dreamBase: DNA modification, RNA regulation and protein binding of expressed pseudogenes in human health and disease.

Although thousands of pseudogenes have been annotated in the human genome, their transcriptional regulation, expression profiles and functional mechanisms are largely unknown. In this study, we developed dreamBase (http://rna.sysu.edu.cn/dreamBase) to facilitate the investigation of DNA modification, RNA regulation and protein binding of potential expressed pseudogenes from multidimensional high-throughput sequencing data. Based on ∼5500 ChIP-seq and DNase-seq datasets, we identified genome-wide binding profiles of various transcription-associated factors around pseudogene loci. By integrating ∼18 000 RNA-seq data, we analysed the expression profiles of pseudogenes and explored their co-expression patterns with their parent genes in 32 cancers and 31 normal tissues. By combining microRNA binding sites, we demonstrated complex post-transcriptional regulation networks involving 275 microRNAs and 1201 pseudogenes. We generated ceRNA networks to illustrate the crosstalk between pseudogenes and their parent genes through competitive binding of microRNAs. In addition, we studied transcriptome-wide interactions between RNA binding proteins (RBPs) and pseudogenes based on 458 CLIP-seq datasets. In conjunction with epitranscriptome sequencing data, we also mapped 1039 RNA modification sites onto 635 pseudogenes. This database will provide insights into the transcriptional regulation, expression, functions and mechanisms of pseudogenes as well as their roles in biological processes and diseases.

Spatial-temporal transcriptional dynamics of long non-coding RNAs in human brain.

The functional architecture of the human brain is greatly determined by the temporal and spatial regulation of the transcription process. However, the spatial and temporal transcriptional landscape of long non-coding RNAs (lncRNAs) during human brain development remains poorly understood. Here, we report the genome-wide lncRNA transcriptional analysis in an extensive series of 1340 post-mortem human brain specimens collected from 16 regions spanning the period from early embryo development to late adulthood. We discovered that lncRNA transcriptome dramatically changed during fetal development, while transited to a surprisingly relatively stable state after birth till the late adulthood. We also discovered that the transcription map of lncRNAs was spatially different, and that this spatial difference was developmentally regulated. Of the 16 brain regions explored (cerebellar cortex, thalamus, striatum, amygdala, hippocampus and 11 neocortex areas), cerebellar cortex showed the most distinct lncRNA expression features from all remaining brain regions throughout the whole developmental period, reflecting its unique developmental and functional features. Furthermore, by characterizing the functional modules and cellular processes of the spatial-temporal dynamic lncRNAs, we found that they were significantly associated with the RNA processing, neuron differentiation and synaptic signal transportation processes. Furthermore, we found that many lncRNAs associated with the neurodegenerative Alzheimer and Parkinson diseases were co-expressed in the fetal development of the human brain, and affected the convergent biological processes. In summary, our study provides a comprehensive map for lncRNA transcription dynamics in human brain development, which might shed light on the understanding of the molecular underpinnings of human brain function and disease.

deepBase v2.0: identification, expression, evolution and function of small RNAs, LncRNAs and circular RNAs from deep-sequencing data.

Small non-coding RNAs (e.g. miRNAs) and long non-coding RNAs (e.g. lincRNAs and circRNAs) are emerging as key regulators of various cellular processes. However, only a very small fraction of these enigmatic RNAs have been well functionally characterized. In this study, we describe deepBase v2.0 (http://biocenter.sysu.edu.cn/deepBase/), an updated platform, to decode evolution, expression patterns and functions of diverse ncRNAs across 19 species. deepBase v2.0 has been updated to provide the most comprehensive collection of ncRNA-derived small RNAs generated from 588 sRNA-Seq datasets. Moreover, we developed a pipeline named lncSeeker to identify 176 680 high-confidence lncRNAs from 14 species. Temporal and spatial expression patterns of various ncRNAs were profiled. We identified approximately 24 280 primate-specific, 5193 rodent-specific lncRNAs, and 55 highly conserved lncRNA orthologs between human and zebrafish. We annotated 14 867 human circRNAs, 1260 of which are orthologous to mouse circRNAs. By combining expression profiles and functional genomic annotations, we developed lncFunction web-server to predict the function of lncRNAs based on protein-lncRNA co-expression networks. This study is expected to provide considerable resources to facilitate future experimental studies and to uncover ncRNA functions.

Feasibility and acceptability of using Wi-Fi access points to provide smoking cessation help at 17 airports and 38 railway stations across China.

BACKGROUND: The use of mobile phone significantly improved the outcomes of tobacco cessation. However, its feasibility and acceptability were unclear in the Chinese population. This study was to explore the feasibility of using Wi-Fi access points (APs) as a platform to provide smoking cessation help at 17 airports and 38 railway stations across China. METHODS: This study was divided into two stages: platform development and population survey. In the first stage, a survey platform was developed and incorporated into Wi-Fi service at airports and railway stations, which could provide survey content as a pop-up window when participants tried to access the Wi-Fi service. In the second stage, a population survey was conducted to explore the intention to receive tobacco cessation support. RESULTS: A total of 20,199 users participated and 13,628 users submitted the survey, with a response rate of 67.47%. The smoking rate was 30.9%. A total of 86.58% of smoking participants and 2.44% of non-smoking participants wished to receive tobacco cessation support, respectively. The multivariate analysis showed intention to receive support did not differ in age, gender, and heaviness of smoking (P > 0.05). CONCLUSION: Providing tobacco cessation support via Wi-Fi APs is feasible and efficient, and smokers have high intention to receive tobacco cessation support. It is suggested hospitals, academia, information technology industries, and government agencies must work together to provide tobacco cessation support via mHealth.

[Effects of plastic film mulching and nitrogen application rate on net global warming potential in semiarid rain-fed maize cropland]. / 地膜覆盖和施氮量对旱作春玉米农田净温室效应的影响.

A one-year field experiment was conducted to evaluate the effects of plastic film mulching (FM) and nitrogen application rates applied to rain-fed maize fields on net global warming potential (Net GWP) and greenhouse gas intensity (GHGI) at the Changwu Agricultural and Ecological Experimental Station. Both GWP and GHGI were affected by the plastic film mulching and nitrogen application rate. Under the FM treatment, maize yield ranged from 1643 to 16699 kg·hm-2, the net GWP (CO2-eq) ranged from 595 to 4376 kg·hm-2·a-1, and the GHGI (CO2-eq) ranged from 213 to 358 kg·t-1. The grain yield of maize, net GWP and GHGI for the UM (no mulching) treatment were 956 to 8821 kg·hm-2, 342 to 4004 kg·hm-2·a-1 and 204 to 520 kg·t-1, respectively. The results suggested that plastic film mulching could simultaneously improve grain yield and decrease GHGI in rain-fed cropland along with nitrogen fertilizer of 250 kg·hm-2.

Comprehensive Genomic Characterization of RNA-Binding Proteins across Human Cancers.

RNA-binding proteins (RBPs) regulate the expression of thousands of transcripts, and some are reported to be involved in human tumorigenesis. However, little is known about the dysregulation of RBPs at the genomic level in human cancers. Here, we conducted comprehensive analyses for expression, somatic copy number alteration (SCNA), and mutation profiles of 1,542 RBPs in ∼7,000 clinical specimens across 15 cancer types. We identified markedly dysregulated RBPs and found that downregulation was a predominant pattern in cancer. Combined with recurrent SCNA data, we identified 76 RBPs as potential drivers. We also discovered a set of 139 RBPs that were significantly mutated in cancers. We confirmed the oncogenic property of six RBPs in colorectal and liver cancer cell lines by using in vitro functional experiments. Our study highlights the potential roles of RBPs in carcinogenesis and lays the groundwork to better understand the functions and mechanisms of RBPs in cancer.

Prognostic Value of a Long Non-coding RNA Signature in Localized Clear Cell Renal Cell Carcinoma.

BACKGROUND: Long non-coding RNAs (lncRNAs) can be used as prognostic biomarkers in many types of cancer. OBJECTIVE: We sought to establish an lncRNA signature to improve postoperative risk stratification for patients with localized clear cell renal cell carcinoma (ccRCC). DESIGN, SETTING, AND PARTICIPANTS: Based on the RNA-seq data of 444 stage I-III ccRCC tumours from The Cancer Genome Atlas project, we built a four-lncRNA-based classifier using the least absolute shrinkage and selection operation (LASSO) Cox regression model in 222 randomly selected samples (training set) and validated the classifier in the remaining 222 samples (internal validation set). We confirmed this classifier in an external validation set of 88 patients with stage I-III ccRCC from a Japan cohort and using quantitative reverse transcription polymerase chain reaction (RT-PCR) in another three independent sets that included 1869 patients from China with stage I-III ccRCC. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Univariable and multivariable Cox regression, Harrell's concordance index (c-index), and time-dependent receiver operating characteristic curves were used to evaluate the association of the classifier with overall survival, disease-specific survival, and disease-free survival. RESULTS AND LIMITATIONS: Using the LASSO Cox regression model, we built a classifier named RCClnc4 based on four lncRNAs: ENSG00000255774, ENSG00000248323, ENSG00000260911, and ENSG00000231666. In the RNA-seq and RT-PCR data sets, the RCClnc4 signature significantly stratified patients into high-risk versus low-risk groups in terms of clinical outcome across and within subpopulations and remained as an independent prognostic factor in multivariate analyses (hazard ratio range, 1.34 [95% confidence interval {CI}: 1.03-1.75; p=0.028] to 1.89 [95% CI, 1.55-2.31; p<0.001]) after adjusting for clinical and pathologic factors. The RCClnc4 signature achieved a higher accuracy (mean c-index, 0.72) than clinical staging systems such as TNM (mean c-index, 0.62) and the stage, size, grade, and necrosis (SSIGN) score (mean c-index, 0.64), currently reported prognostic signatures and biomarkers for the estimation of survival. When integrated with clinical characteristics, the composite clinical and lncRNA signature showed improved prognostic accuracy in all data sets (TNM + RCClnc4 mean c-index, 0.75; SSIGN + RCClnc4 score mean c-index, 0.75). The RCClnc4 classifier was able to identify a clinically significant number of both high-risk stage I and low-risk stage II-III patients. CONCLUSIONS: The RCClnc4 classifier is a promising and potential prognostic tool in predicting the survival of patients with stage I-III ccRCC. Combining the lncRNA classifier with clinical and pathological parameters allows for accurate risk assessment in guiding clinical management. PATIENT SUMMARY: The RCClnc4 classifier could facilitate patient management and treatment decisions.

oncoNcRNA: A Web Portal for Exploring the Non-Coding RNAs with Oncogenic Potentials in Human Cancers.

Non-coding RNAs (ncRNAs) have been shown to contribute to tumorigenesis and progression. However, the functions of the majority of ncRNAs remain unclear. Through integrating published large-scale somatic copy number alterations (SCNAs) data from various human cancer types, we have developed oncoNcRNA, a user-friendly web portal to explore ncRNAs with oncogenic potential in human cancers. The portal characterizes the SCNAs of over 58,000 long non-coding RNAs (lncRNAs), 34,000 piwi-interacting RNAs (piRNAs), 2700 microRNAs (miRNAs), 600 transfer RNAs (tRNAs) and 400 small nucleolar RNAs (snoRNAs) in 64 human cancer types. It enables researchers to rapidly and intuitively analyze the oncogenic potential of ncRNAs of interest. Indeed, we have discovered a large number of ncRNAs which are frequently amplified or deleted within and across tumor types. Moreover, we built a web-based tool, Correlations, to explore the relationships between gene expression and copy number from ~10,000 tumor samples in 36 cancer types identified by The Cancer Genome Atlas (TCGA). oncoNcRNA is a valuable tool for investigating the function and clinical relevance of ncRNAs in human cancers. oncoNcRNA is freely available at http://rna.sysu.edu.cn/onconcrna/.

Integrative analysis reveals clinical phenotypes and oncogenic potentials of long non-coding RNAs across 15 cancer types.

Long non-coding RNAs (lncRNAs) have been shown to contribute to tumorigenesis. However, surprisingly little is known about the comprehensive clinical and genomic characterization of lncRNAs across human cancer. In this study, we conducted comprehensive analyses for the expression profile, clinical outcomes, somatic copy number alterations (SCNAs) profile of lncRNAs in ~7000 clinical samples from 15 different cancer types. We identified significantly differentially expressed lncRNAs between tumor and normal tissues from each cancer. Notably, we characterized 47 lncRNAs which were extensively dysregulated in at least 10 cancer types, suggesting a conserved function in cancer development. We also analyzed the associations between lncRNA expressions and patient survival, and identified sets of lncRNAs that possessed significant prognostic values in specific cancer types. Our combined analysis of SCNA data and expression data uncovered 116 dysregulated lncRNAs are strikingly genomic altered across 15 cancer types, indicating their oncogenic potentials. Our study may lay the groundwork for future functional studies of lncRNAs and help facilitate the discovery of novel clinical biomarkers.

Discovery of Protein-lncRNA Interactions by Integrating Large-Scale CLIP-Seq and RNA-Seq Datasets.

Long non-coding RNAs (lncRNAs) are emerging as important regulatory molecules in developmental, physiological, and pathological processes. However, the precise mechanism and functions of most of lncRNAs remain largely unknown. Recent advances in high-throughput sequencing of immunoprecipitated RNAs after cross-linking (CLIP-Seq) provide powerful ways to identify biologically relevant protein-lncRNA interactions. In this study, by analyzing millions of RNA-binding protein (RBP) binding sites from 117 CLIP-Seq datasets generated by 50 independent studies, we identified 22,735 RBP-lncRNA regulatory relationships. We found that one single lncRNA will generally be bound and regulated by one or multiple RBPs, the combination of which may coordinately regulate gene expression. We also revealed the expression correlation of these interaction networks by mining expression profiles of over 6000 normal and tumor samples from 14 cancer types. Our combined analysis of CLIP-Seq data and genome-wide association studies data discovered hundreds of disease-related single nucleotide polymorphisms resided in the RBP binding sites of lncRNAs. Finally, we developed interactive web implementations to provide visualization, analysis, and downloading of the aforementioned large-scale datasets. Our study represented an important step in identification and analysis of RBP-lncRNA interactions and showed that these interactions may play crucial roles in cancer and genetic diseases.

[Sequence and phylogenetic analysis of the haemagglutinin genes of H9N2 avian influenza viruses isolated in central China during 1998-2008].

The purpose of this study is to explore the effects of the HA sequence variation on the pathogenicity and antigenicity of avian influenza virus(AIV). Haemagglutinin (HA) genes from, 6 of 25 avian influenza viruses (AIVs) H9N2 strains with different pathogenicity isolated in central China during last 10 years were amplified by reverse transcriptase PCR (RT-PCR), completely sequenced and phylogenetically analyzed. The purpose of this study was to explore the effects of the HA sequence variation on the pathogenicity and antigenicity of AIV. The results showed that all 6 representative H9N2 isolates belong to low pathogenic AIVs, since none of the amino acid sequences at the cleavage site of the HA of the isolates possessed the basic motif required for highly pathogenic viruses (R-X-R/K-R). There were eight potential glycosylation sites in HA of the isolates, except that 3# and 12# had an extra one. The higher pathogenicity of 3# and 12# was probably due to the extra glycosylation site (145aa-147aa) in HA1, which might alter the conformational structure of HA resulting in the mutation or deletion of the binding sites of anti-HA antibody, and has effects on receptor binding sites thus changed the antigenicity of the virus. Our results suggested that attention should be paid to the transmission and natural evolution of H9N2 AIV in order to control AIV H9N2.

[Genetic analysis of the nonstructural gene (NS1) of H9N2 avian influenza viruses isolated in China].

The nonstructural genes (NS1) of nine H9N2 subtype avian influenza viruses isolated from diseased chickens on different farms during 1998-2005 were amplified by RT-PCR and completely sequenced. The nucleotide and deduced amino acid sequences of NS1 genes of these isolates were compared. The results showed that NS1 genes of all H9N2 isolates contained 654 bp and encoded 217 amino acids. The homologies of the nucleotide and deduced amino sequences of the isolates were 95.4%-99.8% and 93.6%-100%, respectively. Comparison of the amino acid sequences of NS1 proteins of these isolates with other H9N2 viruses demonstrated that NS1 proteins of the nine strains had a deletion of 13 amino acid residues at the carboxyl terminus, which may be the molecule mark of the isolates in mainland China. Phylogenetic analysis revealed that the NS1 genes of these isolates fell into the same lineage and belonged to allele A. Eight out of nine isolates belonged to the CK/SH/F/98-like lineage while only Ck/HN/A3/98 strain belonged to the Ck/HK/Y280/97-like linease. All the isolates were derived from Ck/BJ/1/94 strain which was the first isolate is mainland China in 1994. The results indicated that H9N2 subtype AIV appeared differentiation following the passage of time and the viruses belonging to Ck/SH/F/98-like acquired an epidemic spread advantage in chicken population in mainland China.