How wapRNA analyzing miRNA data?
2.1  Reference Preparing

For miRNA data analysis, we should preparing the following three type data:
a. Genome sequences
b. Non-miRNA sequences (including mRNA, tRNA, rRNA, snRNA, snoRNA or other structure RNAs)
c. miRBase

2.2  Pre-processing of sequenced reads

For Solexa sequenced reads, pre-processing is needed before mapping to genome.
a. trim the 3กฏ adapter sequence
We use FASTQ/A Clipper from FASTX-Toolkit package for trimming the 3กฏ adapter sequence.
b. Clustering
We will Cluster those identical reads into one tag that including reads sequences and its corresponding times information.
c. Length choosing
Most miRNA length is ranged 18-35; we suggest defining the length range. The default parameters are 15-35
For SOLiD sequenced reads, pre-processing is integrated in mapping package: RNA-MAP.

2.3  Mapping

For Solexa cleaned tags, First, we using BWA software to map to genome sequences, and record the mapping position. Second, removing those non-miRNA tags by comparing to non-miRNA databse (blast)
For SOLiD data, all the above jobs were finished by RNA-MAP software.

2.4  miRNA predication

miRDeep package used for miRNA predication. The candidate novel miRNAs predicated using miRDeep was classified according to the miRBase annotation. That is, if the seed sequence (2-8 base pair) of a novel miRNA is same to miRBase mature sequences, this novel miRNA was denoted to be conserved.

2.5  miRNA target predication

A challenge ahead will be to identify the targets of small RNAs. Since each microRNA can target several mRNA sequences, this will be a daunting task and will require the aid of computational target prediction tools. a number of algorithms have been developed which can be used for microRNA target prediction.Here, we integrated two popular methods: miRanda and RNAHybrid for miRNA target predication, and the combined genes were listed for each miRNA.

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