Codon-Substitution Models for Detecting Molecular Adaptation at Individual Sites Along Specific Lineages
Clicks: 2
ID: 294562
2002
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
0.3
/100
2 views
1 readers
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #202 of 245 articles by views in molecular biology and evolution
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 245 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
The nonsynonymous (amino acid–altering) to synonymous (silent) substitution rate ratio (ω = dN/dS) provides a measure of natural selection at the protein level, with ω = 1, >1, and <1, indicating neutral evolution, purifying selection, and positive selection, respectively. Previous studies that used this measure to detect positive selection have often taken an approach of pairwise comparison, estimating substitution rates by averaging over all sites in the protein. As most amino acids in a functional protein are under structural and functional constraints and adaptive evolution probably affects only a few sites at a few time points, this approach of averaging rates over sites and over time has little power. Previously, we developed codon-based substitution models that allow the ω ratio to vary either among lineages or among sites. In this paper we extend previous models to allow the ω ratio to vary both among sites and among lineages and implement the new models in the likelihood framework. These models may be useful for identifying positive selection along prespecified lineages that affects only a few sites in the protein. We apply those branch-site models as well as previous branch- and site-specific models to three data sets: the lysozyme genes from primates, the tumor suppressor BRCA1 genes from primates, and the phytochrome (PHY) gene family in angiosperms. Positive selection is detected in the lysozyme and BRCA genes by both the new and the old models. However, only the new models detected positive selection acting on lineages after gene duplication in the PHY gene family. Additional tests on several data sets suggest that the new models may be useful in detecting positive selection after gene duplication in gene family evolution.
Abstract Quality Issue:
This abstract appears to be incomplete or contains metadata (25 words).
Try re-searching for a better abstract.
| Reference Key |
openalex_W2029549914
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Ziheng Yang, Rasmus Nielsen |
| Journal | molecular biology and evolution |
| Year | 2002 |
| DOI |
10.1093/oxfordjournals.molbev.a004148
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.