Evidence map›Paper›PMID 38748819›Full record

ArticleGenome biology and evolution2024

A Synergistic, Cultivator Model of De Novo Gene Origination.

UnJin Lee, Shawn M Mozeika, Li Zhao

Abstract read
In one paragraph

Article in Genome biology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Emergence Biases in Molecular Evolution.Genome biology and evolution · 2026
    Review
  2. Review
  3. Article
  4. Article
  5. De Novo Genes: Current Status and Future Goals.Genome biology and evolution · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. De Novo Genes.Annual review of genetics · 2024
    Review
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

3 authors.

UnJin LeeLaboratory of Evolutionary Genetics and Genomics, The Rockefeller University, New York, NY, USA.ORCID 0000-0003-2424-650X
Shawn M MozeikaLaboratory of Evolutionary Genetics and Genomics, The Rockefeller University, New York, NY, USA.ORCID 0009-0009-8330-3624
Li ZhaoLaboratory of Evolutionary Genetics and Genomics, The Rockefeller University, New York, NY, USA.ORCID 0000-0001-6776-1996

Funding

The genetic and epigenetic mechanisms of phenotypic innovationhttps://apps.era.nih.gov/gm/reportCheckList.do?applicationID=9798249R35GM133780 · NIGMS · ROCKEFELLER UNIVERSITY · PI Li Zhao · 2019 to 2026
$3.5M
Allen Distinguished InvestigatorNIGMS NIH HHS R35 GM133780NIH HHS MIRA R35GM133780Paul G Allen Family FoundationRobertson Foundation
6 · The paper itself

Abstract

The origin and fixation of evolutionarily young genes is a fundamental question in evolutionary biology. However, understanding the origins of newly evolved genes arising de novo from noncoding genomic sequences is challenging. This is partly due to the low likelihood that several neutral or nearly neutral mutations fix prior to the appearance of an important novel molecular function. This issue is particularly exacerbated in large effective population sizes where the effect of drift is small. To address this problem, we propose a regulation-focused, cultivator model for de novo gene evolution. This cultivator-focused model posits that each step in a novel variant's evolutionary trajectory is driven by well-defined, selectively advantageous functions for the cultivator genes, rather than solely by the de novo genes, emphasizing the critical role of genome organization in the evolution of new genes.

Indexed as

Evolution, MolecularModels, GeneticHumansMutationSelection, Geneticde novo genesgenome organizationlinkagelncRNAsnatural selection

Identifiers

PMID38748819
PMCPMC11152449

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.