QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

Tillering in sorghum can be associated with either the carbon supply–demand (S/D) balance of the plant or an intrinsic propensity to tiller (PTT). Knowledge of the genetic control of tillering could assist breeders in selecting germplasm with tillering characteristics appropriate for their target environments. The aims of this study were to identify QTL for tillering and component traits associated with the S/D balance or PTT, to develop a framework model for the genetic control of tillering in sorghum. Four mapping populations were grown in a number of experiments in south east Queensland, Australia. The QTL analysis suggested that the contribution of traits associated with either the S/D balance or PTT to the genotypic differences in tillering differed among populations. Thirty-four tillering QTL were identified across the populations, of which 15 were novel to this study. Additionally, half of the tillering QTL co-located with QTL for component traits. A comparison of tillering QTL and candidate gene locations identified numerous coincident QTL and gene locations across populations, including the identification of common non-synonymous SNPs in the parental genotypes of two mapping populations in a sorghum homologue of MAX1, a gene involved in the control of tiller bud outgrowth through the production of strigolactones. Combined with a framework for crop physiological processes that underpin genotypic differences in tillering, the co-location of QTL for tillering and component traits and candidate genes allowed the development of a framework QTL model for the genetic control of tillering in sorghum.

The Genetic Architecture of Climatic Adaptation of Tropical Cattle

Adaptation of global food systems to climate change is essential to feed the world. Tropical cattle production, a mainstay of profitability for farmers in the developing world, is dominated by heat, lack of water, poor quality feedstuffs, parasites, and tropical diseases. In these systems European cattle suffer significant stock loss, and the cross breeding of taurine x indicine cattle is unpredictable due to the dilution of adaptation to heat and tropical diseases. We explored the genetic architecture of ten traits of tropical cattle production using genome wide association studies of 4,662 animals varying from 0% to 100% indicine. We show that nine of the ten have genetic architectures that include genes of major effect, and in one case, a single location that accounted for more than 71% of the genetic variation. One genetic region in particular had effects on parasite resistance, yearling weight, body condition score, coat colour and penile sheath score. This region, extending 20 Mb on BTA5, appeared to be under genetic selection possibly through maintenance of haplotypes by breeders. We found that the amount of genetic variation and the genetic correlations between traits did not depend upon the degree of indicine content in the animals. Climate change is expected to expand some conditions of the tropics to more temperate environments, which may impact negatively on global livestock health and production. Our results point to several important genes that have large effects on adaptation that could be introduced into more temperate cattle without detrimental effects on productivity.

Non-cellulosic cell wall polysaccharides are subject to genotype × environment effects in sorghum (Sorghum bicolor) grain

Sorghum is a staple food for half a billion people and, through growth on marginal land with minimal inputs, is an important source of feed, forage and increasingly, biofuel feedstock. Here we present information about non-cellulosic cell wall polysaccharides in a diverse set of cultivated and wild Sorghum bicolor grains. Sorghum grain contains predominantly starch (64–76) but is relatively deficient in other polysaccharides present in wheat, oats and barley. Despite overall low quantities, sorghum germplasm exhibited a remarkable range in polysaccharide amount and structure. Total (1,3;1,4)-β-glucan ranged from 0.06 to 0.43 (w/w) whilst internal cellotriose:cellotetraose ratios ranged from 1.8 to 2.9:1. Arabinoxylan amounts fell between 1.5 and 3.6 (w/w) and the arabinose:xylose ratio, denoting arabinoxylan structure, ranged from 0.95 to 1.35. The distribution of these and other cell wall polysaccharides varied across grain tissues as assessed by electron microscopy. When ten genotypes were tested across five environmental sites, genotype (G) was the dominant source of variation for both (1,3;1,4)-β-glucan and arabinoxylan content (69–74), with environment (E) responsible for 5–14. There was a small G × E effect for both polysaccharides. This study defines the amount and spatial distribution of polysaccharides and reveals a significant genetic influence on cell wall composition in sorghum grain.

Development of type I genetic markers from expressed sequence tags in highly polymorphic species

Expressed sequence tag (EST) databases provide a primary source of nuclear DNA sequences for genetic marker development in non-model organisms. To date, the process has been relatively inefficient for several reasons: - 1) priming site polymorphism in the template leads to inferior or erratic amplification; - 2) introns in the target amplicon are too large and/or numerous to allow effective amplification under standard screening conditions, and; - 3) at least occasionally, a PCR primer straddles an exon–intron junction and is unable to bind to genomic DNA template. The first is only a minor issue for species or strains with low heterozygosity but becomes a significant problem for species with high genomic variation, such as marine organisms with extremely large effective population sizes. Problems arising from unanticipated introns are unavoidable but are most pronounced in intron-rich species, such as vertebrates and lophotrochozoans. We present an approach to marker development in the Pacific oyster Crassostrea gigas, a highly polymorphic and intron-rich species, which minimizes these problems, and should be applicable to other non-model species for which EST databases are available. Placement of PCR primers in the 3′ end of coding sequence and 3′ UTR improved PCR success rate from 51% to 97%. Almost all (37 of 39) markers developed for the Pacific oyster were polymorphic in a small test panel of wild and domesticated oysters.

Epidemiology and genetic diversity of Tobacco streak virus and related subgroup 1 ilarviruses

A quarter of Australia’s sunflower production is from the central highlands region of Queensland and is currently worth six million dollars ($AUD) annually. From the early 2000s a severe necrosis disorder of unknown aetiology was affecting large areas of sunflower crops in central Queensland, leading to annual losses of up to 20%. Other crops such as mung bean and cotton were also affected. This PhD study was undertaken to determine if the causal agent of the necrosis disorder was of viral origin and, if so, to characterise its genetic diversity, biology and disease cycle, and to develop effective control strategies. The research described in this thesis identified Tobacco streak virus (TSV; genus Ilarvirus, family Bromoviridae) as the causal agent of the previously unidentified necrosis disorder of sunflower in central Queensland. TSV was also the cause of commonly found diseases in a range of other crops in the same region including cotton, chickpea and mung bean. This was the first report from Australia of natural field infections of TSV from these four crops. TSV strains have previously been reported from other regions of Australia in several hosts based on serological and host range studies. In order to determine the relatedness of previously reported TSV strains with TSV from central Queensland, we characterised the genetic diversity of the known TSV strains from Australia. We identified two genetically distinct TSV strains from central Queensland and named them based on their major alternative hosts, TSV-parthenium from Parthenium hysterophorus and TSV-crownbeard from Verbesina encelioides. They share only 81 % total-genome nucleotide sequence identity. In addition to TSV-parthenium and TSV-crownbeard from central Queensland, we also described the complete genomes of two other ilarvirus species. This proved that previously reported TSV strains, TSV-S isolated from strawberry and TSV-Ag from Ageratum houstonianum, were actually the first record of Strawberry necrotic shock virus from Australia, and a new subgroup 1 ilarvirus, Ageratum latent virus. Our results confirmed that the TSV strains found in central Queensland were not related to previously described strains from Australia and may represent new incursions. This is the first report of the genetic diversity within subgroup 1 ilarviruses from Australia. Based on field observations we hypothesised that parthenium and crownbeard were acting as symptomless hosts of TSV-parthenium and TSV-crownbeard, respectively. We developed strain-specific multiplex PCRs for the three RNA segments to accurately characterise the range of naturally infected hosts across central Queensland. Results described in this thesis show compelling evidence that parthenium and crownbeard are the major (symptomless) alternative hosts of TSV-parthenium and TSV-crownbeard. While both TSV strains had wide natural host ranges, the geographical distribution of each strain was closely associated with the respective distribution of their major alternative hosts. Both TSV strains were commonly found across large areas of central Queensland, but we only found strong evidence for the TSV-parthenium strain being associated with major disease outbreaks in nearby crops. The findings from this study demonstrate that both TSV-parthenium and TSV-crownbeard have similar life cycles but some critical differences. We found both TSV strains to be highly seed transmitted from their respective major alternative hosts from naturally infected mother plants and survived in seed for more than 2 years. We conclusively demonstrated that both TSV strains were readily transmitted via virus-infected pollen taken from the major alternative hosts. This transmission was facilitated by the most commonly collected thrips species, Frankliniella schultzei and Microcephalothrips abdominalis. These results illustrate the importance of seed transmission and efficient thrips vector species for the effective survival of these TSV strains in an often harsh environment and enables the rapid development of TSV disease epidemics in surrounding crops. Results from field surveys and inoculation tests indicate that parthenium is a poor host of TSV-crownbeard. By contrast, crownbeard was naturally infected by, and an experimental host of TSV-parthenium. However, this infection combination resulted in non-viable crownbeard seed. These differences appear to be an effective biological barrier that largely restricts these two TSV strains to their respective major alternative hosts. Based on our field observations we hypothesised that there were differences in relative tolerance to TSV infection between different sunflower hybrids and that seasonal variation in disease levels was related to rainfall in the critical early crop stage. Results from our field trials conducted over multiple years conclusively demonstrated significant differences in tolerance to natural infections of TSV-parthenium in a wide range of sunflower hybrids. Glasshouse tests indicate the resistance to TSV-parthenium identified in the sunflower hybrids is also likely to be effective against TSV-crownbeard. We found a significant negative association between TSV disease incidence in sunflowers and accumulated rainfall in the months of March and April with increasing rainfall resulting in reduced levels of disease. Our results indicate that the use of tolerant sunflower germplasm will be a critical strategy to minimise the risk of TSV epidemics in sunflower.

Genetic diversity and epidemiology of Tobacco streak virus and related subgroup 1 Ilarviruses

A quarter of Australia’s sunflower production is from the central highlands region of Queensland and is currently worth six million dollars ($AUD) annually. From the early 2000s a severe necrosis disorder of unknown aetiology was affecting large areas of sunflower crops in central Queensland, leading to annual losses of up to 20%. Other crops such as mung bean and cotton were also affected. This PhD study was undertaken to determine if the causal agent of the necrosis disorder was of viral origin and, if so, to characterise its genetic diversity, biology and disease cycle, and to develop effective control strategies. The research described in this thesis identified Tobacco streak virus (TSV; genus Ilarvirus, family Bromoviridae) as the causal agent of the previously unidentified necrosis disorder of sunflower in central Queensland. TSV was also the cause of commonly found diseases in a range of other crops in the same region including cotton, chickpea and mung bean. This was the first report from Australia of natural field infections of TSV from these four crops. TSV strains have previously been reported from other regions of Australia in several hosts based on serological and host range studies. In order to determine the relatedness of previously reported TSV strains with TSV from central Queensland, we characterised the genetic diversity of the known TSV strains from Australia. We identified two genetically distinct TSV strains from central Queensland and named them based on their major alternative hosts, TSV-parthenium from Parthenium hysterophorus and TSV-crownbeard from Verbesina encelioides. They share only 81 % total-genome nucleotide sequence identity. In addition to TSV-parthenium and TSV-crownbeard from central Queensland, we also described the complete genomes of two other ilarvirus species. This proved that previously reported TSV strains, TSV-S isolated from strawberry and TSV-Ag from Ageratum houstonianum, were actually the first record of Strawberry necrotic shock virus from Australia, and a new subgroup 1 ilarvirus, Ageratum latent virus. Our results confirmed that the TSV strains found in central Queensland were not related to previously described strains from Australia and may represent new incursions. This is the first report of the genetic diversity within subgroup 1 ilarviruses from Australia. Based on field observations we hypothesised that parthenium and crownbeard were acting as symptomless hosts of TSV-parthenium and TSV-crownbeard, respectively. We developed strain-specific multiplex PCRs for the three RNA segments to accurately characterise the range of naturally infected hosts across central Queensland. Results described in this thesis show compelling evidence that parthenium and crownbeard are the major (symptomless) alternative hosts of TSV-parthenium and TSV-crownbeard. While both TSV strains had wide natural host ranges, the geographical distribution of each strain was closely associated with the respective distribution of their major alternative hosts. Both TSV strains were commonly found across large areas of central Queensland, but we only found strong evidence for the TSV-parthenium strain being associated with major disease outbreaks in nearby crops. The findings from this study demonstrate that both TSV-parthenium and TSV-crownbeard have similar life cycles but some critical differences. We found both TSV strains to be highly seed transmitted from their respective major alternative hosts from naturally infected mother plants and survived in seed for more than 2 years. We conclusively demonstrated that both TSV strains were readily transmitted via virus-infected pollen taken from the major alternative hosts. This transmission was facilitated by the most commonly collected thrips species, Frankliniella schultzei and Microcephalothrips abdominalis. These results illustrate the importance of seed transmission and efficient thrips vector species for the effective survival of these TSV strains in an often harsh environment and enables the rapid development of TSV disease epidemics in surrounding crops. Results from field surveys and inoculation tests indicate that parthenium is a poor host of TSV-crownbeard. By contrast, crownbeard was naturally infected by, and an experimental host of TSV-parthenium. However, this infection combination resulted in non-viable crownbeard seed. These differences appear to be an effective biological barrier that largely restricts these two TSV strains to their respective major alternative hosts. Based on our field observations we hypothesised that there were differences in relative tolerance to TSV infection between different sunflower hybrids and that seasonal variation in disease levels was related to rainfall in the critical early crop stage. Results from our field trials conducted over multiple years conclusively demonstrated significant differences in tolerance to natural infections of TSV-parthenium in a wide range of sunflower hybrids. Glasshouse tests indicate the resistance to TSV-parthenium identified in the sunflower hybrids is also likely to be effective against TSV-crownbeard. We found a significant negative association between TSV disease incidence in sunflowers and accumulated rainfall in the months of March and April with increasing rainfall resulting in reduced levels of disease. Our results indicate that the use of tolerant sunflower germplasm will be a critical strategy to minimise the risk of TSV epidemics in sunflower.

Problems and Algorithms for Sequence Segmentations

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.

Algorithms for 13C metabolic flux analysis

The metabolism of an organism consists of a network of biochemical reactions that transform small molecules, or metabolites, into others in order to produce energy and building blocks for essential macromolecules. The goal of metabolic flux analysis is to uncover the rates, or the fluxes, of those biochemical reactions. In a steady state, the sum of the fluxes that produce an internal metabolite is equal to the sum of the fluxes that consume the same molecule. Thus the steady state imposes linear balance constraints to the fluxes. In general, the balance constraints imposed by the steady state are not sufficient to uncover all the fluxes of a metabolic network. The fluxes through cycles and alternative pathways between the same source and target metabolites remain unknown. More information about the fluxes can be obtained from isotopic labelling experiments, where a cell population is fed with labelled nutrients, such as glucose that contains 13C atoms. Labels are then transferred by biochemical reactions to other metabolites. The relative abundances of different labelling patterns in internal metabolites depend on the fluxes of pathways producing them. Thus, the relative abundances of different labelling patterns contain information about the fluxes that cannot be uncovered from the balance constraints derived from the steady state. The field of research that estimates the fluxes utilizing the measured constraints to the relative abundances of different labelling patterns induced by 13C labelled nutrients is called 13C metabolic flux analysis. There exist two approaches of 13C metabolic flux analysis. In the optimization approach, a non-linear optimization task, where candidate fluxes are iteratively generated until they fit to the measured abundances of different labelling patterns, is constructed. In the direct approach, linear balance constraints given by the steady state are augmented with linear constraints derived from the abundances of different labelling patterns of metabolites. Thus, mathematically involved non-linear optimization methods that can get stuck to the local optima can be avoided. On the other hand, the direct approach may require more measurement data than the optimization approach to obtain the same flux information. Furthermore, the optimization framework can easily be applied regardless of the labelling measurement technology and with all network topologies. In this thesis we present a formal computational framework for direct 13C metabolic flux analysis. The aim of our study is to construct as many linear constraints to the fluxes from the 13C labelling measurements using only computational methods that avoid non-linear techniques and are independent from the type of measurement data, the labelling of external nutrients and the topology of the metabolic network. The presented framework is the first representative of the direct approach for 13C metabolic flux analysis that is free from restricting assumptions made about these parameters.In our framework, measurement data is first propagated from the measured metabolites to other metabolites. The propagation is facilitated by the flow analysis of metabolite fragments in the network. Then new linear constraints to the fluxes are derived from the propagated data by applying the techniques of linear algebra.Based on the results of the fragment flow analysis, we also present an experiment planning method that selects sets of metabolites whose relative abundances of different labelling patterns are most useful for 13C metabolic flux analysis. Furthermore, we give computational tools to process raw 13C labelling data produced by tandem mass spectrometry to a form suitable for 13C metabolic flux analysis.

Efficient search for statistically significant dependency rules in binary data

Analyzing statistical dependencies is a fundamental problem in all empirical science. Dependencies help us understand causes and effects, create new scientific theories, and invent cures to problems. Nowadays, large amounts of data is available, but efficient computational tools for analyzing the data are missing. In this research, we develop efficient algorithms for a commonly occurring search problem - searching for the statistically most significant dependency rules in binary data. We consider dependency rules of the form X->A or X->not A, where X is a set of positive-valued attributes and A is a single attribute. Such rules describe which factors either increase or decrease the probability of the consequent A. A classical example are genetic and environmental factors, which can either cause or prevent a disease. The emphasis in this research is that the discovered dependencies should be genuine - i.e. they should also hold in future data. This is an important distinction from the traditional association rules, which - in spite of their name and a similar appearance to dependency rules - do not necessarily represent statistical dependencies at all or represent only spurious connections, which occur by chance. Therefore, the principal objective is to search for the rules with statistical significance measures. Another important objective is to search for only non-redundant rules, which express the real causes of dependence, without any occasional extra factors. The extra factors do not add any new information on the dependence, but can only blur it and make it less accurate in future data. The problem is computationally very demanding, because the number of all possible rules increases exponentially with the number of attributes. In addition, neither the statistical dependency nor the statistical significance are monotonic properties, which means that the traditional pruning techniques do not work. As a solution, we first derive the mathematical basis for pruning the search space with any well-behaving statistical significance measures. The mathematical theory is complemented by a new algorithmic invention, which enables an efficient search without any heuristic restrictions. The resulting algorithm can be used to search for both positive and negative dependencies with any commonly used statistical measures, like Fisher's exact test, the chi-squared measure, mutual information, and z scores. According to our experiments, the algorithm is well-scalable, especially with Fisher's exact test. It can easily handle even the densest data sets with 10000-20000 attributes. Still, the results are globally optimal, which is a remarkable improvement over the existing solutions. In practice, this means that the user does not have to worry whether the dependencies hold in future data or if the data still contains better, but undiscovered dependencies.

Genetic conservation of Phosphine Resistance in the Rice Weevil Sitophilus oryzae (L.)

High levels of resistance to phosphine in the rice weevil Sitophilus oryzae have been detected in Asian countries including China and Vietnam, however there is limited knowledge of the genetic mechanism of resistance in these strains. We find that the genetic basis of strong phosphine resistance is conserved between strains of S. oryzae from China, Vietnam and Australia. Each of four strongly resistant strains has an identical amino acid variant in the encoded dihydrolipoamide dehydrogenase (DLD) enzyme that was previously identified as a resistance factor in Rhyzopertha dominica and Tribolium castaneum. The unique amino acid substitution, Asparagine > Threonine (N505T) of all strongly resistant S. oryzae corresponds to the position of an Asparagine > Histidine variant (N506H) that was previously reported in strongly resistant R. dominica. Progeny (F16 and F18) from two independent crosses showed absolute linkage of N505T to the strong resistance phenotype, indicating that if N505T was not itself the resistance variant that it resided within 1 or 2 genes of the resistance factor. Non-complementation between the strains confirmed the shared genetic basis of strong resistance, which was supported by the very similar level of resistance between the strains, with LC50 values ranging from 0.20 to 0.36 mgL-1 for a 48 hour exposure at 25°C. Thus, the mechanism of high level resistance to phosphine is strongly conserved between R. dominica, T. castaneum and S. oryzae. A fitness cost associated with strongly resistant allele was observed in segregating populations in the absence of selection.

Genetic aspects of outcome in kidney transplantation: cytokine and thrombosis associated candidate genes and gene expression biomarkers

Kidney transplantation (Tx) is the treatment of choice for end stage renal disease. Immunosuppressive medications are given to prevent an immunological rejection of the transplant. However, immunosuppressive drugs increase e.g. the risk of infection, cancer or nephrotoxicity. A major genetic contributors to immunological acceptance of the graft are human leukocyte antigen (HLA) genes. Also other non-HLA gene polymorphisms may predict the future risk of complications before Tx, possibly enabling individualised immunotherapy. Graft function after Tx is monitored using non-specific clinical symptoms and laboratory markers. The definitive diagnosis of graft rejection however relies on a biopsy of the graft. In the acute rejection (AR) diagnostics there is a need for an alternative to biopsy that would be an easily repeatable and simple method for regular use. Frequent surveillance of acute or subclinical rejection (SCR) may improve long-term function. In this thesis, associations between cytokine and thrombosis associated candidate genes and the outcome of kidney Tx were studied. Cytotoxic and co-stimulatory T lymphocyte molecule gene expression biomarkers for the diagnosis of the AR and the SCR were also investigated. We found that polymorphisms in the cytokine genes tumor necrosis factor and interleukin 10 (IL10) of the recipients were associated with AR. In addition, certain IL10 gene polymorphisms of the donors were associated with the incidence of cytomegalovirus infection and occurrence of later infection in a subpopulation of recipients. Further, polymorphisms in genes related to the risk of thrombosis and those of certain cytokines were not associated with the occurrence of thrombosis, infarction, AR or graft survival. In the study of biomarkers for AR, whole blood samples were prospectively collected from adult kidney Tx patients. With real-time quantitative PCR (RT-QPCR) gene expression quantities of CD154 and ICOS differentiated the patients with AR from those without, but not from the patients with other causes of graft dysfunction. Biomarkers for SCR were studied in paediatric kidney Tx patients. We used RT-QPCR to quantify the gene expression of immunological candidate genes in a low-density array format. In addition, we used RT-QPCR to validate the results of the microarray analysis. No gene marker differentiated patients with SCR from those without SCR. This research demonstrates the lack of robust markers among polymorphisms or biomarkers in investigated genes that could be included in routine analysis in a clinical laboratory. In genetic studies, kidney Tx can be regarded as a complex trait, i.e. several environmental and genetic factors may determine its outcome. A number of currently unknown genetic factors probably influence the results of Tx.

An extragenic suppressor of prp24-1 defines genetic interaction between PRP24 and PRP21 gene products of Saccharomyces cerevisiae

The temperature-sensitive prp24-1 mutation defines a gene product required for the first step in pre-mRNA splicing. PRP24 is probably a component of the U6 snRNP particle. We have applied genetic reversion analysis to identify proteins that interact with PRP24. Spontaneous revertants of the temperature-sensitive (ts) prp24-1 phenotype were analyzed for those that are due to extragenic suppression. We then extended our analysis to screen for suppressors that confer a distinct conditional phenotype. We have identified a temperature-sensitive extragenic suppressor, which was shown by genetic complementation analysis to be allelic to prp21-1. This suppressor, prp21-2, accumulates pre-mRNA at the non-permissive temperature, a phenotype similar to that of prp21-1. prp21-2 completely suppresses the splicing defect and restores in vivo levels of the U6 snRNA in the prp24-1 strain. Genetic analysis of the suppressor showed that prp21-2 is not a bypass suppressor of prp24-1. The suppression of prp24-1 by prp21-2 is gene specific and also allele specific with respect to both the loci. Genetic interactions with other components of the pre-spliceosome have also been studied. Our results indicate an interaction between PRP21, a component of the U2 snRNP, and PRP24, a component of the U6 snRNP. These results substantiate other data showing U2-U6 snRNA interactions.

Non-linear Transceiver Designs with Imperfect CSIT Using Convex Optimization

In this paper, we consider non-linear transceiver designs for multiuser multi-input multi-output (MIMO) down-link in the presence of imperfections in the channel state information at the transmitter (CSIT). The base station (BS) is equipped with multiple transmit antennas and each user terminal is equipped with multiple receive antennas. The BS employs Tomlinson-Harashima precoding (THP) for inter-user interference pre-cancellation at the transmitter. We investigate robust THP transceiver designs based on the minimization of BS transmit power with mean square error (MSE) constraints, and balancing of MSE among users with a constraint on the total BS transmit power. We show that these design problems can be solved by iterative algorithms, wherein each iteration involves a pair of convex optimization problems. The robustness of the proposed algorithms to imperfections in CSIT is illustrated through simulations.

Evaluation of a 7-gene genetic profile for athletic endurance phenotype in Ironman championship triathletes

Polygenic profiling has been proposed for elite endurance performance, using an additive model determining the proportion of optimal alleles in endurance athletes. To investigate this model’s utility for elite triathletes, we genotyped seven polymorphisms previously associated with an endurance polygenic profile (ACE Ins/Del, ACTN3 Arg577Ter, AMPD1 Gln12Ter, CKMM 1170bp/985+185bp, HFE His63Asp, GDF8 Lys153Arg and PPARGC1A Gly482Ser) in a cohort of 196 elite athletes who participated in the 2008 Kona Ironman championship triathlon. Mean performance time (PT) was not significantly different in individual marker analysis. Age, sex, and continent of origin had a significant influence on PT and were adjusted for. Only the AMPD1 endurance-optimal Gln allele was found to be significantly associated with an improvement in PT (model p=5.79 x 10-17, AMPD1 genotype p=0.01). Individual genotypes were combined into a total genotype score (TGS); TGS distribution ranged from 28.6 to 92.9, concordant with prior studies in endurance athletes (mean±SD: 60.75±12.95). TGS distribution was shifted toward higher TGS in the top 10% of athletes, though the mean TGS was not significantly different (p=0.164) and not significantly associated with PT even when adjusted for age, sex, and origin. Receiver operating characteristic curve analysis determined that TGS alone could not significantly predict athlete finishing time with discriminating sensitivity and specificity for three outcomes (less than median PT, less than mean PT, or in the top 10%), though models with the age, sex, continent of origin, and either TGS or AMPD1 genotype could. These results suggest three things: that more sophisticated genetic models may be necessary to accurately predict athlete finishing time in endurance events; that non-genetic factors such as training are hugely influential and should be included in genetic analyses to prevent confounding; and that large collaborations may be necessary to obtain sufficient sample sizes for powerful and complex analyses of endurance performance.

SPECT-aided diagnostics and genetic risk factors in Parkinson's disease

Hypokinesia, rigidity, tremor, and postural instability are the cardinal symptoms of Parkinson s disease (PD). Since these symptoms are not specific to PD the diagnosis may be uncertain in early PD. Etiology and pathogenesis of PD remain unclear. There is no neuroprotective therapy. Genetic findings are expected to reveal metabolic routes in PD pathogenesis and thereby eventually lead to therapeutic innovations. In this thesis, we first aimed to study the usefulness and accuracy of 123I-b-CIT SPECT in the diagnosis of PD in a consecutive clinic-based material including various movement disorders. We subsequently a genetic project to identify genetic risk factors for sporadic PD using a candidate gene approach in a case-control setting including 147 sporadic PD patients and 137 spouse controls. Dopamine transporter imaging by 123I-b-CIT SPECT could distinguish PD from essential tremor, drug-induced parkinsonism, dystonia and psychogenic parkinsonism. However, b-CIT uptake in Parkinson plus syndromes (PSP and multiple system atrophy) and dementia with Lewy bodies was not significantly different from PD. 123I-b-CIT SPECT could not reliably differentiate PD from vascular parkinsonism. 123I-b-CIT SPECT was 100% sensitive and specific in the diagnosis of PD in patients younger than 55 years but less specific in older patients, due to differential distribution of the above conditions in the younger and older age groups. 123I-b-CIT SPECT correlated with symptoms and detected bilateral nigrostriatal defect in patients whose PD was still in unilateral stage. Thus, in addition to as a differential diagnostic aid, 123I-b-CIT SPECT may be used to detect PD early, even pre-symptomatically in at-risk individuals. 123I-b-CIT SPECT was used to aid in the collection of patients to the genetic studies. In the genetic part of this thesis we found an association between PD and a polymorphic CAG-repeat in POLG1 gene encoding the catalytic subunit of mitochondrial polymerase gamma. The CAG-repeat encodes a polyglutamine tract (polyQ), the two most common lengths of which are 10Q (86-90%) and 11Q. In our Finnish material, the rarer non-10Q or non-11Q length variants (6Q-9Q, 12Q-14Q, 4R+9Q) were more frequent in patients than in spouse controls (10% vs. 3.5 %, p=0.003), or population controls (p=0.001). Therefore, we performed a replication study in 652 North American PD patients and 292 controls. Non-10/11Q alleles were more common in the US PD patients compared to the controls but the difference did not reach statistical significance (p=0.07). This larger data suggested our original definition of variant length allele might need reconsideration. Most previous studies on phenotypic effects of POLG1 polyQ have defined 10Q as the only normal allele. Non-10Q alleles were significantly more common in patients compared to the controls (17.3% vs. 12.3 %, p= 0.005). This association between non-10Q length variants and PD remained significant when compared to a larger set of 1541 literature controls (p=0.00005). In conclusion, POLG1 polyQ alleles other than 10Q may predispose to PD. We did not find association between PD and parkin or DJ-1, genes underlying autosomal recessive parkinsonism. The functional Val158Met polymorphism, which affects the catalytic effect of COMT enzyme, and another coding polymorphism in COMT were not associated with PD in our patient material. The APOE e2/3/4 polymorphism modifies risk for Alzheimer s disease and prognosis of for example brain trauma. APOE promoter and enhancer polymorphisms 219G/T and +113G/C, and APOE e3 haplotypes, have also been shown to modify the risk of Alzheimer s disease but not reported in PD. No association was found between PD and APOE e2/3/4 polymorphism, the promoter or enhancer polymorphisms, or the e3 haplotypes.