Evidence map›Paper›PMID 18367463›Full record

ArticleMolecular biology and evolution2008

Fast evolution of core promoters in primate genomes.

Han Liang, Yeong-Shin Lin, Wen-Hsiung Li

Open access · bronzeAbstract read
In one paragraph

Article in Molecular biology and evolution, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. Mechanisms of protein evolution.Protein science : a publication of the Protein Society · 2022
    Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Lowly expressed human microRNA genes evolve rapidly.Molecular biology and evolution · 2009
    Article
  7. Article
  8. 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

3 authors at 2 institutions in 2 countries.

Han LiangDepartment of Ecology and Evolution, University of Chicago, USA.
Yeong-Shin Lin
Wen-Hsiung Li
University of Chicago · USNational Yang Ming Chiao Tung University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite much interest in regulatory evolution, how promoters have evolved remains poorly studied, mainly owing to paucity of data on promoter regions. Using a new set of high-quality experimentally determined core promoters of the human genome, we conducted a comparative analysis of 2,492 human and rhesus macaque promoters and their neighboring nearly neutral regions. We found that the core promoters have an average rate of nucleotide substitution substantially higher than that at 4-fold degenerate sites and only slightly lower than that for the assumed neutral controls of neighboring noncoding regions, suggesting that core promoters are subject to very weak selective constraints. Interestingly, we identified 24 core promoters (at false discovery rate = 50%) that have evolved at an accelerated rate compared with the neutral controls, suggesting that they may have undergone positive selection. The inferred positively selected genes show strong bias in molecular function. We also used population genetic approaches to examine the evolution of core promoters in human populations and found evidence of positive selection at some loci. Taken together, our results suggest that positive selection has played a substantial role in the evolution of transcriptional regulation in primates.

Indexed as

Evolution, MolecularGenomePromoter Regions, GeneticAnimalsBase SequenceGenome, HumanHumansMacacaMolecular Sequence DataPopulationPrimates

Identifiers

PMID18367463
PMCPMC2878000
OpenAlexW2128888061

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.