Genomic evaluation techniques have been a huge success in the dairy cattle industry, as they allow accurate enough estimation of breeding values at a young age to allow selection decisions to be made at an earlier stage, thereby increasing the rate of genetic progress per annum. The success of genomic selection techniques relies on the existence of linkage disequilibrium (LD) between markers and quantitative trait loci (QTL) across the population of interest; LD persists across larger distances within breeds than across breeds. Therefore, most success so far has been for selection within breeds, but the industry is keen for “across breed” evaluations to be developed, both in a multi-breed scenario which would allow evaluations for breeds that are numerically too small to carry out evaluations within breeds, and also for the evaluation of crossbred animals. This thesis investigates the potential for applying genomic selection techniques in both the multi-breed and crossbred scenarios. Chapter 2 examines the potential for a multi-breed reference population to improve the accuracy of genomic evaluation for a numerically small breed, for a range of production and non-production traits. The results provide evidence that forming a multi-breed reference population for two closely related breeds (Holstein and Friesian) results in a higher accuracy of GEBVs for the smaller breed, particularly when more phenotypic records are added via the single-step GBLUP method, and when a higher density SNP chip is used. Chapter 3 examines the crossbred scenario, whereby GEBVs are calculated for crossbred individuals based on a crossbred reference population. The population used for analysis was a highly crossbred African population, and GEBVs were calculated for three groups of animals chosen according to whether they had a high or low proportion of imported dairy genetics. Accuracy of prediction was higher than expected, and provided proof of concept for applying genomic selection techniques in crossbred African cattle populations. Chapter 4 investigates the potential for using novel SNPs derived from sequence data in order to estimate genomic relationships across cattle breeds, deploying data from two closely related breeds, Fleckvieh and Simmental, and a further distant European breed, the Brown Swiss. Novel SNPs were selected from sequence based on their putative impact on the genome, with impacts being inferred by SNP annotation software snpEff. Results showed that genomic relationships calculated using novel SNPs have a high correlation with genomic relationships calculated using SNPs common to the Illumina BovineHD SNP chip, though between-breed correlations were lower than those within breeds. The results presented in this thesis demonstrate that utilising a multi-breed reference population can improve the accuracy of prediction for a numerically small breed, and that genomic prediction of highly crossbred individuals is also feasible. However, differences between breeds and also types of crossbred animal suggest that no one solution can be used for all across-breed evaluations, and further research will be needed to allow commercial implementation in further populations.

The advent of next-generation sequencing technologies is transforming biology by enabling individual researchers to sequence the genomes of individual organisms or cells on a massive scale. In order to realize the translational potential of this technology we will need advanced information systems to integrate and interpret this deluge of data. These systems must be capable of extracting the location and function of genes and biological features from genomic data, requiring the coordinated parallel execution of multiple bioinformatics analyses and intelligent synthesis of the results. The resulting databases must be structured to allow complex biological knowledge to be recorded in a computable way, which requires the development of logic-based knowledge structures called ontologies. To visualise and manipulate the results, new graphical interfaces and knowledge acquisition tools are required. Finally, to help understand complex disease processes, these information systems must be equipped with the capability to integrate and make inferences over multiple data sets derived from numerous sources. RESULTS: Here I describe research, design and implementation of some of the components of such a next-generation information system. I first describe the automated pipeline system used for the annotation of the Drosophila genome, and the application of this system in genomic research. This was succeeded by the development of a flexible graphoriented database system called Chado, which relies on the use of ontologies for structuring data and knowledge. I also describe research to develop, restructure and enhance a number of biological ontologies, adding a layer of logical semantics that increases the computability of these key knowledge sources. The resulting database and ontology collection can be accessed through a suite of tools. Finally I describe how the combination of genome analysis, ontology-based database representation and powerful tools can be combined in order to make inferences about genotype-phenotype relationships within and across species. CONCLUSION: The large volumes of complex data generated by high-throughput genomic and systems biology technology threatens to overwhelm us, unless we can devise better computing tools to assist us with its analysis. Ontologies are key technologies, but many existing ontologies are not interoperable or lack features that make them computable. Here I have shown how concerted ontology, tool and database development can be applied to make inferences of value to translational research.

Avian influenza virus (AIV) is a type A virus of the family Orthomyxoviridae and its outbreaks not only cause economic losses in poultry, but also are worldwide threats to human health. The phenotypic changes in host cells induced by pathogens are always accompanied by remarkable changes in gene expression. Therefore understanding the gene expression profile of infected cells at the global level is important to get insights into interactions between hosts and viruses. Different genomic approaches have been utilized in the current study to investigate the host-AIV interactions in chickens. The Ser to Asn mutation on position 631 in the chicken Mx1 protein was reported to result in a positive antiviral function in vitro. With AIV infection, the Mx1 mRNA expression levels in heterozygous birds were significantly up-regulated. Additional mutations on the chicken Mx1 coding region were identified by sequencing. The results showed that most identified mutations were co-segregated with S631N mutation except one insertion in the position of 1544bp in the heterozygous birds. We speculate this insertion might be related to the up-regulation of mRNA expression of heterozygous birds with AIV infection. The miRNAs play critical roles in biological processes and are important effectors in host-pathogen interactions. The miRNA deep sequencing was used to profile miRNAs in AIV infected or non-infected chickens. Differentially expressed miRNAs identified have expanded our knowledge in the functions of these potential immune related chicken miRNAs regulating host response to AIV infection. Both microarray and transcriptome analysis by RNA-Seq were used in the current study to investigate the global gene expression of host response to AIV infection. Through the comprehensive analysis, a list of strong candidate miRNAs such as miR-32 and their host target genes including Mx1 were identified for further elucidating the regulatory mechanism of host-AIV interaction. In summary, we have identified many important candidate host genes and miRNAs which play important roles in the modulation of host response to AIV infection using genomic approaches. Further investigation of underline regulatory mechanisms of these genes, miRNAs or related pathways, followed by functional analysis, could lay solid foundation for understanding cellular and molecular mechanisms of the host-AIV interactions, thereby, pave a way for the development of novel protective strategies against AIV infection in chickens.

The 12-oxo-phytodienoic acid reductases (OPRs) are enzymes of the octadecanoid pathway which converts linolenic acid to a phytohormone, jasmonic acid. Bioinformatics analysis of ESTs and genomic sequences from available private and public databases revealed that the maize genome encodes eight different OPR genes. This number of maize OPR genes has been independently confirmed by Southern blot analysis and by mapping of individual OPR genes to maize chromosomes using oat maize chromosome addition lines. Survey of massively parallel signature sequencing (MPSS) assays revealed that transcripts of each OPR gene accumulate differentially in diverse organs of maize plants. This data suggested that individual OPR genes may have a distinct function in development. Similarly, RNA blot analysis revealed that distinct OPR genes are differentially regulated in response to stress hormones, wounding or pathogen infection. ZmOPR1 and ZmOPR2 appear to have important functions in defense responses to pathogens because they are transiently induced by salicylic acid (SA), chitooligosaccharides and by infection with Cochliobolus carbonum, Bipolaris maydis and Fusarium verticillioides and not by wounding. In contrast to these two genes, ZmOPR6 and ZmOPR7/8 are highly induced by wounding and treatments with wound-associated signaling molecules jasmonic acid, ethylene and abscisic acid. ZmOPR6 and ZmOPR7/8 are not induced by SA treatments or pathogen infections suggesting their specific involvement in wound-induced defense responses. Possible functions of specific OPR genes are discussed.

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

Small noncoding RNAs, including microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), and endogenous small-interfering RNAs (endo-siRNAs), regulate developmental and defense pathways in animals. While many small RNA silencing protein cofactors have been identified, much more is to be learned from a dynamic and quantitative perspective to reveal the underlying mechanisms and designing principles of each pathway. In this dissertation, I present studies that examine the temporal dynamics of small RNA pathways - one from an evolutionary time scale among the nematode species, and one from finely staged Caenorabditis elegans during the first larval stage. I also describe works identifying new cofactors functions in the miRNA pathway, potentially through regulating the spatial dynamics of the miRNA silencing complex.

No description available.

New applications of genomic medicine stemming from the Human Genome Project are predicted to become routine components of primary care. Primary care physicians (PCPs) will increasingly become responsible for screening patients for inherited diseases, recommending genetic testing, and making referrals to genetic services. Clinical applications of genomic medicine will occur at a variable pace. Characteristics of an innovation such as genomic medicine are strong indicators of its potential for adoption. The purpose of this study is to assess whether (and to what extent) physicians' perceptions of genomic medicine as an innovation influence their likelihood of adopting this innovation into primary care. The study's sample consists of 400 primary care physicians in Texas and employs a survey design. Based on Rogers' Diffusion of Innovations Theory, the perceived characteristics of genomic medicine - Relative Advantage, Compatibility, Complexity, Trialability, and Observability - are the study's independent/predictor variables. Likelihood of PCPs Adopting Genomic Medicine is the dependent variable. The nature of the social system (private or group practice) is examined as a possible moderator variable. The study suggests that Texas PCPs who are likely to adopt genomic medicine strongly perceive its clinical uses (such as genetic testing for carrier status or susceptibility to common diseases, testing an embryo for genetic disorders before it is implanted, and supplementing a family history) to be highly advantageous. For half of the PCPs, genetic services such as genetic counseling and genetic testing are not compatible with current practice. Perceived complexity of the innovation is the strongest predictor of likelihood of PCPs adopting genomic medicine. Many PCPs find it difficult to stay updated on genomic medicine and locate genetic services. Although Texas PCPs feel genomic medicine can be gradually incorporated into primary care practice, most are not presently observing their colleagues adopting genomic medicine or assisting their patients to make decisions regarding genetic services. Future efforts to advance the use of genomic medicine in primary care will require more emphasis on genetics in medical school curriculum and continuing education programs. Links with specialists trained in genetic counseling and health education will be essential to translate relevant information to patients and families.

This study analyzes the economic impact of a recent gene marker innovation for seedstock selection in beef cattle. Gene markers are being developed for many beef cattle attributes; this study focused on the tenderness quality of beef using two categories: tender and tough. The study begins by describing conventional procedures for seedstock selection, the science which underlies selection by gene markers and other non-genetic procedures currently being used to improve beef tenderness. After describing the commercialization of the gene marker innovation, a stylized model of a beef supply chain is constructed. The supply chain consists of a representative consumer, a producer/processor group and a monopolist supplier of the patented technology. Welfare changes resulting from the adoption of the innovation were simulated using four sets of demand elasticity data from literatures. An important focus of this research is determining how the economic surplus from the innovation will be shared by consumers, producers and the gene marker monopolist. The consumer and gene marker monopolist benefit from the technology unless the marginal and fixed cost variables (not estimated in this study) of the monopolist, are excessively high. Producer surplus was simulated as positive with three of the four elasticity data sets. The share of surplus capture by producers is generally low relative to the gains captured by consumers and the gene marker monopolist. Comparative static analysis reveal that the benefit from the innovation varies across breeds, being higher for breeds in which the favorable form of the marker gene is more likely to be present. Despite the apparent benefits of the innovation for beef supply chain participants, reported interviews with industry scientists reveal that markers should not be viewed as a replacement for conventional selection techniques. Indeed, selecting seedstock on the basis of a small number of available markers is not likely to produce the benefits that are currently being promised by life science companies. Consequently, this study recommends that the innovation be incorporated into existing seedstock selection practices. Much more analysis is needed to understand the full economic impact of gene markers for beef tenderness and for other beef quality attributes.

Candidate virulence genes were sought through the genetic analyses of two strains of Mycobacterium tuberculosis, one virulent, H37Rv, one attenuated, H37Ra. Derived from the same parent, H37, genomic differences between strains were first examined via two-dimensional DNA technologies: two-dimensional bacterial genome display, and bacterial comparative genomic hybridisation. The two-dimensional technologies were optimised for mycobacterial use, but failed to yield reproducible genomic differences between the two strains. Expression differences between strains during their infection of murine bone-marrow-derived macrophages were then assessed using Bacterial Artificial Chromosome Fingerprint Arrays. This technique successfully identified expression differences between intracellular M. tuberculosis H37Ra and H37Rv, and six candidate genes were confirmed via quantitative real-time PCR for their differential expression at 168 hours post-infection. Genes identified to be upregulated in the attenuated H37Ra were frdB, frdC, and frdD. Genes upregulated in the virulent H37Rv were pks2, aceE, and Rv1571. Further qPCR analysis of these genes at 4 and 96h post-infection revealed that the frd operon (encoding for the fumarate reductase enzyme complex or FRD) was expressed at higher levels in the virulent H37Rv at earlier time points while the expression of aceE and pks2 was higher in the virulent strain throughout the course of infection. Assessment of frd transcripts in oxygen-limited cultures of M. tuberculosis H37Ra and H37Rv showed that the attenuated strain displayed a lag in frdA and frdB expression at the onset of culture when compared to microaerophilic cultures of H37Rv and aerated cultures of H37Ra. Furthermore, inhibition of the fumarate reductase complex in intracellular bacteria resulted in a significant reduction of intracellular growth. Microarray technology was also applied in the expression analysis of intracellular bacteria at 168h post-infection. Forty-eight genes were revealed to be differentially expressed between the H37Ra and H37Rv strains, and a subset were further analysed via qPCR to confirm and validate the microarray data. phoP was expressed at a lower level in the attenuated M. tuberculosis H37Ra, whereas members of the phoPR regulon were up-regulated in the virulent H37Rv. Additionally, a group of genes (Rv3616c-Rv3613c) that may associate with the region of difference 1 were also up-regulated in the virulent H37Rv.