scholarly journals A transcription factor-binding domain of the coactivator CBP is essential for long-term memory and the expression of specific target genes

2006 ◽  
Vol 13 (5) ◽  
pp. 609-617 ◽  
Author(s):  
M. A. Wood ◽  
M. A. Attner ◽  
A. M.M. Oliveira ◽  
P. K. Brindle ◽  
T. Abel
Keyword(s):  
Transcription Factor ◽  
Target Genes ◽  
Transcription Factor Binding ◽  
Binding Domain ◽  
Long Term Memory ◽  
Term Memory ◽  
Factor Binding ◽  
Specific Target

NF-κB transcription factor is required for inhibitory avoidance long-term memory in mice

2005 ◽  
Vol 21 (10) ◽  
pp. 2845-2852 ◽  
Author(s):  
Ramiro Freudenthal ◽  
Mariano M. Boccia ◽  
Gabriela B. Acosta ◽  
Mariano G. Blake ◽  
Emiliano Merlo ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Inhibitory Avoidance ◽  
Long Term Memory ◽  
Term Memory

scholarly journals A Transcription Factor Pulse Can Prime Chromatin for Heritable Transcriptional Memory

2016 ◽  
Vol 37 (4) ◽  
Author(s):  
Aimee Iberg-Badeaux ◽  
Samuel Collombet ◽  
Benoit Laurent ◽  
Chris van Oevelen ◽  
Kuo-Kai Chin ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Rna Polymerase Ii ◽  
Target Genes ◽  
Short Term Memory ◽  
Epigenetic Mechanism ◽  
Short Term ◽  
Term Memory ◽  
Pol Ii ◽  
Transcriptional Memory

ABSTRACT Short-term and long-term transcriptional memory is the phenomenon whereby the kinetics or magnitude of gene induction is enhanced following a prior induction period. Short-term memory persists within one cell generation or in postmitotic cells, while long-term memory can survive multiple rounds of cell division. We have developed a tissue culture model to study the epigenetic basis for long-term transcriptional memory (LTTM) and subsequently used this model to better understand the epigenetic mechanisms that enable heritable memory of temporary stimuli. We find that a pulse of transcription factor CCAAT/enhancer-binding protein alpha (C/EBPα) induces LTTM on a subset of target genes that survives nine cell divisions. The chromatin landscape at genes that acquire LTTM is more repressed than at those genes that do not exhibit memory, akin to a latent state. We show through chromatin immunoprecipitation (ChIP) and chemical inhibitor studies that RNA polymerase II (Pol II) elongation is important for establishing memory in this model but that Pol II itself is not retained as part of the memory mechanism. More generally, our work reveals that a transcription factor involved in lineage specification can induce LTTM and that failure to rerepress chromatin is one epigenetic mechanism underlying transcriptional memory.

scholarly journals Altered Transcription Factor Binding and Gene Bivalency in Islets of Intrauterine Growth Retarded Rats

Cells ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1435
Author(s):  
Yu-Chin Lien ◽  
Paul Zhiping Wang ◽  
Xueqing Maggie Lu ◽  
Rebecca A. Simmons
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Transcription Factor Binding ◽  
Binding Motifs ◽  
Factor Binding ◽  
Intrauterine Growth ◽  
Gene Dysregulation ◽  
Genome Wide

Intrauterine growth retardation (IUGR), which induces epigenetic modifications and permanent changes in gene expression, has been associated with the development of type 2 diabetes. Using a rat model of IUGR, we performed ChIP-Seq to identify and map genome-wide histone modifications and gene dysregulation in islets from 2- and 10-week rats. IUGR induced significant changes in the enrichment of H3K4me3, H3K27me3, and H3K27Ac marks in both 2-wk and 10-wk islets, which were correlated with expression changes of multiple genes critical for islet function in IUGR islets. ChIP-Seq analysis showed that IUGR-induced histone mark changes were enriched at critical transcription factor binding motifs, such as C/EBPs, Ets1, Bcl6, Thrb, Ebf1, Sox9, and Mitf. These transcription factors were also identified as top upstream regulators in our previously published transcriptome study. In addition, our ChIP-seq data revealed more than 1000 potential bivalent genes as identified by enrichment of both H3K4me3 and H3K27me3. The poised state of many potential bivalent genes was altered by IUGR, particularly Acod1, Fgf21, Serpina11, Cdh16, Lrrc27, and Lrrc66, key islet genes. Collectively, our findings suggest alterations of histone modification in key transcription factors and genes that may contribute to long-term gene dysregulation and an abnormal islet phenotype in IUGR rats.

scholarly journals The CBP KIX domain regulates long-term memory and circadian activity

2020 ◽  
Author(s):  
Snehajyoti Chatterjee ◽  
Christopher C. Angelakos ◽  
Ethan Bahl ◽  
Joshua D. Hawk ◽  
Marie E. Gaine ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Long Term Memory ◽  
Creb Binding Protein ◽  
Circadian Activity ◽  
Specific Domain ◽  
Term Memory ◽  
Circadian Genes ◽  
Kix Domain

AbstractCREB-dependent transcription necessary for long-term memory is driven by interactions with CREB-binding protein (CBP), a multi-domain protein that binds numerous transcription factors. Identifying specific domain functions for multi-action proteins is essential to understand processes necessary for healthy living including cognitive function and a robust circadian clock. We investigated the function of the CBP KIX domain in hippocampal memory and gene expression using CBPKIX/KIX mice with mutations that prevent phospho-CREB (Ser133) binding. We found that CBPKIX/KIX mice were impaired in long-term, but not short-term spatial memory in the Morris water maze. Using an unbiased analysis of gene expression after training for hippocampus-dependent memory, we discovered dysregulation of CREB and CLOCK target genes and downregulation of circadian genes in CBPKIX/KIX mice. With our finding that the CBP KIX domain was important for transcription of circadian genes, we profiled circadian activity in CBPKIX/KIX mice. CBPKIX/KIX mice exhibited delayed activity peaks after light offset and longer free-running periods in constant dark, although phase resetting to light was comparable to wildtype. These studies provide insight into the significance of the CBP KIX domain by defining targets of CBP transcriptional co-activation in memory and the role of the CBP KIX domain in vivo on circadian rhythms.

Bioinformatics approaches to predict target genes from transcription factor binding data

Methods ◽  
2017 ◽  
Vol 131 ◽  
pp. 111-119 ◽  
Author(s):  
Alexandra Essebier ◽  
Marnie Lamprecht ◽  
Michael Piper ◽  
Mikael Bodén
Keyword(s):  
Transcription Factor ◽  
Target Genes ◽  
Transcription Factor Binding ◽  
Factor Binding ◽  
Binding Data

Genome Wide Approaches to Identify Protein-DNA Interactions

2020 ◽  
Vol 26 (42) ◽  
pp. 7641-7654 ◽  
Author(s):  
Tao Ma ◽  
Zhenqing Ye ◽  
Liguo Wang
Keyword(s):  
Transcription Factor ◽  
Binding Sites ◽  
Target Genes ◽  
Rapid Development ◽  
Transcription Factor Binding Sites ◽  
Transcription Factor Binding ◽  
Computational Approaches ◽  
Factor Binding ◽  
Genome Wide ◽  
Chip Chip

Background: Transcription factors are DNA-binding proteins that play key roles in many fundamental biological processes. Unraveling their interactions with DNA is essential to identify their target genes and understand the regulatory network. Genome-wide identification of their binding sites became feasible thanks to recent progress in experimental and computational approaches. ChIP-chip, ChIP-seq, and ChIP-exo are three widely used techniques to demarcate genome-wide transcription factor binding sites. Objective: This review aims to provide an overview of these three techniques including their experiment procedures, computational approaches, and popular analytic tools. Conclusion: ChIP-chip, ChIP-seq, and ChIP-exo have been the major techniques to study genome- wide in vivo protein-DNA interaction. Due to the rapid development of next-generation sequencing technology, array-based ChIP-chip is deprecated and ChIP-seq has become the most widely used technique to identify transcription factor binding sites in genome-wide. The newly developed ChIP-exo further improves the spatial resolution to single nucleotide. Numerous tools have been developed to analyze ChIP-chip, ChIP-seq and ChIP-exo data. However, different programs may employ different mechanisms or underlying algorithms thus each will inherently include its own set of statistical assumption and bias. So choosing the most appropriate analytic program for a given experiment needs careful considerations. Moreover, most programs only have command line interface so their installation and usage will require basic computation expertise in Unix/Linux.

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