SNP Discovery and Genomic Architecture of Highly Inbred Leghorn and Fayoumi Chicken Breeds Using Whole Genome Resequencing

Advances in the use of next generation sequencing (NGS) and ability to pool individuals into groups that represent distinct livestock populations has made it possible to examine trait differences between breeds of chicken. The breeds examined are very divergent when compared on their history of laying ability and immune response. The long-term objective is to understand the genetic differences between the Leghorn and Fayoumi breeds for use in developing more productive and disease resistant chickens. Statistical testing of the sequence of the two breeds along with Gene set enrichment analysis (GSEA) to make connections between the genetic variation seen in the NGS data and the breed specific traits of egg laying and heightened immune response can be used to characterize these two breeds. Genetic terms having the highest level of differentiation between the lines appear to group into metabolic processes, with terms over-enriched for immune system process, sexual reproduction, and growth for variants examined between lines. Terms for functions within the Fayoumi and Leghorn populations aligned to immune function and reproductive function, respectively. These results are consistent with known breed phenotypes and provide a means to focus on specific DNA variations and the birds’ genetic diversity that are potentially of more commercial importance

Fatty Acid SNP Interaction Analysis in Angus Sired Beef Cattle

The triacylglyceride (TAG) fatty acid content in meat from Angus-sired cattle was analyzed for non-additive genetic effects. A total of 11,482 significant DNA marker interactions (false discovery rate [FDR] \u3c 0.05) were detected across thirty-seven different TAG fatty acids. Interactions were not evenly distributed amongst all fatty acids analyzed, and types of interactions (additive-by-additive, additive-by-dominance, and dominance-by-dominance) varied within each individual fatty acid. These results indicate that it may be possible to account for additional genetic variance amongst TAG fatty acids over and above individual markers

Evaluation of Responses to Vaccination of Angus Cattle for Four Viruses that Contribute to Bovine Respiratory Disease Complex

Initial antibody titers are maternally-derived from colostrum, then decay with age. Change in antibody titer levels were compared between four viruses contributing to the Bovine Respiratory Disease Complex (BRDC), and evaluation of response to vaccination indicated that antibody production will not occur when high levels of maternal antibodies are present. The maternal antibodies were found to decay with calf age for each of the four viruses, which allowed for the estimation of a maximum circulating titer level under which a positive antibody response to vaccination could occur. Phenotypic correlations were calculated between the antibody titers for the four viruses across multiple time points. Results indicate a difference in the response to vaccination between the four virus antigen

Identifying Molecular Differences in Pigs with Extreme Phenotypes for Weight Gain and Viral Load in Response to PRRS

Blood transcriptome analyses in the early phase after infection with the Porcine Reproductive and Respiratory Syndrome virus (PRRSv) revealed differential gene expression patterns and regulatory networks between pigs with extreme phenotypes for weight gain and viral load. Understanding these differences could lead to identifying biomarkers that would predict which pigs would be more resistant to PRRS

Whole blood microarray analysis of pigs showing extreme phenotypes after a porcine reproductive and respiratory syndrome virus infection

Citation: Schroyen, M., Steibel, J. P., Koltes, J. E., Choi, I., Raney, N. E., Eisley, C., . . . Tuggle, C. K. (2015). Whole blood microarray analysis of pigs showing extreme phenotypes after a porcine reproductive and respiratory syndrome virus infection. Bmc Genomics, 16(1). doi:10.1186/s12864-015-1741-8Background: The presence of variability in the response of pigs to Porcine Reproductive and Respiratory Syndrome virus (PRRSv) infection, and recent demonstration of significant genetic control of such responses, leads us to believe that selection towards more disease resistant pigs could be a valid strategy to reduce its economic impact on the swine industry. To find underlying molecular differences in PRRS susceptible versus more resistant pigs, 100 animals with extremely different growth rates and viremia levels after PRRSv infection were selected from a total of 600 infected pigs. A microarray experiment was conducted on whole blood RNA samples taken at 0, 4 and 7 days post infection (dpi) from these pigs. From these data, we examined associations of gene expression with weight gain and viral load phenotypes. The single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) on the porcine 60 K SNP chip was shown to be associated with viral load and weight gain after PRRSv infection, and so the effect of the WUR10000125 (WUR) genotype on expression in whole blood was also examined. Results: Limited information was obtained through linear modeling of blood gene differential expression (DE) that contrasted pigs with extreme phenotypes, for growth or viral load or between animals with different WUR genotype. However, using network-based approaches, molecular pathway differences between extreme phenotypic classes could be identified. Several gene clusters of interest were found when Weighted Gene Co-expression Network Analysis (WGCNA) was applied to 4dpi contrasted with 0dpi data. The expression pattern of one such cluster of genes correlated with weight gain and WUR genotype, contained numerous immune response genes such as cytokines, chemokines, interferon type I stimulated genes, apoptotic genes and genes regulating complement activation. In addition, Partial Correlation and Information Theory (PCIT) identified differentially hubbed (DH) genes between the phenotypically divergent groups. GO enrichment revealed that the target genes of these DH genes are enriched in adaptive immune pathways. Conclusion: There are molecular differences in blood RNA patterns between pigs with extreme phenotypes or with a different WUR genotype in early responses to PRRSv infection, though they can be quite subtle and more difficult to discover with conventional DE expression analyses. Co-expression analyses such as WGCNA and PCIT can be used to reveal network differences between such extreme response groups. © 2015 Schroyen et al

Increasing Gene Discovery and Coverage Using RNA-Seq of Globin RNA Reduced Porcine Blood Samples

Transcriptome analysis of porcine whole blood has several applications, which include deciphering genetic mechanisms for host responses to viral infection and vaccination. The abundance of alpha- and beta-globin transcripts in blood, however, impedes the ability to cost-effectively detect transcripts of low abundance. Although protocols exist for reduction of globin transcripts from human and mouse/rat blood, preliminary work demonstrated these are not useful for porcine blood Globin Reduction (GR). Our objectives were to develop a porcine specific GR protocol and to evaluate the GR effects on gene discovery and sequence read coverage in RNA-sequencing (RNA-seq) experiments. A GR protocol for porcine blood samples was developed using RNase H with antisense oligonucleotides specifically targeting porcine hemoglobin alpha (HBA) and beta (HBB) mRNAs. Whole blood samples (n = 12) collected in Tempus tubes were used for evaluating the efficacy and effects of GR on RNA-seq. The HBA and HBB mRNA transcripts comprised an average of 46.1% of the mapped reads in pre-GR samples, but those reads reduced to an average of 8.9% in post-GR samples. Differential gene expression analysis showed that the expression level of 11,046 genes were increased, whereas 34 genes, excluding HBA and HBB, showed decreased expression after GR (FDR \u3c0.05). An additional 815 genes were detected only in post-GR samples. Our porcine specific GR primers and protocol minimize the number of reads of globin transcripts in whole blood samples and provides increased coverage as well as accuracy and reproducibility of transcriptome analysis. Increased detection of low abundance mRNAs will ensure that studies relying on transcriptome analyses do not miss information that may be vital to the success of the study

Bioinformatic analyses in early host response to Porcine Reproductive and Respiratory Syndrome virus (PRRSV) reveals pathway differences between pigs with alternate genotypes for a major host response QTL

Citation: Schroyen, M., Eisley, C., Koltes, J. E., Fritz-Waters, E., Choi, I., Plastow, G. S., . . . Tuggle, C. K. (2016). Bioinformatic analyses in early host response to Porcine Reproductive and Respiratory Syndrome virus (PRRSV) reveals pathway differences between pigs with alternate genotypes for a major host response QTL. Bmc Genomics, 17, 16. doi:10.1186/s12864-016-2547-zAdditional Authors: Tuggle, C. K.Background: A region on Sus scrofa chromosome 4 (SSC4) surrounding single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) has been reported to be strongly associated with both weight gain and serum viremia in pigs after infection with PRRS virus (PRRSV). A proposed causal mutation in the guanylate binding protein 5 gene (GBP5) is predicted to truncate the encoded protein. To investigate transcriptional differences between WUR genotypes in early host response to PRRSV infection, an RNA-seq experiment was performed on globin depleted whole blood RNA collected on 0, 4, 7, 10 and 14 days post-infection (dpi) from eight littermate pairs with one AB (favorable) and one AA (unfavorable) WUR genotype animal per litter. Results: Gene Ontology (GO) enrichment analysis of transcripts that were differentially expressed (DE) between dpi across both genotypes revealed an inflammatory response for all dpi when compared to day 0. However, at the early time points of 4 and 7dpi, several GO terms had higher enrichment scores compared to later dpi, including inflammatory response (p < 10(-7)), specifically regulation of NFkappaB (p < 0.01), cytokine, and chemokine activity (p < 0.01). At 10 and 14dpi, GO term enrichment indicated a switch to DNA damage response, cell cycle checkpoints, and DNA replication. Few transcripts were DE between WUR genotypes on individual dpi or averaged over all dpi, and little enrichment of any GO term was found. However, there were differences in expression patterns over time between AA and AB animals, which was confirmed by genotype-specific expression patterns of several modules that were identified in weighted gene co-expression network analyses (WGCNA). Minor differences between AA and AB animals were observed in immune response and DNA damage response (p = 0.64 and p = 0.11, respectively), but a significant effect between genotypes pointed to a difference in ion transport/homeostasis and the participation of G-coupled protein receptors (p = 8e-4), which was reinforced by results from regulatory and phenotypic impact factor analyses between genotypes. Conclusion: We propose these pathway differences between WUR genotypes are the result of the inability of the truncated GBP5 of the AA genotyped pigs to inhibit viral entry and replication as quickly as the intact GBP5 protein of the AB genotyped pigs

Fixed-order H∞ filtering for discrete-time markovian jump linear systems with unobservable jump modes

In practical applications, it is often encountered that the jump modes of a Markovian jump linear system may not be fully accessible to the filter, and thus designing a filter which partially or totally independent of the jump modes becomes significant. In this paper, by virtue of a new stability and H ∞ performance characterization, a novel necessary and sufficient condition for the existence of mode-independent H∞ filters is established in terms of a set of nonlinear matrix inequalities that possess special properties for computation. Then, two com putational approaches are developed to solve the condition. One is based on the solution of a set of linear matrix inequalities (LMIs), and the other is based on the sequential LMI optimization with more computational effort but less conservatism. In addition, a specific property of the feasible solutions enables one to further improve the solvability of these two computational approaches. ©2009 ACA.published_or_final_versionThe 7th Asian Control Conference (ASCC 2009), Hong Kong, China, 27-29 August 2009. In Proceedings of the Asian Control Conference, 2009, p. 424-42

Design and validation of a 90K SNP genotyping assay for the water buffalo (Bubalus bubalis)

Background: The availability of the bovine genome sequence and SNP panels has improved various genomic analyses, from exploring genetic diversity to aiding genetic selection. However, few of the SNP on the bovine chips are polymorphic in buffalo, therefore a panel of single nucleotide DNA markers exclusive for buffalo was necessary for molecular genetic analyses and to develop genomic selection approaches for water buffalo. The creation of a 90K SNP panel for river buffalo and testing in a genome wide association study for milk production is described here. Methods: The genomes of 73 buffaloes of 4 different breeds were sequenced and aligned against the bovine genome, which facilitated the identification of 22 million of sequence variants among the buffalo genomes. Based on frequencies of variants within and among buffalo breeds, and their distribution across the genome, inferred from the bovine genome sequence, 90,000 putative single nucleotide polymorphisms were selected to create an Axiom® Buffalo Genotyping Array 90K. Results: This 90K "SNP-Chip" was tested in several river buffalo populations and found to have ∼70% high quality and polymorphic SNPs. Of the 90K SNPs about 24K were also found to be polymorphic in swamp buffalo. The SNP chip was used to investigate the structure of buffalo populations, and could distinguish buffalo from different farms. A Genome Wide Association Study identified genomic regions on 5 chromosomes putatively involved in milk production. Conclusion: The 90K buffalo SNP chip described here is suitable for the analysis of the genomes of river buffalo breeds, and could be used for genetic diversity studies and potentially as a starting point for genome-assisted selection programmes. This SNP Chip could also be used to analyse swamp buffalo, but many loci are not informative and creation of a revised SNP set specific for swamp buffalo would be advised.Daniela Iamartino, Ezequiel L. Nicolazzi, Curtis P. Van Tassell, James M. Reecy, Eric R. Fritz-Waters, James E. Koltes, Stefano Biffani, Tad S. Sonstegard, Steven G. Schroeder, Paolo Ajmone-Marsan, Riccardo Negrini, Rolando Pasquariello, Paola Ramelli, Angelo Coletta, José F. Garcia, Ahmad Ali, Luigi Ramunno, Gianfranco Cosenza, Denise A.A. de Oliveira, Marcela G. Drummond, Eduardo Bastianetto, Alessandro Davassi, Ali Pirani, Fiona Brew, John L. William