Evidence map›Paper›PMID 22467905›Full record

ArticleGenome biology and evolution2012

Family size and turnover rates among several classes of small non-protein-coding RNA genes in Caenorhabditis nematodes.

Paul Po-Shen Wang, Ilya Ruvinsky

Open access · goldAbstract read
In one paragraph

Article in Genome biology and evolution, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact, top 87% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. SMORE: Synteny Modulator of Repetitive Elements.Life (Basel, Switzerland) · 2017
    Article
  3. Article
  4. Article
  5. 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 2 institutions in 2 countries.

Paul Po-Shen WangDepartment of Ecology and Evolution, Institute for Genomics and Systems Biology, The University of Chicago, IL, USA.
Ilya Ruvinsky
Genomics (United Kingdom) · GBUniversity of Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is important to understand the forces that shape the size and evolutionary histories of gene families. Here, we investigated the evolution of non-protein-coding RNA genes in the genomes of Caenorhabditis nematodes. We specifically focused on nested arrangements, that is, cases in which an RNA gene is entirely contained in an intron of another gene. Comparing these arrangements between species simplifies the inference of orthology and, therefore, of evolutionary fates of nested genes. Two distinct patterns are evident in the data. Genes encoding small nuclear RNAs (snRNAs) and transfer RNAs form large families, which have persisted since before the common ancestor of Metazoa. Yet, individual genes die relatively rapidly, with few orthologs having survived since the divergence of Caenorhabditis elegans and Caenorhabditis briggsae. In contrast, genes encoding small nucleolar RNAs (snoRNAs) are either single-copy or form small families. Individual snoRNAs turn over at a relatively slow rate-most C. elegans genes have clearly identifiable orthologs in C. briggsae. We also found that in Drosophila, genes from larger snRNA families die at a faster rate than their counterparts from single-gene families. These results suggest that a relationship between family size and the rate of gene turnover may be a general feature of genome evolution.

Indexed as

Multigene FamilyAnimalsCaenorhabditisCaenorhabditis elegansEvolution, MolecularGenome, HelminthRNA, HelminthRNA, Small UntranslatedRNA, HelminthRNA, Small Untranslated

Identifiers

PMID22467905
PMCPMC3342880
OpenAlexW2108129476

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.