Single nuclei RNA-Seq supplies snapshot of gene expression across brain

from Spectrum.com by Ann Griswold

A new tool provides speedy analysis of gene expression patterns in individual neurons from postmortem brain tissue. Researchers have used the method to compare the genetic signatures of more than 3,000 neurons from distant brain regions.

Scientists typically use a technique called RNA-Seq to measure gene expression in neurons isolated from postmortem brains. However, analyzing the data from this approach is daunting because the analysis must be done one cell at a time.

The new method combines RNA-Seq with software that allows researchers to analyze the expression patterns of thousands of neurons at once. Researchers from UCSD described the automated technique, called single-nucleus RNA sequencing (SNS), in June in Science.

The researchers tested the method on postmortem brain tissue from a 51-year-old woman with no known neurological illnesses. They used a laser to dissect 3,227 neurons from six brain areas, including those involved in language, cognition, vision and social behavior. They then performed RNA-Seq on the cells, getting a readout for RNAs produced in each cell.

The software identifies genes by matching a short segment of each RNA to a gene on a reference map of the human genome. The researchers then quantified each gene’s expression level.

Overview of single nuclei sampling methodology

rna-seq

A. Schematic of human brain at the level of BA8 showing approximate region sampled, typical tissue quantity processed for fluorescent activated cell sorting (FACS), the approximate proportion of NeuN+ nuclei obtained, the quantity of NeuN+ nuclei needed for a single C1 loading, and the average single nuclei capture rate. Expected sample scaling and minimal tissue needed for a single C1 experiment is summarized. B. Samples generated using pooled sorted NeuN+ nuclei from BA8, BA10, BA17, BA21, BA22 and BA41/42 as well as matching tissue sections were analyzed for expression of oligodendrocyte (Oligo.), astrocyte (Astro.), endothelial (Endo.) and neuronal (Neuro.) marker genes (17). Violin plots show expression values for associated nuclear (Nuc.) and tissue (Tiss.) sample groupings. C. Data sets from ~120 pooled nuclei derived from either BA21 or BA17 were used to confirm enrichment for neurons or glia in NeuN+ and NeuN- sorts, respectively. D. Histograms showing the frequency of all single NeuN+ nuclei analyzed in this study binned by level of RBFOX3 (NeuN) expression. Neuronal nuclei were distinguished on the basis of either SLC17A7 (excitatory) or GAD1 (inhibitory) marker gene expression.

The process correctly identified the subtypes of 2,253 neurons that ramp up brain activity and 972 neurons that dampen it. Within these two broad classes, the neurons fell into 16 groups based on their location and their origin in the developing brain. For example, neurons from the visual cortex show different patterns of gene expression than do neurons from the temporal cortex, which processes hearing and language.

The findings expand the list of features that distinguish neurons from other cells in the brain. Researchers could use the method to identify patterns of gene expression in the brains of people with autism.

Lake BB, Ai R, Kaeser GE, Salathia NS, Yung YC, Liu R, Wildberg A, Gao D, Fung HL, Chen S, Vijayaraghavan R, Wong J, Chen A, Sheng X, Kaper F, Shen R, Ronaghi M, Fan JB, Wang W, Chun J, Zhang K. (2016) Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain. Science 352(6293):1586-90. [abstract]

Source – Spectrum.com

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