Evidence map›Paper›PMID 32176293›Full record

ArticleGenome biology and evolution2020

Significant Evolutionary Constraints on Neuron Cells Revealed by Single-Cell Transcriptomics.

Ganlu Hu, Jie Li, Guang-Zhong Wang

Open access · goldAbstract read
In one paragraph

Article in Genome biology and evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

12 citing papers in PubMed, 81 citations in OpenAlex.

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  8. scBrainMap: a landscape for cell types and associated genetic markers in the brain.Database : the journal of biological databases and curation · 2023
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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

3 authors at 1 institution in 1 country.

Ganlu HuCAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Jie LiCAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Guang-Zhong WangCAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Chinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advances in single-cell RNA-sequencing technology have enabled us to characterize a variety of different cell types in each brain region. However, the evolutionary differences among these cell types remain unclear. Here, we analyzed single-cell RNA-seq data of >280,000 cells and developmental transcriptomes of bulk brain tissues. At the single-cell level, we found that the evolutionary constraints on the cell types of different organs significantly overlap with each other and the transcriptome of neuron cells is one of the most restricted evolutionarily. In addition, mature neurons are under more constraints than neuron stem cells as well as nascent neurons and the order of the constraints of various cell types of the brain is largely conserved in different subregions. We also found that although functionally similar brain regions have comparable evolutionary constraints, the early fetal brain is the least constrained and this pattern is conserved in the mouse, macaque, and humans. These results demonstrate the importance of maintaining the plasticity of early brain development during evolution. The delineation of evolutionary differences between brain cell types has great potential for an improved understanding of the pathogenesis of neurological diseases and drug development efforts aimed at the manipulation of molecular activities at the single-cell level.

Indexed as

Biological EvolutionNeurogenesisTranscriptomeAnimalsBrainComputational BiologyGene Expression ProfilingHaplorhiniHumansMiceNeuronsSingle-Cell Analysisbrain developmentcell typeevolutionary constraintssingle-cell RNA-seqtranscriptome evolution

Identifiers

PMID32176293
PMCPMC7186789
OpenAlexW3010893550

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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.