Homology searches for structural RNAs: from proof of principle to practical use.

نویسنده

  • Sean R Eddy
چکیده

If you search a sequence database for homologs of a structural RNA, you don’t want to search just for linear sequence similarity; you alsowant the search program to consider whether a candidate sequence can be folded into a similar base-paired secondary structure. A powerful and general class of computational methods for combining primary sequence and secondary structure information in RNA homology searches was independently introduced just over 20 years ago by Yasu Sakakibara (working in the lab of David Haussler) and by myself (working as a postdoc with Richard Durbin). The 20th anniversary of the founding of the RNA journal seems a good occasion to look back at the 20 year development arc of “stochastic context-free grammar” (SCFG) methods and software for structural RNA homology searches. My interest in RNA sequence analysis started when I was working on the three catalytic group I introns in bacteriophage T4. The T4 introns were discovered in the mid1980’s by Marlene Belfort, David Shub, and others, not long after Tom Cech’s lab had made the landmark discovery that the Tetrahymena group I intron is a self-splicing catalytic RNA. When I arrived at the University of Colorado at Boulder as a new PhD student, it was easy to get caught up in the excitement about catalytic RNAs and group I introns, especially amongst the close-knit “RNA Club” labs at Boulder, including the Cech and Uhlenbeck labs in chemistry, and the Gold and Yarus labs in biology. What caught my interest about the T4 introns wasn’t so much the chemistry of their catalysis, it was more the biology of why they were in T4 at all. Why would a highly streamlined bacteriophage genome keep three large introns around? My PhD advisor Larry Gold and my co-mentor David Shub had concocted an idea for a possible regulatory function for the T4 introns. The idea was based on the fact that the mechanism of group I splicing requires an exogenous guanosine, and the fact that group I introns seem to occur preferentially in genes having to do with nucleotide metabolism, GTP consumption, and/or nucleotide-like cofactors. For example, two of the three T4 introns were in genes encoding key enzymes in deoxynucleotide synthesis: td, the gene for thymidylate synthase, and nrdB, one of the two subunits of the aerobic ribonucleotide reductase. Larry and David hypothesized that these introns were regulatory, with splicing rates responsive to intracellular small molecule concentrations—perhaps GTP itself. The direct prediction of the Gold/Shub model is that if you constructed an intronless phage, it would be impaired for growth under conditions where it needed to down-regulate td and nrdB. However, two years of my work failed to show any mutant phenotype for the precise triple intron deletion. Indirectly, their idea also made me very interested in searching for more group I introns, not only in T4 but also in other organisms, because you’d expect to see that they too would be in key genes for DNA synthesis, nucleotide metabolism, or GTP consumption. It seemed to me that it ought to be feasible to just search DNA sequences computationally for new group I introns. The 169 kilobase genome sequence of phage T4 was then nearing completion, thanks to the efforts of Betty Kutter and others. The first fast sequence homology searching programs had begun to appear (Pearson and Lipman’s FASTA in 1988, followed quickly by Altschul, Gish, Miller, Myers, and Lipman’s first version of BLAST in 1990), and sequence databases were starting to grow quickly. The power of identifying homologs in sequence databases by computational methods was in the air. My problem was that group I introns generally don’t share much similarity in their linear sequence. Programs like

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عنوان ژورنال:
  • RNA

دوره 21 4  شماره 

صفحات  -

تاریخ انتشار 2015