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-sequence 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 significant 
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.