Evidence map›Paper›PMID 41648187›Full record

ArticlebioRxiv : the preprint server for biology2026

UBIQUITOUS FUNCTIONAL SYNERGY PARTIALLY EXPLAINS WHY MOST TRANSCRIPTION FACTOR BINDING IS NON-FUNCTIONAL.

Chase Mateusiak, Eric Jia, Jessica N Plaggenberg, Zolboo Erdenbataar, Yuchen Wang, Christian Shively, Guochen Liao, Robi D Mitra, Michael R Brent

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Chase MateusiakDepartment of Computer Science, Washington University, Saint Louis, MO 63130.ORCID 0000-0002-2890-4242
Eric JiaDepartment of Computer Science, Washington University, Saint Louis, MO 63130.ORCID 0009-0007-1288-3700
Jessica N PlaggenbergDepartment of Computer Science, Washington University, Saint Louis, MO 63130.
Zolboo ErdenbataarDepartment of Computer Science, Washington University, Saint Louis, MO 63130.ORCID 0009-0004-8330-2019
Yuchen WangDepartment of Computer Science, Washington University, Saint Louis, MO 63130.
Christian ShivelyCenter for Genome Science and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110.ORCID 0000-0001-6485-6658
Guochen LiaoDepartment of Computer Science, Washington University, Saint Louis, MO 63130.ORCID 0009-0009-5239-4295
Robi D MitraCenter for Genome Science and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110.ORCID 0000-0002-2680-4264
Michael R BrentDepartment of Computer Science, Washington University, Saint Louis, MO 63130.ORCID 0000-0002-8689-0299

Funding

Mapping and modeling transcription factor networksR35GM141012 · NIGMS · WASHINGTON UNIVERSITY · PI BRENT, MICHAEL R · 2021 to 2025
$2.0M
NIGMS NIH HHS R35 GM141012
6 · The paper itself

Abstract

Most genes in whose promotor a transcription factor (TF) binds do not change in expression when the concentration of the TF is perturbed. No existing model can predict which bound promotors will respond and which will not. We hypothesized that a gene's response to perturbation of a TF bound in its promotor can depend on which other TFs are bound there, a phenomenon we call functional synergy. This is distinct from cooperative binding, which is already accounted for in the binding location data. To investigate functional synergy, we created a comprehensive dataset on TF binding locations in yeast using a method that is orthogonal to chromatin immunoprecipitation. We then used mathematical modeling to identify high-confidence instances of functional synergy. We found that such synergies are surprisingly common. Responses to perturbations of 44 different TFs were modified by the presence of other TFs. 48 TFs served as modifiers, but some modified responses to many TFs. We conclude that (1) measuring the binding locations of a single TF will not, in general, reveal which genes the TF regulates, and (2) traditional networks linking TFs to their targets must be made substantially more expressive, allowing some TFs to modify the effects of others.

Identifiers

PMID41648187
PMCPMC12871833

What Socratic holds

Textmetadata
LicenceCC BY-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.