RNA Sequencing Increase the Chance of RNA Biomarker Discovery
SummaryBiomarkers are defined as measurable biological characteristics that associate with normal or pathological conditions. They possess clinical relevance, including diagnostic, prognostic, and predictive values. RNA, not only an essential part of central dogma, is certainly a relatively untapped resource for biomarker discovery of various diseases.
- Author Name: Dianna Gellar
Biomarkers are defined as measurable biological characteristics that associate with normal or pathological conditions. They possess clinical relevance, including diagnostic, prognostic, and predictive values. RNA, not only an essential part of central dogma, is certainly a relatively untapped resource for biomarker discovery of various diseases.
Cumulating data show that RNA molecules, including mRNAs, lncRNAs, miRNAs, siRNAs, piRNAs, snoRNAs, snRNAs, are more sensitive and specific than protein biomarkers, since they are easy to detect and quantify at very low abundance. Moreover, RNA has the advantages of providing dynamic insights into cellular states and regulatory processes, comparing DNA biomarkers. Those founds turned scientists’ attentions to RNA based biomarkers.
RNA Sequencing Approach to Identify Biomarker
Microarray analysis and RT-qPCR that are widely used for detecting known RNAs, have provided a wealth of information about transcriptional profiles in pathological states, despite mixed results.
Within the past decades, next generation sequencing (NGS) technology has evolved as a valuable tool for identifying coding and non-coding RNAs at whole genome level. This change has been driven by the realization that researchers need to increase the depth and ways of RNA/DNA sequencing to capture a more comprehensive view. RNA-Seq are capable of annotating structural variants, allele-specific expression and disease-associated SNP, analyzing alternative splicing events. Coupled with bioinformatics pipelines, many extracellular RNAs (exRNAs) continued to be found as potential biomarkers. Circular RNAs (CircRNAs), for instance, were found to be stably existed in exosomes and differentially expressed between cancer and normal serum recently, making a potential source of biomarkers as well.
Long Read Sequencing Technology - The Opportunity of RNA-Seq
RNA analysis based on short read sequencing requires the conversion of RNA template into cDNA strands, in which reverse transcription or amplification could introduce bias and not all transcripts are amplified with the same efficiency, leading to disruption of some types of RNA and transitional amplification of others. Besides, all information about base modifications is lost during RCR amplification. Long read RNA sequencing enables accurate quantification and identification of RNA or cDNA through complete full-length sequencing, without fragmentation or amplification, simplifying assembly and eliminating potential sources of preference. Direct RNA sequencing allows to identify single-base RNA modifications and nucleotide sequences simultaneously, with the longest transcripts currently capable of being processed by nanopore sequencing platform exceeding 20 kb.
RNA Biomarkers Database for Cancer
With the accumulation of the nucleic acid biomarker studies, several disease-centered databases have been created and popularized. Several databases, such as HMDD, CoReCG, BC-BET, and MIRUMIR, are now publicly available for researchers to do integrated analyses and show results without command-line operations or extensive computational understanding.
To conclude, RNA Sequencing (RNA-Seq) is an increasingly popular technology for biomarker discovery in cancer research. High-throughput and long read RNA-Seq produce large quantities of data that can reflect multiple biology but requires complex computational bioinformatics pipelines to enable interpretation. Novel software approaches can bring a standardized, rapid approach to analysis of this data for the purposes of biomarker discovery and application.