Evidence map›Paper›PMID 19995462›Full record

ArticleBMC evolutionary biology2009

Statistical tests for natural selection on regulatory regions based on the strength of transcription factor binding sites.

Alan M Moses

Abstract read
In one paragraph

Article in BMC evolutionary biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Cis-regulatory elements and human evolution.Current opinion in genetics & development · 2014
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Methods to detect selection on noncoding DNA.Methods in molecular biology (Clifton, N.J.) · 2012
    Review
  16. Article
  17. Article
  18. 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

1 author.

Alan M MosesDepartment of Cell & Systems Biology, University of Toronto, Toronto, ON M5S 3B2, Canada. alan.moses@utoronto.ca

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough cis-regulatory changes play an important role in evolution, it remains difficult to establish the contribution of natural selection to regulatory differences between species. For protein coding regions, powerful tests of natural selection have been developed based on comparisons of synonymous and non-synonymous substitutions, and analogous tests for regulatory regions would be of great utility.

resultsHere, tests for natural selection on regulatory regions are proposed based on nucleotide substitutions that occur in characterized transcription factor binding sites (an important type functional element within regulatory regions). In the absence of selection, these substitutions will tend to reduce the strength of existing binding sites. On the other hand, purifying selection will act to preserve the binding sites in regulatory regions, while positive selection can act to create or destroy binding sites, as well as change their strength. Using standard models of binding site strength and molecular evolution in the absence of selection, this intuition can be used to develop statistical tests for natural selection. Application of these tests to two well-characterized regulatory regions in Drosophila provides evidence for purifying selection.

conclusionThis demonstrates that it is possible to develop tests for selection on regulatory regions based on the specific functional constrains on these sequences.

Indexed as

Regulatory Sequences, Nucleic AcidSelection, GeneticAnimalsBinding SitesDrosophilaDrosophila melanogasterDrosophila ProteinsModels, GeneticTranscription FactorsDrosophila ProteinsTranscription Factors

Identifiers

PMID19995462
PMCPMC2800119

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.