mRNA sequencing (mRNA-Seq) has quickly established itself as the method of choice for analyzing the transcriptomes of disease states, biological processes, and a variety of study designs. mRNA-Seq can recognize both known and novel transcript isoforms, gene fusions, and other features, as well as allele-specific expression, in addition to being a highly sensitive and accurate method of quantifying gene expression. Prior knowledge is not a hindrance to mRNA-Seq, which offers a complete picture of the coding transcriptome.
In terms of analyzing the transcriptome, mRNA-Seq has several advantages over gene expression arrays: (1) it has a greater dynamic range, allowing for more sensitive and accurate measurement of fold modifications in gene expression, (2) it captures both known and novel features, and (3) it can be used across a vast range of species.
Other research goals in a wide range of applications involves (1) quantitative profiling of transcripts in various tissues or specimens, under different situations and treatments, (2) discovery of novel transcripts, alternative splicing (AS), and transcript variations, (3) study of developmental mechanisms and drug resistance through tissue-specific transcripts or time-course gene expression, (4) biomarker discovery based on novel transcripts/isoforms, SNP/InDel categorization, and fusion gene evaluation, (5) omics analysis in combination with the transcriptome, and (6) investigation of the pathogenic mechanism and clinical subtypes in clinical diagnosis.
Figure 1. Workflow of mRNA-seq (Sudhagar, 2018)
cDNA Library Preparation: This will necessitate the addition of platform-specific "adapter sequences" and DNA amplification, but the exact procedure will be platform-specific at this point. A reverse transcriptase-mediated first-strand synthesis is accompanied by a DNA polymerase-mediated second strand synthesis in the amplification of DNA.
cDNA Sequencing: Sequence your cDNA library based on desired depth after the library has been prepared and adapters have been added. After the transcript data has been generated, the data can be mapped to a reference genome. The presence of splice variants and modifications can make the alignment process more difficult, and the reference genome used can also affect how difficult this stage is.
RNA-Seq Data Analysis: After the alignment stage, you can concentrate on data analysis. Tools like Sailfish, RSEM, and BitSeq12 will help evaluate expression levels, while more specialized tools like MISO, which evaluates alternatively spliced genes, are available.
Sample quality control (Sample QC) is the first step in the project workflow, and it ensures that the samples meet the RNA-Seq technique's requirements. The appropriate library is then constructed depending on your target organism and application, and it is then quality-tested (Library QC). The samples are then sequenced using a paired-end 150 bp sequencing strategy, and the resulting data is checked for quality (Data QC). Finally, bioinformatic analyses are carried out, with results that are ready for publication. Our mRNA-seq technique follows a step-by-step protocol, as shown in the flowsheet below. The preparation of the sample is followed by the preparation of the RNA library. RNA library is created by ployA capture (or rRNA removal) and reverse transcription of cDNA.