Evidence map›Paper›PMID 35830791›Full record

ArticleCell reports2022

Unified classification of mouse retinal ganglion cells using function, morphology, and gene expression.

Jillian Goetz, Zachary F Jessen, Anne Jacobi, Adam Mani, Sam Cooler, Devon Greer, Sabah Kadri, Jeremy Segal, Karthik Shekhar, Joshua R Sanes and 1 more

Abstract read
In one paragraph

Article in Cell reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 129 papers.

0numbers the graph read from it
0cells of the map it votes in
129citing 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

129 citing papers in PubMed.

  1. Review
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  8. Approaching a connectome of the human foveal retina.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  14. Review
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69 more citing papers are in PubMed but not listed here.

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

11 authors.

Jillian GoetzDepartment of Ophthalmology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Zachary F JessenDepartment of Ophthalmology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Northwestern University Interdepartmental Neuroscience Program, Northwestern University, Evanston, IL, USA; Medical Scientist Training Program, Northwestern University, Chicago, IL, USA.
Anne JacobiF.M. Kirby Neurobiology Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Center for Brain Science and Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA.
Adam ManiDepartment of Ophthalmology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Sam CoolerNorthwestern University Interdepartmental Neuroscience Program, Northwestern University, Evanston, IL, USA.
Devon GreerDepartment of Ophthalmology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Northwestern University Interdepartmental Neuroscience Program, Northwestern University, Evanston, IL, USA.
Sabah KadriDepartment of Pathology, Pritzker School of Medicine, University of Chicago, Chicago, IL, USA.
Jeremy SegalDepartment of Pathology, Pritzker School of Medicine, University of Chicago, Chicago, IL, USA.
Karthik ShekharDepartment of Chemical and Biomolecular Engineering and Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA.
Joshua R SanesCenter for Brain Science and Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA.
Gregory W SchwartzDepartment of Ophthalmology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Department of Neurobiology, Weinberg College of Arts and Sciences, Northwestern University, Evanston, IL, USA. Electronic address: greg.schwartz@northwestern.edu.

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM008152 · NIGMS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ARDEHALI, HOSSEIN · 1987 to 2021
$24.0M
Training Program in Neurobiology of Information StorageT32MH067564 · NIMH · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Daniel A Dombeck · 2003 to 2026
$4.7M
Comprehensive Classification Of Neuronal Subtypes By Single Cell TranscriptomicsU01MH105960 · NIMH · HARVARD UNIVERSITY · PI REGEV, AVIV, SANES, JOSHUA R · 2014 to 2016
$4.5M
Combinatorial roles of cadherins in retinal circuit assembly.R01EY022073 · NEI · HARVARD UNIVERSITY · PI SANES, JOSHUA R · 2012 to 2020
$3.7M
Novel circuit mapping strategies to reverse engineer the retinaDP2EY026770 · NEI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI SCHWARTZ, GREGORY WILLIAM · 2015 to 2015
$2.3M
Functional consequences of heterotypic retinal ganglion cell couplingR01EY031329 · NEI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI SCHWARTZ, GREGORY WILLIAM · 2020 to 2024
$1.8M
Synapses as Independent Computational Units in the Excitatory Pathways of the RetinaR01EY031029 · NEI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI SCHWARTZ, GREGORY WILLIAM · 2020 to 2023
$1.6M
Uncovering the molecular identity of retinal cell types, and their responses to nerve injury using single-cell transcriptomicsR00EY028625 · NEI · UNIVERSITY OF CALIFORNIA BERKELEY · PI SHEKHAR, KARTHIK · 2020 to 2022
$740k
Mechanisms of neurovascular coupling in the retina and their dysfunction in diabetesF30EY031565 · NEI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI JESSEN, ZACHARY · 2020 to 2023
$193k
Functional specialization by asymmetric receptive fields in the retinaF31EY029593 · NEI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI COOLER, SAM · 2018 to 2020
$108k
NEI NIH HHS DP2 EY026770NEI NIH HHS F30 EY031565NEI NIH HHS F31 EY029593NEI NIH HHS R00 EY028625NEI NIH HHS R01 EY022073NEI NIH HHS R01 EY031029NEI NIH HHS R01 EY031329NIGMS NIH HHS T32 GM008152NIMH NIH HHS T32 MH067564NIMH NIH HHS U01 MH105960
6 · The paper itself

Abstract

Classification and characterization of neuronal types are critical for understanding their function and dysfunction. Neuronal classification schemes typically rely on measurements of electrophysiological, morphological, and molecular features, but aligning such datasets has been challenging. Here, we present a unified classification of mouse retinal ganglion cells (RGCs), the sole retinal output neurons. We use visually evoked responses to classify 1,859 mouse RGCs into 42 types. We also obtain morphological or transcriptomic data from subsets and use these measurements to align the functional classification to publicly available morphological and transcriptomic datasets. We create an online database that allows users to browse or download the data and to classify RGCs from their light responses using a machine learning algorithm. This work provides a resource for studies of RGCs, their upstream circuits in the retina, and their projections in the brain, and establishes a framework for future efforts in neuronal classification and open data distribution.

Indexed as

RetinaRetinal Ganglion CellsAnimalsGene ExpressionMiceCP: Neuroscienceretina, retinal ganglion cell, transcriptomics, morphology, light responses, classification

Identifiers

PMID35830791
PMCPMC9364428

What OpenQuestion holds

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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.