Construction of a global map of human gene expression : the process, tools and analysis

This thesis studies human gene expression space using high throughput gene expression data from DNA microarrays. In molecular biology, high throughput techniques allow numerical measurements of expression of tens of thousands of genes simultaneously. In a single study, this data is traditionally obtained from a limited number of sample types with a small number of replicates. For organism-wide analysis, this data has been largely unavailable and the global structure of human transcriptome has remained unknown. This thesis introduces a human transcriptome map of different biological entities and analysis of its general structure. The map is constructed from gene expression data from the two largest public microarray data repositories, GEO and ArrayExpress. The creation of this map contributed to the development of ArrayExpress by identifying and retrofitting the previously unusable and missing data and by improving the access to its data. It also contributed to creation of several new tools for microarray data manipulation and establishment of data exchange between GEO and ArrayExpress. The data integration for the global map required creation of a new large ontology of human cell types, disease states, organism parts and cell lines. The ontology was used in a new text mining and decision tree based method for automatic conversion of human readable free text microarray data annotations into categorised format. The data comparability and minimisation of the systematic measurement errors that are characteristic to each lab- oratory in this large cross-laboratories integrated dataset, was ensured by computation of a range of microarray data quality metrics and exclusion of incomparable data. The structure of a global map of human gene expression was then explored by principal component analysis and hierarchical clustering using heuristics and help from another purpose built sample ontology. A preface and motivation to the construction and analysis of a global map of human gene expression is given by analysis of two microarray datasets of human malignant melanoma. The analysis of these sets incorporate indirect comparison of statistical methods for finding differentially expressed genes and point to the need to study gene expression on a global level.

Computational Methods for Locating and Analyzing Conserved Gene Regulatory DNA Elements

This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome.

Otolith morphology of four mackerel species (Scomberomorus spp.) in Australia: Species differentiation and prediction for fisheries monitoring and assessment

Four species of large mackerels (Scomberomorus spp.) co-occur in the waters off northern Australia and are important to fisheries in the region. State fisheries agencies monitor these species for fisheries assessment; however, data inaccuracies may exist due to difficulties with identification of these closely related species, particularly when specimens are incomplete from fish processing. This study examined the efficacy of using otolith morphometrics to differentiate and predict among the four mackerel species off northeastern Australia. Seven otolith measurements and five shape indices were recorded from 555 mackerel specimens. Multivariate modelling including linear discriminant analysis (LDA) and support vector machines, successfully differentiated among the four species based on otolith morphometrics. Cross validation determined a predictive accuracy of at least 96% for both models. An optimum predictive model for the four mackerel species was an LDA model that included fork length, feret length, feret width, perimeter, area, roundness, form factor and rectangularity as explanatory variables. This analysis may improve the accuracy of fisheries monitoring, the estimates based on this monitoring (i.e. mortality rate) and the overall management of mackerel species in Australia.

Gene flow from Corymbia hybrids in northern New South Wales

Some of the most productive taxa for forestry are interspecific F1 hybrids grown as exotics in the tropics and subtropics. Attributes of resilience, adaptability and vigour which engender the hybrids for wood production, may also exacerbate the risk they present from gene flow to native species gene pools or to local ecologies as weeds. To determine the biological and genetic factors that influence the extent of hybridisation, we examine the distribution and genealogy of wildlings surrounding plantings of locally-exotic Corymbia torelliana (Section Cadageria) near native C. henryi (Section Maculatae) in northern New South Wales. Our study showed pre-mating and pre- and post-zygotic barriers were incomplete, with in situ generation and natural establishment of both F1 hybrids (n = 3) and advanced generation hybrids under the disturbed conditions bordering native forest. As hybrids were located on alluvial flats exposed to frost, they also likely have an extended ecological range relative to native C. henryi. Despite the likely generation of large viable seed crops on F1 trees at the site over many years, establishment success and survival of advanced generation hybrids may be low, as only 5 immature and no mature advanced generation hybrids were identified. Propagation and genetic analysis of a seed crop from one F1 wildling showed early survival and vigour of seedlings in cultivation was high, and that at least for some F1 in some seasons, backcrossing to the recurrent native C. henryi parent is favoured (60%), whereas selfing (10%) and crossing with other F1 (30%) was less frequent. Transport of seed by stingless bees probably accounted for long distance dispersal from C. torelliana, but this mechanism does not appear to supplement gravity-dispersal of seed from the F1. Coupled with other evidence from studies of bee behaviour, controlled pollination in Corymbia sp., and long-term fitness in second generation eucalypt hybrids, we anticipate gene flow via pollen rather than seed will be the greater challenge for managing the risk of introgression of C. torelliana ancestry into native species from the planted F1 hybrid. If large sources of F1 pollen become available to compete with native pollen, gene flow will probably be frequent and hybrids may establish in disturbed conditions and in habitats beyond the ecological range of their native parent. Further study is needed to determine the degree to which outbreeding depression and poor survival inhibits on-going gene flow.

Identification of I-7 expands the repertoire of genes for resistance to Fusarium wilt in tomato to three resistance gene classes

The tomato I-3 and I-7 genes confer resistance to Fusarium oxysporum f. sp. lycopersici (Fol) race 3 and were introgressed into the cultivated tomato, Solanum lycopersicum, from the wild relative Solanum pennellii. I-3 has been identified previously on chromosome 7 and encodes an S-receptor-like kinase, but little is known about I-7. Molecular markers have been developed for the marker-assisted breeding of I-3, but none are available for I-7. We used an RNA-seq and single nucleotide polymorphism (SNP) analysis approach to map I-7 to a small introgression of S. pennellii DNA (c. 210 kb) on chromosome 8, and identified I-7 as a gene encoding a leucine-rich repeat receptor-like protein (LRR-RLP), thereby expanding the repertoire of resistance protein classes conferring resistance to Fol. Using an eds1 mutant of tomato, we showed that I-7, like many other LRR-RLPs conferring pathogen resistance in tomato, is EDS1 (Enhanced Disease Susceptibility 1) dependent. Using transgenic tomato plants carrying only the I-7 gene for Fol resistance, we found that I-7 also confers resistance to Fol races 1 and 2. Given that Fol race 1 carries Avr1, resistance to Fol race 1 indicates that I-7-mediated resistance, unlike I-2- or I-3-mediated resistance, is not suppressed by Avr1. This suggests that Avr1 is not a general suppressor of Fol resistance in tomato, leading us to hypothesize that Avr1 may be acting against an EDS1-independent pathway for resistance activation. The identification of I-7 has allowed us to develop molecular markers for marker-assisted breeding of both genes currently known to confer Fol race 3 resistance (I-3 and I-7). Given that I-7-mediated resistance is not suppressed by Avr1, I-7 may be a useful addition to I-3 in the tomato breeder's toolbox.

Molecular Breeding for Complex Adaptive Traits: How Integrating Crop Ecophysiology and Modelling Can Enhance Efficiency

Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.

Comparison of Prediction Based LSF Quantization Methods using Split VQ

Further improvement in performance, to achieve near transparent quality LSF quantization, is shown to be possible by using a higher order two dimensional (2-D) prediction in the coefficient domain. The prediction is performed in a closed-loop manner so that the LSF reconstruction error is the same as the quantization error of the prediction residual. We show that an optimum 2-D predictor, exploiting both inter-frame and intra-frame correlations, performs better than existing predictive methods. Computationally efficient split vector quantization technique is used to implement the proposed 2-D prediction based method. We show further improvement in performance by using weighted Euclidean distance.

Rhizoctonia -Scots pine interactions: detection, impact on seedling performance and host defence gene response

Rhizoctonia spp. are ubiquitous soil inhabiting fungi that enter into pathogenic or symbiotic associations with plants. In general Rhizoctonia spp. are regarded as plant pathogenic fungi and many cause root rot and other plant diseases which results in considerable economic losses both in agriculture and forestry. Many Rhizoctonia strains enter into symbiotic mycorrhizal associations with orchids and some hypovirulent strains are promising biocontrol candidates in preventing host plant infection by pathogenic Rhizoctonia strains. This work focuses on uni- and binucleate Rhizoctonia (respectively UNR and BNR) strains belonging to the teleomorphic genus Ceratobasidium, but multinucleate Rhizoctonia (MNR) belonging to teleomorphic genus Thanatephorus and ectomycorrhizal fungal species, such as Suillus bovinus, were also included in DNA probe development work. Strain specific probes were developed to target rDNA ITS (internal transcribed spacer) sequences (ITS1, 5.8S and ITS2) and applied in Southern dot blot and liquid hybridization assays. Liquid hybridization was more sensitive and the size of the hybridized PCR products could be detected simultaneously, but the advantage in Southern hybridization was that sample DNA could be used without additional PCR amplification. The impacts of four Finnish BNR Ceratorhiza sp. strains 251, 266, 268 and 269 were investigated on Scot pine (Pinus sylvestris) seedling growth, and the infection biology and infection levels were microscopically examined following tryphan blue staining of infected roots. All BNR strains enhanced early seedling growth and affected the root architecture, while the infection levels remained low. The fungal infection was restricted to the outer cortical regions of long roots and typical monilioid cells detected with strain 268. The interactions of pathogenic UNR Ceratobasidium bicorne strain 1983-111/1N, and endophytic BNR Ceratorhiza sp. strain 268 were studied in single or dual inoculated Scots pine roots. The fungal infection levels and host defence-gene activity of nine transcripts [phenylalanine ammonia lyase (pal1), silbene synthase (STS), chalcone synthase (CHS), short-root specific peroxidase (Psyp1), antimicrobial peptide gene (Sp-AMP), rapidly elicited defence-related gene (PsACRE), germin-like protein (PsGER1), CuZn- superoxide dismutase (SOD), and dehydrin-like protein (dhy-like)] were measured from differentially treated and un-treated control roots by quantitative real time PCR (qRT-PCR). The infection level of pathogenic UNR was restricted in BNR- pre-inoculated Scots pine roots, while UNR was more competitive in simultaneous dual infection. The STS transcript was highly up-regulated in all treated roots, while CHS, pal1, and Psyp1 transcripts were more moderately activated. No significant activity of Sp-AMP, PsACRE, PsGER1, SOD, or dhy-like transcripts were detected compared to control roots. The integrated experiments presented, provide tools to assist in the future detection of these fungi in the environment and to understand the host infection biology and defence, and relationships between these interacting fungi in roots and soils. This study further confirms the complexity of the Rhizoctonia group both phylogenetically and in their infection biology and plant host specificity. The knowledge obtained could be applied in integrated forestry nursery management programmes.

Pathogenicity, functional significance and clinical phenotype of mismatch repair gene MSH2 variants found in cancer patients

DNA ja siinä sijaitsevat geenit ohjaavat kaikkea solujen toimintaa. DNA-molekyyleihin kuitenkin kertyy mutaatioita sekä ympäristön vaikutuksen, että solujen oman toiminnan tuloksena. Mikäli virheitä ei korjata, saattaa tuloksena olla solun muuttuminen syöpäsoluksi. Soluilla onkin käytössä useita DNA-virheiden korjausmekanismeja, joista yksi on ns. mismatch repair (MMR). MMR vastaa DNA:n kahdentumisessa syntyvien virheiden korjauksesta. Periytyvät mutaatiot geeneissä, jotka vastaavat MMR-proteiinien rakentamisesta, aiheuttavat ongelmia DNA:n korjauksessa ja altistavat kantajansa periytyvälle ei-polypoottiselle paksusuolisyöpäoireyhtymälle (hereditary nonpolyposis colorectal cancer, HNPCC). Yleisimmin mutatoituneet MMR-geenit ovat MLH1 ja MSH2. HNPCC periytyy vallitsevasti, eli jo toiselta vanhemmalta peritty geenivirhe altistaa syövälle. MMR-geenivirheen kantaja sairastuu syöpään elämänsä aikana suurella todennäköisyydellä, ja sairastumisikä on vain noin 40 vuotta. Syövälle altistavan geenivirheen löytäminen mutaation kantajilta on hyvin tärkeää, sillä säännöllinen seuranta mahdollistaa kehittymässä olevan kasvaimen havaitsemisen ja poistamisen jo aikaisessa vaiheessa. Tämän on osoitettu alentavan syöpäkuolleisuutta merkittävästi. Varma tieto altistuksen alkuperästä on tärkeä myös niille syöpäsuvun jäsenille, jotka eivät kanna kyseistä mutaatiota. Syövälle altistavien mutaatioiden ohella MMR-geeneistä löydetään säännöllisesti muutoksia, jotka ovat normaalia henkilöiden välistä geneettistä vaihtelua, eikä niiden oleteta lisäävän syöpäaltistusta. Altistavien mutaatioiden erottaminen näistä neutraaleista variaatioista on vaikeaa, mutta välttämätöntä altistuneiden tehokkaan seurannan varmistamiseksi. Tässä väitöskirjassa tutkittiin 18:a MSH2 -geenin mutaatiota. Mutaatiot oli löydetty perheistä, joissa esiintyi paljon syöpiä, mutta niiden vaikutus DNA:n korjaustehoon ja syöpäaltistukseen oli epäselvä. Työssä tutkittiin kunkin mutaation vaikutusta MSH2-proteiinin normaaliin toimintaan, ja tuloksia verrattiin potilaiden ja sukujen kliinisiin tietoihin. Tutkituista mutaatiosta 12 aiheutti puutteita MMR-korjauksessa. Nämä mutaatiot tulkittiin syövälle altistaviksi. Analyyseissä normaalisti toimineet 4 mutaatiota eivät todennäköisesti ole syynä syövän syntyyn kyseisillä perheillä. Tulkinta jätettiin avoimeksi 2 mutaation kohdalla. Tutkimuksesta hyötyivät suoraan kuvattujen mutaatioiden kantajaperheet, joiden geenivirheen syöpäaltistuksesta saatiin tietoa, mahdollistaen perinnöllisyysneuvonnan ja seurannan kohdentamisen sitä tarvitseville. Työ selvensi myös mekanismeja, joilla mutatoitunut MSH2-proteiini voi menettää toimintakykynsä.

Genomic approach to organ-specific growth control

Growth is a fundamental aspect of life cycle of all organisms. Body size varies highly in most animal groups, such as mammals. Moreover, growth of a multicellular organism is not uniform enlargement of size, but different body parts and organs grow to their characteristic sizes at different times. Currently very little is known about the molecular mechanisms governing this organ-specific growth. The genome sequencing projects have provided complete genomic DNA sequences of several species over the past decade. The amount of genomic sequence information, including sequence variants within species, is constantly increasing. Based on the universal genetic code, we can make sense of this sequence information as far as it codes proteins. However, less is known about the molecular mechanisms that control expression of genes, and about the variations in gene expression that underlie many pathological states in humans. This is caused in part by lack of information about the second genetic code that consists of the binding specificities of transcription factors and the combinatorial code by which transcription factor binding sites are assembled to form tissue-specific and/or ligand-regulated enhancer elements. This thesis presents a high-throughput assay for identification of transcription factor binding specificities, which were then used to measure the DNA binding profiles of transcription factors involved in growth control. We developed ‘enhancer element locator’, a computational tool, which can be used to predict functional enhancer elements. A genome-wide prediction of human and mouse enhancer elements generated a large database of enhancer elements. This database can be used to identify target genes of signaling pathways, and to predict activated transcription factors based on changes in gene expression. Predictions validated in transgenic mouse embryos revealed the presence of multiple tissue-specific enhancers in mouse c- and N-Myc genes, which has implications to organ specific growth control and tumor type specificity of oncogenes. Furthermore, we were able to locate a variation in a single nucleotide, which carries a susceptibility to colorectal cancer, to an enhancer element and propose a mechanism by which this SNP might be involved in generation of colorectal cancer.

Computational methods for the prediction of the structure and interactions of coiled-coil peptides

The past several years have seen significant advances in the development of computational methods for the prediction of the structure and interactions of coiled-coil peptides. These methods are generally based on pairwise correlations of amino acids, helical propensity, thermal melts and the energetics of sidechain interactions, as well as statistical patterns based on Hidden Markov Model (HMM) and Support Vector Machine (SVM) techniques. These methods are complemented by a number of public databases that contain sequences, motifs, domains and other details of coiled-coil structures identified by various algorithms. Some of these computational methods have been developed to make predictions of coiled-coil structure on the basis of sequence information; however, structural predictions of the oligomerisation state of these peptides still remains largely an open question due to the dynamic behaviour of these molecules. This review focuses on existing in silico methods for the prediction of coiled-coil peptides of functional importance using sequence and/or three-dimensional structural data.