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Brian O'Leary

Publications and source records attributed to Brian O'Leary.

3 recordsLinked to original sources

High-throughput gene discovery in the rat.

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.

Animals↗

ESTprep: preprocessing cDNA sequence reads.

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

Algorithms↗

EST-based gene discovery in pig: virtual expression patterns and comparative mapping to human.

A molecular understanding of porcine reproduction is of biological interest and economic importance. Our Midwest Consortium has produced cDNA libraries containing the majority of genes expressed in major female reproductive tissues, and we have deposited into public databases 21,499 expressed sequence tag (EST) gene sequences from the 3' end of clones from these libraries. These sequences represent 10,574 different genes, based on sequence comparison among these data, and comparison with existing porcine ESTs and genes indicate as many as 4652 of these EST clusters are novel. In silico analysis identified sequences that are expressed in specific pig tissues or organs and confirmed the broad expression in pig for many genes ubiquitously expressed in human tissues. Furthermore, we have developed computer software to identify sequence similarity of these pig genes with their human counterparts, and to extract the mapping information of these human homologues from genome databases. We demonstrate the utility of this software for comparative mapping by localizing 61 genes on the porcine physical map for Chromosomes (Chrs) 5, 10, and 14.

Algorithms↗