DNA-Binding Specificities of Human Transcription Factors

Jolma, Arttu; Yan, Jian; Whitington, Thomas; Toivonen, Jarkko; Nitta, Kazuhiro R.; Rastas, Pasi; Morgunova, Ekaterina; Enge, Martin; Taipale, Mikko; Wei, Gong-Hong; Palin, Kimmo; Vaquerizas, Juan M.; Vincentelli, Renaud; Luscombe, Nicholas M.; Hughes, Timothy R.; Lemaire, Patrick; Ukkonen, Esko; Kivioja, Teemu; Taipale, Jussi

doi:10.1016/j.cell.2012.12.009

Cited by 1,170 publications

(1,544 citation statements)

References 64 publications

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“…We used the Stubb algorithm (77) for genome-wide scanning of motif matches in conjunction with cis-Metalysis to identify TF motifs or pairs of motifs enriched in noncoding regions around up-and down-regulated socially responsive genes. We used a collection of 368 motifs from JASPAR (78) and Jolma et al (79). For "meta-associations," i.e., motifs (or combinations of two motifs) enriched for DEGs across two or three species, we corrected "meta P values" reported by cis-Metalysis for multiple hypothesis testing, using an empirical FDR estimation.…”

Section: Methodsmentioning

confidence: 99%

Neuromolecular responses to social challenge: Common mechanisms across mouse, stickleback fish, and honey bee

Rittschof

Bukhari

Sloofman

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

142

196

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Certain complex phenotypes appear repeatedly across diverse species due to processes of evolutionary conservation and convergence. In some contexts like developmental body patterning, there is increased appreciation that common molecular mechanisms underlie common phenotypes; these molecular mechanisms include highly conserved genes and networks that may be modified by lineage-specific mutations. However, the existence of deeply conserved mechanisms for social behaviors has not yet been demonstrated. We used a comparative genomics approach to determine whether shared neuromolecular mechanisms could underlie behavioral response to territory intrusion across species spanning a broad phylogenetic range: house mouse (Mus musculus), stickleback fish (Gasterosteus aculeatus), and honey bee (Apis mellifera). Territory intrusion modulated similar brain functional processes in each species, including those associated with hormone-mediated signal transduction and neurodevelopment. Changes in chromosome organization and energy metabolism appear to be core, conserved processes involved in the response to territory intrusion. We also found that several homologous transcription factors that are typically associated with neural development were modulated across all three species, suggesting that shared neuronal effects may involve transcriptional cascades of evolutionarily conserved genes. Furthermore, immunohistochemical analyses of a subset of these transcription factors in mouse again implicated modulation of energy metabolism in the behavioral response. These results provide support for conserved genetic "toolkits" that are used in independent evolutions of the response to social challenge in diverse taxa.genetic hotspot | NF-κB signaling | brain metabolism | aggression S imilar phenotypes can have a shared molecular basis, even among distantly related species (1-3). This phenomenon has been observed for an array of traits, including morphological adaptations like coat color or wing patterning, rapid adaptations like drug resistance, and artificially selected phenological traits like flowering time (reviewed in ref. 2). Shared molecular mechanisms can arise convergently as a result of de novo mutations at genetic hotspots (2) or as a result of conservation. Both of these processes result in "genetic toolkits" or genes that are repeatedly used over evolutionary time to give rise to similar phenotypes (3). The phenomenon of genetic toolkits challenges fundamental notions about evolutionary convergence, conservation, and the origins of biodiversity.The role of genetic toolkits in shaping behavioral phenotypes is unclear (4, 5). Behaviors are typically polygenic (6) and they show great nuance and plasticity within a species, raising the possibility that cross-species similarities in behavior are superficial. Social behaviors in particular present a challenge to the genetic toolkit concept: these behaviors are critical to survival and reproductive success, but across species there is significant variation in the contexts for an...

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Section: Methodsmentioning

confidence: 99%

Neuromolecular responses to social challenge: Common mechanisms across mouse, stickleback fish, and honey bee

Rittschof

Bukhari

Sloofman

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

142

196

View full text Add to dashboard Cite

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“…Alternative methods are needed for capturing genome-wide binding data for many organisms. In vitro TFBS identification methods such as Protein Binding Microarrays (PBM) and High Throughput Systematic Evolution of Ligands by Exponential Enrichment (HT-SELEX) have achieved the highest throughput for deducing TF binding specificities in vitro [9][10][11] , but these methods use short synthetic oligonucleotides lacking secondary DNA modifications and genomic context, both important determinants of selective TF binding in vivo [12][13][14][15][16] . The DAP-seq technique 15 described here employs an in vitro-expressed affinitytagged TF in combination with high-throughput sequencing of a genomic DNA library, allowing for the generation of genome-wide binding site maps reflective of both local sequence context and DNA methylation status.…”

Section: Introductionmentioning

confidence: 99%

Mapping genome-wide transcription-factor binding sites using DAP-seq

Bartlett¹,

O’Malley²,

Huang³

et al. 2017

Nat Protoc

439

285

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In order to enable low-cost, high-throughput generation of cistrome and epicistrome maps for any organism, we developed DNA affinity purification sequencing (DAP-seq), a transcription factor (TF) binding site discovery assay that couples affinity-purified TFs with next-generation sequencing of a genomic DNA library. The method is fast, inexpensive, and more easily scaled than ChIP-seq. DNA libraries are constructed using native genomic DNA from any source of interest, preserving cell-and tissue-specific chemical modifications that are known to impact TF binding (such as DNA methylation) and providing increased specificity compared to in silico motif prediction methods such as protein binding microarrays (PBM) and systematic evolution of ligands by exponential enrichment (SELEX). The resulting DNA library is incubated with an affinity-tagged in vitro expressed TF, and TF-DNA complexes are purified using magnetic separation of the affinity tag. Bound genomic DNA is eluted from the TF and sequenced using next-generation sequencing. Sequence reads are mapped to a reference genome, identifying genome-wide binding locations for each TF assayed, from which sequence motifs can then be

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“…To check whether our findings based on ChIP-seq data are consistent with the TF regulatory motifs' result, we collected recognition motifs of 505 TFs from several studies (9,39,40). We searched the matches of TF motifs near gene transcription start sites and applied RABIT to characterize TF activity in regulating tumor gene expression (SI Appendix, Fig.…”

Section: Significancementioning

confidence: 99%

“…For example, the ENCODE project generated 689 ChIP-seq TF-binding profiles (7,8). Additionally, several studies have profiled the recognition motifs for hundreds of TFs, which could be integrated together to elucidate the genome-wide regulatory network (9). Meanwhile, the TCGA project generated datasets for over 18 cancer types, which include gene expression, copy number alteration (CNA), DNA methylation, and somatic mutation profiles (10).…”

mentioning

confidence: 99%

Inference of transcriptional regulation in cancers

Jiang

Freedman

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Despite the rapid accumulation of tumor-profiling data and transcription factor (TF) ChIP-seq profiles, efforts integrating TF binding with the tumor-profiling data to understand how TFs regulate tumor gene expression are still limited. To systematically search for cancerassociated TFs, we comprehensively integrated 686 ENCODE ChIPseq profiles representing 150 TFs with 7484 TCGA tumor data in 18 cancer types. For efficient and accurate inference on gene regulatory rules across a large number and variety of datasets, we developed an algorithm, RABIT (regression analysis with background integration). In each tumor sample, RABIT tests whether the TF target genes from ChIP-seq show strong differential regulation after controlling for background effect from copy number alteration and DNA methylation. When multiple ChIP-seq profiles are available for a TF, RABIT prioritizes the most relevant ChIP-seq profile in each tumor. In each cancer type, RABIT further tests whether the TF expression and somatic mutation variations are correlated with differential expression patterns of its target genes across tumors. Our predicted TF impact on tumor gene expression is highly consistent with the knowledge from cancer-related gene databases and reveals many previously unidentified aspects of transcriptional regulation in tumor progression. We also applied RABIT on RNAbinding protein motifs and found that some alternative splicing factors could affect tumor-specific gene expression by binding to target gene 3′UTR regions. Thus, RABIT (rabit.dfci.harvard.edu) is a general platform for predicting the oncogenic role of gene expression regulators.regulatory inference | tumor profiling | transcription factor | RNA-binding proteinT umorigenesis is a multistep process requiring alterations in gene expression programs (1, 2). Transcription factors (TFs) are instrumental in driving these gene expression programs, and misregulation of these TFs can result in the acquisition of tumorrelated properties (3). For example, E2F1 is overexpressed in many cancer types and promotes tumor proliferation by regulating expression of genes involved in cell differentiation, metabolism, and development (4). As another example, FOXM1 plays an important role in promoting cell proliferation and cell cycle progression through transcriptional activation of many G2/M-specific genes. Increased FOXM1 gene expression was detected in numerous cancer types, and FOXM1 is a promising therapeutic target for cancer treatment (5). TFs also play critical roles in inducing the tumor microenvironment for metastasis. For example, SNAI1/2, TWIST, and ZEB1/2 orchestrate the expression of genes involved in cell polarity, cell-cell contact, cytoskeleton structure, and extracellular matrix degradation. The joint effect of these TFs promotes cancer cell motility and invasion in the metastatic process (2, 6).With the rapid development of high-throughput technologies, large amounts of datasets have been generated for regulatory proteins. For example, the ENCODE project generated 689 C...

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DNA-Binding Specificities of Human Transcription Factors

Cited by 1,170 publications

References 64 publications

Neuromolecular responses to social challenge: Common mechanisms across mouse, stickleback fish, and honey bee

Neuromolecular responses to social challenge: Common mechanisms across mouse, stickleback fish, and honey bee

Mapping genome-wide transcription-factor binding sites using DAP-seq

Inference of transcriptional regulation in cancers

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