Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

MKL1-dependent tenascin-C transcription

ABSTRACT: The aim of the experiment is to investigate whether megakaryoblastic leukemia factor-1 (MKL1) induces tenascin-C in normal mammary epithelial HC11 and tumor mammary epithelial 4T1 cell lines, as well as to identify other genes that are transcriptionally regulated by MKL1. For this purpose, we compared the transcriptomes of HC11 and 4T1 cell lines stably expressing the full length (FL) MKL1 protein (HC11-FL and 4T1-FL cell lines) to respective control cell lines stably transfected with an empty vector (HC11-control and 4T1-control cell lines).

ORGANISM(S): Mus musculus

SUBMITTER: Maria Asparuhova

PROVIDER: E-MEXP-3232 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

The transcriptional regulator megakaryoblastic leukemia-1 mediates serum response factor-independent activation of tenascin-C transcription by mechanical stress.

Asparuhova Maria B MB Ferralli Jacqueline J Chiquet Matthias M Chiquet-Ehrismann Ruth R

FASEB journal : official publication of the Federation of American Societies for Experimental Biology 20110624 10

The extracellular matrix protein tenascin-C (TNC) is up-regulated in processes influenced by mechanical stress, such as inflammation, tissue remodeling, wound healing, and tumorigenesis. Cyclic strain-induced TNC expression depends on RhoA-actin signaling, the pathway that regulates transcriptional activity of serum response factor (SRF) by its coactivator megakaryoblastic leukemia-1 (MKL1). Therefore, we tested whether MKL1 controls TNC transcription. We demonstrate that overexpression of MKL1 ...[more]

PMID: 21705668

Similar Datasets

Project description:We have previously shown that HC11 mammary epithelial cells react strongly to the overexpression of megakaryoblastic leukemia-1 (Mkl1) with induction of tenascin-C expression. The present study was designed to find genes co-regulated with tenascin-C by Mkl1 in a SAP domain-dependent manner and without the involvement of serum response factor (SRF). For this purpose, we compared the transcriptomes of three stable HC11 cell strains that either overexpress full length Mkl1-RFP (HC11-FL), Mkl1-RFP with a mutated SRF-interaction site (HC11-mutB1) or Mkl1-RFP with a deletion of the SAP domain (HC11-ΔSAP). HC11 cell strains stably expressing either FL-, mutB1- or ∆SAP-Mkl1-RFP clones were grown in triplicates in 0.03% FCS/RPMI medium without EGF for 48 h before total RNA was extracted. RNA was converted into labeled cDNA and hybridized to Affymetrix GeneChip Mouse Gene 1.0 ST arrays. RMA normalized expression values were calculated with the affy package from the Bioconductor 2.4 release (1) and differentially expressed genes were identified using moderated t-statistics calculated with the empirical Bayes method as implemented in the Bioconductor limma package (2). To be considered as differentially expressed between HC11-mutB1 and HC11-FL as well as HC11-∆SAP and HC11-FL cell lines, genes had to pass the filters: adjusted P-value ≤ 0.01 (with Benjamin-Hochberg false discovery correction), a minimum absolute linear fold change difference of 2.0 and a minimum average expression value of 4.0 (log2). References: (1) Gentleman, R., Carey, V., Bates, D., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., Hornik, K., Hothorn, T., Huber, W., Iacus, S., Irizarry, R., Leisch, F., Li, C., Maechler, M., Rossini, A., Sawitzki, G., Smith, C., Smyth, G., Tierney, L., Yang, J., Zhang, J. (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biology 5, R80 (2) Smyth, G. K., Speed, T. (2003) Normalization of cDNA microarray data. Methods 31, 265-273

Project description:Voltage gated calcium channels play a central role in regulating the electrical and biochemical properties of neurons and muscle cells. Cells coordinate the expression of voltage gated calcium channels with the expression of other proteins that regulate membrane potential and calcium homeostasis. We report that the C-terminus of CaV 1.2, an L-type calcium channel (LTC) contains a C-terminal fragment that translocates to the nucleus and regulates transcription. This calcium channel associated transcription factor (CCAT) associates with transcriptional co-regulators such as p54nrb/NonO and binds to endogenous promoters. CCAT regulates the expression of gap junctions, sodium calcium exchangers, NMDA receptors, potassium channels and other proteins that regulate neuronal signaling. Electrical activity and developmental processes regulate the nuclear localization of CCAT, suggesting that the CCAT integrates information about the number of LTCs with information about the developmental history and electrical activity of a cell. These findings provide the first evidence that voltage gated calcium channels can directly activate transcription and suggest a novel mechanism linking voltage gated channels to the function and differentiation of excitable cells. Experiment Overall Design: The goal of these experiments was to identify the genes that are regulated by CCAT, a novel transcription factor derived from the C-terminus of CaV1.2. Neuro2A neuroblastoma cells were transfected with the last 503 AA of CaV1.2 which is full length CCAT (CCAT FL) or with the last 280 AA of CaV1.2, a form of CCAT that lacks the transcriptional activation domain (CCAT DTA). The mRNA from either CCAT FL or CCAT DTA expressing cells was hybridized to Agilent mouse genome microarrays along with mRNA from untransfected neuro2A cells (CCAT FL or DTA A series). Subsequent investigation revealed that transfection with the PA1 plasmid by itself increases the expression of some genes. To control for this effect we compared Neuro2A cells transfected with full length CCAT (in PA1) with Neuro2A cells transfectected with PA1 alone (CCAT FL B series). The microarray data was analyzed with the Rossetta Luminator gene expression data analysis system.

Project description:Chickens divergently selected for either high abdominal fat content (fat genotype) or low abdominal fat content (lean genotype) at SRA-INRA, France were used to profile abdominal adipose gene expression during juvenile development (1 to 11 weeks of age) and to identify differentially expressed genes associated with genotype and age. The fat line (FL) and lean line (LL) chickens are different in various phenotypic and metabolic measurements, including abdominal fatness, plasma glycemia and T3. The FL and LL chickens represent unique models for characterizing biomedical and agricultural traits. The Del-Mar 14K Chicken Integrated Systems microarrays were used for a transcriptional scan in abdominal adipose during juvenile development using a balanced block hybridization design. Fluorescence intensities were normalized within array (without background subtraction), and between array (aquantile method) in LIMMA package R [Smyth, G. K. (2004) Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology, Vol. 3, No. 1, Article 3] producing M-values (log-2 expression ratios) and A-values (average log-2 expression values). Normalized values were analyzed using a two factor ANOVA model. A total of 1,020 differentially expressed functional genes were identified (FDR<0.05). Genes were determined to have a significant effect of age (422), genotype (344), or an age by genotype interaction (254). The differentially expressed genes include metabolic enzymes, acute phase proteins, growth factors, coagulation factors, immune factors and transcription factors involved in various pathways. Several of the functional genes are also identified as positional candidate genes within QTLs in an F2 population established from an intercross between the FL and LL lines. Keywords: Divergently selected chickens, fatness, transcriptional profiling, differentially expressed genes A balanced block design was used for microarray hybridizations, where half of the birds of each genotype and age were labeled with Alexa Flour 647 (red) and the other half with Alexa Flour 555 (green). Four biological replicates were used for each genotype (FL or LL) at six different ages (1, 3, 5, 7, 9 and 11 wk).

Project description:Comparison of gene expression profiles of wild-type and fl-mutant upland cotton ovules Data for six replicate experiments performed with biologically independent samples. Cy3 and Cy5 dyes were used as follows: Set 1: wt+5-Cy5 wt+3-Cy3 Set 1 (dye swap): wt+5-Cy3 wt+3-Cy5 Set 2: wt+5-Cy5 wt+3-Cy3 Set 2 (dye swap): wt+5-Cy3 wt+3-Cy5 Set 3: wt+5-Cy5 wt+3-Cy3 Set 3 (dye swap): wt+5-Cy3 wt+3-Cy5 GSM63341, GSM63342, GSM63343, GSM63344, GSM63345, GSM63346 Data for 3 replicate experiments performed with biologically independent samples. Cy3 and Cy5 dyes were used as follows: Set 1: wt+3-Cy5 vs wt+3-Cy3 Set 2: wt+3-Cy3 vs wt+3-Cy5 Set 3: wt+3-Cy5 vs wt+3-Cy3 GSM63365, GSM63366, GSM63367 Data for six replicate experiments performed with biologically independent samples. Cy3 and Cy5 dyes were used as follows: Set 1: wt+3-Cy5 wt-3-Cy3 Set 1 (dye swap): wt+3-Cy3 wt-3-Cy5 Set 2: wt+3-Cy5 wt-3-Cy3 Set 2 (dye swap): wt+3-Cy3 wt-3-Cy5 Set 3: wt+3-Cy5 wt-3-Cy3 Set 3 (dye swap): wt+3-Cy3 wt-3-Cy5 GSM63368, GSM63369, GSM63370, GSM63371, GSM63372, GSM63373 Data for six replicate experiments performed with biologically independent samples. Cy3 and Cy5 dyes were used as follows: Set 1: 0wt-Cy5 wt+3-Cy3 Set 1 (dye swap): 0wt-Cy3 wt+3-Cy5 Set 2: 0wt-Cy5 wt+3-Cy3 Set 2 (dye swap): 0wt-Cy3 wt+3-Cy5 Set 3: 0wt-Cy5 wt+3-Cy3 Set 3 (dye swap): 0wt-Cy3 wt+3-Cy5 GSM63374, GSM63375, GSM63376, GSM63377, GSM63378, GSM63379 Data for six replicate experiments performed with biologically independent samples. Cy3 and Cy5 dyes were used as follows: Set 1: wt+3-Cy5 fl+3-Cy3 Set 1 (dye swap): wt+3-Cy3 fl+3-Cy5 Set 2: wt+3-Cy5 fl+3-Cy3 Set 2 (dye swap): wt+3-Cy3 fl+3-Cy5 Set 3: wt+3-Cy5 fl+3-Cy3 Set 3 (dye swap): wt+3-Cy3 fl+3-Cy5 GSM63391, GSM63392, GSM63393, GSM63394, GSM63395, GSM63396 Data for six replicate experiments performed with biologically independent samples. Cy3 and Cy5 dyes were used as follows: Set 1: wt+10-Cy5 fl+10-Cy3 Set 1 (dye swap): wt+10-Cy3 fl+10-Cy5 Set 2: wt+10-Cy5 fl+10-Cy3 Set 2 (dye swap): wt+10-Cy3 fl+10-Cy5 Set 3: wt+10-Cy5 fl+10-Cy3 Set 3 (dye swap): wt+10-Cy3 fl+10-Cy5 GSM63397, GSM63398, GSM63399, GSM63400, GSM63401, GSM63402 Data for six replicate experiments performed with biologically independent samples. Cy3 and Cy5 dyes were used as follows: Set 1: wt+10-Cy5 wt+3-Cy3 Set 1 (dye swap): wt+10-Cy3 wt+3-Cy5 Set 2: wt+10-Cy5 wt+3-Cy3 Set 2 (dye swap): wt+10-Cy3 wt+3-Cy5 Set 3: wt+10-Cy5 wt+3-Cy3 Set 3 (dye swap): wt+10-Cy3 wt+3-Cy5 GSM63403, GSM63404, GSM63405, GSM63406, GSM63407, GSM63408 Data for six replicate experiments performed with biologically independent samples. Cy3 and Cy5 dyes were used as follows: Set 1: wt+15-Cy5 wt+3-Cy3 Set 1 (dye swap): wt+15-Cy3 wt+3-Cy5 Set 2: wt+15-Cy5 wt+3-Cy3 Set 2 (dye swap): wt+15-Cy3 wt+3-Cy5 Set 3: wt+15-Cy5 wt+3-Cy3 Set 3 (dye swap): wt+15-Cy3 wt+3-Cy5 GSM63409, GSM63410, GSM63411, GSM63412, GSM63413, GSM63414 Data for six replicate experiments performed with biologically independent samples. Cy3 and Cy5 dyes were used as follows: Set 1: wt+20-Cy5 wt+3-Cy3 Set 1 (dye swap): wt+20-Cy3 wt+3-Cy5 Set 2: wt+20-Cy5 wt+3-Cy3 Set 2 (dye swap): wt+20-Cy3 wt+3-Cy5 Set 3: wt+20-Cy5 wt+3-Cy3 Set 3 (dye swap): wt+20-Cy3 wt+3-Cy5 GSM63415, GSM63416, GSM63417, GSM63418, GSM63419, GSM63420

Dataset Information

MKL1-dependent tenascin-C transcription

Publications

The transcriptional regulator megakaryoblastic leukemia-1 mediates serum response factor-independent activation of tenascin-C transcription by mechanical stress.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure