Degradome Sequencing Q&A

Unlike animals, plant miRNAs usually undergo complete or near-complete pairing with target genes to cause target gene shearing and thus regulate gene expression, so there will be fewer false positives and more accurate identification results. Compared to animals, plants are more suitable for studying miRNA target genes using degradome sequencing. In contrast, model organisms or species with detailed transcriptome information are more suitable for miRNA target genes using degradome sequencing than species with incomplete transcriptome information.

Although raw signal prediction can predict the target genes of miRNAs with high throughput, there are a lot of false positives and the results are not reliable. RACE validation is time-consuming and labor-intensive, and does not have the same high throughput as raw signal prediction. Therefore, the advantage of degradome sequencing is that not only the target genes of miRNAs can be detected in high throughput, but also the results are obtained by biological experiments, which greatly improves the credibility of the experimental results.

Alignment Score is a score for the prediction of target genes by applying targetfinder to the cDNA library and small RNA library of the sequenced species. miRNA and mRNA are compared and scored as complementary pairings (1 score for a mismatch or deletion, 0.5 score for a G:U pairing, double score for mismatch and G:U pairing in the core region, starting from the 2nd nt to the 13th nt of microRNA). The alignment score is defined as the degree of match between target gene and miRNA, the lower the score the more complete the match is and the more reliable it is.