Beyond cleaved small RNA targets: unraveling the complexity of plant RNA degradome data

Degradation is essential for RNA maturation, turnover, and quality control. RNA degradome sequencing that integrates a modified 5'-rapid amplification of cDNA ends protocol with next-generation sequencing technologies is a high-throughput approach for profiling the 5'-end of uncapped RNA fragments on a genome-wide scale. The primary application of degradome sequencing has been to identify the truncated transcripts that result from endonucleolytic cleavage guided by microRNAs or small interfering RNAs. As many pathways are involved in RNA degradation, degradome data should contain other RNA species besides the cleavage remnants of small RNA targets. Nevertheless, no systematic approaches have been established to explore the hidden complexity of plant degradome.

Through analyzing Arabidopsis and rice RNA degradome data, we recovered 11 short motifs adjacent to predominant and abundant uncapped 5'-ends. Uncapped ends associated with several of these short motifs were more prevalent than those targeted by most miRNA families especially in the 3' untranslated region of transcripts. Through genome-wide analysis, five motifs showed preferential accumulation of uncapped 5'-ends at the same position in Arabidopsis and rice. Moreover, the association of uncapped 5'-ends with a CA-repeat motif and a motif recognized by Pumilio/Fem-3 mRNA binding factor (PUF) proteins was also found in non-plant species, suggesting that common mechanisms are present across species. Based on these motifs, potential sources of RNA ends that constitute degradome data were proposed and further examined. The 5'-end of small nucleolar RNAs could be precisely captured by degradome sequencing. Position-specific enrichment of uncapped 5'-ends was seen upstream of motifs recognized by several RNA binding proteins especially for the binding site of PUF proteins. False uncapped 5'-ends produced from capped transcripts through non-specific PCR amplification were common artifacts among degradome datasets.

The complexity of plant RNA degradome data revealed in this study may contribute to the alternative applications of degradome in RNA research.