Fiona M McCarthy

Interests

Teaching

informatics, genomics, virology

Research

bioinformatics, ontologies, genomics, functional genomics

Courses

Scholarly Contributions

Journals/Publications

• Lyons, E., Burgess, S. C., Sonstegard, T. S., Pendarvis, K., Mccarthy, F. M., Lyons, E., Gresham, C. R., Davey, S., Cooksey, A. M., Burgess, S. C., Bridges, S. M., & Bomhoff, M. (2019). Chickspress: a resource for chicken gene expression.. Database : the journal of biological databases and curation, 2019(1). doi:10.1093/database/baz058
  More info

  High-throughput sequencing and proteomics technologies are markedly increasing the amount of RNA and peptide data that are available to researchers, which are typically made publicly available via data repositories such as the NCBI Sequence Read Archive and proteome archives, respectively. These data sets contain valuable information about when and where gene products are expressed, but this information is not readily obtainable from archived data sets. Here we report Chickspress (http://geneatlas.arl.arizona.edu), the first publicly available gene expression resource for chicken tissues. Since there is no single source of chicken gene models, Chickspress incorporates both NCBI and Ensembl gene models and links these gene sets with experimental gene expression data and QTL information. By linking gene models from both NCBI and Ensembl gene prediction pipelines, researchers can, for the first time, easily compare gene models from each of these prediction workflows to available experimental data for these products. We use Chickspress data to show the differences between these gene annotation pipelines. Chickspress also provides rapid search, visualization and download capacity for chicken gene sets based upon tissue type, developmental stage and experiment type. This first Chickspress release contains 161 gene expression data sets, including expression of mRNAs, miRNAs, proteins and peptides. We provide several examples demonstrating how researchers may use this resource.
• Tavlarides-hontz, P., Pendarvis, K., Parcells, M. S., Neerukonda, S. N., & Mccarthy, F. M. (2019). Comparison of the Transcriptomes and Proteomes of Serum Exosomes from Marek's Disease Virus-Vaccinated and Protected and Lymphoma-Bearing Chickens.. Genes, 10(2), 116. doi:10.3390/genes10020116
  More info

  Marek's disease virus (MDV) is the causative agent of Marek's disease (MD), a complex pathology of chickens characterized by paralysis, immunosuppression, and T-cell lymphomagenesis. MD is controlled in poultry production via vaccines administered in ovo or at hatch, and these confer protection against lymphoma formation, but not superinfection by MDV field strains. Despite vaccine-induced humoral and cell-mediated immune responses, mechanisms eliciting systemic protection remain unclear. Here we report the contents of serum exosomes to assess their possible roles as indicators of systemic immunity, and alternatively, tumor formation. We examined the RNA and protein content of serum exosomes from CVI988 (Rispens)-vaccinated and protected chickens (VEX), and unvaccinated tumor-bearing chickens (TEX), via deep-sequencing and mass spectrometry, respectively. Bioinformatic analyses of microRNAs (miRNAs) and predicted miRNA targets indicated a greater abundance of tumor suppressor miRNAs in VEX compared to TEX. Conversely, oncomiRs originating from cellular (miRs 106a-363) and MDV miRNA clusters were more abundant in TEX compared to VEX. Most notably, mRNAs mapping to the entire MDV genome were identified in VEX, while mRNAs mapping to the repeats flanking the unique long (IRL/TRL) were identified in TEX. These data suggest that long-term systemic vaccine-induced immune responses may be mediated at the level of VEX which transfer viral mRNAs to antigen presenting cells systemically. Proteomic analyses of these exosomes suggested potential biomarkers for VEX and TEX. These data provide important putative insight into MDV-mediated immune suppression and vaccine responses, as well as potential serum biomarkers for MD protection and susceptibility.
• Cannon, S. B., Yu, J., Woodhouse, M. R., Williams, J., Wegrzyn, J. L., Ware, D., Wang, L., Walls, R., Unni, D., Unda, V. P., Tello-ruiz, M. K., Subramaniam, S., Staton, M., Sen, T. Z., Sanderson, L., Reiser, L., Reecy, J. M., Poelchau, M. F., Park, C. A., , Nesdill, D., et al. (2018). AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture.. Database : the journal of biological databases and curation, 2018(2018), 1-32. doi:10.1093/database/bay088
  More info

  The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices.
• Joyce, B. L., Haug-Baltzell, A. K., Hulvey, J. P., McCarthy, F., Devisetty, U. K., & Lyons, E. (2017). Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms. Journal of visualized experiments: JoVE.
• Joyce, B., Baltzell, A., McCarthy, F., Bomhoff, M., & Lyons, E. (2017). iAnimal: Cyberinfrastructure to Support Data-driven Science. Bioinformatics in Aquaculture: Principles and Methods, 527--545.
• Kelly, A. C., Bidwell, C. A., McCarthy, F. M., Taska, D. J., Anderson, M. J., Camacho, L. E., & Limesand, S. W. (2017). RNA sequencing exposes adaptive and immune responses to intrauterine growth restriction in fetal sheep islets. Endocrinology, 158(4), 743--755.
• Krishnavajhala, A., Muire, P. J., Hanson, L., Wan, H., McCarthy, F., Zhou, A., & Petrie-Hanson, L. (2017). Transcriptome Changes Associated with Protective Immunity in T and B Cell-Deficient Rag1-/-Mutant Zebrafish. International Journal of Immunology, 5(2), 20--36.
• Pinchuk, L. M., Pharr, G. T., Pendarvis, K., Mccarthy, F. M., & Ammari, M. G. (2017). Evaluation of bovine viral diarrhea virus interactions with its host proteome during the course of infection. Biomedical Research and Clinical Practice, 2(3). doi:10.15761/brcp.1000140
• Rice, E. S., Kohno, S., John, J. S., Pham, S., Howard, J., Lareau, L. F., O'Connell, B. L., Hickey, G., Armstrong, J., Deran, A., & others, . (2017). Improved genome assembly of American alligator genome reveals conserved architecture of estrogen signaling. Genome research, 27(5), 686--696.
• Smith, K. E., Kelly, A. C., Min, C. G., Weber, C. S., McCarthy, F. M., Steyn, L. V., Badarinarayana, V., Stanton, J. B., Kitzmann, J. P., Strop, P., & others, . (2017). Acute Ischemia Induced by High-Density Culture Increases Cytokine Expression and Diminishes the Function and Viability of Highly Purified Human Islets of Langerhans. Transplantation, 101(11), 2705--2712.
• Zhang, J., & Mccarthy, F. M. (2017). Development of avian anatomy ontology annotation. F1000Research, 6. doi:10.7490/f1000research.1113801.1
• Ammari, M. G., Gresham, C. R., McCarthy, F. M., & Nanduri, B. (2016). HPIDB 2.0: a curated database for host--pathogen interactions. Database, 2016, baw103.
• Koltes, J., Reecy, J., Lyons, E., McCarthy, F., Vaughn, M., Carson, J., Fritz-Waters, E., & Williams, J. (2016). P1039 Bioinformatics resources for animal genomics using CyVerse cyberinfrastructure.. Journal of Animal Science, 94(7supplement4), 33--34.
• Mykles, D. L., Burnett, K. G., Durica, D. S., Joyce, B. L., McCarthy, F. M., Schmidt, C. J., & Stillman, J. H. (2016). Resources and recommendations for using transcriptomics to address grand challenges in comparative biology. Integrative and comparative biology, icw083.
• Rice, E. S., Kohno, S., John, J. S., Pham, S., Howard, J., Lareau, L., O'Connell, B., Hickey, G., Armstrong, J., Deran, A., & others, . (2016). Improved genome assembly of American alligator genome reveals conserved architecture of estrogen signaling. bioRxiv, 067165.
• Andersson, L., Archibald, A. L., Bottema, C. D., Brauning, R., Burgess, S. C., Burt, D. W., Casas, E., Cheng, H. H., Clarke, L., Couldrey, C., Dalrymple, B. P., Elsik, C. G., Foissac, S., Giuffra, E., Groenen, M. A., Hayes, B. J., Huang, L. S., Khatib, H., Kijas, J. W., , Kim, H., et al. (2015). Coordinated international action to accelerate genome-to-phenome with FAANG, the Functional Annotation of Animal Genomes project. Genome biology, 16, 57.
  More info

  We describe the organization of a nascent international effort, the Functional Annotation of Animal Genomes (FAANG) project, whose aim is to produce comprehensive maps of functional elements in the genomes of domesticated animal species.
• Haug-Baltzell, A., Jarvis, E. D., McCarthy, F. M., & Lyons, E. (2015). Identification of dopamine receptors across the extant avian family tree and analysis with other clades uncovers a polyploid expansion among vertebrates. Frontiers in neuroscience, 9, 361.
  More info

  Dopamine is an important central nervous system transmitter that functions through two classes of receptors (D1 and D2) to influence a diverse range of biological processes in vertebrates. With roles in regulating neural activity, behavior, and gene expression, there has been great interest in understanding the function and evolution dopamine and its receptors. In this study, we use a combination of sequence analyses, microsynteny analyses, and phylogenetic relationships to identify and characterize both the D1 (DRD1A, DRD1B, DRD1C, and DRD1E) and D2 (DRD2, DRD3, and DRD4) dopamine receptor gene families in 43 recently sequenced bird genomes representing the major ordinal lineages across the avian family tree. We show that the common ancestor of all birds possessed at least seven D1 and D2 receptors, followed by subsequent independent losses in some lineages of modern birds. Through comparisons with other vertebrate and invertebrate species we show that two of the D1 receptors, DRD1A and DRD1B, and two of the D2 receptors, DRD2 and DRD3, originated from a whole genome duplication event early in the vertebrate lineage, providing the first conclusive evidence of the origin of these highly conserved receptors. Our findings provide insight into the evolutionary development of an important modulatory component of the central nervous system in vertebrates, and will help further unravel the complex evolutionary and functional relationships among dopamine receptors.
• Herman, E. M., Schmidt, M. A., Pendarvis, K., Parrott, W. A., Mccarthy, F. M., Hildebrand, D. F., Herman, E. M., He, Y., Cooksey, A. M., & Berg, R. H. (2015). Transgenic soya bean seeds accumulating β-carotene exhibit the collateral enhancements of oleate and protein content traits.. Plant biotechnology journal, 13(4), 590-600. doi:10.1111/pbi.12286
  More info

  Transgenic soya bean (Glycine max) plants overexpressing a seed-specific bacterial phytoene synthase gene from Pantoea ananatis modified to target to plastids accumulated 845 μg β carotene g(-1) dry seed weight with a desirable 12:1 ratio of β to α. The β carotene accumulating seeds exhibited a shift in oil composition increasing oleic acid with a concomitant decrease in linoleic acid and an increase in seed protein content by at least 4% (w/w). Elevated β-carotene accumulating soya bean cotyledons contain 40% the amount of abscisic acid compared to nontransgenic cotyledons. Proteomic and nontargeted metabolomic analysis of the mid-maturation β-carotene cotyledons compared to the nontransgenic did not reveal any significant differences that would account for the altered phenotypes of both elevated oleate and protein content. Transcriptomic analysis, confirmed by RT-PCR, revealed a number of significant differences in ABA-responsive transcripton factor gene expression in the crtB transgenics compared to nontransgenic cotyledons of the same maturation stage. The altered seed composition traits seem to be attributed to altered ABA hormone levels varying transcription factor expression. The elevated β-carotene, oleic acid and protein traits in the β-carotene soya beans confer a substantial additive nutritional quality to soya beans.
• Schmid, M., Smith, J., Burt, D. W., Aken, B. L., Antin, P. B., Archibald, A. L., Ashwell, C., Blackshear, P. J., Boschiero, C., Brown, C. T., Burgess, S. C., Cheng, H. H., Chow, W., Coble, D. J., Cooksey, A., Crooijmans, R. P., Damas, J., Davis, R. V., de Koning, D., , Delany, M. E., et al. (2015). Third Report on Chicken Genes and Chromosomes 2015. Cytogenetic and genome research, 145(2), 78-179.
• Smith, K., Kelly, A. C., Weber, C., Min, C., Smith, B., Mccarthy, F., Steyn, L. V., Badarinarayana, V., Strop, P., Lynch, R. M., & others, . (2015). Acute ischemic exposure leads to functional deficits and a transcriptome enriched in inflammatory and hypoxic pathways in human islets. Xenotransplantation, 22, S149.
• Sun, L., Lamont, S. J., Cooksey, A. M., McCarthy, F., Tudor, C. O., Vijay-Shanker, K., DeRita, R. M., Rothschild, M., Ashwell, C., Persia, M. E., & Schmidt, C. J. (2015). Transcriptome response to heat stress in a chicken hepatocellular carcinoma cell line. Cell stress & chaperones, 20(6), 939-50.
  More info

  Heat stress triggers an evolutionarily conserved set of responses in cells. The transcriptome responds to hyperthermia by altering expression of genes to adapt the cell or organism to survive the heat challenge. RNA-seq technology allows rapid identification of environmentally responsive genes on a large scale. In this study, we have used RNA-seq to identify heat stress responsive genes in the chicken male white leghorn hepatocellular (LMH) cell line. The transcripts of 812 genes were responsive to heat stress (p < 0.01) with 235 genes upregulated and 577 downregulated following 2.5 h of heat stress. Among the upregulated were genes whose products function as chaperones, along with genes affecting collagen synthesis and deposition, transcription factors, chromatin remodelers, and genes modulating the WNT and TGF-beta pathways. Predominant among the downregulated genes were ones that affect DNA replication and repair along with chromosomal segregation. Many of the genes identified in this study have not been previously implicated in the heat stress response. These data extend our understanding of the transcriptome response to heat stress with many of the identified biological processes and pathways likely to function in adapting cells and organisms to hyperthermic stress. Furthermore, this study should provide important insight to future efforts attempting to improve species abilities to withstand heat stress through genome-wide association studies and breeding.
• Fox, S. E., Geniza, M., Hanumappa, M., Naithani, S., Sullivan, C., Preece, J., Tiwari, V. K., Elser, J., Leonard, J. M., Sage, A., Gresham, C., Kerhornou, A., Bolser, D., McCarthy, F., Kersey, P., Lazo, G. R., & Jaiswal, P. (2014). De novo transcriptome assembly and analyses of gene expression during photomorphogenesis in diploid wheat Triticum monococcum. PloS one, 9(5), e96855.
  More info

  Triticum monococcum (2n) is a close ancestor of T. urartu, the A-genome progenitor of cultivated hexaploid wheat, and is therefore a useful model for the study of components regulating photomorphogenesis in diploid wheat. In order to develop genetic and genomic resources for such a study, we constructed genome-wide transcriptomes of two Triticum monococcum subspecies, the wild winter wheat T. monococcum ssp. aegilopoides (accession G3116) and the domesticated spring wheat T. monococcum ssp. monococcum (accession DV92) by generating de novo assemblies of RNA-Seq data derived from both etiolated and green seedlings.
• Green, R. E., Braun, E. L., Armstrong, J., Earl, D., Nguyen, N., Hickey, G., Vandewege, M. W., St John, J. A., Capella-Gutiérrez, S., Castoe, T. A., Kern, C., Fujita, M. K., Opazo, J. C., Jurka, J., Kojima, K. K., Caballero, J., Hubley, R. M., Smit, A. F., Platt, R. N., , Lavoie, C. A., et al. (2014). Three crocodilian genomes reveal ancestral patterns of evolution among archosaurs. Science (New York, N.Y.), 346(6215), 1254449.
  More info

  To provide context for the diversification of archosaurs--the group that includes crocodilians, dinosaurs, and birds--we generated draft genomes of three crocodilians: Alligator mississippiensis (the American alligator), Crocodylus porosus (the saltwater crocodile), and Gavialis gangeticus (the Indian gharial). We observed an exceptionally slow rate of genome evolution within crocodilians at all levels, including nucleotide substitutions, indels, transposable element content and movement, gene family evolution, and chromosomal synteny. When placed within the context of related taxa including birds and turtles, this suggests that the common ancestor of all of these taxa also exhibited slow genome evolution and that the comparatively rapid evolution is derived in birds. The data also provided the opportunity to analyze heterozygosity in crocodilians, which indicates a likely reduction in population size for all three taxa through the Pleistocene. Finally, these data combined with newly published bird genomes allowed us to reconstruct the partial genome of the common ancestor of archosaurs, thereby providing a tool to investigate the genetic starting material of crocodilians, birds, and dinosaurs.
• Jaratlerdsiri, W., Deakin, J., Godinez, R. M., Shan, X., Peterson, D. G., Marthey, S., Lyons, E., McCarthy, F. M., Isberg, S. R., Higgins, D. P., Chong, A. Y., John, J. S., Glenn, T. C., Ray, D. A., & Gongora, J. (2014). Comparative genome analyses reveal distinct structure in the saltwater crocodile MHC. PloS one, 9(12), e114631.
  More info

  The major histocompatibility complex (MHC) is a dynamic genome region with an essential role in the adaptive immunity of vertebrates, especially antigen presentation. The MHC is generally divided into subregions (classes I, II and III) containing genes of similar function across species, but with different gene number and organisation. Crocodylia (crocodilians) are widely distributed and represent an evolutionary distinct group among higher vertebrates, but the genomic organisation of MHC within this lineage has been largely unexplored. Here, we studied the MHC region of the saltwater crocodile (Crocodylus porosus) and compared it with that of other taxa. We characterised genomic clusters encompassing MHC class I and class II genes in the saltwater crocodile based on sequencing of bacterial artificial chromosomes. Six gene clusters spanning ∼452 kb were identified to contain nine MHC class I genes, six MHC class II genes, three TAP genes, and a TRIM gene. These MHC class I and class II genes were in separate scaffold regions and were greater in length (2-6 times longer) than their counterparts in well-studied fowl B loci, suggesting that the compaction of avian MHC occurred after the crocodilian-avian split. Comparative analyses between the saltwater crocodile MHC and that from the alligator and gharial showed large syntenic areas (>80% identity) with similar gene order. Comparisons with other vertebrates showed that the saltwater crocodile had MHC class I genes located along with TAP, consistent with birds studied. Linkage between MHC class I and TRIM39 observed in the saltwater crocodile resembled MHC in eutherians compared, but absent in avian MHC, suggesting that the saltwater crocodile MHC appears to have gene organisation intermediate between these two lineages. These observations suggest that the structure of the saltwater crocodile MHC, and other crocodilians, can help determine the MHC that was present in the ancestors of archosaurs.
• Schmidt, M. A., Parrott, W. A., Hildebrand, D. F., Berg, R. H., Cooksey, A., Pendarvis, K., He, Y., McCarthy, F., & Herman, E. M. (2014). Transgenic soya bean seeds accumulating β-carotene exhibit the collateral enhancements of oleate and protein content traits. Plant biotechnology journal.
  More info

  Transgenic soya bean (Glycine max) plants overexpressing a seed-specific bacterial phytoene synthase gene from Pantoea ananatis modified to target to plastids accumulated 845 μg β carotene g(-1) dry seed weight with a desirable 12:1 ratio of β to α. The β carotene accumulating seeds exhibited a shift in oil composition increasing oleic acid with a concomitant decrease in linoleic acid and an increase in seed protein content by at least 4% (w/w). Elevated β-carotene accumulating soya bean cotyledons contain 40% the amount of abscisic acid compared to nontransgenic cotyledons. Proteomic and nontargeted metabolomic analysis of the mid-maturation β-carotene cotyledons compared to the nontransgenic did not reveal any significant differences that would account for the altered phenotypes of both elevated oleate and protein content. Transcriptomic analysis, confirmed by RT-PCR, revealed a number of significant differences in ABA-responsive transcripton factor gene expression in the crtB transgenics compared to nontransgenic cotyledons of the same maturation stage. The altered seed composition traits seem to be attributed to altered ABA hormone levels varying transcription factor expression. The elevated β-carotene, oleic acid and protein traits in the β-carotene soya beans confer a substantial additive nutritional quality to soya beans.
• Buza, T. J., & McCarthy, F. M. (2013). Functional genomics: applications to production agriculture.. Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 8(054), 1-21.
• Buza, T., & McCarthy, F. M. (2013). Functional genomics: Applications to production agriculture. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 8.
  More info

  Abstract: Functional genomics enables agricultural researchers to investigate how gene expression and regulation contributes to complex production traits at a genome-wide level. There are many different techniques for utilizing functional genomic approaches and new high-throughput technologies are accelerating the amount and complexity of data collected from functional genomics experiments. In this review, we highlight some of the different areas of functional genomics, including some emerging techniques, with a specific focus on how they are being applied to production livestock and aquaculture systems. We look at how transcriptomics, proteomics, metabolomics, interactomics, epigenetics and nutrigenomics are applied to improve our understanding of complex production traits and how the environment affects these traits. We also discuss how changing technologies contribute to functional genomics and the resources agricultural researchers require to ensure that their functional genomics data are effectively translated into benefits for society. © CAB International 2013.
• Das, P. J., McCarthy, F., Vishnoi, M., Paria, N., Gresham, C., Gang, L. i., Kachroo, P., Sudderth, A. K., Teague, S., Love, C. C., Varner, D. D., Chowdhary, B. P., & Raudsepp, T. (2013). Stallion Sperm Transcriptome Comprises Functionally Coherent Coding and Regulatory RNAs as Revealed by Microarray Analysis and RNA-seq. PLoS ONE, 8(2).
  More info

  PMID: 23409192;PMCID: PMC3569414;Abstract: Mature mammalian sperm contain a complex population of RNAs some of which might regulate spermatogenesis while others probably play a role in fertilization and early development. Due to this limited knowledge, the biological functions of sperm RNAs remain enigmatic. Here we report the first characterization of the global transcriptome of the sperm of fertile stallions. The findings improved understanding of the biological significance of sperm RNAs which in turn will allow the discovery of sperm-based biomarkers for stallion fertility. The stallion sperm transcriptome was interrogated by analyzing sperm and testes RNA on a 21,000-element equine whole-genome oligoarray and by RNA-seq. Microarray analysis revealed 6,761 transcripts in the sperm, of which 165 were sperm-enriched, and 155 were differentially expressed between the sperm and testes. Next, 70 million raw reads were generated by RNA-seq of which 50% could be aligned with the horse reference genome. A total of 19,257 sequence tags were mapped to all horse chromosomes and the mitochondrial genome. The highest density of mapped transcripts was in gene-rich ECA11, 12 and 13, and the lowest in gene-poor ECA9 and X; 7 gene transcripts originated from ECAY. Structural annotation aligned sperm transcripts with 4,504 known horse and/or human genes, rRNAs and 82 miRNAs, whereas 13,354 sequence tags remained anonymous. The data were aligned with selected equine gene models to identify additional exons and splice variants. Gene Ontology annotations showed that sperm transcripts were associated with molecular processes (chemoattractant-activated signal transduction, ion transport) and cellular components (membranes and vesicles) related to known sperm functions at fertilization, while some messenger and micro RNAs might be critical for early development. The findings suggest that the rich repertoire of coding and non-coding RNAs in stallion sperm is not a random remnant from spermatogenesis in testes but a selectively retained and functionally coherent collection of RNAs. © 2013 Das et al.
• Das, P. J., McCarthy, F., Vishnoi, M., Paria, N., Gresham, C., Li, G., Kachroo, P., Sudderth, A. K., Teague, S., Love, C. C., Varner, D. D., Chowdhary, B. P., & Raudsepp, T. (2013). Stallion sperm transcriptome comprises functionally coherent coding and regulatory RNAs as revealed by microarray analysis and RNA-seq. PloS one, 8(2).
  More info

  Mature mammalian sperm contain a complex population of RNAs some of which might regulate spermatogenesis while others probably play a role in fertilization and early development. Due to this limited knowledge, the biological functions of sperm RNAs remain enigmatic. Here we report the first characterization of the global transcriptome of the sperm of fertile stallions. The findings improved understanding of the biological significance of sperm RNAs which in turn will allow the discovery of sperm-based biomarkers for stallion fertility. The stallion sperm transcriptome was interrogated by analyzing sperm and testes RNA on a 21,000-element equine whole-genome oligoarray and by RNA-seq. Microarray analysis revealed 6,761 transcripts in the sperm, of which 165 were sperm-enriched, and 155 were differentially expressed between the sperm and testes. Next, 70 million raw reads were generated by RNA-seq of which 50% could be aligned with the horse reference genome. A total of 19,257 sequence tags were mapped to all horse chromosomes and the mitochondrial genome. The highest density of mapped transcripts was in gene-rich ECA11, 12 and 13, and the lowest in gene-poor ECA9 and X; 7 gene transcripts originated from ECAY. Structural annotation aligned sperm transcripts with 4,504 known horse and/or human genes, rRNAs and 82 miRNAs, whereas 13,354 sequence tags remained anonymous. The data were aligned with selected equine gene models to identify additional exons and splice variants. Gene Ontology annotations showed that sperm transcripts were associated with molecular processes (chemoattractant-activated signal transduction, ion transport) and cellular components (membranes and vesicles) related to known sperm functions at fertilization, while some messenger and micro RNAs might be critical for early development. The findings suggest that the rich repertoire of coding and non-coding RNAs in stallion sperm is not a random remnant from spermatogenesis in testes but a selectively retained and functionally coherent collection of RNAs.
• Hill, D. P., Sitnikov, D., Legge, D., Park, J., Burgess, S. C., Zweifel, A. E., Xenarios, I., Wood, W., Wood, V., Wong, E. D., Westerfield, M., Weng, S., Wang, S. J., Tweedie, S., Tognolli, M., Thomas, P. D., Talmud, P. J., Sundaram, S., Stutz, A., , Sternberg, P. W., et al. (2013). Gene Ontology annotations and resources.. Nucleic acids research, 41(Database issue), D530-5. doi:10.1093/nar/gks1050
  More info

  The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.
• Lyons, E., Mccarthy, F. M., & Lyons, E. (2013). From data to function: functional modeling of poultry genomics data.. Poultry science, 92(9), 2519-29. doi:10.3382/ps.2012-02808
  More info

  One of the challenges of functional genomics is to create a better understanding of the biological system being studied so that the data produced are leveraged to provide gains for agriculture, human health, and the environment. Functional modeling enables researchers to make sense of these data as it reframes a long list of genes or gene products (mRNA, ncRNA, and proteins) by grouping based upon function, be it individual molecular functions or interactions between these molecules or broader biological processes, including metabolic and signaling pathways. However, poultry researchers have been hampered by a lack of functional annotation data, tools, and training to use these data and tools. Moreover, this lack is becoming more critical as new sequencing technologies enable us to generate data not only for an increasingly diverse range of species but also individual genomes and populations of individuals. We discuss the impact of these new sequencing technologies on poultry research, with a specific focus on what functional modeling resources are available for poultry researchers. We also describe key strategies for researchers who wish to functionally model their own data, providing background information about functional modeling approaches, the data and tools to support these approaches, and the strengths and limitations of each. Specifically, we describe methods for functional analysis using Gene Ontology (GO) functional summaries, functional enrichment analysis, and pathways and network modeling. As annotation efforts begin to provide the fundamental data that underpin poultry functional modeling (such as improved gene identification, standardized gene nomenclature, temporal and spatial expression data and gene product function), tool developers are incorporating these data into new and existing tools that are used for functional modeling, and cyberinfrastructure is being developed to provide the necessary extendibility and scalability for storing and analyzing these data. This process will support the efforts of poultry researchers to make sense of their functional genomics data sets, and we provide here a starting point for researchers who wish to take advantage of these tools.
• Manda, P., McCarthy, F., & Bridges, S. M. (2013). Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships. Journal of Biomedical Informatics, 46(5), 849-856.
  More info

  PMID: 23850840;Abstract: The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support ( MOSupport) and Multi-ontology Confidence ( MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships. © 2013 The Authors.
• Manda, P., McCarthy, F., & Bridges, S. M. (2013). Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships. Journal of biomedical informatics, 46(5).
  More info

  The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships.
• Ammari, M., McCarthy, F., Nanduri, B., Pinchuk, G., & Pinchuk, L. (2012). Understanding the Pathogenesis of Cytopathic and Noncytopathic Bovine Viral Diarrhea Virus Infection Using Proteomics. Proteomic Applications in Biology.
• Chouvarine, P., Cooksey, A. M., McCarthy, F. M., Ray, D. A., Baldwin, B. S., Burgess, S. C., & Peterson, D. G. (2012). Transcriptome-based differentiation of closely-related Miscanthus lines. PloS one, 7(1).
  More info

  Distinguishing between individuals is critical to those conducting animal/plant breeding, food safety/quality research, diagnostic and clinical testing, and evolutionary biology studies. Classical genetic identification studies are based on marker polymorphisms, but polymorphism-based techniques are time and labor intensive and often cannot distinguish between closely related individuals. Illumina sequencing technologies provide the detailed sequence data required for rapid and efficient differentiation of related species, lines/cultivars, and individuals in a cost-effective manner. Here we describe the use of Illumina high-throughput exome sequencing, coupled with SNP mapping, as a rapid means of distinguishing between related cultivars of the lignocellulosic bioenergy crop giant miscanthus (Miscanthus × giganteus). We provide the first exome sequence database for Miscanthus species complete with Gene Ontology (GO) functional annotations.
• Das, P., ,, M. F., Paria, N., Vishnoi, M., Gresham, C., Gang, ., Kachroo, P., Sudderth, K., Teague, S., Love, C., Varner, D., Chowdhary, B., & Raudsepp, T. (2012). Stallion sperm transcriptome comprises functionally coherent coding and regulatory RNAs as revealed by microarray analysis and RNA-seq. PLOS One.
• Li, X., Swaggerty, C. L., Kogut, M. H., Chiang, H., Wang, Y., Genovese, K. J., He, H., McCarthy, F. M., Burgess, S. C., Pevzner, I. Y., & Zhou, H. (2012). Systemic response to Campylobacter jejuni infection by profiling gene transcription in the spleens of two genetic lines of chickens. Immunogenetics, 64(1).
  More info

  Campylobacter jejuni (C. jejuni) is a leading cause of human bacterial enteritis worldwide with poultry products being a major source of C. jejuni contamination. The chicken is the natural reservoir of C. jejuni where bacteria colonize the digestive tract of poultry, but rarely cause symptoms of disease. To understand the systemic molecular response mechanisms to C. jejuni infection in chickens, total splenic RNA was isolated and applied to a whole genome chicken microarray for comparison between infected (I) and non-infected (N) chickens within and between genetic lines A and B. There were more total splenic host genes responding to the infection in resistant line A than in susceptible line B. Specifically, genes for lymphocyte activation, differentiation and humoral response, and Ig light and heavy chain were upregulated in the resistant line. In the susceptible line, genes for regulation of erythrocyte differentiation, hemopoiesis, and RNA biosynthetic process were all downregulated. An interaction analysis between genetic lines and treatment demonstrated distinct defense mechanisms between lines: the resistant line promoted apoptosis and cytochrome c release from mitochondria, whereas the susceptible line responded with a downregulation of both functions. This was the first time that such systemic defensive mechanisms against C. jejuni infection have been reported. The results of this study revealed novel molecular mechanisms of the systemic host responses to C. jejuni infection in chickens that warrant further investigation.
• Manda, P., Ozkan, S., Wang, H., McCarthy, F., & Bridges, S. (2012). Cross-ontology Multi-level Association Rule Mining in the Gene Ontology. PLoS One, e47411. doi: 10.1371/journal.pone.0047411.
• Manda, P., Ozkan, S., Wang, H., McCarthy, F., & Bridges, S. M. (2012). Cross-Ontology Multi-level Association Rule Mining in the Gene Ontology. PLoS ONE, 7(10).
  More info

  PMID: 23071802;PMCID: PMC3470562;Abstract: The Gene Ontology (GO) has become the internationally accepted standard for representing function, process, and location aspects of gene products. The wealth of GO annotation data provides a valuable source of implicit knowledge of relationships among these aspects. We describe a new method for association rule mining to discover implicit co-occurrence relationships across the GO sub-ontologies at multiple levels of abstraction. Prior work on association rule mining in the GO has concentrated on mining knowledge at a single level of abstraction and/or between terms from the same sub-ontology. We have developed a bottom-up generalization procedure called Cross-Ontology Data Mining-Level by Level (COLL) that takes into account the structure and semantics of the GO, generates generalized transactions from annotation data and mines interesting multi-level cross-ontology association rules. We applied our method on publicly available chicken and mouse GO annotation datasets and mined 5368 and 3959 multi-level cross ontology rules from the two datasets respectively. We show that our approach discovers more and higher quality association rules from the GO as evaluated by biologists in comparison to previously published methods. Biologically interesting rules discovered by our method reveal unknown and surprising knowledge about co-occurring GO terms. © 2012 Manda et al.
• Manda, P., Ozkan, S., Wang, H., McCarthy, F., & Bridges, S. M. (2012). Cross-Ontology multi-level association rule mining in the Gene Ontology. PloS one, 7(10).
  More info

  The Gene Ontology (GO) has become the internationally accepted standard for representing function, process, and location aspects of gene products. The wealth of GO annotation data provides a valuable source of implicit knowledge of relationships among these aspects. We describe a new method for association rule mining to discover implicit co-occurrence relationships across the GO sub-ontologies at multiple levels of abstraction. Prior work on association rule mining in the GO has concentrated on mining knowledge at a single level of abstraction and/or between terms from the same sub-ontology. We have developed a bottom-up generalization procedure called Cross-Ontology Data Mining-Level by Level (COLL) that takes into account the structure and semantics of the GO, generates generalized transactions from annotation data and mines interesting multi-level cross-ontology association rules. We applied our method on publicly available chicken and mouse GO annotation datasets and mined 5368 and 3959 multi-level cross ontology rules from the two datasets respectively. We show that our approach discovers more and higher quality association rules from the GO as evaluated by biologists in comparison to previously published methods. Biologically interesting rules discovered by our method reveal unknown and surprising knowledge about co-occurring GO terms.
• McCarthy, F. M., St, J. J., Braun, E., Isberg, S., Miles, L., Chong, A., Gongora, J., Dalzell, P., Moran, C., Bed, H. B., Abzhanov, A., Burgess, S., Cooksey, A., Castoe, T., Crawford, N., Densmore, L., Drew, ., Edwards, ., Faircloth, B., , Fujita, ., et al. (2012). Sequencing three crocodilian genomes to illuminate the evolution of archosaurs and amniotes. Genome Biology, 13, 1.
• Pillai, L., Chouvarine, P., Tudor, C. O., Schmidt, C. J., Vijay-Shanker, K., & McCarthy, F. M. (2012). Developing a biocuration workflow for AgBase, a non-model organism database. Database : the journal of biological databases and curation, 2012.
  More info

  AgBase provides annotation for agricultural gene products using the Gene Ontology (GO) and Plant Ontology, as appropriate. Unlike model organism species, agricultural species have a body of literature that does not just focus on gene function; to improve efficiency, we use text mining to identify literature for curation. The first component of our annotation interface is the gene prioritization interface that ranks gene products for annotation. Biocurators select the top-ranked gene and mark annotation for these genes as 'in progress' or 'completed'; links enable biocurators to move directly to our biocuration interface (BI). Our BI includes all current GO annotation for gene products and is the main interface to add/modify AgBase curation data. The BI also displays Extracting Genic Information from Text (eGIFT) results for each gene product. eGIFT is a web-based, text-mining tool that associates ranked, informative terms (iTerms) and the articles and sentences containing them, with genes. Moreover, iTerms are linked to GO terms, where they match either a GO term name or a synonym. This enables AgBase biocurators to rapidly identify literature for further curation based on possible GO terms. Because most agricultural species do not have standardized literature, eGIFT searches all gene names and synonyms to associate articles with genes. As many of the gene names can be ambiguous, eGIFT applies a disambiguation step to remove matches that do not correspond to this gene, and filtering is applied to remove abstracts that mention a gene in passing. The BI is linked to our Journal Database (JDB) where corresponding journal citations are stored. Just as importantly, biocurators also add to the JDB citations that have no GO annotation. The AgBase BI also supports bulk annotation upload to facilitate our Inferred from electronic annotation of agricultural gene products. All annotations must pass standard GO Consortium quality checking before release in AgBase. Database URL: http://www.agbase.msstate.edu/.
• Pillai, L., Chouvarine, P., Tudor, C. O., Schmidt, C. J., Vijay-Shanker, K., & McCarthy, F. M. (2012). Developing a biocuration workflow for AgBase, a non-model organism database.. Database : the journal of biological databases and curation, 2012, bas038.
  More info

  PMID: 23160411;PMCID: PMC3500517;Abstract: AgBase provides annotation for agricultural gene products using the Gene Ontology (GO) and Plant Ontology, as appropriate. Unlike model organism species, agricultural species have a body of literature that does not just focus on gene function; to improve efficiency, we use text mining to identify literature for curation. The first component of our annotation interface is the gene prioritization interface that ranks gene products for annotation. Biocurators select the top-ranked gene and mark annotation for these genes as 'in progress' or 'completed'; links enable biocurators to move directly to our biocuration interface (BI). Our BI includes all current GO annotation for gene products and is the main interface to add/modify AgBase curation data. The BI also displays Extracting Genic Information from Text (eGIFT) results for each gene product. eGIFT is a web-based, text-mining tool that associates ranked, informative terms (iTerms) and the articles and sentences containing them, with genes. Moreover, iTerms are linked to GO terms, where they match either a GO term name or a synonym. This enables AgBase biocurators to rapidly identify literature for further curation based on possible GO terms. Because most agricultural species do not have standardized literature, eGIFT searches all gene names and synonyms to associate articles with genes. As many of the gene names can be ambiguous, eGIFT applies a disambiguation step to remove matches that do not correspond to this gene, and filtering is applied to remove abstracts that mention a gene in passing. The BI is linked to our Journal Database (JDB) where corresponding journal citations are stored. Just as importantly, biocurators also add to the JDB citations that have no GO annotation. The AgBase BI also supports bulk annotation upload to facilitate our Inferred from electronic annotation of agricultural gene products. All annotations must pass standard GO Consortium quality checking before release in AgBase. Database URL: http://www.agbase.msstate.edu/.
• Pillai, L., Chouvarine, P., Tudor, C., Schmidt, C., Vijay-Shanker, K., & McCarthy, F. (2012). Developing a biocuration workflow for AgBase, a non-model organism database. Database 2012:bas038, doi: 10.1093.
• Burgess, S. C., Swiderski, C. E., Nanduri, B., Mujahid, N., Mccarthy, F. M., Costa, L. R., Burgess, S. C., & Bright, L. A. (2011). Functional modelling of an equine bronchoalveolar lavage fluid proteome provides experimental confirmation and functional annotation of equine genome sequences.. Animal genetics, 42(4), 395-405. doi:10.1111/j.1365-2052.2010.02158.x
  More info

  The equine genome sequence enables the use of high-throughput genomic technologies in equine research, but accurate identification of expressed gene products and interpreting their biological relevance require additional structural and functional genome annotation. Here, we employ the equine genome sequence to identify predicted and known proteins using proteomics and model these proteins into biological pathways, identifying 582 proteins in normal cell-free equine bronchoalveolar lavage fluid (BALF). We improved structural and functional annotation by directly confirming the in vivo expression of 558 (96%) proteins, which were computationally predicted previously, and adding Gene Ontology (GO) annotations for 174 proteins, 108 of which lacked functional annotation. Bronchoalveolar lavage is commonly used to investigate equine respiratory disease, leading us to model the associated proteome and its biological functions. Modelling of protein functions using Ingenuity Pathway Analysis identified carbohydrate metabolism, cell-to-cell signalling, cellular function, inflammatory response, organ morphology, lipid metabolism and cellular movement as key biological processes in normal equine BALF. Comparative modelling of protein functions in normal cell-free bronchoalveolar lavage proteomes from horse, human, and mouse, performed by grouping GO terms sharing common ancestor terms, confirms conservation of functions across species. Ninety-one of 92 human GO categories and 105 of 109 mouse GO categories were conserved in the horse. Our approach confirms the utility of the equine genome sequence to characterize protein networks without antibodies or mRNA quantification, highlights the need for continued structural and functional annotation of the equine genome and provides a framework for equine researchers to aid in the annotation effort.
• McCarthy, F. M., Gresham, C. R., Buza, T. J., Chouvarine, P., Pillai, L. R., Kumar, R., Ozkan, S., Wang, H., Manda, P., Arick, T., Bridges, S. M., & Burgess, S. C. (2011). AgBase: supporting functional modeling in agricultural organisms. Nucleic acids research, 39(Database issue).
  More info

  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.
• Sanders, W. S., Wang, N., Bridges, S. M., Malone, B. M., Dandass, Y. S., McCarthy, F. M., Nanduri, B., Lawrence, M. L., & Burgess, S. C. (2011). The proteogenomic mapping tool. BMC bioinformatics, 12.
  More info

  High-throughput mass spectrometry (MS) proteomics data is increasingly being used to complement traditional structural genome annotation methods. To keep pace with the high speed of experimental data generation and to aid in structural genome annotation, experimentally observed peptides need to be mapped back to their source genome location quickly and exactly. Previously, the tools to do this have been limited to custom scripts designed by individual research groups to analyze their own data, are generally not widely available, and do not scale well with large eukaryotic genomes.
• Ammari, M., McCarthy, F. M., Nanduri, B., & Pinchuk, L. M. (2010). Analysis of Bovine Viral Diarrhea Viruses-infected monocytes: Identification of cytopathic and non-cytopathic biotype differences. BMC Bioinformatics, 11(SUPPL. 6).
  More info

  PMID: 20946620;PMCID: PMC3026383;Abstract: Background: Bovine Viral Diarrhea Virus (BVDV) infection is widespread in cattle worldwide, causing important economic losses. Pathogenesis of the disease caused by BVDV is complex, as each BVDV strain has two biotypes: non-cytopathic (ncp) and cytopathic (cp). BVDV can cause a persistent latent infection and immune suppression if animals are infected with an ncp biotype during early gestation, followed by a subsequent infection of the cp biotype. The molecular mechanisms that underscore the complex disease etiology leading to immune suppression in cattle caused by BVDV are not well understood.Results: Using proteomics, we evaluated the effect of cp and ncp BVDV infection of bovine monocytes to determine their role in viral immune suppression and uncontrolled inflammation. Proteins were isolated by differential detergent fractionation and identified by 2D-LC ESI MS/MS. We identified 137 and 228 significantly altered bovine proteins due to ncp and cp BVDV infection, respectively. Functional analysis of these proteins using the Gene Ontology (GO) showed multiple under- and over- represented GO functions in molecular function, biological process and cellular component between the two BVDV biotypes. Analysis of the top immunological pathways affected by BVDV infection revealed that pathways representing macropinocytosis signalling, virus entry via endocytic pathway, integrin signalling and primary immunodeficiency signalling were identified only in ncp BVDV-infected monocytes. In contrast, pathways like actin cytoskeleton signalling, RhoA signalling, clathrin-mediated endocytosis signalling and interferon signalling were identified only in cp BDVD-infected cells. Of the six common pathways involved in cp and ncp BVDV infection, acute phase response signalling was the most significant for both BVDV biotypes. Although, most shared altered host proteins between both BVDV biotypes showed the same type of change, integrin alpha 2b (ITGA2B) and integrin beta 3 (ITGB3) were down- regulated by ncp BVDV and up- regulated by cp BVDV infection.Conclusions: This study shows that, as we expected, there are significant functional differences in the host proteins that respond to cp or ncp BVDV infection. The combined use of GO and systems biology network modelling facilitated a better understanding of host-pathogen interactions. © 2010 Pinchuk et al; licensee BioMed Central Ltd.
• Ammari, M., McCarthy, F. M., Nanduri, B., & Pinchuk, L. M. (2010). Analysis of Bovine Viral Diarrhea Viruses-infected monocytes: identification of cytopathic and non-cytopathic biotype differences. BMC bioinformatics, 11 Suppl 6, S9.
  More info

  Bovine Viral Diarrhea Virus (BVDV) infection is widespread in cattle worldwide, causing important economic losses. Pathogenesis of the disease caused by BVDV is complex, as each BVDV strain has two biotypes: non-cytopathic (ncp) and cytopathic (cp). BVDV can cause a persistent latent infection and immune suppression if animals are infected with an ncp biotype during early gestation, followed by a subsequent infection of the cp biotype. The molecular mechanisms that underscore the complex disease etiology leading to immune suppression in cattle caused by BVDV are not well understood.
• Higgins, S. E., Ellestad, L. E., Trakooljul, N., McCarthy, F., Saliba, J., Cogburn, L. A., & Porter, T. E. (2010). Transcriptional and pathway analysis in the hypothalamus of newly hatched chicks during fasting and delayed feeding. BMC Genomics, 11(1).
  More info

  PMID: 20214824;PMCID: PMC2848243;Abstract: Background: The hypothalamus plays a central role in regulating appetite and metabolism. However, the gene networks within the hypothalamus that regulate feed intake and metabolism, and the effects of fasting on those pathways are not completely understood in any species. The present experiment evaluated global hypothalamic gene expression in newly hatched chicks using microarray analysis to elucidate genes and pathways regulated by feeding, fasting, and delayed feeding. Ten groups of chicks were sampled over four days post-hatch, including fed, fasted, and 48 h fasted followed by access to feed for 4 h, 24 h, and 48 h. Hypothalamic samples were collected for microarray analysis (n = 4). Expression patterns of selected genes were confirmed by quantitative real-time PCR. Pathway analysis of the microarray results predicted a network of genes involved in neuropeptide or neurotransmitter signaling. To confirm the functionality of this predicted gene network, hypothalamic neurons from fed and fasted chicks were isolated and cultured in the presence of neuropeptide Y, somatostatin, α-melanocyte stimulating hormone, norepinephrine, and L-phospho-serine. Results confirmed functional relationships among members of the predicted gene network. Moreover, the effects observed were dependant upon the nutritional state of the animals (fed vs. fasted).Results: Differences in gene expression (≥ 1.6 fold) were detected in 1,272 genes between treatments, and of those, 119 genes were significantly (P < 0.05) different. Pathway Miner analysis revealed that six genes (SSTR5, NPY5R, POMC, ADRB2, GRM8, and RLN3) were associated within a gene network. In vitro experiments with primary hypothalamic neurons confirmed that receptor agonists involved in this network regulated expression of other genes in the predicted network, and this regulation within the network was influenced by the nutritional status and age of the chick.Conclusions: Microarray analysis of the hypothalamus during different nutritional states revealed that many genes are differentially regulated. We found that functional interactions exist among six differentially regulated genes associated within a putative gene network from this experiment. Considering that POMC, an important gene in controlling metabolism, was central to this network, this gene network may play an important role in regulation of feeding and metabolism in birds. © 2010 Higgins et al; licensee BioMed Central Ltd.
• Higgins, S. E., Ellestad, L. E., Trakooljul, N., McCarthy, F., Saliba, J., Cogburn, L. A., & Porter, T. E. (2010). Transcriptional and pathway analysis in the hypothalamus of newly hatched chicks during fasting and delayed feeding. BMC genomics, 11, 162.
  More info

  The hypothalamus plays a central role in regulating appetite and metabolism. However, the gene networks within the hypothalamus that regulate feed intake and metabolism, and the effects of fasting on those pathways are not completely understood in any species. The present experiment evaluated global hypothalamic gene expression in newly hatched chicks using microarray analysis to elucidate genes and pathways regulated by feeding, fasting, and delayed feeding. Ten groups of chicks were sampled over four days post-hatch, including fed, fasted, and 48 h fasted followed by access to feed for 4 h, 24 h, and 48 h. Hypothalamic samples were collected for microarray analysis (n = 4). Expression patterns of selected genes were confirmed by quantitative real-time PCR. Pathway analysis of the microarray results predicted a network of genes involved in neuropeptide or neurotransmitter signaling. To confirm the functionality of this predicted gene network, hypothalamic neurons from fed and fasted chicks were isolated and cultured in the presence of neuropeptide Y, somatostatin, alpha-melanocyte stimulating hormone, norepinephrine, and L-phospho-serine. Results confirmed functional relationships among members of the predicted gene network. Moreover, the effects observed were dependent upon the nutritional state of the animals (fed vs. fasted).
• Manda, P., Freeman, M. G., Bridges, S. M., Jankun-Kelly, T. J., Nanduri, B., McCarthy, F. M., & Burgess, S. C. (2010). GOModeler--a tool for hypothesis-testing of functional genomics datasets. BMC bioinformatics, 11 Suppl 6, S29.
  More info

  Functional genomics technologies that measure genome expression at a global scale are accelerating biological knowledge discovery. Generating these high throughput datasets is relatively easy compared to the downstream functional modelling necessary for elucidating the molecular mechanisms that govern the biology under investigation. A number of publicly available 'discovery-based' computational tools use the computationally amenable Gene Ontology (GO) for hypothesis generation. However, there are few tools that support hypothesis-based testing using the GO and none that support testing with user defined hypothesis terms.Here, we present GOModeler, a tool that enables researchers to conduct hypothesis-based testing of high throughput datasets using the GO. GOModeler summarizes the overall effect of a user defined gene/protein differential expression dataset on specific GO hypothesis terms selected by the user to describe a biological experiment. The design of the tool allows the user to complement the functional information in the GO with his/her domain specific expertise for comprehensive hypothesis testing.
• Pechanova, O., Pechan, T., Ozkan, S., McCarthy, F. M., Williams, W. P., & Luthe, D. S. (2010). Proteome profile of the developing maize (Zea mays L.) rachis. Proteomics, 10(16), 3051-3055.
  More info

  PMID: 20662101;Abstract: In this study, we performed the first high-throughput proteomic analysis of developing rachis (cob) from maize genotype Mp313E. Using two proteomic approaches, 2-DE and 2-D LC, we identified 967 proteins. A 2-D proteome reference map was established. Functional classification of identified proteins revealed that proteins involved in various cellular metabolisms, response to stimulus and transport, were the most abundant. © 2010 WILEY-VCH Verlag GmbH & Co. KGaA.
• Pechanova, O., Pechan, T., Ozkan, S., McCarthy, F. M., Williams, W. P., & Luthe, D. S. (2010). Proteome profile of the developing maize (Zea mays L.) rachis. Proteomics, 10(16), 3051-5.
  More info

  In this study, we performed the first high-throughput proteomic analysis of developing rachis (cob) from maize genotype Mp313E. Using two proteomic approaches, 2-DE and 2-D LC, we identified 967 proteins. A 2-D proteome reference map was established. Functional classification of identified proteins revealed that proteins involved in various cellular metabolisms, response to stimulus and transport, were the most abundant.
• Rasaputra, K. S., Liyanage, R., Lay Jr., J. O., McCarthy, F. M., & Rath, N. C. (2010). Tibial dyschondroplasia-associated proteomic changes in chicken growth plate cartilage. Avian Diseases, 54(4), 1166-1171.
  More info

  PMID: 21313835;Abstract: Tibial dyschondroplasia (TD) is a poultry leg problem that affects the proximal growth plate of the tibia, preventing its transition to bone. To understand the disease-induced proteomic changes, we compared the protein extracts of cartilage from normal and TD-affected growth plates. TD was induced by feeding thiram to chickens 2 wk before tissue harvest. Proteins were extracted from whole tissues and from conditioned media (CM) prepared by incubating appropriate growth plate tissues in serum-free culture medium for 48 hr. The extracts were prefractionated to contain proteins ranging between 10 and 100 kD. Equal amounts of proteins were subjected to 2D gel electrophoresis with three individual samples per group. The gels were silver stained, and digital images were compared and analyzed with Melanie software to determine differentially expressed protein spots. On comparison of two sets of gels, 47 matching spots were detected in tissue extracts and 27 in CM extracts. Among the matching spots, 12 were determined to be down-regulated in tissue extracts (P ≤ 0.05) and two in CM extracts (P ≤ 0.05) of TD-affected growth plates. Altogether, 32 protein spots could be identified in both tissue and CM extracts by in-gel trypsin digestion, followed by peptide mass fingerprinting and mass spectrometry (MS)/MS fragmentation. The down-regulated proteins included alpha-enolase, G protein, origin recognition complex, peptidyl prolyl isomerase, calumenin, type II collagen precursor, and the expressed sequence tag pgm2n.pk014.f20, a protein with homology to human reticulocalbin-3 (RCN3). Most of the down-regulated proteins are associated with signal transduction, energy metabolism, and secretory functions that are integral to cell viability. Consistent with our earlier findings that the TD chondrocytes are nonviable, the current results suggest that thiram very likely interferes with basic metabolic functions of chondrocytes, leading to their death and, consequently, to the pathogenesis of TD. © American Association of Avian Pathologists 2010.
• van den Berg, B. H., McCarthy, F. M., Lamont, S. J., & Burgess, S. C. (2010). Re-annotation is an essential step in systems biology modeling of functional genomics data. PloS one, 5(5), e10642.
  More info

  One motivation of systems biology research is to understand gene functions and interactions from functional genomics data such as that derived from microarrays. Up-to-date structural and functional annotations of genes are an essential foundation of systems biology modeling. We propose that the first essential step in any systems biology modeling of functional genomics data, especially for species with recently sequenced genomes, is gene structural and functional re-annotation. To demonstrate the impact of such re-annotation, we structurally and functionally re-annotated a microarray developed, and previously used, as a tool for disease research. We quantified the impact of this re-annotation on the array based on the total numbers of structural- and functional-annotations, the Gene Annotation Quality (GAQ) score, and canonical pathway coverage. We next quantified the impact of re-annotation on systems biology modeling using a previously published experiment that used this microarray. We show that re-annotation improves the quantity and quality of structural- and functional-annotations, allows a more comprehensive Gene Ontology based modeling, and improves pathway coverage for both the whole array and a differentially expressed mRNA subset. Our results also demonstrate that re-annotation can result in a different knowledge outcome derived from previous published research findings. We propose that, because of this, re-annotation should be considered to be an essential first step for deriving value from functional genomics data.
• Bridges, S. M., Burgess, S. C., & McCarthy, F. M. (2009). Introduction to the proceedings of the Avian Genomics and Gene Ontology Annotation Workshop. BMC genomics, 10 Suppl 2, I1.
  More info

  The Avian Genomics Conference and Gene Ontology Annotation Workshop brought together researchers and students from around the world to present their latest research addressing the delivery of value from the billions of base-pairs of Archosaur sequence that have become available in the last few years. This editorial describes the conference itself and introduces the ten peer-reviewed manuscripts accepted for publications in the proceedings. These manuscripts address issues ranging from the poultry industry view of USDA genomics policy to the genomics of a wide variety of Archeosaur species including chicken, duck, alligator, and condors and their pathogens.
• Bright, L. A., Burgess, S. C., Chowdhary, B., Swiderski, C. E., & McCarthy, F. M. (2009). Structural and functional-annotation of an equine whole genome oligoarray. BMC bioinformatics, 10 Suppl 11, S8.
  More info

  The horse genome is sequenced, allowing equine researchers to use high-throughput functional genomics platforms such as microarrays; next-generation sequencing for gene expression and proteomics. However, for researchers to derive value from these functional genomics datasets, they must be able to model this data in biologically relevant ways; to do so requires that the equine genome be more fully annotated. There are two interrelated types of genomic annotation: structural and functional. Structural annotation is delineating and demarcating the genomic elements (such as genes, promoters, and regulatory elements). Functional annotation is assigning function to structural elements. The Gene Ontology (GO) is the de facto standard for functional annotation, and is routinely used as a basis for modelling and hypothesis testing, large functional genomics datasets.
• Burgess, S. C., Mccarthy, F. M., Konieczka, J. H., Burgess, S. C., & Berg, B. H. (2009). ArrayIDer: automated structural re-annotation pipeline for DNA microarrays.. BMC bioinformatics, 10(1), 30. doi:10.1186/1471-2105-10-30
  More info

  Systems biology modeling from microarray data requires the most contemporary structural and functional array annotation. However, microarray annotations, especially for non-commercial, non-traditional biomedical model organisms, are often dated. In addition, most microarray analysis tools do not readily accept EST clone names, which are abundantly represented on arrays. Manual re-annotation of microarrays is impracticable and so we developed a computational re-annotation tool (ArrayIDer) to retrieve the most recent accession mapping files from public databases based on EST clone names or accessions and rapidly generate database accessions for entire microarrays..We utilized the Fred Hutchinson Cancer Research Centre 13K chicken cDNA array - a widely-used non-commercial chicken microarray - to demonstrate the principle that ArrayIDer could markedly improve annotation. We structurally re-annotated 55% of the entire array. Moreover, we decreased non-chicken functional annotations by 2 fold. One beneficial consequence of our re-annotation was to identify 290 pseudogenes, of which 66 were previously incorrectly annotated..ArrayIDer allows rapid automated structural re-annotation of entire arrays and provides multiple accession types for use in subsequent functional analysis. This information is especially valuable for systems biology modeling in the non-traditional biomedical model organisms.
• Burt, D. W., Carrë, W., Fell, M., Law, A. S., Antin, P. B., Maglott, D. R., Weber, J. A., Schmidt, C. J., Burgess, S. C., & McCarthy, F. M. (2009). The Chicken Gene Nomenclature Committee report. BMC genomics, 10 Suppl 2, S5.
  More info

  Comparative genomics is an essential component of the post-genomic era. The chicken genome is the first avian genome to be sequenced and it will serve as a model for other avian species. Moreover, due to its unique evolutionary niche, the chicken genome can be used to understand evolution of functional elements and gene regulation in mammalian species. However comparative biology both within avian species and within amniotes is hampered due to the difficulty of recognising functional orthologs. This problem is compounded as different databases and sequence repositories proliferate and the names they assign to functional elements proliferate along with them. Currently, genes can be published under more than one name and one name sometimes refers to unrelated genes. Standardized gene nomenclature is necessary to facilitate communication between scientists and genomic resources. Moreover, it is important that this nomenclature be based on existing nomenclature efforts where possible to truly facilitate studies between different species. We report here the formation of the Chicken Gene Nomenclature Committee (CGNC), an international and centralized effort to provide standardized nomenclature for chicken genes. The CGNC works in conjunction with public resources such as NCBI and Ensembl and in consultation with existing nomenclature committees for human and mouse. The CGNC will develop standardized nomenclature in consultation with the research community and relies on the support of the research community to ensure that the nomenclature facilitates comparative and genomic studies.
• Buza, T. J., Kumar, R., Gresham, C. R., Burgess, S. C., & McCarthy, F. M. (2009). Facilitating functional annotation of chicken microarray data. BMC bioinformatics, 10 Suppl 11, S2.
  More info

  Modeling results from chicken microarray studies is challenging for researchers due to little functional annotation associated with these arrays. The Affymetrix GenChip chicken genome array, one of the biggest arrays that serve as a key research tool for the study of chicken functional genomics, is among the few arrays that link gene products to Gene Ontology (GO). However the GO annotation data presented by Affymetrix is incomplete, for example, they do not show references linked to manually annotated functions. In addition, there is no tool that facilitates microarray researchers to directly retrieve functional annotations for their datasets from the annotated arrays. This costs researchers amount of time in searching multiple GO databases for functional information.
• Gaudet, P., Chisholm, R., Berardini, T., Dimmer, E., Engel, S. R., Fey, P., Hill, D. P., Howe, D., Hu, J. C., Huntley, R., Khodiyar, V. K., Kishore, R., Donghui, L. i., Lovering, R. C., McCarthy, F., Li, N. i., Petri, V., Siegele, D. A., Tweedie, S., , Auken, K. V., et al. (2009). The gene ontology's reference genome project: A unified framework for functional annotation across species. PLoS Computational Biology, 5(7).
  More info

  Abstract: The Gene Ontology (GO) is a collaborative effort that provides structured vocabularies for annotating the molecular function, biological role, and cellular location of gene products in a highly systematic way and in a species-neutral manner with the aim of unifying the representation of gene function across different organisms. Each contributing member of the GO Consortium independently associates GO terms to gene products from the organism(s) they are annotating. Here we introduce the Reference Genome project, which brings together those independent efforts into a unified framework based on the evolutionary relationships between genes in these different organisms. The Reference Genome project has two primary goals: to increase the depth and breadth of annotations for genes in each of the organisms in the project, and to create data sets and tools that enable other genome annotation efforts to infer GO annotations for homologous genes in their organisms. In addition, the project has several important incidental benefits, such as increasing annotation consistency across genome databases, and providing important improvements to the GO's logical structure and biological content. © 2009 Gaudet et al.
• McCarthy, F. M., Mahony, T. J., Parcells, M. S., & Burgess, S. C. (2009). Understanding animal viruses using the Gene Ontology. Trends in microbiology, 17(7), 328-35.
  More info

  Understanding the effects of viral infection has typically focused on specific virus-host interactions such as tissue tropism, immune responses and histopathology. However, modeling viral pathogenesis requires information about the functions of gene products from both virus and host, and how these products interact. Recent developments in the functional annotation of genomes using Gene Ontology (GO) and in modeling functional interactions among gene products, together with an increased interest in systems biology, provide an excellent opportunity to generate global interaction models for viral infection. Here, we review how the GO is being used to model viral pathogenesis, with a focus on animal viruses.
• Burgess, S. C., Wang, N., Mccarthy, F. M., Buza, T. J., Burgess, S. C., & Bridges, S. M. (2008). Gene Ontology annotation quality analysis in model eukaryotes.. Nucleic acids research, 36(2), e12. doi:10.1093/nar/gkm1167
  More info

  Functional analysis using the Gene Ontology (GO) is crucial for array analysis, but it is often difficult for researchers to assess the amount and quality of GO annotations associated with different sets of gene products. In many cases the source of the GO annotations and the date the GO annotations were last updated is not apparent, further complicating a researchers' ability to assess the quality of the GO data provided. Moreover, GO biocurators need to ensure that the GO quality is maintained and optimal for the functional processes that are most relevant for their research community. We report the GO Annotation Quality (GAQ) score, a quantitative measure of GO quality that includes breadth of GO annotation, the level of detail of annotation and the type of evidence used to make the annotation. As a case study, we apply the GAQ scoring method to a set of diverse eukaryotes and demonstrate how the GAQ score can be used to track changes in GO annotations over time and to assess the quality of GO annotations available for specific biological processes. The GAQ score also allows researchers to quantitatively assess the functional data available for their experimental systems (arrays or databases).
• Robinson, K. E., Meers, J., Gravel, J. L., McCarthy, F. M., & Mahony, T. J. (2008). The essential and non-essential genes of Bovine herpesvirus 1. Journal of General Virology, 89(11), 2851-2863.
  More info

  PMID: 18931083;Abstract: Bovine herpesvirus 1 (BoHV-1) is an economically important pathogen of cattle associated with respiratory and reproductive disease. To further develop BoHV-1 as a vaccine vector, a study was conducted to identify the essential and non-essential genes required for in vitro viability. Randominsertion mutagenesis utilizing a Tn5 transposition system and targeted gene deletion were employed to construct gene disruption and gene deletion libraries, respectively, of an infectious clone of BoHV-1. Transposon insertion position and confirmation of gene deletion were determined by direct sequencing. The essential or non-essential requirement of either transposed or deleted open reading frames (ORFs) was assessed by transfection of respective BoHV-1 DNA into host cells. Of the 73 recognized ORFs encoded by the BoHV-1 genome, 33 were determined to be essential and 36 to be non-essential for virus viability in cell culture; determining the requirement of the two dual copy ORFs was inconclusive. The majority of ORFs were shown to conform to the in vitro requirements of BoHV-1 homologues encoded by human herpesvirus 1 (HHV-1). However, ORFs encoding glycoprotein K (UL53), regulatory, membrane, tegument and capsid proteins (UL54, UL49.5, UL49, UL35, UL20, UL16 and UL7) were shown to differ in requirement when compared to HHV-1-encoded homologues. © 2008 DP&F.
• Burgess, S. C., Mccarthy, F. M., Burgess, S. C., & Bridges, S. M. (2007). GOing from functional genomics to biological significance.. Cytogenetic and genome research, 117(1-4), 278-87. doi:10.1159/000103189
  More info

  The chicken genome is sequenced and this, together with microarray and other functional genomics technologies, makes post-genomic research possible in the chicken. At this time, however, such research is hindered by a lack of genomic structural and functional annotations. Bio-ontologies have been developed for different annotation requirements, as well as to facilitate data sharing and computational analysis, but these are not yet optimally utilized in the chicken. Here we discuss genomic annotation and bio-ontologies. We focus specifically on the Gene Ontology (GO), chicken GO annotations and how these can facilitate functional genomics in the chicken. The GO is the most developed and widely used bio-ontology. It is the de facto standard for functional annotation. Despite its critical importance in analyzing microarray and other functional genomics data, relatively few chicken gene products have any GO annotation. When these are available, the average quality of chicken gene products annotations (defined using evidence code weight and annotation depth) is much less than in mouse. Moreover, tools allowing chicken researchers to easily and rapidly use the GO are either lacking or hard to use. To address all of these problems we developed ChickGO and AgBase. Chicken GO annotations are provided by complementary work at MSU-AgBase and EBI-GOA. The GO tools pipeline at AgBase uses GO to derive functional and biological significance from microarray and other functional genomics data. Not only will improved genomic annotation and tools to use these annotations benefit the chicken research community but they will also facilitate research in other avian species and comparative genomics.
• Burgess, S. C., Mccarthy, F. M., Buza, T. J., & Burgess, S. C. (2007). Experimental-confirmation and functional-annotation of predicted proteins in the chicken genome.. BMC genomics, 8(1), 425. doi:10.1186/1471-2164-8-425
  More info

  The chicken genome was sequenced because of its phylogenetic position as a non-mammalian vertebrate, its use as a biomedical model especially to study embryology and development, its role as a source of human disease organisms and its importance as the major source of animal derived food protein. However, genomic sequence data is, in itself, of limited value; generally it is not equivalent to understanding biological function. The benefit of having a genome sequence is that it provides a basis for functional genomics. However, the sequence data currently available is poorly structurally and functionally annotated and many genes do not have standard nomenclature assigned..We analysed eight chicken tissues and improved the chicken genome structural annotation by providing experimental support for the in vivo expression of 7,809 computationally predicted proteins, including 30 chicken proteins that were only electronically predicted or hypothetical translations in human. To improve functional annotation (based on Gene Ontology), we mapped these identified proteins to their human and mouse orthologs and used this orthology to transfer Gene Ontology (GO) functional annotations to the chicken proteins. The 8,213 orthology-based GO annotations that we produced represent an 8% increase in currently available chicken GO annotations. Orthologous chicken products were also assigned standardized nomenclature based on current chicken nomenclature guidelines..We demonstrate the utility of high-throughput expression proteomics for rapid experimental structural annotation of a newly sequenced eukaryote genome. These experimentally-supported predicted proteins were further annotated by assigning the proteins with standardized nomenclature and functional annotation. This method is widely applicable to a diverse range of species. Moreover, information from one genome can be used to improve the annotation of other genomes and inform gene prediction algorithms.
• Burgess, S. C., Shack, L. A., Sagirkaya, H., Peddinti, D., Nanduri, B., Memili, E., Mccarthy, F. M., & Burgess, S. C. (2007). Bovine germinal vesicle oocyte and cumulus cell proteomics.. Reproduction (Cambridge, England), 133(6), 1107-20. doi:10.1530/rep-06-0149
  More info

  Germinal vesicle (GV) breakdown is fundamental for maturation of fully grown, developmentally competent, mammalian oocytes. Bidirectional communication between oocytes and surrounding cumulus cells (CC) is essential for maturation of a competent oocyte. However, neither the factors involved in this communication nor the mechanisms of their actions are well defined. Here, we define the proteomes of GV oocytes and their surrounding CC, including membrane proteins, using proteomics in a bovine model. We found that 4395 proteins were expressed in the CC and 1092 proteins were expressed in oocytes. Further, 858 proteins were common to both the CC and the oocytes. This first comprehensive proteome analysis of bovine oocytes and CC not only provides a foundation for signaling and cell physiology at the GV stage of oocyte development, but are also valuable for comparative studies of other stages of oocyte development at the molecular level. Furthermore, some of these proteins may represent molecular biomarkers for developmental potential of oocytes.
• Burgess, S. C., Williams, W. P., Wang, N., Mccarthy, F. M., Magee, G. B., Luthe, D. S., Burgess, S. C., & Bridges, S. M. (2007). AgBase: a unified resource for functional analysis in agriculture.. Nucleic acids research, 35(Database issue), D599-603. doi:10.1093/nar/gkl936
  More info

  Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessible, public resource 'AgBase' (www.agbase.msstate.edu). We have improved the structural annotation of agriculturally important genomes by experimentally confirming the in vivo expression of electronically predicted proteins and by proteogenomic mapping. Proteogenomic data are available from the AgBase proteogenomics link. We contribute Gene Ontology (GO) annotations and we provide a two tier system of GO annotations for users. The 'GO Consortium' gene association file contains the most rigorous GO annotations based solely on experimental data. The 'Community' gene association file contains GO annotations based on expert community knowledge (annotations based directly from author statements and submitted annotations from the community) and annotations for predicted proteins. We have developed two tools for proteomics analysis and these are freely available on request. A suite of tools for analyzing functional genomics datasets using the GO is available online at the AgBase site. We encourage and publicly acknowledge GO annotations from researchers and provide an online mechanism for agricultural researchers to submit requests for GO annotations.
• Nanduri, B., & McCarthy, F. M. (2007). AgBase: A tool for systems biology in agricultural species. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 2.
  More info

  Abstract: Genome sequences are available for several agriculturally important species (both eukaryotic and prokaryotic) and genome sequences and '-omics' technologies show promise for translating genomics data into increased production efficiency, sustainable agriculture and advances for the bio-economy. However, predictive and preventative systems modelling depends on biological information and not just genomics data. Systems biology approaches allow the integration of various '-omics' data to produce valuable models to understand complex biological systems. The two approaches for doing systems biology are bottom-up modelling and top-down modelling. We focus on top-down systems biology, which entails four fundamental and overlapping steps: the enumeration of the system's parts, elucidation of interactions between these parts, modelling regulation of these interaction networks and generating predictive and dynamic models. Systems biology in agriculturally important species is truly possible only when all the elements required for systems biology become available for these species. The AgBase databases provide critical components for systems biology modelling in agriculture as they provide experimentally based structural annotation of genomic sequences and highly curated functional annotations of gene products using Gene Ontology (GO). The GO underpins network analysis and can also be used to model physiological function in biological systems. Like the '-omics' data being modelled, agricultural databases (and agricultural researchers) need to be better integrated to support the multidisciplinary research required for systems biology. © CABI Publishing 2007.
• Burgess, S. C., Williams, W. P., Wang, N., Nanduri, B., Mccarthy, F. M., Magee, G. B., Luthe, D. S., Lawrence, M. L., Hill, D. P., Dolan, M. E., Camon, E. B., Burgess, S. C., Bridges, S. M., & Barrell, D. G. (2006). AgBase: a functional genomics resource for agriculture.. BMC genomics, 7(1), 229. doi:10.1186/1471-2164-7-229
  More info

  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..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..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.
• Lee, S. -., Pharr, G. T., Cooksey, A. M., McCarthy, F. M., Boyd, B. L., & Pinchuk, L. M. (2006). Differential detergent fractionation for non-electrophoretic bovine peripheral blood monocyte proteomics reveals proteins involved in professional antigen presentation. Developmental and Comparative Immunology, 30(11), 1070-1083.
  More info

  PMID: 16566999;Abstract: Professional antigen presenting cells (APC), dendritic cells (DC) and their myeloid progenitors, monocytes/macrophages are critical controllers of innate and adaptive immunity. Here we show that differential detergent fractionation (DDF) analysis of bovine monocytes reveals proteins related to antigen pattern recognition, uptake and presentation to immunocompetent lymphocytes. We identify 53 bovine proteins involved in immune function of professional APC. In particular, 13 adhesion molecules, three toll-like receptors (TLR1, 6 and 8), three antigen uptake-related proteins (including mannose receptor [MR] precursor), and eight actin-like proteins involved in active endocytosis were identified. In addition, MHC class I and II-related proteins, cytokines, active substances and growth factors have been identified. We conclude that the DDF approach can provide interpretable and meaningful functional information concerning protein expression profiles associated with monocyte activation, transformation into macrophages and/or immature DC, and maturation of monocyte-derived DC in the presence of multiple bovine pathogens. © 2006 Elsevier Ltd. All rights reserved.
• Burgess, S. C., Pharr, G. T., Mccarthy, F. M., Koter, M. D., Burgess, S. C., & Berg, B. H. (2005). Differential detergent fractionation for non-electrophoretic eukaryote cell proteomics.. Journal of proteome research, 4(2), 316-24. doi:10.1021/pr049842d
  More info

  Differential detergent fractionation (DDF), which relies on detergents to sequentially extract proteins from eukaryotic cells, has been used to increase proteome coverage of 2D-PAGE. Here, we used DDF extraction in conjunction with the nonelectrophoretic proteomics method of liquid chromatography and electrospray ionization tandem mass spectrometry. We demonstrate that DDF can be used with 2D-LC ESI MS2 for comprehensive cellular proteomics, including a large proportion of membrane proteins. Compared to some published methods designed to isolate membrane proteins specifically, DDF extraction yields comprehensive proteomes which include twice as many membrane proteins. Two-thirds of these membrane proteins have more than one trans-membrane domain. Since DDF separates proteins based upon their physicochemistry and subcellular localization, this method also provides data useful for functional genome annotation. As more genome sequences are completed, methods which can aid in functional annotation will become increasingly important.
• Mahony, T. J., McCarthy, F. M., Gravel, J. L., & Young, P. L. (2005). Construction of a gene inactivation library for Bovine herpesvirus 1 using infectious clone technology.. Methods in molecular biology (Clifton, N.J.), 292, 387-400.
  More info

  PMID: 15507722;Abstract: The application of infectious clone technology to herpesvirus biology has revolutionized the study of these viruses. Previously the ability to manipulate these large DNA viruses was limited to methods dependent on homologous recombination in mammalian cells. However, the construction of herpesvirus infectious clones using bacterial artificial chromosome vectors has permitted the application of powerful bacterial genetics for the manipulation of these viruses. A method is described for the construction and characterization of a gene inactivation library of Bovine herpesvirus 1 using an infectious clone. The method utilizes transposon-mediated gene inactivation, which permits gene inactivation without any prior knowledge of the viral genomic sequence. Furthermore, as the genetic manipulation is performed in bacteria the inactivation of those viral genes that are essential for viral replication is also possible. The method described here can be readily applied to any herpesvirus clone and provides the tools for precise characterization of all the genes contained within a herpesvirus genome.
• Mahony, T. J., McCarthy, F. M., Gravel, J. L., Corney, B., Young, P. L., & Vilcek, S. (2005). Genetic analysis of bovine viral diarrhoea viruses from Australia. Veterinary Microbiology, 106(1-2), 1-6.
  More info

  PMID: 15737468;Abstract: Eighty-nine bovine viral diarrhoea viruses (BVDV) from Australia have been genetically typed by sequencing of the 5′ untranslated region (5′-UTR) and for selected isolates the Npro region of the viral genome. Phylogenetic reconstructions indicated that all of the samples examined clustered within the BVDV type 1 genotype. Of the 11 previously described genetic groups of BVDV-1, 87 of the samples examined in this study clustered with the BVDV-1c, while two samples clustered with the BVDV-1a. Based on these analyses there appears to be limited genetic variation within the Australian BVDV field isolates. In addition, the phylogenetic reconstructions indicate that the clustering of Australian BVDV in the phylogenetic trees is not a result of geographic isolation. © 2005 Elsevier B.V. All rights reserved.
• Mahony, T. J., McCarthy, F. M., Gravel, J. L., & Young, P. L. (2003). Rapid and efficient construction of recombinant bovine herpesvirus 1 genomes. Journal of Virological Methods, 107(2), 269-274.
  More info

  PMID: 12505643;Abstract: Bovine herpesvirus 1 (BoHV-1) is an important pathogen of cattle. Recombinant bovine herpesvirus 1 viruses (rBoHV) have been studied extensively as potential vaccines for BoHV-1 associated diseases. A method is described which advances protocols used currently for constructing rBoHV by producing recombinant viruses free of parent virus. The method, restriction endonuclease mediated recombination (REMR), utilises a unique NsiI site in the BoHV-1 genome. Following NsiI digestion the two genomic fragments are prevented from recombining by dephosphorylation. However, when the genomic fragments are co-transfected into a susceptible cell-line with a third DNA fragment (DNA bridge), which encodes DNA homologous to the digested viral termini, the three DNA molecules are able to undergo homologous recombination and produce infectious BoHV-1. During the recombination process foreign DNA within the DNA bridge is incorporated into the BoHV-1 genome, producing rBoHV. In the absence of the DNA bridge virus reconstitution does not occur thus eliminating contamination by the nonrecombinant parent virus. As REMR used an NsiI site occurring naturally in the BoHV-1 genome it can be used for the insertion of foreign DNA into the genome without any prior modifications. REMR could also be applied to any herpesvirus for which the genome sequence is known. Crown Copyright © 2002 Published by Elsevier Science B.V. All rights reserved.
• Mahony, T. J., McCarthy, F. M., Gravel, J. L., West, L., & Young, P. L. (2002). Construction and manipulation of an infectious clone of the bovine herpesvirus 1 genome maintained as a bacterial artificial chromosome. Journal of Virology, 76(13), 6660-6668.
  More info

  PMID: 12050379;PMCID: PMC136292;Abstract: The complete genome of bovine herpesvirus 1 (BoHV-1) strain V155 has been cloned as a bacterial artificial chromosome (BAC). Following electroporation into Escherichia coli strain DH10B, the BoHV-1 BAC was stably propagated over multiple generations of its host. BAC DNA recovered from DH10B cells and transfected into bovine cells produced a cytopathic effect which was indistinguishable from that of the parent virus. Analysis of the replication kinetics of the viral progeny indicated that insertion of the BAC vector into the thymidine kinase gene did not affect viral replication. Specific manipulation of the BAC was demonstrated by deleting the gene encoding glycoprotein E by homologous recombination in DH10B cells facilitated by GET recombination. These studies illustrate that the propagation and manipulation of herpesviruses in bacterial systems will allow for rapid and accurate characterization of BoHV-1 genes. In turn, this will allow for the full utilization of BoHV-1 as a vaccine vector.
• Mahony, T. J., Mccarthy, F. M., Gravel, J. L., Clark, K. L., Wilks, C., Mackenzie, J. S., & Young, P. R. (1999). Genetic analysis of Australian bovine viral diarrhoea viruses and bovine herpesviruses. Vet Microbiol.
• McCarthy, F. M., Smith, G. A., & Mattick, J. S. (1999). Molecular characterisation of Australian bovine enteroviruses. Veterinary Microbiology, 68(1-2), 71-81.
  More info

  PMID: 10501163;Abstract: In this study we report the full length (7.4kb) sequence of two Australian bovine enterovirus (BEV) isolates, K2577 and SL305 and the partial sequence of a third isolate, 66/27, which are the prototypes of the three major serological groups of BEV in Australia. Australian BEV isolates have not previously been related to the international classification of BEV into the major serotypes BEV-1 and BEV-2. The sequences of the three representative Australian isolates were compared to the full length sequence of a Northern Ireland isolate (VG527) classified as BEV-1, as well as two partial sequences of isolates from the United States and the United Kingdom classified as BEV-2. All three Australian isolates were classified as BEV-1 on the basis of closer nucleotide and amino acid similarity to the 5'-UTR and capsid proteins of VG527 than to the BEV-2 isolates (79-81% versus 76-77% nucleotide identity in the 5-UTR, and 86-98% versus 65-77% amino acid identity in the capsid proteins). These results indicate that most if not all Australian BEV are BEV-1. The remainder of the genome, which encodes non-structural proteins involved in viral replication, showed high sequence homology as has been observed among such genes in other enteroviruses. A system for full-length amplification of BEV isolates was also developed and the K2577 isolate was cloned to obtain a full-length, infectious DNA copy of the BEV genome. When RNA transcripts of BEV amplification products were transfected into MDBK cells infectious particles were produced. These virus particles were identical to the original virus isolates. This system can be used as a basis for the development of BEV-vectored vaccines as well in further molecular studies of bovine enteroviruses. Copyright (C) 1999 Elsevier Science B.V.
• West, L., Mahony, T., McCarthy, F., Watanabe, J., Hewitt, D., & Hansford, S. (1999). Primary cell cultures isolated from Penaeus monodon prawns. Methods in Cell Science, 21(4), 219-223.
  More info

  PMID: 10627675;Abstract: We have devised a cell culture system for Penaeus monodon prawn cells that uses a defined synthetic medium. Organs were removed from adult prawns ranging in size from 13-19 cm rostrum-to-telson length. Cultures consisted of either a blend of hematopoietic and lymphoid cells or ovarian cells. The cells divide rapidly in culture, doubling on average once per week for 5 to 6 weeks. These cultures continue to survive for at least 5 months but the rates of cell division are low after the first 5-6 weeks. In the literature, unicellular eukaryotic marine organisms such as chytrids may contaminate marine cell cultures. In some cases these eukaryotic contaminants may be difficult to distinguish from prawn cells unless detailed ultrastructure or characteristic developmental stages such as zoospores can be observed. Alternatively, we prepared molecular probes from repeated DNA sequences 100-400 bp in length in the P. monodon genome. These species-specific probes were hybridised to genomic DNA from cell culture to confirm proliferation of P. monodon cells in our cultures.
• Barendse, W., Armitage, S. M., Kossarek, L. M., Shalom, A., Kirkpatrick, B. W., Ryan, A. M., Clayton, D., Li, L., Neibergs, H. L., Zhang, N., Grosse, W. M., Weiss, J., Creighton, P., McCarthy, F., Ron, M., Teale, A. J., Fries, R., McGraw, R. A., Moore, S. S., , Georges, M., et al. (1994). A genetic linkage map of the bovine genome. Nature Genetics, 6(3), 227-235.
  More info

  PMID: 8012383;Abstract: A cattle genetic linkage map was constructed which marks about 90% of the expected length of the cattle genome. Over 200 DNA polymorphisms were genotyped in cattle families which comprise 295 individuals in full sibling pedigrees. One hundred and seventy-one loci were found linked to one other locus. Twenty nine of the 30 chromosome pairs are represented by at least one of the 36 linkage groups. Less than a 50 cM difference was found in the male and female genetic maps. The conserved loci on this map show as many differences in gene order compared to humans as is found between humans and mice. The conservation is consistent with the patterns of karyotypic evolution found in the rodents, primates and artiodactyls. This map will be important for localizing quantitative trait loci and provides a basis for further mapping.
• Moore, S. S., Byrne, K., Berger, K. T., Barendse, W., McCarthy, F., Womack, J. E., & Hetzel, D. J. (1994). Characterization of 65 bovine microsatellites. Mammalian Genome, 5(2), 84-90.
  More info

  PMID: 8180478;Abstract: Microsatellites or simple sequence repeat (SSR) polymorphisms are used widely in the construction of linkage maps in many species. High levels of polymorphism coupled with the ease of analysis of the polymerase chain reaction (PCR) have resulted in this type of maker being one of the most widely used for genetic analysis. In this paper we describe 58 polymorphic bovine microsatellites that were isolated from insert size selected bovine genomic libraries. Primer sequences, number of alleles, and heterozygosity levels in cattle reference families are reported. Chromosomal locations for 47 of these microsatellites as well as for 7 previously described systems derived from entries in the Genbank or EMBL databases have been determined. The markers map to 24 syntenic or chromosomal locations. Polymorphic bovine microsatellites were estimated to occur, on average, every 320 kb, and there is no evidence of clustering in the genome. Thirty of the bovine-derived microsatellite systems gave specific and polymorphic products in sheep, adding to the number of useful markers in that species. © 1994 Springer-Verlag New York Inc.

Proceedings Publications

• Kelly, A., Bidwell, C., Camacho, L., McCarthy, F., & Limesand, S. (2016). Transcriptome Expression Profiles Identify Increased Metabolic Capacity in Adipose Tissue from Fetal Sheep with Intrauterine Growth Restriction.. In REPRODUCTIVE SCIENCES, 23.
• Smith, K. E., Kelly, A. C., VVeber, C., Min, C., Smith, B., McCarthy, F., Steyn, L. V., Badarinarayana, V., Strop, P., Lynch, R. M., & others, . (2015). ASSESSMENT OF THE VIABILITY, FUNCTION, AND TRANSCRIPTOME OF HUMAN ISLETS FOLLOWING ACUTE ISCHEMIC EXPOSURE.. In TRANSPLANTATION, 99.

Presentations

• McCarthy, F. M., Cooksey, A. M., Gresham, C. C., Pendarvis, K., & Burgess, S. C. (2013, January). Expanding Genomic Annotation Resources for Poultry.. Poultry Workshop, Plant and Animal Genome XXI. San Diego, California..
• McCarthy, F. (2012, July). From data to function: resources for modeling poultry genomics data. Poultry Science Association Annual Meeting. Athens, Georgia.
• McCarthy, F., Schmidt, C., Shanker, V., & Burgess, S. (2012). Enabling functional and comparative analysis of genomic data sets for agriculture. Comparative & Functional Genomics Workshop, 33rd International Society for Animal Genetics Conference. Cairns, Australia: International Society for Animal Genetics.

Poster Presentations

• McCarthy, F., Cooksey, A., Pendarvis, K., Gresham, C., & Burgess, S. (2012, November). Chickspress: a compendium of chicken tissue expression. 7th International Chick Meeting. Nagoya, Japan.

Others

• Zhang, G., Li, C., Li, Q., Li, B., Larkin, D. M., Lee, C., Storz, J. F., Antunes, A., Greenwold, M. J., Meredith, R. W., Ödeen, A., Cui, J., Zhou, Q., Xu, L., Pan, H., Wang, Z., Jin, L., Zhang, P., Hu, H., , Yang, W., et al. (2014, Dec). Comparative genomics reveals insights into avian genome evolution and adaptation. Science (New York, N.Y.).
  More info

  Birds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields. We explored bird macroevolution using full genomes from 48 avian species representing all major extant clades. The avian genome is principally characterized by its constrained size, which predominantly arose because of lineage-specific erosion of repetitive elements, large segmental deletions, and gene loss. Avian genomes furthermore show a remarkably high degree of evolutionary stasis at the levels of nucleotide sequence, gene synteny, and chromosomal structure. Despite this pattern of conservation, we detected many non-neutral evolutionary changes in protein-coding genes and noncoding regions. These analyses reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits.
• St John, J. A., Braun, E. L., Isberg, S. R., Miles, L. G., Chong, A. Y., Gongora, J., Dalzell, P., Moran, C., Bed'hom, B., Abzhanov, A., Burgess, S. C., Cooksey, A. M., Castoe, T. A., Crawford, N. G., Densmore, L. D., Drew, J. C., Edwards, S. V., Faircloth, B. C., Fujita, M. K., , Greenwold, M. J., et al. (2012). Sequencing three crocodilian genomes to illuminate the evolution of archosaurs and amniotes. Genome biology.
  More info

  The International Crocodilian Genomes Working Group (ICGWG) will sequence and assemble the American alligator (Alligator mississippiensis), saltwater crocodile (Crocodylus porosus) and Indian gharial (Gavialis gangeticus) genomes. The status of these projects and our planned analyses are described.