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Abstract

Ctr9, the key scaffold subunit in human RNA polymerase II associated factor complex (PAFc), has diverse functions in cells and has been implicated in human diseases. Recently, our study found that loss of Ctr9 led to apparent morphological change, decrease of proliferation, and reduced colony formation in ERα⁺ breast cancer cells. Moreover, Ctr9 and ERα show positive correlation at protein levels and the high levels of Ctr9 are associated with poor survival among all women with ERα⁺ breast cancers, and specifically among those treated with tamoxifen. To gain a molecular understanding of the role of Ctr9 in promoting ERα⁺ breast cancer, we performed a microarray gene expression profiling of Ctr9-regulated transcriptome. Here we provide the experimental details and analysis of the microarray data, which have been deposited into Gene Expression Omnibus (GEO): GSE73388.

1. Direct link to deposited data

Transcriptome Analysis Console Software 4.0 includes the following changes and enhancements: 1. Integration of Expression Console (EC) and Transcriptome Analysis Console (TAC) 2. Incorporation of LIMMA Tools, including batch effect adjustment 3. Support for large datasets in recommended systems 4. Exploratory Grouping Analysis (EGA) 5. The scanned images were analyzed to produce raw data files saved as CEL files. Data analysis and visualization were performed using the Affymetrix Transcriptome Analysis Console (TAC) Software per the manufacturer's protocol. The criteria for selecting differentially expressed genes was 1.5-fold change cutoff and a false discovery rate.

1. The eight CHP files were then imported into the Affymetrix® Transcriptome Analysis Console (TAC) 2.0 (build 2.0.0.9) using the Gene Level Differential Analysis option. Within TAC, the genome assembly hg19 was used with the annotation file HTA-20.na34.hg19.transcript.csv.
2. TAC.exe is the Transcriptome Analysis Console v2.0's primary executable file and it occupies approximately 48.00 KB (49152 bytes) on disk. The executable files below are installed alongside Transcriptome Analysis Console v2.0. They occupy about 97.50 KB (99840 bytes) on disk. TAC.exe (48.00 KB).

The deposited data can be found at: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE73388.

2. Experimental design, materials and methods

2.1. Cell culture and reagents

MCF7-tet-on-shCtr9 cells were generated and characterized previously [1], [2] and maintained in DMEM supplemented with 10% FBS. Cells were cultured at 37 °C in a humidified atmosphere containing 5% CO₂. Doxycycline (Dox) was purchased from Clontech (Mountain View, CA) and used at a final concentration of 500 ng/ml to induce Ctr9-targeting shRNA expression. Dimethyl sulfoxide (DMSO) and 17 β-estradiol (E2) were purchased from Sigma (St. Louis, MO).

2.2. Ctr9 knockdown and E2 induction

In order to globally identify E2- and Ctr9-regulated transcriptome in ERα⁺ breast cancer cells, MCF7-tet-on-shCtr9 cells were maintained in DMEM supplemented with 10% FBS in the absence or presence of 500 ng/mL Dox for 4 days, followed by continuing culture in stripped medium with or without 500 ng/ml Dox for another 3 days. Cells were subsequently treated with DMSO or 10 nM E2 for 4 h prior to cell collection (Fig. 1).

Transcriptome Analysis Console Tac Software Machine

Experimental design for global identification of E2- and Ctr9-regulated transcriptome.

2.3. Total RNA extraction and microarray hybridization

To ensure the biological confidence, three independent experiments were performed as illustrated in Fig. 1. Total RNA from twelve samples was extracted using a Qiagen RNeasy Plus Kit according to manufacturer's protocol. The RNA quantity was determined by NanoDrop spectrophotometer. Purified total RNA was then submitted to the University of Wisconsin Madison Biotechnology Center. RNA quality was assessed on the Agilent 2100 BioAnalyzer using a RNA 6000 Nano Chip. All twelve RNA samples look intact, with both ribosomal peaks present (Fig. 2). 400 ng of total RNA for each sample was used to synthesize double-stranded cDNA and the corresponding in vitro transcription (IVT) cRNA, using the Ambion WT Expression Kit per the manufacturer's instructions. In order to monitor labeling and hybridization quality, 400 ng of polyA control RNA was spiked in for each sample. Subsequently, cRNA was purified and quantified and then subject to single strand (ss) cDNA synthesis. The purified ss cDNA was then fragmented to < 150 bp and end-terminus labeled using Affymetrix GeneChip WT Terminal Labeling Kit following manufacturer's guidelines. The labeled samples were then hybridized to GeneChip Human Transcriptome Array 2.0 containing > 6.0 million distinct probes covering 44,699 protein coding genes and 22,829 non-protein coding genes at 45 °C for 16 h, according to the guidelines in the Affymetrix GeneChip WT Terminal Labeling and Hybridization User Manual.

Assessment of RNA quality on the Agilent 2100 BioAnalyzer.

Transcriptome Analysis Console Tac Software Mac Free

2.4. Data process and analysis

After hybridization, the GeneChip arrays were washed and then stained (streptavidin–phycoerythrin) on an Affymetrix Fluidics Station 450 followed by scanning on a GeneChip 3000 G7 Scanner. The scanned images were analyzed to produce raw data files saved as CEL files. Data analysis and visualization were performed using the Affymetrix Transcriptome Analysis Console (TAC) Software per the manufacturer's protocol. The criteria for selecting differentially expressed genes was 1.5-fold change cutoff and a false discovery rate < 0.05. Based on this criteria, we found that over 1600 genes were regulated by estrogen treatment, and of those 1600, only 50 genes respond to E2 after Ctr9 knockdown, suggesting the essential role of Ctr9 in regulating ERα-dependent gene transcription [2].

Transcriptome Analysis Console (tac) Software Mac

3. Discussion

We described here a dataset composed of microarray gene expression profiling of E2- and Ctr9-regulated genes in MCF7 human breast cancer cells. /packard-bell-easynote-entg71bm-drivers.html. With this genome-wide transcriptome analysis, we were able to demonstrate Ctr9, the key scaffold subunit in human PAFc, as a master-regulator of estrogen signaling in ERα⁺ breast cancer [2]. We believe that this dataset would provide valuable information for researchers who are interested in studying the estrogen response hierarchy in ERα⁺ breast cancer.

Conflict of interest

The authors declare no conflict of interests.

Acknowledgments

This study was supported by a Department of Defense ERA of Hope Award W81XWYH-11-1-0237 to W.X.

References

Transcriptome Analysis Console Tac Software Mac Os

Hello everyone,

I am starting to work with the Affy Transcription Analysis Console (TAC) on some miRNA4.0 data. I would like to output an expression matrix after RMA normalization/summarization. of the miRNA data. I see from the old Affymetrix Expression Console that there was a way to do this:

however, the Affymetrix Expression Console has been discontinued, its functions are now included in the TAC software. However, I cannot seem to find instructions in the TAC manual for how to accomplish this process. I know that many of the downstream analysis tools are included in the TAC software but I NEED to extract this expression matrix for use elsewhere.

Has anyone had success in doing this? Thanks!

As this is commercial software, use their Support service.

Transcriptome Analysis Console Tac Software Mac Download

Just got off the phone with the affy people. Here is how you do this for TAC 4.01:

You must do an analysis even if you dont intend to use its output in order to get to the menu option that allows you to export your expression table. So, load in your .cel files using 'import cel files in the upper left corner of the first screen, you should also have downloaded the appropriate library from the affy site. I stored mine in the same folder as my .cel files.

having loaded some cell files, there should now be a 2 columns one 'File Name' with your cel files, and the next 'Condition' I selected my type as comparison and of course added some values in the condition column so that the test can run. At the top of the screen are two drop down tabs 'analysis type' and 'Summarization' The analysis type should be 'Epression (Gene). I chose my summarization as RMA+DABG (All Organisms) since i am working with a miRNA4.0 chip. Then in the bottom right click 'run analysis'.

This brings up a new two part screen. On the left hand screen there should be three headers 'Sample QC view', 'Summary View', and 'Gene View'. Chose gene view.

This brings up a new screen. on this screen there is a drop down menu option for 'Export' click on it and select the option 'Export..' this brings up a new window of export options. Select 'Sample Signals only' then 'All rows' and then 'All samples'. Then click OK and it will let you export your expression table to a filename of your choice. Note that the row names will be the probeset IDs by default, if you wanted something else for your row name (such as target gene symbols, validated gene symbols, or transcriptID etc) you should, before exporting click on the 'show/hide columns option at the Gene View screen prior to export. This will add a column containing this information and you can later, I assume, use this column for your rownames when importing it in R or whatever.

There, that should do it!