Introduction and Application of Transcriptome Sequencing

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Introduction and Application of Transcriptome Sequencing By definition, a transcriptome is the entire collection of messenger Ribonucleic Acid molecules contained in a specific cell or tissue type in an organism. It correlates with the range of RNA being transcribed from a genome under investigation at a given time and condition. The RNA Molecules involved here are messenger RNA, ribosomal RNA, transfer RNA and the non-coding RNA molecules. Transcriptome sequencing is also called RNA Sequence Technologies. It is the process of sequencing the cDNA of a cell or tissue to collect information about the total RNA content in a sample at a certain condition and time.

Introduction to Transcriptome Sequencing Initially, methods like quantitative polymerase chain reaction and northern blot were used to study gene expression and were based on an inconclusive database. They could only be used to


measure single transcripts. Shortly before the introduction of transcriptome sequencing, gene expression was then measured using the first transcriptomic studies - the sanger sequencingbased approach and hybridization-based microarrays approach. These approaches came as high-throughput options at a significantly lower cost. Large quantities of genes could be detected using a single hybridization. However, these new methods happened to pose some problems. One had to be aware of a certain amount of information about the sequences that are interrogated. Also, where the sequences are nearly identical, cross-hybridization artifact poses a problem during analysis. If there are genes with low or high expressions, it isn't easy to quantify them correctly using these two methods. RNA Sequencing came as a more reliable option designed based on Next Generation Sequencing (NGS). It has exposed and enhanced the understanding of the complex and vibrant nature of transcriptome. The basic procedures involved here are RNA isolation and conversion into complementary DNA, sequence library preparation, then sequencing based on a NextGeneration Sequencing setting. Based on your objectives, you should consider experimental details like the use of biological and technical alternatives, sequencing depth, and its estimated coverage area before the start of this experiment. At times, these factors can scarcely affect the quality of the result obtained. Nevertheless, researchers should design the protein sequencing process to favor the result’s quality, time, and resources invested. The process of isolating RNA from its biological sample should be done with ample precision using the best method available. This is to ensure that the RNA integrity number remains high (from 6 to 10 preferably). Also, RNA protection should be applied to keep it from degrading while being isolated.

Applications of Transcriptome Sequencing 1. Discovery of non-coding RNA Research has it that over 93% of the human genome undergoes transcription to become RNA. A minor 2% of this human genome makes up the protein-encoding region, while the rest of the genome is available for transcription in non-protein encoded RNA (ncRNA) molecule. A few of these ncRNAs regulate gene expression at different levels by binding to proteins, RNA, and DNA. A larger number of ncRNAs are yet to be discovered with their functions. Isolating these RNAs during research can lead to their degradation. This can be avoided by using RNA protection to keep them stable. Non-coding RNAs find practical applications in the treatment of Alzheimer's disease. 2. Comparing different Gene Expression levels Previously, the gene expression levels were compared using microarrays. This method was suitable but had narrowed sensitivity. It could not be used to capture minute changes in the


expression level of the specific gene. RNA sequencing serves as a better option as it can deduce the absolute number of molecules in each of the cell populations and compare the results to find the Gene Expression levels. Through gene expression, protein sequencing has helped researchers achieve a better understanding of the pathogenesis of cancer. Cancer cells are differently expressed and have makeups that make it clear that allele-specific duplications can induce cancer. 3. Used to discover new gene Transcriptome sequencing can produce outputs that can be assembled without foreknowledge of genome annotations. Existing databases do not contain detailed annotations. However, this new technology allows for the discovery of new genes. Some researchers have even discovered four genes related to the reproductive system regarding the differences in salinity. 4. Identification of Sequence Differences Sequence differences like identifying fusion genes and coding sequence polymorphism studies can be identified using transcriptome sequencing. An alternative method (splicing) results in the production of multiple messenger RNA transcripts by one gene. In eukaryotes, gene transcription forms precursors or pre-messenger RNAs during splicing. Transcriptome sequencing, however, detects the sequence of all transcripts alongside their depths.

Conclusion RNA Sequencing is based on Next Generation Sequencing (NGS) technologies. It makes up for the challenges that came with the sanger sequencing-based and hybridization-based microarray approaches. This article gives an overview of what transcriptome sequencing is about and four ways it can be applied to solve problems.


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