NEW YORK (GenomeWeb) – A team led by researchers from Australia's Garvan Institute of Medical Research this week reported new data demonstrating the superiority of a targeted RNA sequencing method called "capture sequencing" (CaptureSeq) over standard RNA sequencing and qRT-PCR for detecting and quantifying genes with low and differential expression, which they say are particularly relevant for studies involving human disease.
The scientists also reported the use of CaptureSeq to quantify long non-coding RNAs (lncRNAs) and novel coding exons across 20 different human tissues, refining previous annotations and creating a new expression atlas.
CaptureSeq was developed in 2011 to enable the characterization of unannotated transcripts that are rarely or transiently expressed and thus below the detection limits of traditional sequencing approaches. The method involves enriching transcripts of interest by hybridizing them to magnetic bead-linked oligonucleotides that are tiled across the region of interest, allowing for targeted purification, multiplexed library preparation, and RNA sequencing at a high depth.
In their latest study, which appeared in Nature Methods, the Garvan team compared the quantitative accuracy of CaptureSeq compared with conventional RNA-seq and qRT-PCR, using the External RNA Control Consortium's (ERCC) RNA standards as an independent reference.
CaptureSeq was found to achieve eightfold sequence coverage — the estimated lower limit at which transcript models can be confidently assembled — for all ERCC standard concentrations tested, corresponding to the assembly of as few as roughly 1,550 transcripts in the input RNA, according to the paper. In contrast, RNA-seq could not reliably detect low ERCC standard concentrations, precluding the measurement of low-abundance standards.
To test the fidelity with which CaptureSeq measures expression differences, the Garvan group captured and sequenced two distinct pools of ERCC standards mixed at different relative concentrations.
"CaptureSeq achieved an accurate appraisal of differential gene expression of twofold or greater across the full range of ERCC standards and outperformed RNA-seq at quantifying the differential expression of low-abundance transcripts," the scientists wrote. Likewise, CaptureSeq outperformed qRT-PCR in terms of accurately measuring low-abundance standards.
RNA-seq and qRT-PCR did, however, perform as well or better that CaptureSeq for higher abundance standards. Still, the Garvan team sees advantages for their approach when it comes to studies investigating human diseases such as cancer.
When they compared the concentrations of ERCC standards to the endogenous RNA population in the human leukemic cell line K562, an estimated 42.1 percent of RNA transcripts were better quantified using CaptureSeq. RNA-seq and CaptureSeq performed similarly for 53.2 percent of transcripts.
RNA-seq did better than CaptureSeq for the most highly expressed 4.6 percent of transcripts enriched for housekeeping, structural, and metabolic genes, they noted. Still, "genes with low expression in K562 cells for which CaptureSeq provided superior quantitative accuracy were enriched for transcription factors and genes associated with cancer or other human diseases."
To further demonstrate CaptureSeq's utility for gene discovery and quantitative profiling, the researchers focused on lncRNAs, which are often poorly annotated, have low expression, and are highly tissue specific.
They identified 13,796 loci that generated 45,399 lncRNA isoforms, of which 27,596 were previously unknown, with 20.6 percent more exons and 13.5 percent more introns compared with previous annotations.
The newly identified lncRNA exons exhibited conservation, single-nucleotide polymorphism, repeat density, and RNA structure profiles similar to those of previous lncRNA annotations, according to the Nature Methods paper. The enhanced coverage also enabled the assembly of more complex structures, with a median of four exons for assembled lncRNAs versus two exons in previous annotations.
"By clustering lncRNA expression levels across human tissues, we also identified co-expressed subsets of lncRNAs, which provided a greatly expanded atlas of lncRNA expression," the team added. "Given its demonstrated advantages over conventional RNA-seq, we anticipate that targeted RNA-seq will become a standard technique for gene-expression profiling in both research and the clinic."