B-Cell and Monocyte Contribution to Systemic Lupus Erythematosus Identified by Cell-Type-Specific Differential Expression Analysis in RNA-Seq Data

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by complex interplay among immune cell types. SLE activity is experimentally assessed by several blood tests, including gene expression profiling of heterogeneous populations of cells in peripheral blood. To better understand the contribution of different cell types in SLE pathogenesis, we applied the two methods in cell-type-specific differential expression analysis, csSAM and DSection, to identify cell-type-specific gene expression differences in heterogeneous gene expression measures obtained using RNA-seq technology. We identified B-cell-, monocyte-, and neutrophil-specific gene expression differences. Immunoglobulin-coding gene expression was altered in B-cells, while a ribosomal signature was prominent in monocytes. On the contrary, genes differentially expressed in the heterogeneous mixture of cells did not show any functional enrichment. Our results identify antigen binding and structural constituents of ribosomes as functions altered by B-cell- and monocyte-specific gene expression differences, respectively. Finally, these results position both csSAM and DSection methods as viable techniques for celltype-specific differential expression analysis, which may help uncover pathogenic, cell-type-specific processes in SLE

Transcriptional changes in trichothiodystrophy cells

Mutations in three of the genes encoding the XPB, XPD and TTDA components of transcription factor TFIIH can result in the clinical phenotype of trichothiodystrophy (TTD). Different mutations in XPB and XPD can instead cause xeroderma pigmentosum (XP). The completely different features of these disorders have been attributed to TTD being a transcription syndrome. In order to detect transcriptional differences between TTD and XP cells from the XP-D complementation group, we have compared gene expression profiles in cultured fibroblasts from normal, XP and TTD donors. Although we detected transcriptional differences between individual cell strains, using an algorithm of moderate stringency, we did not identify any genes whose expression was reproducibly different in proliferating fibroblasts from each type of donor. Following UV-irradiation, many genes were up- and down-regulated in all three cell types. The microarray analysis indicated some apparent differences between the different donor types, but on more detailed inspection, these turned out to be false positives. We conclude that there are minimal differences in gene expression in proliferating fibroblasts from TTD, XP-D and normal donors

Combining GAL4 GFP enhancer trap with split luciferase to measure spatiotemporal promoter activity in Arabidopsis.

In multicellular organisms different types of tissues have distinct gene expression profiles associated with specific function or structure of the cell. Quantification of gene expression in whole organs or whole organisms can give misleading information about levels or dynamics of expression in specific cell types. Tissue- or cell-specific analysis of gene expression has potential to enhance our understanding of gene regulation and interactions of cell signalling networks. The Arabidopsis circadian oscillator is a gene network which orchestrates rhythmic expression across the day/night cycle. There is heterogeneity between cell and tissue types of the composition and behaviour of the oscillator. In order to better understand the spatial and temporal patterns of gene expression, flexible tools are required. By combining a Gateway®-compatible split luciferase construct with a GAL4 GFP enhancer trap system, we describe a tissue-specific split luciferase assay for non-invasive detection of spatiotemporal gene expression in Arabidopsis. We demonstrate the utility of this enhancer trap-compatible split luciferase assay (ETSLA) system to investigate tissue-specific dynamics of circadian gene expression. We confirm spatial heterogeneity of circadian gene expression in Arabidopsis leaves and describe the resources available to investigate any gene of interest

The identification of cell type defining genes across human tissues and the functional study of the endothelial adhesion G protein-coupled receptor L4

Cell type specific gene expression profiles underlie differences in cell morphology, behaviour, and specialized function. Single cell RNA sequencing can be used to measure gene expression in individual cells, but challenges remain including limited read-depth, artefactual changes due to dissociation from tissue, difficulties in the analysis of fragile or morphologically complex cell types, and bias introduced from the analysis of a limited number of biological replicates. In paper I, we used an integrative correlation analysis to define cell type enriched transcripts from bulk RNAseq, generated from visceral and subcutaneous adipose tissue. We identified depot and sex-specific differences. In Paper II, we expanded our analysis to include cell types in 15 human tissue types, to create a cell type enrichment prediction atlas for all protein coding genes. A cross-tissue comparison identified shared enrichment signatures between cell types in different tissues. We also defined core identity profiles of cell types present in all or most tissue types, including endothelial cells (EC), which can vary in gene enrichment profiles across different vascular beds. The focus of paper III was the functional characterisation of one such highly EC enriched gene, adhesion G protein-coupled rector L4 (ADGRL4). EC have a major role in various biological processes, including the regulation of inflammatory responses and haemostasis. The endothelial restricted expression of ADGRL4 is indicative of an important cell type specific role in EC. We depleted ADGRL4 in EC and measured associated changes in proteome and function, under normal and cytokine stimulated conditions. Under inflammatory conditions, ADGRL4 depletion potentiated EC pro-coagulant protein expression and associated thrombin and fibrin formation. Concurrently, ADGRL4 depletion inhibited the expression of inflammation-induced interferon response genes. This indicates that ADGRL4 has a currently unappreciated role in the EC function, with a potential role in the regulation of coagulation during inflammation

Evolution of Neuronal and Endothelial Transcriptomes in Primates

The study of gene expression evolution in vertebrates has hitherto focused on the analysis of transcriptomes in tissues of different species. However, because a tissue is made up of different cell types, and cell types differ with respect to their transcriptomes, the analysis of tissues offers a composite picture of transcriptome evolution. The isolation of individual cells from tissue sections opens up the opportunity to study gene expression evolution at the cell type level. We have stained neurons and endothelial cells in human brains by antibodies against cell type-specific marker proteins, isolated the cells using laser capture microdissection, and identified genes preferentially expressed in the two cell types. We analyze these two classes of genes with respect to their expression in 62 different human tissues, with respect to their expression in 44 human “postmortem” brains from different developmental stages and with respect to between-species brain expression differences. We find that genes preferentially expressed in neurons differ less across tissues and developmental stages than genes preferentially expressed in endothelial cells. We also observe less expression differences within primate species for neuronal transcriptomes. In stark contrast, we see more gene expression differences between humans, chimpanzees, and rhesus macaques relative to within-species differences in genes expressed preferentially in neurons than in genes expressed in endothelial cells. This suggests that neuronal and endothelial transcriptomes evolve at different rates within brain tissue

Reannotation and consolidation of microarray probes for the meta-analysis of gene expression across multiple cell types

Recent advances in global gene expression measurement and the development of large- scale public repositories for storage of such data have made a wealth of information available to researchers. While one gene expression study may lack sufficient replicates to make statistically significant pronouncements, the combination of studies through meta-analysis can yield results with a much greater likelihood of accuracy. In order to combine multiple sets of data, one must first address the issue of cross-comparison between global gene expression platforms, as well as resolve the issue of repeated measures (multiple probes representing the same gene) within each platform. In this work, I present computational methods for probe reannotation and scoring and for redundant probe consolidation that together allow for greatly improved access to data for meta-analysis. I also present an example of the application of these methods, in the analysis of the gene expression regulated by estrogen across multiple cell types. Estrogen, a steroid hormone, interacts with its receptors to regulate gene transcription in both direct and indirect manners. Estrogen has the effect of increasing proliferation in some tissues, while inhibiting proliferation or increasing apoptosis in others. How estrogen achieves these highly divergent results remains unclear. Through meta-analysis of gene expression experiments across multiple cell types, I show that patterns of estrogen regulation in many tissues involve the same key genes and pathways, including cell cycle, p53 signaling, and TGFβ signaling pathways. However, regulation in different cell types can result from regulation of different genes, or the same genes regulated in different directions. Many patterns of gene regulation support known physiological consequences of estrogen on these tissues. In particular, genes promoting proliferation are upregulated in uterus and certain breast and ovarian cancer cell lines. One gene, thrombospondin-1, is up-regulated in eleven out of nineteen cell types and may be a key player in regulating proliferation in re- sponse to estrogen. Results in other cell types are unexpected. Most notably, neither genes promoting nor inhibiting proliferation are differentially regulated upon estrogen treatment in vascular smooth muscle cells, despite estrogen inhibiting proliferation of these cells

Stem Cells Have Different Needs for REST

REST is a well known repressor of neuronal gene expression. Genome-wide analysis of REST occupancy in different cell types now reveals new and cell-specific roles for REST in embryonic stem cells