Introduction to Exome Capture RNA-Sequencing
Many RNA exome sequencing techniques are restricted to a small number of known transcripts or require expensive deep sequencing. RNA exome capture sequencing overcomes these challenges by combining RNA-Seq and exome enrichment.
This technique captures only the coding regions of the transcriptome, resulting in higher throughput and lower sequencing depth than non-exome capture techniques. For sequence-specific capture of the RNA exome, the presence of a poly-A tail is not necessary. As a result, RNA exome capture sequencing is an excellent choice for RNA-Seq with low-quality samples or starting material.
Figure 1. The exome-capture transcriptome protocol. (Cieslik, 2015)
Advantages of Exome Capture RNA-Sequencing
For sequence-specific capture of the RNA exome, the presence of a poly-A tail is not necessary. As a result, RNA exome capture sequencing is an excellent choice for RNA-Seq with low-quality samples or starting material.
Isolating transcriptome coding regions improves discovery power while needing a fraction of the read depth required by total RNA sequencing.
- Allows for high sample throughput and cost-effectiveness.
- Affordability is prioritized by focusing on high-value content.
- Obtains high-quality data from degraded samples, such as FFPE (formalin-fixed, paraffin-embedded) tissues.
- Low sample input, as little as ten nanograms of total RNA, without sacrificing sensitivity.
Application to Clinical Cancer Sequencing
Despite advancements in tissue preservation and handling, obtaining RNA of sufficient integrity from clinical specimens remains a challenge. Oncological tissues obtained through needle core biopsies and preserved as formalin-fixed paraffin-embedded (FFPE) blocks continue to pose a challenge for the most used RNA-seq, despite their widespread use in cell lines. Because expression profiles are useful in cancer diagnosis, prognosis, and therapy, there is a growing clinical need for techniques that yield better data from samples of varying source material and quality. To date, no protocol has been demonstrated to measure absolute gene expression reliably and accurately from degraded RNA, preventing the use of RNA-seq to profile the expression of clinical samples. Novel methods are designed to activate these valuable data for precision medicine approaches or retrospective studies because neither mRNA enrichment “poly(A)” nor rRNA depletion “Ribo-Zero” libraries can be efficiently produced from degraded and cross-linked RNA.
Another option is to use complementary capture probes to directly select for known transcripts. Direct target enrichment protocols were first developed to separate the exome from total genomic DNA for cost-effective clinical resequencing, and then adapted for cDNA targets. In capture sequencing, each transcript of interest is probed multiple times with an excess of probes, allowing transcript recovery even if the poly(A) tail is missing. Targeted RNA sequencing has recently been proposed as a method for sampling low-abundance isoforms and even measuring gene expression. However, recommending a novel transcriptome profiling protocol for routine use in a clinical or research setting necessitates a thorough assessment of its relative merits across a variety of metrics. Since poly(A) RNA-seq and Ribo-Zero libraries are the most used for research and by The Cancer Genome Atlas, it's critical that the recommended method is largely compatible with them.
References
- Cieslik M, Chugh R, Wu YM, et al. The use of exome capture RNA-seq for highly degraded RNA with application to clinical cancer sequencing. Genome research. 2015 Sep 1;25(9).
- Hrdlickova R, Toloue M, Tian B. RNA‐Seq methods for transcriptome analysis. Wiley Interdisciplinary Reviews: RNA. 2017 Jan;8(1).
- Schuierer S, Carbone W, Knehr J, et al. A comprehensive assessment of RNA-seq protocols for degraded and low-quantity samples. BMC genomics. 2017 Dec;18(1).
