Ziel dieser Arbeit war es, verschiedene Aspekte der Verwendung von genetischen Markern in der genomischen Charakterisierung und Analyse von verschiedenen Tierpopulationen zu untersuchen. Zu Beginn werden die verschiedenen Anwendungsbereiche von genetischen Markern in der Tierzucht beschrieben. In der ersten Analyse wurden acht Hühnerrassen für 9‘216 Single Nucleotide Polymorphism (SNPs) und 29 Microsatelliten (Single Sequence Repeats, SSRs) typisiert. Um die Rassen zu differenzieren wurden zwei unterschiedliche Methoden herangezogen: (i) die Bayesian Model-based Clustering Analyse, die im Programm STRUCTURE (Version 2.3) implementiert ist und (ii) eine Hauptkomponenten-Analyse (Principal Component Analysis, PCA), bei der eine Differenzierung der Rassen aufgrund ihres Euklidischen Abstandes zueinander durchgeführt wurde. Die Ergebnisse der STRUCTURE Analyse zeigten, dass die Wiederholbarkeit bei SNPs, unabhängig von Ihrer Anzahl, höher war als bei den SSR. Bei der Zuordnung eines Individuums zu einer der Rassen wurden die höchsten Werte für 29 SSRs und 100 SNPs errechnet. Die PCA-basierte Methode ergab, dass 2.4 SNPs je SSR benötigt werden, um eine vergleichbare Differenzierung zu erreichen. Dieses Ergebnis ist vergleichbar mit Untersuchungen, die an Menschen oder Rindern durchgeführt wurden. Unter Verwendung aller SNPs konnte im Vergleich zu allen vorhandenen SSRs eine genetisch inhomogene Rasse detektiert werden. Aufgrund dieser Ergebnisse und der deutlich größeren Anzahl an verfügbaren SNPs verglichen mit SSRs kann davon ausgegangen werden, dass SNP-basierte Ansätze weiter an Bedeutung gewinnen werden. Des Weiteren wurde eine umfassende Kartierung von Selektionssignaturen auf den Autosomen des Göttinger Minischweins durchgeführt. Für die Suche nach Selektions-signaturen wurden die mittels des Illumina Porcine BeadChip 60K (Illumina, San Diego, USA) gewonnenen SNP Daten anhand von zwei Methoden untersucht: Zum einen wurde der Long Range Haplotype Test (LRH) angewendet, der im Softwarepacket SWEEP integriert ist. Zum anderen wurden die genomischen Anteile der drei Ausgangsrassen für jeden SNP aufgrund einer Bayes‘schen Methode geschätzt. Es konnte eine signifikante Veränderung der Anteile der Ausgangsrassen verglichen mit den berechneten pedigree-basierten Erwartungswert festgestellt werden. Hierbei fiel auf, dass die Zuteilung der Allele zu einer der drei Ausgangsrassen sowohl zwischen als auch innerhalb der Chromosomen hoch variabel ist. Es wurde angenommen, dass eine lokale Abweichung der Zusammensetzung als Hinweis darauf interpretiert werden kann, dass diese Region unter gerichteter Selektion stand. Mit Hilfe dieses Indikators und den Ergebnissen des LRH-Testes konnte eine Vielzahl von Regionen identifiziert werden, die unter Selektion standen. Einige dieser Regionen beherbergen Kandidatengene, die funktionell mit den Zuchtzielen der Göttinger Minischweine im Zusammenhang stehen, z.B. SOCS2, TXN, DDR2 und GRB10, die mit der Körpergröße in Verbindung gebracht werden, oder das PRLR Gen, das die Wurfgröße beeinflusst. Die Ergebnisse dieser Untersuchungen lassen Rückschlüsse darauf zu, dass die Beziehung der Gene SOCS2 und GRB10 zu dem IGF-1 Gen der mögliche Grund für den Zwergwuchs im Göttinger Minischwein sein könnte. In einem weiteren Schritt wurden die Ergebnisse der Kartierung der Selektionssignaturen auf den Autosomen des Göttinger Minischweins validiert. Hierfür wurde die Cross Population Extended Haplotype Homozygosity (XPEHH) berechnet. Diese Methode basiert, genau wie der LRH-Test, auf dem Auffinden von Regionen ausgedehnter Haplotypenhomozygotie. Die beiden Ansätze unterscheiden sich dadurch, dass beim LRH-Test innerhalb einer Rasse und beim XPEHH im Vergleich zweier Rassen Selektionssignaturen aufgedeckt werden. Als Vergleichsrassen wurden Tiere der Rassen Göttinger Minischwein, Deutsche Landrasse und Large White mit dem Illumina Porcine BeadChip 60K (Illumina, San Diego, USA) genotypisiert. Mit Hilfe des XPEHH-Tests konnten weitere Regionen identifiziert werden, die unter Selektion standen. Aufgrund des Vergleichs von Großschweinerassen mit dem Göttinger Minischwein und dem erneuten Auffinden des SOCS2 Gens wird die Vermutung bestärkt, dass es sich hierbei um eines der wichtigsten Gene für den Zwergwuchs beim Göttinger Minischwein handelt. Zusammenfassend ergibt sich, dass SNP-basierte Ansätze einen deutlich besseren Einblick in die genomische Architektur von Populationen ermöglichen. Dadurch wird ein besseres Verständnis von Selektion und Differenzierung von Rasse auf genomischer Ebene erreicht.

The recent decade has witnessed great advances in microarray and genotyping technologies which allow genome-wide single nucleotide polymorphism (SNP) data to be captured on a single chip. As a consequence, genome-wide association studies require the development of algorithms capable of manipulating ultra-large-scale SNP datasets. Towards this goal, this thesis proposes two SNP selection methods; the first using Independent Component Analysis (ICA) and the second based on a modified version of Fast Orthogonal Search. The first proposed technique, based on ICA, is a filtering technique; it reduces the number of SNPs in a dataset, without the need for any class labels. The second proposed technique, orthogonal search based SNP selection, is a multivariate regression approach; it selects the most informative features in SNP data to accurately model the entire dataset. The proposed methods are evaluated by applying them to publicly available gene SNP datasets, and comparing the accuracies of each method in reconstructing the datasets. In addition, the selection results are compared with those of another SNP selection method based on Principal Component Analysis (PCA), which was also applied to the same datasets. The results demonstrate the ability of orthogonal search to capture a higher amount of information than ICA SNP selection approach, all while using a smaller number of SNPs. Furthermore, SNP reconstruction accuracies using the proposed ICA methodology demonstrated the ability to summarize a greater or equivalent amount of information in comparison with the amount of information captured by the PCA-based technique reported in the literature. The execution time of the second developed methodology, mFOS, has paved the way for its application to large-scale genome wide datasets. / Thesis (Master, Computing) -- Queen's University, 2010-12-15 18:03:00.208

<p>Stepska vi&scaron;nja (<em>Prunus fruticosa&nbsp;</em> Pall.)&nbsp; je autotetraploidna vrsta (FFFF, 2n = 4x = 32)&nbsp;koja se prema taksonomskom položaju svrstava u familiju&nbsp;<em> Rosaceae</em>,&nbsp; rod&nbsp; <em>Prunus</em>. Ova vrsta &nbsp;pripada sekciji&nbsp;<em> Eurocerasus</em>&nbsp; u koju se pored nje ubrajaju jo&scaron; i tre&scaron;nja (<em>Prunus avium</em>&nbsp; L.) &nbsp;i vi&scaron;nja <em>(Prunus cerasus</em>&nbsp; L.). Stepska vi&scaron;nja i tre&scaron;nja su među najranijim derivatima roda&nbsp; Prunus, dok je vi&scaron;nja nastala kroz proces prirodne hibridizacije između ove dve vrste nekoliko puta u toku istorije.&nbsp; Utvrđivanje nivoa diverziteta među biljnim&nbsp; materijalom&nbsp; koji&nbsp; se&nbsp; koristi&nbsp; u&nbsp; oplemenjivačkom radu&nbsp; je&nbsp; od&nbsp; izuzetne&nbsp; važnosti&nbsp; za unapređenje&nbsp; agronomskih svojstava bilo&nbsp; koje&nbsp; biljne&nbsp; vrste.&nbsp; Jedan od prvih koraka u istraživanju nivoa diverziteta jeste morfolo&scaron;ka karakterizacija germplazme.&nbsp; Nasuprot ovom tipu markera nalaze se molekularni markeri kojima se detektuju razlike na nivou DNK. Cilj ovog rada je bio ispitivanje inter-&nbsp; i&nbsp; intrapopulacione varijabilnosti stepske&nbsp; vi&scaron;nje (<em>P. &nbsp;fruticosa</em>) upotrebom fenotipskih, mikrosatelitskih i SNP markera, a dobijeni rezultati će olak&scaron;ati i ubrzati oplemenjivački proces tre&scaron;nje i vi&scaron;nje. Fenotipska svojstva su ispoljila visok nivo varijabilnosti prevashodno za kvantitativne markere, dok je ne&scaron;to niži stepen varijacija uočen kod kvalitativnih karaktera, a potpuno odsustvo varijabilnosti je uočeno samo u&nbsp; svojstvu prisustva lisnih žlezda. Populacije stepske vi&scaron;nje su pokazale visok nivo polimorfizma unutar i između populacija primenom mikrosatelitskih markera, a broj detektovanih alela u okviru lokusa se kretao od 2 (BPPCT022, UDP-018) do 11 (BPPCT034). Varijabilnost na nivou sekvenci DNK u okviru populacija vrste<em>&nbsp; P.&nbsp; fruticosa&nbsp;</em>je visoka, ovo je potvrđeno analizom 170256 SNP markera. Populacije stepske vi&scaron;nje na nivou sva tri tipa markera&nbsp; su pokazale visok stepen varijabilnosti kada se govori o svim analiziranim lokalitetima kao jednoj populaciji, dok je ona bila ne&scaron;to niža između jedinki na jednom lokalitetu. Bujnost kao fenotipska karakteristika pokazala je značajan nivo vezanosti za dva SNP markera Primenom generalnog linearnog modela (General Linear Model,&nbsp; GLM) u asocijativnom mapiranju genoma stepske vi&scaron;nje otkriven &nbsp;je značajan nivo vezanosti između pojedinih SNP markera i ispitivanih fenotipskih karakteristika na hromozomu 7 (S7_8740459) i na hromozomu 8 (S8_6142814). Stepska &nbsp;vi&scaron;nja kao divlji srodnik vrsta od velikog ekonomskog značaja kao &scaron;to su tre&scaron;nja i vi&scaron;nja može imati značajnu ulogu u njihovom unapređenju, a u ovom radu je potvrđeno da poseduje veliki diverzitet &scaron;to je čini jo&scaron; značajnijom i potencijalnim izvorom nove varijabilnosti.</p> / <p>European ground cherry&nbsp; <em>(Prunus fruticos</em>a&nbsp; Pall.)&nbsp; is autotetraploid species&nbsp; (FFFF, 2n = 4x = 32) and belongs to <em>Prunus genus</em> and <em>Rosaceae</em> family. It is a part of&nbsp; Eurocerasus section that also includes sweet cherry (Prunus avium&nbsp; L.) and sour cherry <em>(Prunus cerasus</em>&nbsp; L.). Sweet cherry and ground cherry are presumably early derivatives of ancestral Prunus while sour cherry arose from natural hybridization between these two species several times trough history. Determination of diversity is of great importance in every breeding program, and morphological characterization continues to be the first step for the description&nbsp; and classification of that diversity. Other available tolls for measuring diversity among germplasm are molecular markers. Aim of this research was to determine level of inter-&nbsp; and intrapopulation variability in European ground cherry<em> (P.&nbsp; fruticosa&nbsp;</em> Pall.)&nbsp; using phenotypic, SSR and SNP markers to facilitate cherry breeding. Phenotype characteristics exhibited high level of variability especially for quantitative traits, while qualitative traits had shown lower level of variability. Only presence of leaf nectaries had absence of variability; all analyzed accessions had nectaries on their leaves. Microsatellite markers confirmed high variability between and within all analyzed populations of ground cherry. Number of alleles per markers ranged from 2 (BPPCT002 and UDP-018) to 11 (BPPCT034). Analysis of 170,256 SNP markers confirmed high level of variability in DNA sequences of<em> P. fruticosa</em>. All analyzed populations of ground cherry showed overall high level of variability using all types of markers, while variability was relatively lower within each population. Association study revealed significant level of association between several traits and SNP markers. Vigor as a trait of interest showed significant association with SNP on chromosome 7 (S7_8740459) and chromosome 8 (S8_6142814). European ground cherry as one of wild relatives of economically important fruit species, such as sweet and sour cherry, holds great potential in their improvement. Its high level of diversity, revealed in this research, provides additional source of variability and makes it valuable for breeding programs.</p>

Single Nucleotide Polymorphisms (SNPs) are the most frequent genomic variations and the main basis for genetic differences among individuals and many diseases. As genotyping millions of SNPs at once is now possible with the microarrays and advanced sequencing technologies, SNPs are becoming more popular as genomic biomarkers. Like other high-throughput research techniques, genome wide association studies (GWAS) of SNPs usually hit a bottleneck after statistical analysis of significantly associated SNPs, as there is no standardized approach to prioritize SNPs or to select representative SNPs that show association with the conditions under study. In this study, a java based integrated system that makes use of major public databases to prioritize SNPs according to their biological relevance and statistical significance has been constructed. The Analytic Hierarchy Process, has been utilized for objective prioritization of SNPs and a new emerging methodology for second-wave analysis of genes and pathways related to disease associated SNPs based on a combined p-value approach is applied into the prioritization scheme. Using the subset of SNPs that is most representative of all SNPs associated with the diseases reduces the required computational power for analysis and decreases cost of following association and biomarker discovery studies. In addition to the proposed prioritization system, we have developed a novel feature selection method based on Simulated Annealing (SA) for representative SNP selection. The validity and accuracy of developed model has been tested on real life case control data set and produced biologically meaningful results. The integrated desktop application developed in our study will facilitate reliable identification of SNPs that are involved in the etiology of complex diseases, ultimately supporting timely identification of genomic disease biomarkers, and development of personalized medicine approaches and targeted drug discoveries.

The aim of the current thesis was the analysis of the genetics of sex determination of farmed fish with sexual dimorphism, using Next Generation Sequencing. Three different species of farmed fish with sex-determining systems of varying complexity were studied. Both full-sibs and more distantly related specimens of Atlantic halibut (Hippoglossus hippoglossus), Nile tilapia (Oreochromis niloticus) and European sea bass (Dicentrarchus labrax) were used for this study. Application of Restriction-site Associated DNA sequencing (RAD-seq) and double digest Restriction-site Associated DNA sequencing (ddRAD-seq), two related techniques based on next generation sequencing, allowed the identification of thousands of Single Nucleotide Polymorphisms (SNPs; &gt; 3,000) for each of the above species. The first SNP-based genetic maps for the above species were constructed during the current study. The first evidence concerning the location of the sex-determining region of Atlantic halibut is provided in this study. In the case of Nile tilapia both novel sex-determining regions and fine mapping of the major sex-determining region are presented. In the study of European sea bass evidence concerning the absence of a major sex-determining gene was provided. Indications of putative sex-determining regions in this species are also provided. The results of the current thesis help to broaden current knowledge concerning sex determination in three important farmed fish. In addition the results of the current thesis have practical applications as well, towards the production of mono-sex stocks of those species for the aquaculture industry.