Biology subjects

Mahony, S.

Publications and source records attributed to Mahony, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Oncofetal RNA-binding proteins of IGF2BP family suppress IRF-3 and NF-kB dependent transcription downstream of cytosolic RNA sensors

Activation of innate inflammatory signaling and tumor-specific antigen presentation in cancer cells provides a foundation for anti-cancer immunotherapies. Here, we show that the insulin-like growth factor 2 mRNA-binding proteins (IGF2BP1, IGF2BP2, and IGF2BP3), which are upregulated across diverse human malignancies, including acute myeloid leukemia (AML), suppress RNA-sensing pattern recognition receptor signaling and downstream ISRE-and NF-{kappa}B-dependent transcription. Among these pathways, RIG-I signaling is particularly sensitive to IGF2BP-mediated inhibition. This suppressive effect is strongest when all three IGF2BP paralogs are co-expressed, especially in embryonic-like hematoendothelial cells and leukemia stem cells. Mechanistically, IGF2BPs suppress innate immune signaling by directly binding to TNFAIP3 mRNA and promoting its expression. Consequently, inhibition of IGF2BPs activates innate immune signaling and induces MHC class I gene expression in AML cells, highlighting IGF2BPs as promising therapeutic targets to enhance RIG-I- and TLR-based cancer immunotherapies. HighlightsO_LIIGF2BP family of proteins regulate PRR responses C_LIO_LIIGF2BP levels affect chromatin accessibility and pan-transcriptome C_LIO_LISV40 large T antigen induces de novo expression of IGF2BPs C_LIO_LITNFAIP3 mRNA levels and stability are regulated by IGF2BPs C_LI

cancer biology↗

bioRxiv2026

Widespread Regulatory Turnover Across Human Segmental Duplications

Segmental duplications (SDs) are a pervasive feature of eukaryotic genomes, enabling genomic innovation via the duplication of genes and cis-regulatory elements. However, the regulatory mechanisms that govern these regions of the genome after duplication are not well understood. The repetitive nature of SDs pose problems for short-read assays such as ChIP-seq and DNase-seq as they create reads that map to more than one location along the genome. Moreover, the newest Telomere-to-Telomere (T2T) human genome assembly has revealed previously unknown segmental duplications. In this study, we used the Telomere-to-Telomere genome assembly along with the probabilistic allocation of multi-mapped reads by our software Allo to better understand the regulatory mechanisms governing segmental duplications in the human genome. Using 134 transcription factor ChIP-seq datasets in GM12878, we found that transcription factor binding sites within segmental duplications are rarely conserved across paralogous copies. Similarly, chromatin states defined via histone ChIP-seq datasets are also poorly conserved across segmentally duplicated regions. In contrast, paralogous genes within SDs exhibit highly correlated expression patterns. Hi-C analysis revealed that many SD paralogs have higher than expected spatial proximity, suggesting that three-dimensional genome organization may buffer transcriptional divergence following duplication despite the loss of cis-regulatory regions. Together, our results suggest that regulatory regions undergo rapid turnover following segmental duplication, but the regulatory impact may be buffered by spatial proximity within the nucleus. Tissue-specific genes and transcription factors showed greater divergence, highlighting the role of SDs in expanding specialized cellular functions.

bioinformatics↗

bioRxiv2026

TPCAV: Interpreting deep learning genomics models via concept attribution

Interpreting genomics deep learning models remains challenging. Existing feature attribution methods are largely restricted to one-hot DNA inputs and therefore cannot assess the influence of more general genomic features such as chromatin states or genomic repeats. Concept attribution methods offer an input-agnostic global interpretation framework, yet they have not been systematically applied to interpret neural network applications in genomics. We present the first application of concept attribution to interpret genomics deep learning models by adapting the Testing with Concept Activation Vectors (TCAV) method. We improve upon the original TCAV method by incorporating a PCA-based decorrelation transformation to address correlated and redundant embedding features commonly observed in genomics deep learning models, resulting in the Testing with PCA-projected Concept Activation Vectors (TPCAV) approach. We also introduce a strategy for extracting concept-specific input attribution maps. We evaluate our approach by interpreting influential biological concepts across a diverse set of genomics models spanning multiple input representations and prediction tasks. We demonstrate that TPCAV provides comparable motif feature interpretation to TF-MoDISco on one-hot encoded DNA-based transcription factor binding prediction models. TPCAV also enables robust interpretive analysis of how more general biological concepts such as repetitive elements and chromatin state annotations contribute towards predictions. TPCAV uniquely generalizes to interpret features learned by tokenized foundation models as well as models incorporating chromatin signals as inputs. We further show that TPCAV can identify representative regions associated with specific concepts, motivating downstream investigation of distinct regulatory mechanisms. TPCAV provides a flexible and robust complement to existing model interpretation techniques.

bioinformatics↗

bioRxiv2026

Human CCR4-NOT suppresses pervasive transcription and retrotransposable elements

CCR4-NOT regulates multiple steps in gene regulation and has been well studied in budding yeast. Although primarily cytoplasmic, where it plays an essential role in mRNA degradation, the human complex has poorly characterized nuclear functions. Here, we used auxin-induced degradation to rapidly deplete the scaffold subunit CNOT1 and the E3 ligase CNOT4, and characterized the transcriptional functions of the human CCR4-NOT complex. Using transient transcriptome profiling (TT-Seq) to measure ongoing transcription, we found widespread activation of RNA synthesis in depleted cells across genic and intergenic regions. Interestingly, fewer genes were repressed, including KRAB-Zinc-Finger-protein (KZNF) genes, especially those on chromosome 19. KZNFs repress genes and retrotransposable elements (rTEs), and consistent with decreased KZNF expression, rTEs, mainly Long Interspersed Nuclear Elements (LINEs), were activated. Full-length active LINEs and rTEs lying outside of genes were activated, suggesting that the increased transcription is not the direct result of transcription of the genes the rTEs are embedded in. We found that most activated transcription events were in proximity to KZNF binding sites, suggesting that KZNF regulation contributes to the suppression of genic and rTE transcription. Finally, we demonstrate that CCR4-NOT regulates the stability of rTE RNAs, indicating that the complex tightly controls transposon expression by repressing transcription and targeting their RNAs for decay.

molecular biology↗

bioRxiv2025

Chromatin state dynamics during the Plasmodium falciparum intraerythrocytic development cycle

The interdependence of chromatin states and transcription factor (TF) binding in eukaryotic genomes is critical for the proper regulation of gene expression. In this study, we explore the connection between TFs and chromatin states in the human malaria parasite, Plasmodium falciparum, throughout its 48-hour asexual intraerythrocytic developmental cycle (IDC). Most P. falciparum genes are expressed in a periodic manner during the IDC, accompanied by dynamic shifts in histone modifications and chromatin accessibility. Leveraging genome-wide profiles of chromatin accessibility, histone modifications, and Heterochromatin Protein 1 (HP1) occupancy, we characterize chromatin state dynamics during the IDC. Our results indicate that several chromatin states remain stable throughout the lifecycle, while others are dynamic and are linked to gene activation or repression. We further characterize chromatin state dynamics at the genome-wide DNA binding sites for a selection of Plasmodium TFs, allowing us to group TFs according to their chromatin preferences. By correlating changes in chromatin accessibility, histone modifications, and TF binding, we provide a global overview of the chromatin state dynamics that coordinate P. falciparum asexual blood stage development.

genomics↗

bioRxiv2025

Optimized ChIP-exo for mammalian cells and patterned sequencing flow cells

By combining chromatin immunoprecipitation (ChIP) with an exonuclease digestion of protein-bound DNA fragments, ChIP-exo characterizes genome-wide protein-DNA interactions at near base-pair resolution. However, the widespread adoption of ChIP-exo has been hindered by several technical challenges, including lengthy protocols, the need for multiple custom reactions, and incompatibilities with recent Illumina sequencing platforms. To address these barriers, we systematically optimized and adapted the ChIP-exo library construction protocol for the unique requirements of mammalian cells and current sequencing technologies. We introduce a Mammalian-Optimized ChIP-exo (MO-ChIP-exo) protocol that builds upon previous ChIP-exo protocols with systematic optimization of crosslinking, harvesting, and library construction. We validate MO-ChIP-exo by comparing it to previously published ChIP-exo protocols and demonstrate its adaptability to both suspension (K562) and adherent (HepG2, mESC) cell lines. This improved protocol provides a more robust and efficient method for generating high-quality ChIP-exo libraries from mammalian cells. SUMMARYChIP-exo is a genome-wide protein-DNA binding assay with unrivalled resolution, but its widespread adoption has been hindered by technical challenges, particularly when applied to mammalian cells or when used with recent sequencing platforms. We introduce a Mammalian-Optimized ChIP-exo (MO-ChIP-exo) protocol with key modifications that overcome previous technical hurdles. We demonstrate that our optimized protocol produces high-quality data comparable to previously published protocols and is adaptable for use with both suspension (K562) and adherent (HepG2, mESC) cell lines.

genomics↗

bioRxiv2024

Human CCR4-NOT is a global regulator of gene expression and is a novel silencer of retrotransposon activation

CCR4-NOT regulates multiple steps in gene regulation and has been well studied in budding yeast, but much less is known about the human complex. Auxin-induced degradation was used to rapidly deplete the scaffold subunit CNOT1, and CNOT4, to characterize the functions of human CCR4-NOT in gene regulation. Depleting CNOT1 increased RNA levels and caused a widespread decrease in RNA decay. In contrast, CNOT4 depletion only modestly changed steady-state RNA levels and, surprisingly, led to a global acceleration in mRNA decay. Further, depleting either subunit resulted in a global increase in RNA synthesis. In contrast to most of the genome, the transcription of KRAB-Zinc-Finger-protein (KZNFs) genes, especially those on chromosome 19, was repressed. KZNFs are transcriptional repressors of retrotransposable elements (rTEs), and consistent with the decreased KZNFs expression, rTEs, mainly Long Interspersed Nuclear Elements (LINEs), were activated. These data establish CCR4-NOT as a global regulator of gene expression and a novel silencer of rTEs.

molecular biology↗

bioRxiv2024

Intragenomic conflict underlies extreme phenotypic plasticity in queen-worker caste determination in honey bees (Apis mellifera)

Caste determination of honey bees (Apis mellifera) is a prime example of developmental plasticity, where differences in larval diet will result in identical genotypes yielding either long-lived, reproductive queens or short-lived, facultatively sterile workers. Beyond environmental factors, intragenomic conflict between genes inherited from the mother (matrigenes) versus the father (patrigenes) is also hypothesized to generate this plasticity. In honey bees, the Kinship Theory of Intragenomic Conflict predicts selection on patrigenes to enhance traits that result in fitness gained through reproduction, and thus patrigenes should favor the queen caste fate. Here, we conducted allele-specific transcriptome analyses on queen-destined larvae (QL) and worker-destined larvae (WL) at 192 hours post-fertilization (hpf), a critical stage for caste determination. Our findings reveal hundreds of genes with parent-of-origin effects (POEs), with significant patrigene-biased transcription in QL. Genes with POEs in honey bees resemble imprinted genes in other taxa in terms of genomic clustering, recombination rate, intron length and CpG density, and a subset are maintained from 24hpf eggs. Previous studies demonstrated that DNA methylation, the canonical regulatory mechanism underlying transcriptional POEs in placental mammals, angiosperms, and some insects, is not operating in honey bees or other social insects. We use allele-specific ChIP-seq analyses to demonstrate that POEs on caste-specific histone post-translational modification (HPTM) profiles of H3K27me3, H3K4me3 and H3K27ac are associated with POEs on transcription. Together, these findings suggest that parent-of-origin intragenomic conflicts may contribute broadly to phenotypic plasticity and may be associated with HPTMs, suggesting a "non-canonical" genomic imprinting-like system in social insects.

developmental biology↗

bioRxiv2023

Systematic Dissection of Sequence Features Affecting the Binding Specificity of a Pioneer Factor Reveals Binding Synergy Between FOXA1 and AP-1

Despite the unique ability of pioneer transcription factors (PFs) to target nucleosomal sites in closed chromatin, they only bind a small fraction of their genomic motifs. The underlying mechanism of this selectivity is not well understood. Here, we design a high-throughput assay called ChIP-ISO to systematically dissect sequence features affecting the binding specificity of a classic PF, FOXA1. Combining ChIP-ISO with in vitro and neural network analyses, we find that 1) FOXA1 binding is strongly affected by co-binding TFs AP-1 and CEBPB, 2) FOXA1 and AP-1 show binding cooperativity in vitro, 3) FOXA1s binding is determined more by local sequences than chromatin context, including eu-/heterochromatin, and 4) AP-1 is partially responsible for differential binding of FOXA1 in different cell types. Our study presents a framework for elucidating genetic rules underlying PF binding specificity and reveals a mechanism for context-specific regulation of its binding.

genetics↗

bioRxiv2023

SEM: sized-based expectation maximization for characterizing nucleosome positions and subtypes

Genome-wide nucleosome profiles are predominantly characterized using MNase-seq, which involves extensive MNase digestion and size selection to enrich for mono-nucleosome-sized fragments. Most available MNase-seq analysis packages assume that nucleosomes uniformly protect 147bp DNA fragments. However, some nucleosomes with atypical histone or chemical compositions protect shorter lengths of DNA. The rigid assumptions imposed by current nucleosome analysis packages ignore variation in nucleosome lengths, potentially blinding investigators to regulatory roles played by atypical nucleosomes. To enable the characterization of different nucleosome types from MNase-seq data, we introduce the Size-based Expectation Maximization (SEM) nucleosome calling package. SEM employs a hierarchical Gaussian mixture model to estimate the positions and subtype identity of nucleosomes from MNase-seq fragments. Nucleosome subtypes are automatically identified based on the distribution of protected DNA fragment lengths at nucleosome positions. Benchmark analysis indicates that SEM is on par with existing packages in terms of standard nucleosome-calling accuracy metrics, while uniquely providing the ability to characterize nucleosome subtype identities. Using SEM on a low-dose MNase H2B MNase-ChIP-seq dataset from mouse embryonic stem cells, we identified three nucleosome types: short-fragment nucleosomes, canonical nucleosomes, and dinucleosomes. The short-fragment nucleosomes can be divided further into two subtypes based on their chromatin accessibility. Interestingly, the subset of short-fragment nucleosomes in accessible regions exhibit high MNase sensitivity and display distribution patterns around transcription start sites (TSSs) and CTCF peaks, similar to the previously reported "fragile nucleosomes". These SEM-defined accessible short-fragment nucleosomes are found not just in promoters, but also in enhancers and other regulatory regions. Additional investigations reveal their co-localization with the chromatin remodelers Chd6, Chd8, and Ep400. In summary, SEM provides an effective platform for distinguishing various nucleosome subtypes, paving the way for future exploration of non-standard nucleosomes.

bioinformatics↗

bioRxiv2023

Joint sequence & chromatin neural networks characterize the differential abilities of Forkhead transcription factors to engage inaccessible chromatin

The DNA-binding activities of transcription factors (TFs) are influenced by both intrinsic sequence preferences and extrinsic interactions with cell-specific chromatin landscapes and other regulatory proteins. Disentangling the roles of these binding determinants remains challenging. For example, the FoxA subfamily of Forkhead domain (Fox) TFs are known pioneer factors that can bind to relatively inaccessible sites during development. Yet FoxA TF binding also varies across cell types, pointing to a combination of intrinsic and extrinsic forces guiding their binding. While other Forkhead domain TFs are often assumed to have pioneering abilities, how sequence and chromatin features influence the binding of related Fox TFs has not been systematically characterized. Here, we present a principled approach to compare the relative contributions of intrinsic DNA sequence preference and cell-specific chromatin environments to a TFs DNA-binding activities. We apply our approach to investigate how a selection of Fox TFs (FoxA1, FoxC1, FoxG1, FoxL2, and FoxP3) vary in their binding specificity. We over-express the selected Fox TFs in mouse embryonic stem cells, which offer a platform to contrast each TFs binding activity within the same preexisting chromatin background. By applying a convolutional neural network to interpret the Fox TF binding patterns, we evaluate how sequence and preexisting chromatin features jointly contribute to induced TF binding. We demonstrate that Fox TFs bind different DNA targets, and drive differential gene expression patterns, even when induced in identical chromatin settings. Despite the association between Forkhead domains and pioneering activities, the selected Fox TFs display a wide range of affinities for preexiting chromatin states. Using sequence and chromatin feature attribution techniques to interpret the neural network predictions, we show that differential sequence preferences combined with differential abilities to engage relatively inaccessible chromatin together explain Fox TF binding patterns at individual sites and genome-wide.

genomics↗

bioRxiv2023

Allo: Accurate allocation of multi-mapped reads enables regulatory element analysis at repeats

Transposable elements (TEs) and other repetitive regions have been shown to contain gene regulatory elements, including transcription factor binding sites. Unfortunately, regulatory elements harbored by repeats have proven difficult to characterize using short-read sequencing assays such as ChIP-seq or ATAC-seq. Most regulatory genomics analysis pipelines discard "multi-mapped" reads that align equally well to multiple genomic locations. Since multi-mapped reads arise predominantly from repeats, current analysis pipelines fail to detect a substantial portion of regulatory events that occur in repetitive regions. To address this shortcoming, we developed Allo, a new approach to allocate multi-mapped reads in an efficient, accurate, and user-friendly manner. Allo combines probabilistic mapping of multi-mapped reads with a convolutional neural network that recognizes the read distribution features of potential peaks, offering enhanced accuracy in multi-mapping read assignment. Allo also provides read-level output in the form of a corrected alignment file, making it compatible with existing regulatory genomics analysis pipelines and downstream peak-finders. In a demonstration application on CTCF ChIP-seq data, we show that Allo results in the discovery of thousands of new CTCF peaks. Many of these peaks contain the expected cognate motif and/or serve as TAD boundaries. We additionally apply Allo to a diverse collection of ENCODE ChIP-seq datasets, resulting in multiple previously unidentified interactions between transcription factors and repetitive element families. Finally, we show that Allo may be particularly effective in identifying ChIP-seq peaks in younger TEs, which hold evolutionary significance due to their emergence during human evolution from primates.

bioinformatics↗

bioRxiv2023

Cross-species regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes

Knowledge of locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state Regulatory Potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbored distinctive transcription factor binding motifs that were similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we showed that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.

genomics↗

bioRxiv2023

DNA sequence context and the chromatin landscape differentiate sequence-specific transcription factor binding in the human malaria parasite, Plasmodium falciparum

Development of the human malaria parasite, Plasmodium falciparum, is regulated by a limited number of sequence-specific transcription factors (TFs). However, the mechanisms by which these TFs recognize genome-wide binding sites is still largely unknown. To address TF specificity, we investigated the binding of two TF subsets that either bind CACACA or GTGCAC DNA sequence motifs and further characterized PfAP2-G and PfAP2-EXP which bind unique DNA motifs (GTAC and TGCATGCA). We interrogated the impact of DNA sequence and chromatin context on P. falciparum TF binding by integrating high-throughput in vitro and in vivo binding assays, DNA shape predictions, epigenetic post-translational modifications, and chromatin accessibility. We determined that DNA sequence context minimally impacts binding site selection for CACACA-binding TFs, while chromatin accessibility, epigenetic patterns, co-factor recruitment, and dimerization contribute to differential binding. In contrast, GTGCAC-binding TFs prefer different DNA sequence context in addition to chromatin dynamics. Finally, we find that TFs that preferentially bind divergent DNA motifs may bind overlapping genomic regions in vivo due to low-affinity binding to other sequence motifs. Our results demonstrate that TF binding site selection relies on a combination of DNA sequence and chromatin features, thereby contributing to the complexity of P. falciparum gene regulatory mechanisms. Key PointsO_LISequence and chromatin context determine differential DNA-binding specificity of P. falciparum TFs C_LIO_LITFs with paralogous DNA-binding domains in P. falciparum are not functionally redundant C_LIO_LITFs with differing sequence-specificity can co-occupy sites through low-affinity DNA interactions C_LI

genomics↗

bioRxiv2023

Genotypic and phenotypic evidence indicates the introduction of two distinct forms of a non-native species (Gekko gecko) to Florida, USA

The red-spotted tokay gecko Gekko gecko (Linnaeus, 1758) is a widely distributed Asian gecko that has established outside of its native range in Florida, USA. This study used genotypic and phenotypic data to determine whether multiple, distinct forms of red-spotted tokay gecko are present in Florida, specifically the morphologically distinct "G. g. gecko" and "Form B". Two discrete mitochondrial clades (ND2) were identified in Florida tokay geckos, the native range distributions of which were found to correspond closely with the native ranges of G. g. gecko (the Malay Archipelago) and Form B (mainland Asia), respectively. Furthermore, each mitochondrial clade was non-randomly associated with a separate nuclear (RAG-1) clade, supporting the existence of two discrete genotypic lineages, representative of G. g. gecko and Form B. Both lineages were detected in Florida, and population-level morphological structure was non-randomly associated with genotype, confirming a genotype-phenotype link. Multiple lines of evidence thus indicate the introduction of both forms of tokay gecko to Florida, where hybridisation likely also occurs. The link between morphological Form B and a unique genotypic lineage also indicates the existence of a tokay gecko taxon distinct from the recognised subspecies G. g. azhari Mertens, 1955 and G. g. gecko (Linnaeus, 1758).

zoology↗

bioRxiv2022

The ENCODE Imputation Challenge: A critical assessment of methods for cross-cell type imputation of epigenomic profiles

Functional genomics experiments are invaluable for understanding mechanisms of gene regulation. However, comprehensively performing all such experiments, even across a fixed set of sample and assay types, is often infeasible in practice. A promising alternative to performing experiments exhaustively is to, instead, perform a core set of experiments and subsequently use machine learning methods to impute the remaining experiments. However, questions remain as to the quality of the imputations, the best approaches for performing imputations, and even what performance measures meaningfully evaluate performance of such models. In this work, we address these questions by comprehensively analyzing imputations from 23 imputation models submitted to the ENCODE Imputation Challenge. We find that measuring the quality of imputations is significantly more challenging than reported in the literature, and is confounded by three factors: major distributional shifts that arise because of differences in data collection and processing over time, the amount of available data per cell type, and redundancy among performance measures. Our systematic analyses suggest several steps that are necessary, but also simple, for fairly evaluating the performance of such models, as well as promising directions for more robust research in this area.

bioinformatics↗

bioRxiv2021

PEGR: a flexible management platform for reproducible epigenomic and genomic research

Reproducibility is a significant challenge in (epi)genomic research due to the complexity of experiments composed of traditional biochemistry and informatics. Recent advances have exacerbated this challenge as high-throughput sequencing data is generated at an unprecedented pace. Here we report on our development of a Platform for Epi-Genomic Research (PEGR), a web-based project management platform that tracks and quality controls experiments from conception to publication-ready figures, compatible with multiple assays and bioinformatic pipelines. It supports rigor and reproducibility for biochemists working at the wet bench, while continuing to fully support reproducibility and reliability for bioinformaticians through integration with the Galaxy platform.

bioinformatics↗

bioRxiv2021

Synthetic genomic reconstitution reveals principles of mammalian Hox cluster regulation

Precise Hox gene expression is crucial for embryonic patterning. Intra-Hox transcription factor binding and distal enhancer elements have emerged as the major regulatory modes controlling Hox gene expression. However, quantifying their relative contributions has remained elusive. Here, we introduce synthetic regulatory reconstitution, a novel conceptual framework for studying gene regulation and apply it to the HoxA cluster. We synthesized and delivered variant rat HoxA clusters (130-170 kilobases each) to an ectopic location in the mouse genome. We find that a HoxA cluster lacking distal enhancers recapitulates correct patterns of chromatin remodeling and transcription in response to patterning signals, while distal enhancers are required for full transcriptional output. Synthetic regulatory reconstitution is a generalizable strategy to decipher the regulatory logic of gene expression in complex genomes. One-Sentence SummaryReconstitution of gene regulation using large DNA constructs unravels the regulatory logic of a developmental gene locus.

synthetic biology↗