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Genomic context sensitizes regulatory elements to genetic disruption [DNAse-seq]

ABSTRACT: Enhancer function is frequently investigated piecemeal using truncated reporter assays or single deletion analysis, thus it remains unclear to what extent their function is influenced by surrounding genomic context. Using our Big-IN technology for targeted integration of large DNAs, we analyzed the regulatory architecture of the Igf2/H19 locus, a paradigmatic model of enhancer selectivity. We assembled payloads containing a 157-kb functional Igf2/H19 locus and engineered mutations to genetically direct CTCF occupancy at the imprinting control region (ICR) that switches the target gene of the H19 enhancer cluster. Contrasting the activity of payloads delivered to the endogenous locus or to a safe harbor locus (Hprt) revealed that the functional elements comprising the Igf2/H19 locus are highly sensitive to their native context. Exchanging components of the Igf2/H19 locus with the well-studied Sox2 locus showed that the H19 enhancer cluster in particular functioned poorly out of context, and required its native surroundings to activate Sox2 expression. Conversely, the Sox2 locus control region (LCR) could activate both Igf2 and H19 outside its native context, but its activity was only partially modulated by CTCF occupancy at the ICR. Analysis of regulatory DNA actuation across different cell types revealed that, while the H19 enhancers are tightly coordinated within their native locus, the Sox2 LCR acts more independently. We show that these enhancer clusters typify broader classes of loci genome-wide. Our results show that unexpected dependencies may influence even the most studied functional elements, and our synthetic regulatory genomics approach permits large-scale manipulation of complete loci to investigate how locus architecture relates to function.

ORGANISM(S): Mus musculus

PROVIDER: GSE241707 | GEO | 2024/03/13

REPOSITORIES: GEO

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Project description:Abstract: Dysregulation of the imprinted H19/IGF2 locus can lead to Silver-Russell Syndrome (SRS) in humans. However, the mechanism of how abnormal H19/IGF2 expression contributes to various SRS phenotypes remains unclear, largely due to incomplete understanding of the developmental functions of these two genes. We previously generated a mouse model with humanized H19/IGF2 ICR (hIC1) on the paternal allele that exhibited H19/Igf2 dysregulation together with SRS-like growth restriction and perinatal lethality. Here we dissect the role of H19 and Igf2 in cardiac and placental development utilizing multiple mouse models with varying levels of H19 and Igf2. We report severe cardiac defects such as ventricular septal defects (VSDs) and thinned myocardium, placental anomalies including thrombosis and vascular malformations, together with growth restriction in mouse embryos that correlated with the extent of H19/Igf2 dysregulation. Transcriptomic analysis using cardiac endothelial cells of these mouse models shows that H19/Igf2 dysregulation disrupts pathways related to extracellular matrix (ECM) and proliferation of endothelial cells. Our work links the heart and placenta through regulation by H19 and Igf2, demonstrating that accurate dosage of both H19 and Igf2 is critical for normal embryonic development, especially related to the cardiac-placental axis. Methods: E12.5 hearts were lysed with Collagenase, Dispase II, and DNase I. Cardiac endothelial cells were collected using MACS CD31 microbeads and RNA was isolated using RNeasy Micro kit. After confirming RNA integrity using Bioanalyzer, mRNA library was generated from 25ng RNA using NEBNext Poly(A) mRNA Magnetic Isolation Module and Ultra II RNA Library Prep Kit. Library quality was assessed by Bioanalyzer and TapeStation. Sequencing was performed on NovaSeq 6000. Quality of raw fastq reads was assessed using FastQC version 0.11.5. Reads were aligned to the GRCm38/mm10 reference using STAR version 2.4.0i with default parameters and maximum fragment size of 2000 bp. Properly paired primary alignments were retained for downstream analysis using Samtools version 1.9. Count matrices were generated using FeatureCounts version 1.6.2 against RefSeq gene annotation and read into DESeq2 to perform normalization and statistical analysis.

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Genomic context sensitizes regulatory elements to genetic disruption [DNAse-seq]

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