Development and Application of Comparative Gene Co-expression Network Methods in Brachypodium distachyon

Gene discovery and characterization is a long and labor-intensive process. Gene co-expression network analysis is a long-standing powerful approach that can strongly enrich signals within gene expression datasets to predict genes critical for many cellular functions. Leveraging this approach with a large number of transcriptome datasets does not yield a concomitant increase in network granularity. Independently generated datasets that describe gene expression in various tissues, developmental stages, times of day, and environments can carry conflicting co-expression signals. The gene expression responses of the model C3 grass Brachypodium distachyon to abiotic stress is characterized by a co-expression-based analysis, identifying 22 modules of genes, annotated with putative DNA regulatory elements and functional terms. A great deal of co-expression elasticity is found among the genes characterized therein. An algorithm, dGCNA, designed to determine statistically significant changes in gene-gene co-expression relationships is presented. The algorithm is demonstrated on the very well-characterized circadian system of Arabidopsis thaliana, and identifies potential strong signals of molecular interactions between a specific transcription factor and putative target gene loci. Lastly, this network comparison approach based on edge-wise similarities is demonstrated on many pairwise comparisons of independent microarray datasets, to demonstrate the utility of fine-grained network comparison, rather than amassing as large a dataset as possible. This approach identifies a set of 182 gene loci which are differentially expressed under drought stress, change their co-expression strongly under loss of thermocycles or high-salinity stress, and are associated with cell-cycle and DNA replication functions. This set of genes provides excellent candidates for the generation of rhythmic growth under thermocycles in Brachypodium distachyon

Characterisation of fission yeast DNA replication origins.

In many eukaryotic organisms the chromosomal origins of DNA replication (ORIs) are not characterised by a clearly defined consensus sequence. In this thesis using the fission yeast, for the first time I have carried out a genome-wide analysis to identify such ORIs during the mitotic and meiotic cell cycles. The data can be summarised as follows: a total of 401 ORIs were identified which were used 29 percent of the time during mitotic S-phase and were spaced every 31 kilobases (kb) on average. The same ORIs were used during pre-meiotic S-phase although with lower efficiency in most chromosomal regions. A further 503 potential ORIs were used less efficiently at eight percent of the time during mitotic S-phase. This totals 904 ORIs which were distributed at an average inter-origin distance of 14 kilobases (kb) throughout 12.5 megabases (Mb) of the three chromosomes of fission yeast. These data support the idea of a continuum of ORI activity. The 401 efficient ORI loci contained A+T-rich regions located between genes, and these intergenic regions were typically larger than average. ORIs were not defined by a strict sequence consensus but the presence of AT-hook binding sequences. When the initiation factors Cdc18 and Cdt1 were over-expressed, regions of DNA containing particularly efficient ORIs with exceptionally large AT-hook binding domains became over-amplified, suggesting that interactions between these factors and efficient ORIs may be important for the mechanism ensuring that an ORI only fires once in each S-phase

Horizontal gene transfer dynamics and distribution of fitness effects during microbial in silico evolution

<p>Abstract</p> <p>Background</p> <p>Horizontal gene transfer (HGT) is a process that facilitates the transfer of genetic material between organisms that are not directly related, and thus can affect both the rate of evolution and emergence of traits. Recent phylogenetic studies reveal HGT events are likely ubiquitous in the Tree of Life. However, our knowledge of HGT's role in evolution and biological organization is very limited, mainly due to the lack of ancestral evolutionary signatures and the difficulty to observe complex evolutionary dynamics in a laboratory setting. Here, we utilize a multi-scale microbial evolution model to comprehensively study the effect of HGT on the evolution of complex traits and organization of gene regulatory networks.</p> <p>Results</p> <p>Large-scale simulations reveal a distinct signature of the Distribution of Fitness Effect (DFE) for HGT events: during evolution, while mutation fitness effects become more negative and neutral, HGT events result in a balanced effect distribution. In either case, lethal events are significantly decreased during evolution (33.0% to 3.2%), a clear indication of mutational robustness. Interestingly, evolution was accelerated when populations were exposed to correlated environments of increasing complexity, especially in the presence of HGT, a phenomenon that warrants further investigation. High HGT rates were found to be disruptive, while the average transferred fragment size was linked to functional module size in the underlying biological network. Network analysis reveals that HGT results in larger regulatory networks, but with the same sparsity level as those evolved in its absence. Observed phenotypic variability and co-existing solutions were traced to individual gain/loss of function events, while subsequent re-wiring after fragment integration was necessary for complex traits to emerge.</p

Role of ppGpp in regulating global gene expression in Escherichia coli.

Bacteria grow when nutrient availability supports basic biochemical requirements and remain in stationary phase when basic needs go unmet. This deceptively simple phenomenon requires the orchestrated expression of thousands of genes. Free-living bacteria use a nucleotide second messenger, ppGpp, as a physiological signal and effector to appropriately coordinate global gene expression according to the nutritional quality of the environment. Over the last four decades, expression of many individual genes has been tied to the absence or presence of ppGpp, yet the full scope of gene expression mediated by ppGpp remained undefined. This dissertation defines the role of ppGpp in regulating global gene expression in a model bacterium, Escherichia coli

Using single-cell RNA-seq to assess the effect of common genetic variants on gene expression during development

Over the last fifteen years, genome-wide association studies (GWAS) have been used to identify thousands of DNA variants associated with complex traits and diseases, by exploiting naturally occurring genetic variation in large populations of individuals. More recently, similar approaches have been applied to RNA sequencing (RNA-seq) data to find variants associated with expression level, called expression quantitative trait loci (eQTL). Recent advances in experimental techniques have provided an unprecedented opportunity to measure gene expression at the single cell level, and the chance to study cellular heterogeneity. This represents a remarkable advance over traditional bulk sequencing methods, particularly to study cell fate commitment events in development. The challenge of studying early human development is partially overcome by advances in stem cell technologies. In particular, induced pluripotent stem cells (iPSCs) and cells derived therefrom represent a fantastic system to study development in vitro. In this thesis, I investigate the computational challenges of using single cell expression profiles to perform expression quantitative trait locus (eQTL) mapping, and provide suitable approaches for the identification of cell type and context-specific eQTL using single cell expression profiles. I further explore the application of such methods across a range of human iPSC-derived cell types, using data from the human induced pluripotent stem cell initiative (HipSci) project.Funding was provided via the EMBL international PhD programme

Transcriptional profiling of Aspergillus niger

The industrially important fungus Aspergillus niger feeds naturally on decomposing plant material, of which a significant proportion is lipid. Examination of the A. niger genome sequence suggested that all proteins required for metabolic conversion of lipids are present, including 63 predicted lipases. In contrast to polysaccharide-degrading enzyme networks, not much is known about the signaling and regulatory processes that control lipase expression and activity in fungi. This project was aimed to gain better understanding of lipid degradation mechanisms and how this process is regulated in A. niger, primarily via assessment of its gene transcription levels. Minimizing biological and technical variation is crucial for experiments in which transcription levels are determined, such as microarray and quantitative real-time PCR experiments. However, A. niger is difficult to cultivate in a reproducible way due to its filamentous growth. In addition, the complex processing steps of transcriptomics technologies add non-experimental variation to the biological variation. To reduce this data noise, robust protocols based on a batch-fermentation setup were developed. Variation in this setup was surveyed by examining the fungal transcriptional response towards a pulse of D-xylose. The sources of non-experimental variation were described by variance components analysis. Two-thirds of total variation stems from differences in routine handling of fermentations, but in absolute terms this variation is low. As D-xylose is an inducer of the xylanolytic system, the high reproducibility of cultures for the first time allowed a detailed description of the global fungal transcriptional response towards D-xylose using microarrays. The transcriptional response towards three plant derived oils was examined in another study. Both olive oil and a wheat-gluten extracted oil induce the transcription of genes involved in lipid metabolism and peroxisome assembly, albeit with different expression profiles. The third oil, a plant membrane lipid, did not trigger a transcriptional response. Microarray data are related to the physiology of the fungus. To better understand the general principles that underlie gene regulation and gene transcription, microarray data from cultures grown under mildly and strongly perturbed conditions were analyzed for co-expression of genes. Despite the diverse culturing conditions, co-expressed gene modules could be identified. Some of these modules can be related to biological functions. For some modules, conserved promoter elements were identified, which suggests that genes in these modules are regulated on a transcriptional level. The work described in this thesis shows that (i) high-quality -omics data for A. niger can be generated; that (ii) analysis and interpretation of these data enhances our understanding of the xylanolytic and lipid metabolic regulons; and (iii) that these data give insight into the regulatory mechanisms of this fungus. <br/

INTEGRATED MOLECULAR PROFILING FOR ANALYZING AND PREDICTING THERAPEUTIC MECHANISM, RESPONSE, BIOMARKER AND TARGET

Ph.DDOCTOR OF PHILOSOPH

In Vitro and In Vivo Models of Colorectal Cancer for Clinical Application

The Special Issue "In Vitro and In Vivo Models of Colorectal Cancer for Clinical Application", edited by Marta Baiocchi and Ann Zeuner for Cancers, collects original research papers and reviews, depicting the current state and the perspectives of CRC models for preclinical and translational research. Original research papers published in this issue focus on some of the hottest topics in CRC research, such as circulating tumor cells, epigenetic regulation of stemness states, new therapeutic targets, molecular CRC classification and experimental CRC models such as organoids and PDXs. Additionally, four reviews on CRC stem cells, immunotherapy and drug discovery provide an updated viewpoint on key topics linking benchtop to bedside research in CRC

Genetic variation in DNA repair proteins modifies the course of Huntington’s disease

Huntington’s disease (HD) is caused by a CAG repeat expansion in HTT on chromosome 4. Onset and progression are inversely correlated with repeat length, but a significant proportion of the variability in each is due to modifiers elsewhere in the genome. Recent genome-wide association studies have identified the DNA repair genes FAN1 and MSH3 as modifiers of onset and progression respectively. This thesis finds that variants associated with HD disease course also influence onset in other polyglutamine diseases, suggesting a shared pathogenic mechanism involving DNA repair. In blood from HD patients there is significant transcriptional dysregulation, particularly involving immune, metabolic and DNA repair pathways, which correlates with disease severity, parallels dysregulation seen in the most affected HD brain regions and overlaps with Alzheimer’s disease. To study the role of DNA repair, several cell models of somatic instability were developed, including patient-derived lymphoblasts and induced pluripotent stem cells, which show exponential repeat expansion that continues in differentiated medium spiny neurons (MSNs). In a FAN1 knockout U20S cell model of HD, FAN1 is shown to protect against repeat instability, and this function is dependent on protein concentration and CAG repeat length, but does not require its nuclease activity. shRNA-mediated FAN1 knockdown accelerates repeat expansion in both patient-derived iPSCs and MSNs. Through chromatin immunoprecipitation, FAN1 is shown to bind, but not specifically target, CAG repeat DNA. AAV9-mediated miRNA Fan1 knockdown in the striatum and liver of R6/2 mice did not accelerate repeat expansion, likely because only 23% knockdown was achieved. Illumina sequencing of the MSH3 region that influences HD progression identified a repeat variant that is associated with decreased MSH3 expression, reduced somatic expansion, delayed onset and slower progression in HD and myotonic dystrophy type 1 (DM1). These results suggest MSH3 promotes and FAN1 protects against repeat instability, which in turn influences the course of repeat expansion diseases

Personalized Nutrition

Awareness of the influence of our genetic variation to dietary response (nutrigenetics) and how nutrients may affect gene expression (nutrigenomics) is prompting a revolution in the field of nutrition. Nutrigenetics/Nutrigenomics provide powerful approaches to unravel the complex relationships among nutritional molecules, genetic variants and the biological system. This publication contains selected papers from the ‘3rd Congress of the International Society of Nutrigenetics/Nutrigenomics’ held in Bethesda, Md., in October 2009. The contributions address frontiers in nutrigenetics, nutrigenomics, epigenetics, transcriptomics as well as non-coding RNAs and posttranslational gene regulations in various diseases and conditions. In addition to scientific studies, the challenges and opportunities facing governments, academia and the industry are included