Ph.D. Simon Fraser University, 1997
407 Cancer & Genetics Research Complex
The Barbazuk lab uses computational, comparative and functional genomics to study genome architecture, function and evolution. In order to address these questions, genome sequences and well-established catalogues of genes and their positions within the genome are required. As more and more genome data becomes available, the methods used to catalogue genes become more robust, and ultimately the questions of genome organization, gene interaction and regulation can be addressed. Our lab works with crop (particularly maize and tomato), model (Arabidopsis) and non-model genomes where we apply comparative analysis and computational methods to investigate gene structure, gene content, gene/genome organization and regulation.
We are currently examining:
Next generation sequencing of transcriptome and genome sequence data: We are actively using next generation sequence data from multiple platforms to examine and characterize genomes and transcriptomes. We currently have projects that apply next generation sequence technologies to investigate gene content, gene structure, expression, gene gain/loss, genome architecture and sequence diversity.
Gene Annotation and gene structure: Plant genome sequence is the knowledge infrastructure for the next generation of plant molecular genetics and crop improvement, and will provide the foundation for crop improvement. The products of ongoing and future plant sequencing projects are collections of large contiguous nucleotide segments for which there is no a priori knowledge of content or function. Therefore, high throughput computational tools that can accurately identify genes within genomic sequence are absolutely necessary for annotating and understanding the maize genome. In collaboration with Dr. Michael Brent at Washington University, are improving gene prediction in maize and tomato by identifying a comprehensive “training set” of complete and annotated gene models; and, using these to optimize TWINSCAN. TWINSCAN is a next-generation gene discovery tool developed by Michael Brent. Originally designed for human gene prediction, it improves gene detection by integrating traditional probability models like those underlying GENSCAN and FGENESH with information from the alignments between two genomes.
Alternative Splicing: Alternative splicing (AS) creates multiple mRNA transcripts from a single gene. While AS is known to contribute to gene regulation and proteome diversity in animals, the study of its importance in plants is in its early stages. However, recently available plant genome and transcript sequence data sets are enabling a global analysis of AS in many plant species. Results of genome analysis have revealed differences between animals and plants in the frequency of alternative splicing. The proportion of plant genes that have one or more alternative transcript isoforms is approximately 20%, indicating that AS in plants is not rare, although this rate is ~1/3 of that observed in human. The majority of plant AS events have not been functionally characterized, but evidence suggests that AS participates in important plant functions including stress response, and may impact domestication and trait selection. The increasing availability of plant genome sequence data is enabling larger comparative analyses that will identify functionally important plant AS events based on their evolutionary conservation; determine the influence of genome duplication on the evolution of AS; and discover plant specific cis elements that regulate AS.
- Yan Fu, Oliver Bannach, Hao Chen, Jan-Hendrik Teune, Axel Schmitz, Gerhard Steger, Liming Xiong, and W. Brad Barbazuk . Alternative Splicing of Anciently Exonized 5S rRNA Regulates Plant Transcription Factor TFIIIA. Genome Research 2009 19:913-21.
- W. Brad Barbazuk, Yan Fu, Karen M. McGinnis. Genome-wide analyses of alternative splicing in plants: Opportunities and Challenges. Genome Research 2008 18:1381-92.
- Subramanian S, Fu Y, Sunkar R, Barbazuk BW, Zhu JK, Yu O. Novel and nodulation-regulated microRNAs in soybean roots. BMC Genomics. 2008 9:160
- W. Brad Barbazuk, Scott J. Emrich*, Hsin D. Chen, Li Li, and Patrick S. Schnable. SNP discovery in maize via 454 transcriptome sequencing.Plant J. 2007 51:910-18
- Scott J. Emrich, W. Brad Barbazuk, Li Li and Patrick S. Schnable. Gene discovery and annotation using LCM-454 transcriptome sequencing. Genome Research 2007 17:69-73. Epub 2006 Nov 9.
- Barbazuk, W. B, Bedell, J. A and Pablo D. Rabinowicz. Reduced representation sequencing: a success in maize and a promise for other plant genomes.BioEssays 2005; 27:839-848
|Lucas Boatwrightemail@example.com||Non-model transcriptome assembly, differential expression and functional annotation|
|Nathan Catlinfirstname.lastname@example.org||Comparative genomics, phylogenomics, polyploidy|
|Wenbin Meiemail@example.com||Comparative genomics, alternative splicing, phylogenomics|
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