Systematic analysis of transcription factor combinatorial binding uncovers TEAD1 as an antagonist of tissue-specific transcription factors in human organogenesis

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors present a pipeline for the identification of transcription factor (TF) co-occurrence in regulatory regions. This pipeline aims to generate a catalogue of combinations of TFs working together, and the authors apply this during human embryonic development. In particular, they identified co-occurrences of TFs starting from H3K27ac ChIP-seq and RNA-seq input data to select active enhancers and transcribed TFs. The pipeline is applied to explore TF motifs co-occurrence at tissue-specific developmental enhancers across 11 human embryonic tissues. The application of the pipeline suggests the presence of regulatory patterns in different human developmental tissue-specific enhancers in association with ubiquitous TFs. The authors further explore the role of TEAD1 (an ubiquitously expressed TF) as a repressor. They test the role of TEAD1 as a co-repressor using a luciferase assay and tissue-specific enhancers, either alone or combined with a YAP coactivator. Overall, this paper presents an important aspect in mammalian gene regulation, the cooperative binding of TFs, and provides an important resource for TF pairs.

Strengths:

I appreciated the number of datasets analysed and the validation of a subset of enhancers.

Weaknesses:

Not many, but probably validation at more enhancers could have made the paper stronger.

Reviewer #2 (Public review):

Summary:

Garcia-Mora et al. presented a two-step bioinformatics pipeline using H3K27ac ChIP-seq and RNA-seq data from 11 human embryonic tissues published by the same groups of senior authors. "First Search" identifies motifs for TFs that are both tissue-restricted in expression and enriched in tissue-specific enhancers. "Second Search" then looks for additional motifs that co-occur near each "First Search" motif. The authors here went further than previous motif co-occurrence/co-enrichment analyses by identifying TEAD motifs as (1) representing a ubiquitously expressed family and (2) showing high co-occurrence with tissue-specific motifs at tissue-specific enhancers. They then elaborate on this finding and speculate that "TEAD, in concert with cardiac-restricted transcriptional regulators, may contribute to the recruitment of CHD4 and may play a role in attenuating the activity of enhancers involved in cardiomyocyte differentiation." They also discussed validation experiments using the luciferase assay.

Strengths:

The manuscript is well-written and easy to follow for the most part.

Weaknesses:

My main concerns and criticisms are about the sensitivity of the method and the validation of experiment designs and conclusions. Some examples where validation could be improved are as follows:

(1) The authors propose a mechanism of a TF trio (TEAD - CHD4 - tissue-specific TFs). However, only one validation experiment checked CHD4. CHD4 binding was not mentioned at all in the other cases.

(2) The authors integrated E12.5 TEAD binding with E11.5 acetylation data, and it would be important to show that this experimental approach is valid or otherwise qualify its limitations.

(3) Motif co-occurrence analysis was extended to claiming TF interactions without further validation.

Reviewer #3 (Public review):

Summary:

Mora et al employ published ChIP-seq and RNA-seq from embryonic tissues to nominate transcription factors that work combinatorially during development. This manuscript addresses an important gap in knowledge regarding the complexities of gene regulation. However, as written, the manuscript is focused on confirming mostly known associations and does not unveil principles that can be broadly applied, given multiple technical caveats that are outlined below.

Strengths:

(1) Instead of focusing on a single transcription factor motif enriched within peaks, the authors search the flanking regions of enriched motifs to nominate additional transcription factors that may work cooperatively to provide organ specificity. This type of analysis is a crucial next step in the gene regulation field, as transcription factors rarely work independently.

(2) Figure 6 is a good demonstration of the preliminary experiments that can be done to test the activity of co-occurring motifs.

(3) This is a really nice resource of organ-specific motif associations that can be used to generate many testable hypotheses.

(4) The rationale and writing are very clear and easy to read.

Weaknesses:

(1) Much of this manuscript focuses on confirming transcription factor relationships that have been reported previously. For example, it is well known that GATA4 interacts with MEF2 in the ventricle. There are limited new or unexpected associations discussed and tested.

(2) Embryonic tissues are highly heterogeneous, limiting the utility of the bulk ChIP-seq employed in these analyses. Does the cellular heterogeneity explain the discrepancy between TEAD binding and histone acetylation? Similarly, how does conservation between species affect the TF predictions?

(3) Some of the interpretations should also be fleshed out a bit more to clarify the advantage of the analyses presented here. For example, if Gata4 and Foxa2 transcripts are expressed during different stages of development, then it's likely that (as stated by the authors) these motifs are not used during the same stage of development. But examining the flanking regions wasn't necessary to make that statement. This type of conclusion seems tangential to the benefit of this analysis, which is to understand which TFs work together in a single organ at a single time point.

(4) This manuscript hinges on luciferase assays whose results can be difficult to translate to complex gene regulation networks. Many motifs are often clustered together, which makes designing experiments at endogenous loci important in studies such as this one.

Author response:

Reviewer #1:

Point 1

Not many weaknesses, but probably validation at more enhancers could have made the paper stronger.

We experimentally validated two sets of enhancers from two distinct tissues and observed similar effects. While this supports the idea that the TEAD-tissue-specific TF interaction we observe is not restricted to a single tissue, we agree that testing additional enhancers from a third tissue would strengthen our conclusions. We will acknowledge in the discussion that including a third tissue could provide additional support for the generality of our findings.

Reviewer #2:

Point 1

The authors propose a mechanism of a TF trio (TEAD - CHD4 - tissue-specific TFs). However, only one validation experiment checked CHD4. CHD4 binding was not mentioned at all in the other cases.

Indeed, CHD4 binding was experimentally validated at only one enhancer. This was a deliberate decision based on two key considerations:

(1) Consistent functional response across enhancers: We tested multiple enhancers (n =8) for functional response to the TEAD+YAP and GATA4/6 combination. All enhancers tested exhibited the same trend—attenuation of GATA-mediated activation upon co-expression of TEAD or TEAD/YAP. This consistent pattern supports a shared mechanism across these elements.

(2) Substantial prior evidence supporting CHD4 recruitment by both GATA4 and YAP: Specifically, CHD4 recruitment by GATA4 has been described in the context of cardiovascular development[1], and CHD4 can also be recruited by TEAD coactivator YAP2. Furthermore, published genomic occupancy data from embryonic heart tissue show widespread co-binding of GATA4, TEAD, and CHD4[1,3], including at most of the cardiac enhancers we functionally tested (4 out of 5).

Given the consistent enhancer responses and the supporting literature and genomic data indicating TEAD-CHD4 co-occupancy, we chose to validate CHD4 binding at a representative enhancer as a proof of concept.

We will clarify this rationale in the revised manuscript to better address this concern.

Reviewer #2:

Point 2

The authors integrated E12.5 TEAD binding with E11.5 acetylation data, and it would be important to show that this experimental approach is valid or otherwise qualify its limitations.

We will provide additional evidence in support of this approach in the revised manuscript or alternatively acknowledge its limitations.

Reviewer #2:

Point 3

Motif co-occurrence analysis was extended to claiming TF interactions without further validation.

We thank the reviewer for pointing out this important distinction. We reviewed the manuscript and identified seven instances where TF interactions were mentioned. Four of these correctly refer to previously established protein-protein interactions. For the remaining instances, we will adjust the wording to reflect the level of evidence, e.g. describe combinatorial binding based on motif co-occurrence, rather than implying direct interaction.

Reviewer #3:

Point 1

Much of this manuscript focuses on confirming transcription factor relationships that have been reported previously. For example, it is well known that GATA4 interacts with MEF2 in the ventricle. There are limited new or unexpected associations discussed and tested.

We thank the reviewer for this important observation and see the recurrence of known interactions, such as GATA4-MEF2, not as a drawback, but as an important validation of our methodology.

The identification of novel TF-TF combinations was geared toward uncovering shared regulatory principles across diverse human developmental tissues. While analysing 13 heterogeneous embryonic tissues introduced limitations, such as cellular complexity that may obscure rare interactions, it also allowed the identification of robust, recurrent patterns across tissues. Indeed, using this approach, we identified the widespread combinatorial effect of TEAD in partnership with lineage-specific TFs, which is explored more in depth in the manuscript.

Another main goal of the study was to develop and demonstrate a generalizable strategy for identifying combinatorial TF binding patterns that underlie tissue-specific gene regulation. Given the inherent heterogeneity of the embryonic organs analysed, the approach is naturally biased toward recovering the most prevalent, and often well-characterized, TF combinations. While we fully acknowledge this limitation, we believe that the ability to robustly recover well-established TF partnerships across multiple organs provides a valuable proof of concept. The next step will be to apply this strategy to single-cell RNA datasets, in order to define TF relationships at higher resolution, for example, resolving associations down to specific family members that cooperate within distinct lineages or cell types, and identifying less frequent or underrepresented TF-TF relationships.

In this context, we believe that our strategy has successfully highlighted shared enhancer logic and offers a framework for future high-resolution dissection of TF cooperativity at the single-cell level. The rationale for analysing heterogeneous tissues, along with its limitations, will be addressed in the revised version.

Reviewer #3:

Point 2

Embryonic tissues are highly heterogeneous, limiting the utility of the bulk ChIP-seq employed in these analyses. Does the cellular heterogeneity explain the discrepancy between TEAD binding and histone acetylation? Similarly, how does conservation between species affect the TF predictions?

We thank the reviewer for raising these important points. We acknowledge the limitations of using bulk ChIP-seq data in the context of complex embryonic tissues (see also previous point). We cannot exclude that the discrepancy between TEAD binding and histone acetylation is an effect of cellular heterogeneity. Indeed, we mention in the results “Our ventricle-specific enhancers were sampled at a single time point and likely represent enhancers that are selectively active in different cell types and developmental stages, given the heterogeneity of cell types in the ventricle”. The limitation of bulk ChIP-seq will be addressed in the discussion. In the specific case of the enhancers selected for validation, the binding site sequences are conserved between species, suggesting that the cis-regulatory activity is likely to be similar in both.

Reviewer #3:

Point 3

Some of the interpretations should also be fleshed out a bit more to clarify the advantage of the analyses presented here. For example, if Gata4 and Foxa2 transcripts are expressed during different stages of development, then it's likely that (as stated by the authors) these motifs are not used during the same stage of development. But examining the flanking regions wasn't necessary to make that statement. This type of conclusion seems tangential to the benefit of this analysis, which is to understand which TFs work together in a single organ at a single time point.

We appreciate the reviewer’s comment and the opportunity to clarify our interpretation. The reviewer refers to the finding that GATA4 and FOXA2 motifs are flanked by different sets of motifs in liver enhancers, suggesting that these TFs operate within distinct regulatory contexts.

Our aim was not to state that GATA4 and FOXA2 do not function simultaneously—this can indeed be inferred from their non-overlapping expression patterns. Rather, we intended to highlight the potential of our approach, even when applied to bulk data, to resolve distinct regulatory modules that may act in different subpopulations of cells or developmental windows within the same tissue.

We will revise the relevant section of the manuscript to make this interpretative point clearer.

Reviewer #3:

Point 4

This manuscript hinges on luciferase assays whose results can be difficult to translate to complex gene regulation networks. Many motifs are often clustered together, which makes designing experiments at endogenous loci important in studies such as this one.

We agree with the Reviewer that luciferase assays represent an oversimplified model of gene regulation and do not fully capture the complexity of endogenous regulatory networks. We will explicitly acknowledge this limitation in the discussion.

Mutagenesis of TEAD and tissue-specific TF motifs at endogenous loci would provide more conclusive evidence. However, our goal was to test the generality of TEAD effect across multiple enhancers and tissues. Despite its limitations, a luciferase-based assay was the most feasible approach, as an endogenous strategy would not have allowed us to assess a broader set of enhancers efficiently. Additionally, the presence of recurrent motifs and the potential functional redundancy among enhancers targeting the same gene can complicate the interpretation of single-locus perturbations.

References

(1) Robbe ZL, Shi W, Wasson LK, Scialdone AP, Wilczewski CM, Sheng X, et al. CHD4 is recruited by GATA4 and NKX2-5 to repress noncardiac gene programs in the developing heart. Genes Dev. 2022 Apr 1;36(7–8):468–82.

(2) Kim M, Kim T, Johnson RL, Lim DS. Transcriptional Co-repressor Function of the Hippo Pathway Transducers YAP and TAZ. Cell Rep. 2015 Apr;11(2):270–82.

(3) Akerberg BN, Gu F, VanDusen NJ, Zhang X, Dong R, Li K, et al. A reference map of murine cardiac transcription factor chromatin occupancy identifies dynamic and conserved enhancers. Nat Commun. 2019 Oct 28;10(1):4907.