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The co-chaperone XAP2 is required for activation of hypothalamic thyrotropin-releasing hormone transcription in vivo

Transcriptional control of hypothalamic thyrotropin-releasing hormone (TRH) integrates central regulation of the hypothalamo-hypophyseal-thyroid axis and hence thyroid hormone (triiodothyronine (T(3))) homeostasis. The two β thyroid hormone receptors, TRβ1 and TRβ2, contribute to T(3) feedback on TRH, with TRβ1 having a more important role in the activation of TRH transcription. How TRβ1 fulfils its role in activating TRH gene transcription is unknown. By using a yeast two-hybrid screening of a mouse hypothalamic complementary DNA library, we identified a novel partner for TRβ1, hepatitis virus B X-associated protein 2 (XAP2), a protein first identified as a co-chaperone protein. TR–XAP2 interactions were TR isoform specific, being observed only with TRβ1, and were enhanced by T(3) both in yeast and mammalian cells. Furthermore, small inhibitory RNA-mediated knockdown of XAP2 in vitro affected the stability of TRβ1. In vivo, siXAP2 abrogated specifically TRβ1-mediated (but not TRβ2) activation of hypothalamic TRH transcription. This study provides the first in vivo demonstration of a regulatory, physiological role for XAP2

<i>Xenopus tropicalis</i> Genome Re-Scaffolding and Re-Annotation Reach the Resolution Required for <i>In Vivo</i> ChIA-PET Analysis

<div><p>Genome-wide functional analyses require high-resolution genome assembly and annotation. We applied ChIA-PET to analyze gene regulatory networks, including 3D chromosome interactions, underlying thyroid hormone (TH) signaling in the frog <i>Xenopus tropicalis</i>. As the available versions of <i>Xenopus tropicalis</i> assembly and annotation lacked the resolution required for ChIA-PET we improve the genome assembly version 4.1 and annotations using data derived from the paired end tag (PET) sequencing technologies and approaches (e.g., DNA-PET [gPET], RNA-PET etc.). The large insert (~10Kb, ~17Kb) paired end DNA-PET with high throughput NGS sequencing not only significantly improved genome assembly quality, but also strongly reduced genome “fragmentation”, reducing total scaffold numbers by ~60%. Next, RNA-PET technology, designed and developed for the detection of full-length transcripts and fusion mRNA in whole transcriptome studies (ENCODE consortia), was applied to capture the 5' and 3' ends of transcripts. These amendments in assembly and annotation were essential prerequisites for the ChIA-PET analysis of TH transcription regulation. Their application revealed complex regulatory configurations of target genes and the structures of the regulatory networks underlying physiological responses. Our work allowed us to improve the quality of <i>Xenopus tropicalis</i> genomic resources, reaching the standard required for ChIA-PET analysis of transcriptional networks. We consider that the workflow proposed offers useful conceptual and methodological guidance and can readily be applied to other non-conventional models that have low-resolution genome data.</p></div

Benefit of genome re-annotation with RNA-PET for ChIA-PET analysis.

<p>A. Genomic view of an un-annotated gene. Track order: Ensembl genes, RNA-PET-based models, ChIA-PET TR binding density, RNA Pol-II binding density, RNA-Seq reads density with (+T₃) and without (-T₃) THs treatment. B. Close up of TR binding sites. Track order: Ensembl genes, RNA-PET-based genes, location of ChIP-qPCR probes, RNA-PET PETs, TR binding density and RNA Pol-II binding density. C: ChIP-qPCR validation of TR binding at locations shown in B. Ab: antibody, T₃: 3’,5,3’ triiodothyronine treatment. D: Transcriptional induction assayed by RT-qPCR.</p

Examples of genome annotation improvements.

<p>Track order: Ensembl models, RNA-PET based models, RNA-PET ditags and RNA-Seq reads density. A, B, C: <i>sumo1</i>, <i>cadm2</i> and <i>kiaa1958</i> loci. D: Un-annotated gene split over scaffold_1031 and scaffold_1460.</p

Benefit of genome re-annotation with RNA-PET for ChIA-PET analysis.

<p>A. Large genomic view of the <i>bcl6</i> locus. Track order: Ensembl genes, RNA-PET-based models, ChIA-PET TR binding density, interaction PETs, RNA Pol-II binding density, RNA-Seq reads density with (+T₃) and without (-T₃) treatment with thyroid hormones. B. Close up on TR binding sites. Track order: Ensembl genes, RNA-PET-based genes, location of ChIP-qPCR probes, RNA-PET ditags, TR binding density and RNA Pol-II binding density. C: ChIP-qPCR validation of TR binding at locations shown in B. Ab: Antibody, T₃: 3’,5,3’ triiodothyronine treatment. D: Induction of <i>trpg1</i>, <i>lpp</i> and <i>bcl6</i> genes transcription assayed by RT-qPCR. E: Three-dimensional model of the locus topology.</p

RNA-PET efficiently captures transcripts ends.

<p>A. Overlap between RNA-Seq reads and Ensembl and RNA-PET-based models. B. Demarcation of gene model boundaries by RNA-PET. The histogram shows the relative size of Ensembl gene models in bins of various sizes. C. Enrichment of RNA-Pol II around Ensembl gene models and RNA-PET-based models. This shows that RNA-Pol II density fits well with RNA-PET based models, but not Ensembl models.</p