RankComp is implemented in R script that is freely available from Supplementary Materials.

AbstractriboCIRC is a translatome data-oriented circRNA database specifically designed for hosting, exploring, analyzing, and visualizing translatable circRNAs from multi-species. The database provides a comprehensive repository of computationally predicted ribosome-associated circRNAs; a manually curated collection of experimentally verified translated circRNAs; an evaluation of cross-species conservation of translatable circRNAs; a systematic de novo annotation of putative circRNA-encoded peptides, including sequence, structure, and function; and a genome browser to visualize the context-specific occupant footprints of circRNAs. It represents a valuable resource for the circRNA research community and is publicly available at http://www.ribocirc.com.

Current pathway analysis approaches are primarily dedicated to capturing deregulated pathways at the population level and cannot provide patient-specific pathway deregulation information. In this article, the authors present a simple approach, called individPath, to detect pathways with significantly disrupted intra-pathway relative expression orderings for each disease sample compared with the stable, normal intra-pathway relative expression orderings pre-determined in previously accumulated normal samples. Through the analysis of multiple microarray data sets for lung and breast cancer, the authors demonstrate individPath's effectiveness for detecting cancer-associated pathways with disrupted relative expression orderings at the individual level and dissecting the heterogeneity of pathway deregulation among different patients. The portable use of this simple approach in clinical contexts is exemplified by the identification of prognostic intra-pathway gene pair signatures to predict overall survival of resected early-stage lung adenocarcinoma patients and signatures to predict relapse-free survival of estrogen receptor-positive breast cancer patients after tamoxifen treatment.

Researchers usually measure only a few technical replicates of two types of cell line, resistant or sensitive to a drug, and use a fold-change (FC) cut-off value to detect differentially expressed (DE) genes. However, the FC cut-off lacks statistical control and is biased towards the identification of genes with low expression levels in both cell lines. Here, viewing every pair of resistant-sensitive technical replicates as an experiment, we proposed an algorithm to identify DE genes by evaluating the reproducibility of the expression difference or FC between every two independent experiments without overlapping samples. Using four small datasets of cancer cell line resistant or sensitive to a drug, we demonstrated that this algorithm could efficiently capture reproducible DE genes significantly enriched in biological pathways relevant to the corresponding drugs, whereas many of them could not be found by the FC and other commonly used methods. Therefore, the proposed algorithm is an effective complement to current approaches for analysing small cancer cell line data.

Human ribosomes have long been thought to be uniform factories with little regulatory function. Accumulating evidence emphasizes the heterogeneity of ribosomal protein (RP) expression in specific cellular functions and development. However, a systematic understanding of functional relevance of RPs is lacking. Here, we surveyed translational and transcriptional changes after individual knockdown of 75 RPs, 44 from the large subunit (60S) and 31 from the small subunit (40S), by Ribo-seq and RNA-seq analyses. Deficiency of individual RPs altered specific subsets of genes transcriptionally and translationally. RP genes were under cotranslational regulation upon ribosomal stress, and deficiency of the 60S RPs and the 40S RPs had opposite effects. RP deficiency altered the expression of genes related to eight major functional classes, including the cell cycle, cellular metabolism, signal transduction and development. 60S RP deficiency led to greater inhibitory effects on cell growth than did 40S RP deficiency, through P53 signaling. Particularly, we showed that eS8/RPS8 deficiency stimulated apoptosis while eL13/RPL13 or eL18/RPL18 deficiency promoted senescence. We also validated the phenotypic impacts of uL5/RPL11 and eL15/RPL15 deficiency on retina development and angiogenesis, respectively. Overall, our study provides a valuable resource for and novel insights into ribosome regulation in cellular activities, development and diseases.

Supplemental Digital Content is available in the text.

Motivation Predicting disease-related long non-coding RNAs (lncRNAs) can be used as the biomarkers for disease diagnosis and treatment. The development of effective computational prediction approaches to predict lncRNA-disease associations (LDAs) can provide insights into the pathogenesis of complex human diseases and reduce experimental costs. However, few of the existing methods use microRNA (miRNA) information and consider the complex relationship between inter-graph and intra-graph in complex-graph for assisting prediction. Results In this paper, the relationships between the same types of nodes and different types of nodes in complex-graph are introduced. We propose a multi-channel graph attention autoencoder model to predict LDAs, called MGATE. First, an lncRNA-miRNA-disease complex-graph is established based on the similarity and correlation among lncRNA, miRNA and diseases to integrate the complex association among them. Secondly, in order to fully extract the comprehensive information of the nodes, we use graph autoencoder networks to learn multiple representations from complex-graph, inter-graph and intra-graph. Thirdly, a graph-level attention mechanism integration module is adopted to adaptively merge the three representations, and a combined training strategy is performed to optimize the whole model to ensure the complementary and consistency among the multi-graph embedding representations. Finally, multiple classifiers are explored, and Random Forest is used to predict the association score between lncRNA and disease. Experimental results on the public dataset show that the area under receiver operating characteristic curve and area under precision-recall curve of MGATE are 0.964 and 0.413, respectively. MGATE performance significantly outperformed seven state-of-the-art methods. Furthermore, the case studies of three cancers further demonstrate the ability of MGATE to identify potential disease-correlated candidate lncRNAs. The source code and supplementary data are available at https://github.com/sheng-n/MGATE. Contact huanglan@jlu.edu.cn, wy6868@jlu.edu.cn

Cryptophthalmos (CO, MIM: 123570) is rare congenital anomalies of eyelid formation, which can occur alone or in combination with multiple congenital anomalies as part of Fraser syndrome (FS) or Manitoba Oculotrichoanal syndrome. Causal mutations have been identified for these syndromes but not in the isolated cases. Here, we described two patients from two unrelated Chinese families: one with unilateral isolated CO, while the other with unilateral CO and renal agenesis. A novel homozygous mutation (c.6499C>T: p.Arg2167Trp) and compound heterozygote mutations (c.15delG; c.6499C>T: p.Arg2167Trp) in FREM2 (NM_172862) were identified for the two patients, respectively. The deletion mutation c.15delG resulted in a frameshift and triggered the nonsense-mediated mRNA decay. For the shared missense mutation, p.Arg2167Trp altered a conserved residue and was predicted to affect protein structure by in silico analysis. Functional analysis revealed that Arg2167Trp mutant decreased its interaction with FRAS1 related extracellular matrix 1 (FREM1) and impaired the function of the FRAS1-FRAS1 related extracellular matrix 1 (FREM2)-FREM1 ternary complex required for normal embryogenesis. Furthermore, considering that mutation (c.5914C>T: p.Glu1972Lys) in FREM2 causes FS, a severe systemic disorder, we also compared these two different missense mutations. Our results showed that p.Arg2167Trp had a weaker effect in interrupting interactions between FREM2 and FREM1 than FS-associated missense mutation p.Glu1972Lys. Overall, our data demonstrate that the homozygous mutation p.Arg2167Trp in FREM2 causes isolated CO, which will facilitate our better understanding of the molecular mechanisms underlying the disease.