Integrated Genome-Wide CTCF and CohesinSA1 Occupancy and Expression Analyses in Erythropoiesis

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 1305-1305
Author(s):  
Vincent P Schulz ◽  
Laurie A. Steiner ◽  
Yelena Maksimova ◽  
Patrick G. Gallagher

Abstract Abstract 1305 CTCF and cohesion are critical regulators of cellular growth, development and differentiation. CTCF has multiple functions including acting at gene promoters as a transcriptional activator or repressor, mediating long-range chromatin interactions, and acting as a chromatin insulator element. The cohesin complex is also multifunctional, participating in chromosome segregation during cell division, facilitating DNA-promoter interactions through cell-type specific DNA-looping, participating in DNA repair, and participating with CTCF in enhancer blocking. The cohesin complex is composed of 4 proteins Smc1, Smc3, Scc1, and either SA1 or SA2. The presence of SA1 or SA2 is mutually excusive, leading to 2 related, but distinct complexes, cohesinSA1 and cohesin.SA2. The SA1 component of the complex directly interacts with CTCF. To gain insight into how CTCF and cohesin regulate genes in erythroid development, chromatin immunoprecipitation coupled with high throughput sequencing (ChIP-seq) and mRNA transcriptome analyses were performed in human CD34+ hematopoietic stem and progenitor cells and cultured primary human erythroid (R3/R4 stage) cells, the results combined, and the interactomes compared. The MACS program identified 26,330 sites of CTCF and 23,396 sites of cohesinSA1 occupancy in CD34+ and 39,782 sites of CTCF and 33,497 sites of cohesinSA1 occupancy in erythroid cell chromatin (p<10e-5, fold enrichment>5). In CD34+ cells, the majority of CTCF and cohesinSA1 binding sites were located in intergenic regions (56 and 57%,) and introns (33 and 34%). In contrast, in erythroid cells, CTCF and cohesinSA1 binding had migrated to gene promoters (16% vs 2% and 24% vs 2%, respectively) with less binding in intergenic regions and introns. Sites of binding in erythroid cells were similar to that observed in fibroblasts, another differentiated cell-type. CTCF has sites of both cell-type specific and cell-type invariant binding. The Galaxy tool was utilized to compare sites of CTCF occupancy in 7 additional cell types. In CD34+ cells, only 5% sites of CTCF binding were CD34+ cell-type specific. In erythroid cells, 36% of CTCF binding sites were erythroid-specific. These unique sites were located primarily in enhancers and introns and were rarely seen in promoters. Refseq genes within 3kb of erythroid cell-specific CTCF sites were highly significantly enriched for the following GO terms: induction of apoptosis by extracellular signals, cytoskeleton organization, cellular response to stress, and macromolecule catabolic process. In both cell types, RefSeq genes within 3kb of an invariant CTCF site were consistently expressed at lower levels c.f. genes within 3kb of CD34+- or erythroid cell-specific CTCF sites. Analyzing CTCF-cohesinSA1 co-occupancy, there were 17,755 sites of CTCF and cohesinSA1 co-occupancy in CD34+ cells, accounting for 75% of CTCF sites and 67% of cohesinSA1 sites. In erythroid cells, 19,933 sites of occupancy were shared between CTCF and cohesinSA1, representing 50% of CTCF sites and 60% of cohesinSA1 sites. Finally, it has been suggested that CTCF marks chromatin domains in a cell-type specific manner. To determine whether CTCF and cohesinSA1 are present at domain boundaries in erythropoiesis, ChIP-seq for H3K27me3, a repressive chromatin mark, was performed. Chromatin domains were predicted using the Rseg program. 9,480 and 18,511 H3K27me3 chromatin domains were identified in CD34+ and erythroid cells, respectively, with average domain lengths of 31kb in CD34+ and 28kb in erythroid cells. There were 692 and 2,096 CTCF sites that marked domain boundaries in CD34+ and erythroid cells, respectively. These CTCF sites were cell-type specific, as only 75 of these CTCF sites were shared between CD34+ and erythroid cells. In both cell types, the majority of CTCF sites marking domain boundaries were found in distal intergenic regions and introns. CohesinSA1 was also frequently found at domain boundaries, present at 566 and 1830 domain boundaries in CD34+ and erythroid cells, respectively. Co-localization of CTCF with cohesinSA1 at domain boundaries was also common, with 66% of CTCF sites and 58% of CTCF sites binding both CTCF and cohesionSA1 in CD34+ and erythroid cells, respectively. These data indicate that CTCF and cohesin have multiple roles in regulating gene expression in erythropoiesis. Disclosures: No relevant conflicts of interest to declare.

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 2083-2083
Author(s):  
Nathaniel James Pope ◽  
Emery H Bresnick

Abstract Abstract 2083 The constant physiological demand to generate large numbers of red blood cells requires a complex genetic network established by the master regulatory transcription factor GATA-1, which orchestrates erythroblast survival, proliferation, and differentiation. Many questions remain regarding how GATA-1 instigates genetic networks and to what extent GATA-1-independent mechanisms regulate erythropoiesis. Med1, a component of the broadly expressed Mediator complex (Mediator), facilitates GATA-1-dependent transcriptional activation at select target genes, although its contribution to GATA-1 function in cell-based assays is considerably less than that of the cell type-specific coregulator Friend of GATA-1. Med1-nullizygous mice have hematopoietic, cardiac, and vascular defects, though the underlying mechanisms are not defined. Furthermore, whether Med1 coactivator activity is dedicated to GATA-1 in erythroid cells and whether it controls numerous or a restricted cohort of genes is also unclear. Using a genetic complementation assay in GATA-1-null erythroid cells and a functional genomics approach, we demonstrate that Med1 regulates a restricted gene ensemble in erythroid cells, consisting predominantly of genes not controlled by GATA-1. Of the 265 Med1-regulated genes and 1054 GATA-1-regulated genes, only 35 genes were regulated by Med1 and GATA-1. Given the preponderance of GATA-1-independent Med1 targets, it is attractive to propose that Med1 has important GATA-1-independent functions required to exert its crucial hematopoietic activities. Since Med1 is a Mediator subunit, it is presumed to function through Mediator to regulate target genes. However, Med1 interacts with various trans-acting factors, and therefore its gene regulatory activity may not invariably rely on Mediator or a Mediator subcomplex. As Mediator is largely unstudied in erythroid cells, we asked whether Mediator subunit expression is regulated upon primary human erythroid cell maturation ex vivo. Mining the Human Erythroblast Maturation Database revealed that Med25 is strongly up-regulated during maturation. Knockdown of Med25 significantly dysregulated all ten of the highest responding Med1 target genes. Simultaneous knockdowns of Med1 and Med25 altered expression of 9 of the 10 top Med1 target genes, resembling the individual factor knockdowns. These results support the hypothesis that Med1 and Med25 function in the erythroid Mediator complex to regulate these genes. Med1 regulated these genes in a cell type-specific manner, as 8 of the 10 top Med1 targets in G1E-ER-GATA-1 proerythroblast-like cells and Mouse Erythroleukemia Cells were not dysregulated upon Med1 knockdown in Mouse Embryonic Fibroblasts. As Med1 modulated, but was not essential for, GATA-1-dependent transcription, we reasoned that certain Med1 target genes may exert GATA-1-independent activities to control erythroid cell development and/or function. The Med1 target gene Rrad encodes a small GTPase induced during primary human erythroid cell maturation, but its regulation/function has not been described in the hematopoietic system. Loss-of-function analysis in G1E-ER-GATA-1 cells indicated that Rrad confers survival. Knocking-down Rrad increased early apoptosis 2.5 fold (p < 0.05). The Rrad requirement for survival was more pronounced when cells were deprived of Erythropoietin (Epo) and Stem Cell Factor (SCF). In cells cultured without Epo, early apoptosis increased 7.0 fold upon Rrad knockdown [from 1.0% ± 0.1% to 7.2% ± 0.5% (p < 0.05)]. Removing SCF from the media significantly increased apoptotic cells, and Rrad knockdown elevated this further from 28% ± 2.4% to 46% ± 2.8% (p < 0.01), while the number of live cells decreased 4.7 fold (p < 0.01). These studies established a dual role for Mediator in erythroid cell regulation as a context-dependent GATA-1 coregulator and a GATA-1-independent regulator of cell type-specific genes, including potentially critical regulators of erythroid cell development, survival, and function. Mechanistically, given the greater than twenty components of the canonical Mediator, it will be particularly instructive to compare our findings to that of other key Mediator components, which shall yield a comprehensive understanding of their regulation and function during the progressive transitions from erythroid precursors to the erythrocyte. Disclosures: No relevant conflicts of interest to declare.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 1200-1200
Author(s):  
Vincent P Schulz ◽  
Kimberly Lezon-Geyda ◽  
Yelena Maksimova ◽  
Patrick G Gallagher

Abstract Identification of cell-type specific enhancers is important for understanding the regulation of programs controlling cellular development and differentiation. Recent studies have shown that enhancers are frequently associated with biologically relevant and disease-associated genetic variants. We hypothesized that unique sets of enhancers and super enhancers regulate gene expression in erythroid cells, a specialized cell type evolved to carry oxygen, and associated variants influence erythroid phenotypic variability. Active enhancers are part of a chromatin landscape marked by histone H3 lysine 4 monomethylation (H3K4me1) and histone H3 lysine 27 acetylation (H3K27Ac). A subset of enhancers, called super enhancers, important for regulating genes critical for cell-type specific identify, have been described. Super enhancers span large regions of chromatin, have domains of transcription factors (TF), significant amounts of H3K4me1 and H3K27Ac modification, and significant amounts of Mediator (MED1) occupancy, frequently with the transcriptional activator BRD4. Using ChIP-seq, genome wide maps of enhancers were constructed for H3K4me1, H3K27Ac, MED1, and BRD4 using primary human erythroid cell chromatin. These data were combined with parallel gene expression analyses determined via RNA-seq and enhancers and super enhancers identified. Cell and tissue-type specific enhancers act over distances of tens to hundreds of kilobases, thus bona fide erythroid enhancers are expected to be enriched in the genomic vicinity of genes expressed and functional in erythroid cells. Sites of occupancy of H3K4me1 were correlated with levels of gene expression in erythroid cells. To exclude gene promoters, H3K4me1 within 1kb of annotated transcriptional start sites (TSS) were excluded from analyses. Consistent with their predicted function, there was significantly higher levels of erythroid transcription for genes with H3K4me1 occupancy within 1-50kb of the TSS of genes cf. genes with H3K4me1 occupancy >50kb of a TSS (p value<2.2e-16). There was also significantly higher expression of genes with H3K4me1 occupancy within 1-50kb of the TSS in erythroid cells cf. non-erythroid cells (T lymphocyte). The top over represented TF motifs at sites of H3K4me1 were GATA1, AP1/NFE2, and KLF1. To explore whether candidate erythroid enhancers are enriched in regions associated with biologically relevant erythroid cell traits, candidate enhancers were mapped to a data set of erythroid-associated SNPs from the NHGRI GWAS catalog. 32 enhancers mapped to sites previously associated with biologically relevant erythroid traits. SNPs changed TF binding motifs at numerous enhancers including GATA1 motifs in the BCL11A, TFRC and ATP24 loci, an NFE2 motif in the ATP2B4 locus, and a TAL1 motif in the BCL11A locus. Super enhancers were identified as described (Cell 153:307, 2013) by finding regions with the highest levels of clustered chromatin modification/occupancy. Super enhancers defined by H3K4me1 and H3K27Ac modifications yielded 231 regions, BRD4 occupancy yielded 166 regions, and MED1 occupancy yielded 52 regions. H3K4me1/H3K27Ac-marked SE regions were found near the FOXO3, GATA2, STAT5A, TAL1, and ZFPM1 gene loci. BRD4- and MED1-marked super enhancers were found near the critical erythroid volume regulatory gene PIEZO1. The top over represented TF motifs at super enhancer sites defined by H3K4me1 were TAL1/RUNX1, GATA1, KLF1, defined by BRD4 were TAL1, KLF1, and MYC, and defined by MED1 were GATA1, MYC and CTCF. Mapping of super enhancers to erythroid-associated SNPs from the GWAS catalog of the NHGRI revealed many super enhancers mapped to regions associated with biologically relevant erythroid cell traits. For example, super enhancers identified by H3K4me1 mapped to loci for BCL11A, TFRC, KIT, HBS1L, MYB, ANK1, HK1, and the alpha-globin gene cluster; super enhancers identified by BRD4 localized to the alpha-globin cluster and the PIEZO1 gene locus. Perturbation of enhancer function during erythroid development and differentiation may lead to dysregulation of gene expression with concomitant phenotypic consequences. Insights into regulation of programs of gene expression in obtained from study of erythroid enhancers will provide insights into the functional significance of sequence variation associated with quantitative traits and inherited and acquired hematologic disease. Disclosures: No relevant conflicts of interest to declare.


Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 368-368
Author(s):  
Mack Su ◽  
Laurie A Steiner ◽  
Hannah Bogardus ◽  
Vincent P Schulz ◽  
Ross C Hardison ◽  
...  

Abstract Abstract 368 Identification of cell-type specific enhancers is important for understanding the regulation of programs controlling cellular development and differentiation. Recent studies utilizing genomic methodologies have shown that enhancers are frequently associated with biologically relevant and disease-associated genetic variants. Enhancers are typically marked by the co-transcriptional activator protein p300 or by groups of cell-expressed transcription factors. We hypothesized that a unique set of enhancers regulate gene expression in human erythroid cells, a highly specialized cell type evolved to provide adequate amounts of oxygen throughout the body. Using chromatin immunoprecipitation followed by massively parallel sequencing, genome-wide maps of candidate enhancers were constructed for p300 and four transcription factors, GATA1, NF-E2, KLF1, and SCL, in primary human erythroid cells. These data were combined with parallel gene expression analyses and candidate enhancers identified. Cell and tissue-type specific enhancers act over distances of tens to hundreds of kilobases, thus bona fide erythroid enhancers are expected to be enriched in the genomic vicinity of genes expressed and functional in erythroid cells. Sites of occupancy were correlated with levels of gene expression. Promoter sites within 2kb of annotated transcriptional start sites (TSS) were excluded. Consistent with their predicted function, there was significant enrichment of p300 peaks within 2–50kb of the TSS of genes highly expressed in erythroid cells c.f. peaks >100kb of a TSS. There was also significant enrichment of combinations of 2, 3, and 4 co-localizing erythroid transcription factor peaks within 2–50kb of the TSS of genes highly expressed in erythroid cells. In contrast, similar to other cell type-specific enhancers, there was no enrichment of p300 or erythroid transcription factor sites within 2–50kb of genes highly expressed in nonerythroid cells. When analyses were performed comparing a set of erythroid-specific genes vs. a random set of genes, there was significant enrichment of combinations of 2, 3, and 4 co-localizing erythroid transcription factor binding sites, but not p300, within 2–50kb of the TSS of erythroid-specific genes. Evolutionary analyses revealed high conservation between man and chimp for p300 and erythroid transcription factors. However, there was a very large falloff between human and mouse, with. Disclosures: No relevant conflicts of interest to declare.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 963-963
Author(s):  
Yannis Hara ◽  
Mark Stottlemyer ◽  
Kim Alving ◽  
Nis Halland ◽  
Alexandra Hicks ◽  
...  

Abstract Introduction: Novel and safe therapeutic targets to increase expression of fetal hemoglobin (HbF) have potential to treat b-hemoglobinopathies (Platt, Brambilla et al. 1994, Steinberg 2020), including sickle cell disease (SCD) in which red blood cell (RBC) hemoglobin S resulting from a mutation in the hemoglobin β-globin subunit causes RBC sickling and hemolysis triggering vascular inflammation (Piel, Steinberg et al. 2017, Kato, Piel et al. 2018). Serum- and glucocorticoid-regulated kinase 1 (SGK1) is a serine/threonine kinase in the AGK kinase family that controls physiological processes such as cell growth, proliferation, migration, and apoptosis (Hayashi, Tapping et al. 2001, Sang, Kong et al. 2020). SGK1 is regulated by multiple ligands (insulin, cAMP, IGF-1, steroids, IL-2 and TGF-β) and phosphorylation by SGK1 modulates the activity of downstream effectors including ion channels (ENaC), Na-Cl cotransporters (NCC), membrane transporters, cellular enzymes (GSK3B) and transcription factors (FOXO3a, β-catenin, NF-κB and SP1) (Brunet, Park et al. 2001, Snyder, Olson et al. 2002, Loffing, Flores et al. 2006, Bruhn, Pearson et al. 2010, Boccitto and Kalb 2011, Wang, Hu et al. 2017). Previous studies show that SGK1 mediates survival signals in HEK cells by inhibiting FOXO3a through phosphorylation at Ser-315 (Brunet, Park et al. 2001). Recently, metformin was shown to induce HbF in erythroid cells through FOXO3a activation and metformin prevents RBC sickling in SCD (Zhang, Paikari et al. 2018). Thus, we hypothesized that inhibition of SGK1 and subsequent alleviation of SGK1-induced FOXO3a inhibition, may induce expression of erythroid cell HbF. Methods: We studied the ability of SGK1 to inhibit HbF induction in erythroid cells by culturing CD34+ hematopoietic progenitor stem cells from both healthy and SCD blood donors using a 21-day differentiation protocol. After confirming expression of SGK1 in CD34+ cells by Western blot, SGK1 activity was inhibited using the selective and potent SGK1 inhibitor RA04075215A (Halland, Schmidt et al. 2015). SGK1 is activated by phosphorylation at Thr256 and we confirmed target engagement through measurement of Thr256 phosphorylation on Western blots. To decipher the effect of SGK1 inhibition on the SGK1 downstream pathway, we assessed the inhibition of FOXO3a triggered by SGK1 through evaluation of FOXO3a phosphorylation Ser315. In parallel, we quantified HbF gene transcripts by qPCR, determined the level of HbF protein by Western blot, and quantified F-cells by flow cytometry. Finally, to evaluate the effect of SGK1 inhibition on RBC sickling, we performed a cell sickling assay upon completion of erythroid differentiation in culture. Fully differentiated CD34+ cells from SCD blood donors were incubated under in hypoxia (2% O 2) for 4 hours and then abnormal shaped cells were analyzed using the Amnis® ImageStream® flow cytometer. Results: By day 21 of differentiation, HbF protein expression in CD34+ cells increases significantly in RA04075215A-treated cells versus untreated controls. In addition, a combination of SGK1 inhibition and hydroxyurea treatment reveals a potential synergistic induction of HbF. Western blot analysis shows a decrease in phospho-SGK1 phosphorylated at Thr-256 with SGK1 inhibition, confirming target engagement and loss of SGK1 activity. Downstream of SGK1, phospho-FOXO3a phosphorylated at Ser-315 was also decreased significantly following SGK1 inhibition, demonstrating alleviation of FOXO3a inhibition. Finally, in the RBC sickling assay, RA04075215A-treated cells were significantly protected from sickling under hypoxia compared to controls. Conclusion: In summary, this study establishes SGK1 as a potential new therapeutic target in SCD. We demonstrate that SGK1 inhibition induces HbF in CD34+ cells through FOXO3a transcription factor activation and prevents CD34+ cells from sickling. In the future, in vivo studies are necessary to confirm the role of SGK1 in HbF induction and to assess the efficacy of SGK1 inhibition in improving markers of SCD. Disclosures No relevant conflicts of interest to declare.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Houri Hintiryan ◽  
Ian Bowman ◽  
David L. Johnson ◽  
Laura Korobkova ◽  
Muye Zhu ◽  
...  

AbstractThe basolateral amygdalar complex (BLA) is implicated in behaviors ranging from fear acquisition to addiction. Optogenetic methods have enabled the association of circuit-specific functions to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. Here, we apply machine-learning based computational and informatics analysis techniques to the results of circuit-tracing experiments to create a foundational, comprehensive BLA connectivity map. The analyses identify three distinct domains within the anterior BLA (BLAa) that house target-specific projection neurons with distinguishable morphological features. We identify brain-wide targets of projection neurons in the three BLAa domains, as well as in the posterior BLA, ventral BLA, posterior basomedial, and lateral amygdalar nuclei. Inputs to each nucleus also are identified via retrograde tracing. The data suggests that connectionally unique, domain-specific BLAa neurons are associated with distinct behavior networks.


Author(s):  
Hee-Dae Kim ◽  
Jing Wei ◽  
Tanessa Call ◽  
Nicole Teru Quintus ◽  
Alexander J. Summers ◽  
...  

AbstractDepression is the leading cause of disability and produces enormous health and economic burdens. Current treatment approaches for depression are largely ineffective and leave more than 50% of patients symptomatic, mainly because of non-selective and broad action of antidepressants. Thus, there is an urgent need to design and develop novel therapeutics to treat depression. Given the heterogeneity and complexity of the brain, identification of molecular mechanisms within specific cell-types responsible for producing depression-like behaviors will advance development of therapies. In the reward circuitry, the nucleus accumbens (NAc) is a key brain region of depression pathophysiology, possibly based on differential activity of D1- or D2- medium spiny neurons (MSNs). Here we report a circuit- and cell-type specific molecular target for depression, Shisa6, recently defined as an AMPAR component, which is increased only in D1-MSNs in the NAc of susceptible mice. Using the Ribotag approach, we dissected the transcriptional profile of D1- and D2-MSNs by RNA sequencing following a mouse model of depression, chronic social defeat stress (CSDS). Bioinformatic analyses identified cell-type specific genes that may contribute to the pathogenesis of depression, including Shisa6. We found selective optogenetic activation of the ventral tegmental area (VTA) to NAc circuit increases Shisa6 expression in D1-MSNs. Shisa6 is specifically located in excitatory synapses of D1-MSNs and increases excitability of neurons, which promotes anxiety- and depression-like behaviors in mice. Cell-type and circuit-specific action of Shisa6, which directly modulates excitatory synapses that convey aversive information, identifies the protein as a potential rapid-antidepressant target for aberrant circuit function in depression.


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.


2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jinting Guan ◽  
Yiping Lin ◽  
Yang Wang ◽  
Junchao Gao ◽  
Guoli Ji

Abstract Background Genome-wide association studies have identified genetic variants associated with the risk of brain-related diseases, such as neurological and psychiatric disorders, while the causal variants and the specific vulnerable cell types are often needed to be studied. Many disease-associated genes are expressed in multiple cell types of human brains, while the pathologic variants affect primarily specific cell types. We hypothesize a model in which what determines the manifestation of a disease in a cell type is the presence of disease module comprised of disease-associated genes, instead of individual genes. Therefore, it is essential to identify the presence/absence of disease gene modules in cells. Methods To characterize the cell type-specificity of brain-related diseases, we construct human brain cell type-specific gene interaction networks integrating human brain nucleus gene expression data with a referenced tissue-specific gene interaction network. Then from the cell type-specific gene interaction networks, we identify significant cell type-specific disease gene modules by performing statistical tests. Results Between neurons and glia cells, the constructed cell type-specific gene networks and their gene functions are distinct. Then we identify cell type-specific disease gene modules associated with autism spectrum disorder and find that different gene modules are formed and distinct gene functions may be dysregulated in different cells. We also study the similarity and dissimilarity in cell type-specific disease gene modules among autism spectrum disorder, schizophrenia and bipolar disorder. The functions of neurons-specific disease gene modules are associated with synapse for all three diseases, while those in glia cells are different. To facilitate the use of our method, we develop an R package, CtsDGM, for the identification of cell type-specific disease gene modules. Conclusions The results support our hypothesis that a disease manifests itself in a cell type through forming a statistically significant disease gene module. The identification of cell type-specific disease gene modules can promote the development of more targeted biomarkers and treatments for the disease. Our method can be applied for depicting the cell type heterogeneity of a given disease, and also for studying the similarity and dissimilarity between different disorders, providing new insights into the molecular mechanisms underlying the pathogenesis and progression of diseases.


1989 ◽  
Vol 92 (2) ◽  
pp. 231-239
Author(s):  
P.I. Francz ◽  
K. Bayreuther ◽  
H.P. Rodemann

Methods for the selective enrichment of various subpopulations of the human skin fibroblast cell line HH-8 have been developed. These methods permit the selection of homogeneous populations of the three mitotic fibroblast cell types MF I, II and III, and the four postmitotic cell types PMF IV, V, VI and VII. These seven cell types exhibit differentiation-dependent and cell-type-specific patterns of [35S]methionine-labelled polypeptides in total soluble cytoplasmic and nuclear proteins, also in membrane-bound proteins, and in secreted proteins. In the differentiation sequence MF II-MF III-PMF IV - PMF V - PMF VI 14 cell-type-specific marker proteins have been found in the cytoplasmic and nuclear fraction, also 24 cell-type-specific marker proteins have been found in the membrane-bound protein fraction, and 11 cell-type-specific marker proteins in the secreted protein fraction. Markers in spontaneously arising and experimentally selected or induced populations of a single fibroblast cell type were found to be identical.


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.


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