Homology-independent discovery of replicating pathogenic circular RNAs by deep sequencing and a new computational algorithm

A common challenge in pathogen discovery by deep sequencing approaches is to recognize viral or subviral pathogens in samples of diseased tissue that share no significant homology with a known pathogen. Here we report a homology-independent approach for discovering viroids, a distinct class of free circular RNA subviral pathogens that encode no protein and are known to infect plants only. Our approach involves analyzing the sequences of the total small RNAs of the infected plants obtained by deep sequencing with a unique computational algorithm, progressive filtering of overlapping small RNAs (PFOR). Viroid infection triggers production of viroid-derived overlapping siRNAs that cover the entire genome with high densities. PFOR retains viroid-specific siRNAs for genome assembly by progressively eliminating nonoverlapping small RNAs and those that overlap but cannot be assembled into a direct repeat RNA, which is synthesized from circular or multimeric repeated-se- quence templates during viroid replication. We show that viroids from the two known families are readily identified and their full- length sequences assembled by PFOR from small RNAs sequenced from infected plants. PFOR analysis of a grapevine library further identified a viroid-like circular RNA 375 nt long that shared no sig- nificant sequence homology with known molecules and encoded active hammerhead ribozymes in RNAs of both plus and minus polarities, which presumably self-cleave to release monomer from multimeric replicative intermediates. A potential application of the homology-independent approach for viroid discovery in plant and animal species where RNA replication triggers the biogenesis of siRNAs is discussed.