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Fig. 4 | BMC Genomics

Fig. 4

From: CANEapp: a user-friendly application for automated next generation transcriptomic data analysis

Fig. 4

Detection and of novel long noncoding RNAs by CANEapp and their validation by real-time PCR. a Filtering strategies and protein-coding potential prediction. (Right) CANEapp preserves any transcripts that contain a splice junction (a) or single-exon transcripts expressed in a majority of samples (c), whereas single-exon transcripts detected in a minority of samples are filtered out (b). (Center) Loci that have insufficient read coverage are not considered for differential expression testing. (Left) In order to differentiate between novel noncoding RNAs and potential protein-coding genes, each isoform from a novel locus is tested for presence of a significant open reading frame. Loci that contain at least one isoform with an open reading frame are not considered novel noncoding RNA. b Gel electrophoresis image of PCR amplification products for experimentally validated novel long noncoding RNAs. 5 novel antisense RNAs and 3 long intergenic noncoding RNAs (lincRNAs) predicted from the human RNA-seq dataset analysis were amplified with real-time PCR. For mouse cortex dataset, real-time PCR was performed on RNA extracted from adult mouse cortex. 3 antisense RNAs and 5 lincRNAs were successfully validated. c and d Novel long noncoding RNAs span a wide range of expression levels in human and mouse tissues. Relative expression of validated long noncoding RNAs was calculated by normalizing it to the Ct value of the endogenous control beta-actin

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