Skip to content
DraconiticResearch
Search Sources API
174,684 studies31 sourcesUpdated 52 min ago
Peer-reviewedCC BY-NC-NDNature

Connecting single-cell transcriptomes to projectomes in the mouse visual cortex

  • Staci A. Sorensen1,2
  • Nathan W. Gouwens3,2
  • Yun Wang3,2
  • Matthew Mallory3,2
  • Agata Budzillo3,2
  • Rachel A. Dalley3,2
  • Brian Lee3,2
  • Olga Gliko3,2
  • Hsien-Chi Kuo3,2
  • Xiuli Kuang4
  • Rusty Mann3,2
  • Leila Ahmadinia3,2
88 more authors
  • Lauren Alfiler3,2
  • Fahimeh Baftizadeh3,2
  • Katherine S. Baker3,2
  • Sarah Bannick3,2
  • Darren Bertagnolli3,2
  • Kris Bickley3,2
  • Phillip Bohn3,2
  • Jasmine Bomben3,2
  • Chris Bowman3,2
  • Gabriella Boyer3,2
  • Krissy Brouner3,4
  • Dillan Brown3,4
  • Alex Cahoon3,2
  • Natalie Chen3,2
  • Chao Chen4,2
  • Kai Chen4,2
  • Maggie M. Chvilicek3,2
  • Forrest Collman3,2
  • Tanya L. Daigle3,2
  • Tim Dawes3,2
  • Rebecca A. de Frates3,2
  • Nick Dee3,2
  • Maxwell Departee3,2
  • Tom Egdorf3,2
  • Laila El-Hifnawi3,2
  • Rachel Enstrom3,2
  • Luke Esposito3,2
  • Colin Farrell3,2
  • Rohan Gala3,2
  • Clare Gamlin3,2
  • Amanda Gary3,2
  • Andrew Glomb3,2
  • Olena Gerasymchuk3,2
  • Jeff Goldy3,2
  • Hong Gu3,2
  • Kristen Hadley3,4
  • Mike Hawrylycz3,2
  • Alex M. Henry3,2
  • DiJon D. Hill3,2
  • Karla E. Hirokawa3,2
  • Zili Huang4,2
  • Katelyn Johnson3,2
  • Zoe Juneau3,5,6
  • Sara Kebede3,2
  • Lisa Kim3,4
  • Lauren Kruse3,2
  • Changkyu Lee3,2
  • Arielle L. Leon3,2

60 listed; 100 in total.

6 affiliations
  1. 1Allen Institute for Brain Science, Seattle, WA, USA. [email protected]
  2. 2Allen Institute for Brain Science
  3. 3Allen Institute for Brain Science, Seattle, WA, USA
  4. 4School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, China
  5. 5Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
  6. 6HUST-Suzhou Institute for Brainsmatics, JITRI Institute for Brainsmatics, Suzhou, China
Open at sourceDOICite

Abstract

The mammalian brain is composed of diverse neuron types that play different functional roles. Recent single-cell RNA sequencing approaches have led to a whole brain taxonomy of transcriptomically-defined cell types, yet cell type definitions that include multiple cellular properties can offer additional insights into a neuron's role in brain circuits. While the Patch-seq method can investigate how transcriptomic properties relate to the local morphological and electrophysiological properties of cell types, linking transcriptomic identities to long-range projections is a major unresolved challenge. To address this, we collected coordinated Patch-seq and whole brain morphology data sets of excitatory neurons in mouse visual cortex. From the Patch-seq data, we defined 16 integrated morpho-electric-transcriptomic (MET)-types; in parallel, we reconstructed the complete morphologies of 300 neurons. We unified the two data sets with a multi-step classifier, to integrate cell type assignments and interrogate cross-modality relationships. We find that transcriptomic variations within and across MET-types correspond with morphological and electrophysiological phenotypes. In addition, this variation, along with the anatomical location of the cell, can be used to predict the projection targets of individual neurons. We also shed new light on infragranular cell types and circuits, including cell-type-specific, interhemispheric projections. With this approach, we establish a comprehensive, integrated taxonomy of excitatory neuron types in mouse visual cortex and create a system for integrated, high-dimensional cell type classification that can be extended to the whole brain and potentially across species.

Related

  1. Integrating single-cell and bulk transcriptomes identifies neuronal heat-stress-associated candidate genes in a reef-building coral
    R. Li, M. Tresguerres, C. D. Kenkel
    bioRxivPreprintCC BY-NDFull textMolecular biology & gene regulationbioRxiv
  2. Integrated re-analysis of bulk and single-cell transcriptomic data reveals limited ferroptosis and neuroinflammation signatures after sevoflurane exposure in the aged rat hippocampus and human prefrontal cortex cells
    Zhenrong Zhang, Chen Hu, Yan Liu +3
    Frontiers in cell and developmental biologyPeer-reviewedCC BYFull textGeneral biochemistryEurope PMC
  3. Common-Garden Transcriptomes Distinguish Leaf-Form-Associated from Site-Associated Expression in Zygophyllum xanthoxylum
    Xiaoyang Wang, Wenjing Shen, Xingshun Wang +4
    International journal of molecular sciencesPeer-reviewedCC BYFull textGeneral biochemistryEurope PMC
  4. IsoPrism predicts isoform usage from short-read transcriptomes through structure-guided competitive allocation.
    Peiyi Yan, Jingchen Liu, Xuejian Cui +3
    Briefings in bioinformaticsPeer-reviewedCC BY-NCFull textMolecular biology & gene regulationEurope PMC
  5. Paternal diet shapes paternal and maternal transcriptomes in the early embryo through parallel sperm-associated mechanisms
    L. C. Steg, I. Blanc Giro, K. Uzel +2
    bioRxivPreprintCC BYFull textMolecular biology & gene regulationbioRxiv

Cite

BibTeXRIS
BibTeX
@article{sorensen2026connecting,
  title = {{Connecting single-cell transcriptomes to projectomes in the mouse visual cortex}},
  author = {Staci A. Sorensen and Nathan W. Gouwens and Yun Wang and Matthew Mallory and Agata Budzillo and Rachel A. Dalley and Brian Lee and Olga Gliko and Hsien-Chi Kuo and Xiuli Kuang and Rusty Mann and Leila Ahmadinia and Lauren Alfiler and Fahimeh Baftizadeh and Katherine S. Baker and Sarah Bannick and Darren Bertagnolli and Kris Bickley and Phillip Bohn and Jasmine Bomben and Chris Bowman and Gabriella Boyer and Krissy Brouner and Dillan Brown and Alex Cahoon and Natalie Chen and Chao Chen and Kai Chen and Maggie M. Chvilicek and Forrest Collman and Tanya L. Daigle and Tim Dawes and Rebecca A. de Frates and Nick Dee and Maxwell Departee and Tom Egdorf and Laila El-Hifnawi and Rachel Enstrom and Luke Esposito and Colin Farrell and Rohan Gala and Clare Gamlin and Amanda Gary and Andrew Glomb and Olena Gerasymchuk and Jeff Goldy and Hong Gu and Kristen Hadley and Mike Hawrylycz and Alex M. Henry and DiJon D. Hill and Karla E. Hirokawa and Zili Huang and Katelyn Johnson and Zoe Juneau and Sara Kebede and Lisa Kim and Lauren Kruse and Changkyu Lee and Arielle L. Leon},
  journal = {Nature},
  year = {2026},
  month = jul,
  doi = {10.1038/s41586-026-10424-8},
  url = {https://doi.org/10.1038/s41586-026-10424-8},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - Connecting single-cell transcriptomes to projectomes in the mouse visual cortex
AU  - Staci A. Sorensen
AU  - Nathan W. Gouwens
AU  - Yun Wang
AU  - Matthew Mallory
AU  - Agata Budzillo
AU  - Rachel A. Dalley
AU  - Brian Lee
AU  - Olga Gliko
AU  - Hsien-Chi Kuo
AU  - Xiuli Kuang
AU  - Rusty Mann
AU  - Leila Ahmadinia
AU  - Lauren Alfiler
AU  - Fahimeh Baftizadeh
AU  - Katherine S. Baker
AU  - Sarah Bannick
AU  - Darren Bertagnolli
AU  - Kris Bickley
AU  - Phillip Bohn
AU  - Jasmine Bomben
AU  - Chris Bowman
AU  - Gabriella Boyer
AU  - Krissy Brouner
AU  - Dillan Brown
AU  - Alex Cahoon
AU  - Natalie Chen
AU  - Chao Chen
AU  - Kai Chen
AU  - Maggie M. Chvilicek
AU  - Forrest Collman
AU  - Tanya L. Daigle
AU  - Tim Dawes
AU  - Rebecca A. de Frates
AU  - Nick Dee
AU  - Maxwell Departee
AU  - Tom Egdorf
AU  - Laila El-Hifnawi
AU  - Rachel Enstrom
AU  - Luke Esposito
AU  - Colin Farrell
AU  - Rohan Gala
AU  - Clare Gamlin
AU  - Amanda Gary
AU  - Andrew Glomb
AU  - Olena Gerasymchuk
AU  - Jeff Goldy
AU  - Hong Gu
AU  - Kristen Hadley
AU  - Mike Hawrylycz
AU  - Alex M. Henry
AU  - DiJon D. Hill
AU  - Karla E. Hirokawa
AU  - Zili Huang
AU  - Katelyn Johnson
AU  - Zoe Juneau
AU  - Sara Kebede
AU  - Lisa Kim
AU  - Lauren Kruse
AU  - Changkyu Lee
AU  - Arielle L. Leon
PY  - 2026
DA  - 2026/07/01
JO  - Nature
DO  - 10.1038/s41586-026-10424-8
UR  - https://doi.org/10.1038/s41586-026-10424-8
AB  - The mammalian brain is composed of diverse neuron types that play different functional roles. Recent single-cell RNA sequencing approaches have led to a whole brain taxonomy of transcriptomically-defined cell types, yet cell type definitions that include multiple cellular properties can offer additional insights into a neuron's role in brain circuits. While the Patch-seq method can investigate how transcriptomic properties relate to the local morphological and electrophysiological properties of cell types, linking transcriptomic identities to long-range projections is a major unresolved challenge. To address this, we collected coordinated Patch-seq and whole brain morphology data sets of excitatory neurons in mouse visual cortex. From the Patch-seq data, we defined 16 integrated morpho-electric-transcriptomic (MET)-types; in parallel, we reconstructed the complete morphologies of 300 neurons. We unified the two data sets with a multi-step classifier, to integrate cell type assignments and interrogate cross-modality relationships. We find that transcriptomic variations within and across MET-types correspond with morphological and electrophysiological phenotypes. In addition, this variation, along with the anatomical location of the cell, can be used to predict the projection targets of individual neurons. We also shed new light on infragranular cell types and circuits, including cell-type-specific, interhemispheric projections. With this approach, we establish a comprehensive, integrated taxonomy of excitatory neuron types in mouse visual cortex and create a system for integrated, high-dimensional cell type classification that can be extended to the whole brain and potentially across species.
SN  - 0028-0836
SN  - 1476-4687
ER  -