Evidence map›Paper›PMID 21573208›Full record

ArticlePLoS computational biology2011

Gene expression in the rodent brain is associated with its regional connectivity.

Lior Wolf, Chen Goldberg, Nathan Manor, Roded Sharan, Eytan Ruppin

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
1.9field-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

38 citing papers in PubMed, 60 citations in OpenAlex.

  1. Article
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  3. Towards a biologically annotated brain connectome.Nature reviews. Neuroscience · 2023
    Review
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  18. Review
  19. Network neuroscience.Nature neuroscience · 2017
    Review
  20. Cognitive genomics: Linking genes to behavior in the human brain.Network neuroscience (Cambridge, Mass.) · 2017
    Article
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

5 authors at 1 institution in 1 country.

Lior WolfBlavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel. wolf@cs.tau.ac.i
Chen Goldberg
Nathan Manor
Roded Sharan
Eytan Ruppin
Tel Aviv University · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The putative link between gene expression of brain regions and their neural connectivity patterns is a fundamental question in neuroscience. Here this question is addressed in the first large scale study of a prototypical mammalian rodent brain, using a combination of rat brain regional connectivity data with gene expression of the mouse brain. Remarkably, even though this study uses data from two different rodent species (due to the data limitations), we still find that the connectivity of the majority of brain regions is highly predictable from their gene expression levels-the outgoing (incoming) connectivity is successfully predicted for 73% (56%) of brain regions, with an overall fairly marked accuracy level of 0.79 (0.83). Many genes are found to play a part in predicting both the incoming and outgoing connectivity (241 out of the 500 top selected genes, p-value<1e-5). Reassuringly, the genes previously known from the literature to be involved in axon guidance do carry significant information about regional brain connectivity. Surveying the genes known to be associated with the pathogenesis of several brain disorders, we find that those associated with schizophrenia, autism and attention deficit disorder are the most highly enriched in the connectivity-related genes identified here. Finally, we find that the profile of functional annotation groups that are associated with regional connectivity in the rodent is significantly correlated with the annotation profile of genes previously found to determine neural connectivity in C. elegans (Pearson correlation of 0.24, p<1e-6 for the outgoing connections and 0.27, p<1e-5 for the incoming). Overall, the association between connectivity and gene expression in a specific extant rodent species' brain is likely to be even stronger than found here, given the limitations of current data.

Indexed as

Models, NeurologicalAlgorithmsAnimalsArtificial IntelligenceBrainCaenorhabditis elegansComputational BiologyDatabases, FactualGene ExpressionMiceNeural PathwaysRats

Identifiers

PMID21573208
PMCPMC3088660
OpenAlexW2074051274

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.