A Computer-Based Method of Selecting Clones for a Full-Length cDNA Project: Simultaneous Collection of Negligibly Redundant and Variant cDNAs

Abstract

We describe a computer-based method that selects representative clones for full-length sequencing in a full-length cDNA project. Our method classifies end sequences using two kinds of criteria, grouping, and clustering. Grouping places together variant cDNAs, family genes, and cDNAs with sequencing errors. Clustering separates those cDNA clones into distinct clusters. The full-length sequences of the clones selected by grouping are determined preferentially, and then the sequences selected by clustering are determined. Grouping reduced the number of rice cDNA clones for full-length sequencing to 21% and mouse cDNA clones to 25%. Rice full-length sequences selected by grouping showed a 1.07-fold redundancy. Mouse full-length sequences showed a 1.04-fold redundancy, which can be reduced by ∼30% from the selection using our previous method. To estimate the coverage of unique genes, we used FANTOM (Functional Annotation of RIKEN Mouse cDNA Clones) clusters (the RIKEN Genome Exploration Research Group 2001). Grouping covered almost all unique genes (93% of FANTOM clusters), and clustering covered all genes. Therefore, our method is useful for the selection of appropriate representative clones for full-length sequencing, thereby greatly reducing the cost, labor, and time necessary for this process.[The programs used in this paper are available online at http://genome.gsc.riken.go.jp/software/2C.]Full-length cDNA projects attempt to collect all mRNAs transcribed from the genome and determine the full-length cDNA sequences in their entirety. Considerable effort has been expended to improve the techniques involved. At the completion of mouse and human full-length cDNA projects, 30,000 to 100,000 full-length cDNA sequences will have been determined. The determination of full-length sequences requires large amounts of reagents, manpower, and time, which can be reduced by removing redundant full-length cDNA clones that potentially number in the thousands. As an experimental approach, mRNAs transcribed at high levels can be removed by normalization and subtraction during the construction of cDNA libraries (Carninci et al. 1996(Carninci et al. , 1997(Carninci et al. , 1998(Carninci et al. , 2000Carninci and Hayashizaki 1999). However, because experimental normalization and subtraction are very difficult to apply to similar clones belonging to the same gene family, redundancies remain in the normalized cDNA library. Another possibility is, after end sequencing of the cDNAs, to identify negligibly redundant clones by a computational approach to classify the end sequences.In general, when several full-length cDNA sequences are determined, redundancy can be reduced using homology search software by aligning the full-length cDNA sequences with their end sequences. Genomic sequences are also useful for reducing the redundancy. However, early in a project or when genome sequences are unavailable, the end sequences need to be classified. Several programs for clustering singleread expressed sequence tags (EST) have been reported (Adam...

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