Project description:check the effect of over expression and down regulation of this clade of TFs Experiment Overall Design: each line have two replicate
Project description:Reprogramming approaches often produce heterogeneous cell fates and the mechanisms behind this heterogeneity are not well-understood. To address this gap, we developed scTF-seq, a technique inducing single-cell barcoded and doxycycline-inducible transcription factor (TF) overexpression while quantifying TF dose-dependent transcriptomic changes. Applied to mouse embryonic multipotent stromal cells (MSCs), scTF-seq produced a gain-of-function atlas for 384 murine TFs. This atlas offers a valuable resource for gene regulation and reprogramming research, identifying key TFs governing MSC lineage differentiation, cell cycle control, and their interplay. Leveraging the single-cell resolution, we dissected reprogramming heterogeneity along dose. We thereby revealed TF dose-dependent and stochastic cell state transitions, unveiling gene expression signatures that enhance our understanding and prediction of reprogramming efficiency. By exploring the relationship between TF dose and function, scTF-seq also allowed us to classify TFs into three sensitivity classes: low- versus high-capacity TFs with the latter split into ‘low’ and ‘high’ dose-sensitive groups. Finally, in combinatorial scTF-seq, we observed that the same TF can exhibit both synergistic and antagonistic effects on another TF depending on its dose. In summary, scTF-seq provides a powerful tool for gaining mechanistic insights into how TFs determine cell states, while offering valuable perspectives for cellular engineering strategies. For analysis and more details about this data, you can check our GitHub: https://github.com/DeplanckeLab/TF-seq
Project description:Targeting of general coactivators, such as BRD4, is an emerging strategy to interfere with oncogenic transcription factors (TFs) in cancer. However, coactivator perturbations have the potential to influence the function of numerous TFs, thereby resulting in biological pleiotropy. Here we identify TAF12, an 18 kilodalton subunit of TFIID/SAGA coactivator complexes, as a selective requirement for acute myeloid leukemia (AML) progression. We trace this AML-specific dependency to a direct interaction between the TAF12/TAF4 histone-fold heterodimer and the transactivation domain of MYB, a TF with established roles in leukemogenesis. Ectopic expression of a histone-fold domain fragment of TAF4 can efficiently squelch TAF12 in cells, suppress MYB, and regress AML in mice. Our study reveals a strategy for potent MYB inhibition in AML and highlights how an oncogenic TF can be selectively neutralized by targeting a general coactivator complex.
Project description:Targeting of general coactivators, such as BRD4, is an emerging strategy to interfere with oncogenic transcription factors (TFs) in cancer. However, coactivator perturbations have the potential to influence the function of numerous TFs, thereby resulting in biological pleiotropy. Here we identify TAF12, an 18 kilodalton subunit of TFIID/SAGA coactivator complexes, as a selective requirement for acute myeloid leukemia (AML) progression. We trace this AML-specific dependency to a direct interaction between the TAF12/TAF4 histone-fold heterodimer and the transactivation domain of MYB, a TF with established roles in leukemogenesis. Ectopic expression of a histone-fold domain fragment of TAF4 can efficiently squelch TAF12 in cells, suppress MYB, and regress AML in mice. Our study reveals a strategy for potent MYB inhibition in AML and highlights how an oncogenic TF can be selectively neutralized by targeting a general coactivator complex.
Project description:In order to functionally characterize OsRDR4, a member of γ-clade RNA dependent RNA polymerase (RDR) in rice, transgenics were raised for the overexpression (OE) and knock-down (KD) of OsRDR4 in the background of Oryza sativa indica cultivar, Pusa Basmati 1. The knockdown lines showed developmental defects in terms of delayed flowering, short tillers, poor seed setting, etc.
Project description:we profiled miRNA gene expression with the Illumina hybridization system in K562 cells induced by hemin and K562 cells with over-expressing or knocking-down GATA-1, EKLF or NF-E2 treatments. To find differential expression miRNAs, we profiled miRNA gene expression with the Illumina hybridization system in untreated, hemin-treated 48h and 72h K562 cells. To define GATA-1, EKLF or NF-E2 directly targeted miRNA genes, a comprehensive analysis of TF induced miRNA gene expression changes was performed using over-expressing or knocking-down TFs in K562 cells and illumina miRNA profiling Beadchip system.
Project description:a pull-down assay using a concatenated tandem array of consensus TF response elements (catTFRE) to trap the TFs expressed in mouse livers following treatment with or without H2O2
Project description:This dataset uses DNase-seq to profile the genome-wide DNase I hypersensitivity of mES and mES-derived cells along an early pancreatic lineage and provides the locations of putative Transcription Factor (TF) binding sites using the PIQ algorithm. DNase-seq takes advantage of the preferential cutting of DNase I in open chromatin and steric blockage of of DNase I by tightly bound TFs that protect associated genomic DNA sequences. After deep sequencing of DNase IM-bM-^@M-^Sdigested genomic DNA from intact nuclei, genome-wide data on chromatin accessibility as well as TF-specific DNase I protection profiles that reveal the genomic binding locations of a majority of TFs are obtained. Such TF signature M-bM-^@M-^XDNase profilesM-bM-^@M-^Y reflect the effect of the TF on DNA shape and local chromatin architecture, extending hundreds of base pairs from a TF binding site, and these profiles are centered on M-bM-^@M-^XDNase footprintsM-bM-^@M-^Y at the binding motif itself, which reflects the biophysics of protein-DNA binding. An algorithm, PIQ, is then applied that models the specific profile of each factor, and in combination with sequence information predicts the likely binding locations of over 700 TFs genome wide. This dataset includes DNase-seq hypersensitivity data from 6 mES-derived cell types: mESC, Mesendoderm, Mesoderm, Endoderm, Intestinal Endoderm, and Prepancreatic Endoderm. For each cell type, TF binding site predictions are made based on the identification TF-specific DNase-seq profiles over any of 1331 possible binding motifs. After significance thesholding, genome-wide binding site predictions for <700 TFs are included.
Project description:Site-specific transcription factors (TFs) play an essential role in mammalian development and function as they are vital for the majority of cellular processes. Despite their biological importance, TF proteomic data is scarce in the literature, likely due to difficulties in detecting peptides as the abundance of TFs in cells tends to be low. In recent years, significant improvements in mass spectrometry (MS)-based technologies in terms of sensitivity and specificity have increased the interest in developing quantitative methodologies specifically targeting relatively lowly abundant proteins such as TFs in mammalian models. Such efforts would be greatly aided by the availability of TF peptide-specific information as such data would not only enable improvements in speed and accuracy of protein identifications, but also ameliorate cross-comparisons of quantitative proteomics data and allow for a more efficient development of targeted proteomics assays. However, to date, no comprehensive TF proteotypic peptide database has been developed. To address this evident lack of TF peptide data in public repositories, we are generating a comprehensive, experimentally derived TF proteotypic peptide spectral library dataset based on in vitro protein expression. Our library currently contains peptide information for 89 TFs, and this number is set to increase in the near future.