Dataset Information

Identification of CTCF as a master regulator of the clustered protocadherin genes.

ABSTRACT: The brain is a large and complex network of neurons. Specific neuronal connectivity is thought to be based on the combinatorial expression of the 52 protocadherins (Pcdh) membrane adhesion proteins, whereby each neuron expresses only a specific subset. Pcdh genes are arranged in tandem, in a cluster of three families: Pcdh?, Pcdh? and Pcdh?. The expression of each Pcdh gene is regulated by a promoter that has a regulatory conserved sequence element (CSE), common to all 52 genes. The mechanism and factors controlling individual Pcdh gene expression are currently unknown. Here we show that the promoter of each Pcdh gene contains a gene-specific conserved control region, termed specific sequence element (SSE), located adjacent and upstream to the CSE and activates transcription together with the CSE. We purified the complex that specifically binds the SSE-CSE region and identified the CCTC binding-factor (CTCF) as a key molecule that binds and activates Pcdh promoters. Our findings point to CTCF as a factor essential for Pcdh expression and probably governing neuronal connectivity.

SUBMITTER: Golan-Mashiach M

PROVIDER: S-EPMC3333863 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of CTCF as a master regulator of the clustered protocadherin genes.

Golan-Mashiach Michal M Grunspan Moshe M Emmanuel Rafi R Gibbs-Bar Liron L Dikstein Rivka R Shapiro Ehud E

Nucleic acids research 20111230 8

The brain is a large and complex network of neurons. Specific neuronal connectivity is thought to be based on the combinatorial expression of the 52 protocadherins (Pcdh) membrane adhesion proteins, whereby each neuron expresses only a specific subset. Pcdh genes are arranged in tandem, in a cluster of three families: Pcdhα, Pcdhβ and Pcdhγ. The expression of each Pcdh gene is regulated by a promoter that has a regulatory conserved sequence element (CSE), common to all 52 genes. The mechanism an ...[more]

PMID: 22210889

Similar Datasets

Project description:Analytic approaches confined to fold-change comparisons of gene expression patterns between states of health and disease are unable to distinguish between primary causal disease drivers and secondary noncausal events. Genome-wide reverse engineering approaches can facilitate the identification of candidate genes that may distinguish between causal and associative interactions and may account for the emergence or maintenance of pathologic phenotypes. In this work, we used the algorithm for the reconstruction of accurate cellular networks (ARACNE) to analyze a large gene expression profile data set (313 gingival tissue samples from a cross-sectional study of 120 periodontitis patients) obtained from clinically healthy (n = 70) or periodontitis-affected (n = 243) gingival sites. The generated transcriptional regulatory network of the gingival interactome was subsequently interrogated with the master regulator inference algorithm (MARINA) and gene expression signature data from healthy and periodontitis-affected gingiva. Our analyses identified 41 consensus master regulator genes (MRs), the regulons of which comprised between 25 and 833 genes. Regulons of 7 MRs (HCLS1, ZNF823, XBP1, ZNF750, RORA, TFAP2C, and ZNF57) included >500 genes each. Gene set enrichment analysis indicated differential expression of these regulons in gingival health versus disease with a type 1 error between 2% and 0.5% and with >80% of the regulon genes in the leading edge. Ingenuity pathway analysis showed significant enrichment of 36 regulons for several pathways, while 6 regulons (those of MRs HCLS1, IKZF3, ETS1, NHLH2, POU2F2, and VAV1) were enriched for >10 pathways. Pathways related to immune system signaling and development were the ones most frequently enriched across all regulons. The unbiased analysis of genome-wide regulatory networks can enhance our understanding of the pathobiology of human periodontitis and, after appropriate validation, ultimately identify target molecules of diagnostic, prognostic, or therapeutic value.

Project description:The cadherin family is classified into classical cadherins, desmosomal cadherins and protocadherins (PCDHs). Genomic structures distinguish between PCDHs and other cadherins, and between clustered and non-clustered PCDHs. The phylogenetic analysis with full sequences of non-clustered PCDHs enabled them to be further classified into three subgroups: ?1 (PCDH1, PCDH7, PCDH9, PCDH11 and PCDH20), ?2 (PCDH8, PCDH10, PCDH12, PCDH17, PCDH18 and PCDH19) and ? (PCDH15, PCDH16, PCDH21 and MUCDHL). ?-PCDH members except PCDH21 have either higher or lower numbers of cadherin repeats than those of other PCDHs. Non-clustered PCDHs are expressed predominantly in the nervous system and have spatiotemporally diverse expression patterns. Especially, the region-specific expressions of non-clustered PCDHs have been observed in cortical area of early postnatal stage and in caudate putaman and/or hippocampal formation of mature brains, suggesting that non-clustered PCDHs play roles in the circuit formation and maintenance. The non-clustered PCDHs appear to have homophilic/heterophilc cell-cell adhesion properties, and each member has diverse cell signaling partnership distinct from those of other members (PCDH7/TAF1; PCDH8/TAO2?; PCDH10/Nap1; PCDH11/?-catenin; PCDH18/mDab1). Furthermore, each PCDH has several isoforms with differential cytoplasmic sequences, suggesting that one PCDH isoform could activate intracellular signaling differential from other isoforms. These facts suggest that non-clustered PCDHs play roles as a mediator of a regulator of other molecules as well as cell-cell adhesion. Furthermore, some non-clustered PCDHs have been considered to be involved in neuronal diseases such as autism-spectrum disorders, schizophrenia, and female-limited epilepsy and cognitive impairment, suggesting that they play multiple, tightly regulated roles in normal brain function. In addition, some non-clustered PCDHs have been suggested as candidate tumor suppressor genes in several tissues. Although molecular adhesive and regulatory properties of some PCDHs began to be unveiled, the endeavor to understand the molecular mechanism of non-clustered PCDH is still in its infancy and requires future study.

Project description:BackgroundObesity predisposes individuals to multiple cardiometabolic disorders, including type 2 diabetes (T2D). As body mass index (BMI) cannot reliably differentiate fat from lean mass, the metabolically detrimental abdominal obesity has been estimated using waist-hip ratio (WHR). Waist-hip ratio adjusted for body mass index (WHRadjBMI) in turn is a well-established sex-specific marker for abdominal fat and adiposity, and a predictor of adverse metabolic outcomes, such as T2D. However, the underlying genes and regulatory mechanisms orchestrating the sex differences in obesity and body fat distribution in humans are not well understood.MethodsWe searched for genetic master regulators of WHRadjBMI by employing integrative genomics approaches on human subcutaneous adipose RNA sequencing (RNA-seq) data (n ~ 1400) and WHRadjBMI GWAS data (n ~ 700,000) from the WHRadjBMI GWAS cohorts and the UK Biobank (UKB), using co-expression network, transcriptome-wide association study (TWAS), and polygenic risk score (PRS) approaches. Finally, we functionally verified our genomic results using gene knockdown experiments in a human primary cell type that is critical for adipose tissue function.ResultsHere, we identified an adipose gene co-expression network that contains 35 obesity GWAS genes and explains a significant amount of polygenic risk for abdominal obesity and T2D in the UKB (n = 392,551) in a sex-dependent way. We showed that this network is preserved in the adipose tissue data from the Finnish Kuopio Obesity Study and Mexican Obesity Study. The network is controlled by a novel adipose master transcription factor (TF), TBX15, a WHRadjBMI GWAS gene that regulates the network in trans. Knockdown of TBX15 in human primary preadipocytes resulted in changes in expression of 130 network genes, including the key adipose TFs, PPARG and KLF15, which were significantly impacted (FDR < 0.05), thus functionally verifying the trans regulatory effect of TBX15 on the WHRadjBMI co-expression network.ConclusionsOur study discovers a novel key function for the TBX15 TF in trans regulating an adipose co-expression network of 347 adipose, mitochondrial, and metabolically important genes, including PPARG, KLF15, PPARA, ADIPOQ, and 35 obesity GWAS genes. Thus, based on our converging genomic, transcriptional, and functional evidence, we interpret the role of TBX15 to be a main transcriptional regulator in the adipose tissue and discover its importance in human abdominal obesity.

Project description:Neurite self-recognition and avoidance are fundamental properties of all nervous systems1. These processes facilitate dendritic arborization2,3, prevent formation of autapses4 and allow free interaction among non-self neurons1,2,4,5. Avoidance among self neurites is mediated by stochastic cell-surface expression of combinations of about 60 isoforms of ?-, ?- and ?-clustered protocadherin that provide mammalian neurons with single-cell identities1,2,4-13. Avoidance is observed between neurons that express identical protocadherin repertoires2,5, and single-isoform differences are sufficient to prevent self-recognition10. Protocadherins form isoform-promiscuous cis dimers and isoform-specific homophilic trans dimers10,14-20. Although these interactions have previously been characterized in isolation15,17-20, structures of full-length protocadherin ectodomains have not been determined, and how these two interfaces engage in self-recognition between neuronal surfaces remains unknown. Here we determine the molecular arrangement of full-length clustered protocadherin ectodomains in single-isoform self-recognition complexes, using X-ray crystallography and cryo-electron tomography. We determine the crystal structure of the clustered protocadherin ?B4 ectodomain, which reveals a zipper-like lattice that is formed by alternating cis and trans interactions. Using cryo-electron tomography, we show that clustered protocadherin ?B6 ectodomains tethered to liposomes spontaneously assemble into linear arrays at membrane contact sites, in a configuration that is consistent with the assembly observed in the crystal structure. These linear assemblies pack against each other as parallel arrays to form larger two-dimensional structures between membranes. Our results suggest that the formation of ordered linear assemblies by clustered protocadherins represents the initial self-recognition step in neuronal avoidance, and thus provide support for the isoform-mismatch chain-termination model of protocadherin-mediated self-recognition, which depends on these linear chains11.

Dataset Information

Identification of CTCF as a master regulator of the clustered protocadherin genes.

Publications

Identification of CTCF as a master regulator of the clustered protocadherin genes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets