Shane C Burgess

PMID: 20961407;PMCID: PMC3218658;Abstract:

Background: A comprehensive transcriptome survey, or gene atlas, provides information essential for a complete understanding of the genomic biology of an organism. We present an atlas of RNA abundance for 92 adult, juvenile and fetal cattle tissues and three cattle cell lines.Results: The Bovine Gene Atlas was generated from 7.2 million unique digital gene expression tag sequences (300.2 million total raw tag sequences), from which 1.59 million unique tag sequences were identified that mapped to the draft bovine genome accounting for 85% of the total raw tag abundance. Filtering these tags yielded 87,764 unique tag sequences that unambiguously mapped to 16,517 annotated protein-coding loci in the draft genome accounting for 45% of the total raw tag abundance. Clustering of tissues based on tag abundance profiles generally confirmed ontology classification based on anatomy. There were 5,429 constitutively expressed loci and 3,445 constitutively expressed unique tag sequences mapping outside annotated gene boundaries that represent a resource for enhancing current gene models. Physical measures such as inferred transcript length or antisense tag abundance identified tissues with atypical transcriptional tag profiles. We report for the first time the tissue-specific variation in the proportion of mitochondrial transcriptional tag abundance.Conclusions: The Bovine Gene Atlas is the deepest and broadest transcriptome survey of any livestock genome to date. Commonalities and variation in sense and antisense transcript tag profiles identified in different tissues facilitate the examination of the relationship between gene expression, tissue, and gene function. © 2010 Harhay et al.; licensee BioMed Central Ltd.

Abstract:

Proteomics is the study of the entire protein compliment of an organism. The blood plasma is the only tissue in which an organism's entire proteome may be potentially represented. First results toward mapping the broiler plasma proteome are presented here. Blood was taken from eight 18 day-old representative commercial broiler chickens. Plasma was isolated from each sample and pooled. For initial sample fractioning a 0.4 μl aliquot of the pooled plasma was run on one dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis. Based on relative amounts of protein, the gel was divided into three fractions. The proteins were in-gel digested with trypsin. Two-dimensional liquid chromatography in-line with electrospray ionization tandem mass spectrometry was then used for "shot-gun" qualitative plasma proteomics. The resulting tandem mass spectra were then searched against the non-redundant chicken protein database. Generally accepted high stringency statistical criteria for protein identification were used. Eighty-four chicken proteins were identified. Our work demonstrates the future potential for plasma proteomics for identifying biomarkers of disease and production in chickens. © Asian Network for Scientific Information, 2004.

PMID: 21834139;Abstract:

This study is the first proteomics analysis of the muscularis complexus (pipping muscle) in chicken (Gallus gallus) broiler embryos. We used differential detergent fractionation and nano-HPLC-MS/MS analysis to identify 676 proteins from all cellular components. The identified proteins were functionally classified in accordance with their involvement in various cellular activities. © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PMID: 21075795;PMCID: PMC3013706;Abstract:

AgBase (http://www.agbase.msstate.edu/) provides resources to facilitate modeling of functional genomics data and structural and functional annotation of agriculturally important animal, plant, microbe and parasite genomes. The website is redesigned to improve accessibility and ease of use, including improved search capabilities. Expanded capabilities include new dedicated pages for horse, cat, dog, cotton, rice and soybean. We currently provide 590 240 Gene Ontology (GO) annotations to 105 454 gene products in 64 different species, including GO annotations linked to transcripts represented on agricultural microarrays. For many of these arrays, this provides the only functional annotation available. GO annotations are available for download and we provide comprehensive, species-specific GO annotation files for 18 different organisms. The tools available at AgBase have been expanded and several existing tools improved based upon user feedback. One of seven new tools available at AgBase, GOModeler, supports hypothesis testing from functional genomics data. We host several associated databases and provide genome browsers for three agricultural pathogens. Moreover, we provide comprehensive training resources (including worked examples and tutorials) via links to Educational Resources at the AgBase website. © The Author(s) 2010.

PMID: 16961921;PMCID: PMC1618847;Abstract:

Background: Many agricultural species and their pathogens have sequenced genomes and more are in progress. Agricultural species provide food, fiber, xenotransplant tissues, biopharmaceuticals and biomedical models. Moreover, many agricultural microorganisms are human zoonoses. However, systems biology from functional genomics data is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation and agricultural research communities are smaller with limited funding compared to many model organism communities. Description: To facilitate systems biology in these traditionally agricultural species we have established "AgBase", a curated, web-accessible, public resource http://www.agbase.msstate.edu for structural and functional annotation of agricultural genomes. The AgBase database includes a suite of computational tools to use GO annotations. We use standardized nomenclature following the Human Genome Organization Gene Nomenclature guidelines and are currently functionally annotating chicken, cow and sheep gene products using the Gene Ontology (GO). The computational tools we have developed accept and batch process data derived from different public databases (with different accession codes), return all existing GO annotations, provide a list of products without GO annotation, identify potential orthologs, model functional genomics data using GO and assist proteomics analysis of ESTs and EST assemblies. Our journal database helps prevent redundant manual GO curation. We encourage and publicly acknowledge GO annotations from researchers and provide a service for researchers interested in GO and analysis of functional genomics data. Conclusion: The AgBase database is the first database dedicated to functional genomics and systems biology analysis for agriculturally important species and their pathogens. We use experimental data to improve structural annotation of genomes and to functionally characterize gene products. AgBase is also directly relevant for researchers in fields as diverse as agricultural production, cancer biology, biopharmaceuticals, human health and evolutionary biology. Moreover, the experimental methods and bioinformatics tools we provide are widely applicable to many other species including model organisms. © 2006 McCarthy et al; licensee BioMed Central Ltd.