RNA World/Project description/en
• • •
RNA World project description
RNA World is a distributed supercomputer that uses Internet-connected computers to advance RNA research. This system is dedicated to identify, analyze, structurally predict and design RNA molecules on the basis of established bioinformatics software in a high-performance, high-throughput fashion.
In contrast to classical bioinformatic approaches, RNA World does not rely on individual desktop computers, web servers or supercomputers. Instead, it represents a continuously evolving cluster of world-wide distributed machines of any type. As such, RNA World is very heterogenous and, depending on the sub-project, currently addresses Internet-connected computers running Linux, Windows and OSX operating systems - your computer could be an important part of it. The fact that hardware and electricity costs are shared among the volunteer contributors raises the possibility of performing interesting analyses which under economical aspects would often not be affordable. In return, RNA World is not for profit, exclusively uses open source code and will make its results available to the public.
In its present form, RNA World runs a fully automated high-throughput analysis software version of Infernal1, a program suite originally developed in Sean Eddys laboratory for the systematic identification of non-coding RNAs. The goal of this RNA World sub-project is to systematically identify all known RNA family members in all organisms known to date and make the results available to the public in a timely fashion. With your help, we also aim at supplying established bioinformatic databases such as Rfam2 with our results to help reduce their future maintenance costs.
In contrast to other distributed and grid computing projects, the RNA World developers are currently designing generalized user interfaces that, in parallel to the projects our own research team is following up, allow non-associated individual scientists to submit their own projects in a manner similar to using a web server interface - of course, free of cost.
Every protein in a cell is produced from a transiently synthesized messenger molecule, termed mRNA. This mRNA is then recognized by a cellular machinery that translates the base sequence of mRNA into its corresponding protein (which is a sequence of amino acids). This protein synthesis machinery, termed ribosome, is actually a ribozyme, i.e. it is a catalytically active assembly of several RNA molecules. Consequently, RNAs do not only serve as messenger molecules or perform structural functions as e.g. in tRNA but may also act as catalysts that perform biochemical reactions as is the case for protein enzymes. Of course, the ribosome also contains numerous proteins as it is a very complex ribonucleoprotein particle but these predominantly serve structural functions, e.g. to give the ribosome its shape.
Fascinatingly, the initial analysis of the human genome sequence revealed that, apparently, only a very small fraction of the DNA of our genome is encoding proteins. Scientists at first thought "what is all this junk DNA about?" or "can't we just delete it?". Today, it has become clear that probably a major fraction of regulatory events taking place in a human cell might be governed by small RNAs, the so-called miRNAs. Among other functions, these appear responsible for making sure that a skin cell becomes a skin cell while a muscle, liver or hair cell differentiates to a muscle, liver or hair cell during development and all this although the genetic material (DNA) of all of these very different cell types is essentially identical. On top of that it seems that many cancer types are accompanied by or even result from a deregulated miRNA profile in the affected cell. Moreover, viruses have been discovered to bring along miRNAs to modify the target cell's regulatory network leading to diseases.
Hence, we can clearly state that investing into RNA research, e.g. by supporting the RNA World distributed supercomputer project, will ultimately lead to important discoveries that might also have significant impact on future health care.
(1) Infernal 1.0: inference of RNA alignments. Nawrocki EP, Kolbe DL, Eddy SR. Bioinformatics. 2009 May 15;25(10):1335-7. Epub 2009 Mar 23. PMID: 19307242.
(2) Rfam: updates to the RNA families database. Gardner PP, Daub J, Tate JG, Nawrocki EP, Kolbe DL, Lindgreen S, Wilkinson AC, Finn RD, Griffiths-Jones S, Eddy SR, Bateman A. Nucleic Acids Res. 2009 Jan;37(Database issue):D136-40. Epub 2008 Oct 25. PMID: 18953034.
(3) Petabyte-scale innovations at the European Nucleotide Archive. Cochrane G, Akhtar R, Bonfield J, Bower L, Demiralp F, Faruque N, Gibson R, Hoad G, Hubbard T, Hunter C, Jang M, Juhos S, Leinonen R, Leonard S, Lin Q, Lopez R, Lorenc D, McWilliam H, Mukherjee G, Plaister S, Radhakrishnan R, Robinson S, Sobhany S, Hoopen PT, Vaughan R, Zalunin V, Birney E. Nucleic Acids Res. 2009 Jan;37(Database issue):D19-25. Epub 2008 Oct 31. PMID: 18978013.