ABSTRACT
The rat is an important animal model for human diseases and is widely used in physiology. In this article we present a new strategy for gene discovery based on the production of ESTs from serially subtracted and normalized cDNA libraries, and we describe its application for the development of a comprehensive nonredundant collection of rat ESTs. Our new strategy appears to yield substantially more EST clusters per ESTs sequenced than do previous approaches that did not use serial subtraction. However, multiple rounds of library subtraction resulted in high frequencies of otherwise rare internally primed cDNAs, defining the limits of this powerful approach. To date, we have generated >200,000 3' ESTs from >100 cDNA libraries representing a wide range of tissues and developmental stages of the laboratory rat. Most importantly, we have contributed to approximately 50,000 rat UniGene clusters. We have identified, arrayed, and derived 5' ESTs from >30,000 unique rat cDNA clones. Complete information, including radiation hybrid mapping data, is also maintained locally at http://genome.uiowa.edu/clcg.html. All of the sequences described in this article have been submitted to the dbEST division of the NCBI.
Subject(s)
Genes/genetics , Animals , DNA, Complementary/genetics , Expressed Sequence Tags , Female , Gene Library , Humans , Male , Mice , Polyadenylation/genetics , RNA Processing, Post-Transcriptional/genetics , Rats , Rats, Sprague-Dawley , Sequence Analysis, DNA/methods , Sequence Analysis, DNA/statistics & numerical data , SoftwareABSTRACT
MOTIVATION: High accuracy of data always governs the large-scale gene discovery projects. The data should not only be trustworthy but should be correctly annotated for various features it contains. Sequence errors are inherent in single-pass sequences such as ESTs obtained from automated sequencing. These errors further complicate the automated identification of EST-related sequencing. A tool is required to prepare the data prior to advanced annotation processing and submission to public databases. RESULTS: This paper describes ESTprep, a program designed to preprocess expressed sequence tag (EST) sequences. It identifies the location of features present in ESTs and allows the sequence to pass only if it meets various quality criteria. Use of ESTprep has resulted in substantial improvement in accurate EST feature identification and fidelity of results submitted to GenBank. AVAILABILITY: The program is freely available for download from http://genome.uiowa.edu/pubsoft/software.html
