Integrating heterogeneous sequence information for transcriptome-wide microarray design; a Zebrafish example

A complete gene-expression microarray should preferably detect all genomic sequences that can be expressed as RNA in an organism, i.e. the transcriptome. However, our knowledge of a transcriptome of any organism still is incomplete and transcriptome information is continuously being updated. Here, we present a strategy to integrate heterogeneous sequence information that can be used as input for an up-to-date microarray design.

Our algorithm consists of four steps. In the first step transcripts from different resources are grouped into Transcription Clusters (TCs) by looking at the similarity of all transcripts. TCs are groups of transcripts with a similar length. If a transcript is much smaller than a TC to which it is highly similar, it will be annotated as a subsequence of that TC and is used for probe design only if the probe designed for the TC does not query the subsequence. Secondly, all TCs are mapped to a genome assembly and gene information is added to the design. Thirdly TC members are ranked according to their trustworthiness and the most reliable sequence is used for the probe design. The last step is the actual array design. We have used this strategy to build an up-to-date zebrafish microarray.

With our strategy and the software developed, it is possible to use a set of heterogeneous transcript resources for microarray design, reduce the number of candidate target sequences on which the design is based and reduce redundancy. By changing the parameters in the procedure it is possible to control the similarity within the TCs and thus the amount of candidate sequences for the design. The annotation of the microarray is carried out simultaneously with the design.