Dynamics of alternative splicing during somatic cell reprogramming reveals functions for RNA-binding proteins CPSF3, hnRNP UL1, and TIA1

C.V. was recipient of an FPI-Severo Ochoa Fellowship from the Spanish Ministry of Economy and Competitiveness. Work in J.V. laboratory is supported by the European Research Council (ERC AdvG 670146), AGAUR, Spanish Ministry of Economy and Competitiveness (BFU 2017 89308-P) and the Centre of Excellence Severo Ochoa. Work in T.G.'s laboratory was supported by the European Research Council FP7/2007-2013 (ERC Synergy Grant 4D-Genome) the Ministerio de Educación y Ciencia (SAF.2012-37167) and AGAUR. We acknowledge support of the Spanish Ministry of Science and Innovation to the EMBL partnership and the CERCA Programme / Generalitat de Catalunya.UDTRIASBackground: Somatic cell reprogramming is the process that allows differentiated cells to revert to a pluripotent state. In contrast to the extensively studied rewiring of epigenetic and transcriptional programs required for reprogramming, the dynamics of post-transcriptional changes and their associated regulatory mechanisms remain poorly understood. Here we study the dynamics of alternative splicing changes occurring during efficient reprogramming of mouse B cells into induced pluripotent stem (iPS) cells and compare them to those occurring during reprogramming of mouse embryonic fibroblasts. Results: We observe a significant overlap between alternative splicing changes detected in the two reprogramming systems, which are generally uncoupled from changes in transcriptional levels. Correlation between gene expression of potential regulators and specific clusters of alternative splicing changes enables the identification and subsequent validation of CPSF3 and hnRNP UL1 as facilitators, and TIA1 as repressor of mouse embryonic fibroblasts reprogramming. We further find that these RNA-binding proteins control partially overlapping programs of splicing regulation, involving genes relevant for developmental and morphogenetic processes. Conclusions: Our results reveal common programs of splicing regulation during reprogramming of different cell types and identify three novel regulators of this process and their targets

A unique bipartite Polycomb signature regulates stimulus-response transcription during development

Rapid cellular responses to environmental stimuli are fundamental for development and maturation. Immediate early genes can be transcriptionally induced within minutes in response to a variety of signals. How their induction levels are regulated and their untimely activation by spurious signals prevented during development is poorly understood. We found that in developing sensory neurons, before perinatal sensory-activity-dependent induction, immediate early genes are embedded into a unique bipartite Polycomb chromatin signature, carrying active H3K27ac on promoters but repressive Ezh2-dependent H3K27me3 on gene bodies. This bipartite signature is widely present in developing cell types, including embryonic stem cells. Polycomb marking of gene bodies inhibits mRNA elongation, dampening productive transcription, while still allowing for fast stimulus-dependent mark removal and bipartite gene induction. We reveal a developmental epigenetic mechanism regulating the rapidity and amplitude of the transcriptional response to relevant stimuli, while preventing inappropriate activation of stimulus-response genes.T.K. was supported by a Japan Society for the Promotion of Science fellowship, and O.J. was supported by an EMBO Long-Term fellowship. F.M.R. was supported by the Swiss National Science Foundation (31003A_149573 and 31003A_175776). This project has also received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant no. 810111-EpiCrest2Reg). F.M.R. and M.B.S. were also supported by the Novartis Research Foundation.Peer reviewe

Transcriptome characterization by RNA sequencing identifies a major molecular and clinical subdivision in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) has heterogeneous clinical and biological behavior. Whole-genome and -exome sequencing has contributed to the characterization of the mutational spectrum of the disease, but the underlying transcriptional profile is still poorly understood. We have performed deep RNA sequencing in different subpopulations of normal B-lymphocytes and CLL cells from a cohort of 98 patients, and characterized the CLL transcriptional landscape with unprecedented resolution. We detected thousands of transcriptional elements differentially expressed between the CLL and normal B cells, including protein-coding genes, noncoding RNAs, and pseudogenes. Transposable elements are globally derepressed in CLL cells. In addition, two thousand genes-most of which are not differentially expressed-exhibit CLL-specific splicing patterns. Genes involved in metabolic pathways showed higher expression in CLL, while genes related to spliceosome, proteasome, and ribosome were among the most down-regulated in CLL. Clustering of the CLL samples according to RNA-seq derived gene expression levels unveiled two robust molecular subgroups, C1 and C2. C1/C2 subgroups and the mutational status of the immunoglobulin heavy variable (IGHV) region were the only independent variables in predicting time to treatment in a multivariate analysis with main clinico-biological features. This subdivision was validated in an independent cohort of patients monitored through DNA microarrays. Further analysis shows that B-cell receptor (BCR) activation in the microenvironment of the lymph node may be at the origin of the C1/C2 differences

Fine-mapping reveals novel alternative splicing of the dopamine transporter

Center for Human Genetic Research, Massachusetts General Hospital and Department of Neurology, Harvard Medical School, Harvard University, Boston, Massachusetts.Graduate Program in Biology and Biomedical Science, Yale University, New Haven, Connecticut.The dopamine transporter gene (, ) has been implicated in the pathogenesis of numerous psychiatric and neurodevelopmental disorders, including schizophrenia (SZ). We previously detected association between SZ and intronic variants that replicated in two independent Caucasian samples, but had no obvious function. In follow-up analyses, we sequenced the coding and intronic regions of to identify complete linkage disequilibrium patterns of common variations. We genotyped 78 polymorphisms, narrowing the potentially causal region to two correlated clusters of associated SNPs localized predominantly to introns 3 and 4. Our computational analysis of these intronic regions predicted a novel cassette exon within intron 3, designated E3b, which is conserved among primates. We confirmed alternative splicing of E3b in post-mortem human substantia nigra (SN). As E3b introduces multiple in-frame stop codons, the open reading frame is truncated and the spliced product may undergo nonsense mediated decay. Thus, factors that increase E3b splicing could reduce the amount of unspliced product available for translation. Observations consistent with this prediction were made using cellular assays and in post-mortem human SN. In mini-gene constructs, the extent of splicing is also influenced by at least two common haplotypes, so the alternative splicing was evaluated in relation to SZ risk. Meta-analyses across genome-wide association studies did not support the initial associations and further post-mortem studies did not suggest case-control differences in splicing. These studies do not provide a compelling link to schizophrenia. However, the impact of the alternative splicing on other neuropsychiatric disorders should be investigated. © 2010 Wiley-Liss, Inc

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease

Deconvolving specific from non-specific effects in differential gene expression experiments

Understanding the mechanisms of action upon cellular perturbations is a fundamental endeavor in molecular and chemical biology. Differential expression analysis is a widely used approach for probing these mechanisms, yet it presents substantial interpretational challenges due to the presence of secondary effects and the complex impact of experimental treatments on gene expression. To address this, we introduce orthos, an approach that employs Deep Generative Networks to disentangle specific and non-specific effects of perturbations on gene expression. Trained on large collections of human and mouse gene expression contrasts compiled for this work, orthos isolates non-specific effects by learning the patterns of expression changes that manifest time and again in unrelated experiments. We demonstrate, in diverse experimental settings, that the specific component obtained from the decomposition is a more informative and robust experimental signature and a better proxy for the direct molecular effects of a treatment compared to the original contrast, thereby drastically enhancing the interpretability of differential expression results. In addition, orthos allows identification of experiments with similar specific effects, aiding in the mapping of new treatments to their mechanisms of action. In summary, orthos constitutes a novel strategy in the analysis and interpretation of gene expression data and offers a powerful platform for the study of genetic, physiological, and pharmacological treatments in basic and applied research

Deconvolving specific from non-specific effects in differential gene expression experiments

Understanding the mechanisms of action upon cellular perturbations is a fundamental endeavor in molecular and chemical biology. Differential expression analysis is a widely used approach for probing these mechanisms, yet it presents substantial interpretational challenges due to the presence of secondary effects and the complex impact of experimental treatments on gene expression. To address this, we introduce orthos, an approach that employs Deep Generative Networks to disentangle specific and non-specific effects of perturbations on gene expression. Trained on large collections of human and mouse gene expression contrasts compiled for this work, orthos isolates non-specific effects by learning the patterns of expression changes that manifest time and again in unrelated experiments. We demonstrate, in diverse experimental settings, that the specific component obtained from the decomposition is a more informative and robust experimental signature and a better proxy for the direct molecular effects of a treatment compared to the original contrast, thereby drastically enhancing the interpretability of differential expression results. In addition, orthos allows identification of experiments with similar specific effects, aiding in the mapping of new treatments to their mechanisms of action. In summary, orthos constitutes a novel strategy in the analysis and interpretation of gene expression data and offers a powerful platform for the study of genetic, physiological, and pharmacological treatments in basic and applied research

Neo-Sumerian account Texts in the Horn Archaeological Museum: Seal Impressions

While Sigrist supplies linguistic analysis, Gavin and his assistants provide composite drawings of the seal impressions. AU Press cataloguehttps://digitalcommons.andrews.edu/books/1080/thumbnail.jp

Genome-wide identification of Fas/CD95 alternative splicing regulators reveals links with iron homeostasis

Alternative splicing of Fas/CD95 exon 6 generates either a membrane-bound receptor that promotes, or a soluble isoform that inhibits, apoptosis. Using an automatized genome-wide siRNA screening for alternative splicing regulators of endogenous transcripts in mammalian cells, we identified 200 genes whose knockdown modulates the ratio between Fas/CD95 isoforms. These include classical splicing regulators; core spliceosome components; and factors implicated in transcription and chromatin remodeling, RNA transport, intracellular signaling, and metabolic control. Coherent effects of genes involved in iron homeostasis and pharmacological modulation of iron levels revealed a link between intracellular iron and Fas/CD95 exon 6 inclusion. A splicing regulatory network linked iron levels with reduced activity of the Zinc-finger-containing splicing regulator SRSF7, and in vivo and in vitro assays revealed that iron inhibits SRSF7 RNA binding. Our results uncover numerous links between cellular pathways and RNA processing and a mechanism by which iron homeostasis can influence alternative splicing