Data_Sheet_1_Interpreting Non-coding Genetic Variation in Multiple Sclerosis Genome-Wide Associated Regions.docx

Multiple sclerosis (MS) is the most common neurological disorder in young adults. Despite extensive studies, only a fraction of MS heritability has been explained, with association studies focusing primarily on protein-coding genes, essentially for the difficulty of interpreting non-coding features. However, non-coding RNAs (ncRNAs) and functional elements, such as super-enhancers (SE), are crucial regulators of many pathways and cellular mechanisms, and they have been implicated in a growing number of diseases. In this work, we searched for possible enrichments in non-coding elements at MS genome-wide associated loci, with the aim to highlight their possible involvement in the susceptibility to the disease. We first reconstructed the linkage disequilibrium (LD) structure of the Italian population using data of 727,478 single-nucleotide polymorphisms (SNPs) from 1,668 healthy individuals. The genomic coordinates of the obtained LD blocks were intersected with those of the top hits identified in previously published MS genome-wide association studies (GWAS). By a bootstrapping approach, we hence demonstrated a striking enrichment of non-coding elements, especially of circular RNAs (circRNAs) mapping in the 73 LD blocks harboring MS-associated SNPs. In particular, we found a total of 482 circRNAs (annotated in publicly available databases) vs. a mean of 194 ± 65 in the random sets of LD blocks, using 1,000 iterations. As a proof of concept of a possible functional relevance of this observation, we experimentally verified that the expression levels of a circRNA derived from an MS-associated locus, i.e., hsa_circ_0043813 from the STAT3 gene, can be modulated by the three genotypes at the disease-associated SNP. Finally, by evaluating RNA-seq data of two cell lines, SH-SY5Y and Jurkat cells, representing tissues relevant for MS, we identified 18 (two novel) circRNAs derived from MS-associated genes. In conclusion, this work showed for the first time that MS-GWAS top hits map in LD blocks enriched in circRNAs, suggesting circRNAs as possible novel contributors to the disease pathogenesis.</p

Data_Sheet_2_Interpreting Non-coding Genetic Variation in Multiple Sclerosis Genome-Wide Associated Regions.xlsx

Multiple sclerosis (MS) is the most common neurological disorder in young adults. Despite extensive studies, only a fraction of MS heritability has been explained, with association studies focusing primarily on protein-coding genes, essentially for the difficulty of interpreting non-coding features. However, non-coding RNAs (ncRNAs) and functional elements, such as super-enhancers (SE), are crucial regulators of many pathways and cellular mechanisms, and they have been implicated in a growing number of diseases. In this work, we searched for possible enrichments in non-coding elements at MS genome-wide associated loci, with the aim to highlight their possible involvement in the susceptibility to the disease. We first reconstructed the linkage disequilibrium (LD) structure of the Italian population using data of 727,478 single-nucleotide polymorphisms (SNPs) from 1,668 healthy individuals. The genomic coordinates of the obtained LD blocks were intersected with those of the top hits identified in previously published MS genome-wide association studies (GWAS). By a bootstrapping approach, we hence demonstrated a striking enrichment of non-coding elements, especially of circular RNAs (circRNAs) mapping in the 73 LD blocks harboring MS-associated SNPs. In particular, we found a total of 482 circRNAs (annotated in publicly available databases) vs. a mean of 194 ± 65 in the random sets of LD blocks, using 1,000 iterations. As a proof of concept of a possible functional relevance of this observation, we experimentally verified that the expression levels of a circRNA derived from an MS-associated locus, i.e., hsa_circ_0043813 from the STAT3 gene, can be modulated by the three genotypes at the disease-associated SNP. Finally, by evaluating RNA-seq data of two cell lines, SH-SY5Y and Jurkat cells, representing tissues relevant for MS, we identified 18 (two novel) circRNAs derived from MS-associated genes. In conclusion, this work showed for the first time that MS-GWAS top hits map in LD blocks enriched in circRNAs, suggesting circRNAs as possible novel contributors to the disease pathogenesis.</p

<i>In-silico</i> prediction of an ESE-enriched 25-bp sequence and identification of the interacting proteins.

<p>(A) Schematic representation of the minigene construct containing the 75-bp <i>FGG</i> pseudoexon activated by the IVS6-320A>T mutation (indicated by an arrow). (bottom) ESE elements predicted by the ESEFinder program (<a href="http://rulai.cshl.edu/cgi-bin/tools/ESE3/esefinder.cgi?process=home" target="_blank">http://rulai.cshl.edu/cgi-bin/tools/ESE3/esefinder.cgi?process=home</a>) in the pseudoexon sequence are indicated by the histogram bars; the ESE-enriched 25-bp sub-region is underlined. (B) Western blot analysis of RNA-protein pulldown assays for the identification of <i>trans</i>-acting factors binding to the 25-bp region. (top) Sequences used in pulldown experiments. (bottom) Western blot analysis of hnRNP and SR proteins immunoprecipitated from HeLa nuclear extracts with either the wild-type or the scrambled 25-bp (as negative control) pseudoexon sequence.</p

Functional characterization of the 25-bp region.

<p>(A) Effect of the 25-bp region on pseudoexon inclusion. Minigene constructs either containing (M) or lacking (M-del25) the 25-bp region were transiently transfected in HeLa cells. The relative amount of pseudoexon inclusion was measured by fluorescent RT-PCR. (top) Schematic representation of the RT-PCR products; primers used in RT-PCR experiments are indicated by arrows. The length of each fragment is also indicated. (bottom, left and middle panels) GeneMapper windows displaying fluorescence peaks corresponding to the RT-PCR products. The fluorescence peak areas were measured as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059333#pone-0059333-g002" target="_blank">Figure 2B</a> legend. (bottom, right panel) Histograms representing the relative amount of transcripts including or skipping the pseudoexon, as assessed by calculating the ratio of the corresponding fluorescence peak areas (setting the sum of all peaks as 100%). Bars represent mean ± SD of 3 independent experiments, each performed in triplicate. (B) Knock-down experiments showing that silencing of hnRNP F in the absence of the 25-bp region significantly promotes pseudoexon inclusion. Quantitation by qRT-PCR demonstrates that the hnRNP F splicing-enhancer activity is dependent on the integrity of the 25-bp region. The results were analyzed by unpaired t-test (***P<0.001).</p

Dual Role of G-runs and hnRNP F in the Regulation of a Mutation-Activated Pseudoexon in the Fibrinogen Gamma-Chain Transcript

<div><p>Most pathological pseudoexon inclusion events originate from single activating mutations, suggesting that many intronic sequences are on the verge of becoming exons. However, the precise mechanisms controlling pseudoexon definition are still largely unexplored. Here, we investigated the <i>cis</i>-acting elements and <i>trans</i>-acting regulatory factors contributing to the regulation of a previously described fibrinogen gamma-chain (<i>FGG</i>) pseudoexon, which is activated by a deep-intronic mutation (IVS6-320A>T). This pseudoexon contains several G-run elements, which may be bound by heterogeneous nuclear ribonucleoproteins (hnRNPs) F and H. To explore the effect of these proteins on <i>FGG</i> pseudoexon inclusion, both silencing and overexpression experiments were performed in eukaryotic cells. While hnRNP H did not significantly affect pseudoexon splicing, hnRNP F promoted pseudoexon inclusion, indicating that these two proteins have only partially redundant functions. To verify the binding of hnRNP F and the possible involvement of other <i>trans</i>-acting splicing modulators, pulldown experiments were performed on the region of the pseudoexon characterized by both a G-run and enrichment for exonic splicing enhancers. This 25-bp-long region strongly binds hnRNP F/H and weakly interacts with Serine/Arginine-rich protein 40, which however was demonstrated to be dispensable for <i>FGG</i> pseudoexon inclusion in overexpression experiments. Deletion analysis, besides confirming the splicing-promoting role of the G-run within this 25-bp region, demonstrated that two additional hnRNP F binding sites might instead function as silencer elements. Taken together, our results indicate a major role of hnRNP F in regulating <i>FGG</i> pseudoexon inclusion, and strengthen the notion that G-runs may function either as splicing enhancers or silencers of the same exon.</p> </div

Functional dissection of G-run elements within the pseudoexon sequence.

<p>(top) The complete 75-bp-long pseudoexon sequence and flanking splice sites; nucleotides belonging to the pseudoexon are in capital letters; the star indicates the IVS6-320A>T mutation; the deleted sequences (shaded in gray) are indicated. (bottom) Histograms representing the relative amount of transcripts including or skipping the pseudoexon, calculated for each deletion mutant as described in the legend of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059333#pone-0059333-g002" target="_blank">Figure 2B</a>. Bars represent mean ± SD of 3 independent experiments, each performed in triplicate. The results were analyzed by unpaired t-test. Statistical significance was calculated referring to the M construct (*P<0.05; **P<0.01; ***P<0.001).</p

Effect of hnRNP H and F modulation on the regulation of <i>FGG</i> pseudoexon splicing.

<p>(A) Knockdown of hnRNP H and F. Western blot (left) and corresponding densitometric analysis (middle) demonstrating the actual silencing of hnRNP H and F proteins in RNAi experiments. (right) Relative expression levels of wild-type and pseudoexon-containing transcripts by qRT-PCR. The ratio between the two isoforms in samples silenced for either hnRNP F or H was also calculated. (B) Transient overexpression of hnRNP F. (left) GeneMapper windows displaying fluorescence peaks corresponding to RT-PCR products obtained from the cDNA of cells transfected with constructs expressing the M minigene with or without hnRNP F overexpression. The fluorescence peak areas were measured by the GeneMapper v4.0 software. The X-axis represents data points (size standard peaks are also indicated) and the Y-axis represents fluorescence units. (right) Histograms represent the relative amount of transcripts including or skipping the pseudoexon, as assessed by calculating the ratio of the corresponding fluorescence peak areas (setting the sum of all peaks as 100%). Bars represent mean ± SD of 3 independent experiments, each performed in triplicate. The results were analyzed by unpaired t-test (*P<0.05; **P<0.01; ***P<0.001).</p

Schematic representation of the 75-bp <i>FGG</i> pseudoexon activated by the IVS6-320A>T mutation.

<p>(top) The fibrinogen cluster; boxes and lines represent exons and intronic/intergenic regions, respectively (only exons are drawn to scale); the two parallel slanted lines indicate breaks in the scale. (middle) The <i>FGG</i> minigene (M) cloned in pTargeT vector; the star marks the IVS6-320A>T mutation. (bottom) The complete 75-bp-long pseudoexon sequence and flaking splice sites; nucleotides belonging to the pseudoexon are in capital letters; the strength of pseudoexon splice sites, calculated by using the NNSPLICE 0.9 (<a href="http://www.fruitfly.org/seq_tools/splice.html" target="_blank">http://www.fruitfly.org/seq_tools/splice.html</a>) and the Netgene2 (<a href="http://www.cbs.dtu.dk/services/NetGene2/" target="_blank">http://www.cbs.dtu.dk/services/NetGene2/</a>) software is reported below the corresponding sequence; G-stretches are shaded in gray.</p

<i>In-vitro</i> analysis of the impact of c.2245-40A>G variant on <i>COL4A5</i> pre-mRNA splicing.

<p>(A) Schematic representation of the hybrid pBS-KS-COL4A5_ex29 minigene where α-globin exons are represented by light grey boxes, fibronectin (<i>FN1</i>) exons by white boxes, whereas introns are shown as black lines (not to scale). Exon 29 of <i>COL4A5</i> is represented by a dark grey box. The c.2245-40A>G mutation in intron 28 is indicated by a star. Primers used in RT-PCR assays are also indicated. (B) On the left, agarose gel (2%) electrophoresis of RT-PCR products obtained from RNA of HEK293 cells transfected with the wild-type (wt) or mutant (mut) minigene vector. M: molecular weight marker (pUC9-<i>Hae</i>III). In the middle, GeneMapper windows show fluorescence peaks corresponding to the molecular species amplified by RT-PCR. Grey shaded peaks correspond to the RT-PCR-labeled products, whose relative quantitation is reported on the right of the panel (%). Unshaded peaks represent the size standard (ROX-500 HD). The <i>x</i> axis indicates fluorescence units. On the right, schematic representation of the splicing products, as verified by Sanger sequencing. The length of each fragment is shown.</p

Image_1_Mycobacterium tuberculosis Drives Expansion of Low-Density Neutrophils Equipped With Regulatory Activities.TIF

In human tuberculosis (TB) neutrophils represent the most commonly infected phagocyte but their role in protection and pathology is highly contradictory. Moreover, a subset of low-density neutrophils (LDNs) has been identified in TB, but their functions remain unclear. Here, we have analyzed total neutrophils and their low-density and normal-density (NDNs) subsets in patients with active TB disease, in terms of frequency, phenotype, functional features, and gene expression signature. Full-blood counts from Healthy Donors (H.D.), Latent TB infected, active TB, and cured TB patients were performed. Frequency, phenotype, burst activity, and suppressor T cell activity of the two different subsets were assessed by flow cytometry while NETosis and phagocytosis were evaluated by confocal microscopy. Expression analysis was performed by using the semi-quantitative RT-PCR array technology. Elevated numbers of total neutrophils and a high neutrophil/lymphocyte ratio distinguished patients with active TB from all the other groups. PBMCs of patients with active TB disease contained elevated percentages of LDNs compared with those of H.D., with an increased expression of CD66b, CD33, CD15, and CD16 compared to NDNs. Transcriptomic analysis of LDNs and NDNs purified from the peripheral blood of TB patients identified 12 genes differentially expressed: CCL5, CCR5, CD4, IL10, LYZ, and STAT4 were upregulated, while CXCL8, IFNAR1, NFKB1A, STAT1, TICAM1, and TNF were downregulated in LDNs, as compared to NDNs. Differently than NDNs, LDNs failed to phagocyte live Mycobacterium tuberculosis (M. tuberculosis) bacilli, to make oxidative burst and NETosis, but caused significant suppression of antigen-specific and polyclonal T cell proliferation which was partially mediated by IL-10. These insights add a little dowel of knowledge in understanding the pathogenesis of human TB.</p