Biology subjects

Zador, A. M.

Publications and source records attributed to Zador, A. M..

4 recordsLinked to original sources

bioRxiv2018

Single-cell molecular connectomics of intracortically-projecting neurons

The neocortex is organized into distinct areas, whose interconnectivity underlies sensorimotor transformations and integration1-7. These behaviorally critical functions are mediated by intracortically-projecting neurons (ICPN), which are a heterogeneous population of cells sending axonal branches to distinct cortical areas as well as to subcortical targets8-10. Although population-based11-14 and single-cell15-19 intracortical wiring diagrams are being identified, the transcriptional signatures corresponding to single-cell axonal projections of ICPN to multiple sites remain unknown. To address this question, we developed a high-throughput approach, \"ConnectID\", to link connectome and transcriptome in single neurons. ConnectID combines MAPseq projection mapping17,20 (to identify single-neuron multiplex projections) with single-cell RNA sequencing (to identify corresponding gene expression). Using primary somatosensory cortex (S1) ICPN as proof-of-principle neurons, we identify three cardinal targets: (1) the primary motor cortex (M1), (2) the secondary somatosensory cortex (S2) and (3) subcortical targets (Sub). Using ConnectID, we identify transcriptional modules whose combined activities reflect multiplex projections to these cardinal targets. Based on these findings, we propose that the combinatorial activity of connectivity-defined transcriptional modules serves as a generic molecular mechanism to create diverse axonal projection patterns within and across neuronal cell types.

neuroscience↗

bioRxiv2018

Spatial organization of projection neurons in the mouse auditory cortex identified by in situ barcode sequencing

Understanding neural circuits requires deciphering interactions among myriad cell types defined by spatial organization, connectivity, gene expression, and other properties. Resolving these cell types requires both single neuron resolution and high throughput, a challenging combination with conventional methods. Here we introduce BARseq, a multiplexed method based on RNA barcoding for mapping projections of thousands of spatially resolved neurons in a single brain, and relating those projections to other properties such as gene or Cre expression. Mapping the projections to 11 areas of 3579 neurons in mouse auditory cortex using BARseq confirmed the laminar organization of the three top classes (IT, PT-like and CT) of projection neurons. In depth analysis uncovered a novel projection type restricted almost exclusively to transcriptionally-defined subtypes of IT neurons. By bridging anatomical and transcriptomic approaches at cellular resolution with high throughput, BARseq can potentially uncover the organizing principles underlying the structure and formation of neural circuits.

neuroscience↗

bioRxiv2017

Efficient in situ barcode sequencing using padlock probe-based BaristaSeq

Cellular DNA/RNA tags (barcodes) allow for multiplexed cell lineage tracing and neuronal projection mapping with cellular resolution. Conventional approaches to reading out cellular barcodes trade off spatial resolution with throughput. Bulk sequencing achieves high throughput but sacrifices spatial resolution, whereas manual cell picking has low throughput. In situ sequencing could potentially achieve both high spatial resolution and high throughput, but current in situ sequencing techniques are inefficient at reading out cellular barcodes. Here we describe BaristaSeq, an optimization of a targeted, padlock probe-based technique for in situ barcode sequencing compatible with Illumina sequencing chemistry. BaristaSeq results in a five-fold increase in amplification efficiency, with a sequencing accuracy of at least 97%. BaristaSeq could be used for barcode-assisted lineage tracing, and to map long-range neuronal projections.\n\nKey PointsO_LIIn situ sequencing by gap-filling padlock probes is limited by the strand displacement of DNA polymerases\nC_LIO_LIIllumina sequencing chemistry offers superior signal-to-noise ratio in situ compared to sequencing by ligation\nC_LIO_LIBaristaSeq as an accurate method for barcode sequencing in situ with improved gap-filling efficiency\nC_LI

molecular biology↗

bioRxiv2017

A single-cell anatomical blueprint for intracortical information transfer from primary visual cortex

The wiring diagram of the neocortex determines how information is processed across dozens of cortical areas. Each area communicates with multiple others via extensive long-range axonal projections 1-6, but the logic of inter-area information transfer is unresolved. Specifically, the extent to which individual neurons send dedicated projections to single cortical targets or distribute their signals across multiple areas remains unclear5,7-20. Distinguishing between these possibilities has been challenging because axonal projections of only a few individual neurons have been reconstructed. Here we map the projection patterns of axonal arbors from 591 individual neurons in mouse primary visual cortex (V1) using two complementary methods: whole-brain fluorescence-based axonal tracing21,22 and high-throughput DNA sequencing of genetically barcoded neurons (MAPseq)23. Although our results confirm the existence of dedicated projections to certain cortical areas, we find these are the exception, and that the majority of V1 neurons broadcast information to multiple cortical targets. Furthermore, broadcasting cells do not project to all targets randomly, but rather comprise subpopulations that either avoid or preferentially innervate specific subsets of cortical areas. Our data argue against a model of dedicated lines of intracortical information transfer via \"one neuron - one target area\" mapping. Instead, long-range communication between a sensory cortical area and its targets may be based on a principle whereby individual neurons copy information to, and potentially coordinate activity across, specific subsets of cortical areas.

neuroscience↗