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Automated reconstruction of dendritic and axonal arbors reveals molecular correlates of neuroanatomy

Gliko, Olga and Mallory, Matt and Dalley, Rachel and Gala, Rohan and Gornet, James and Zeng, Hongkui and Sorensen, Staci and Sümbül, Uygar (2022) Automated reconstruction of dendritic and axonal arbors reveals molecular correlates of neuroanatomy. . (Unpublished)

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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 arbor reconstruction on a dataset of 802 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 many cellular properties used to define cell types. We uncover molecular correlates of laminar innervation on multiple molecularly defined neuronal subclasses and types. In particular, our results reveal molecular correlates of the variability in Layer 1 (L1) innervation even in a transcriptomically defined subpopulation of Martinotti cells in the adult mouse neocortex.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper ItemData ItemCode ItemCode
Gliko, Olga0000-0002-5014-7209
Mallory, Matt0000-0002-8744-3837
Dalley, Rachel0000-0001-7461-7845
Gala, Rohan0000-0003-1872-0957
Gornet, James0000-0002-5431-7340
Zeng, Hongkui0000-0002-0326-5878
Sorensen, Staci0000-0002-6799-2126
Sümbül, Uygar0000-0001-7134-8897
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license. This version posted March 8, 2022. We wish to thank the Allen Institute for Brain Science founder, Paul G Allen, for his vision, encouragement and support. We thank Michael Hawrylycz and Claire Gamlin for helpful feedback on the manuscript. This work was supported by the National Institute Of Mental Health of the National Institutes of Health under award numbers 1U01MH114824-01 and 1RF1MH128778-01. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Data availability: Transcriptomic and morphological data supporting the findings of this study is available online at (“Neurons in Mouse Primary Visual Cortex”). Code availability: Code pertaining to this study as well as the trained neural network model for automated segmentation are available at and The authors have declared no competing interest.
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Paul G. Allen Family FoundationUNSPECIFIED
Record Number:CaltechAUTHORS:20220314-687639400
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Official Citation:Automated reconstruction of dendritic and axonal arbors reveals molecular correlates of neuroanatomy. Olga Gliko, Matt Mallory, Rachel Dalley, Rohan Gala, James Gornet, Hongkui Zeng, Staci Sorensen, Uygar Sümbül. bioRxiv 2022.03.07.482900; doi:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:113899
Deposited By: Tony Diaz
Deposited On:14 Mar 2022 20:31
Last Modified:14 Mar 2022 20:31

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