Evidence map›Paper›PMID 39068160›Full record

ArticleNature communications2024

High-throughput analysis of dendrite and axonal arbors reveals transcriptomic correlates of neuroanatomy.

Olga Gliko, Matt Mallory, Rachel Dalley, Rohan Gala, James Gornet, Hongkui Zeng, Staci A Sorensen, Uygar Sümbül

Abstract read
In one paragraph

Article in Nature communications, 2024. 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
–field-weighted citation impact
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.

  1. Review
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  3. Article
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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

8 authors.

Olga GlikoAllen Institute, Seattle, WA, USA. olgag@alleninstitute.org.ORCID 0000-0002-5014-7209
Matt MalloryAllen Institute, Seattle, WA, USA.
Rachel DalleyAllen Institute, Seattle, WA, USA.
Rohan GalaAllen Institute, Seattle, WA, USA.ORCID 0000-0003-1872-0957
James GornetCalifornia Institute of Technology, Pasadena, CA, USA.
Hongkui ZengAllen Institute, Seattle, WA, USA.ORCID 0000-0002-0326-5878
Staci A SorensenAllen Institute, Seattle, WA, USA.ORCID 0000-0002-6799-2126
Uygar SümbülAllen Institute, Seattle, WA, USA. uygars@alleninstitute.org.ORCID 0000-0001-7134-8897

Funding

Generation of novel cell type specific mouse genetic toolsU19MH114830 · NIMH · ALLEN INSTITUTE · PI ZENG, HONGKUI · 2017 to 2021
$64.7M
Collaboratory for atlasing cell type anatomy in the female and male mouse brainU01MH114824 · NIMH · COLD SPRING HARBOR LABORATORY · PI MITRA, PARTHA PRATIM · 2017 to 2021
$11.7M
Establishing a Comprehensive and Standardized Cell Type Characterization PlatformU01MH105982 · NIMH · ALLEN INSTITUTE · PI ANDERSON, DAVID J, ZENG, HONGKUI · 2014 to 2016
$5.1M
Scalable tools for consistent identification of neuronal cell types in mouse and humanRF1MH128778 · NIMH · ALLEN INSTITUTE · PI SORENSEN, STACI A, SUMBUL, UYGAR · 2021 to 2021
$1.1M
NIMH NIH HHS RF1 MH128778NIMH NIH HHS U01 MH105982NIMH NIH HHS U01 MH114824NIMH NIH HHS U19 MH114830U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) 1RF1MH128778-01U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) 1U01MH114824-01
6 · The paper itself

Abstract

Neuronal anatomy is central to the organization and function of brain cell types. However, anatomical variability within apparently homogeneous populations of cells can obscure such insights. Here, we report large-scale automation of neuronal morphology reconstruction and analysis on a dataset of 813 inhibitory neurons characterized using the Patch-seq method, which enables measurement of multiple properties from individual neurons, including local morphology and transcriptional signature. We demonstrate that these automated reconstructions can be used in the same manner as manual reconstructions to understand the relationship between some, but not all, cellular properties used to define cell types. We uncover gene expression correlates of laminar innervation on multiple transcriptomically defined neuronal subclasses and types. In particular, our results reveal correlates of the variability in Layer 1 (L1) axonal innervation in a transcriptomically defined subpopulation of Martinotti cells in the adult mouse neocortex.

Indexed as

AxonsDendritesNeocortexTranscriptomeAnimalsGene Expression ProfilingMaleMiceMice, Inbred C57BLNeuroanatomyNeurons

Identifiers

PMID39068160
PMCPMC11283452

What OpenQuestion holds

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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.