%) and two other classes (Agaricomycetes and Sordariomycetes, 8.3% in total). Compared with the fungal community of other reported fig wasps, Agaricomycetes and Eurotiomycetes were found to be unique to C. solmsi. In addition, the ratio of total fungal reads to RGSD-CS was estimated to be at least 4.8 × 10(-3), which indicated that a large amount of fungal data was contained in RGSD-CS. However, rarefaction measure indicated that a deeper sequencing coverage with RGSD-CS was required to discover the entire fungal community of C. solmsi. CONCLUSION: This study investigated the richness and composition of fungal community in RGSD-CS and provided new insights into the efficient study of microbial diversity using raw genomic sequence data.

The influences of PRG-1 on the expression of small RNAs and mRNAs.

BACKGROUND: In metazoans, Piwi-related Argonaute proteins play important roles in maintaining germline integrity and fertility and have been linked to a class of germline-enriched small RNAs termed piRNAs. Caenorhabditis elegans encodes two Piwi family proteins called PRG-1 and PRG-2, and PRG-1 interacts with the C. elegans piRNAs (21U-RNAs). Previous studies found that mutation of prg-1 causes a marked reduction in the expression of 21U-RNAs, temperature-sensitive defects in fertility and other phenotypic defects. RESULTS: In this study, we wanted to systematically demonstrate the function of PRG-1 in the regulation of small RNAs and their targets. By analyzing small RNAs and mRNAs with and without a mutation in prg-1 during C. elegans development, we demonstrated that (1) mutation of prg-1 leads to a decrease in the expression of 21U-RNAs, and causes 35 ~ 40% of miRNAs to be down-regulated; (2) in C. elegans, approximately 3% (6% in L4) of protein-coding genes are differentially expressed after mutating prg-1, and 60 ~ 70% of these substantially altered protein-coding genes are up-regulated; (3) the target genes of the down-regulated miRNAs and the candidate target genes of the down-regulated 21U-RNAs are enriched in the up-regulated protein-coding genes; and (4) PRG-1 regulates protein-coding genes by down-regulating small RNAs (miRNAs and 21U-RNAs) that target genes that participate in the development of C. elegans. CONCLUSIONS: In prg-1-mutated C. elegans, the expression of miRNAs and 21U-RNAs was reduced, and the protein-coding targets, which were associated with the development of C. elegans, were up-regulated. This may be the mechanism underlying PRG-1 function.

Exploring noncoding variants in genetic diseases: from detection to functional insights.

Previous studies on genetic diseases predominantly focused on protein-coding variations, overlooking the vast noncoding regions in the human genome. The development of high-throughput sequencing technologies and functional genomics tools has enabled the systematic identification of functional noncoding variants. These variants can impact gene expression, regulation, and chromatin conformation, thereby contributing to disease pathogenesis. Understanding the mechanisms that underlie the impact of noncoding variants on genetic diseases is indispensable for the development of precisely targeted therapies and the implementation of personalized medicine strategies. The intricacies of noncoding regions introduce a multitude of challenges and research opportunities. In this review, we introduce a spectrum of noncoding variants involved in genetic diseases, along with research strategies and advanced technologies for their precise identification and in-depth understanding of the complexity of the noncoding genome. We will delve into the research challenges and propose potential solutions for unraveling the genetic basis of rare and complex diseases.