scholarly journals Mapping Transcription Factor Networks By Comparing Tf Binding Locations To Tf Perturbation Responses

2019 ◽  
Author(s):  
Yiming Kang ◽  
Nikhil R. Patel ◽  
Christian Shively ◽  
Pamela Samantha Recio ◽  
Xuhua Chen ◽  
...  

ABSTRACTBackgroundA transcription-factor (TF) network map indicates the direct, functional targets of each TF -- the genes it regulates by binding to their cis-regulatory DNA. Data on the genomic binding locations of each TF and the transcriptional responses to perturbations of its activity, such as overexpressing it, could support TF network mapping. Systematic data sets of both types exist for yeast and for human K562 and HEK293 cells.ResultsIn previous data, most TF binding sites appear to be non-functional, so one cannot take the genes in whose promoters a TF binds as its direct, functional (DF) targets. Taking the genes that are both bound by a TF and responsive to a perturbation of it as its DF targets (intersection algorithm) is also not safe, as we show by deriving a new lower bound on the expected false discovery rate of the intersection algorithm. When there are many non-functional binding sites and many indirect targets, non-functional sites are expected to occur in the cis-regulatory DNA of indirect targets by chance. Dual threshold optimization, a new method for setting significance thresholds on binding and response data, improves the intersection algorithm, as does post-processing perturbation-response data with NetProphet 2.0. A comprehensive new data set measuring the transcriptional response shortly after inducing overexpression of a TF also helps, as does transposon calling cards, a new method for identifying TF binding locations.ConclusionsThe combination of dual threshold optimization and NetProphet greatly expands the high-confidence TF network map in both yeast and human. In yeast, measuring the response shortly after inducing TF overexpression and measuring binding locations by using transposon calling cards improve the network synergistically.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 283-283
Author(s):  
Andre M. Pilon ◽  
Elliott H. Margulies ◽  
Hatice Ozel Abaan ◽  
Amy Werner- Allen ◽  
Tim M. Townes ◽  
...  

Abstract Erythroid Kruppel-Like Factor (EKLF; KLF1) is the founding member of the Kruppel family of transcription factors, with 3 C2H2 zinc-fingers that bind a 9-base consensus sequence (NCNCNCCCN). The functions of EKLF, first identified as an activator of the beta-globin locus, include gene activation and chromatin remodeling. Our knowledge of genes regulated by EKLF is limited, as EKLF-deficient mice die by embryonic day 15 (E15), due to a severe anemia. Analysis of E13.5 wild type and EKLF-deficient fetal liver (FL) erythroid cells revealed that EKLF-deficient cells fail to complete terminal erythroid maturation (Pilon et al. submitted). Coupling chromatin immunoprecipitation and ultra high-throughput massively parallel sequencing (ChIP-seq) is increasingly being used for mapping protein-DNA interactions in vivo on a genome-wide scale. ChIP-seq allows a simultaneous analysis of transcription factor binding in every region of the genome, defining an “interactome”. To elucidate direct EKLF-dependent effects on erythropoiesis, we have combined ChIP-seq with expression array (“transcriptome”) analyses. We feel that integration of ChIP-seq and microarray data can provide us detailed knowledge of the role of EKLF in erythropoiesis. Chromatin was isolated from E13.5 FL cells of mice whose endogenous EKLF gene was replaced with a fully functional HA-tagged EKLF gene. ChIP was performed using a highly specific high affinity anti-HA antibody. A library of EKLF-bound FL chromatin enriched by anti-HA IP was created and subjected to fluorescent in situ sequencing on a Solexa 1G platform, providing 36-base signatures that were mapped to unique sites in the mouse genome, defining the EKLF “interactome.” The frequency with which a given signature appears provides a measurable peak of enrichment. We performed three biological/technical replicates and analyzed each data set individually as well as the combined data. To validate ChIP-seq results, we examined the locus of a known EKLF target gene, a-hemoglobin stabilizing protein (AHSP). Peaks corresponded to previously identified DNase hypersensitive sites, regions of histone hyperacetylation, and sites of promoter-occupancy determined by ChIP-PCR. A genome wide analysis, focusing on the regions with the highest EKLF occupancy revealed a set of 531 locations where high levels EKLF binding occurs. Of these sites, 119 (22%) are located 10 kb or more from the nearest gene and are classified as intergenic EKLF binding sites. Another 78 sites (14.6%) are within 10 kb of an annotated RefSeq gene. A plurality of the binding sites, 222 (42%), are within RefSeq coordinates and are classified as intragenic EKLF binding sites. Microarray profiling of mRNA from sorted, matched populations of dE13.5 WT and EKLF-deficient FL erythroid progenitor cells showed dysregulation of >3000 genes (p<0.05). Ingenuity Pathways Analysis (IPA) of the >3000 dysregulated mRNAs indicated significant alteration of a cell cycle-control network, centered about the transcription factor, E2f2. We confirmed significantly decreased E2f2 mRNA and protein levels by real-time PCR and Western blot, respectively; demonstrated that EKLF-deficient FL cells accumulate in G0/G1 by cell cycle analysis; and verified EKLF-binding to motifs within the E2f2 promoter by ChIP-PCR and analysis of the ChIP Seq data. We hypothesized that only a subset of the 3000 dysregulated genes would be direct EKLF targets. We limited the ChIP-seq library to display the top 5% most frequently represented fragments across the genome, and applied this criterion to the network of dysregulated mRNAs in the IPA cell cycle network. ChIP-seq identified peaks of EKLF association with 60% of the loci in this pathway. However, consistent with the role of EKLF as a transcriptional activator, 95% of the occupied genomic loci corresponded to mRNAs whose expression in EKLF-deficient FL cells was significantly decreased (p<0.05). The majority (59%) of these EKLF-bound sites were located at intragenic sites (i.e., introns), while a minority (15% and 26%) were found adjacent to the genes or in intergenic regions. We have shown that both the AHSP and E2f2 loci require EKLF to cause the locus to become activated and sensitive to DNase I digestion in erythroid cells. Based on the increased frequency of intragenic EKLF-binding sites, particularly in genes of the cell cycle network, we propose that the occupancy of intragenic sites by EKLF may facilitate chromatin modification.


2003 ◽  
Vol 284 (4) ◽  
pp. R1147-R1150 ◽  
Author(s):  
Ralf Mrowka ◽  
Karola Steinhage ◽  
Andreas Patzak ◽  
Pontus B. Persson

Evolutionary pressure has resulted in the conservation of certain nucleotide sequences. These conserved regions are potentially important for certain functions. Here we give an example of a comparison between noncoding sequences combined with other independent database information to shed light onto the regulation of the renin gene, a gene that has great importance for cardiovascular and renal homeostasis. To combine the information regarding conservation and weight matrices of transcription factor (TF) binding sites, an algorithm was developed (TFprofile). Notably, a local peak in the resulting binding profile coincides with a previously experimentally identified regulatory region for the renin gene. The existence of further peaks in the binding profile in the conserved 3.9-kb-long hRENc DNA block upstream of the renin gene suggests additional regions of potential importance for gene regulation. The algorithm TFprofile may be used to integrate information on cross-species evolutionary conservation and aspects of TF binding characteristics to provide putative regulatory DNA regions for experimental verification.


2007 ◽  
Vol 05 (01) ◽  
pp. 105-116 ◽  
Author(s):  
MARKUS T. FRIBERG

We present an algorithm for predicting transcription factor binding sites based on ChIP-chip and phylogenetic footprinting data. Our algorithm is robust against low promoter sequence similarity and motif rearrangements, because it does not depend on multiple sequence alignments. This, in turn, allows us to incorporate information from more distant species. Representative random data sets are used to estimate the score significance. Our algorithm is fully automatic, and does not require human intervention. On a recent S. cerevisiae data set, it achieves higher accuracy than the previously best algorithms. Adaptive ChIP-chip threshold and the modular positional bias score are two general features of our algorithm that increase motif prediction accuracy and could be implemented in other algorithms as well. In addition, since our algorithm works partly orthogonally to other algorithms, combining several algorithms can increase prediction accuracy even further. Specifically, our method finds 6 motifs not found by the 2nd best algorithm.


2021 ◽  
Author(s):  
Jasmin Moneer ◽  
Stefan Siebert ◽  
Stefan Krebs ◽  
Jack Cazet ◽  
Andrea Prexl ◽  
...  

In Hydra, Notch inhibition causes defects in head patterning and prevents differentiation of proliferating nematocyte progenitor cells into mature nematocytes. To understand the molecular mechanisms by which the Notch pathway regulates these processes we performed RNAseq and identified genes that are differentially regulated in response to 48 hours of treating the animals with the Notch-inhibitor DAPT. To identify candidate direct regulators of Notch-signalling, we profiled gene expression changes that occur during subsequent restoration of Notch-activity and performed promoter analyses to identify RBPJ transcription factor binding sites in the regulatory regions of Notch-responsive genes. Interrogating the available single cell sequencing data set revealed gene expression patterns of Notch-regulated Hydra genes. By these analyses a comprehensive picture of the molecular pathways regulated by Notch signalling in head patterning and in interstitial cell differentiation in Hydra emerged. As prime candidates for direct Notch-target genes, in addition to HyHes, we suggest Sp5 and HyAlx. They rapidly recovered their expression levels after DAPT removal and possess Notch-responsive RBPJ transcription factor binding sites in their regulatory regions.


2017 ◽  
Author(s):  
Mark J. Berger ◽  
Aaron M. Wenger ◽  
Harendra Guturu ◽  
Gill Bejerano

AbstractGenetic variation in cis-regulatory elements is thought to be a major driving force in morphological and physiological change. However, identifying transcription factor binding events which code for complex traits remains a challenge, motivating novel means of detecting putatively important binding events. Using a curated set of 1,154 high-quality transcription factor motifs, we demonstrate that independently eroded binding sites are enriched for independently lost traits in three distinct pairs of placental mammals. We show that these independently eroded events pinpoint the loss of hindlimbs in dolphin and manatee, degradation of vision in naked mole-rat and star-nosed mole, and the loss of scrotum in white rhinoceros and Weddell seal. Our study exhibits a novel methodology to detect cis-regulatory mutations which help explain a portion of the molecular mechanism underlying complex trait formation and loss.Author SummaryEvolution has produced an astounding variety of species with incredibly diverse phenotypes. A central question in evolutionary developmental biology is how (and which) DNA evolves to encode all of these different traits. A prevailing hypothesis is that changes in regulatory DNA, short stretches of DNA which control the expression of protein-coding genes, drive important differences in trait formation between species. The basic building block of regulatory DNA is thought to be transcription factor binding sites, shortl genomic sequences which attract proteins whose central role is to control the rate of transcription. In this study, we asked whether the independent erosion of otherwise highly conserved transcription factor binding sites points to a trait shared between species which have undergone similar adaptations. We show that our method is able to point to the loss of hindlimbs in dolphin and manatee, poor vision in naked mole-rat and star-nosed mole, and loss of scrotum in Weddell seal and white rhinoceros. Overall, our study exhibits a means of detecting evolutionarily important genomic regions which help explain a portion of complex trait loss and retention.


2017 ◽  
Author(s):  
Ben J. Vincent ◽  
Max V. Staller ◽  
Francheska Lopez-Rivera ◽  
Meghan D.J. Bragdon ◽  
Zeba Wunderlich ◽  
...  

AbstractHunchback is a bifunctional transcription factor that can activate and repress gene expression in Drosophila development. We investigated the regulatory DNA sequence features that control Hunchback function by perturbing enhancers for one of its target genes, even-skipped. While Hunchback directly represses the eve stripe 3+7 enhancer, we found that in the eve stripe 2+7 enhancer, Hunchback repression is prevented by Caudal binding—this relationship is called counter-repression. We found evidence that this relationship is conserved by comparing predicted binding sites for Hunchback and Caudal across orthologous eve stripe 2 enhancers. These results alter the textbook view of eve stripe 2 regulation wherein Hb is depicted as a direct activator. Instead, to generate stripe 2, Hunchback repression must be counteracted by Caudal binding. We discuss the implications of this interaction for eve stripe 2 regulation and evolution.


Author(s):  
Erik W van Zwet ◽  
Katherina J Kechris ◽  
Peter J Bickel ◽  
Michael B. Eisen

Transcription factors and many other DNA-binding proteins recognize more than one specific sequence. Among sequences recognized by a given DNA-binding protein, different positions exhibit varying degrees of conservation. The reason is that base pairs that are more extensively contacted by the protein tend to be more conserved. This observation can be used in the discovery of transcription factor binding sites. Here we present a rigorous means to accomplish this. In particular, we constrain the order of the information (entropy) in the columns of the position specific weight matrix (PWM) which characterizes the motif being sought. We then show how to compute the maximum likelihood estimate of a PWM under such order restrictions. This computation is easily integrated with the EM algorithm or the Gibbs sampler to enhance performance in the search for motifs in unaligned sequences. We demonstrate our method on a well-known data set of binding sites of the transcription factor Crp in E. coli.


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