RNA sequencing, also known as RNA-Seq, is a powerful technique used to study gene expression at the transcript level and is primarily used to measure the abundance of RNA molecules. While its primary purpose is not variant detection like DNA sequencing, RNA-Seq can still be applied for variant detection in certain contexts. Here are some applications of RNA-Seq for detecting variants:

  1. Single Nucleotide Polymorphism (SNP) Detection: RNA-Seq can be used to detect single nucleotide variations in expressed genes. By aligning RNA-Seq reads to a reference genome or transcriptome, you can identify SNPs in coding regions. This is particularly useful for studying genetic variations associated with diseases.
  2. Alternative Splicing: RNA-Seq is excellent for studying alternative splicing, a process where different combinations of exons are included in the final mRNA transcript. Variants in splicing sites or regulatory elements can lead to altered splicing patterns, which can be detected through RNA-Seq data analysis.
  3. Fusion Gene Detection: RNA-Seq can be used to identify gene fusions or chimeric transcripts, which are often the result of structural variations such as translocations. These fusions can be detected by examining RNA-Seq read pairs that map to different genes.
  4. Allelic Expression Imbalance: RNA-Seq can detect allelic expression imbalance by quantifying the expression levels of alleles for a given gene. This can reveal whether one allele is expressed more than the other due to genetic variants.
  5. SNV Detection in Non-Coding RNAs: In addition to coding RNAs, RNA-Seq can also be used to detect single nucleotide variations in non-coding RNAs, such as microRNAs, long non-coding RNAs, and small nucleolar RNAs, which play important roles in gene regulation.
  6. RNA Editing Detection: RNA editing events, such as adenosine-to-inosine (A-to-I) editing, can be identified through RNA-Seq by comparing the sequenced RNA to the reference genome. This can reveal post-transcriptional modifications of RNA molecules.
  7. Transcriptome Profiling in Cancer: RNA-Seq can be applied to identify variants and mutations in cancer-related genes, providing insights into the genetic basis of cancer and potential therapeutic targets.
  8. Pathogen Detection: In viral and microbial RNA-Seq, variants and mutations in pathogen genomes can be detected, which is crucial for understanding the evolution of infectious agents and monitoring changes in virulence.
    When using RNA-Seq for variant detection, it's important to consider the limitations, such as the need for appropriate bioinformatics tools and careful data analysis. Additionally, since RNA-Seq provides information on expressed transcripts, it is more suitable for detecting variants in transcribed regions of the genome compared to DNA sequencing, which can cover the entire genome.

Dr. Md. Monirul Islam
Senior Scientist

Fig: In a typical RNA-seq experiment, RNA is isolated from target samples, sequencing libraries are created, a high-throughput sequencer is used to produce hundreds of millions of short paired-end reads, the reads are aligned to a reference genome or transcriptome, and then downstream analysis is performed for expression estimation, differential expression, transcript isoform discovery, and other purposes.