Beyond barcoding : a mitochondrial genomics approach to molecular phylogenetics and diagnostics of blowflies (Diptera: Calliphoridae)

Members of the Calliphoridae (blowflies) are significant for medical and veterinary management, due to the ability of some species to consume living flesh as larvae, and for forensic investigations due to the ability of others to develop in corpses. Due to the difficulty of accurately identifying larval blowflies to species there is a need for DNA-based diagnostics for this family, however the widely used DNA-barcoding marker, cox1, has been shown to fail for several groups within this family. Additionally, many phylogenetic relationships within the Calliphoridae are still unresolved, particularly deeper level relationships. Sequencing whole mt genomes has been demonstrated both as an effective method for identifying the most informative diagnostic markers and for resolving phylogenetic relationships. Twenty-seven complete, or nearly so, mt genomes were sequenced representing 13 species, seven genera and four calliphorid subfamilies and a member of the related family Tachinidae. PCR and sequencing primers developed for sequencing one calliphorid species could be reused to sequence related species within the same superfamily with success rates ranging from 61% to 100%, demonstrating the speed and efficiency with which an mt genome dataset can be assembled. Comparison of molecular divergences for each of the 13 protein-coding genes and 2 ribosomal RNA genes, at a range of taxonomic scales identified novel targets for developing as diagnostic markers which were 117–200% more variable than the markers which have been used previously in calliphorids. Phylogenetic analysis of whole mt genome sequences resulted in much stronger support for family and subfamily-level relationships. The Calliphoridae are polyphyletic, with the Polleninae more closely related to the Tachinidae, and the Sarcophagidae are the sister group of the remaining calliphorids. Within the Calliphoridae, there was strong support for the monophyly of the Chrysomyinae and Luciliinae and for the sister-grouping of Luciliinae with Calliphorinae. Relationships within Chrysomya were not well resolved. Whole mt genome data, supported the previously demonstrated paraphyly of Lucilia cuprina with respect to L. sericata and allowed us to conclude that it is due to hybrid introgression prior to the last common ancestor of modern sericata populations, rather than due to recent hybridisation, nuclear pseudogenes or incomplete lineage sorting.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

Cardiomyopathy classification : ongoing debate in the genomics era

Cardiomyopathies represent a group of diseases of the myocardium of the heart and include diseases both primarily of the cardiac muscle and systemic diseases leading to adverse effects on the heart muscle size, shape, and function. Traditionally cardiomyopathies were defined according to phenotypical appearance. Now, as our understanding of the pathophysiology of the different entities classified under each of the different phenotypes improves and our knowledge of the molecular and genetic basis for these entities progresses, the traditional classifications seem oversimplistic and do not reflect current understanding of this myriad of diseases and disease processes. Although our knowledge of the exact basis of many of the disease processes of cardiomyopathies is still in its infancy, it is important to have a classification system that has the ability to incorporate the coming tide of molecular and genetic information. This paper discusses how the traditional classification of cardiomyopathies based on morphology has evolved due to rapid advances in our understanding of the genetic and molecular basis for many of these clinical entities.

A population genomics overview of the neuronal nitric oxide synthase (nNOS) gene and its relationship to migraine susceptibility

The ubiquitous chemical messenger molecule nitric oxide (NO) has been implicated in a diverse range of biological activities including neurotransmission, smooth muscle motility and mediation of nociception. Endogenous synthesis of NO by the neuronal isoform of the nitric oxide synthase gene family has an essential role within the central and peripheral nervous systems in addition to the autonomic innervation of cerebral blood vessels. To investigate the potential role of NO and more specifically the neuronal nitric oxide synthase (nNOS) gene in migraine susceptibility, we investigated two microsatellite repeat variants residing within the 5′ and 3′ regions of the nNOS gene. Population genomic evaluation of the two nNOS repeat variants indicated significant linkage disequilibrium between the two loci. Z-DNA conformational sequence structures within the 5′ region of the nNOS gene have the potential to enhance or repress gene promoter activity. We suggest that genetic analysis of this 5′ repeat variant is the more functional variant expressing gene wide information that could affect endogenous NO synthesis and potentially result in diseased states. However, no association with migraine (with or without aura) was seen in our extensive case-control cohort (n = 579 affected with matched controls), when both the 5′ and 3′ genetic variants were investigated.

Insect mitochondrial genomics : implications for evolution and phylogeny

The mitochondrial (mt) genome is, to date, the most extensively studied genomic system in insects, outnumbering nuclear genomes tenfold and representing all orders versus very few. Phylogenomic analysis methods have been tested extensively, identifying compositional bias and rate variation, both within and between lineages, as the principal issues confronting accurate analyses. Major studies at both inter- and intraordinal levels have contributed to our understanding of phylogenetic relationships within many groups. Genome rearrangements are an additional data type for defining relationships, with rearrangement synapomorphies identified across multiple orders and at many different taxonomic levels. Hymenoptera and Psocodea have greatly elevated rates of rearrangement offering both opportunities and pitfalls for identifying rearrangement synapomorphies in each group. Finally, insects are model systems for studying aberrant mt genomes, including truncated tRNAs and multichromosomal genomes. Greater integration of nuclear and mt genomic studies is necessary to further our understanding of insect genomic evolution.

Transient expression vectors for functional genomics, quantification of promoter activity and RNA silencing in plants

Background We describe novel plasmid vectors for transient gene expression using Agrobacterium, infiltrated into Nicotiana benthamiana leaves. We have generated a series of pGreenII cloning vectors that are ideally suited to transient gene expression, by removing elements of conventional binary vectors necessary for stable transformation such as transformation selection genes. Results We give an example of expression of heme-thiolate P450 to demonstrate effectiveness of this system. We have also designed vectors that take advantage of a dual luciferase assay system to analyse promoter sequences or post-transcriptional regulation of gene expression. We have demonstrated their utility by co-expression of putative transcription factors and the promoter sequence of potential target genes and show how orthologous promoter sequences respond to these genes. Finally, we have constructed a vector that has allowed us to investigate design features of hairpin constructs related to their ability to initiate RNA silencing, and have used these tools to study cis-regulatory effect of intron-containing gene constructs. Conclusion In developing a series of vectors ideally suited to transient expression analysis we have provided a resource that further advances the application of this technology. These minimal vectors are ideally suited to conventional cloning methods and we have used them to demonstrate their flexibility to investigate enzyme activity, transcription regulation and post-transcriptional regulatory processes in transient assays.

How to sequence and annotate insect mitochondrial genomes for systematic and comparative genomics research

Over the past decade the mitochondrial (mt) genome has become the most widely used genomic resource available for systematic entomology. While the availability of other types of ‘–omics’ data – in particular transcriptomes – is increasing rapidly, mt genomes are still vastly cheaper to sequence and are far less demanding of high quality templates. Furthermore, almost all other ‘–omics’ approaches also sequence the mt genome, and so it can form a bridge between legacy and contemporary datasets. Mitochondrial genomes have now been sequenced for all insect orders, and in many instances representatives of each major lineage within orders (suborders, series or superfamilies depending on the group). They have also been applied to systematic questions at all taxonomic scales from resolving interordinal relationships (e.g. Cameron et al., 2009; Wan et al., 2012; Wang et al., 2012), through many intraordinal (e.g. Dowton et al., 2009; Timmermans et al., 2010; Zhao et al. 2013a) and family-level studies (e.g. Nelson et al., 2012; Zhao et al., 2013b) to population/biogeographic studies (e.g. Ma et al., 2012). Methodological issues around the use of mt genomes in insect phylogenetic analyses and the empirical results found to date have recently been reviewed by Cameron (2014), yet the technical aspects of sequencing and annotating mt genomes were not covered. Most papers which generate new mt genome report their methods in a simplified form which can be difficult to replicate without specific knowledge of the field. Published studies utilize a sufficiently wide range of approaches, usually without justification for the one chosen, that confusion about commonly used jargon such as ‘long PCR’ and ‘primer walking’ could be a serious barrier to entry. Furthermore, sequenced mt genomes have been annotated (gene locations defined) to wildly varying standards and improving data quality through consistent annotation procedures will benefit all downstream users of these datasets. The aims of this review are therefore to: 1. Describe in detail the various sequencing methods used on insect mt genomes; 2. Explore the strengths/weakness of different approaches; 3. Outline the procedures and software used for insect mt genome annotation, and; 4. Highlight quality control steps used for new annotations, and to improve the re-annotation of previously sequenced mt genomes used in systematic or comparative research.

The Anadara trapezia transcriptome : a resource for molluscan physiological genomics

In this study we undertook deep sequencing of the blood cockle, Anadara trapezia, transcriptome to generate genomic resources for future functional genomics analyses. Over 27 million high quality paired end reads were assembled into 75 024 contigs. Of these contigs, 29 013 (38.7%) received significant BLASTx hits and gene ontology (GO) terms were assigned to 13 718 of these sequences. This resourcewill facilitate physiological genomic studies to test the gene expression response of A. trapezia to various environmental stresses.

Comparative genomics of koala, cattle and sheep strains of Chlamydia pecorum

Background Chlamydia pecorum is an important pathogen of domesticated livestock including sheep, cattle and pigs. This pathogen is also a key factor in the decline of the koala in Australia. We sequenced the genomes of three koala C. pecorum strains, isolated from the urogenital tracts and conjunctiva of diseased koalas. The genome of the C. pecorum VR629 (IPA) strain, isolated from a sheep with polyarthritis, was also sequenced. Results Comparisons of the draft C. pecorum genomes against the complete genomes of livestock C. pecorum isolates revealed that these strains have a conserved gene content and order, sharing a nucleotide sequence similarity > 98%. Single nucleotide polymorphisms (SNPs) appear to be key factors in understanding the adaptive process. Two regions of the chromosome were found to be accumulating a large number of SNPs within the koala strains. These regions include the Chlamydia plasticity zone, which contains two cytotoxin genes (toxA and toxB), and a 77 kbp region that codes for putative type III effector proteins. In one koala strain (MC/MarsBar), the toxB gene was truncated by a premature stop codon but is full-length in IPTaLE and DBDeUG. Another five pseudogenes were also identified, two unique to the urogenital strains C. pecorum MC/MarsBar and C. pecorum DBDeUG, respectively, while three were unique to the koala C. pecorum conjunctival isolate IPTaLE. An examination of the distribution of these pseudogenes in C. pecorum strains from a variety of koala populations, alongside a number of sheep and cattle C. pecorum positive samples from Australian livestock, confirmed the presence of four predicted pseudogenes in koala C. pecorum clinical samples. Consistent with our genomics analyses, none of these pseudogenes were observed in the livestock C. pecorum samples examined. Interestingly, three SNPs resulting in pseudogenes identified in the IPTaLE isolate were not found in any other C. pecorum strain analysed, raising questions over the origin of these point mutations. Conclusions The genomic data revealed that variation between C. pecorum strains were mainly due to the accumulation of SNPs, some of which cause gene inactivation. The identification of these genetic differences will provide the basis for further studies to understand the biology and evolution of this important animal pathogen. Keywords: Chlamydia pecorum; Single nucleotide polymorphism; Pseudogene; Cytotoxin

Genetics and genomics of ankylosing spondylitis

Ankylosing spondylitis (AS) is a common, highly heritable arthropathy, the pathogenesis of which is poorly understood. The mechanism by which the main gene for the disease, HLA-B27, leads to AS is unknown. Genetic and genomic studies have demonstrated involvement of the interleukin-23 (IL-23) signaling pathway in AS, a finding which has stimulated much new research into the disease and has led to therapeutic trials. Several other genes and genetic regions, including further major histocompatibility complex (MHC) and non-MHC loci, have been shown to be involved in the disease, but it is not clear yet how they actually induce the condition. These findings have shown that there is a strong genetic overlap between AS and Crohn's disease in particular, although there are also major differences in the genes involved in the two conditions, presumably explaining their different presentations. Genomic and proteomic studies are in an early phase but have potential both as diagnostic/prognostic tools and as a further hypothesis-free tool to investigate AS pathogenesis. Given the slow progress in studying the mechanism of association of HLA-B27 with AS, these may prove to be more fruitful approaches to investigating the pathogenesis of the disease. © 2009 John Wiley & Sons A/S.

Genomics of ankylosing spondylitis

Ankylosing spondylitis (AS) is the prototypic and most prevalent and debilitating spondyloarthropathy, a group of arthritides where the spine and pelvis are specifically targeted. Unlike many other forms of arthritis in which joint damage is mediated through tissue destruction, in AS uncontrolled bone formation occurs, frequently resulting in joint fusion and consequently significant disability. It is estimated that there are 2.4 million spondyloarthritis sufferers in the U.S., twice as many as rheumatoid arthritis. The pathogenesis of AS is very poorly understood and both genetics and gene expression profiling approaches have been utilized to elucidate the underlying mechanisms and pathways that drive the disease. Using powerful genome-wide association study approaches a number of candidate genes have been found to be associated with AS. However, although such approaches can identify genes that can contribute to the disease process, they do not inform us of the actual changes in gene/cell activity at any point in the disease process. Expression profiling allows us to take a "snapshot" of cellular activity and what gene activity changes are underlying those changes. A number of expression profiling studies have been undertaken in AS, looking at both circulating cells and tissues from affected joints. The results to date have been somewhat disappointing with little consensus on gene activity changes due to the low power of the studies undertaken. Some more recent better powered studies have identified diagnostic expression profiles that do point to a possible role for expression profiling in early AS diagnosis. Future studies will require collaborative approaches to target specific disease stages and sites with larger numbers of samples.

Rice molecular breeding laboratories in the genomics era: Current status and future considerations

Using DNA markers in plant breeding with marker-assisted selection (MAS) could greatly improve the precision and efficiency of selection, leading to the accelerated development of new crop varieties. The numerous examples of MAS in rice have prompted many breeding institutes to establish molecular breeding labs. The last decade has produced an enormous amount of genomics research in rice, including the identification of thousands of QTLs for agronomically important traits, the generation of large amounts of gene expression data, and cloning and characterization of new genes, including the detection of single nucleotide polymorphisms. The pinnacle of genomics research has been the completion and annotation of genome sequences for indica and japonica rice. This information-coupled with the development of new genotyping methodologies and platforms, and the development of bioinformatics databases and software tools-provides even more exciting opportunities for rice molecular breeding in the 21st century. However, the great challenge for molecular breeders is to apply genomics data in actual breeding programs. Here, we review the current status of MAS in rice, current genomics projects and promising new genotyping methodologies, and evaluate the probable impact of genomics research. We also identify critical research areas to "bridge the application gap" between QTL identification and applied breeding that need to be addressed to realize the full potential of MAS, and propose ideas and guidelines for establishing rice molecular breeding labs in the postgenome sequence era to integrate molecular breeding within the context of overall rice breeding and research programs.