Transcription factor expression landscape in Drosophila embryonic cell lines.

BACKGROUND: Transcription factor (TF) proteins are a key component of the gene regulatory networks that control cellular fates and function. TFs bind DNA regulatory elements in a sequence-specific manner and modulate target gene expression through combinatorial interactions with each other, cofactors, and chromatin-modifying proteins. Large-scale studies over the last two decades have helped shed light on the complex network of TFs that regulate development in Drosophila melanogaster. RESULTS: Here, we present a detailed characterization of expression of all known and predicted Drosophila TFs in two well-established embryonic cell lines, Kc167 and S2 cells. Using deep coverage RNA sequencing approaches we investigate the transcriptional profile of all 707 TF coding genes in both cell types. Only 103 TFs have no detectable expression in either cell line and 493 TFs have a read count of 5 or greater in at least one of the cell lines. The 493 TFs belong to 54 different DNA-binding domain families, with significant enrichment of those in the zf-C2H2 family. We identified 123 differentially expressed genes, with 57 expressed at significantly higher levels in Kc167 cells than S2 cells, and 66 expressed at significantly lower levels in Kc167 cells than S2 cells. Network mapping reveals that many of these TFs are crucial components of regulatory networks involved in cell proliferation, cell-cell signaling pathways, and eye development. CONCLUSIONS: We produced a reference TF coding gene expression dataset in the extensively studied Drosophila Kc167 and S2 embryonic cell lines, and gained insight into the TF regulatory networks that control the activity of these cells.

Rapid and efficient purification of Drosophila homeodomain transcription factors for biophysical characterization.

Homeodomain transcription factors (HD TFs) are a large class of evolutionarily conserved DNA binding proteins that contain a basic 60-amino acid region required for binding to specific DNA sites. In Drosophila melanogaster, many of these HD TFs are expressed in the early embryo and control transcription of target genes in development through their interaction with cis-regulatory modules. Previous studies where some of the Drosophila HD TFs were purified required the use of strong denaturants (i.e. 6 M urea) and multiple chromatography columns, making the downstream biochemical examination of the isolated protein difficult. To circumvent these obstacles, we have developed a streamlined expression and purification protocol to produce large yields of Drosophila HD TFs. Using the HD TFs FUSHI-TARAZU (FTZ), ANTENNAPEDIA (ANTP), ABDOMINAL-A (ABD-A), ABDOMINAL-B (ABD-B), and ULTRABITHORAX (UBX) as examples, we demonstrate that our 3-day protocol involving the overexpression of His6-SUMO fusion constructs in E. coli followed by a Ni2+-IMAC, SUMO-tag cleavage with the SUMO protease Ulp1, and a heparin column purification produces pure, soluble protein in biological buffers around pH 7 in the absence of denaturants. Electrophoretic mobility shift assays (EMSA) confirm that the purified HD proteins are functional and nuclear magnetic resonance (NMR) spectra confirm that the purified HDs are well-folded. These purified HD TFs can be used in future biophysical experiments to structurally and biochemically characterize how and why these HD TFs bind to different DNA sequences and further probe how nucleotide differences contribute to TF-DNA specificity in the HD family.

The dynamic DNA methylation cycle from egg to sperm in the honey bee Apis mellifera.

In honey bees (Apis mellifera), the epigenetic mark of DNA methylation is central to the developmental regulation of caste differentiation, but may also be involved in additional biological functions. In this study, we examine the whole genome methylation profiles of three stages of the haploid honey bee genome: unfertilised eggs, the adult drones that develop from these eggs and the sperm produced by these drones. These methylomes reveal distinct patterns of methylation. Eggs and sperm show 381 genes with significantly different CpG methylation patterns, with the vast majority being more methylated in eggs. Adult drones show greatly reduced levels of methylation across the genome when compared with both gamete samples. This suggests a dynamic cycle of methylation loss and gain through the development of the drone and during spermatogenesis. Although fluxes in methylation during embryogenesis may account for some of the differentially methylated sites, the distinct methylation patterns at some genes suggest parent-specific epigenetic marking in the gametes. Extensive germ line methylation of some genes possibly explains the lower-than-expected frequency of CpG sites in these genes. We discuss the potential developmental and evolutionary implications of methylation in eggs and sperm in this eusocial insect species.

Parent-of-origin effects on genome-wide DNA methylation in the Cape honey bee (Apis mellifera capensis) may be confounded by allele-specific methylation.

BACKGROUND: Intersexual genomic conflict sometimes leads to unequal expression of paternal and maternal alleles in offspring, resulting in parent-of-origin effects. In honey bees reciprocal crosses can show strong parent-of-origin effects, supporting theoretical predictions that genomic imprinting occurs in this species. Mechanisms behind imprinting in honey bees are unclear but differential DNA methylation in eggs and sperm suggests that DNA methylation could be involved. Nonetheless, because DNA methylation is multifunctional, it is difficult to separate imprinting from other roles of methylation. Here we use a novel approach to investigate parent-of-origin DNA methylation in honey bees. In the subspecies Apis mellifera capensis, reproduction of females occurs either sexually by fertilization of eggs with sperm, or via thelytokous parthenogenesis, producing female embryos derived from two maternal genomes. RESULTS: We compared genome-wide methylation patterns of sexually-produced, diploid embryos laid by a queen, with parthenogenetically-produced diploid embryos laid by her daughters. Thelytokous embryos inheriting two maternal genomes had fewer hypermethylated genes compared to fertilized embryos, supporting the prediction that fertilized embryos have increased methylation due to inheritance of a paternal genome. However, bisulfite PCR and sequencing of a differentially methylated gene, Stan (GB18207) showed strong allele-specific methylation that was maintained in both fertilized and thelytokous embryos. For this gene, methylation was associated with haplotype, not parent of origin. CONCLUSIONS: The results of our study are consistent with predictions from the kin theory of genomic imprinting. However, our demonstration of allele-specific methylation based on sequence shows that genome-wide differential methylation studies can potentially confound imprinting and allele-specific methylation. It further suggests that methylation patterns are heritable or that specific sequence motifs are targets for methylation in some genes.

MARZ: an algorithm to combinatorially analyze gapped n-mer models of transcription factor binding.

BACKGROUND: A key challenge in understanding the molecular mechanisms that control gene regulation is the characterization of the specificity with which transcription factor proteins bind to specific DNA sequences. A number of computational approaches have been developed to examine these interactions, including simple mononucleotide and dinucleotide position weight matrix models. RESULTS: Here we develop a novel, unbiased computational algorithm, MARZ, that systematically analyzes all possible gapped matrices across a fixed number of nucleotides. In addition, to evaluate the ability of these matrix models to predict in vivo binding sites, we utilize a new scoring system and, in combination with established scoring methods and statistical analysis, test the performance of 32 different gapped matrices on the well characterized HUNCHBACK transcription factor in Drosophila. CONCLUSIONS: Our results indicate that in many cases gapped matrix models can outperform traditional models, but that the relative strength of the binding sites considered in the analysis can profoundly influence the predictive ability of specific models.

A parent-of-origin effect on honeybee worker ovary size.

Apis mellifera capensis is unique among honeybees in that unmated workers can produce pseudo-clonal female offspring via thelytokous parthenogenesis. Workers use this ability to compete among themselves and with their queen to be the mother of new queens. Males could therefore enhance their reproductive success by imprinting genes that enhance fertility in their daughter workers. This possibility sets the scene for intragenomic conflict between queens and drones over worker reproductive traits. Here, we show a strong parent-of-origin effect for ovary size (number of ovarioles) in reciprocal crosses between two honeybee subspecies, A. m. capensis and Apis mellifera scutellata. In this cross, workers with an A. m. capensis father had 30% more ovarioles than genotypically matched workers with an A. m. scutellata father. Other traits we measured (worker weight at emergence and the presence/absence of a spermatheca) are influenced more by rearing conditions than by parent-of-origin effects. Our study is the first to show a strong epigenetic (or, less likely, cytoplasmic maternal) effect for a reproductive trait in the honeybee and suggests that a search for parent-of-origin effects in other social insects may be fruitful.

Flanking sequence context-dependent transcription factor binding in early Drosophila development.

BACKGROUND: Gene expression in the Drosophila embryo is controlled by functional interactions between a large network of protein transcription factors (TFs) and specific sequences in DNA cis-regulatory modules (CRMs). The binding site sequences for any TF can be experimentally determined and represented in a position weight matrix (PWM). PWMs can then be used to predict the location of TF binding sites in other regions of the genome, although there are limitations to this approach as currently implemented. RESULTS: In this proof-of-principle study, we analyze 127 CRMs and focus on four TFs that control transcription of target genes along the anterio-posterior axis of the embryo early in development. For all four of these TFs, there is some degree of conserved flanking sequence that extends beyond the predicted binding regions. A potential role for these conserved flanking sequences may be to enhance the specificity of TF binding, as the abundance of these sequences is greatly diminished when we examine only predicted high-affinity binding sites. CONCLUSIONS: Expanding PWMs to include sequence context-dependence will increase the information content in PWMs and facilitate a more efficient functional identification and dissection of CRMs.

Dissecting the regulatory switches of development: lessons from enhancer evolution in Drosophila.

Cis-regulatory modules are non-protein-coding regions of DNA essential for the control of gene expression. One class of regulatory modules is embryonic enhancers, which drive gene expression during development as a result of transcription factor protein binding at the enhancer sequences. Recent comparative studies have begun to investigate the evolution of the sequence architecture within enhancers. These analyses are illuminating the way that developmental biologists think about enhancers by revealing their molecular mechanism of function.

Transcriptome profile in Drosophila Kc and S2 embryonic cell lines.

Drosophila melanogaster cell lines are an important resource for a range of studies spanning genomics, molecular genetics, and cell biology. Amongst these valuable lines are Kc167 (Kc) and Schneider 2 (S2) cells, which were originally isolated in the late 1960s from embryonic sources and have been used extensively to investigate a broad spectrum of biological activities including cell-cell signaling and immune system function. Whole-genome tiling microarray analysis of total RNA from these two cell types was performed as part of the modENCODE project over a decade ago and revealed that they share a number of gene expression features. Here, we expand on these earlier studies by using deep-coverage RNA-sequencing approaches to investigate the transcriptional profile in Kc and S2 cells in detail. Comparison of the transcriptomes reveals that ∼75% of the 13,919 annotated genes are expressed at a detectable level in at least one of the cell lines, with the majority of these genes expressed at high levels in both cell lines. Despite the overall similarity of the transcriptional landscape in the two cell types, 2,588 differentially expressed genes are identified. Many of the genes with the largest fold change are known only by their "CG" designations, indicating that the molecular control of Kc and S2 cell identity may be regulated in part by a cohort of relatively uncharacterized genes. Our data also indicate that both cell lines have distinct hemocyte-like identities, but share active signaling pathways and express a number of genes in the network responsible for dorsal-ventral patterning of the early embryo.

Investigating the sequence landscape in the Drosophila initiator core promoter element using an enhanced MARZ algorithm.

The core promoter elements are important DNA sequences for the regulation of RNA polymerase II transcription in eukaryotic cells. Despite the broad evolutionary conservation of these elements, there is extensive variation in the nucleotide composition of the actual sequences. In this study, we aim to improve our understanding of the complexity of this sequence variation in the TATA box and initiator core promoter elements in Drosophila melanogaster. Using computational approaches, including an enhanced version of our previously developed MARZ algorithm that utilizes gapped nucleotide matrices, several sequence landscape features are uncovered, including an interdependency between the nucleotides in position 2 and 5 in the initiator. Incorporating this information in an expanded MARZ algorithm improves predictive performance for the identification of the initiator element. Overall our results demonstrate the need to carefully consider detailed sequence composition features in core promoter elements in order to make more robust and accurate bioinformatic predictions.

The Dictyostelium discoideum genome lacks significant DNA methylation and uncovers palindromic sequences as a source of false positives in bisulfite sequencing.

DNA methylation, the addition of a methyl (CH3) group to a cytosine residue, is an evolutionarily conserved epigenetic mark involved in a number of different biological functions in eukaryotes, including transcriptional regulation, chromatin structural organization, cellular differentiation and development. In the social amoeba Dictyostelium, previous studies have shown the existence of a DNA methyltransferase (DNMA) belonging to the DNMT2 family, but the extent and function of 5-methylcytosine in the genome are unclear. Here, we present the whole genome DNA methylation profile of Dictyostelium discoideum using deep coverage replicate sequencing of bisulfite-converted gDNA extracted from post-starvation cells. We find an overall very low number of sites with any detectable level of DNA methylation, occurring at significant levels in only 303-3432 cytosines out of the ∼7.5 million total cytosines in the genome depending on the replicate. Furthermore, a knockout of the DNMA enzyme leads to no overall decrease in DNA methylation. Of the identified sites, significant methylation is only detected at 11 sites in all four of the methylomes analyzed. Targeted bisulfite PCR sequencing and computational analysis demonstrate that the methylation profile does not change during development and that these 11 cytosines are most likely false positives generated by protection from bisulfite conversion due to their location in hairpin-forming palindromic DNA sequences. Our data therefore provide evidence that there is no significant DNA methylation in Dictyostelium before fruiting body formation and identify a reproducible experimental artifact from bisulfite sequencing.

Molecular dissection of cis-regulatory modules at the Drosophila bithorax complex reveals critical transcription factor signature motifs.

At the Drosophila melanogaster bithorax complex (BX-C) over 330kb of intergenic DNA is responsible for directing the transcription of just three homeotic (Hox) genes during embryonic development. A number of distinct enhancer cis-regulatory modules (CRMs) are responsible for controlling the specific expression patterns of the Hox genes in the BX-C. While it has proven possible to identify orthologs of known BX-C CRMs in different Drosophila species using overall sequence conservation, this approach has not proven sufficiently effective for identifying novel CRMs or defining the key functional sequences within enhancer CRMs. Here we demonstrate that the specific spatial clustering of transcription factor (TF) binding sites is important for BX-C enhancer activity. A bioinformatic search for combinations of putative TF binding sites in the BX-C suggests that simple clustering of binding sites is frequently not indicative of enhancer activity. However, through molecular dissection and evolutionary comparison across the Drosophila genus we discovered that specific TF binding site clustering patterns are an important feature of three known BX-C enhancers. Sub-regions of the defined IAB5 and IAB7b enhancers were both found to contain an evolutionarily conserved signature motif of clustered TF binding sites which is critical for the functional activity of the enhancers. Together, these results indicate that the spatial organization of specific activator and repressor binding sites within BX-C enhancers is of greater importance than overall sequence conservation and is indicative of enhancer functional activity.

Functional evolution of cis-regulatory modules at a homeotic gene in Drosophila.

It is a long-held belief in evolutionary biology that the rate of molecular evolution for a given DNA sequence is inversely related to the level of functional constraint. This belief holds true for the protein-coding homeotic (Hox) genes originally discovered in Drosophila melanogaster. Expression of the Hox genes in Drosophila embryos is essential for body patterning and is controlled by an extensive array of cis-regulatory modules (CRMs). How the regulatory modules functionally evolve in different species is not clear. A comparison of the CRMs for the Abdominal-B gene from different Drosophila species reveals relatively low levels of overall sequence conservation. However, embryonic enhancer CRMs from other Drosophila species direct transgenic reporter gene expression in the same spatial and temporal patterns during development as their D. melanogaster orthologs. Bioinformatic analysis reveals the presence of short conserved sequences within defined CRMs, representing gap and pair-rule transcription factor binding sites. One predicted binding site for the gap transcription factor KRUPPEL in the IAB5 CRM was found to be altered in Superabdominal (Sab) mutations. In Sab mutant flies, the third abdominal segment is transformed into a copy of the fifth abdominal segment. A model for KRUPPEL-mediated repression at this binding site is presented. These findings challenge our current understanding of the relationship between sequence evolution at the molecular level and functional activity of a CRM. While the overall sequence conservation at Drosophila CRMs is not distinctive from neighboring genomic regions, functionally critical transcription factor binding sites within embryonic enhancer CRMs are highly conserved. These results have implications for understanding mechanisms of gene expression during embryonic development, enhancer function, and the molecular evolution of eukaryotic regulatory modules.

Fitting thermodynamic-based models: Incorporating parameter sensitivity improves the performance of an evolutionary algorithm.

A detailed comprehension of transcriptional regulation is critical to understanding the genetic control of development and disease across many different organisms. To more fully investigate the complex molecular interactions controlling the precise expression of genes, many groups have constructed mathematical models to complement their experimental approaches. A critical step in such studies is choosing the most appropriate parameter estimation algorithm to enable detailed analysis of the parameters that contribute to the models. In this study, we develop a novel set of evolutionary algorithms that use a pseudo-random Sobol Set to construct the initial population and incorporate parameter sensitivities into the adaptation of mutation rates, using local, global, and hybrid strategies. Comparison of the performance of these new algorithms to a number of current state-of-the-art global parameter estimation algorithms on a range of continuous test functions, as well as synthetic biological data representing models of gene regulatory systems, reveals improved performance of the new algorithms in terms of runtime, error and reproducibility. In addition, by analyzing the ability of these algorithms to fit datasets of varying quality, we provide the experimentalist with a guide to how the algorithms perform across a range of noisy data. These results demonstrate the improved performance of the new set of parameter estimation algorithms and facilitate meaningful integration of model parameters and predictions in our understanding of the molecular mechanisms of gene regulation.

Analyzing the stability of gene expression using a simple reaction-diffusion model in an early Drosophila embryo.

In all complex organisms, the precise levels and timing of gene expression controls vital biological processes. In higher eukaryotes, including the fruit fly Drosophila melanogaster, the complex molecular control of transcription (the synthesis of RNA from DNA) and translation (the synthesis of proteins from RNA) events driving this gene expression are not fully understood. In particular, for Drosophila melanogaster, there is a plethora of experimental data, including quantitative measurements of both RNA and protein concentrations, but the precise mechanisms that control the dynamics of gene expression during early development and the processes which lead to steady-state levels of certain proteins remain elusive. This study analyzes a current mathematical modeling approach in an attempt to better understand the long-term behavior of gene regulation. The model is a modified reaction-diffusion equation which has been previously employed in predicting gene expression levels and studying the relative contributions of transcription and translation events to protein abundance [10,11,24]. Here, we use Matrix Algebra and Analysis techniques to study the stability of the gene expression system and analyze equilibria, using very general assumptions regarding the parameter values incorporated into the model. We prove that, given realistic biological parameter values, the system will result in a unique, stable equilibrium solution. Additionally, we give an example of this long-term behavior using the model alongside actual experimental data obtained from Drosophila embryos.

Methylation-dependent silencing at the H19 imprinting control region by MeCP2.

Methylation of CpG dinucleotides is correlated with transcriptional repression of genes, including imprinted genes. In the case of the imprinted H19 gene, a 2 kb imprinting control region (ICR) is subject to differential methylation, as it is methylated only on the silenced paternal allele. This region has previously been shown to act as a silencer element at the endogenous locus. The proteins that bind at the H19 differentially methylated domain (DMD) and mediate transcriptional silencing have yet to be identified, although a family of proteins containing a methyl-CpG-binding domain (MBD), of which MeCP2 is the best characterised, are obvious candidates. MeCP2 can bind to a single methylated CpG dinucleotide through its MBD and also contains a transcriptional repression domain (TRD). The TRD interacts with Sin3a and histone deacetylases (HDACs) in vivo, forming a repressive complex. Here we show that MeCP2 is recruited to the H19 DMD in vivo and can silence a reporter gene regulated by the H19 DMD in a methylation-dependent manner. This repression can be alleviated by deletion of the TRD from MeCP2 or by inhibition of HDAC activity. These data indicate that transcriptional silencing from the H19 ICR involves recruitment of MeCP2 and presumably an associated protein complex with deacetylase activity. This complex may also be recruited to the ICR in vivo, resulting in a compact, repressive chromatin structure capable of silencing the paternal H19 allele.

Spatial distribution of predicted transcription factor binding sites in Drosophila ChIP peaks.

In the development of the Drosophila embryo, gene expression is directed by the sequence-specific interactions of a large network of protein transcription factors (TFs) and DNA cis-regulatory binding sites. Once the identity of the typically 8-10bp binding sites for any given TF has been determined by one of several experimental procedures, the sequences can be represented in a position weight matrix (PWM) and used to predict the location of additional TF binding sites elsewhere in the genome. Often, alignments of large (>200bp) genomic fragments that have been experimentally determined to bind the TF of interest in Chromatin Immunoprecipitation (ChIP) studies are trimmed under the assumption that the majority of the binding sites are located near the center of all the aligned fragments. In this study, ChIP/chip datasets are analyzed using the corresponding PWMs for the well-studied TFs; CAUDAL, HUNCHBACK, KNIRPS and KRUPPEL, to determine the distribution of predicted binding sites. All four TFs are critical regulators of gene expression along the anterio-posterior axis in early Drosophila development. For all four TFs, the ChIP peaks contain multiple binding sites that are broadly distributed across the genomic region represented by the peak, regardless of the prediction stringency criteria used. This result suggests that ChIP peak trimming may exclude functional binding sites from subsequent analyses.

Nucleotide Interdependency in Transcription Factor Binding Sites in the Drosophila Genome.

A long-standing objective in modern biology is to characterize the molecular components that drive the development of an organism. At the heart of eukaryotic development lies gene regulation. On the molecular level, much of the research in this field has focused on the binding of transcription factors (TFs) to regulatory regions in the genome known as cis-regulatory modules (CRMs). However, relatively little is known about the sequence-specific binding preferences of many TFs, especially with respect to the possible interdependencies between the nucleotides that make up binding sites. A particular limitation of many existing algorithms that aim to predict binding site sequences is that they do not allow for dependencies between nonadjacent nucleotides. In this study, we use a recently developed computational algorithm, MARZ, to compare binding site sequences using 32 distinct models in a systematic and unbiased approach to explore nucleotide dependencies within binding sites for 15 distinct TFs known to be critical to Drosophila development. Our results indicate that many of these proteins have varying levels of nucleotide interdependencies within their DNA recognition sequences, and that, in some cases, models that account for these dependencies greatly outperform traditional models that are used to predict binding sites. We also directly compare the ability of different models to identify the known KRUPPEL TF binding sites in CRMs and demonstrate that a more complex model that accounts for nucleotide interdependencies performs better when compared with simple models. This ability to identify TFs with critical nucleotide interdependencies in their binding sites will lead to a deeper understanding of how these molecular characteristics contribute to the architecture of CRMs and the precise regulation of transcription during organismal development.

Global sensitivity analysis of a dynamic model for gene expression in Drosophila embryos.

It is well known that gene regulation is a tightly controlled process in early organismal development. However, the roles of key processes involved in this regulation, such as transcription and translation, are less well understood, and mathematical modeling approaches in this field are still in their infancy. In recent studies, biologists have taken precise measurements of protein and mRNA abundance to determine the relative contributions of key factors involved in regulating protein levels in mammalian cells. We now approach this question from a mathematical modeling perspective. In this study, we use a simple dynamic mathematical model that incorporates terms representing transcription, translation, mRNA and protein decay, and diffusion in an early Drosophila embryo. We perform global sensitivity analyses on this model using various different initial conditions and spatial and temporal outputs. Our results indicate that transcription and translation are often the key parameters to determine protein abundance. This observation is in close agreement with the experimental results from mammalian cells for various initial conditions at particular time points, suggesting that a simple dynamic model can capture the qualitative behavior of a gene. Additionally, we find that parameter sensitivites are temporally dynamic, illustrating the importance of conducting a thorough global sensitivity analysis across multiple time points when analyzing mathematical models of gene regulation.

Deciphering the combinatorial architecture of a Drosophila homeotic gene enhancer.

In Drosophila, the 330 kb bithorax complex regulates cellular differentiation along the anterior­posterior axis during development in the thorax and abdomen and is comprised of three homeotic genes: Ultrabithorax, abdominal-A, and Abdominal-B. The expression of each of these genes is in turn controlled through interactions between transcription factors and a number of cis-regulatory modules in the neighboring intergenic regions. In this study, we examine how the sequence architecture of transcription factor binding sites mediates the functional activity of one of these cis-regulatory modules. Using computational, mathematical modeling and experimental molecular genetic approaches we investigate the IAB7b enhancer, which regulates Abdominal-B expression specifically in the presumptive seventh and ninth abdominal segments of the early embryo. A cross-species comparison of the IAB7b enhancer reveals an evolutionarily conserved signature motif containing two FUSHI-TARAZU activator transcription factor binding sites. We find that the transcriptional repressors KNIRPS, KRUPPEL and GIANT are able to restrict reporter gene expression to the posterior abdominal segments, using different molecular mechanisms including short-range repression and competitive binding. Additionally, we show the functional importance of the spacing between the two FUSHI-TARAZU binding sites and discuss the potential importance of cooperativity for transcriptional activation. Our results demonstrate that the transcriptional output of the IAB7b cis-regulatory module relies on a complex set of combinatorial inputs mediated by specific transcription factor binding and that the sequence architecture at this enhancer is critical to maintain robust regulatory function.