X chromosome inactivation: Activation of Silencing

X chromosome inactivation is a process that ensures equal expression of the X chromosomes between males, which have one X and one Y chromosome, and females, which have two X chromosomes, in mammals. Females initiate inactivation of one of their two X chromosomes early during embryogenesis, by expressing an untranslated RNA from the X-encoded Xist gene. Xist RNA coats and silences the X chromosome in cis, after which the silenced state of the inactive X chromosome is propagated through many cell divisions. Three major research questions dominate the field of XCI. How is a cell able to count the number of X chromosomes present? How is it possible that only one of the two X chromosomes in female diploid cells is inactivated? And how is the X chromosome silenced in cis? Although many researchers have attempted to explain the initiation and regulation of the XCI process with a wide array of models, none of the proposed models is able to explain all observations made with deletion and overexpression studies in mouse ES cell lines and embryos. Therefore, the aim of this thesis is to obtain additional data, and to postulate a comprehensive model for the initiation of XCI in the mouse. This model will encompass how the cell is able to detect the number of X chromosomes and how it can inactivate only one of them without inactivating all X chromosomes present in a cell. The discovery of an important activator of XCI initiation strengthens this model. Furthermore, the mechanism of spreading of Xist RNA, and thus the silencing of the X chromosome in cis, will be addressed. A hypothesis regarding the spreading of Xist RNA over the inactive X, and how Xist RNA is restricted to the Xi, will be formulated. Overall, the most important conundrums in XCI will be addressed in this thesis, and we present a more logical and complete model explaining the regulation of XCI

X chromosome inactivation: Activation of Silencing

X chromosome inactivation is a process that ensures equal expression of the X chromosomes between males, which have one X and one Y chromosome, and females, which have two X chromosomes, in mammals. Females initiate inactivation of one of their two X chromosomes early during embryogenesis, by expressing an untranslated RNA from the X-encoded Xist gene. Xist RNA coats and silences the X chromosome in cis, after which the silenced state of the inactive X chromosome is propagated through many cell divisions. Three major research questions dominate the field of XCI. How is a cell able to count the number of X chromosomes present? How is it possible that only one of the two X chromosomes in female diploid cells is inactivated? And how is the X chromosome silenced in cis? Although many researchers have attempted to explain the initiation and regulation of the XCI process with a wide array of models, none of the proposed models is able to explain all observations made with deletion and overexpression studies in mouse ES cell lines and embryos. Therefore, the aim of this thesis is to obtain additional data, and to postulate a comprehensive model for the initiation of XCI in the mouse. This model will encompass how the cell is able to detect the number of X chromosomes and how it can inactivate only one of them without inactivating all X chromosomes present in a cell. The discovery of an important activator of XCI initiation strengthens this model. Furthermore, the mechanism of spreading of Xist RNA, and thus the silencing of the X chromosome in cis, will be addressed. A hypothesis regarding the spreading of Xist RNA over the inactive X, and how Xist RNA is restricted to the Xi, will be formulated. Overall, the most important conundrums in XCI will be addressed in this thesis, and we present a more logical and complete model explaining the regulation of XCI

Genome-wide dynamics of Pol II elongation and its interplay with promoter proximal pausing, chromatin, and exons

Production of mRNA depends critically on the rate of RNA polymerase II (Pol II) elongation. To dissect Pol II dynamics in mouse ES cells, we inhibited Pol II transcription at either initiation or promoter-proximal pause escape with Triptolide or Flavopiridol, and tracked Pol II kinetically using GRO-seq. Both inhibitors block transcription of more than 95% of genes, showing that pause escape, like initiation, is a ubiquitous and crucial step within the transcription cycle. Moreover, paused Pol II is relatively stable, as evidenced from half-life measurements at ∼3200 genes. Finally, tracking the progression of Pol II after drug treatment establishes Pol II elongation rates at over 1000 genes. Notably, Pol II accelerates dramatically while transcribing through genes, but slows at exons. Furthermore, intergenic variance in elongation rates is substantial, and is influenced by a positive effect of H3K79me2 and negative effects of exon density and CG content within genes.DOI: http://dx.doi.org/10.7554/eLife.02407.001

Context-specific effects of genetic variants associated with autoimmune disease

Autoimmune diseases such as rheumatoid arthritis and coeliac disease are typical examples of complex genetic diseases caused by a combination of genetic and non-genetic risk factors. Insight into the genetic risk factors (single nucleotide polymorphisms (SNPs)) has increased since genome-wide association studies (GWAS) became possible in 2007 and, for individual diseases, SNPs can now explain some 15-50% of genetic risk. GWAS have also shown that some 50% of the genetic risk factors for individual autoimmune diseases overlap between different diseases. Thus, shared risk factors may converge to pathways that, when perturbed by genetic variation, predispose to autoimmunity in general. This raises the question of what determines disease specificity, and suggests that identical risk factors may have different effects in various autoimmune diseases. Addressing this question requires translation of genetic risk factors to causal genes and then to molecular and cellular pathways. Since > 90% of the genetic risk factors are found in the non-coding part of the genome (i.e. outside the exons of protein-coding genes) and can have an impact on gene regulation, there is an urgent need to better understand the non-coding part of the genome. Here, we will outline the methods being used to unravel the gene regulatory networks perturbed in autoimmune diseases and the importance of doing this in the relevant cell types. We will highlight findings in coeliac disease, which manifests in the small intestine, to demonstrate how cell type and disease context can impact on the consequences of genetic risk factors

Molecular Biomarkers for Celiac Disease:Past, Present and Future

Celiac disease (CeD) is a complex immune-mediated disorder that is triggered by dietary gluten in genetically predisposed individuals. CeD is characterized by inflammation and villous atrophy of the small intestine, which can lead to gastrointestinal complaints, malnutrition, and malignancies. Currently, diagnosis of CeD relies on serology (antibodies against transglutaminase and endomysium) and small-intestinal biopsies. Since small-intestinal biopsies require invasive upper-endoscopy, and serology cannot predict CeD in an early stage or be used for monitoring disease after initiation of a gluten-free diet, the search for non-invasive biomarkers is ongoing. Here, we summarize current and up-and-coming non-invasive biomarkers that may be able to predict, diagnose, and monitor the progression of CeD. We further discuss how current and emerging techniques, such as (single-cell) transcriptomics and genomics, can be used to uncover the pathophysiology of CeD and identify non-invasive biomarkers

A Combined mRNA- and miRNA-Sequencing Approach Reveals miRNAs as Potential Regulators of the Small Intestinal Transcriptome in Celiac Disease

Celiac disease (CeD) is triggered by gluten and results in inflammation and villous atrophy of the small intestine. We aimed to explore the role of miRNA-mediated deregulation of the transcriptome in CeD. Duodenal biopsies of CeD patients (n = 33) and control subjects (n = 10) were available for miRNA-sequencing, with RNA-sequencing also available for controls (n = 5) and CeD (n = 6). Differential expression analysis was performed to select CeD-associated miRNAs and genes. MiRNA‒target transcript pairs selected from public databases that also displayed a strong negative expression correlation in the current dataset (R < −0.7) were used to construct a CeD miRNA‒target transcript interaction network. The network includes 2030 miRNA‒target transcript interactions, including 423 experimentally validated pairs. Pathway analysis found that interactions are involved in immune-related pathways (e.g., interferon signaling) and metabolic pathways (e.g., lipid metabolism). The network includes 13 genes previously prioritized to be causally deregulated by CeD-associated genomic variants, including STAT1. CeD-associated miRNAs might play a role in promoting inflammation and decreasing lipid metabolism in the small intestine, thereby contributing unbalanced cell turnover in the intestinal crypt. Some CeD-associated miRNAs deregulate genes that are also affected by genomic CeD-risk variants, adding an additional layer of complexity to the deregulated transcriptome in CeD

Single-Cell RNA Sequencing of Peripheral Blood Mononuclear Cells From Pediatric Coeliac Disease Patients Suggests Potential Pre-Seroconversion Markers

Celiac Disease (CeD) is a complex immune disorder involving villous atrophy in the small intestine that is triggered by gluten intake. Current CeD diagnosis is based on late-stage pathophysiological parameters such as detection of specific antibodies in blood and histochemical detection of villus atrophy and lymphocyte infiltration in intestinal biopsies. To date, no early onset biomarkers are available that would help prevent widespread villous atrophy and severe symptoms and co-morbidities. To search for novel CeD biomarkers, we used single-cell RNA sequencing (scRNAseq) to investigate PBMC samples from 11 children before and after seroconversion for CeD and 10 control individuals matched for age, sex and HLA-genotype. We generated scRNAseq profiles of 9559 cells and identified the expected major cellular lineages. Cell proportions remained stable across the different timepoints and health conditions, but we observed differences in gene expression profiles in specific cell types when comparing patient samples before and after disease development and comparing patients with controls. Based on the time when transcripts were differentially expressed, we could classify the deregulated genes as biomarkers for active CeD or as potential pre-diagnostic markers. Pathway analysis showed that active CeD biomarkers display a transcriptional profile associated with antigen activation in CD4+ T cells, whereas NK cells express a subset of biomarker genes even before CeD diagnosis. Intersection of biomarker genes with CeD-associated genetic risk loci pinpointed genetic factors that might play a role in CeD onset. Investigation of potential cellular interaction pathways of PBMC cell subpopulations highlighted the importance of TNF pathways in CeD. Altogether, our results pinpoint genes and pathways that are altered prior to and during CeD onset, thereby identifying novel potential biomarkers for CeD diagnosis in blood