In the mammalian embryo, epiblast cells must exit the naive state and acquire formative pluripotency. This cell state transition is recapitulated by mouse embryonic stem cells (ESCs), which undergo pluripotency progression in defined conditions in vitro. However, our understanding of the molecular cascades and gene networks involved in the exit from naive pluripotency remains fragmentary. Here, we employed a combination of genetic screens in haploid ESCs, CRISPR/Cas9 gene disruption, large-scale transcriptomics and computational systems biology to delineate the regulatory circuits governing naive state exit. Transcriptome profiles for 73 ESC lines deficient for regulators of the exit from naive pluripotency predominantly manifest delays on the trajectory from naive to formative epiblast. We find that gene networks operative in ESCs are also active during transition from pre- to post-implantation epiblast in utero. We identified 496 naive state-associated genes tightly connected to the in vivo epiblast state transition and largely conserved in primate embryos. Integrated analysis of mutant transcriptomes revealed funnelling of multiple gene activities into discrete regulatory modules. Finally, we delineate how intersections with signalling pathways direct this pivotal mammalian cell state transition.

https://www.embopress.org/doi/pdf/10.15252/embj.2020105776

Cooperative genetic networks drive embryonic stem cell transition from naïve to formative pluripotency.

Genetic background drives phenotypic variability in pluripotent stem cells (PSCs). Most studies to date have used transcript abundance as the primary molecular readout of cell state in PSCs. We performed a comprehensive proteogenomics analysis of 190 genetically diverse mouse embryonic stem cell (mESC) lines. The quantitative proteome is highly variable across lines, and we identified pluripotency-associated pathways that were differentially activated in the proteomics data that were not evident in transcriptome data from the same lines. Integration of protein abundance to transcript levels and chromatin accessibility revealed broad co-variation across molecular layers as well as shared and unique drivers of quantitative variation in pluripotency-associated pathways. Quantitative trait locus (QTL) mapping localized the drivers of these multi-omic signatures to genomic hotspots. This study reveals post-transcriptional mechanisms and genetic interactions that underlie quantitative variability in the pluripotent proteome and provides a regulatory map for mESCs that can provide a basis for future mechanistic studies. 

Genetic dissection of the pluripotent proteome through multi-omics data integration

Genetic background is a major driver of phenotypic variability in pluripotent stem cells (PSCs). Most studies of variation in PSCs have relied on transcript abundance as the primary molecular readout of cell state. However, little is known about how proteins, the primary functional units in the cell, vary across genetically diverse PSCs, how protein abundance relates to variation in other cell characteristics, and how genetic background confers these effects. Here we present a comprehensive genetic study characterizing the pluripotent proteome of 190 unique mouse embryonic stem cell lines (mESCs) derived from genetically heterogeneous Diversity Outbred (DO) mice. The quantitative proteome is highly variable across DO mESCs, and we identified differentially activated pluripotency-associated pathways in the proteomics data that were not evident in transcriptome data from the same cell lines. Comparisons of protein abundance to transcript levels and chromatin accessibility show broad co-variation across molecular layers and variable correlation across samples, with some lines showing high and others low correlation between these multi-omics datasets. Integration of these three molecular data types using multi-omics factor analysis revealed shared and unique drivers of quantitative variation in pluripotency-associated pathways. QTL mapping localized the genetic drivers of this quantitative variation to a number of genomic hotspots, and demonstrated that multi-omics data integration consolidates the influence of genetic signals shared across molecular traits to increase QTL detection power and overcome the limitations inherent in mapping individual molecular features. This study reveals transcriptional and post-transcriptional mechanisms and genetic interactions that underlie quantitative variability in the pluripotent proteome, and in so doing provides a regulatory map for mouse ESCs that can provide a rational basis for future mechanistic studies, including studies of human PSCs.

In the mammalian embryo, epiblast cells must exit their naive state and acquire formative pluripotency. This cell state transition is recapitulated by mouse embryonic stem cells (ESCs), which undergo pluripotency progression in defined conditions in vitro. However, our understanding of the molecular cascades and gene-networks involved in the exit from naive pluripotency remains fragmented. Here we employed a combination of genetic screens in haploid ESCs, CRISPR/Cas9 gene disruption, large-scale transcriptomics and computational systems-biology to delineate the regulatory circuits governing naive state exit. Transcriptome profiles for 73 knockout ESC lines predominantly manifest delays on the trajectory from naive to formative epiblast. We find that gene networks operative in ESCs are active during transition from pre- to post-implantation epiblast in utero. We identified 374 naive-associated genes tightly connected to epiblast state and largely conserved in human ESCs and primate embryos. Integrated analysis of mutant transcriptomes revealed funneling of multiple gene activities into discrete regulatory modules. Finally, we delineate how intersections with signaling pathways direct this pivotal mammalian cell state transition.

/pdf/cooperative-genetic-networks-drive-a-mammalian-cell-state-30td3fe99l.pdf

Cooperative genetic networks drive a mammalian cell state transition

The Wnt/β-catenin signaling pathway is a critical regulator of development and stem cell maintenance. Mounting evidence suggests that the context-specific outcome of Wnt signaling is determined by the collaborative action of multiple transcription factors, including members of the highly conserved forkhead box (FOX) protein family. However, the contribution of FOX transcription factors to Wnt signaling has not been investigated in a systematic manner. Here, we performed uniform gain-of-function screens of all 44 human FOX transcription factors to identify and classify new regulators of the Wnt/β-catenin pathway. By combining β-catenin reporter assays with Wnt pathway-focused qPCR arrays and proximity proteomics of selected FOX family members, we determine that most FOX proteins are involved in the regulation of Wnt pathway activity and the expression of Wnt ligands and target genes. Moreover, as a proof of principle we characterize class D and I FOX transcription factors as physiologically relevant positive and negative regulators of Wnt/β-catenin signaling, respectively. We conclude that FOX proteins are common regulators of the Wnt/β-catenin pathway that may control the outcome of Wnt signaling in a tissue-specific manner.

/pdf/fox-transcription-factors-are-common-regulators-of-wnt-b-1pop3c2b.pdf

FOX transcription factors are common regulators of Wnt/β-catenin signaling

Modulation of Wnt target gene expression via the TCF/LEFs remains poorly understood. We employ proximity-based biotin labeling (BioID) to examine GSK-3 inhibitor effects on the TCF7L1 interactome in mouse ESCs. We generated ESC lines with biotin ligase BirA* fused to TCF7L1 by knocking it into the endogenous TCF7L1 locus or by inserting a dox-inducible BirA*-TCF7L1 transgene into the Rosa26 locus. Induction yielded BirA*-TCF7L1 levels 3-fold higher than in the endogenous system, but substantial overlap in biotinylated proteins with high peptide counts were detected by each method. Known TCF7L1 interactors TLE3/4 and β-catenin, and numerous proteins not previously associated with TCF7L1, were identified in both systems. Despite reduced BirA*-TCF7L1 levels, the number of hits identified with both BioID approaches increased after GSK-3 inhibition. We elucidate the network of TCF7L1 proximal proteins regulated by GSK-3 inhibition, validate the utility of endogenous BioID, and provide mechanistic insights into TCF7L1 target gene regulation.

Endogenous BioID elucidates TCF7L1 interactome modulation upon GSK-3 inhibition in mouse ESCs

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Endogenous BioID elucidates TCF7L1 interactome modulation upon GSK-3 inhibition in mouse ESCs