Release date: 2015-03-10
In general, the DNA contained in all cells in a certain species should be exactly the same, just because there is a difference between the RNAs expressed in each cell, so that these cells are different.
But "Why are tumor cells different from normal cells?"
Such an important issue involves not only the mutation of DNA, but also the RNA in different cells to solve the problem, which requires the use of RNA sequencing technology.
Upgraded version of DNA sequencing
RNA sequencing first requires the extraction of all RNA from a biological sample, followed by reverse transcription into c-DNA for high-throughput sequencing.
But compared to a static chromosome, the intracellular transcriptome is actually a dynamic process that is constantly changing. With the development of this technology, RNA sequencing can not only detect mRNA transcription, but also observe RNA expression profiles including different RNAs and small RNAs (miRNA, tRNA and ribosomal RNA).
Through research on RNA, researchers hope to determine when and where some cell types turn genes on and off. This is very helpful for the study of many diseases.
3D style map of RNA
RNA sequencing VS microarray
However, since the birth of RNA sequencing, it has had to face the debate among microarray technology enthusiasts. This technology is an important breakthrough technology in the field of genomics and a routine method for studying transcript information.
RNA sequencing is an ideal detection platform because of its ability to perform unbiased detection of new transcriptions, which means it does not require specific probes. Therefore, RNA sequencing is more adaptable than microarrays.
From a clinical perspective, RNA sequencing provides a lower signal-to-noise ratio and the ability to detect less or less abundant transcripts with greater specificity and sensitivity. This is very valuable for clinicians.
In many cases, the two techniques can be combined to make a more accurate assessment of the transcriptome. In particular, many RNA sequencing protocols have not been standardized, and researchers can use microarrays to verify the results of sequencing.
Standard to be established
However, RNA sequencing wants to change from a pure analytical method to a clinical testing tool. Scientists and regulators must develop standard analytical methods and baseline data to ensure accurate and reproducible testing.
Although there are many publications and conferences that focus on evaluating RNA sequencing platforms, specific laboratory protocols, and data analysis software, there is far no consensus.
In October last year, the FDA published details of the US Congressional guidelines for laboratory development diagnostic tests (LDTs) and accompanying diagnostics on its website, which will include RNA sequencing. This is a very important step for RNA sequencing to be used as an important clinical diagnostic tool.
RNA and precision medicine
The famous Mayo Clinic has recently developed a MAP-RSeq analysis approach that combines a bioinformatics tool to analyze Paired-End RNA sequencing data through an internally developed method.
Because RAN sequencing is highly adaptable to different clinical conditions, many scientists and publications indicate that RNA sequencing will be used clinically for all types of cancer.
If the laboratory development stage sets a base for the ability of RNA sequencing to be applied to the clinic, then with the advent of the era of precision medicine, this base will expand indefinitely in the next few years. If scientists can develop standard practices as soon as possible so that RNA sequencing can handle a large amount of clinical work, this will be critical for precision medicine.
Source: HI gene
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