Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression analysis of mutant U2AF35 transduced cells

ABSTRACT: In this study, to obtain the biological impact of the mutated U2AF35, HeLa and TF-1 cells were retrovirally transduced with either mock, wild-type or S34F mutant of U2AF35, and Expression array was performed. Expression analysis was performed for mock, wild-type U2AF35 or S34F mutant transduced HeLa and MDS-derived TF-1 cell line in triplicate.

ORGANISM(S): Homo sapiens

SUBMITTER: Aiko Sato-Otsubo

PROVIDER: E-GEOD-31172 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Frequent pathway mutations of splicing machinery in myelodysplasia.

Yoshida Kenichi K Sanada Masashi M Shiraishi Yuichi Y Nowak Daniel D Nagata Yasunobu Y Yamamoto Ryo R Sato Yusuke Y Sato-Otsubo Aiko A Kon Ayana A Nagasaki Masao M Chalkidis George G Suzuki Yutaka Y Shiosaka Masashi M Kawahata Ryoichiro R Yamaguchi Tomoyuki T Otsu Makoto M Obara Naoshi N Sakata-Yanagimoto Mamiko M Ishiyama Ken K Mori Hiraku H Nolte Florian F Hofmann Wolf-Karsten WK Miyawaki Shuichi S Sugano Sumio S Haferlach Claudia C Koeffler H Phillip HP Shih Lee-Yung LY Haferlach Torsten T Chiba Shigeru S Nakauchi Hiromitsu H Miyano Satoru S Ogawa Seishi S

Nature 20110911 7367

Myelodysplastic syndromes and related disorders (myelodysplasia) are a heterogeneous group of myeloid neoplasms showing deregulated blood cell production with evidence of myeloid dysplasia and a predisposition to acute myeloid leukaemia, whose pathogenesis is only incompletely understood. Here we report whole-exome sequencing of 29 myelodysplasia specimens, which unexpectedly revealed novel pathway mutations involving multiple components of the RNA splicing machinery, including U2AF35, ZRSR2, SR ...[more]

PMID: 21909114

Similar Datasets

Project description:Multiple gene expression studies have demonstrated that breast cancer biological diversity is associated with distinct transcriptional programs. Transcription factors, because of their unique ability to coordinate the expression of multiple genes, are speculated to play a role in generating phenotypic plasticity associated with cancer progression including acquired drug resistance. Combinatorial libraries of artificial zinc-finger transcription factors (ZF-TFs) provide a robust means for inducing and understanding various functional components of the cancer phenotype. Herein, we utilized combinatorial ZF-TF library technology to better understand how breast cancer cells acquire resistance to a fulvestrant, a clinically important anti-endocrine therapeutic agent. We isolated six ZF-TF library members capable of inducing stable, long-term anti-endocrine drug-resistance in two independent estrogen receptor positive breast cancer cell lines. Comparative gene expression profile analysis of the ZF-TF-transduced breast cancer cell lines revealed a 72-gene cluster that constituted a common signature for the fulvestrant-resistance phenotype. Pathway enrichment-analysis of gene expression data revealed that the ZF-TF-induced fulvestrant resistance is associated with an estrogen receptor negative-like gene set and four unique myb-regulated gene sets. Furthermore, we identified a set of genes strongly expressed in the ZF-TF-induced fulvestrant-resistant cells that was correlated with a lower probability of distant metastasis-free or death-from-relapse-free survival of breast cancer patients. MCF7-R73 cells, a monoclonal MCF7 subline that is highly sensitive to fulvestrant-induced cytocidal activity, underwent retroviral transduction with the zinc finger transcription factor (ZF-TF) activator library or with a control plasmid encoding only the NF-kB p65 activation domain. Both populations of cells were enriched for transduced cells by selecting for growth in puromycin and for fulvestrant-resistant cells by selecting with 100 nM fulvestrant. After 6 weeks of continuous treatment with fulvestrant, hundreds of drug-resistant colonies emerged from the population of cells infected with the ZF-TF activator library. By contrast, as expected, the control MCF7cell line transduced by NF-kB p65-only underwent massive cell death resulting in the complete absence of resistant colonies. DNA encoding the zinc-finger arrays was rescued by PCR from genomic DNA of pooled fulvestrant-resistant cells. The sequences of the ZF-TFs were determined and 46 unique ZF-TF clones identified. These 46 unique ZF-TFs were re-cloned into the retroviral vector and converted into clonal virus stocks that were used to transduce MCF7-R73 cells. These 46 retrovirally transduced cell populations were then challenged with fulvestrant. As compared with the control MCF-238 cells, MCF7-R73 cells transduced with six unique ZF-TFs demonstrated survival and growth in the presence of 100nM fulvestrant.

Project description:Binding of transcription factors (TFs) to regulatory sequences is a pivotal step in the control of gene expression. Despite many advances in the characterization of sequence motifs recognized by TFs, our ability to quantitatively predict TF binding to different regulatory sequences is still limited. Here, we present a novel experimental assay termed BunDLE-seq that provides quantitative measurements of TF binding to thousands of fully designed sequences of 200 bp in length within a single experiment. Applying this binding assay to two yeast TFs we demonstrate that sequences outside the core TF binding site profoundly affect TF binding. We show that TF-specific models based on the sequence or DNA shape of the regions flanking the core binding site are highly predictive of the measured differential TF binding. We further characterize the dependence of TF binding, accounting for measurements of single and co-occurring binding events, on the number and location of binding sites and on the TF concentration. Finally, by coupling our in vitro TF binding measurements, and another application of our method probing nucleosome formation, to in vivo expression measurements carried out with the same template sequences now serving and promoters, we offer insights into mechanisms that may determine the different expression outcomes observed. Our assay thus paves the way to a more comprehensive understanding of TF binding to regulatory sequences, and allows the characterization of TF binding determinants within and outside of core binding sites. Binding experiments were carried out with one of two input libraries; Lib1 (also referred to as “main lib”) includes designed sequence variants of length 150bp, and Lib2 (also referred to as “constant flanks lib”) includes designed sequence variants of length 200bp. The sequences of the variants of interest can be found in the second column of the processed data file (BunDLE-seq_data, see 3 excel sheets). EXP1, EXP2 and EXP3 were carried out using Lib1, and EXP4 was carried out using Lib2. Binding experiments were carried out with different proteins (in different concentrations) – DNA was extracted from bound bands that were formed on the gel and amplified with a primer with a unique 5bp upstream tail specifying the identity of the originating band (also referred to as “band barcode”). Data from the following bands was used in the analysis: EXP1_band1, no-protein band – with band barcode “AACGA”, EXP1_band2, single Gcn4 (conc 1:8) bound band* – with band barcode “TCGTA” , EXP1_band3, histones bound band – with band barcode “AGATA”, EXP2_band1, no-protein band – with band barcode “AACGA”, EXP2_band2, single Gcn4 (conc 1:8) bound band* – with band barcode “AGATA”, EXP2_band2, single Gcn4 (conc 1:7) bound band – with band barcode “CACTT”, EXP2_band2, single Gcn4 (conc 1:6) bound band – with band barcode “TCGTA”, EXP2_band2, single Gcn4 (conc 1:5) bound band – with band barcode “CATCA”, EXP2_band2, single Gcn4 (conc 1:4) bound band – with band barcode “TATTA”, EXP2_band2, single Gcn4 (conc 1:3) bound band – with band barcode “AGTCA”, EXP2_band2, single Gcn4 (conc 1:2) bound band – with band barcode “ACGAA”, EXP2_band2, single Gcn4 (conc 1:1) bound band – with band barcode “ACAGA”, EXP2_band2, two Gcn4 (conc 1:1) bound band – barcoded with “GTAGA”, EXP3_band1, no-protein band – with band barcode “GCATA”, EXP3_band2, single Gal4 (conc 1:1) bound band – with band barcode “GATGT”, EXP3_band3, single Gal4 (conc 3:1) bound band – with band barcode “GTTCA”, EXP3_band4, two Gal4 (conc 3:1) bound band – with band barcode “CTCAA”, EXP4_band1, no-protein band – with band barcode “GAGTA”, EXP4_band2, single Gcn4 (conc 1:3) bound band – “TACCA”, EXP4_band3, no-protein band – with band barcode “TCGTT”, EXP4_band3, single Gal4 (conc 3:1) bound band – with band barcode “ACATC”, *biological replicates

Dataset Information

Expression analysis of mutant U2AF35 transduced cells

Publications

Frequent pathway mutations of splicing machinery in myelodysplasia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure