Evidence map›Paper›PMID 23433342›Full record

ArticleBMC evolutionary biology2013

A system-level, molecular evolutionary analysis of mammalian phototransduction.

Brandon M Invergo, Ludovica Montanucci, Hafid Laayouni, Jaume Bertranpetit

Open access · goldAbstract read
In one paragraph

Article in BMC evolutionary biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

10 citing papers in PubMed, 29 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 1 country.

Brandon M InvergoInstitute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain.
Ludovica Montanucci
Hafid Laayouni
Jaume Bertranpetit
Institut de Biologia Evolutiva · ESPompeu Fabra University · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVisual perception is initiated in the photoreceptor cells of the retina via the phototransduction system. This system has shown marked evolution during mammalian divergence in such complex attributes as activation time and recovery time. We have performed a molecular evolutionary analysis of proteins involved in mammalian phototransduction in order to unravel how the action of natural selection has been distributed throughout the system to evolve such traits.

resultsWe found selective pressures to be non-randomly distributed according to both a simple protein classification scheme and a protein-interaction network representation of the signaling pathway. Proteins which are topologically central in the signaling pathway, such as the G proteins, as well as retinoid cycle chaperones and proteins involved in photoreceptor cell-type determination, were found to be more constrained in their evolution. Proteins peripheral to the pathway, such as ion channels and exchangers, as well as the retinoid cycle enzymes, have experienced a relaxation of selective pressures. Furthermore, signals of positive selection were detected in two genes: the short-wave (blue) opsin (OPN1SW) in hominids and the rod-specific Na+/ Ca2+, K+ ion exchanger (SLC24A1) in rodents.

conclusionsThe functions of the proteins involved in phototransduction and the topology of the interactions between them have imposed non-random constraints on their evolution. Thus, in shaping or conserving system-level phototransduction traits, natural selection has targeted the underlying proteins in a concerted manner.

Indexed as

Light Signal TransductionSelection, GeneticAnimalsHumansOpsinsPhotoreceptor Cells, VertebratePrimatesSystems BiologyOpsins

Identifiers

PMID23433342
PMCPMC3616935
OpenAlexW2163252113

What OpenQuestion holds

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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.