Summary: Researchers improved BARseq to map millions of neurons, improving our understanding of brain connections. This advanced technique reveals how vision loss changes the visual cortex, making it more similar to neighboring brain areas.
This information can inform treatments for diseases like Alzheimer’s and schizophrenia. The study highlights the potential of BARseq to revolutionize neuroscience.
Highlights:
- BARseq maps millions of neurons, identifying cells by their gene expression and tracing neuronal circuits.
- Vision loss alters the visual cortex, making it resemble neighboring brain areas.
- This research advances treatment strategies for brain disorders by understanding neural connections.
Source: CSHL
Understanding the connections between different areas of the brain could pave the way for better treatment strategies for diseases like Alzheimer’s, schizophrenia and depression.
In 2019, as a postdoc in the Zador Lab at Cold Spring Harbor Laboratory (CSHL), Xiaoyin Chen helped develop a technique to map these connections. BARseq identifies brain cells by the genes they use and traces the connecting neural circuits. Early versions of BARseq mapped gene expression across thousands of neuronal pathways, using “barcodes” or short snippets of RNA.
Chen is now an assistant research scientist at the Allen Brain Institute. He recently reunited with Professor Anthony Zador of CSHL to improve the capabilities of BARseq. What does this look like? Instead of thousands of neurons, BARseq can now map millions.
“We are working to advance BARseq. We want this to be easy for everyone to use, faster and more responsive. Can we read more information with it? With a much larger scale, you can start to answer different questions,” says Chen.
The team began their search for answers in the brain’s visual cortex. Sight is one of the most common ways humans perceive the world. Information passes from the eyes to the visual cortex to be processed. But what happens in the brain when neuronal incursions from the visual cortex are cut off or don’t form at all?
“People have known for a long time that visual input is very important in shaping the brain,” Chen says. “But we don’t know, with the exact cell type resolution provided by BARseq, what’s actually happening.”
The team used BARseq to map the brains of nine mice and trace gene expression in each mouse’s visual cortex. This is the first time this technique has been used to map so many entire brains. Surprisingly, the team found that if the mice became blind, genes in the visual cortex began to resemble those in neighboring cortical areas of the brain.
“The effects of vision loss were very widespread,” says Chen. “The visual cortex itself changes. It looks more like the areas around it. Many questions remain about how development controls this configuration.
Chen is now working to expand BARseq’s capabilities even further. He and his team use this technique to study how connections are made in the developing brain and how those connections evolve.
“Understanding how cortical areas are constituted is the first step to understanding these connections,” he says. “But that is not enough. We have yet to discover how they progress during development. BARseq can bring us closer to this goal.
About this research news in neuroscience and brain mapping
Author: Sarah Giarnieri
Source: CSHL
Contact: Sara Giarnieri – CSHL
Picture: Image is credited to Neuroscience News
Original research: Free access.
“In situ whole-cortex sequencing reveals input-dependent area identity” by Xiaoyin Chen et al. Nature
Abstract
In situ sequencing of the entire cortex reveals input-dependent area identity
The cerebral cortex is composed of neuronal types with diverse gene expression and organized into specialized cortical areas. These areas, each with characteristic cytoarchitecture, connectivity, and neuronal activity, are connected in modular networks.
However, it remains to be determined whether these spatial organizations are reflected in neuronal transcriptomic signatures and how these signatures are established during development.
Here, we used BARseq, a high-throughput in situ sequencing technique, to interrogate the expression of 104 cell type marker genes in 10.3 million cells, including 4,194,658 cortical neurons across nine forebrain hemispheres of mouse, at cellular resolution. De novo clustering of gene expression in single neurons revealed transcriptomic types consistent with previous single-cell RNA sequencing studies.
The composition of transcriptomic types is highly predictive of cortical area identity. Furthermore, areas with similar compositions of transcriptomic types, which we defined as cortical modules, overlap with highly connected areas, suggesting that the same modular organization is reflected in both transcriptomic signatures and connectivity. .
To explore how the transcriptomic profiles of cortical neurons are developmentally dependent, we assessed the distribution of cell types after neonatal binocular enucleation.
Notably, binocular enucleation caused cell type composition profiles to shift from visual areas to neighboring cortical areas within the same module, suggesting that peripheral inputs sharpen the distinct transcriptomic identities of areas within cortical modules.
With the high throughput, low cost, and reproducibility of BARseq, our study provides proof of principle for using large-scale in situ sequencing to reveal brain-wide molecular architecture and understand its development.
News Source : neurosciencenews.com
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