BackgroundObservational studies have identified various associations between neuroimaging alterations and neuropsychiatric disorders. However, whether such associations could truly reflect causal relations remains still unknown.ResultsHere, we leveraged genome-wide association studies (GWAS) summary statistics for (1) 11 psychiatric disorders (sample sizes varied from n = 9,725 to 1,331,010); (2) 110 diffusion tensor imaging (DTI) measurement (sample size n = 17,706); (3) 101 region-of-interest (ROI) volumes, and investigate the causal relationship between brain structures and neuropsychiatric disorders by two-sample Mendelian randomization. Among all DTI-Disorder combinations, we observed a significant causal association between the superior longitudinal fasciculus (SLF) and the risk of Anorexia nervosa (AN) (Odds Ratio [OR] = 0.62, 95 % confidence interval: 0.50 ~ 0.76, P = 6.4 × 10− 6). Similar significant associations were also observed between the body of the corpus callosum (fractional anisotropy) and Alzheimer’s disease (OR = 1.07, 95 % CI: 1.03 ~ 1.11, P = 4.1 × 10− 5). By combining all observations, we found that the overall p-value for DTI − Disorder associations was significantly elevated compared to the null distribution (Kolmogorov-Smirnov P = 0.009, inflation factor λ = 1.37), especially for DTI − Bipolar disorder (BP) (λ = 2.64) and DTI − AN (λ = 1.82). In contrast, for ROI-Disorder combinations, we only found a significant association between the brain region of pars triangularis and Schizophrenia (OR = 0.48, 95 % CI: 0.34 ~ 0.69, P = 5.9 × 10− 5) and no overall p-value elevation for ROI-Disorder analysis compared to the null expectation.ConclusionsAs a whole, we show that SLF degeneration may be a risk factor for AN, while DTI variations could be causally related to some neuropsychiatric disorders, such as BP and AN. Also, the white matter structure might have a larger impact on neuropsychiatric disorders than subregion volumes.

BackgroundA new class of regulatory elements called super-enhancers, comprised of multiple neighboring enhancers, have recently been reported to be the key transcriptional drivers of cellular, developmental, and disease states.ResultsHere, we defined super-enhancer RNAs as highly expressed enhancer RNAs that are transcribed from a cluster of localized genomic regions. Using the cap analysis of gene expression sequencing data from FANTOM5, we systematically explored the enhancer and messenger RNA landscapes in hundreds of different cell types in response to various environments. Applying non-negative matrix factorization (NMF) to super-enhancer RNA profiles, we found that different cell types were well classified. In addition, through the NMF of individual time-course profiles from a single cell-type, super-enhancer RNAs were clustered into several states with progressive patterns. We further investigated the enriched biological functions of the proximal genes involved in each pattern, and found that they were associated with the corresponding developmental process.ConclusionsThe proposed super-enhancer RNAs can act as a good alternative, without the complicated measurement of histone modifications, for identifying important regulatory elements of cell type specification and identifying dynamic cell states.

BackgroundLong non-coding RNAs (lncRNAs) play vital roles in many important biological processes in plants. Currently, a large fraction of plant lncRNA studies center at lncRNA identification and functional analysis. Only a few plant lncRNA studies focus on understanding their evolutionary history, which is crucial for an in-depth understanding of lncRNAs. Therefore, the integration of large volumes of plant lncRNA data is required to deeply investigate the evolution of lncRNAs.ResultsWe present a large-scale evolutionary analysis of lncRNAs in 25 flowering plants. In total, we identified 199,796 high-confidence lncRNAs through data integration analysis, and grouped them into 5497 lncRNA orthologous families. Then, we divided the lncRNAs into groups based on the degree of sequence conservation, and quantified the various characteristics of 756 conserved Arabidopsis thaliana lncRNAs. We found that compared with non-conserved lncRNAs, conserved lncRNAs might have more exons, longer sequence length, higher expression levels, and lower tissue specificities. Functional annotation based on the A. thaliana coding-lncRNA gene co-expression network suggested potential functions of conserved lncRNAs including autophagy, locomotion, and cell cycle. Enrichment analysis revealed that the functions of conserved lncRNAs were closely related to the growth and development of the tissues in which they were specifically expressed.ConclusionsComprehensive integration of large-scale lncRNA data and construction of a phylogenetic tree with orthologous lncRNA families from 25 flowering plants was used to provide an oversight of the evolutionary history of plant lncRNAs including origin, conservation, and orthologous relationships. Further analysis revealed a differential characteristic profile for conserved lncRNAs in A. thaliana when compared with non-conserved lncRNAs. We also examined tissue specific expression and the potential functional roles of conserved lncRNAs. The results presented here will further our understanding of plant lncRNA evolution, and provide the basis for further in-depth studies of their functions.

BackgroundVarious epigenetic factors are responsible for the non-genetic regulation on gene expression. The epigenetically dysregulated oncogenes or tumor suppressors by miRNA and/or DNA methylation are often observed in cancer cells. Each of these epigenetic regulators has been studied well in cancer progressions; however, their mutual regulatory relationship in cancer still remains unclear. In this study, we propose an integrative framework to systematically investigate epigenetic interactions between miRNA and methylation at the alternatively spliced mRNA level in bladder cancer. Each of these epigenetic regulators has been studied well in cancer progressions; however, their mutual regulatory relationship in cancer still remains unclear.ResultsThe integrative analyses yielded 136 significant combinations (methylation, miRNA and isoform). Further, overall survival analysis on the 136 combinations based on methylation and miRNA, high and low expression groups resulted in 13 combinations associated with survival. Additionally, different interaction patterns were examined.ConclusionsOur study provides a higher resolution of molecular insight into the crosstalk between two epigenetic factors, DNA methylation and miRNA. Given the importance of epigenetic interactions and alternative splicing in cancer, it is timely to identify and understand the underlying mechanisms based on epigenetic markers and their interactions in cancer, leading to alternative splicing with primary functional impact.