Evidence map›Paper›PMID 40210719›Full record

ArticleMolecular systems biology2025

Constraints on the optimization of gene product diversity.

Daohan Jiang, Nevraj Kejiou, Yi Qiu, Alexander F Palazzo, Matt Pennell

Abstract read
In one paragraph

Article in Molecular systems biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Daohan JiangDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
Nevraj KejiouDepartment of Biochemistry, University of Toronto, Toronto, Canada.
Yi QiuDepartment of Biochemistry, University of Toronto, Toronto, Canada.
Alexander F PalazzoDepartment of Biochemistry, University of Toronto, Toronto, Canada. alex.pallazo@utoronto.edu.ORCID http://orcid.org/0000-0002-9700-1995
Matt PennellDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA. mpennell@cornell.edu.ORCID http://orcid.org/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
Canadian Government | Natural Sciences and Engineering Research Council of Canada (NSERC) 492860HHS | NIH | National Institute of General Medical Sciences (NIGMS) R35GM151348Jean D'Alembert Foundation ANR-11-IDEX-0003NIGMS NIH HHS R35 GM151348
6 · The paper itself

Abstract

RNA and proteins can have diverse isoforms due to post-transcriptional and post-translational modifications. A fundamental question is whether these isoforms are mostly beneficial or the result of noisy molecular processes. To assess the plausibility of these explanations, we developed mathematical models depicting different regulatory architectures and investigated isoform evolution under multiple population genetic regimes. We found that factors beyond selection, such as effective population size and the number of cis-acting loci, significantly influence evolutionary outcomes. We found that sub-optimal phenotypes are more likely to evolve when populations are small and/or when the number of cis-loci is large. We also discovered that opposing selection on cis- and trans-acting loci can constrain adaptation, leading to a non-monotonic relationship between effective population size and optimization. More generally, our models provide a quantitative framework for developing statistical tests to analyze empirical data; as a demonstration of this, we analyzed A-to-I RNA editing levels in coleoids and found these to be largely consistent with non-adaptive explanations.

Indexed as

Genetic VariationModels, GeneticEvolution, MolecularGenetics, PopulationPhenotypeProtein IsoformsRNA EditingSelection, GeneticProtein IsoformsConstraintEvolutionary TheoryGene Product DiversityOptimizationPost-transcriptional Modification

Identifiers

PMID40210719
PMCPMC12048591

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.