Panagiotis Papasaikas

Epigenomic analysis detects widespread gene-body DNA hypomethylation in chronic lymphocytic leukemia.

We have extensively characterized the DNA methylomes of 139 patients with chronic lymphocytic leukemia (CLL) with mutated or unmutated IGHV and of several mature B-cell subpopulations through the use of whole-genome bisulfite sequencing and high-density microarrays. The two molecular subtypes of CLL have differing DNA methylomes that seem to represent epigenetic imprints from distinct normal B-cell subpopulations. DNA hypomethylation in the gene body, targeting mostly enhancer sites, was the most frequent difference between naive and memory B cells and between the two molecular subtypes of CLL and normal B cells. Although DNA methylation and gene expression were poorly correlated, we identified gene-body CpG dinucleotides whose methylation was positively or negatively associated with expression. We have also recognized a DNA methylation signature that distinguishes new clinico-biological subtypes of CLL. We propose an epigenomic scenario in which differential methylation in the gene body may have functional and clinical implications in leukemogenesis.

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.

The Spliceosome: The Ultimate RNA Chaperone and Sculptor

The spliceosome, one of the most complex machineries of eukaryotic cells, removes intronic sequences from primary transcripts to generate functional messenger and long noncoding RNAs (lncRNA). Genetic, biochemical, and structural data reveal that the spliceosome is an RNA-based enzyme. Striking mechanistic and structural similarities strongly argue that pre-mRNA introns originated from self-catalytic group II ribozymes. However, in the spliceosome, protein components organize and activate the catalytic-site RNAs, and recognize and pair together splice sites at intron boundaries. The spliceosome is a dynamic, reversible, and flexible machine that chaperones small nuclear (sn) RNAs and a variety of pre-mRNA sequences into conformations that enable intron removal. This malleability likely contributes to the regulation of alternative splicing, a prevalent process contributing to cell differentiation, homeostasis, and disease.

Functional Splicing Network Reveals Extensive Regulatory Potential of the Core Spliceosomal Machinery

Pre-mRNA splicing relies on the poorly understood dynamic interplay between >150 protein components of the spliceosome. The steps at which splicing can be regulated remain largely unknown. We systematically analyzed the effect of knocking down the components of the splicing machinery on alternative splicing events relevant for cell proliferation and apoptosis and used this information to reconstruct a network of functional interactions. The network accurately captures known physical and functional associations and identifies new ones, revealing remarkable regulatory potential of core spliceosomal components, related to the order and duration of their recruitment during spliceosome assembly. In contrast with standard models of regulation at early steps of splice site recognition, factors involved in catalytic activation of the spliceosome display regulatory properties. The network also sheds light on the antagonism between hnRNP C and U2AF, and on targets of antitumor drugs, and can be widely used to identify mechanisms of splicing regulation.

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.

Reconstruction of composite regulator-target splicing networks from high-throughput transcriptome data

We present a computational framework tailored for the modeling of the complex, dynamic relationships that are encountered in splicing regulation. The starting point is whole-genome transcriptomic data from high-throughput array or sequencing methods that are used to quantify gene expression and alternative splicing across multiple contexts. This information is used as input for state of the art methods for Graphical Model Selection in order to recover the structure of a composite network that simultaneously models exon co-regulation and their cognate regulators. Community structure detection and social network analysis methods are used to identify distinct modules and key actors within the network. As a proof of concept for our framework we studied the splicing regulatory network for Drosophila development using the publicly available modENCODE data. The final model offers a comprehensive view of the splicing circuitry that underlies fly development. Identified modules are associated with major developmental hallmarks including maternally loaded RNAs, onset of zygotic gene expression, transitions between life stages and sex differentiation. Within-module key actors include well-known developmental-specific splicing regulators from the literature while additional factors previously unassociated with developmental-specific splicing are also highlighted. Finally we analyze an extensive battery of Splicing Factor knock-down transcriptome data and demonstrate that our approach captures true regulatory relationships.

Fine-mapping reveals novel alternative splicing of the dopamine transporter

The dopamine transporter gene (SLC6A3, DAT) has been implicated in the pathogenesis of numerous psychiatric and neurodevelopmental disorders, including schizophrenia (SZ). We previously detected association between SZ and intronic SLC6A3 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 SLC6A3 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 SLC6A3 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.

Splicing in 4D

Flexibility in regulating RNA splicing can generate diverse phenotypic differences among equivalent organs across vertebrates. In the chapter of The Origin of Species entitled “Difficulties on Theory,” Charles Darwin found it “most difficult to conjecture by what transitions an organ could have arrived at its present state.” On pages 1587 and 1593 of this issue, Barbosa-Morais et al. (1) and Merkin et al. (2) advance our understanding of the molecular mechanism by which the genome generates differences in organs between species. This part of the answer relies on the broken syntax of genomic messages and uncovers striking differences in how evolution shapes the different layers of gene regulation.

Correction to: The Spliceosome: The Ultimate RNA Chaperone and Sculptor

Due to a production error, a low-resolution version of Figure 5 was inadvertently published in the version of the above Review article by Papasaikas and Valcarcel that was originally published online on December 9, 2015. The correct, high-resolution version now appears in the article online and in print. Trends in Biochemical Sciences regrets this error and apologizes for any confusion it has caused.