scholarly journals Neonatal genetics of gene expression reveal the origins of autoimmune and allergic disease risk

2019 ◽  
Author(s):  
Qin Qin Huang ◽  
Howard H. F. Tang ◽  
Shu Mei Teo ◽  
Scott C. Ritchie ◽  
Artika P. Nath ◽  
...  

AbstractChronic immune-mediated diseases of adulthood often originate in early childhood. To investigate genetic associations between neonatal immunity and disease, we collected cord blood samples from a birth cohort and mapped expression quantitative trait loci (eQTLs) in resting monocytes and CD4+ T cells as well as in response to lipopolysaccharide (LPS) or phytohemagglutinin (PHA) stimulation, respectively. Cis-eQTLs were largely specific to cell type or stimulation, and response eQTLs were identified for 31% of genes with cis-eQTLs (eGenes) in monocytes and 52% of eGenes in CD4+ T cells. We identified trans-eQTLs and mapped cis regulatory factors which act as mediators of trans effects. There was extensive colocalisation of causal variants for cell type- and stimulation-specific neonatal cis-eQTLs and those of autoimmune and allergic diseases, in particular CTSH (Cathepsin H) which showed widespread colocalisation across diseases. Mendelian randomisation showed causal neonatal gene transcription effects on disease risk for BTN3A2, HLA-C and many other genes. Our study elucidates the genetics of gene expression in neonatal conditions and cell types as well as the aetiological origins of autoimmune and allergic diseases.

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3296-3296
Author(s):  
Raul Teruel Montoya ◽  
Xianguo Kong ◽  
Shaji Abraham ◽  
Lin Ma ◽  
Leonard C. Edelstein ◽  
...  

Abstract Abstract 3296 Genetic modification of hematopoietic stem cells (HSCs) has the potential to benefit acquired and congenital hematological disorders. Despite the use of so-called “tissue-specific” promoters to drive expression of the desired transgene, off-target (and consequent deleterious) effects have been observed. MicroRNAs (miRNAs) are important regulators of gene expression. They associate with Argonaute proteins and most typically target 3'UTRs, where complementary base-pairing results in repressed gene expression via RNA decay and translation inhibition. Most miRNAs are ubiquitously expressed, and although some are claimed to be “tissue specific,” such claims have generally not been rigorously validated. The long-term goal of this work is identifying “cell preferential” miRNA expression that could be exploited in expression vectors to minimize off-target transgene expression in HSCs. Initially, total RNA was extracted with Trizol from the megakaryocyte and T-lymphocyte cell lines, Meg-01 and Jurkat, and miRNAs were profiled by Nanostring technology (Nanostring Technologies, Denver, CO). MiR-495 was determined to be highly expressed in Meg-01 and very low in Jurkat cells. A luciferase reporter construct was generated with four canonical binding sites for miR-495 in the 3'UTR and transfected into both cell lines. Compared to control vector without miR-495 binding sites, luciferase expression showed a 50% reduction in Meg-01 cells, but no knock down in Jurkat cells. These experiments indicated that different levels of endogenous miRNA levels can regulate transgene expression through a novel design in the 3'UTR. We next turned our attention to human hematopoietic cells. We reasoned that the long-term goal of minimal off-target transgene expression in HSCs would require knowledge of miRNAs that had little or no detectable expression (“selectively reduced [SR]”) in one cell type and were highly expressed in other cell types. In this manner, the transgene expression would be dampened only in the non-target cells. As a surrogate for bone marrow progenitors and as proof of principle, we used primary cells in normal human peripheral blood. T-cells, B-cells, platelets and granulocytes were purified by density centrifugation followed by immunoselection from five healthy human donors. Flow cytometry using membrane specific markers demonstrate >97% purity of each specific cell preparation. Total RNA was extracted and miRNAs were profiled as above. First, we identified 277 miRNAs that were differentially expressed between any pair of cell types (p-value<0.05 by ANOVA). Second, we performed ranked pair-wise comparisons across all cell types to determine SR miRNAs. This analysis revealed 5 platelet SR-miRNAs, 6 B-cell SR-miRNAs, 2 T-cell SR-miRNAs and 4 granulocyte SR-miRNAs. Lastly, we considered which of these 17 SR-miRNAs would be the best single SR-miRNA within and across cell types. SR-miRNAs were normalized to let-7b, a miRNA we determined to be equivalently expressed across all cell types, and hence, an ideal normalizer. Lineage-specific SR-miRNAs were selected based on extremely low expression in only one cell type and highest fold change of expression compared to the other cell types. The best SR-miRNAs were miR-29b (SR in platelets), miR-125a-5p (SR in B-cells) and miR-146a (SR in granulocytes). The SR expression levels of these 3 miRNAs were validated by qRT-PCR. Our analysis identified no good SR-miRNAs in T-cells. On-going experiments are testing the selective effects of the SR miRNAs in lentiviral vector infection of cord blood CD34+ cells differentiated along specific lineages. In summary, we have demonstrated in hematopoietic cell lines that SR endogenous miRNAs can regulate the expression of transgenes via tandem arrangement of their target sites in the 3'UTR. Additionally, we have identified miRNAs that are specifically expressed at a very low level in one blood cell type and at high levels in other cell types. These miRNAs could potentially be utilized as new biological tools in gene therapy for hematological disorders to restrict transgene expression and avoid the negative consequences of off-target expression. Disclosures: No relevant conflicts of interest to declare.


2021 ◽  
Author(s):  
Julien Bryois ◽  
Daniela Calini ◽  
Will Macnair ◽  
Lynette Foo ◽  
Eduard Urich ◽  
...  

Most expression quantitative trait loci (eQTL) studies to date have been performed in heterogeneous brain tissues as opposed to specific cell types. To investigate the genetics of gene expression in adult human cell types from the central nervous system (CNS), we performed an eQTL analysis using single nuclei RNA-seq from 196 individuals in eight CNS cell types. We identified 6108 eGenes, a substantial fraction (43%, 2620 out of 6108) of which show cell-type specific effects, with strongest effects in microglia. Integration of CNS cell-type eQTLs with GWAS revealed novel relationships between expression and disease risk for neuropsychiatric and neurodegenerative diseases. For most GWAS loci, a single gene colocalized in a single cell type providing new clues into disease etiology. Our findings demonstrate substantial contrast in genetic regulation of gene expression among CNS cell types and reveal genetic mechanisms by which disease risk genes influence neurological disorders.


2020 ◽  
Author(s):  
Masaru Koido ◽  
Chung-Chau Hon ◽  
Satoshi Koyama ◽  
Hideya Kawaji ◽  
Yasuhiro Murakawa ◽  
...  

SUMMARYTranscription is regulated through complex mechanisms involving non-coding RNAs (ncRNAs). However, because transcription of ncRNAs, especially enhancer RNAs, is often low and cell type-specific, its dependency on genotype remains largely unexplored. Here, we developed mutation effect prediction on ncRNA transcription (MENTR), a quantitative machine learning framework reliably connecting genetic associations with expression of ncRNAs, resolved to the level of cell type. MENTR-predicted mutation effects on ncRNA transcription were concordant with estimates from previous genetic studies in a cell type-dependent manner. We inferred reliable causal variants from 41,223 GWAS variants, and proposed 7,775 enhancers and 3,548 long-ncRNAs as complex trait-associated ncRNAs in 348 major human primary cells and tissues, including plausible enhancer-mediated functional alterations in single-variant resolution in Crohn’s disease. In summary, we present new resources for discovering causal variants, the biological mechanisms driving complex traits, and the sequence-dependency of ncRNA regulation in relevant cell types.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Guillermo Palou-Márquez ◽  
Isaac Subirana ◽  
Lara Nonell ◽  
Alba Fernández-Sanlés ◽  
Roberto Elosua

Abstract Background The integration of different layers of omics information is an opportunity to tackle the complexity of cardiovascular diseases (CVD) and to identify new predictive biomarkers and potential therapeutic targets. Our aim was to integrate DNA methylation and gene expression data in an effort to identify biomarkers related to cardiovascular disease risk in a community-based population. We accessed data from the Framingham Offspring Study, a cohort study with data on DNA methylation (Infinium HumanMethylation450 BeadChip; Illumina) and gene expression (Human Exon 1.0 ST Array; Affymetrix). Using the MOFA2 R package, we integrated these data to identify biomarkers related to the risk of presenting a cardiovascular event. Results Four independent latent factors (9, 19, 21—only in women—and 27), driven by DNA methylation, were associated with cardiovascular disease independently of classical risk factors and cell-type counts. In a sensitivity analysis, we also identified factor 21 as associated with CVD in women. Factors 9, 21 and 27 were also associated with coronary heart disease risk. Moreover, in a replication effort in an independent study three of the genes included in factor 27 were also present in a factor identified to be associated with myocardial infarction (CDC42BPB, MAN2A2 and RPTOR). Factor 9 was related to age and cell-type proportions; factor 19 was related to age and B cells count; factor 21 pointed to human immunodeficiency virus infection-related pathways and inflammation; and factor 27 was related to lifestyle factors such as alcohol consumption, smoking and body mass index. Inclusion of factor 21 (only in women) improved the discriminative and reclassification capacity of the Framingham classical risk function and factor 27 improved its discrimination. Conclusions Unsupervised multi-omics data integration methods have the potential to provide insights into the pathogenesis of cardiovascular diseases. We identified four independent factors (one only in women) pointing to inflammation, endothelium homeostasis, visceral fat, cardiac remodeling and lifestyles as key players in the determination of cardiovascular risk. Moreover, two of these factors improved the predictive capacity of a classical risk function.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
John A. Halsall ◽  
Simon Andrews ◽  
Felix Krueger ◽  
Charlotte E. Rutledge ◽  
Gabriella Ficz ◽  
...  

AbstractChromatin configuration influences gene expression in eukaryotes at multiple levels, from individual nucleosomes to chromatin domains several Mb long. Post-translational modifications (PTM) of core histones seem to be involved in chromatin structural transitions, but how remains unclear. To explore this, we used ChIP-seq and two cell types, HeLa and lymphoblastoid (LCL), to define how changes in chromatin packaging through the cell cycle influence the distributions of three transcription-associated histone modifications, H3K9ac, H3K4me3 and H3K27me3. We show that chromosome regions (bands) of 10–50 Mb, detectable by immunofluorescence microscopy of metaphase (M) chromosomes, are also present in G1 and G2. They comprise 1–5 Mb sub-bands that differ between HeLa and LCL but remain consistent through the cell cycle. The same sub-bands are defined by H3K9ac and H3K4me3, while H3K27me3 spreads more widely. We found little change between cell cycle phases, whether compared by 5 Kb rolling windows or when analysis was restricted to functional elements such as transcription start sites and topologically associating domains. Only a small number of genes showed cell-cycle related changes: at genes encoding proteins involved in mitosis, H3K9 became highly acetylated in G2M, possibly because of ongoing transcription. In conclusion, modified histone isoforms H3K9ac, H3K4me3 and H3K27me3 exhibit a characteristic genomic distribution at resolutions of 1 Mb and below that differs between HeLa and lymphoblastoid cells but remains remarkably consistent through the cell cycle. We suggest that this cell-type-specific chromosomal bar-code is part of a homeostatic mechanism by which cells retain their characteristic gene expression patterns, and hence their identity, through multiple mitoses.


1985 ◽  
Vol 5 (2) ◽  
pp. 419-421
Author(s):  
K M Zezulak ◽  
H Green

During the differentiation of preadipose 3T3 cells into adipose cells, the mRNAs for three proteins increase strikingly in abundance. To determine the degree of cell-type specificity in the expression of these mRNAs, we estimated their abundances in several nonadipose tissues of the mouse. None of these mRNAs was strictly confined to adipocytes, but the ensemble of three mRNAs was rather specific to adipocytes. Insofar as is revealed by these three markers, the distinctive phenotype of adipocytes is the result of the enhanced expression of a number of genes, none of which is completely silent in all other cell types.


eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Sinisa Hrvatin ◽  
Christopher P Tzeng ◽  
M Aurel Nagy ◽  
Hume Stroud ◽  
Charalampia Koutsioumpa ◽  
...  

Enhancers are the primary DNA regulatory elements that confer cell type specificity of gene expression. Recent studies characterizing individual enhancers have revealed their potential to direct heterologous gene expression in a highly cell-type-specific manner. However, it has not yet been possible to systematically identify and test the function of enhancers for each of the many cell types in an organism. We have developed PESCA, a scalable and generalizable method that leverages ATAC- and single-cell RNA-sequencing protocols, to characterize cell-type-specific enhancers that should enable genetic access and perturbation of gene function across mammalian cell types. Focusing on the highly heterogeneous mammalian cerebral cortex, we apply PESCA to find enhancers and generate viral reagents capable of accessing and manipulating a subset of somatostatin-expressing cortical interneurons with high specificity. This study demonstrates the utility of this platform for developing new cell-type-specific viral reagents, with significant implications for both basic and translational research.


2019 ◽  
Author(s):  
Jing Yang ◽  
Amanda McGovern ◽  
Paul Martin ◽  
Kate Duffus ◽  
Xiangyu Ge ◽  
...  

AbstractGenome-wide association studies have identified genetic variation contributing to complex disease risk. However, assigning causal genes and mechanisms has been more challenging because disease-associated variants are often found in distal regulatory regions with cell-type specific behaviours. Here, we collect ATAC-seq, Hi-C, Capture Hi-C and nuclear RNA-seq data in stimulated CD4+ T-cells over 24 hours, to identify functional enhancers regulating gene expression. We characterise changes in DNA interaction and activity dynamics that correlate with changes gene expression, and find that the strongest correlations are observed within 200 kb of promoters. Using rheumatoid arthritis as an example of T-cell mediated disease, we demonstrate interactions of expression quantitative trait loci with target genes, and confirm assigned genes or show complex interactions for 20% of disease associated loci, including FOXO1, which we confirm using CRISPR/Cas9.


2012 ◽  
Vol 93 (5) ◽  
pp. 1046-1058 ◽  
Author(s):  
James C. Towler ◽  
Bahram Ebrahimi ◽  
Brian Lane ◽  
Andrew J. Davison ◽  
Derrick J. Dargan

Broad cell tropism contributes to the pathogenesis of human cytomegalovirus (HCMV), but the extent to which cell type influences HCMV gene expression is unclear. A bespoke HCMV DNA microarray was used to monitor the transcriptome activity of the low passage Merlin strain of HCMV at 12, 24, 48 and 72 h post-infection, during a single round of replication in human fetal foreskin fibroblast cells (HFFF-2s), human retinal pigmented epithelial cells (RPE-1s) and human astrocytoma cells (U373MGs). In order to correlate transcriptome activity with concurrent biological responses, viral cytopathic effect, growth kinetics and genomic loads were examined in the three cell types. The temporal expression pattern of viral genes was broadly similar in HFFF-2s and RPE-1s, but dramatically different in U373MGs. Of the 165 known HCMV protein-coding genes, 41 and 48 were differentially regulated in RPE-1s and U373MGs, respectively, compared with HFFF-2s, and 22 of these were differentially regulated in both RPE-1s and U373MGs. In RPE-1s, all differentially regulated genes were downregulated, but, in U373MGs, some were down- and others upregulated. Differentially regulated genes were identified among the immediate-early, early, early late and true-late viral gene classes. Grouping of downregulated genes according to function at landmark stages of the replication cycle led to the identification of potential bottleneck stages (genome replication, virion assembly, and virion maturation and release) that may account for cell type-dependent viral growth kinetics. The possibility that cell type-specific differences in expressed cellular factors are responsible for modulation of viral gene expression is discussed.


2022 ◽  
Author(s):  
Takaho Tsuchiya ◽  
Hiroki Hori ◽  
Haruka Ozaki

Motivation: Cell-cell communications regulate internal cellular states of the cell, e.g., gene expression and cell functions, and play pivotal roles in normal development and disease states. Furthermore, single-cell RNA sequencing methods have revealed cell-to-cell expression variability of highly variable genes (HVGs), which is also crucial. Nevertheless, the regulation on cell-to-cell expression variability of HVGs via cell-cell communications is still unexplored. The recent advent of spatial transcriptome measurement methods has linked gene expression profiles to the spatial context of single cells, which has provided opportunities to reveal those regulations. The existing computational methods extract genes with expression levels that are influenced by neighboring cell types based on the spatial transcriptome data. However, limitations remain in the quantitativeness and interpretability: it neither focuses on HVGs, considers cooperation of neighboring cell types, nor quantifies the degree of regulation with each neighboring cell type. Results: Here, we propose CCPLS (Cell-Cell communications analysis by Partial Least Square regression modeling), which is a statistical framework for identifying cell-cell communications as the effects of multiple neighboring cell types on cell-to-cell expression variability of HVGs, based on the spatial transcriptome data. For each cell type, CCPLS performs PLS regression modeling and reports coefficients as the quantitative index of the cell-cell communications. Evaluation using simulated data showed our method accurately estimated effects of multiple neighboring cell types on HVGs. Furthermore, by applying CCPLS to the two real datasets, we demonstrate CCPLS can be used to extract biologically interpretable insights from the inferred cell-cell communications.


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