Evidence map›Paper›PMID 19815689›Full record

ArticleMolecular biology and evolution2010

Estimates of the effect of natural selection on protein-coding content.

Von Bing Yap, Helen Lindsay, Simon Easteal, Gavin Huttley

Open access · hybridAbstract read
In one paragraph

Article in Molecular biology and evolution, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed, 46 citations in OpenAlex.

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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 2 institutions in 2 countries.

Von Bing YapDepartment of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore. stayapvb@nus.edu.sg
Helen Lindsay
Simon Easteal
Gavin Huttley
Australian National University · AUNational University of Singapore · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analysis of natural selection is key to understanding many core biological processes, including the emergence of competition, cooperation, and complexity, and has important applications in the targeted development of vaccines. Selection is hard to observe directly but can be inferred from molecular sequence variation. For protein-coding nucleotide sequences, the ratio of nonsynonymous to synonymous substitutions (omega) distinguishes neutrally evolving sequences (omega = 1) from those subjected to purifying (omega < 1) or positive Darwinian (omega > 1) selection. We show that current models used to estimate omega are substantially biased by naturally occurring sequence compositions. We present a novel model that weights substitutions by conditional nucleotide frequencies and which escapes these artifacts. Applying it to the genomes of pathogens causing malaria, leprosy, tuberculosis, and Lyme disease gave significant discrepancies in estimates with approximately 10-30% of genes affected. Our work has substantial implications for how vaccine targets are chosen and for studying the molecular basis of adaptive evolution.

Indexed as

CodonEvolution, MolecularModels, GeneticModels, StatisticalSelection, GeneticBase CompositionChi-Square DistributionComputer SimulationGenes, ProtozoanMutationPlasmodiumSequence AlignmentCodon

Identifiers

PMID19815689
PMCPMC2822286
OpenAlexW2144493375

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.