Articles by Matthew J. Nesbitt in JoVE
Automated Gel Size Selection to Improve the Quality of Next-generation Sequencing Libraries Prepared from Environmental Water Samples Miguel I. Uyaguari-Diaz1, Jared R. Slobodan2, Matthew J. Nesbitt2, Matthew A. Croxen3, Judith Isaac-Renton1,3, Natalie A. Prystajecky1,3, Patrick Tang1,3 1Department of Pathology and Laboratory Medicine, Faculty of Medicine, The University of British Columbia, 2Coastal Genomics, 3British Columbia Public Health Microbiology and Reference Laboratory This manuscript describes an automated gel size selection approach for purifying DNA fragments for next-generation sequencing. The Ranger Technology provides complete automation of the entire process of agarose gel loading, electrophoretic analysis, and recovery of targeted DNA fragments allowing for high-throughput and high quality next-generation sequencing libraries.
Other articles by Matthew J. Nesbitt on PubMed
Identifying Novel Genes in C. Elegans Using SAGE Tags BMC Molecular Biology. 2010 | Pubmed ID: 21143975 Despite extensive efforts devoted to predicting protein-coding genes in genome sequences, many bona fide genes have not been found and many existing gene models are not accurate in all sequenced eukaryote genomes. This situation is partly explained by the fact that gene prediction programs have been developed based on our incomplete understanding of gene feature information such as splicing and promoter characteristics. Additionally, full-length cDNAs of many genes and their isoforms are hard to obtain due to their low level or rare expression. In order to obtain full-length sequences of all protein-coding genes, alternative approaches are required.