2010 Projects

Computational design and experimental evaluation of new antimalarial agents interacting with a novel protein foldase and chaperone, PfFKBP35

Supervisors: Dr. Angus Bell (TCD), Dr. Anthony Chubb

Immunophilins are proteins that mediate the actions of the immunosuppressive drugs such as cyclosporin A and FK506. They are involved in the folding, transport and regulation of other proteins in cells. They are abundant in a wide variety of organisms and interact with proteins involved in diverse functions including the expression of genes, transduction of signals and microbial disease. They are potential targets for new drugs for Alzheimer's disease, cancer and AIDS. Dr. Bell's group has discovered a new and unusual FK506-binding protein (FKBP)-type immunophilin in the most lethal human malarial parasite Plasmodium falciparum, PfFKBP35. The protein has both foldase and molecular chaperone activities which can be both inhibited by FK506 and related (non-immunosuppressive) compounds that have potent antimalarial activity. This background, and the observation that PfFKBP35 is (unusually) the sole protein of its class in this parasite, makes PfFKBP35 an attractive target for antimalarial drug design. Advantageously, the 3D structure of the protein, as well as of the major human FKBP, is now known. The immunosuppressive drug FK506 fits into an open, solvent exposed pocket in the binding protein PfFKBP35.

This interaction is similar to that of protein-protein interactions which can be inhibited with constrained peptides that are readily synthesised using solid-phase peptide synthesis (SPPS). Virtual High Throughput Screening will thus involve the creation of novel databases of combinatorial peptides, both linear and cyclically constrained, containing both natural and non-natural amino acids. The final virtual products of SPPS will be linked combinatorially using SMILES (Simplified Molecular Input Line Entry System), energy minimised, and searched using docking and pharmacophore screening.

Ligands predicted in silico to have selective and high-affinity binding to PfFKBP35 would then be tested in Dr. Bell's laboratory for actual binding affinity, activity on cultured parasites and human cytotoxicity. Bioactivity data would then inform the computational design in an iterative way leading to the most potent and selective agents. This research may lead to a new therapeutic agent for malaria, a disease of massive world-wide importance.

Development and Validation of novel predictive tools for the diagnosis and prognosis of prostate cancer

Supervisors: Prof. William Watson, Prof. Brendan Murphy

Prostate cancer is the most commonly diagnosed cancer in Ireland and the world. It is also the third most common cause of male cancer deaths. With an aging population there is a projected 275% increase in the incidence of prostate cancer in Ireland. This projected increase is of major concern due to the dilemmas associated with both the detection and treatment of prostate cancer. The diagnosis of prostate cancer is traditionally based on three parameters: palpation of the gland, serum PSA and presence of cancer in a needle biopsy, however there are issues with sensitivity and specificity despite the use of these parameters in clinical adjunctive decision-making tools. Studies carried out by our current Bioinformatics and Computational Biomedicine PhD student, Mr Yue Fan, has identified panels of serum biomarkers which help in both the identification and pathological status of prostate cancer which is essential in determining the most appropriate treatment strategy for the patient. Building on these current findings we now plan to develop and validate appropriate tools that will incorporate the current clinical parameters with these new novel panels of serum biomarkers to build predictive nomogrames and decision-making tools. These will then better identify and assist therapeutic selection and planning while also reducing patient anxiety. Clinical and 3 year follow up data from 560 patients (as well as 5 year follow up from 248 patients) already exists from the Prostate Cancer Research Consortium BIMS database. This data combined with the assessment of the novel panel of serum markers in the corresponding serum from the patients will be used to build nomograms using appropriate statistical methods including various data reduction, feature selection, classification and cluster analysis techniques.

References:
  1. Fan Y, Murphy TB, Watson RW. digeR: a graphical user interface R package for analyzing 2D-DIGE data. Bioinformatics. 2009 Nov 15;25(22):3033-4. Epub 2009 Aug 25. PMID: 19706743
  2. Fanning DM, Yue F, Fitzpatrick JM, Watson RW. Novel predictive tools for Irish radical prostatectomy pathological outcomes: development and validation. Ir J Med Sci. 2009 Jul 14. [Epub ahead of print] PMID: 19597915
  3. Byrne JC, Downes MR, O'Donoghue N, O'Keane C, O'Neill A, Fan Y, Fitzpatrick JM, Dunn M, Watson RW. 2D-DIGE as a strategy to identify serum markers for the progression of prostate cancer. J Proteome Res. 2009 Feb;8(2):942-57. PMID: 19093873

Uncovering the evolution of mammalian sensory perception using next generation sequencing technologies

Supervisors: Dr. Emma Teeling, Prof. Desmond Higgins

Today, the landscape of comparative genomics and experimental genetics is rapidly changing and these paradigm shifts in molecular methodologies have resulted from a new generation of DNA sequencing technologies. However these technologies are not without their drawbacks. Genome assembly using these short read sequence (SRS) technologies has mainly occurred by incorporating a reference genome that has been annotated and sequenced using traditional 'Sanger' methods. De-novo sequence assembly, from data generated from an organism not sequenced before, poses a problem due the repeat nature of the non-coding regions within the genome. Both computational capabilities and biological skills are required to optimise and analyse these new data. This is a huge biological problem that must be addressed if scientists are to analyse emergent SRS data and interpret the vast quantities of data that will be generated in the ambitious sequencing projects such as Genome 10K.

Genomic sequence data from phylogenetically divergent mammals that live in unique environmental niches holds much ecological, evolutionary and biomedical information. Of all mammals, bats are perhaps the most unusual and specialised. They are successful nocturnal animals that exist in diverse ecological niches throughout the globe, feeding on insects, small mammals, fish, blood, nectar, fruit and pollen (Teeling et al. 2005). Their global success is largely attributed to their unique ability to fly and use sophisticated laryngeal echolocation or 'biosonar'. Bats use sound to develop an acoustic image of their environment and produce some of the loudest airborne vocalizations recorded in nature (Jones & Teeling 2006). However, it has been argued that bats have developed this acoustic sense at the expense of their other senses, such as vision and olfaction. Indeed, the age-old phrase 'as blind as a bat' refers to this very process. Therefore, due to its species level divergence in sensory perception and apparent evolutionary plasticity, the bat genome is ideally suited for examining the molecular mechanisms behind sensory perception.

During this PhD the student will investigate the use/limitations of next generation sequence data in a molecular comparative analysis of sensory perception in mammals, focusing particularly on bats. To do this the student will: (1) Generate and analyse whole retinal de-novo transcriptome sequence data using next generation sequences from six species of bat with varying visual capabilities. This work will be undertaking in conjunction with the Broad Institute and will allow us to benchmark our assembly methods with traditional assembly methods. (2) Amplify, sequence and annotate the largest mammalian multi-gene family, the Olfactory Receptor subgenome, from a myriad of mammals by combining traditional PCR methods with Illumina Next Generation sequencing and analyse these data in a novel bioinformatic framework. The project is part of an SFI funded project in Dr. Teeling's laboratory (http://batlab.ucd.ie) in collaboration with Prof. Higgin's laboratory (http://bioinf.ucd.ie).

References:
  1. Jones G. & E. C. Teeling. Evolution of Echolocation in Bats. (2006). Trends in Ecology and Evolution, 21: 149-156.
  2. Hayden S., M. Bekaert, T. A. Crider, S. Mariani, W. J. Murphy & E. C. Teeling. EcologicalAdaptation Determines Functional Mammalian Olfactory Subgenomes. (2010). Genome Research, 20: 1-9.
  3. Teeling E. C., M. S. Springer, O. Madsen, P. J. Bates, S. J. O'Brien, W. J. Murphy. (2005). A Molecular Phylogeny for Bats Illuminates Biogeography and the Fossil Record. Science, 307: 580-584.
  4. Zhao H., S. J. Rossiter, E. C. Teeling, C. Li, J. Cotton, S. Zhang. (2009). The Evolution of Vision in Nocturnal Mammals. Proceedings of the National Academy of Science, 106: 8980-8985.

Motif and domain determinants of protein localization in mammalian cells

Supervisors: Prof. Jez Simpson. Prof. Denis Shields

Co-localisation of proteins within cellular sub-compartments is critical for many protein-protein interactions, mediating cell signalling processes. The question is, "Why do proteins go where they go in the cell?" Our imaging methods allow the visualisation of proteins, based on fluorescent tags attached to both the N and C termini. However, N- and C-terminally tagged proteins do not always go to the same location. This suggests that elements at the N- and C-termini may be important for localization of these proteins. In this project, the cellular distribution of proteins will be investigated in relation to the presence and absence of proteins domains, and of computationally identified terminal motifs (http://bioware.ucd.ie/slimfinder). A key question that will be addressed is whether particular combinations of motifs and domains play a role in specificity of localization and co-complex membership within the protein interaction network. Predictions arising from this computational modelling of protein localisation will then be tested by experimentally visualising the location of protein constructs with mutations in terminal motifs and domains.

Protein modifications working as digital computing devices: The dynamics of Ring1B polyubiquitination and degradation

Supervisors: Prof. Boris Kholodenko, Prof. Walter Kolch

The controlled destruction of proteins plays an important role not only in keeping cells healthy, but also in transducing signals that determine the behaviour of cells. The critical protein modification is the attachment of a small protein called Ubiquitin by a process termed ubiquitination. Ubiquitination targets proteins for destruction. Recent discoveries have revealed much more intricate roles of ubiquitination. For instance, different forms of ubiquitination can switch protein activities on or off. The fact that ubiquitination can occur in different forms generates different states that can function akin to a biological computational device. This device is involved in the regulation of gene expression that regulates the differentiation of cells.

This project aims to explore the relationship between state spaces and biological functions of different ubiquitinations using a protein called Ring1B as paradigm. You will be working closely with experimental biologists and cutting edge life science technologies. The project is in collaboration with Aaron Ciechanover, who received the 2004 Nobel Prize in Chemistry for the discovery of the ubiquitin system. As result we aim to gain a new systems level understanding of how the modification of the Ring1B protein by different ubiquitin chains can function as a biological computer.

References
  1. Ben-Saadon, R., Zaaroor, D., Ziv, T. & Ciechanover, A. (2006) The polycomb protein Ring1B generates self atypical mixed ubiquitin chains required for its in vitro histone H2A ligase activity, Mol Cell. 24, 701-11.
  2. Chen, Z. J. & Sun, L. J. (2009) Nonproteolytic functions of ubiquitin in cell signaling, Mol Cell. 33, 275-86.
  3. Kaimachnikov, N. P. & Kholodenko, B. N. (2009) Toggle switches, pulses and oscillations are intrinsic properties of the Src activation/deactivation cycle, FEBS J. 276, 4102-18.
  4. Kholodenko, B. N. (2006) Cell-signalling dynamics in time and space, Nat Rev Mol Cell Biol. 7, 165-176.

Tracking faulty gene expression in cancer by dynamic mathematical modelling

Supervisors: Prof. Boris Kholodenko, Prof. Walter Kolch

Cells in an organism are immersed in an ocean of growth factors and hormones. How different external cues employ shared signalling pathways to generate specific cellular outcomes has been a long-standing puzzle in cell biology. This project aims to understand how the spatio-temporal dynamics of cell signalling pathways determines the expression of immediate early genes and eventually cell phenotypic responses, such as growth, division or differentiation. Major human diseases such as cancer emerge from altered signalling and gene function. Using a systems biology approach, consisting of iterative cycles of experimental data collection and model building, this project will develop mechanistic dynamic models of complex regulatory interactions between cytoplasmic and nuclear signalling processes and transcription factor expression responses. These models involve signalling-to-transcription feedforward loops and transcriptional feedback loops, which are difficult to understand without modelling. Using the models and a variety of mathematical techniques, the systems dynamics and responses to perturbations will be analysed to pinpoint the fragile nodes most amenable to therapeutic interference to treat cancer. The project will combine cutting edge wet and dry methods. Thus, the successful candidate will be embedded in an interdisciplinary team of modellers and biologists at Systems Biology Ireland.

References
  1. von Kriegsheim, A. et al. Cell fate decisions are specified by the dynamic ERK interactome. Nature Cell Biol 11, 1458-64 (2009).
  2. Kholodenko, B. N. (2006) Cell-signaling dynamics in time and space, Nature Rev Mol Cell Biol. 7, 165-176.

Molecular adaptation to signals from the environment: Mathematical modelling of the Epidermal Growth Factor (EGF) receptor internalisation pathways

Supervisors: Prof. Boris Kholodenko, Prof. Walter Kolch

Cells receive information about their environment when cell surface receptors bind extracellular signalling molecules. Cells adapt to signals when activated receptors are removed from the cell surface through a process called internalisation. Recent discoveries have demonstrated that differentially modified epidermal growth factor (EGF) receptors (EGFR) take distinct routes of internalisation, recycling back to the membrane or degradation. Receptor activation is followed by its autophosphorylation on tyrosine residues, but the critical modification of the receptor is the attachment of a small protein called ubiquitin in a process termed ubiquitination. Following activation, EGFR can be ubiquitinated on six distinct lysine residues within the kinase domain. Internalised EGFR molecules that are not ubitiquinated can preserve normal tyrosine phosphorylation patterns, but rapidly recycle to the plasma membrane. EGFR recycling preferentially occurs via a clathrin-mediated endocytotic (CME) pathway, whereas non-clathrin-endocytosis (NCE) targets EGFR for degradation. Since the CME pathway prolongs EGFR signalling, whereas the NCE pathway promotes receptor degradation, we hypothesize that selected perturbations to the EGFR ubiquitination machinery will have profound effects on cell signalling outcomes. This project will focus on the mathematical modelling of the molecular machinery of EGFR internalisation, ubiquitination, recycling and degradation, and it will be conducted in close collaboration with experimental colleagues in our laboratory, Italy and UK.

References
  1. Sigismund, S., Argenzio, E., Tosoni, D., Cavallaro, E., Polo, S. & Di Fiore, P. P. (2008) Clathrin-mediated internalization is essential for sustained EGFR signaling but dispensable for degradation, Dev Cell. 15, 209-19.
  2. Huang, F., Kirkpatrick, D., Jiang, X., Gygi, S. & Sorkin, A. (2006) Differential regulation of EGF receptor internalization and degradation by multiubiquitination within the kinase domain, Mol Cell. 21, 737-48.
  3. Birtwistle, M. R. & Kholodenko, B. N. (2009) Endocytosis and signalling: a meeting with mathematics, Mol Oncol. 3, 308-20.

How growth factors reprogram cell fate by regulating gene expression

Supervisors: Prof. Walter Kolch, Prof. Boris Kholodenko

Growth factors, such as EGF (Epidermal Growth Factor), which bind receptors at the cell surface, can reprogram the behaviour of cells by changing the expression of genes in the nucleus. This process is altered in many diseases such as cancer. Which genes are activated is critically depended on the duration of signalling (transient versus sustained), but the molecular mechanisms how different duration of EGF signalling specifies gene expression are still unknown. This is the topic of this project. The duration of EGF signalling is determined by the removal of the EGF receptor from the cell surface and internalization into intracellular compartments. This process is regulated by ubiquitination, a modification of the EGF receptor that is induced as a consequence of receptor activation. Using EGF receptor mutants which cannot be modified by ubiquitination, we will explore how ubiquitination changes the duration of signalling from the cell membrane to the nucleus, and how this affects gene expression and also cell proliferation. For this we will use (i) biochemical methods to measure the activity of signalling pathways that connect the EGF receptor at the cell surface with the nucleus; (ii) molecular biology methods to measure changes in gene expression; and (ii) imaging methods to follow the internalization of the EGF receptor. These data will be used to build a mathematical model that can simulate how the dynamics of signal duration changes gene expression. The modeling work will be carried out through close collaboration with computational scientists. Such collaborations are typical in the highly interdisciplinary environment at SBI. The candidate will primarily work experimentally, but also can participate in the modeling work.

References
  1. Birtwistle, M. R., Hatakeyama, M., Yumoto, N., Ogunnaike, B. A., Hoek, J. B. & Kholodenko, B. N. (2007) Ligand-dependent responses of the ErbB signaling network: experimental and modeling analyses, Mol Syst Biol. 3, 144.
  2. Birtwistle, M. R. & Kholodenko, B. N. (2009) Endocytosis and signalling: a meeting with mathematics, Mol Oncol. 3, 308-20.
  3. Sorkin, A. & Goh, L. K. (2009) Endocytosis and intracellular trafficking of ErbBs, Exp Cell Res. 315, 683-96.

Molecular signalling machines: Switches, oscillations and excitable behaviour of signalling networks

Supervisors: Prof. Boris Kholodenko, Prof. Walter Kolch

The fate of cells including their survival, growth and differentiation is regulated by growth factors and hormones. These external signals are typically received by receptors at the cell surface and processed by intricate intracellular signal transduction networks in order to generate a specific biological response. The nodes of these networks are made of protein complexes, where different proteins assemble into molecular machines that process the signal. Recent results show that the composition of these molecular machines can change dynamically, and that these changes are critical for determining cell fate. In this project we will focus on such a dynamically changing signalling machine that has the Raf-1 protein as core component. Raf-1 is a proto-oncogene that is frequently de-regulated in cancer and helps the cancer to survive, grow and spread. These functions are enabled by associations of Raf-1 with (1) the kinase MEK to stimulate cell proliferation; (2) the MST2 kinase to prevent cell death; and (3) the Rho-associated protein kinase to enable cell motility. We will build mathematical models that can capture the dynamic transitions between these different Raf-1 protein assemblies and predict the biological outcomes programmed by them. The candidate will work closely with theoretical and experimental colleagues in a highly interdisciplinary environment. The primary task will be the mathematical modelling, but there also is opportunity to engage in experimental work.

References
  1. von Kriegsheim, A., Baiocchi, D., Birtwistle, M., Sumpton, D., Bienvenut, W., Morrice, N., Yamada, K., Lamond, A., Kalna, G., Orton, R., Gilbert, D. & Kolch, W. (2009) Cell fate decisions are specified by the dynamic ERK interactome, Nat Cell Biol. 11, 1458-64.
  2. Kolch, W. (2005) Coordinating ERK/MAPK signalling through scaffolds and inhibitors, Nat Rev Mol Cell Biol. 6, 827-37.
  3. O'Neill, E., Rushworth, L., Baccarini, M. & Kolch, W. (2004) Role of the kinase MST2 in suppression of apoptosis by the proto-oncogene product Raf-1, Science. 306, 2267-70.
  4. Ehrenreiter, K., Piazzolla, D., Velamoor, V., Sobczak, I., Small, J. V., Takeda, J., Leung, T. & Baccarini, M. (2005) Raf-1 regulates Rho signaling and cell migration, J Cell Biol. 168, 955-64.
  5. Markevich, N., Hoek, J. B. & Kholodenko, B. N. (2004). Signaling switches and bistability arising from multisite phosphorylation in protein kinase cascades. J Cell Biology, 164, 353-359.
  6. Kholodenko, B. N. (2006) Cell-signaling dynamics in time and space, Nature Rev Mol Cell Biol. 7, 165-176.
  7. Markevich, N., Tsyganov MA, Hoek, J. B. & Kholodenko, B. N. (2006) Long-range signaling by phosphoprotein waves arising from bistability in protein kinase cascades. Mol Syst Biol. 2006; 2:61. PMID: 17102806
  8. Kaimachnikov, N. P. & Kholodenko, B. N. (2009) Toggle switches, pulses and oscillations are intrinsic properties of the Src activation/deactivation cycle, FEBS J. 276, 4102-18.

Spatiotemporal code of signal specificity and systems-level modeling of pathway crosstalk

Supervisors: Prof. Boris Kholodenko, Prof. Walter Kolch

Cells respond to a myriad of external cues using a limited number of signaling pathways that convert multiple inputs into diverse cellular decisions. A challenge in cell signaling research is to understand how different cues and receptors give rise to unique gene expression responses despite the promiscuous routing of signals through overlapping pathways. The current modeling and experimental project will connect cell response specificity with distinct temporal and spatial activation profiles of key effector kinases, such as the mitogen-activated protein kinases, protein kinase B/AKT, and critical transcriptional regulators (immediate early genes). A closely related topic, which will be explored in this project, is how pathway crosstalk influences the spatiotemporal activation profiles of these key regulators. In fact, during the past 25 years of signaling research, individual receptors and pathways have been extensively studied, yet how signaling networks integrate multiple cues is not understood.

This project will focus on understanding signal specificity and crosstalk in receptor tyrosine kinase networks stimulated by a variety of growth factors, including epidermal growth factor, insulin, insulin-like growth factor 1, fibroblast growth factor and some other stimuli. Central to the research will be the construction and analysis of mechanistic, compartmental ordinary differential equation models for signal propagation in time and space. The PhD candidate may choose to work only on modeling, or can also be involved with both modeling and experimental aspects, or work only on experimental problems. Modeling work will benefit from large amounts of quantitative data that will be generated specifically for modeling purposes by experimentalists working on the project.

References
  1. Kholodenko, B. N. (2006) Cell-signalling dynamics in time and space, Nature Rev Mol Cell Biol. 7, 165-176.
  2. Borisov, N., Aksamitiene, E., Kiyatkin, A., Legewie, S., Berkhout, J., Maiwald, T., Kaimachnikov, N. P., Timmer, J., Hoek, J. B. & Kholodenko, B. N. (2009) Systems-level interactions between insulin-EGF networks amplify mitogenic signaling, Mol Syst Biol. 5, 256.

Computational Studies of Glycosylated Antibodies and Antibody-Antigen Interactions

Supervisors: Prof. Robert J. Woods (NUIG), Prof. Pauline M. Rudd

Glycans, both in the form of polysaccharides or glycoconjugates (bound to proteins and lipids), are the most abundant class of biomolecules and are increasingly being implicated in human health. Glycosylation is by far the most important post-translational modification in terms of the number of proteins modified and the diversity generated. Since glycoproteins, glycolipids and glycan-binding proteins are frequently located on the cell's primary interface with the external environment, the cell surface, many biologically significant events can be attributed to glycan recognition. For this reason the rapidly expanding glycoscience field is being increasingly recognized as an important component of life science research.

Many protein-carbohydrate interactions are implicated in disease states including inflammation, autoimmunity and cancer as well as viral, bacterial and parasitic infections. However, our overall knowledge and understanding of such complex and diverse interactions is relatively poor. The project will aim to improve our understanding of antibody-antigen interactions in particular to elucidate the functional role of the carbohydrate component and the conformational properties. The study will address how information derived from experimental characterization of complex carbohydrates can be integrated with molecular modelling to yield a complete understanding of the structural and dynamic features including: conformational properties of oligosaccharides, the effects of protein-carbohydrate attachment and studies of protein-oligosaccharide interactions.

The Wood's lab offers expertise in structural glycobiology through collaboration, and training of students in the techniques of molecular modelling of olig- and polysaccharides, molecular dynamics and docking of oligosaccharides to protein receptors. The group have developed and actively maintain the GLYCAM portal that features a novel force field that can be used in conjunction with AMBER for computational studies of glycoproteins (http://glycam.ccrc.uga.edu/). The portal also includes a suite of utilities and libraries for building carbohydrates and parameters for molecular modelling and simulations to probe oligosaccharide and glycoprotein interaction and dynamics.

The Rudd group have developed a high-throughput HPLC platform for sequencing oligosaccharides structures which has been widely accepted over the last decade and is applicable in the areas of biomarker discovery, disease profiling, bio-therapeutic quality control and the bioprocessing industry. The project will utilise these technologies to sequence the glycan components of antibodies that will help support the modelling and simulation studies. The group also have an analytical bioinformatics programme that will be actively developed with the Woods group to develop unified resources for the glycoscience community.

Annotation and analysis of high-throughput sequences from human acrocentric Chromosomes

Supervisors: Prof. Brian McStay (NUIG), Prof. Cathal Seoighe (NUIG)

Almost a decade after the publication of the sequence of the human genome, the short arms of the acrocentric chromosomes (HSA13, 14, 15, 21 and 22) remain unsequenced. Each of these chromosomal arms contains an array of ribosomal gene repeats termed the nucleolar organiser region (NOR). The precise organization of rDNA repeats within NORs remains poorly understood but recent research using molecular combing techniques suggests that as much 30% of rDNA gene repeats may be inverted or rearranged. Such alternative rDNA repeat configurations are hypothesized to have important implications in cancer and aging. At NUI Galway we have developed protocols for preparing DNA from nucleoli isolated from human cells. This DNA is highly enriched for acrocentric chromosome short arm DNA, including NORs, as determined by back painting onto metaphase chromosomes. Molecular combing of nucleolar DNA confirms that a large proportion of rDNA repeats within NORs are rearranged (see Fig 1). We have used nucleolar DNA as a template in next generation (454) sequencing and have obtained 7.3x105 sequence reads of average length 287bp (i.e. 208 Mb of sequence) with approximately 9.5% of sequence reads mapping to ribosomal RNA genes. The objectives of this project will be to attempt the assembly or partial assembly of these high-throughput sequence reads and to develop a custom annotation pipeline. Assembled or individual sequence reads will then be used to investigate the structure of rDNA repeats as well as the sequences flanking the rDNA gene clusters. Coverage of the acrocentric chromosomes is sufficient (approximately four-fold) to provide a high probability of confirming or refuting the existence of rearranged rDNA gene clusters. Having characterised the structure of rearranged rDNA repeats, a series of PCR primers will be developed to permit the analysis of rearranged rDNA in human disease and aging.

To the extent possible, high-throughput sequence reads will also be used to investigate divergence of distinct rDNA gene clusters and spacer regions as well as sequences proximal and distal to the rDNA gene clusters.

Figure 1. Nucleoli were isolated from HeLa cells and resuspended in low-melting point agarose blocks. Blocks were digested with proteinase K. Blocks were melted and the agarose removed by digestion with agarase. Nucleolar DNA was then combed onto treated coverslips using a molecular combing apparatus supplied by Genomic Vision (Paris). After fixation probes were hybridised using 18S (green) and 28S (red) rDNA probes. Upper and lower panels show canonical (normal) and non-canonical (rearranged) repeats respectively.

Further reading
  1. McStay B, Grummt I (2008) The epigenetic regulation of ribosomal gene expression. Annu Rev Cell Dev Biol. 24:131-57.

The effects of combinations of inherited genetic variants on common diseases

Supervisors: Prof. Denis Shields, Dr. Derek Greene, Dr. Gerard Cagney (SFI funded: position available to start in April 2010 so early applications welcome)

Genetic variation is currently being studied using chips mapping 1 million polymorphisms in populations of thousands of patients. While synergy among genetic factors contributes to disease, the number of combinations is enormous, presenting an urgent research challenge. Furthermore, the influence of many variants on disease risk is very small. In this project we will develop approaches to map interacting genetic combinations in a variety of common inflammatory, neurological and cardiovascular diseases.

The project will first reduce the search space of pairwise interactions from a computationally intractable thousand billion interactions. This will rely on existing methods (filtering out variants which do not make a fractional contribution to disease on their own) and develop additional filters. The search space will also be reduced by focusing on interactions that are biologically plausible. For example, genes that regulate each-other and genes that are of similar function are more likely to interact to contribute to disease. We will also incorporate information from what is known about pairs of variants that interact to alter gene expression (RNA production from the DNA). We will apply these methods to a variety of diseases including Crohn's disease, autism, bipolar disorder (manic depression) and cardiovascular disease.

This project would suit a student with statistical, computational, or mathematical training and an interest in genetics.



© University College Dublin, 2010. Some public domain images obtained from NIH Image Bank