Evidence map›Paper›PMID 38390967›Full record

ArticleeLife2024

High-throughput mapping of single-neuron projection and molecular features by retrograde barcoded labeling.

Peibo Xu, Jian Peng, Tingli Yuan, Zhaoqin Chen, Hui He, Ziyan Wu, Ting Li, Xiaodong Li, Luyue Wang, Le Gao and 5 more

Open access · goldAbstract read
In one paragraph

Article in eLife, 2024. 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
4.2field-weighted citation impact, top 5% 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, 18 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

15 authors at 3 institutions in 1 country.

Peibo Xu *Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.ORCID https://orcid.org/0000-0001-7129-0445
Jian Peng *School of Life Science and Technology & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China.
Tingli Yuan *Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.ORCID https://orcid.org/0000-0001-6676-8790
Zhaoqin Chen *Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.
Hui He *Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.
Ziyan WuInstitute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.
Ting LiSchool of Life Science and Technology & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China.
Xiaodong LiInstitute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.ORCID https://orcid.org/0000-0002-2459-8778
Luyue WangCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Science, Shanghai, China.
Le GaoInstitute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.
Jun YanInstitute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.
Wu WeiCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Science, Shanghai, China.
Chengyu T LiInstitute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.
Zhen-Ge LuoSchool of Life Science and Technology & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China.ORCID https://orcid.org/0000-0001-5037-0542
Yuejun ChenInstitute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, China.ORCID https://orcid.org/0000-0002-4625-2604
Center for Excellence in Brain Science and Intelligence Technology · CNShanghaiTech University · CNShanghai Institute of Nutrition and Health · CN

Funding

Central Guidance on Local Science and Technology Development Fund YDZX20233100001002National Key Research and Development Program of China 2018YFA0108000National Key Research and Development Program of China 2019YFA0709504National Key Research and Development Program of China 2021ZD0202500National Natural Science Foundation of China 31827803National Natural Science Foundation of China 32130035National Natural Science Foundation of China 32161133024National Natural Science Foundation of China 32170806National Natural Science Foundation of China 92168107National Natural Science Foundation of China 92368204Shanghai Municipal Science and Technology Major Project 2018SHZDZX05Shanghai Science and Technology Development Funds 23JS1401400STI2030-Major Projects 2021ZD0200900Strategic Priority Research Program of the Chinese Academy of Sciences XDB32030200the Innovations of Science and Technology 2030 from the Ministry of Science and Technology of China 2021ZD0203601the Shanghai Municipal Science and Technology Major Project 2021SHZDZX
6 · The paper itself

Abstract

Deciphering patterns of connectivity between neurons in the brain is a critical step toward understanding brain function. Imaging-based neuroanatomical tracing identifies area-to-area or sparse neuron-to-neuron connectivity patterns, but with limited throughput. Barcode-based connectomics maps large numbers of single-neuron projections, but remains a challenge for jointly analyzing single-cell transcriptomics. Here, we established a rAAV2-retro barcode-based multiplexed tracing method that simultaneously characterizes the projectome and transcriptome at the single neuron level. We uncovered dedicated and collateral projection patterns of ventromedial prefrontal cortex (vmPFC) neurons to five downstream targets and found that projection-defined vmPFC neurons are molecularly heterogeneous. We identified transcriptional signatures of projection-specific vmPFC neurons, and verified

Indexed as

NeuritesNeuronsBrainNeural PathwaysPrefrontal CortexconnectomemousemPFCneurosciencescRNA-seq

Identifiers

PMID38390967
PMCPMC10914349
OpenAlexW4392110697

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.