Genetic Mechanisms Underlying Autism Spectrum Disorders

Autism is a childhood-onset developmental disorder characterized by deficits in reciprocal social interaction, verbal and non-verbal communication, and dependence on routines and rituals. It belongs to a spectrum of disorders (autism spectrum disorders, ASDs) which share core symptoms but show considerable variation in severity. The whole spectrum affects 0.6-0.7% of children worldwide, inducing a substantial public health burden and causing suffering to the affected families. Despite having a very high heritability, ASDs have shown exceptional genetic heterogeneity, which has complicated the identification of risk variants and left the etiology largely unknown. However, recent studies suggest that rare, family-specific factors contribute significantly to the genetic basis of ASDs. In this study, we investigated the role of DISC1 (Disrupted-in-schizophrenia-1) in ASDs, and identified association with markers and haplotypes previously associated with psychiatric phenotypes. We identified four polymorphic micro-RNA target sites in the 3 UTR of DISC1, and showed that hsa-miR-559 regulates DISC1 expression in vitro in an allele-specific manner. We also analyzed an extended autism pedigree with genealogical roots in Central Finland reaching back to the 17th century. To take advantage of the beneficial characteristics of population isolates to gene mapping and reduced genetic heterogeneity observed in distantly related individuals, we performed a microsatellite-based genome-wide screen for linkage and linkage disequilibrium in this pedigree. We identified a putative autism susceptibility locus on chromosome 19p13.3 and obtained further support for previously reported loci at 1q23 and 15q11-q13. To follow-up these findings, we extended our study sample from the same sub-isolate and initiated a genome-wide analysis of homozygosity and allelic sharing using high-density SNP markers. We identified a small number of haplotypes shared by different subsets of the genealogically connected cases, along with convergent biological pathways from SNP and gene expression data, which highlighted axon guidance molecules in the pathogenesis of ASDs. In conclusion, the results obtained in this thesis show that multiple distinct genetic variants are responsible for the ASD phenotype even within single pedigrees from an isolated population. We suggest that targeted resequencing of the shared haplotypes, linkage regions, and other susceptibility loci is essential to identify the causal variants. We also report a possible micro-RNA mediated regulatory mechanism, which might partially explain the wide-range neurobiological effects of the DISC1 gene.

Data fusion and matching by maximizing statistical dependencies

The core aim of machine learning is to make a computer program learn from the experience. Learning from data is usually defined as a task of learning regularities or patterns in data in order to extract useful information, or to learn the underlying concept. An important sub-field of machine learning is called multi-view learning where the task is to learn from multiple data sets or views describing the same underlying concept. A typical example of such scenario would be to study a biological concept using several biological measurements like gene expression, protein expression and metabolic profiles, or to classify web pages based on their content and the contents of their hyperlinks. In this thesis, novel problem formulations and methods for multi-view learning are presented. The contributions include a linear data fusion approach during exploratory data analysis, a new measure to evaluate different kinds of representations for textual data, and an extension of multi-view learning for novel scenarios where the correspondence of samples in the different views or data sets is not known in advance. In order to infer the one-to-one correspondence of samples between two views, a novel concept of multi-view matching is proposed. The matching algorithm is completely data-driven and is demonstrated in several applications such as matching of metabolites between humans and mice, and matching of sentences between documents in two languages.

Overwintering ecology of northern field layer plants : snow and photosynthesis in Vaccinium vitis-idaea L.

Winter is a significant period for the seasonality of northern plants, but is often overlooked when studying the interactions of plants and their environment. This study focuses on the effects of overwintering conditions, including warm winter periods, snow, and snowmelt on boreal and sub-Arctic field layer plants. Wintertime photosynthesis and related physiological factors of evergreen dwarf shrubs, particularly of Vaccinium vitis-idaea, are emphasised. The work combines experiments both in the field and in growth chambers with measurements in natural field conditions. Evergreen dwarf shrubs are predominantly covered by snow in the winter. The protective snow cover provides favourable conditions for photosynthesis, especially during the spring before snowmelt. The results of this study indicate that photosynthesis occurs under the snow in V. vitis-idaea. The light response of photosynthesis determined in field conditions during the period of snow cover shows that positive net CO2 exchange is possible under the snow in the prevailing light and temperature. Photosynthetic capacity increases readily during warm periods in winter and the plants are thus able to replenish carbohydrate reserves lost through respiration. Exposure to low temperatures in combination with high light following early snowmelt can set back photosynthesis as sustained photoprotective measures are activated and photodamage begins to build up. Freezing may further decrease the photosynthetic capacity. The small-scale distribution of many field layer plants, including V. vitis-idaea and other dwarf shrubs, correlates with the snow distribution in a forest. The results of this study indicate that there are species-specific differences in the snow depth affinity of the field and ground layer species. Events and processes taking place in winter can have a profound effect on the overall performance of plants and on the interactions between plants and their environment. Understanding the processes involved in the overwintering of plants is increasingly important as the wintertime climate in the north is predicted to change in the future.

The role of Acinetobacter sp. in biological phosphorus removal from forest industry wastewaters

Yhteenveto: Acinetobacter sp. metsäteollisuuden jätevesien biologisessa fosforinpoistossa