Sequencing-based whole-transcriptome analysis (i.e., RNA-Seq) can be a powerful tool when used to measure gene expression, detect novel transcripts, characterize transcript isoforms, and identify sequence polymorphisms. However, this method can be inefficient when the goal is to study only one component of the transcriptome, such as long noncoding RNAs (lncRNAs), which constitute only a small fraction of transcripts in a total RNA sample. Here, researchers from Roche NimbleGen describe a target enrichment method where a total RNA sample is converted to a sequencing-ready cDNA library and hybridized to a complex pool of lncRNA-specific biotinylated long oligonucleotide capture probes prior to sequencing. The resulting sequence data are highly enriched for the targets of interest, dramatically increasing the efficiency of next-generation sequencing approaches for the analysis of lncRNAs.
Comparison of lncRNA isoform detection for captured (SeqCap RNA ) and non-captured (RNA-Seq ) libraries. SeqCap RNA and RNA-Seq were used to analyze kidney and liver RNA samples. SeqCap RNA data was generated starting with total RNA. RNA-Seq data was generated starting with ribo-depleted RNA. The sequence data was subsampled to various numbers of reads (x-axis) from 1 to 20 million reads. SeqCap RNA data (red) which includes a capture step detects more lncRNA isoforms than non-captured RNA-Seq data (black) even with 20× less sequencing data