Replicating circular RNAs are independent plant pathogens known as viroids, or 
act to modulate the pathogenesis of plant and animal viruses as their satellite 
RNAs. The rate of discovery of these subviral pathogens was low over the past 40 
years because the classical approaches are technical demanding and 
time-consuming. We previously described an approach for homology-independent 
discovery of replicating circular RNAs by analysing the total small RNA 
populations from samples of diseased tissues with a computational program known 
as progressive filtering of overlapping small RNAs (PFOR). However, PFOR written 
in PERL language is extremely slow and is unable to discover those subviral 
pathogens that do not trigger in vivo accumulation of extensively overlapping 
small RNAs. Moreover, PFOR is yet to identify a new viroid capable of initiating 
independent infection. Here we report the development of PFOR2 that adopted 
parallel programming in the C++ language and was 3 to 8 times faster than PFOR. 
A new computational program was further developed and incorporated into PFOR2 to 
allow the identification of circular RNAs by deep sequencing of long RNAs 
instead of small RNAs. PFOR2 analysis of the small RNA libraries from grapevine 
and apple plants led to the discovery of Grapevine latent viroid (GLVd) and 
Apple hammerhead viroid-like RNA (AHVd-like RNA), respectively. GLVd was 
proposed as a new species in the genus Apscaviroid, because it contained the 
typical structural elements found in this group of viroids and initiated 
independent infection in grapevine seedlings. AHVd-like RNA encoded a 
biologically active hammerhead ribozyme in both polarities, and was not 
specifically associated with any of the viruses found in apple plants. We 
propose that these computational algorithms have the potential to discover novel 
circular RNAs in plants, invertebrates and vertebrates regardless of whether 
they replicate and/or induce the in vivo accumulation of small RNAs.