Evidence map›Paper›PMID 23745134›Full record

ArticleEvolutionary applications2013

A phylomedicine approach to understanding the evolution of auditory sensory perception and disease in mammals.

John D Kirwan, Michaël Bekaert, Jennifer M Commins, Kalina T J Davies, Stephen J Rossiter, Emma C Teeling

Open access · goldAbstract read
In one paragraph

Article in Evolutionary applications, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
4.0field-weighted citation impact, top 7% 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

6 citing papers in PubMed, 17 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

6 authors at 3 institutions in 2 countries.

John D KirwanUCD School of Biology and Environmental Science & UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin Dublin, Ireland.
Michaël Bekaert
Jennifer M Commins
Kalina T J Davies
Stephen J Rossiter
Emma C Teeling
University College Dublin · IEQueen Mary University of London · GBUniversity of Stirling · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hereditary deafness affects 0.1% of individuals globally and is considered as one of the most debilitating diseases of man. Despite recent advances, the molecular basis of normal auditory function is not fully understood and little is known about the contribution of single-nucleotide variations to the disease. Using cross-species comparisons of 11 'deafness' genes (Myo15, Ush1 g, Strc, Tecta, Tectb, Otog, Col11a2, Gjb2, Cldn14, Kcnq4, Pou3f4) across 69 evolutionary and ecologically divergent mammals, we elucidated whether there was evidence for: (i) adaptive evolution acting on these genes across mammals with similar hearing capabilities; and, (ii) regions of long-term evolutionary conservation within which we predict disease-associated mutations should occur. We find evidence of adaptive evolution acting on the eutherian mammals in Myo15, Otog and Tecta. Examination of selection pressures in Tecta and Pou3f4 across a taxonomic sample that included a wide representation of auditory specialists, the bats, did not uncover any evidence for a role in echolocation. We generated 'conservation indices' based on selection estimates at nucleotide sites and found that known disease mutations fall within sites of high evolutionary conservation. We suggest that methods such as this, derived from estimates of evolutionary conservation using phylogenetically divergent taxa, will help to differentiate between deleterious and benign mutations.

Indexed as

hearingphylomedicinepositive selectionpurifying selection

Identifiers

PMID23745134
PMCPMC3673470
OpenAlexW1996595186

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.