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

ABSTRACT: 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.

SUBMITTER: Wu Q

PROVIDER: S-EPMC3309787 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

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

Wu Qingfa Q Wang Ying Y Cao Mengji M Pantaleo Vitantonio V Burgyan Joszef J Li Wan-Xiang WX Ding Shou-Wei SW

Proceedings of the National Academy of Sciences of the United States of America 20120215 10

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 dee ...[more]

PMID: 22345560

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Project description: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.

Dataset Information

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

Publications

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

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