L-rhamnose-1-dehydrogenase gene and L-rhamnose catabolism in the yeast Pichia stipitis

The purpose of this work was to identify some of the genes of the catabolic route of L-rhamnose in the yeast Pichia stipitis. There are at least two distinctly different pathways for L-rhamnose catabolism. The one described in bacteria has phosphorylated intermediates and the enzymes and the genes of this route have been described. The pathway described in yeast does not have phosphorylated intermediates. The intermediates and the enzymes of this pathway are known but none of the genes have been identified. The work was started by purifying the L-rhamnose dehydrogenase, which oxidates L-rhamnose to rhamnonic acid-gamma-lactone. NAD is used as a cofactor in this reaction. A DEAE ion exchange column was used for purification. The active fraction was further purified using a non-denaturing PAGE and the active protein identified by zymogram staining. In the last step the protein was separated in a SDS-PAGE, the protein band trypsinated and analysed by MALDI-TOF MS. This resulted in the identification of the corresponding gene, RHA1, which was then, after a codon change, expressed in Saccharomyces cerevisiae. Also C- or N-terminal histidine tags were added but as the activity of the enzyme was lost or strongly reduced these were not used. The kinetic properties of the protein were analysed in the cell extract. Substrate specifity was tested with different sugars; L-rhamnose, L-lyxose and L-mannose were oxidated by the enzyme. Vmax values were 180 nkat/mg, 160 nkat/mg and 72 nkat/mg, respectively. The highest affinity was towards L-rhamnose, the Km value being 0.9 mM. Lower affinities were obtained with L-lyxose, Km 4.3 mM, and L-mannose Km 25 mM. Northern analysis was done to study the transcription of RHA1 with different carbon sources. Transcription was observed only on L-rhamnose suggesting that RHA1 expression is L-rhamnose induced. A RHA1 deletion cassette for P. stipitis was constructed but the cassette had integrated randomly and not targeted to delete the RHA1 gene. Enzyme assays for L-lactaldehyde dehydrogenase were done similarly to L-rhamnose dehydrogenase assays. NAD is used as a cofactor also in this reaction where L-lactaldehyde is oxidised to L-lactate. The observed enzyme activities were very low and the activity was lost during the purification procedures.

Sequence variation in the putative effector gene SIX8 facilitates molecular differentiation of Fusarium oxysporum f. sp. cubense

Fusarium oxysporum f. sp. cubense (Foc), causal agent of fusarium wilt of banana, is among the most destructive pathogens of banana and plantain. The development of a molecular diagnostic capable of reliably distinguishing between the various races of the pathogen is of key importance to disease management. However, attempts to distinguish isolates using the standard molecular loci typically used for fungal phylogenetics have been complicated by a poor correlation between phylogeny and pathogenicity. Among the available alternative loci are several putative effector genes, known as SIX genes, which have been successfully used to differentiate the three races of F. oxysporum f. sp. lycopersici. In this study, an international collection of Foc isolates was screened for the presence of the putative effector SIX8. Using a PCR and sequencing approach, variation in Foc-SIX8 was identified which allowed race 4 to be differentiated from race 1 and 2 isolates, and tropical and subtropical race 4 isolates to be distinguished from one another.

Fungal community structure in disease suppressive soils assessed by 28S LSU gene sequencing

Natural biological suppression of soil-borne diseases is a function of the activity and composition of soil microbial communities. Soil microbe and phytopathogen interactions can occur prior to crop sowing and/or in the rhizosphere, subsequently influencing both plant growth and productivity. Research on suppressive microbial communities has concentrated on bacteria although fungi can also influence soil-borne disease. Fungi were analyzed in co-located soils 'suppressive' or 'non-suppressive' for disease caused by Rhizoctonia solani AG 8 at two sites in South Australia using 454 pyrosequencing targeting the fungal 28S LSU rRNA gene. DNA was extracted from a minimum of 125 g of soil per replicate to reduce the micro-scale community variability, and from soil samples taken at sowing and from the rhizosphere at 7 weeks to cover the peak Rhizoctonia infection period. A total of ∼994,000 reads were classified into 917 genera covering 54% of the RDP Fungal Classifier database, a high diversity for an alkaline, low organic matter soil. Statistical analyses and community ordinations revealed significant differences in fungal community composition between suppressive and non-suppressive soil and between soil type/location. The majority of differences associated with suppressive soils were attributed to less than 40 genera including a number of endophytic species with plant pathogen suppression potentials and mycoparasites such as Xylaria spp. Non-suppressive soils were dominated by Alternaria , Gibberella and Penicillum. Pyrosequencing generated a detailed description of fungal community structure and identified candidate taxa that may influence pathogen-plant interactions in stable disease suppression. © 2014 Penton et al.

Resistance gene analogues in sugarcane and sorghum and their association with quantitative trait loci for rust resistance

Fifty-four different sugarcane resistance gene analogue (RGA) sequences were isolated, characterized, and used to identify molecular markers linked to major disease-resistance loci in sugarcane. Ten RGAs were identified from a sugarcane stem expressed sequence tag (EST) library; the remaining 44 were isolated from sugarcane stem, leaf, and root tissue using primers designed to conserved RGA motifs. The map location of 31 of the RGAs was determined in sugarcane and compared with the location of quantitative trait loci (QTL) for brown rust resistance. After 2 years of phenotyping, 3 RGAs were shown to generate markers that were significantly associated with resistance to this disease. To assist in the understanding of the complex genetic structure of sugarcane, 17 of the 31 RGAs were also mapped in sorghum. Comparative mapping between sugarcane and sorghum revealed syntenic localization of several RGA clusters. The 3 brown rust associated RGAs were shown to map to the same linkage group (LG) in sorghum with 2 mapping to one region and the third to a region previously shown to contain a major rust-resistance QTL in sorghum. These results illustrate the value of using RGAs for the identification of markers linked to disease resistance loci and the value of simultaneous mapping in sugarcane and sorghum.

Methods to improve gene signal: Application to cDNA microarrays

Microarrays are high throughput biological assays that allow the screening of thousands of genes for their expression. The main idea behind microarrays is to compute for each gene a unique signal that is directly proportional to the quantity of mRNA that was hybridized on the chip. A large number of steps and errors associated with each step make the generated expression signal noisy. As a result, microarray data need to be carefully pre-processed before their analysis can be assumed to lead to reliable and biologically relevant conclusions. This thesis focuses on developing methods for improving gene signal and further utilizing this improved signal for higher level analysis. To achieve this, first, approaches for designing microarray experiments using various optimality criteria, considering both biological and technical replicates, are described. A carefully designed experiment leads to signal with low noise, as the effect of unwanted variations is minimized and the precision of the estimates of the parameters of interest are maximized. Second, a system for improving the gene signal by using three scans at varying scanner sensitivities is developed. A novel Bayesian latent intensity model is then applied on these three sets of expression values, corresponding to the three scans, to estimate the suitably calibrated true signal of genes. Third, a novel image segmentation approach that segregates the fluorescent signal from the undesired noise is developed using an additional dye, SYBR green RNA II. This technique helped in identifying signal only with respect to the hybridized DNA, and signal corresponding to dust, scratch, spilling of dye, and other noises, are avoided. Fourth, an integrated statistical model is developed, where signal correction, systematic array effects, dye effects, and differential expression, are modelled jointly as opposed to a sequential application of several methods of analysis. The methods described in here have been tested only for cDNA microarrays, but can also, with some modifications, be applied to other high-throughput technologies. Keywords: High-throughput technology, microarray, cDNA, multiple scans, Bayesian hierarchical models, image analysis, experimental design, MCMC, WinBUGS.

Gene flow from transgenic plant populations: models and applications for risk assessment

The future use of genetically modified (GM) plants in food, feed and biomass production requires a careful consideration of possible risks related to the unintended spread of trangenes into new habitats. This may occur via introgression of the transgene to conventional genotypes, due to cross-pollination, and via the invasion of GM plants to new habitats. Assessment of possible environmental impacts of GM plants requires estimation of the level of gene flow from a GM population. Furthermore, management measures for reducing gene flow from GM populations are needed in order to prevent possible unwanted effects of transgenes on ecosystems. This work develops modeling tools for estimating gene flow from GM plant populations in boreal environments and for investigating the mechanisms of the gene flow process. To describe spatial dimensions of the gene flow, dispersal models are developed for the local and regional scale spread of pollen grains and seeds, with special emphasis on wind dispersal. This study provides tools for describing cross-pollination between GM and conventional populations and for estimating the levels of transgenic contamination of the conventional crops. For perennial populations, a modeling framework describing the dynamics of plants and genotypes is developed, in order to estimate the gene flow process over a sequence of years. The dispersal of airborne pollen and seeds cannot be easily controlled, and small amounts of these particles are likely to disperse over long distances. Wind dispersal processes are highly stochastic due to variation in atmospheric conditions, so that there may be considerable variation between individual dispersal patterns. This, in turn, is reflected to the large amount of variation in annual levels of cross-pollination between GM and conventional populations. Even though land-use practices have effects on the average levels of cross-pollination between GM and conventional fields, the level of transgenic contamination of a conventional crop remains highly stochastic. The demographic effects of a transgene have impacts on the establishment of trangenic plants amongst conventional genotypes of the same species. If the transgene gives a plant a considerable fitness advantage in comparison to conventional genotypes, the spread of transgenes to conventional population can be strongly increased. In such cases, dominance of the transgene considerably increases gene flow from GM to conventional populations, due to the enhanced fitness of heterozygous hybrids. The fitness of GM plants in conventional populations can be reduced by linking the selectively favoured primary transgene to a disfavoured mitigation transgene. Recombination between these transgenes is a major risk related to this technique, especially because it tends to take place amongst the conventional genotypes and thus promotes the establishment of invasive transgenic plants in conventional populations.

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.

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.

Skhematicheskiĭ chertezh Meliorativnogo tovarishchestva "VIN-SAD"

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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.