RNA sequencing

RNA sequencing

RNA sequencing techniques are used to determine the sequence of nucleotide bases, adenine (A), cytosine (C), guanine (G) and uracil (U) in RNA molecules.

Usually RNA is first converted into cDNA (complementary DNA) with a reverse transcriptase enzyme and then a second strand synthesis reaction is performed so that DNA sequencing techniques can be applied to double stranded DNA copies of RNA transcripts. Since this method can lose information from the 5' and 3' ends of the transcript, other methods have been developed that omit the second strand synthesis reaction and ligate adapters to the cDNA for sequencing reactions. Sequencing adapters are consistent sequences that when applied to flank the cDNA fragments produces a cDNA library.

RNA sequencing is replacing gene expression arrays to analyse the spectrum and abundance of transcripts in a given cell or tissue type at a given time. The technique called RNA-Seq, also known as whole transcriptome shotgun sequencing generates cDNA and uses it in next-generation sequencing.

UK-based Oxford Nanopore Technologies devised a system to directly sequence RNA with a device called the MinION, where electrical current is applied across a nanoscale molecular pore and current fluctuations detect the RNA sequence as the RNA molecule snakes through the pore. This RNA sequencing device was used by NASA on the International Space Station because NASA is interested in using it to identify on board microorganisms and to monitor changes in human health or microbiomes and also the possibility of detecting life based on DNA or RNA elsewhere in the universe.

RNA-Seq delivers an unbiased and unprecedented high-resolution view of the global transcriptional landscape, which allows an affordable and accurate approach for gene expression quantification and differential gene expression analysis between multiple groups of samples. RNA-Seq can identify novel and previously-unexpected transcripts without the need for a reference genome, allowing de novo assembly of new transcriptome that is not previously studied before. It also enables the discovery of novel gene structures, alternatively spliced isoforms, gene fusions, SNPs/InDel, and allele-specific expression (ASE).

i. RNA-Seq is a sensitive tool for gene expression profiling. Compared to microarray, RNA-Seq offers a digital read that is more accurate for all gene expression.

The authors found 1089 genes differentially expressed between the CLL and normal B cells (Table 1). As was expected, the most differentially expressed genes are immunoglobulins due to the clonality of the CLL cells. Pathway analyses revealed that genes involved in metabolic pathways had higher expression in CLL, while genes related to splicesome, proteasome, and ribosome were substantially down-regulated in CLL.

Figure 1. CLL transcriptional landscape. (A) The coding potential of differentially expressed genes between the CLL and normal samples. (B) Normalized expression of transposable elements (TEs). (C) Genes with condition-specific splicing ratios. (D) Allele-specific expression of somatic mutations.

Figure 4. Major transcriptional CLL subgroups. (A) Clustering of CLL and normal samples. (B) Consensus cluster. (C) Multidimensional scaling of CLL and normal samples based on gene expression. (D&E) Enrichment score plot.




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