Evidence map›Paper›PMID 17826006›Full record

ArticleGene2007

Evolution of protein families: is it possible to distinguish between domains of life?

Marta Sales-Pardo, Albert O B Chan, Luís A N Amaral, Roger Guimerà

Open access · greenAbstract readComparative Study
In one paragraph

Article in Gene, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 47% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

4 authors at 1 institution in 1 country.

Marta Sales-PardoDepartment of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA. msales@northwestern.edu
Albert O B Chan
Luís A N Amaral
Roger Guimerà
Northwestern University · US

Funding

Integrative Approach to Characterizing Gene RegulationK25GM069546 · NIGMS · NORTHWESTERN UNIVERSITY · PI AMARAL, LUIS A. NUNES · 2004 to 2008
$786k
NIGMS NIH HHS K25 GM069546
6 · The paper itself

Abstract

Understanding evolutionary relationships between species can shed new light into the rooting of the tree of life and the origin of eukaryotes, thus, resulting in a long standing interest in accurately assessing evolutionary parameters at time scales on the order of a billion of years. Prior work suggests large variability in molecular substitution rates, however, we still do not know whether such variability is due to species-specific trends at a genomic scale, or whether it can be attributed to the fluctuations inherent in any stochastic process. Here, we study the statistical properties of gene and protein-family sizes in order to quantify the long time scale evolutionary differences and similarities across species. We first determine the protein families of 209 species of bacteria and 20 species of archaea. We find that we are unable to reject the null hypothesis that the protein-family sizes of these species are drawn from the same distribution. In addition, we find that for species classified in the same phylogenetic branch or in the same lifestyle group, family size distributions are not significantly more similar than for species in different branches. These two findings can be accounted for in terms of a dynamical birth, death, and innovation model that assumes identical protein-family evolutionary rates for all species. Our theoretical and empirical results thus strongly suggest that the variability empirically observed in protein-family size distributions is compatible with the expected stochastic fluctuations for an evolutionary process with identical genomic evolutionary rates. Our findings hold special importance for the plausibility of some theories of the origin of eukaryotes which require drastic changes in evolutionary rates for some period during the last 2 billion years.

Indexed as

Evolution, MolecularAnimalsArchaeal ProteinsBacterial ProteinsComputer SimulationDatabases, ProteinGenome, ArchaealGenome, BacterialHumansArchaeal ProteinsBacterial Proteins

Identifiers

PMID17826006
PMCPMC2441766
OpenAlexW2033009644

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.