Evidence map›Paper›PMID 20382830›Full record

ArticleGenetics2010

The evolutionary dynamics of operon distributions in eukaryote genomes.

Asher D Cutter, Aneil F Agrawal

Open access · bronzeAbstract read
In one paragraph

Article in Genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
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

12 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Resolution of polycistronic RNA by SL2RNA (New York, N.Y.) · 2020
    Article
  3. Article
  4. Genes · 2020
    Article
  5. Investigating Evolutionary Dynamics of RHA1 Operons.Evolutionary bioinformatics online · 2016
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Trans-splicing and operons in C. elegans.WormBook : the online review of C. elegans biology · 2012
    Review
  11. Article
  12. Article
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 at 1 institution in 1 country.

Asher D CutterDepartment of Ecology and Evolutionary Biology, Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, Ontario M5S 3B2, Canada. asher.cutter@utoronto.ca
Aneil F Agrawal
University of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genes in nematode and ascidian genomes frequently occur in operons--multiple genes sharing a common promoter to generate a polycistronic primary transcript--and such genes comprise 15-20% of the coding genome for Caenorhabditis elegans and Ciona intestinalis. Recent work in nematodes has demonstrated that the identity of genes within operons is highly conserved among species and that the unifying feature of genes within operons is that they are expressed in germline tissue. However, it is generally unknown what processes are responsible for generating the distribution of operon sizes across the genome, which are composed of up to eight genes per operon. Here we investigate several models for operon evolution to better understand their abundance, distribution of sizes, and evolutionary dynamics over time. We find that birth-death models of operon evolution reasonably describe the relative abundance of operons of different sizes in the C. elegans and Ciona genomes and generate predictions about the number of monocistronic, nonoperon genes that likely participate in the birth-death process. This theory, and applications to C. elegans and Ciona, motivates several new and testable hypotheses about eukaryote operon evolution.

Indexed as

GenomeAnimalsBiological EvolutionCaenorhabditis elegansEukaryotaEukaryotic CellsNematodaOperon

Identifiers

PMID20382830
PMCPMC2881147
OpenAlexW2137734254

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.