Evidence map›Paper›PMID 42779983›Full record

ArticlebioRxiv : the preprint server for biology2026

Unicellular and Multicellular Modes of Selection Impose Distinct Constraints on Cellular Phenotype Evolution.

Mark Kim, Matt Pennell

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

2 authors.

Mark KimDepartment of Computational Biology, Cornell University, United States.
Matt PennellDepartment of Computational Biology, Cornell University, United States.ORCID 0000-0002-2886-3970

Funding

Leveraging phylogenetic approaches to investigate the evolution of geneexpressionR35GM151348 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Matthew Wesley Pennell · 2023 to 2026
$1.6M
NIGMS NIH HHS R35 GM151348
6 · The paper itself

Abstract

Single-cell sequencing data have revealed that cellular phenotypes, such as gene expression states, are often low-dimensional, suggesting that cellular variation may arise from combinations of a smaller set of gene expression programs. A genome therefore defines a repertoire of cellular phenotypes that can be configured through different combinations of programs. However, organisms vary in how much of this repertoire is exposed to selection. In unicellular organisms, different phenotypes are often expressed across environments or life-cycle stages, so selection in a given context acts primarily through the phenotype expressed there. In multicellular organisms, multiple phenotypes can coexist within an individual and contribute jointly to fitness. Here, we use a geometric model to ask how selection acting through cellular phenotypes separately or jointly constrains the ability of a shared genome to evolve and maintain differentiated phenotypes across multiple functional demands. We vary the number of functional demands and how many corresponding phenotypes contribute jointly to fitness. We find similar evolutionary outcomes when demands are weakly divergent. Under strongly divergent demands, however, selection on one phenotype at a time leads to reduced differentiation as demands accumulate, even when sufficient programs are available. As more phenotypes contribute jointly to fitness, differentiation and performance improve. When all phenotypes contribute jointly, differentiation is maintained until demands outnumber programs. Our results suggest that how cellular phenotypes are organized in time and space can impose distinct constraints on the evolution of differentiation from a shared genome.

Identifiers

PMID42779983
PMCPMC13596391

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.