Structural and functional-annotation of an equine whole genome oligoarray

<p>Abstract</p> <p>Background</p> <p>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 <it>de facto </it>standard for functional annotation, and is routinely used as a basis for modelling and hypothesis testing, large functional genomics datasets.</p> <p>Results</p> <p>An Equine Whole Genome Oligonucleotide (EWGO) array with 21,351 elements was developed at Texas A&M University. This 70-mer oligoarray was designed using the approximately 7× assembled and annotated sequence of the equine genome to be one of the most comprehensive arrays available for expressed equine sequences. To assist researchers in determining the biological meaning of data derived from this array, we have structurally annotated it by mapping the elements to multiple database accessions, including UniProtKB, Entrez Gene, NRPD (Non-Redundant Protein Database) and UniGene. We next provided GO functional annotations for the gene transcripts represented on this array. Overall, we GO annotated 14,531 gene products (68.1% of the gene products represented on the EWGO array) with 57,912 annotations. GAQ (GO Annotation Quality) scores were calculated for this array both before and after we added GO annotation. The additional annotations improved the <it>meanGAQ </it>score 16-fold. This data is publicly available at <it>AgBase </it><url>http://www.agbase.msstate.edu/</url>.</p> <p>Conclusion</p> <p>Providing additional information about the public databases which link to the gene products represented on the array allows users more flexibility when using gene expression modelling and hypothesis-testing computational tools. Moreover, since different databases provide different types of information, users have access to multiple data sources. In addition, our GO annotation underpins functional modelling for most gene expression analysis tools and enables equine researchers to model large lists of differentially expressed transcripts in biologically relevant ways.</p

Genes and regulatory mechanisms associated with experimentally-induced bovine respiratory disease identified using supervised machine learning methodology

AbstractBovine respiratory disease (BRD) is a multifactorial disease involving complex host immune interactions shaped by pathogenic agents and environmental factors. Advancements in RNA sequencing and associated analytical methods are improving our understanding of host response related to BRD pathophysiology. Supervised machine learning (ML) approaches present one such method for analyzing new and previously published transcriptome data to identify novel disease-associated genes and mechanisms. Our objective was to apply ML models to lung and immunological tissue datasets acquired from previous clinical BRD experiments to identify genes that classify disease with high accuracy. Raw mRNA sequencing reads from 151 bovine datasets (n = 123 BRD, n = 28 control) were downloaded from NCBI-GEO. Quality filtered reads were assembled in a HISAT2/Stringtie2 pipeline. Raw gene counts for ML analysis were normalized, transformed, and analyzed with MLSeq, utilizing six ML models. Cross-validation parameters (fivefold, repeated 10 times) were applied to 70% of the compiled datasets for ML model training and parameter tuning; optimized ML models were tested with the remaining 30%. Downstream analysis of significant genes identified by the top ML models, based on classification accuracy for each etiological association, was performed within WebGestalt and Reactome (FDR ≤ 0.05). Nearest shrunken centroid and Poisson linear discriminant analysis with power transformation models identified 154 and 195 significant genes for IBR and BRSV, respectively; from these genes, the two ML models discriminated IBR and BRSV with 100% accuracy compared to sham controls. Significant genes classified by the top ML models in IBR (154) and BRSV (195), but not BVDV (74), were related to type I interferon production and IL-8 secretion, specifically in lymphoid tissue and not homogenized lung tissue. Genes identified in Mannheimia haemolytica infections (97) were involved in activating classical and alternative pathways of complement. Novel findings, including expression of genes related to reduced mitochondrial oxygenation and ATP synthesis in consolidated lung tissue, were discovered. Genes identified in each analysis represent distinct genomic events relevant to understanding and predicting clinical BRD. Our analysis demonstrates the utility of ML with published datasets for discovering functional information to support the prediction and understanding of clinical BRD.</jats:p

Hematological and gene co-expression network analyses of high-risk beef cattle defines immunological mechanisms and biological complexes involved in bovine respiratory disease and weight gain

AbstractBovine respiratory disease (BRD), the leading disease complex in beef cattle production systems, remains highly elusive regarding diagnostics and disease prediction. Previous research has employed cellular and molecular techniques to describe hematological and gene expression variation that coincides with BRD development. Here, we utilized weighted gene co-expression network analysis (WGCNA) to leverage total gene expression patterns from cattle at arrival and generate hematological and clinical trait associations to describe mechanisms that may predict BRD development.Gene expression counts of previously published RNA-Seq data from 23 cattle (2017; n=11 Healthy, n=12 BRD) were used to construct gene co-expression modules and correlation patterns with complete blood count (CBC) and clinical datasets. Modules were further evaluated for cross-populational preservation of expression with RNA-Seq data from 24 cattle in an independent population (2019; n=12 Healthy, n=12 BRD). Genes within well-preserved modules were subject to functional enrichment analysis for significant Gene Ontology terms and pathways. Genes which possessed high module membership and association with BRD development, regardless of module preservation (“hub genes”), were utilized for protein-protein physical interaction network and clustering analyses.Five well-preserved modules of co-expressed genes were identified. One module (“steelblue”), involved in alpha-beta T-cell complexes and Th2-type immunity, possessed significant correlation with increased erythrocytes, platelets, and BRD development. One module (“purple”), involved in mitochondrial metabolism and rRNA maturation, possessed significant correlation with increased eosinophils, fecal egg count per gram, and weight gain over time. Fifty-two interacting hub genes, stratified into 11 clusters, may possess transient function involved in BRD development not previously described in literature. This study identifies co-expressed genes and coordinated mechanisms associated with BRD, which necessitates further investigation in BRD-prediction research.Author SummaryBovine respiratory disease (BRD), the leading disease in beef cattle, is a highly dynamic disease complex. Through simultaneous sequencing of thousands of genes active in the blood of cattle at arrival, we pursued the co-expression patterns of these genes to evaluate associations with BRD development and severity overtime. This approach allows for a better understanding of gene expression active in cattle at arrival, and the discovery of new molecules and biological complexes that may predict BRD before the onset of clinical signs. Our work provides evidence that genes related to T-cells, a type of immune cell, are strongly co-expressed when cattle arrive to beef production system, and correlate with increased red blood cell (RBC) factors and BRD development. Further analysis shows that genes involved in cellular energy production and the respiratory electron transport are strongly co-expressed when cattle arrive to beef production system, and correlate with increased eosinophils, a type of immune cell, and weight gain overtime. Additionally, using genes which strongly correlate with BRD development and severity overtime, we identify a novel protein interaction complex that may drive future research for discovering new ways to manage and treat BRD in beef cattle.</jats:sec

Effect of a syringe aspiration technique versus a mechanical suction technique and use of N-butylscopolammonium bromide on the quantity and quality of bronchoalveolar lavage fluid samples obtained from horses with the summer pasture endophenotype of equine asthma

Abstract OBJECTIVE To evaluate the effect of 2 bronchoalveolar lavage (BAL) sampling techniques and the use of N-butylscopolammonium bromide (NBB) on the quantity and quality of BAL fluid (BALF) samples obtained from horses with the summer pasture endophenotype of equine asthma. ANIMALS 8 horses with the summer pasture endophenotype of equine asthma. PROCEDURES BAL was performed bilaterally (right and left lung sites) with a flexible videoendoscope passed through the left or right nasal passage. During lavage of the first lung site, a BALF sample was collected by means of either gentle syringe aspiration or mechanical suction with a pressure-regulated wall-mounted suction pump. The endoscope was then maneuvered into the contralateral lung site, and lavage was performed with the alternate fluid retrieval technique. For each horse, BAL was performed bilaterally once with and once without premedication with NBB (21-day interval). The BALF samples retrieved were evaluated for volume, total cell count, differential cell count, RBC count, and total protein concentration. RESULTS Use of syringe aspiration significantly increased total BALF volume (mean volume increase, 40 mL [approx 7.5% yield]) and decreased total RBC count (mean decrease, 142 cells/μL), compared with use of mechanical suction. The BALF nucleated cell count and differential cell count did not differ between BAL procedures. Use of NBB had no effect on BALF retrieval. CONCLUSIONS AND CLINICAL RELEVANCE Results indicated that retrieval of BALF by syringe aspiration may increase yield and reduce barotrauma in horses at increased risk of bronchoconstriction and bronchiolar collapse. Further studies to determine the usefulness of NBB and other bronchodilators during BAL procedures in horses are warranted.</jats:p

Modeling the pasture-associated severe equine asthma bronchoalveolar lavage fluid proteome identifies molecular events mediating neutrophilic airway inflammation

Background: Pasture-associated severe equine asthma is a warm season, environmentally-induced respiratory disease characterized by reversible airway obstruction, persistent and non-specific airway hyper-responsiveness, and chronic neutrophilic airway inflammation. During seasonal exacerbation, signs vary from mild to life-threatening episodes of wheezing, coughing, and chronic debilitating labored breathing. Purpose: In human asthma, neutrophilic airway inflammation is associated with more severe and steroid-refractory asthma phenotypes, highlighting a need to decipher the mechanistic basis of this disease characteristic. We hypothesize that the collective biological activities of proteins in bronchoalveolar lavage fluid (BALF) of horses with pasture-associated severe asthma predict changes in neutrophil functions that contribute to airway neutrophilic inflammation. Methods: Using shotgun proteomics, we identified 1,003 unique proteins in cell-free BALF from six horses experiencing asthma exacerbation and six control herdmates. Contributions of each protein to ten neutrophil functions were modeled using manual biocuration to determine each protein's net effect on the respective neutrophil functions. Results: A total of 417 proteins were unique to asthmatic horses, 472 proteins were unique to control horses (p<0.05), and 114 proteins were common in both groups. Proteins whose biological activities are responsible for increasing neutrophil migration, chemotaxis, cell spreading, transmigration, and infiltration, which would collectively bring neutrophils to airways, were over-represented in the BALF of asthmatic relative to control horses. By contrast, proteins whose biological activities support neutrophil activation, adhesion, phagocytosis, respiratory burst, and apoptosis, which would collectively shorten neutrophil lifespan, were under-represented in BALF of asthmatic relative to control horses. Interaction networks generated using Ingenuity® Pathways Analysis further support the results of our biocuration. Conclusion: Congruent with our hypothesis, the collective biological functions represented in differentially expressed proteins of BALF from horses with pasture-associated severe asthma support neutrophilic airway inflammation. This illustrates the utility of systems modeling to organize functional genomics data in a manner that characterizes complex molecular events associated with clinically relevant disease.College of Veterinary Medicine, Mississippi State University, Mississippi StateOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]