The Fgf/Erf/NCoR1/2 repressive axis controls trophoblast cell fate

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Abstract

Placental development relies on coordinated cell fate decisions governed by signalling inputs. However, little is known about how signalling cues are transformed into repressive mechanisms triggering lineage-specific transcriptional signatures. Here, we demonstrate that upon inhibition of the Fgf/Erk pathway in mouse trophoblast stem cells (TSCs), the Ets2 repressor factor (Erf) interacts with the Nuclear Receptor Co-Repressor Complex 1 and 2 (NCoR1/2) and recruits it to key trophoblast genes. Genetic ablation of Erf or Tbl1x (a component of the NCoR1/2 complex) abrogates the Erf/NCoR1/2 interaction. This leads to mis-expression of Erf/NCoR1/2 target genes, resulting in a TSC differentiation defect. Mechanistically, Erf regulates expression of these genes by recruiting the NCoR1/2 complex and decommissioning their H3K27ac-dependent enhancers. Our findings uncover how the Fgf/Erf/NCoR1/2 repressive axis governs cell fate and placental development, providing a paradigm for Fgf-mediated transcriptional control.

Abstract

Repression of gene expression contributes to lineage-specific transcriptional signatures. Here Lackner et al. demonstrate that the Erf-NCoR1/2 complex controls trophoblast differentiation by linking signalling with transcriptional repression

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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael Love, Wolfgang Huber, Simon Anders (2014)

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.

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STAR: ultrafast universal RNA-seq aligner.

Alexander Dobin, Carrie A. Davis, Felix Schlesinger … (2013)

Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

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Fast gapped-read alignment with Bowtie 2.

Ben Langmead, Steven L Salzberg (2022)

As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.

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Author and article information

Contributors

Paulina A. Latos:

ORCID: http://orcid.org/0000-0001-7457-956X

paulina.latos@meduniwien.ac.at

Journal

Journal ID (nlm-ta): Nat Commun

Journal ID (iso-abbrev): Nat Commun

Title: Nature Communications

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2041-1723

Publication date (Electronic): 4 May 2023

Publication date PMC-release: 4 May 2023

Publication date Collection: 2023

Volume: 14

Electronic Location Identifier: 2559

Affiliations

[1 ]GRID grid.22937.3d, ISNI 0000 0000 9259 8492, Center for Anatomy and Cell Biology, , Medical University of Vienna, ; A-1090 Vienna, Austria

[2 ]GRID grid.14826.39, ISNI 0000 0000 9799 657X, Institute of Molecular Pathology, ; A-1030 Vienna, Austria

Author information

Andreas Lackner http://orcid.org/0000-0003-1168-7947

Henrieta Papuchova http://orcid.org/0000-0002-4832-5213

Elisabeth Roitinger http://orcid.org/0000-0002-3405-7801

Karl Mechtler http://orcid.org/0000-0002-3392-9946

Paulina A. Latos http://orcid.org/0000-0001-7457-956X

Article

Publisher ID: 38101

DOI: 10.1038/s41467-023-38101-8

PMC ID: 10193302

PubMed ID: 37137875

SO-VID: b84d531b-b0a5-4bb6-b69e-134b1ab99c6b

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 14 March 2022

Date accepted : 15 April 2023

Funding

Funded by: FundRef https://doi.org/10.13039/501100002428, Austrian Science Fund (Fonds zur Förderung der Wissenschaftlichen Forschung);

Award ID: P 32176

Award Recipient : Paulina A. Latos

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ScienceOpen disciplines: Uncategorized

Keywords: stem-cell differentiation,epigenetics

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ScienceOpen disciplines: Uncategorized

Keywords: stem-cell differentiation, epigenetics

The Fgf/Erf/NCoR1/2 repressive axis controls trophoblast cell fate

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Gamma Delta T cells

Most cited references 110

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

STAR: ultrafast universal RNA-seq aligner.

Fast gapped-read alignment with Bowtie 2.

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