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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.

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 5,675 genomes, comprising 2,998 Chinese samples (∼26.2X, NyuWa) and 2,677 samples from the 1000 Genomes Project (∼7.4X, 1KGP). We discovered that LINE-1 insertions were highly enriched at 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.

Small proteins specifically refer to proteins consisting of less than 100 amino acids translated from small open reading frames (sORFs), which were usually missed in previous genome annotation. The significance of small proteins has been revealed in current years, along with the discovery of their diverse functions. However, systematic annotation of small proteins is still insufficient. SmProt was specially developed to provide valuable information on small proteins for scientific community. Here we present the update of SmProt, which emphasizes reliability of translated sORFs, genetic variants in translated sORFs, disease-specific sORF translation events or sequences, and remarkably increased data volume. More components such as non-ATG translation initiation, function, and new sources are also included. SmProt incorporated 638,958 unique small proteins curated from 3,165,229 primary records, which were computationally predicted from 419 ribosome profiling (Ribo-seq) datasets or collected from literature and other sources from 370 cell lines or tissues in 8 species (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Saccharomyces cerevisiae, Caenorhabditis elegans, and Escherichia coli). In addition, small protein families identified from human microbiomes were also collected. All datasets in SmProt are free to access, and available for browse, search, and bulk downloads at http://bigdata.ibp.ac.cn/SmProt/ .

The lack of Chinese population specific haplotype reference panel and whole genome sequencing resources has greatly hindered the genetics studies in the world’s largest population. Here we presented the NyuWa genome resource of 71.1M SNPs and 8.2M indels based on deep (26.2X) sequencing of 2,999 Chinese individuals, and constructed NyuWa reference panel of 5,804 haplotypes and 19.3M variants, which is the first publicly available Chinese population specific reference panel with thousands of samples. There were 25.0M novel variants in NyuWa genome resource, and 3.2M specific variants in NyuWa reference panel. Compared with other panels, NyuWa reference panel reduces the Han Chinese imputation error rate by the range of 30% to 51%. Population structure and imputation simulation tests supported the applicability of one integrated reference panel for both northern and southern Chinese. In addition, a total of 22,504 loss-of-function variants in coding and noncoding genes were identified, including 11,493 novel variants. These results highlight the value of NyuWa genome resource to facilitate genetics research in Chinese and Asian populations.

Summary The lack of haplotype reference panels and whole-genome sequencing resources specific to the Chinese population has greatly hindered genetic studies in the world’s largest population. Here, we present the NyuWa genome resource, based on deep (26.2×) sequencing of 2,999 Chinese individuals, and construct a NyuWa reference panel of 5,804 haplotypes and 19.3 million variants, which is a high-quality publicly available Chinese population-specific reference panel with thousands of samples. Compared with other panels, the NyuWa reference panel reduces the Han Chinese imputation error rate by a margin ranging from 30% to 51%. Population structure and imputation simulation tests support the applicability of one integrated reference panel for northern and southern Chinese. In addition, a total of 22,504 loss-of-function variants in coding and noncoding genes are identified, including 11,493 novel variants. These results highlight the value of the NyuWa genome resource in facilitating genetic research in Chinese and Asian populations.

Whole genome sequencing technology has facilitated the discovery of a large number of somatic mutations in enhancers (SMEs), whereas the utility of SMEs in tumorigenesis has not been fully explored. Here we present Ennet, a method to comprehensively investigate SMEs enriched networks (SME-networks) in cancer by integrating SMEs, enhancer-gene interactions and gene-gene interactions. Using Ennet, we performed a pan-cancer analysis in 2004 samples from 8 cancer types and found many well-known cancer drivers were involved in the SME-networks, includingESR1,SMAD3,MYC,EGFR,BCL2andPAX5. Meanwhile, Ennet also identified many new networks with less characterization but have potentially important roles in cancer, including a large SME-network in medulloblastoma (MB), which contains genes enriched in the glutamate receptor and neural development pathways. Interestingly, SME-networks are specific across cancer types, and the vast majority of the genes identified by Ennet have few mutations in gene bodies. Collectively, our work suggests that using enhancer-only somatic mutations can be an effective way to discover potential cancer-driving networks. Ennet provides a new perspective to explore new mechanisms for tumor progression from SMEs.

// Guifeng Wei 1,2,* , Huaxia Luo 1,2,* , Yu Sun 1,2,* , Jiagen Li 3 , Liqing Tian 1 , Wei Liu 1,2 , Lihui Liu 1,2 , Jianjun Luo 1 , Jie He 3 and Runsheng Chen 1,4 1 Bioinformatics Laboratory and CAS Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China 2 University of Chinese Academy of Sciences, Beijing, China 3 Department of Thoracic Surgery, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China 4 Research Network of Computational Biology, RNCB, Beijing, China * These authors have contributed equally to this work Correspondence to: Runsheng Chen, email: // Jie He, email: // Keywords : ESCC, long noncoding RNAs, tumor suppressor, metastasis, Epist Received : March 16, 2015 Accepted : May 02, 2015 Published : May 19, 2015 Abstract Esophageal Squamous Cell Carcinoma (ESCC) is among the most common malignant cancers worldwide. In the past, extensive efforts have been made to characterize the involvement of protein-coding genes in ESCC tumorigenesis but few for long noncoding RNAs (lncRNAs). To investigate the transcriptome profile and functional relevance of lncRNAs, we performed an integrative analysis of a customized combined lncRNA-mRNA microarray and RNA-seq data on ESCCs and matched normal tissues. We identified numerous lncRNAs that were differentially expressed between the normal and tumor tissues, termed “ESCC-associated lncRNAs (ESCALs)”, of which, the majority displayed restricted expression pattern. Also, a subset of ESCALs appeared to be associated with ESCC patient survival. Gene set enrichment analysis (GSEA) further suggested that over half of the ESCALs were positively- or negatively- associated with metastasis. Among these, we identified a novel nuclear-retained lncRNA, named Epist , which is generally highly expressed in esophagus, and which is down-regulated during ESCC progression. Epist over-expression and knockdown studies further suggest that Epist inhibits the metastasis, acting as a tumor suppressor in ESCC. Collectively, our analysis of the ESCC transcriptome identified the potential tumor suppressing lncRNA Epist , and provided a foundation for future efforts to identify functional lncRNAs for cancerous therapeutic targeting.

Long noncoding RNAs (lncRNAs) are pervasively transcribed in the human genome. Recent studies suggest that the involvement of lncRNAs in human diseases could be far more prevalent than previously appreciated. Here we have identified a lncRNA termed Lnc_bc060912 whose expression is increased in human lung and other tumors. Lnc_bc060912 is 1.2 kb in length and is composed of two exons. The expression of Lnc_bc060912 was repressed by p53. Lnc_bc060912 suppressed cell apoptosis. Using a recently developed method for RNA-pulldown with formaldehyde cross-linking, we found that Lnc_bc060912 interacted with the two DNA damage repair proteins PARP1 and NPM1. Together, these results suggest that Lnc_bc060912, via PARP1 and NPM1, affects cell apoptosis and may play important roles in tumorigenesis and cancer progression.

Increasing evidence indicates that long noncoding RNAs (lncRNAs) have important roles in various physiological processes and dysfunction of lncRNAs could be a prevalent cause in human diseases. Here we functionally characterized the nuclear-enriched lncRNA SNHG1, which is highly expressed in multiple types of cancer. We also provide evidence that SNHG1 promotes cancer cell growth by regulating gene expression both in cis and in trans. SNHG1 was involved in the AKT signaling pathway as it promotes the neighboring transcription of the protein-coding gene SLC3A2 in cis by binding the Mediator complex to facilitate the establishment of enhancer-promoter interaction. In trans, SNHG1 directly interacted with central domain of FUBP1 and antagonize the binding of FBP-interacting repressor to FUBP1, thereby coordinating the expression of the oncogene MYC. Collectively, our findings demonstrate that lncRNA SNHG1 can function both in cis and in trans with distinct mechanisms to regulate transcription, promoting tumorigenesis and cancer progression.

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.

Noncoding RNAs are increasingly being recognized as important players in eukaryote biology. However, despite major efforts in mapping the Caenorhabditis elegans transcriptome over the last couple of years, nonpolyadenylated and intermediate-size noncoding RNAs (is-ncRNAs) are still incompletely explored. We have combined an enzymatic approach with full-length RNA-Seq of is-ncRNAs in C. elegans. A total of 473 novel is-ncRNAs has been identified, of which a substantial fraction was associated with transcription factor binding sites and developmentally regulated expression patterns. Analysis of sequence and secondary structure permitted classification of more than 200 is-ncRNAs into several known RNA classes, while another 33 is-ncRNAs were identified as belonging to two previously uncharacterized groups of is-ncRNAs. Three of the unclassified is-ncRNAs contain the 5′ Alu domain common to SRP RNAs and specifically bound with the SRP9/14 heterodimer in vitro. One of these (inc394) showed 65% sequence identity with the human, neuron-specific BC200 RNA. Structure-based clustering analysis and in vitro binding experiments supported the notion that the nematode stem-bulge RNAs (sbRNAs) are homologs (or functional analogs) of the Y RNAs. Moreover, analysis of the differential libraries showed that some mature snoRNAs undergo secondary 5′ cap modification after processing of the primary transcript, thus suggesting the existence of a wider range of functional RNAs arising from processed and modified fragments of primary transcripts.

Summary: 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.

The identification and characterization of long non-coding RNAs (lncRNAs) in diverse biological processes has recently developed rapidly. The large amounts of non-coding RNAs scale consistent with developmental complexity in eukaryotes, indicating that most of these transcripts may have functions in the regulation of biological processes and disorder in the organisms. In particular, Understanding of the overall biological significance of lncRNAs in cancers still remains limited. Here, we found a nuclear-retained lncRNA, termed Lnc_ASNR (apoptosis suppressing-noncoding RNA), which serves as a repressor of apoptosis. Lnc_ASNR was discovered in a set of microarray data derived from four kinds of tumor and adjacent normal tissue samples and displayed significant up-regulation in the tumor tissues. Using an RNA-pull down assay, we found that Lnc_ASNR interacted with the protein ARE/poly (U)-binding/degradation factor 1(AUF1), which is reported to promote rapid degradation of the Bcl-2 mRNA, an inhibitor of apoptosis. Lnc_ASNR binds to AUFI in nucleus, decreasing the cytoplasmic proportion of AUF1 which targets the B-cell lymphoma-2 (Bcl-2) mRNA. Taken together, the overall effect of Lnc_ASNR expression is thus a decrease in cell apoptosis indicating that Lnc_ASNR may play a vital role in tumorigenesis and carcinogenesis.

Introduction. Small noncoding RNAs have important regulatory functions in different cell pathways. It is believed that most of them mainly play role in gene post-transcriptional regulation in the cytoplasm. Recent evidence suggests miRNA and siRNA activity in the nucleus. Here, we show distinct genome-wide sub-cellular localization distribution profiles of small noncoding RNAs in human breast cancer cells.Methods. We separated breast cancer cell nuclei from cytoplasm, and identified small RNA sequences using a high-throughput sequencing platform. To determine the relationship between miRNA sub-cellular distribution and cancer progression, we used microarray analysis to examine the miRNA expression levels in nucleus and cytoplasm of three human cell lines, one normal breast cell line and two breast cancer cell lines. Logistic regression and SVM were used for further analysis.Results. The sub-cellular distribution of small noncoding RNAs shows that numerous miRNAs and their isoforms (isomiR) not only locate to the cytoplasm but also appeare in the nucleus. Subsequent microarray analyses indicated that the miRNA nuclear-cytoplasmic-ratio is a significant characteristic of different cancer cell lines.Conclusions. Our results indicate that the sub-cellular distribution is important for miRNA function, and that the characterization of the small RNAs sub-cellular localizome may contribute to cancer research and diagnosis.

Summary C/EBPα is a critical transcriptional regulator of adipogenesis. How C/EBPα transcription is itself regulated is poorly understood, however, and remains a key question that needs to be addressed for a complete understanding of adipogenic development. Here, we identify a lncRNA, ADINR (adipogenic differentiation induced noncoding RNA), transcribed from a position ∼450 bp upstream of the C/EBPα gene, that orchestrates C/EBPα transcription in vivo. Depletion of ADINR leads to a severe adipogenic defect that is rescued by overexpression of C/EBPα. Moreover, we reveal that ADINR RNA specifically binds to PA1 and recruits MLL3/4 histone methyl-transferase complexes so as to increase H3K4me3 and decrease H3K27me3 histone modification in the C/EBPα locus during adipogenesis. These results show that ADINR plays important roles in regulating the differentiation of human mesenchymal stem cells into adipocytes by modulating C/EBPα in cis., Graphical Abstract, Highlights • The lncRNA ADINR is developmentally regulated during adipogenesis • ADINR promotes adipogenesis by activating C/EBPα transcription in cis • ADINR activates C/EBPα transcription by an MLL3/4-dependent mechanism • MLL3/4 recruitment to the C/EBPα promoter requires binding of PA1 to ADINR, Chen and colleagues show that the lncRNA ADINR regulates the development of hMSCs along the adipogenic pathway through transcriptional regulation of C/EBPα expression by exerting its effect on C/EBPα’s promoter.