A computational platform for the high-throughput identification of short RNAs and their targets in plants

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Most of the RNA molecules in cells are involved in protein production (ribosomal, transfer or messenger RNAs). However there are RNA molecules with other functions. Two classes of such non-coding RNAs which have been recently discovered are microRNAs (miRNAs) and small interfering RNAs (siRNAs). These regulatory RNA molecules are very short (19-24 nucleotides) and are thus commonly known as short RNAs (sRNAs). Some sRNAs can interact with specific mRNAs because they have partially complementary sequences. As a result of these interactions the expression of the targeted mRNAs is significantly reduced. Other sRNAs can target the chromosomes and trigger DNA modification. More than a hundred miRNAs have been identified in plant species (Arabidopsis, rice and poplar). However, the total number of sRNAs in plants is much higher: A recent experimental study identified about 75,000 sRNAs in Arabidopsis. In addition, several miRNAs found in one species were absent from the other suggesting that there are miRNAs which are specific to certain groups of plants. To systematically identify sRNAs in plants, the co-PIs laboratories have started to use a novel high-throughput sequencing technology (454 pyrosequencing). Initially, they are studying Arabidopsis and later, as the genome sequences will become available, tomato and alfalfa sRNAs will be analysed. This novel technology produces about 200,000 sRNA sequences for each sample. Preliminary results from the 454 technology are currently processed manually using standard bioinformatics tools. However, such an analysis is unfeasible for the millions of sRNA sequences that will be derived from future 454 experiments. The main goal of this project is to develop a computational platform dedicated to the analysis of data generated by the high-throughput 454 sRNA sequencing projects. This platform will classify new sRNAs, some of which will be subjected to further experimental work, and search for possible RNA targets. It will be initially tested on 454 data from Arabidopis, and subsequently on tomato and alfalfa. Later in the project, a comparative analysis tools will be incorporated for mutant analysis. New bioinformatics tools and novel sRNAs discovered through this project will be made publically available. Identifying the full complement of sRNAs in different plant species will allow us to characterise an important and little understood layer of regulation in specific plant traits such as fleshy fruit development and ripening in tomato, and nitrogen fixation in alfalfa.