Decoding Neuron Transcriptome
The human brain is composed of billions of neurons and supporting cells, forming a complex network. Understanding the molecular mechanism of neurons in the process of information processing is a basic goal of neuroscience, and new tools can better characterize the maintenance of neuron function and the development of dysfunction in the nervous system, and promote important advances in the neurological field. With the advent of the "post-genome" era, Next-Generation Sequencing (NGS) technology is rapidly detecting the ability to change the molecular basis of neuronal function, transcriptome analysis to determine the complete molecular characteristics of cells, and epigenetic analysis to determine cascade of events that induced or maintain these characteristics.
Transcriptome reflected the gene expression profile of RNA molecules, represented the current molecular state of a given cell population, and clarified the molecular characteristics of a specific cell population and cell state. The cell types of the mammalian brain are highly heterogeneous, and half of the cells are glial cells. There are thousands of types of neuron cells, which differ in shape, size, connection, and electrical characteristics. Even in the same neuron subtype, the molecular characteristics will vary depending on the signal input and the local environment.
Neuron Characteristics Determined by NGS
NGS covers a set of sequencing technologies that can read relatively short nucleotide sequences of millions to billions of DNA fragments in parallel. Sequencing technology has developed at an astonishing speed, making the cost of base sequencing drop rapidly. NGS is used in many analyses, such as genomic DNA mutation screening, bisulfite sequencing, chromatin capture, and immunoprecipitation. In addition, NGS has catalyzed many new biological analysis methods as shown in Fig.1, enabling a more comprehensive and more mechanical description of the molecular characteristics of cells.
Fig.1 Neuronal cell characteristics determined by NGS testing. (Shin, 2014)
One of the most rapidly adopted applications of NGS is profiling of gene expression. In the Gene Expression Comprehensive Database (GEO), there are more than 2500 RNA-sequencing (RNA-seq) data sets, and this number is increasing rapidly. In fact, 85% of the human genome is transcribed, although the functions of most non-coding RNAs are not explained, they are particularly high in mammalian brains and show region-specific expression. These phenomena imply a strict regulation of the gene transcriptome in the central nervous system (CNS) and an important role in neuronal responses. Using target-specific amplification for quantitative PCR (qPCR) to select mRNA molecules from total RNA, and to save chain information of different complexity and performance through a variety of library preparation schemes are two important considerations when performing RNA-seq.
Fig.2 Three widely used protocols for strand-specific RNA sequencing library preparation. (Shin, 2014)
Advantages of RNA-sqe
- RNA-seq has a larger dynamic range to estimate the number of each mRNA molecule.
- RNA-seq can quantify the expression digitally, and the expression level is highly accurate and repeatable.
- RNA-seq does not have a priori set for detecting and quantifying transcripts, so it can quantify the abundance of isoforms, splice variants and even post-transcriptional RNA base modifications (RNA editing) in each transcript.
- RNA-seq can reveal new rare transcripts.
Emerging sequencing technologies related to neuroscience are developing rapidly, new analytical methods are emerging to explore new aspects of the epigenome or transcriptome. The transcriptome is an unbiased snapshot of the structure and abundance of RNA molecules. Using transcriptome analysis, not only can we begin to map gene-function relationships at the cellular level, but we can also better understand the pathophysiology of abnormal neuronal behavior. Creative Biolabs has advanced technology and services in neurobiology research. Please feel free to contact us if you are interested or have any questions.
- Shin J.; et al. Decoding neural transcriptomes and epigenomes via high-throughput sequencing. Nature neuroscience. 2014, 17(11): 1463-1475.