Conserved and divergent signals in 5' splice site sequences across fungi, metazoa and plants.

In eukaryotic organisms the ensemble of 5' splice site sequences reflects the balance between natural nucleotide variability and minimal molecular constraints necessary to ensure splicing fidelity. This compromise shapes the underlying statistical patterns in the composition of donor splice site sequences. The scope of this study was to mine conserved and divergent signals in the composition of 5' splice site sequences. Because 5' donor sequences are a major cue for proper recognition of splice sites, we reasoned that statistical regularities in their composition could reflect the biological functionality and evolutionary history associated with splicing mechanisms. Results: We considered a regularized maximum entropy modeling framework to mine for non-trivial two-site correlations in donor sequence datasets corresponding to 30 different eukaryotes. For each analyzed species, we identified minimal sets of two-site coupling patterns that were able to replicate, at a given regularization level, the observed one-site and two-site frequencies in donor sequences. By performing a systematic and comparative analysis of 5'splice sites we showed that lineage information could be traced from joint di-nucleotide probabilities. We were able to identify characteristic two-site coupling patterns for plants and animals, and propose that they may echo differences in splicing regulation previously reported between these groups.

ASpli: integrative analysis of splicing landscapes through RNA-Seq assays.

MOTIVATION: Genome-wide analysis of alternative splicing has been a very active field of research since the early days of next generation sequencing technologies. Since then, ever-growing data availability and the development of increasingly sophisticated analysis methods have uncovered the complexity of the general splicing repertoire. A large number of splicing analysis methodologies exist, each of them presenting its own strengths and weaknesses. For instance, methods exclusively relying on junction information do not take advantage of the large majority of reads produced in an RNA-seq assay, isoform reconstruction methods might not detect novel intron retention events, some solutions can only handle canonical splicing events, and many existing methods can only perform pairwise comparisons. RESULTS: In this contribution, we present ASpli, a computational suite implemented in R statistical language, that allows the identification of changes in both, annotated and novel alternative-splicing events and can deal with simple, multi-factor or paired experimental designs. Our integrative computational workflow, that considers the same GLM model applied to different sets of reads and junctions, allows computation of complementary splicing signals. Analyzing simulated and real data, we found that the consolidation of these signals resulted in a robust proxy of the occurrence of splicing alterations. While the analysis of junctions allowed us to uncover annotated as well as non-annotated events, read coverage signals notably increased recall capabilities at a very competitive performance when compared against other state-of-the-art splicing analysis algorithms. AVAILABILITY AND IMPLEMENTATION: ASpli is freely available from the Bioconductor project site https://doi.org/doi:10.18129/B9.bioc.ASpli. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

TDR Targets 6: driving drug discovery for human pathogens through intensive chemogenomic data integration.

The volume of biological, chemical and functional data deposited in the public domain is growing rapidly, thanks to next generation sequencing and highly-automated screening technologies. These datasets represent invaluable resources for drug discovery, particularly for less studied neglected disease pathogens. To leverage these datasets, smart and intensive data integration is required to guide computational inferences across diverse organisms. The TDR Targets chemogenomics resource integrates genomic data from human pathogens and model organisms along with information on bioactive compounds and their annotated activities. This report highlights the latest updates on the available data and functionality in TDR Targets 6. Based on chemogenomic network models providing links between inhibitors and targets, the database now incorporates network-driven target prioritizations, and novel visualizations of network subgraphs displaying chemical- and target-similarity neighborhoods along with associated target-compound bioactivity links. Available data can be browsed and queried through a new user interface, that allow users to perform prioritizations of protein targets and chemical inhibitors. As such, TDR Targets now facilitates the investigation of drug repurposing against pathogen targets, which can potentially help in identifying candidate targets for bioactive compounds with previously unknown targets. TDR Targets is available at https://tdrtargets.org.

Identification and functional analysis of healing regulators in Drosophila.

Wound healing is an essential homeostatic mechanism that maintains the epithelial barrier integrity after tissue damage. Although we know the overall steps in wound healing, many of the underlying molecular mechanisms remain unclear. Genetically amenable systems, such as wound healing in Drosophila imaginal discs, do not model all aspects of the repair process. However, they do allow the less understood aspects of the healing response to be explored, e.g., which signal(s) are responsible for initiating tissue remodeling? How is sealing of the epithelia achieved? Or, what inhibitory cues cancel the healing machinery upon completion? Answering these and other questions first requires the identification and functional analysis of wound specific genes. A variety of different microarray analyses of murine and humans have identified characteristic profiles of gene expression at the wound site, however, very few functional studies in healing regulation have been carried out. We developed an experimentally controlled method that is healing-permissive and that allows live imaging and biochemical analysis of cultured imaginal discs. We performed comparative genome-wide profiling between Drosophila imaginal cells actively involved in healing versus their non-engaged siblings. Sets of potential wound-specific genes were subsequently identified. Importantly, besides identifying and categorizing new genes, we functionally tested many of their gene products by genetic interference and overexpression in healing assays. This non-saturated analysis defines a relevant set of genes whose changes in expression level are functionally significant for proper tissue repair. Amongst these we identified the TCP1 chaperonin complex as a key regulator of the actin cytoskeleton essential for the wound healing response. There is promise that our newly identified wound-healing genes will guide future work in the more complex mammalian wound healing response.

The spliceosome assembly factor GEMIN2 attenuates the effects of temperature on alternative splicing and circadian rhythms.

The mechanisms by which poikilothermic organisms ensure that biological processes are robust to temperature changes are largely unknown. Temperature compensation, the ability of circadian rhythms to maintain a relatively constant period over the broad range of temperatures resulting from seasonal fluctuations in environmental conditions, is a defining property of circadian networks. Temperature affects the alternative splicing (AS) of several clock genes in fungi, plants, and flies, but the splicing factors that modulate these effects to ensure clock accuracy throughout the year remain to be identified. Here we show that GEMIN2, a spliceosomal small nuclear ribonucleoprotein assembly factor conserved from yeast to humans, modulates low temperature effects on a large subset of pre-mRNA splicing events. In particular, GEMIN2 controls the AS of several clock genes and attenuates the effects of temperature on the circadian period in Arabidopsis thaliana. We conclude that GEMIN2 is a key component of a posttranscriptional regulatory mechanism that ensures the appropriate acclimation of plants to daily and seasonal changes in temperature conditions.

Role for LSM genes in the regulation of circadian rhythms.

Growing evidence suggests that core spliceosomal components differentially affect RNA processing of specific genes; however, whether changes in the levels or activities of these factors control specific signaling pathways is largely unknown. Here we show that some SM-like (LSM) genes, which encode core components of the spliceosomal U6 small nuclear ribonucleoprotein complex, regulate circadian rhythms in plants and mammals. We found that the circadian clock regulates the expression of LSM5 in Arabidopsis plants and several LSM genes in mouse suprachiasmatic nucleus. Further, mutations in LSM5 or LSM4 in Arabidopsis, or down-regulation of LSM3, LSM5, or LSM7 expression in human cells, lengthens the circadian period. Although we identified changes in the expression and alternative splicing of some core clock genes in Arabidopsis lsm5 mutants, the precise molecular mechanism causing period lengthening remains to be identified. Genome-wide expression analysis of either a weak lsm5 or a strong lsm4 mutant allele in Arabidopsis revealed larger effects on alternative splicing than on constitutive splicing. Remarkably, large splicing defects were not observed in most of the introns evaluated using RNA-seq in the strong lsm4 mutant allele used in this study. These findings support the idea that some LSM genes play both regulatory and constitutive roles in RNA processing, contributing to the fine-tuning of specific signaling pathways.

Utilization of extracellular information before ligand-receptor binding reaches equilibrium expands and shifts the input dynamic range.

Cell signaling systems sense and respond to ligands that bind cell surface receptors. These systems often respond to changes in the concentration of extracellular ligand more rapidly than the ligand equilibrates with its receptor. We demonstrate, by modeling and experiment, a general "systems level" mechanism cells use to take advantage of the information present in the early signal, before receptor binding reaches a new steady state. This mechanism, pre-equilibrium sensing and signaling (PRESS), operates in signaling systems in which the kinetics of ligand-receptor binding are slower than the downstream signaling steps, and it typically involves transient activation of a downstream step. In the systems where it operates, PRESS expands and shifts the input dynamic range, allowing cells to make different responses to ligand concentrations so high as to be otherwise indistinguishable. Specifically, we show that PRESS applies to the yeast directional polarization in response to pheromone gradients. Consideration of preexisting kinetic data for ligand-receptor interactions suggests that PRESS operates in many cell signaling systems throughout biology. The same mechanism may also operate at other levels in signaling systems in which a slow activation step couples to a faster downstream step.

Fibulin-2 is a key mediator of the pro-neurogenic effect of TGF-beta1 on adult neural stem cells.

Transforming growth factor beta 1 (TGF-beta1), an anti-inflammatory cytokine, has been shown to have pro-neurogenic effects on adult Neural Stem Cells (aNSC) from the dentate gyrus and in vivo models. Here, we expanded the observation of the pro-neurogenic effect of TGF-beta1 on aNSC from the subventricular zone (SVZ) of adult rats and performed a functional genomic analysis to identify candidate genes to mediate its effect. 10 candidate genes were identified by microarray analysis and further validated by qRT-PCR. Of these, Fibulin-2 was increased 477-fold and its inhibition by siRNA blocks TGF-beta1 pro-neurogenic effect. Curiously, Fibulin-2 was not expressed by aNSC but by a GFAP-positive population in the culture, suggesting an indirect mechanism of action. TGF-beta1 also induced Fibulin-2 in the SVZ in vivo. Interestingly, 5 out of the 10 candidate genes identified are known to interact with integrins, paving the way for exploring their functional role in adult neurogenesis. In conclusion, we have identified 10 genes with putative pro-neurogenic effects, 5 of them related to integrins and provided proof that Fibulin-2 is a major mediator of the pro-neurogenic effects of TGF-beta1. These data should contribute to further exploring the molecular mechanism of adult neurogenesis of the genes identified and the involvement of the integrin pathway on adult neurogenesis.

LNK genes integrate light and clock signaling networks at the core of the Arabidopsis oscillator.

Light signaling pathways and the circadian clock interact to help organisms synchronize physiological and developmental processes with periodic environmental cycles. The plant photoreceptors responsible for clock resetting have been characterized, but signaling components that link the photoreceptors to the clock remain to be identified. Here we describe a family of night light-inducible and clock-regulated genes (LNK) that play a key role linking light regulation of gene expression to the control of daily and seasonal rhythms in Arabidopsis thaliana. A genomewide transcriptome analysis revealed that most light-induced genes respond more strongly to light during the subjective day, which is consistent with the diurnal nature of most physiological processes in plants. However, a handful of genes, including the homologous genes LNK1 and LNK2, are more strongly induced by light in the middle of the night, when the clock is most responsive to this signal. Further analysis revealed that the morning phased LNK1 and LNK2 genes control circadian rhythms, photomorphogenic responses, and photoperiodic dependent flowering, most likely by regulating a subset of clock and flowering time genes in the afternoon. LNK1 and LNK2 themselves are directly repressed by members of the TIMING OF CAB1 EXPRESSION/PSEUDO RESPONSE REGULATOR family of core-clock genes in the afternoon and early night. Thus, LNK1 and LNK2 integrate early light signals with temporal information provided by core oscillator components to control the expression of afternoon genes, allowing plants to keep track of seasonal changes in day length.

MISTIC: Mutual information server to infer coevolution.

MISTIC (mutual information server to infer coevolution) is a web server for graphical representation of the information contained within a MSA (multiple sequence alignment) and a complete analysis tool for Mutual Information networks in protein families. The server outputs a graphical visualization of several information-related quantities using a circos representation. This provides an integrated view of the MSA in terms of (i) the mutual information (MI) between residue pairs, (ii) sequence conservation and (iii) the residue cumulative and proximity MI scores. Further, an interactive interface to explore and characterize the MI network is provided. Several tools are offered for selecting subsets of nodes from the network for visualization. Node coloring can be set to match different attributes, such as conservation, cumulative MI, proximity MI and secondary structure. Finally, a zip file containing all results can be downloaded. The server is available at http://mistic.leloir.org.ar. In summary, MISTIC allows for a comprehensive, compact, visually rich view of the information contained within an MSA in a manner unique to any other publicly available web server. In particular, the use of circos representation of MI networks and the visualization of the cumulative MI and proximity MI concepts is novel.

Impact of upstream and downstream constraints on a signaling module's ultrasensitivity.

Much work has been done on the study of the biochemical mechanisms that result in ultrasensitive behavior of simple biochemical modules. However, in a living cell, such modules are embedded in a bigger network that constrains the range of inputs that the module will receive as well as the range of the module's outputs that network will be able to detect. Here, we studied how the effective ultrasensitivity of a modular system is affected by these restrictions. We use a simple setup to explore to what extent the dynamic range spanned by upstream and downstream components of an ultrasensitive module impact on the effective sensitivity of the system. Interestingly, we found for some ultrasensitive motifs that dynamic range limitations imposed by downstream components can produce effective sensitivities much larger than that of the original module when considered in isolation.

The Missing Person problem through the lens of information theory.

Missing person cases typically require a genetic kinship test to determine the relationship between an unidentified individual and the relatives of the missing person. When not enough genetic evidence has been collected the lack of statistical power of these tests might lead to unreliable results. This is particularly true when just a few distant relatives are available for genotyping. In this contribution, we considered a Bayesian network approach for kinship testing and proposed several information theoretic metrics in order to quantitatively evaluate the information content of pedigrees. We show how these statistics are related to the widely used likelihood ratio values and could be employed to efficiently prioritize family members in order to optimize the statistical power in missing person problems. Our methodology seamlessly integrates with Bayesian modeling approaches, like the GENis platform that we have recently developed for high-throughput missing person identification tasks. Furthermore, our approach can also be easily incorporated into Elston-Stewart forensic frameworks. To facilitate the application of our methodology, we have developed the forensIT package, freely available on CRAN repository, which implements all the methodologies described in our manuscript.

scX: A user-friendly tool for scRNA-seq exploration.

Single-cell RNA sequencing (scRNA-seq) has transformed our ability to explore biological systems. Nevertheless, proficient expertise is essential for handling and interpreting the data. In this paper, we present scX, an R package built on the Shiny framework that streamlines the analysis, exploration, and visualization of single-cell experiments. With an interactive graphic interface, implemented as a web application, scX provides easy access to key scRNAseq analyses, including marker identification, gene expression profiling, and differential gene expression analysis. Additionally, scX seamlessly integrates with commonly used single-cell Seurat and Single-CellExperiment R objects, resulting in efficient processing and visualization of varied datasets. Overall, scX serves as a valuable and user-friendly tool for effortless exploration and sharing of single-cell data, simplifying some of the complexities inherent in scRNAseq analysis.

Transcriptional dynamics orchestrating the development and integration of neurons born in the adult hippocampus.

The adult hippocampus generates new granule cells (aGCs) with functional capabilities that convey unique forms of plasticity to the preexisting circuits. While early differentiation of adult radial glia-like cells (RGLs) has been studied extensively, the molecular mechanisms guiding the maturation of postmitotic neurons remain unknown. Here, we used a precise birthdating strategy to study aGC differentiation using single-nuclei RNA sequencing. Transcriptional profiling revealed a continuous trajectory from RGLs to mature aGCs, with multiple immature stages bearing increasing levels of effector genes supporting growth, excitability, and synaptogenesis. Analysis of differential gene expression, pseudo-time trajectory, and transcription factors (TFs) revealed critical transitions defining four cellular states: quiescent RGLs, proliferative progenitors, immature aGCs, and mature aGCs. Becoming mature aGCs involved a transcriptional switch that shuts down pathways promoting cell growth, such SoxC TFs, to activate programs that likely control neuronal homeostasis. aGCs overexpressing Sox4 or Sox11 remained immature. Our results unveil precise molecular mechanisms driving adult RGLs through the pathway of neuronal differentiation.

Transcriptional dynamics orchestrating the development and integration of neurons born in the adult hippocampus.

The adult hippocampus generates new granule cells (aGCs) that exhibit distinct functional capabilities along development, conveying a unique form of plasticity to the preexisting circuits. While early differentiation of adult radial glia-like neural stem cells (RGL) has been studied extensively, the molecular mechanisms guiding the maturation of postmitotic neurons remain unknown. Here, we used a precise birthdating strategy to follow newborn aGCs along differentiation using single-nuclei RNA sequencing (snRNA-seq). Transcriptional profiling revealed a continuous trajectory from RGLs to mature aGCs, with multiple sequential immature stages bearing increasing levels of effector genes supporting growth, excitability and synaptogenesis. Remarkably, four discrete cellular states were defined by the expression of distinct sets of transcription factors (TFs): quiescent neural stem cells, proliferative progenitors, postmitotic immature aGCs, and mature aGCs. The transition from immature to mature aCGs involved a transcriptional switch that shutdown molecular cascades promoting cell growth, such as the SoxC family of TFs, to activate programs controlling neuronal homeostasis. Indeed, aGCs overexpressing Sox4 or Sox11 remained stalled at the immature state. Our results unveil precise molecular mechanisms driving adult neural stem cells through the pathway of neuronal differentiation.

scX: a user-friendly tool for scRNAseq exploration.

Motivation: Single-cell RNA sequencing (scRNAseq) has transformed our ability to explore biological systems. Nevertheless, proficient expertise is essential for handling and interpreting the data. Results: In this article, we present scX, an R package built on the Shiny framework that streamlines the analysis, exploration, and visualization of single-cell experiments. With an interactive graphic interface, implemented as a web application, scX provides easy access to key scRNAseq analyses, including marker identification, gene expression profiling, and differential gene expression analysis. Additionally, scX seamlessly integrates with commonly used single-cell Seurat and SingleCellExperiment R objects, resulting in efficient processing and visualization of varied datasets. Overall, scX serves as a valuable and user-friendly tool for effortless exploration and sharing of single-cell data, simplifying some of the complexities inherent in scRNAseq analysis. Availability and implementation: Source code can be downloaded from https://github.com/chernolabs/scX. A docker image is available from dockerhub as chernolabs/scx.

Reduced glioma growth following dexamethasone or anti-angiopoietin 2 treatment.

All patients with glioblastoma, the most aggressive and common form of brain cancer, develop cerebral edema. This complication is routinely treated with dexamethasone, a steroidal anti-inflammatory drug whose effects on brain tumors are not fully understood. Here we show that dexamethasone can reduce glioma growth in mice, even though it depletes infiltrating T cells with potential antitumor activity. More precisely, T cells with helper or cytotoxic function were sensitive to dexamethasone, but not those that were negative for the CD4 and CD8 molecules, including gammadelta and natural killer (NK) T cells. The antineoplastic effect of dexamethasone was indirect, as it did not meaningfully affect the growth and gene expression profile of glioma cells in vitro. In contrast, hundreds of dexamethasone-modulated genes, notably angiopoietin 2 (Angpt2), were identified in cultured cerebral endothelial cells by microarray analysis. The ability of dexamethasone to attenuate Angpt2 expression was confirmed in vitro and in vivo. Selective neutralization of Angpt2 using a peptide-Fc fusion protein reduced glioma growth and vascular enlargement to a greater extent than dexamethasone, without affecting T cell infiltration. In conclusion, this study suggests a mechanism by which dexamethasone can slow glioma growth, providing a new therapeutic target for malignant brain tumors.

Ultrasensitivity in signaling cascades revisited: Linking local and global ultrasensitivity estimations.

Ultrasensitive response motifs, capable of converting graded stimuli into binary responses, are well-conserved in signal transduction networks. Although it has been shown that a cascade arrangement of multiple ultrasensitive modules can enhance the system's ultrasensitivity, how a given combination of layers affects a cascade's ultrasensitivity remains an open question for the general case. Here, we introduce a methodology that allows us to determine the presence of sequestration effects and to quantify the relative contribution of each module to the overall cascade's ultrasensitivity. The proposed analysis framework provides a natural link between global and local ultrasensitivity descriptors and it is particularly well-suited to characterize and understand mathematical models used to study real biological systems. As a case study, we have considered three mathematical models introduced by O'Shaughnessy et al. to study a tunable synthetic MAPK cascade, and we show how our methodology can help modelers better understand alternative models.

Dehydroepiandrosterone (DHEA) is an anabolic steroid like dihydrotestosterone (DHT), the most potent natural androgen, and tetrahydrogestrinone (THG).

We have recently taken advantage of the unique power of DNA microarrays to compare the genomic expression profile of tetrahydrogestrinone (THG) with that of dihydrotestosterone (DHT), the most potent natural androgen, thus clearly demonstrating that THG is an anabolic steroid. In 2004, the U.S. Controlled Substances Act has been modified to include androstenedione (4-dione) as an anabolic steroid. However, despite the common knowledge that dehydroepiandrosterone (DHEA) is the precursor of testosterone, DHEA has been excluded from the list of anabolic steroids. We thus used the same DNA microarray technology to analyze the expression profile of practically all the 30,000 genes of the mouse genome modulated by DHEA and DHT in classical androgen-sensitive tissues. Daily subcutaneous injections of DHT (0.1mg) or DHEA (3mg) for 1 month in gonadectomized C57BL6/129 SV mice increased ventral prostate, dorsal prostate, seminal vesicle and preputial gland weight (p<0.01 for all tissues). As early as 24h after single injection of the two steroids, 878, 2681 and 14 probe sets were commonly stimulated or inhibited (p<0.01, change> or =30%), in the prostate (ventral+dorsal), seminal vesicles and preputial glands, respectively, compared to tissues from gonadectomized control animals. After 7 days of daily treatment with DHEA and DHT, 629, 919 and 562 probe sets were commonly modulated in the same tissues while after 27 days of treatment, 1195, 5127 and 2883 probe sets were modulated, respectively. In analogy with the data obtained with THG, the present microarray data provide an extremely precise and unquestionable genomic signature and proof of the androgenic/anabolic activity of DHEA. Such data add to the literature showing that DHEA is transformed into androgens in the human peripheral tissues as well as in laboratory animal species, including the monkey, thus exerting potent androgenic/anabolic activity. The present microarray approach to identify anabolic compounds is applicable to all potential androgenic/anabolic compounds.