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Das Herz ist das zentrale Kreislauforgan in unserem Körper und jede Abweichung seiner Funktion wirkt sich negativ auf die Homöostase des gesamten Körpers aus. Die Herzfunktion beruht auf der Synergie der Zellen, die das Organ bilden. Die detaillierte zelluläre Zusammensetzung sowie die Funktionalität der einzelnen Zellen müssen noch ermittelt werden, und diese Arbeit ist eine wichtige Ergänzung dieser Bemühungen. Dank der jüngsten Entwicklungen in den Einzelzelltechnologien sind wir nun in der Lage, Transkriptome einzelner Zellen aus komplexem Gewebe in beispiellosem Umfang zu charakterisieren. Im ersten Schritt eines solchen Experiments müssen die Zellen und Zellkerne aus dem Gewebe befreit und vereinzelt werden. Herzgewebe wirft in dieser Hinsicht einzigartige Herausforderungen auf, darunter die Knappheit des gesunden menschlichen Herzgewebes für die Forschung, das Vorhandensein von Kardiomyozyten, die aufgrund ihrer Größe nicht durch Microfluid-basierte Standardinstrumente passen und deren Multinukleation, sowie mögliche Voreingenommenheit verschiedener Methoden zur Gewebedissoziation. Hier präsentiere ich den umfassenden Zellatlas des gesunden erwachsenen menschlichen Herzens. Ich beginne mit der Methodenentwicklung zur Isolierung von einzelnen Zellen und Zellkernen aus Mausherzen. Um den Zellatlas des menschlichen Herzens zu erstellen, analysiere ich einen Datensatz von fast einer halben Million Einzelzellen und Zellkerne aus sechs Herzregionen von vierzehn gesunden Menschen. In diesem Atlas definieren wir 11 Hauptzelltypen und 62 Zellzustände des menschlichen Herzens. Ein tieferer Fokus wird auf das Herzgefäßsystem gelegt und die Zellen der arterio-venösen Achse sowie deren Wechselwirkungen und potenzielle Funktionalität werden definiert. Insgesamt präsentiert diese Dissertation einen komplex Datensatz aus menschlichem Herzgewebe und liefert neue Einblicke in die Biologie des gesunden Herzens mit Implikationen für kardiovaskuläre Erkrankungen. The heart is the central circulatory organ in our bodies and any discrepancies of its function relative to healthy homeostasis negatively impact the whole body. Cardiac function relies on the synergy of all the cells that constitute the organ. The detailed cellular composition as well as the heterogeneity and functionality of the individual cells is yet to be established and this work is a major advance in this effort. Thanks to the recent developments in single cell genomics technologies, we are now able to profile transcriptomes from individual cells of complex tissues at unprecedented scale. In the first step of such an experiment, the single cells and nuclei need to be liberated from the tissue. Heart tissue presents a unique set of challenges in this regard, including the scarcity of healthy human cardiac tissue for research, large cardiomyocytes that do not fit into the standard droplet-based instruments, multinucleation of cardiomyocytes that might skew the proportions of the recovered nuclei as well as potential bias of tissue dissociation methods. Here I present a cell atlas of the free walls, apex and septum of the healthy adult human heart. I start with methods development for the isolation of single cells and single nuclei from mouse heart. Next, I move to the building of the atlas of the human cells and nuclei, where I describe the dataset of close to half a million single cells and nuclei sampled from 14 organ donors, defining 11 major cell types and 62 cell states of the heart. A deeper focus on the cardiac vasculature defined the cells of the arterio-venous axis as well as their interactions and potential functionality. Overall, this thesis presents a joined dataset of single cells and single nuclei from human cardiac tissues and provides new insights into cardiac biology in heath with implications for cardiovascular disease.

Geschätzt mehr als 6.000 Erkrankungen werden durch Veränderungen im Genom verursacht. Ursachen gibt es viele: Eine genomische Variante kann die Translation eines Proteins stoppen, die Genregulation stören oder das Spleißen der mRNA in eine andere Isoform begünstigen. All diese Prozesse müssen überprüft werden, um die zum beschriebenen Phänotyp passende Variante zu ermitteln. Eine Automatisierung dieses Prozesses sind Varianteneffektmodelle. Mittels maschinellem Lernen und Annotationen aus verschiedenen Quellen bewerten diese Modelle genomische Varianten hinsichtlich ihrer Pathogenität. Die Entwicklung eines Varianteneffektmodells erfordert eine Reihe von Schritten: Annotation der Trainingsdaten, Auswahl von Features, Training verschiedener Modelle und Selektion eines Modells. Hier präsentiere ich ein allgemeines Workflow dieses Prozesses. Dieses ermöglicht es den Prozess zu konfigurieren, Modellmerkmale zu bearbeiten, und verschiedene Annotationen zu testen. Der Workflow umfasst außerdem die Optimierung von Hyperparametern, Validierung und letztlich die Anwendung des Modells durch genomweites Berechnen von Varianten-Scores. Der Workflow wird in der Entwicklung von Combined Annotation Dependent Depletion (CADD), einem Varianteneffektmodell zur genomweiten Bewertung von SNVs und InDels, verwendet. Durch Etablierung des ersten Varianteneffektmodells für das humane Referenzgenome GRCh38 demonstriere ich die gewonnenen Möglichkeiten Annotationen aufzugreifen und neue Modelle zu trainieren. Außerdem zeige ich, wie Deep-Learning-Scores als Feature in einem CADD-Modell die Vorhersage von RNA-Spleißing verbessern. Außerdem werden Varianteneffektmodelle aufgrund eines neuen, auf Allelhäufigkeit basierten, Trainingsdatensatz entwickelt. Diese Ergebnisse zeigen, dass der entwickelte Workflow eine skalierbare und flexible Möglichkeit ist, um Varianteneffektmodelle zu entwickeln. Alle entstandenen Scores sind unter cadd.gs.washington.edu und cadd.bihealth.org frei verfügbar. More than 6,000 diseases are estimated to be caused by genomic variants. This can happen in many possible ways: a variant may stop the translation of a protein, interfere with gene regulation, or alter splicing of the transcribed mRNA into an unwanted isoform. It is necessary to investigate all of these processes in order to evaluate which variant may be causal for the deleterious phenotype. A great help in this regard are variant effect scores. Implemented as machine learning classifiers, they integrate annotations from different resources to rank genomic variants in terms of pathogenicity. Developing a variant effect score requires multiple steps: annotation of the training data, feature selection, model training, benchmarking, and finally deployment for the model's application. Here, I present a generalized workflow of this process. It makes it simple to configure how information is converted into model features, enabling the rapid exploration of different annotations. The workflow further implements hyperparameter optimization, model validation and ultimately deployment of a selected model via genome-wide scoring of genomic variants. The workflow is applied to train Combined Annotation Dependent Depletion (CADD), a variant effect model that is scoring SNVs and InDels genome-wide. I show that the workflow can be quickly adapted to novel annotations by porting CADD to the genome reference GRCh38. Further, I demonstrate the integration of deep-neural network scores as features into a new CADD model, improving the annotation of RNA splicing events. Finally, I apply the workflow to train multiple variant effect models from training data that is based on variants selected by allele frequency. In conclusion, the developed workflow presents a flexible and scalable method to train variant effect scores. All software and developed scores are freely available from cadd.gs.washington.edu and cadd.bihealth.org.

Ciliaten sind prototypische, üblicherweise einzellige Eukaryoten mit getrennten Keimbahn- und somatischen Zellkernen. Das somatische Genom entsteht aus dem Keimbahngenom durch einen Prozess der Transposase-vermittelten DNA-Eliminierung und Genom-Neuordnung während der sexuellen Fortpflanzung. Aktuelle Modelle für die Reorganisation des Genoms bei Wimpertierchen gehen davon aus, dass kleine RNAs während der sexuellen Fortpflanzung in den sich entwickelnden somatischen Kern transportiert werden und Transposasen dabei helfen, keimlinienspezifische Sequenzen zu identifizieren und auszuschneiden. Diese Sequenzen, die so genannten intern eliminierten Sequenzen (IES), und ihre Exzisasen werden von einer Maschinerie begleitet, die ihre Entfernung durchführt. Dazu gehören Dicer-ähnliche und Piwi/Argonaute-Proteine, die kleine RNAs erzeugen und transportieren, sowie Proteine, die das Chromatin verändern und die DNA für die Exzision zugänglich machen. Blepharisma gehört zu einer früh divergiereden Klasse von Ciliaten, die als Heterotrichea bekannt sind. Obwohl die Reorganisation des Genoms bei später divergierenden Ciliaten wie den oligohymenophoren Ciliaten Tetrahymena und Paramecium und den spirotrichen Oxytricha untersucht wurde, gibt es deutliche Unterschiede in der Art und Weise, wie sie dies tun. Die Untersuchung dieses Prozesses in einem früh divergiereden Ciliaten wie Blepharisma ist ein wichtiger Beitrag zum Verständnis, wie konserviert die verschiedenen Elemente der Genom- Reorganisationsmaschinerie unter Ciliaten sind. Diese Arbeit bietet den ersten Blick aus genomischer Sicht auf die verschiedenen Teilnehmer und mutmaßlichen Mechanismen der Genomreorganisation in Blepharisma. Mittels Long-Read-Sequenzierung und Annotationsmethoden, die auf die atypischen Genomeigenschaften von Blepharisma zugeschnitten sind, wurden annotierte Referenzgenome für die somatischen und Keimbahnkerne von Blepharisma stoltei (Stamm ATCC 30299) erstellt. Das somatische Genom von B. stoltei ist kompakt (41 Mb), gen-dicht (25710 Gene) und enthält kurze, 15-16 Nukleotide umfassende spliceosomale Introns. Wir haben Schlüsselkomponenten identifiziert, die an der Reorganisation des Genoms im somatischen Genom von Blepharisma beteiligt sind, und sie mit denen der Modell-Ciliaten Paramecium, Tetrahymena und Oxytricha verglichen. Es wurden vier Transposase-Familien gefunden, die in den somatischen und Keimbahn-Genomen kodiert sind, nämlich die PiggyBac-,Tc1/Mariner-, Mutator- und Merlin-Familien. Es ist bekannt, dass PiggyBac-Transposasen die wichtigsten Transposasen sind, die in den Modell-Ciliaten Paramecium und Tetrahymena an der Reorganisation des Genoms beteiligt sind, während sie in Oxytricha, wo vermutlich eine Transposase aus einer anderen Familie verwendet wird, gänzlich fehlen. In Paramecium koordinieren sechs somatisch kodierte PiggyBacs, die nicht zur Katalyse fähig sind, sowie ein katalytisch vollständiges Homolog, namens PiggyMac, die DNA-Exzision. Dies ähnelt der Situation in Blepharisma, wo es dreizehn Homologe der PiggyBac-Transposase gibt, von denen nur eine eine vollständige katalytische Triade besitzt und daher wahrscheinlich die primäre Exzisase ist. Die keimbahnbegrenzten genomischen Regionen von Blepharisma wurden ebenfalls charakterisiert. Die IES von Blepharisma haben zwei wesentliche Merkmale mit den IES von Paramecium gemeinsam, nämlich eine periodische Längenverteilung für kurze IES und überwiegend durch TA-Dinukleotide abgegrenzte IES-Grenzen. Wir haben auch eine Klasse von kleinen RNAs („small RNAs“ ) mit 24 Nukleotiden identifiziert, die mit fortschreitender Entwicklung in Blepharisma zunehmend den IESs zugeordnet werden. Diese Tendenzen ähneln denen, die in Paramecium und Tetrahymena beobachtet wurden, weshalb wir vorschlagen, dass es sich auch hier um so genannte "Scan"-RNAs (scnRNAs) handelt, die die IES-Exzision steuern. Die phylogenetische Analyse der PiggyBac-Homologe von Blepharisma hat gezeigt, dass sie einen gemeinsamen Ursprung mit den PiggyBac-Homologen von Paramecium und Tetrahymena haben, wobei letztere evolutionär stärker divergieren als Blepharisma und auf jüngeren Zweigen des phylogenetischen Stammbaums der Ciliaten zu finden sind. Mehrere Indizien aus diesen Studien deuten daher darauf hin, dass eine PiggyBac-Transposase höchstwahrscheinlich die wichtigste IES-Exzisase in Blepharisma ist und dass der letzte gemeinsame Vorfahre der Ciliaten ebenfalls diesen Transposasetyp besaß. Ciliates are prototypical, conventionally unicellular eukaryotes with separate germline and somatic nuclei. The somatic genome arises from the germline genome through a process of transposase-mediated DNA elimination and genome rearrangement during sexual reproduction. Current models for genome reorganization in ciliates posit that small RNAs are transported to the developing somatic nucleus during sexual reproduction, aiding transposases in identifying and excising germline-specific sequences. Accompanying these sequences, known as Internally Eliminated Sequences (IESs), and their excisases is the machinery to carry out their removal. This includes Dicer-like and Piwi/Argonaute proteins, which generate and transport small RNAs, as well as proteins that alter chromatin, and make DNA accessible for excision. The ciliate Blepharisma belongs to an early diverging class of ciliates known as the Heterotrichea. Though genome reorganization has been studied in later diverging ciliates such the oligohymenophorean ciliates Tetrahymena and Paramecium and the spirotrich Oxytricha there are pronounced differences in how they do so. Studying this process in an early diverging ciliate like Blepharisma is an important contribution to the understanding of how conserved the different elements of the genome reorganization machinery among ciliates are. This thesis provides the first look, from a genomic perspective, at the various participants and putative mechanisms of genome reorganization in Blepharisma. Annotated reference genomes for the somatic and germline nuclei of Blepharisma stoltei (strain ATCC 30299) were generated using long-read sequencing and annotation methods tailored to the atypical genome properties of Blepharisma. The B. stoltei somatic genome is compact (41 Mb), gene-dense (25710 genes) and contains short, 15-16 nucleotide spliceosomal introns. We identified key components involved in genome reorganization in the Blepharisma somatic genome and compared them with those of the model ciliates Paramecium, Tetrahymena and Oxytricha. Four transposase families were found encoded in the somatic and germline genomes, namely the PiggyBac, Tc1/Mariner, Mutator and Merlin families. PiggyBac transposases are known to be the main transposases involved in genome reorganization in the model ciliates Paramecium and Tetrahymena, but are entirely absent in Oxytricha, which is thought to use a transposase from another family. In Paramecium, six somatically encoded PiggyBacs incapable of catalysis, plus one catalytically complete homolog called the PiggyMac, coordinate DNA excision. This resembles the situation in Blepharisma, which has thirteen homologs of the PiggyBac transposase, only one of which has a complete catalytic triad and is hence likely to be the primary excisase. The germline-limited genomic regions of Blepharisma were also characterized. Blepharisma IESs share two key features with the IESs of Paramecium, namely a periodic length distribution for short IESs and predominantly TA-dinucleotide delineated IES boundaries. We also identified a class of 24-nucleotide small RNAs that increasingly map to IESs as development progresses in Blepharisma. These trends are similar to those observed in Paramecium and Tetrahymena, hence we propose that they are also so-called “scan” RNAs (scnRNAs) that guide IES excision. Phylogenetic analysis of the Blepharisma PiggyBac homologs showed that they share common ancestry with the PiggyBac homologs of Paramecium and Tetrahymena, where the latter are evolutionarily more divergent than Blepharisma and are located on more recently diverging branches of the ciliate phylogenetic tree. Several lines of evidence from these studies therefore indicate that a PiggyBac transposase is the most likely the main IES excisase in Blepharisma and that the last ciliate common ancestor also possessed this type of transposase.

Objective: Due to widespread presence and exposure to environmental pollutants, structural and functional changes in membrane transporters could occur, leading to plasental transport of these compounds. In this study, the effects of PCBs on SLC abd ABCB1 membrane transport molecules were evaluated. Materials and Methods: Hemochorial structured human placenta and endotheliochorial structured dog placenta were analyzed for 28 pollutants (PCB, PBDE, PAH and Organochlorines) using GC-MS. The expression profile of the placental whole genome were investigated with RNAseq, and in silico (molecular chelation) and in vitro (SLC and ABCB1 mRNA expression in the placental cell line HTR8/SVneo treated with PCB 101, PCB118) were evaluated. Results: PCB101 826.4μg/kg in one sample out of 60 samples tested; In 23 samples, PCB118 was found to be between 0.14 and 41.9μg/kg. In the bioinformatics findings, there were differences in 742 genes between PCB positive and negative samples in 55 samples that were sequenced (p, Amaç: Çevresel kirletici maruziyetine bağlı olarak işlevselliği değişen ve bozulan membran transportları nedeniyle, bu maddeler plasental bariyeri geçerek plasental kan dolaşımına geçebilmektedir. Çalışmada, çevresel kirleticilerin bu transport proteinleriyle etkileşimlerinin moleküler boyutta incelenmesi amaçlanmaktadır. Gereç ve Yöntem: Araştırma kapsamında hemokoryal yapıya sahip insan ve endotelyokoryal yapıya sahip köpek plasentasında; 28 kirleticinin analizi GC-MS ile yapılmış (PCB, PBDE, PAH ve Organik klorlu pestisitler); RNAseq ile plasental tüm genom ifade profili araştırılmış, in siliko (moleküler kenetleme) ve in vitro (PCB 101, PCB118 uygulanan plasental hücre hattı HTR8/SVneo’da SLC ve ABCB1 mRNA ifadesi) değerlendirilmiştir. Bulgular: Test edilen 60 örnek içerisinde bir örnekte PCB101 826.4μg/kg; 23 örnekte ise PCB118 0.14 ile 41,9μg/kg arasında bulundu. Biyoinformatik bulgularda sekans analizi yapılan 55 numunede PCB pozitif ve negatif numuneler arasında 742 gende farklılık bulundu (p

Amaç: Bu çalışma, bir makine öğrenmesi yöntemi olan XGBoost yöntemi ile açık erişimli kolorektal kanser gen verilerini sınıflandırmayı ve temel genleri tanımlamayı amaçlamaktadır.Gereç ve Yöntem: Çalışmada açık erişimli kolorektal kanser gen veri seti kullanıldı. Veri seti, sağlıklı kontrollerden 10 mukozanın ve kolorektal kanserli 12 hastanın kolon mukozasının gen dizileme sonuçlarını içeriyordu. Hastalığı sınıflandırmak için makine öğrenmesi yöntemlerinden biri olan XGboost kullanıldı. Model performansı için doğruluk, dengelenmiş doğruluk, duyarlılık, seçicilik, pozitif tahmin değeri ve negatif tahmin değeri performans metrikleri değerlendirildi.Bulgular: Değişken seçim yöntemine göre 17 gen seçilmiş ve bu girdi değişkenleri ile modelleme yapılmıştır. Modelleme sonuçlarından elde edilen doğruluk, dengeli doğruluk, duyarlılık, özgüllük, pozitif tahmin değeri, negatif tahmin değeri ve F1 puanı sırasıyla %95.5, %95.8, %91.7, %1, %1 ve %90.9 ve %95.7 idi. XGboost tekniği sonucundan elde edilen değişken önemliliklerine göre, CYR61, NR4A, FOSB ve NR4A2 genleri kolorektal kanser için biyolojik belirteçler olarak kullanılabilir.Sonuç: Bu araştırma sonucunda kolorektal kanserle bağlantılı olabilecek genlerin yanı sıra hastalığa yönelik genetik biyobelirteçler de belirlendi. Gelecekte, tespit edilen genlerin güvenilirliği doğrulanabilir, bu genlere dayalı olarak terapötik prosedürler oluşturulabilir ve klinik pratikteki yararları belgelenebilir., Purpose: This study aims to classify open-access colorectal cancer gene data and identify essential genes with the XGBoost method, a machine learning method.Materials and Methods: The open-access colorectal cancer gene dataset was used in the study. The dataset included gene sequencing results of 10 mucosae from healthy controls and the colonic mucosa of 12 patients with colorectal cancer. XGboost, one of the machine learning methods, was used to classify the disease. Accuracy, balanced accuracy, sensitivity, selectivity, positive predictive value, and negative predictive value performance metrics were evaluated for model performance.Results: According to the variable selection method, 17 genes were selected, and modeling was performed with these input variables. Accuracy, balanced accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score obtained from modeling results were 95.5%, 95.8%, 91.7%, 1%, 1%, and 90.9%, and 95.7%, respectively. According to the variable impotance acquired from the XGboost technique results, the CYR61, NR4A, FOSB, and NR4A2 genes can be employed as biomarkers for colorectal cancer. Conclusion: As a consequence of this research, genes that may be linked to colorectal cancer and genetic biomarkers for the illness were identified. In the future, the detected genes' reliability can be verified, therapeutic procedures can be established based on these genes, and their usefulness in clinical practice may be documented.

Çoğu normal doku hücresiyle karşılaştırıldığında kanser hücrelerinde belirgin olarak farklı metabolik yolaklarda değişiklikler görülür. Omik tabanlı veri entegrasyonu, mide kanseri araştırmalarında kapsamlı bir şekilde uygulanmıştır. Bu çalışmalar, mide kanseri heterojenliği ve evrelemesi ile bağlantılı çok sayıda mutasyon, gen ekspresyon farklılıkları, protein farklılıkları, epigenetik mutasyonlar ve metabolit konsantrasyon farklılıklarını başarıyla tanımlamıştır. Son zamanlarda, mide kanserinin genomik altyapısı kapsamlı bir şekilde araştırılmış ve gözden geçirilmiştir. Kanser genom atlası ve Asya Araş- tırma Grubu verileri dahil olmak üzere tüm genomik verilerin kullanımı ile mide kanserine karşı klinik terapötiklere rehberlik edebilecek yeni ve sağlam moleküler sınıflandırıcıların geliştirilmesine olanak sağlamıştır. Proteomik, protein ekspresyonu ve translasyon sonrası modifikasyonlar hakkında ek bilgi sağlayarak genomik ve transkriptomik yaklaşımları tamamlar. Şimdiye kadar mide kanserindeki proteomik çalışmaların çoğu, plazma örneklerinden biyobelirteçlerin keşfine odaklanmıştır. Proteomik verilerinin diğer tipteki omik verileriyle entegrasyonu, somatik mutasyonlarla ilişkili sinyal yollarının aydınlatılmasına da olanak sağladı. Farklı transkriptomik alt tipleri ortaya çıkan mide kanserinin sınıflandırılması için gen ekspresyonu da uygulanmıştır. Hem popülasyon hem de tek hücre düzeyinde gen ekspresyonu profili, mide kanserinin heterojenliğini ve immün mikroçevre ile mide kanseri arasındaki karmaşık ilişkiyi aydınlatır ve bu da doğru tanı ve kişiselleştirilmiş terapötik yaklaşımlar geliştirmek için değerli ipuçları sağlayabilir. Metabolomik çalışmalar ile plazma örneklerinden mide kanseri ile ilişkili biyobelirteçlerin keşfine odaklanıldı. Hedeflenen veya hedeflenmeyen metabolomik analizler kullanılarak plazma, idrar, mide suyu ve karsinom dokularında çok sayıda metabolik değişiklik tanımlanmıştır. Genomik, transkriptomik, proteomik ve metabolomik araştırmalar hücreler dokular ve organlarla ilişkili çoklu hastalıklarda etiyolojik süreçlerin geniş ölçekli kesitlerini elde etme imkanı sağlamaktadır. Bunlar, geleneksel yaklaşımların ötesine geçerek bazı spesifik bozuklukların kritik biyolojik proseslerini belirlenmesine de olanak sağlamaktadır. Omik özellikler ile mide kanseri gelişimi arasında güçlü ilişkiler ortaya koyan mide kanseri araştırmalarında Omik çalışmaları yaygın olarak uygulanmıştır. Genom, transkriptom, proteom ve metabolom düzeylerinden elde edilen omik verileri ile mide kanseri kapsamlı bir şekilde katmanlara ayrılmıştır ve ortaya çıkan alt tipler, terapötik sonuçlarla güçlü korelasyonlar göstermektedir. Çoklu omik verilerinin sistem biyolojisi tabanlı entegrasyonu, kanser teşhisi ve tedavisine ilişkin birçok öngörü sağlamıştır

Genome-Mining- und Bioinformatik-Technologien sind in der heutigen Zeit f��r die Suche nach neuartigen Sekund��rmetaboliten (SM) unverzichtbar geworden. SM sind eine gro��e Gruppe von Verbindungen mit unterschiedlichen Strukturen und Eigenschaften. Sie werden meist von Enzymen produziert, deren entsprechende Gene im Genom kolokalisiert sind und in biosynthetischen Genclustern (BGC) organisiert sind. Die Identifizierung und Suche von BGC ist ein Schl��sselaspekt der Naturstoffbioinformatik geworden. Dar��ber hinaus ist die Entdeckung neuer SM-Klassen in den Genomen von Pilzen, sogenannter ���Dark Matter���-BGC, ein Gegenstand derzeitiger Forschung. In dieser Dissertation wurden verschiedene Themen mit dem Ziel behandelt, den Nachweis und die Analyse exotischer Biosynthesewege von SM zu erleichtern. Diese verschiedenen Themen besitzen als gemeinsamen roten Faden die Suche und Beschreibung von SM-BGC. Diese Doktorarbeit umfasst mehrere ver��ffentlichte und eingereichte Studien, die in einer angemessenen Reihenfolge thematisch geordnet sind. Das erste angesprochene Thema ist die Identifizierung neuer BGC in Pilzen. Zu diesem Zweck wurde eine neue Methode zum Analysieren von Pilzgenomen eingef��hrt, diese detektiert ribosomal synthetisierte und posttranslational modifizierte Peptide (RiPPs) durch Kombination und Anpassung vorhandener Werkzeuge, gefolgt von einer umfangreichen manuellen Kurierung basierend auf der Identifizierung konservierter Dom��nen, (vergleichende) phylogenetische Analysen und durch die Anwendung von RNASeq-Daten. RiPPs sind eine sehr vielf��ltige Gruppe von SM und wurden vor kurzem in Pilzgenomen eingehend untersucht. Gene, die an der Biosynthese von RiPPs in Pilzen beteiligt sind, wie f��r viele andere SM, sind in BGC gepackt. Die vorliegende Ver��ffentlichung ist der erste Bericht ��ber das Potenzial der Pilzgattung Trichoderma zur Produktion von RiPPs. Erw��hnenswert ist, dass die mit dieser neuartigen Methode entdeckten Cluster, Gene beinhalten die Enzyme kodieren f��r den Biosyntheseweg f��r neuartige uncharakterisierte Pilz-RiPPs. Neben dem Aspekt, nach neuartigen BGCs zu suchen, war die eingehende Analyse der gefundenen BGC ein Ziel. BGC k��nnen sogenannte Gap-Gene enthalten, die nicht an der Biosynthese des SM beteiligt sind. Gap-Gene von Genen zu unterscheiden, die an der Biosynthese beteiligt sind, ist eine langwierige, teure und m��hsame Aufgabe. Diesem Thema widmeten sich zwei Studien, von denen die erste das Functional Order Tool (FunOrder) als halbautomatische Methode zur Identifizierung koevolution��r verkn��pfter Gene in BGC vorstellte. Die Ergebnisse legen nahe, dass die Koevolution von Proteinfamilien f��r die Differenzierung von Gap-Genen von biosynthetisch aktiven Genen genutzt werden kann. In der anschlie��enden Studie wird das verbesserte und vollautomatisierte FundOrder 2 vorgestellt, bei den fr��heren Einschr��nkungen durch die Einf��hrung einer vollautomatisierten und verbesserten Bestimmung von koevolvierten Genen behoben wurden. Der automatisierte Nachweis koevolvierender Gene verwendet mehrere mathematische Indizes, um die optimale Anzahl von Gengruppen in den FunOrder-Daten zu bestimmen und die Implementierung von k-Means-Clustering basierend auf den ersten drei Hauptkomponenten (PC) einer Hauptkomponentenanalyse (PCA) bestimmt diese. FunOrder 2 kann als wesentliche Verbesserung gegen��ber seinem Vorg��nger angesehen werden, insbesondere durch die automatisierte Analyse ohne Bias und die Anpassung an gr����ere Datenbanken. Im weiterer Folge wird Sequenzierung, Assemblierung und Analyse neuartiger uncharakterisierter Pilzarten thematisiert, mit dem Hauptfokus auf die Suche und Analyse ihres SM-Produktionspotenzials. Vier Genome wurden sequenziert und in zwei Studien pr��sentiert, die das letzte Thema dieser Arbeit behandeln. Zun��chst wird die Genomsequenz des schwarzen hefe��hnlichen Pilz Aureobasidium pullulans var. aubasidani CBS 100524, mit industrieller Relevanz durch ausgeschiedene extrazellul��re Polysaccharide, vorgestellt und kurz beschrieben. Darauf folgt eine Studie, die eine eingehende vergleichende Genomanalyse und die phylogenetische Reklassifizierung von drei sequenzierten Wardomyces moseri St��mmen durchf��hrt. W. Gams beschrieb den Ascomyceten W. moseri erstmals 1995. W��hrend einer phylogenetischen Studie im Jahr 2016 wurde W. moseri als phylogenetisch fehlplaziert beschrieben und sollte daher neu bewertet werden. Das metabolische Potenzial dieses historischen Pilzes wurde analysiert und seine Taxonomie neu bewertet, indem die Genome des Ex-Isotyp-Stamms W. moseri CBS 164.80 und zwei Isolate von der anderen Seite der Welt, W. moseri TUCIM 5827 und TUCIM 5799, sequenziert wurden. Es konnte gezeigt werden, wie historische St��mme aus bereits bestehenden Stamm-Sammlungen f��r die Suche nach neuartigen Naturstoffen benutzt werden k��nnen. Im Anhang aufgef��hrt sind abschlie��end interdisziplin��re Studien, die aus Kooperationen mit verschiedenen Arbeitsgruppen hervorgegangen sind., Genome mining and bioinformatics technologies have become essential to the discovery process of novel secondary metabolites (SMs). SMs are a vast group of compounds with different structures and properties. Enzymes whose corresponding genes are co-localized in the genome, organized in biosynthetic gene clusters (BGCs), readily produce them. The identification and search of BGCs is a key aspect of natural product bioinformatics. Further, the detection of novel SM classes in the genomes of fungi, so termed ���dark-matter��� BGCs, is an ongoing subject of research. In this thesis, various topics were addressed for the ultimate goal to facilitate the detection and analysis of exotic biosynthetic pathways of SMs. These different subjects are connected by the search for and description of SM BGCs. This thesis encloses several published and submitted studies and orders them thematically. The first issue addressed is the identification of novel BGCs in fungi, a novel method to mine fungal genomes for ribosomally synthesized and post-translationally modified peptides (RiPPs) by combining and adapting existing tools followed by extensive manual curation based on conserved domain identification, (comparative) phylogenetic analysis, and RNASeq data was introduced for this purpose. RiPPs are a highly diverse group of SM and have been recently started to be studied in more depth in fungal genomes. Genes involved in the biosynthesis of fungal RiPPs, as for many other SMs, are packed in BGCs. The presented publication is the first report of the potential of the fungal genus Trichoderma to produce RiPPs and the clusters detected by this novel method encode genes that ultimately lead to novel uncharacterized fungal RiPPs. Besides the aspect to search for novel BGCs, the in depth analysis of detected BGCs was a target. BGCs may contain so-called gap genes, which are not involved in the biosynthesis of the SM. To differentiate gap genes from genes involved in the biosynthesis is a lengthy, expensive and arduous task. This topic was addressed by two studies the first describing and introducing the Functional Order tool (FunOrder), as a semi-automated method for the identification of co-evolutionary linked genes in BGCs. The results suggest that protein family co-evolution can be leveraged for the differentiation of gap genes from genes involved in the biosynthesis of a SM. In the subsequent study, the improved and fully automated FunOrder 2 is presented, where previous limitations were address by introducing a fully automated and enhanced determination of co-evolved genes. The automated detection of co-evolving genes uses several mathematical indices to determine the optimal number of gene groups in the FunOrder output and the implementation of k-means clustering based on the first three principal components (PC) of a principal component analysis (PCA) detects them. FunOrder 2 can be seen as a major improvement over its predecessor, especially considering the unbiased automated analysis and the adaptation to larger databases. The last theme is the topic of sequencing, assembly and analysis of novel uncharacterized fungal species primarily for the search and analysis of their slumbering SM production potential. Four genomes have been sequenced included in two studies that address the final topic in this thesis. First, the genome sequence of the black yeast-like strain Aureobasidium pullulans var. aubasidani CBS 100524 with industrial relevance due to excreted extracellular polysaccharides is introduced and briefly described. This is followed by a study performing an in depth comparative genomic analysis and phylogenetic replacement of three sequenced Wardomyces moseri strains. W. Gams first described the ascomycete W. moseri in 1995. During a phylogenetic study in 2016 W. moseri was suggested to be phylogenetically misplaced and should therefore be re-evaluated. The metabolic potential of this historic fungus was analyzed and its taxonomy re-evaluated, by sequencing the genomes of the ex-isotype strain W. moseri CBS 164.80 and two isolates from the opposite side of the world, W. moseri TUCIM 5827 and TUCIM 5799. It could be demonstrated how historic strains from already existing collections can be used for the search of novel natural products.Finally listed in the appendix, are interdisciplinary studies fruited from collaborations with different working groups

Die Prozesse, durch die Organismen an ihre Umwelt angepasst werden, und die zur Vielfalt der Organismen führen, sind Gegenstand evolutionsbiologischer Fragestellungen. Üblicherweise startet Artenbildung durch das graduelle Auftreten physischer Barrieren, welches dann in reproduktive Inkompatibilitäten und/oder ökologische Differenzierungen mündet. Obwohl die weltweite Biodiversität hauptsächlich durch wirbellose Organismen gestellt wird, sind diese in Studien zu Artenbildungsmechanismen unterrepräsentiert. Eine beeindruckende Evolutionsgeschichte von etwa 550 Millionen Jahren weisen die Mollusken auf, bei denen es zu einer dramatischen Variation der Körperbaupläne und einer enormen morphologischen Variabilität kam. Süßwassermollusken sind besonders als Studienobjekte geeignet, da sie ein durch natürliche Barrieren begrenztes Habitat bewohnen. Die Süßwasserschnecken der Gattung Brotia bilden einen Artenschwarm im Kaek River in Thailand und sind eine der wenigen bekannten Schneckenradiationen im Süßwasser. Brandt beschrieb zehn Brotia-Arten, dieser Befund wurde später auf sieben Arten begrenzt. Demnach unterscheiden sich diese Schnecken in der Morphologie ihrer Schale und bilden drei verschiedene Radulatypen aus. Die Analysen dieses integrierten evolutionssystematischen Datensatzes aus traditionellen und modernen morphologischen und genetischen Methoden deuten darauf hin, dass die Anzahl an Brotia-Arten noch kleiner ist als die vorherigen Studien vermuten ließen. Es finden sich jeweils zwei genetische Cluster am Oberlauf und am Unterlauf des Kaek River; mit einer Mischzone im Mittelauf. Eine Analyse der genetisch bestimmten Individuen dieser Cluster zeigte signifikante Schalenmorphologische Unterschiede. Weiterführende Studien müssen klären, ob diese durch genomische Untersuchungen aufgedeckten Cluster lediglich Populationen weniger, aber phänotypisch extrem diverser Brotia-Arten sind. Evolutionary biologists try to untangle and explain two major features of the living world, viz. the process by which organisms adapt to their environment and the processes that lead to species diversity. Speciation might start by physical isolation, which can also be accumulative and further result in reproductive incompatibilities and/or ecological differences. Although invertebrates represent the majority of biodiversity they are underrepresented in speciation studies. The at least 550 million years of evolution within the phylum Mollusca have resulted in a dramatic variation in body plans and enormous morphological diversity, which makes them an ideal group for comparative studies of phenotypic diversity, speciation and radiation. Freshwater mollusc taxa are exceptionally suited for such studies because they inhabit an environment with clear boundaries that act as dispersal barriers. The Brotia species flock found along the Kaek River in northern Thailand is one of very few known radiations of gastropods in a riverine setting. The species were reported to exhibit distinct shell morphologies and radula types. The main objective of this study was to investigate this species swarm, potentially being a new system to study speciation and even adaptive radiation in invertebrates in a riverine setting. Morphology and ecology, inter- and intraspecific divergence of Brotia were investigated. The analyses of an integrated dataset found hints that the actual number of species might be substantially lower than expected. Both, mitochondrial and nuclear markers revealed a geographic structure separating headwaters from the lower river courses, with an area of admixture in between. Additionally, in both geographic areas two clusters were identified, which are significantly different in morphology. Future studies will have to determine whether these clusters are populations of originally only two, but now highly diverse Brotia species.

Simple Summary The number of local farm animal breeds is declining worldwide. However, these breeds have different degrees of genetic diversity. Measuring genetic diversity is important for the development of conservation strategies and, therefore, various genomic analysis techniques are available. The aim of the present work was to shed light on the use of these techniques in diversity studies of local breeds. In summary, a total of 133 worldwide studies that examined genetic diversity in local cattle, sheep, goat, chicken and pig breeds were reviewed. The results show that over time, almost all available genomic techniques were used and various diversity parameters were calculated. Therefore, the present results provide a comprehensive overview of the application of these techniques in the field of local breeds. This can provide helpful insights into the advancement of the conservation of breeds with high genetic diversity. Abstract Globally, many local farm animal breeds are threatened with extinction. However, these breeds contribute to the high amount of genetic diversity required to combat unforeseen future challenges of livestock production systems. To assess genetic diversity, various genotyping techniques have been developed. Based on the respective genomic information, different parameters, e.g., heterozygosity, allele frequencies and inbreeding coefficient, can be measured in order to reveal genetic diversity between and within breeds. The aim of the present work was to shed light on the use of genotyping techniques in the field of local farm animal breeds. Therefore, a total of 133 studies across the world that examined genetic diversity in local cattle, sheep, goat, chicken and pig breeds were reviewed. The results show that diversity of cattle was most often investigated with microsatellite use as the main technique. Furthermore, a large variety of diversity parameters that were calculated with different programs were identified. For 15% of the included studies, the used genotypes are publicly available, and, in 6%, phenotypes were recorded. In conclusion, the present results provide a comprehensive overview of the application of genotyping techniques in the field of local breeds. This can provide helpful insights to advance the conservation of breeds.

We assessed SARS-CoV-2 genome diversity and probable impact on epidemiology, immune response and clinical disease in Turkey.Complete genomes and partial Spike (S) sequences were accessed from the Global Initiative on Sharing Avian Influenza Data (GISAID) database. The genomes were analysed for variations and recombinations using appropriate softwares.Four hundred ten complete genomes and 206 S region sequences were included. Overall, 1,200 distinct nucleotide variations were noted. Mean variation count was 14.2 per genome and increased significantly during the course of the pandemic. The most frequent variations were identified as A23403G (D614G;92.9,%), C14408T (P323L, 92.2%), C3037T (89.8%), C241T (83.4%) and GGG28881AAC (RG203KR, 62.6%). The A23403G mutation was the most frequent variation in the S region sequences (99%). Most genomes (98.3%) belonged in the SARS-CoV-2 haplogroup A. No evidence for recombination was identified in genomes representing sub-haplogroup branches. The variants B.1.1.7, B.1.351 and P.1 were detected, with a statistically-significant time-associated increase in B.1.1.7 prevalence.We described prominent SARS-CoV-2 variations as well as comparisons with global virus diversity. Continuing a molecular surveillance in agreement with local disease epidemiology appears to be crucial, as vaccination and mitigation efforts are ongoing. (English) [ABSTRACT FROM AUTHOR] Turkiye kaynakli SARS-CoV-2 genomik dizi cesitliliginin ve epidemiyoloji, bagisik yanit ve hastalik seyri uzerine muhtemel etkili varyasyonlarin incelenmesi.“Global Initiative on Sharing Avian Influenza Data” (GISAID) veri tabaninda yer alan tum genom ve “Spike” (S) bolgesine ait verilere ulasilarak uygun yazilimlar yardimiyla varyasyon ve muhtemel rekombinasyonlar arastirildi.Toplam 410 tam genom ve 206 S bolgesi dizisi incelendi, 1200 farkli nukleotid duzeyinde varyasyon saptandi. Genom basina toplam varyasyon ortalamasi 14.2 olarak hesaplandi ve salginin ilerleyisi suresince istatistiksel olarak anlamli artis izlendi. En sik saptanan varyasyonlar A23403G (D614G;92.9,%), C14408T (P323L, 92.2%), C3037T (89.8%), C241T (83.4%) ve GGG28881AAC (RG203KR, 62.6%) olarak siralandi. S bolgesi dizilerinde de A23403G, en yaygin varyasyon (%99) seklinde izlendi. Incelenen genomlarin siklikla (%98.3) SARS-CoV-2 A haplogrubuna ait oldugu goruldu. Alt haplogruplari temsil eden genomlarda yapilan incelemelerde rekombinasyon bulgusu saptanmadi. Calisma grubunda B.1.1.7, B.1.351 ve P.1 varyantlari tespit edildi. B.1.1.7 prevalansinda izlenen zamanla iliskili artis, istatistiksel olarak anlamli bulundu.Calismada ulkemiz kaynakli SARS-CoV-2 genomlarinda belli basli varyasyonlar belirlenmis ve kuresel virus cesitliligi isiginda degerlendirilmistir. Kontrol ve asilama calismalari ile eszamanli olarak onemli varyantlarin tanimlanabilmesi icin, bolgesel epidemiyoloji ile uyumlu molekuler surveyans calismalari surdurulmelidir. (Turkish) [ABSTRACT FROM AUTHOR] Copyright of Turkish Journal of Biochemistry / Turk Biyokimya Dergisi is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Next-generation sequencing technologies have revolutionized our ability to assess genetic variation across the genome of patients in a variety of clinical contexts. However, interpreting the clinical relevance of variation is now the major bottleneck for implementation of genomic health care in rare disease, cancer, and precision medicine settings. Although terminologies exist to describe clinical data, standard formats for capturing clinical data about individuals have not existed, which hinders data exchange and limits the ability to perform analyses. The Human Phenotype Ontology was initially developed in 2008 to provide a standard ontology for the analysis of clinical phenotype data with a focus in medical genetics and rare disease (RD). It has grown to become the de facto international standard for RD phenotype analysis. The emerging Phenopacket standard of the Global Alliance for Genomics and Health provides a structural for capturing and computing over detailed descriptions of individual patients and is being developed to enable standardized phenotypic data exchange in medical and scientific settings., Sequenzierungstechnologien der nächsten Generation verändern grundlegend unsere Fähigkeit, genetische Variationen im gesamten Patientengenom in einer Vielzahl von klinischen Kontexten zu erkennen. Die Interpretation der klinischen Relevanz von Variationen ist heute der größte Engpassfaktor in der Einführung der genomischen Gesundheitsversorgung bei seltenen Erkrankungen, Krebs und der Präzisionsmedizin. Obwohl es Terminologien zur Beschreibung klinischer Daten gibt, existierte bisher keine Standardisierung bei der Erfassung klinischer Daten über einzelne Patienten. Dadurch wird der Datenaustausch erschwert und die Durchführung von Analysen einschränkt. Die Human Phenotype Ontology wurde 2008 entwickelt, um eine Standardontologie für die Analyse von klinischen Phänotypdaten mit Fokus auf medizinische Genetik und seltene Erkrankungen (SE) bereitzustellen. Sie hat sich zum internationalen De-facto-Standard für die Phänotypanalyse von SE entwickelt. Der im Entstehen begriffene Phenopacket-Standard der Global Alliance for Genomics and Health bietet ein Gerüst für die Erfassung und Berechnung überdetaillierter Beschreibungen einzelner Patienten und wird weiterentwickelt, um einen standardisierten phänotypischen Datenaustausch im medizinischen und wissenschaftlichen Bereich zu ermöglichen., Mission – Innovation: Telematics, eHealth and High-Definition Medicine in Patient-Centered Acute Medicine, p. 139