Evidence map›Paper›PMID 25678762›Full record

ArticleMolecular vision2015

Gene expression changes during retinal development and rod specification.

Fiona C Mansergh, Matthew Carrigan, Karsten Hokamp, G Jane Farrar

Open access · greenAbstract read
In one paragraph

Article in Molecular vision, 2015. 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
0.9field-weighted citation impact, top 25% 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, 9 citations in OpenAlex.

  1. Review
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  7. Retinal remodeling in human retinitis pigmentosa.Experimental eye research · 2016
    Review
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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 1 institution in 1 country.

Fiona C ManserghSmurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland.
Matthew CarriganSmurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland.
Karsten HokampSmurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland.
G Jane FarrarSmurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland.
Trinity College Dublin · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeRetinitis pigmentosa (RP) typically results from individual mutations in any one of >70 genes that cause rod photoreceptor cells to degenerate prematurely, eventually resulting in blindness. Gene therapies targeting individual RP genes have shown efficacy at clinical trial; however, these therapies require the surviving photoreceptor cells to be viable and functional, and may be economically feasible for only the more commonly mutated genes. An alternative potential treatment strategy, particularly for late stage disease, may involve stem cell transplants into the photoreceptor layer of the retina. Rod progenitors from postnatal mouse retinas can be transplanted and can form photoreceptors in recipient adult retinas; optimal numbers of transplantable cells are obtained from postnatal day 3-5 (P3-5) retinas. These cells can also be expanded in culture; however, this results in the loss of photoreceptor potential. Gene expression differences between postnatal retinas, cultured retinal progenitor cells (RPCs), and rod photoreceptor precursors were investigated to identify gene expression patterns involved in the specification of rod photoreceptors.

methodsMicroarrays were used to investigate differences in gene expression between cultured RPCs that have lost photoreceptor potential, P1 retinas, and fresh P5 retinas that contain significant numbers of transplantable photoreceptors. Additionally, fluorescence-activated cell sorting (FACS) sorted Rho-eGFP-expressing rod photoreceptor precursors were compared with Rho-eGFP-negative cells from the same P5 retinas. Differential expression was confirmed with quantitative polymerase chain reaction (q-PCR).

resultsAnalysis of the microarray data sets, including the use of t-distributed stochastic neighbor embedding (t-SNE) to identify expression pattern neighbors of key photoreceptor specific genes, resulted in the identification of 636 genes differentially regulated during rod specification. Forty-four of these genes when mutated have previously been found to cause retinal disease. Although gene function in other tissues may be known, the retinal function of approximately 61% of the gene list is as yet undetermined. Many of these genes' promoters contain binding sites for the key photoreceptor transcription factors Crx and Nr2e3; moreover, the genomic clustering of differentially regulated genes appears to be non-random.

conclusionsThis study aids in understanding gene expression differences between rod photoreceptor progenitors versus cultured RPCs that have lost photoreceptor potential. The results provide insights into rod photoreceptor development and should expedite the development of cell-based treatments for RP. Furthermore, the data set includes a large number of retinopathy genes; less-well-characterized genes within this data set are a resource for those seeking to identify novel retinopathy genes in patients with RP (GEO accession: GSE59201).

Indexed as

Gene Expression Regulation, DevelopmentalAnimalsAnimals, NewbornBinding SitesEye ProteinsGene Expression ProfilingGenes, ReporterGreen Fluorescent ProteinsHomeodomain ProteinsMiceMolecular Sequence AnnotationMultigene FamilyOligonucleotide Array Sequence AnalysisOrphan Nuclear ReceptorsPrimary Cell CulturePromoter Regions, Geneticcone rod homeobox proteinenhanced green fluorescent proteinEye ProteinsGreen Fluorescent ProteinsHomeodomain ProteinsNr2e3 protein, mouseOrphan Nuclear ReceptorsTrans-Activators

Identifiers

PMID25678762
PMCPMC4301594
OpenAlexW2128430524

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.