Analysis of the vomeronasal organ transcriptome reveals variable gene expression depending on age and function in rabbits

The vomeronasal organ (VNO) is a chemosensory organ specialized in pheromone detection that shows a broad morphofunctional and genomic diversity among mammals. However, its expression patterns have only been well-characterized in mice. Here, we provide the first comprehensive RNA sequencing study of the rabbit VNO across gender and sexual maturation stages. We characterized the VNO transcriptome, updating the number and expression of the two main vomeronasal receptor families, including 128 V1Rs and 67 V2Rs. Further, we defined the expression of formyl-peptide receptor and transient receptor potential channel families, both known to have specific roles in the VNO. Several sex hormone-related pathways were consistently enriched in the VNO, highlighting the relevance of this organ in reproduction. Moreover, whereas juvenile and adult VNOs showed significant transcriptome differences, male and female did not. Overall, these results contribute to understand the genomic basis of behavioural responses mediated by the VNO in a non-rodent modelS

Update of the keratin gene family: evolution, tissue-specific expression patterns, and relevance to clinical disorders.

Intermediate filament (IntFil) genes arose during early metazoan evolution, to provide mechanical support for plasma membranes contacting/interacting with other cells and the extracellular matrix. Keratin genes comprise the largest subset of IntFil genes. Whereas the first keratin gene appeared in sponge, and three genes in arthropods, more rapid increases in keratin genes occurred in lungfish and amphibian genomes, concomitant with land animal-sea animal divergence (~ 440 to 410 million years ago). Human, mouse and zebrafish genomes contain 18, 17 and 24 non-keratin IntFil genes, respectively. Human has 27 of 28 type I "acidic" keratin genes clustered at chromosome (Chr) 17q21.2, and all 26 type II "basic" keratin genes clustered at Chr 12q13.13. Mouse has 27 of 28 type I keratin genes clustered on Chr 11, and all 26 type II clustered on Chr 15. Zebrafish has 18 type I keratin genes scattered on five chromosomes, and 3 type II keratin genes on two chromosomes. Types I and II keratin clusters-reflecting evolutionary blooms of keratin genes along one chromosomal segment-are found in all land animal genomes examined, but not fishes; such rapid gene expansions likely reflect sudden requirements for many novel paralogous proteins having divergent functions to enhance species survival following sea-to-land transition. Using data from the Genotype-Tissue Expression (GTEx) project, tissue-specific keratin expression throughout the human body was reconstructed. Clustering of gene expression patterns revealed similarities in tissue-specific expression patterns for previously described "keratin pairs" (i.e., KRT1/KRT10, KRT8/KRT18, KRT5/KRT14, KRT6/KRT16 and KRT6/KRT17 proteins). The ClinVar database currently lists 26 human disease-causing variants within the various domains of keratin proteins

Computational epigenetics : bioinformatic methods for epigenome prediction, DNA methylation mapping and cancer epigenetics

Epigenetic research aims to understand heritable gene regulation that is not directly encoded in the DNA sequence. Epigenetic mechanisms such as DNA methylation and histone modifications modulate the packaging of the DNA in the nucleus and thereby influence gene expression. Patterns of epigenetic information are faithfully propagated over multiple cell divisions, which makes epigenetic gene regulation a key mechanism for cellular differentiation and cell fate decisions. In addition, incomplete erasure of epigenetic information can lead to complex patterns of non-Mendelian inheritance. Stochastic and environment-induced epigenetic defects are known to play a major role in cancer and ageing, and they may also contribute to mental disorders and autoimmune diseases. Recent technical advances — such as the development of the ChIP-on-chip and ChIP-seq protocols for genome-wide mapping of epigenetic information — have started to convert epigenetic research into a high-throughput endeavor, to which bioinformatics is expected to make significant contributions. This thesis describes computational work at the intersection of epigenetics and genome research, aiming to address the bioinformatic challenges posed by the human epigenome. While its methods are carried over and adapted from bioinformatics and related fields (including data mining, machine learning, statistics, algorithms, optimization, software engineering and databases), its overarching goal is to contribute to epigenetic research, both directly through analyzing and modeling of epigenetic information, and indirectly through the development of practically useful methods and software toolkits. This thesis is broadly structured into four parts. The first part gives a brief introduction into epigenetic regulation and inheritance, and reviews the emerging field of computational epigenetics. The second part addresses the question of genome-epigenome interactions using machine learning methods. It is shown that accurate predictions of DNA methylation and other epigenetic modifications can be derived from the genomic DNA sequence. Based on this finding, the EpiGRAPH web service for epigenome analysis and prediction is described, and methods for refined annotation of CpG islands in the human genome are proposed. The third part is dedicated to large-scale analysis of DNA methylation, which is the best-known epigenetic phenomenon. The BiQ Analyzer software toolkit is presented, together with a bioinformatic analysis of the "National Methylome Project for Chromosome 21'; dataset, for which BiQ Analyzer had played an enabling role. This part concludes with statistical modeling of DNA methylation variation and an analysis of its implications for DNA methylation mapping in a large number of human individuals. The fourth part describes two pilot projects applying the bioinformatic concepts of this thesis to cancer epigenetics. First, genome-scale datasets are probed for evidence of a link between DNA methylation and Polycomb binding, which is believed to play a role in epigenetic deregulation of cancer cells. Second, a biomarker that tests for cancer-specific DNA methylation is optimized and validated for use in clinical settings. Arguably the most interesting result of this thesis is the unexpectedly high correlation between genome and epigenome that was found by several methods and based on multiple epigenome datasets. This finding suggests that the role of the genome for epigenetic regulation has been underappreciated, and it underlines the importance of integrated analysis of genome and epigenome. With the EpiGRAPH web service for (epi-) genome analysis and prediction, a research tool is provided to facilitate further investigation of this striking interaction.Ziel epigenetischer Forschung ist ein besseres Verständnis der Mechanismen erblicher Gen-Regulation, die nicht direkt in der DNA-Sequenz codiert sind. Epigenetische Veränderungen des Genoms — wie zum Beispiel DNA-Methylierung und Histon-Modifikationen — beeinflussen die räumliche Anordnung der DNA im Zellkern und damit auch die Gen-Expression. Epigenetische Informationen werden über viele Zellteilungen stabil weitergegeben, weswegen die epigenetische Gen-Regulation ein Schlüsselmechanismus für Zell-Differenzierung und Determinierung ist. Darüber hinaus ergeben sich aus dem unvollständigen Löschen von epigenetischen Informationen komplexe nicht-Mendelsche Vererbungsgänge. Stochastische und umweltinduzierte epigenetische Defekte spielen eine wichtige Rolle für Krebs und molekulares Altern, und sie scheinen ebenfalls psychische Störungen und Autoimmun-Erkrankungen zu beeinflussen. In Folge technischer Fortschritte — wie etwa der Entwicklung der ChIP-on-chip und ChIP-seq Protokolle zur genomweiten Kartierung epigenetischer Informationen — hat eine Transformation der epigenetischen Forschung hin zu Hochdurchsatz-Analysen begonnen, zu der die Bioinformatik einen wichtigen Beitrag leisten muss. Diese Dissertation beschreibt bioinformatische Studien an der Schnittstelle von Epigenetik und Genomforschung, mit dem Ziel einer adäquaten Antwort auf die analytischen Herausforderungen des menschlichen Epigenoms. Während ihre Methoden aus der Bioinformatik und benachbarten Gebieten (Data Mining, maschinelles Lernen, Statistik, Algorithmik, Optimierung, Software Engineering und Datenbanken) entlehnt und adaptiert sind, ist es das übergeordnete Ziel der Arbeit, einen Beitrag zur epigenetischen Forschung zu leisten; und zwar sowohl direkt durch die Analyse und Modellierung epigenetischer Daten, also auch indirekt durch die Entwicklung praktisch verwertbarer Methoden und Software-Werkzeuge. Diese Dissertation gliedert sich grob in vier Teile. Der erste Teil führt in den Themenkomplex der epigenetischen Vererbung und Gen-Regulation ein und fasst das junge Forschungsgebiet "Computational Epigenetics" zusammen. Der zweite Teil adressiert die Frage nach Genom-Epigenom-Interaktionen mit Methoden des maschinellen Lernens. Es wird gezeigt, dass aus der genomischen DNA-Sequenz eine akkurate Vorhersage der DNA-Methylierung sowie anderer epigenetischer Modifikationen abgeleitet werden kann. Basierend auf diesem Ergebnis werden der EpiGRAPH-Webservice zur Epigenom-Analyse und Vorhersage beschrieben sowie Methoden für die verbesserte Annotation von CpG-Inseln in Wirbeltier- Genomen ausgearbeitet. Der dritte Teil beschäftigt sich mit der Hochdurchsatzanalyse von DNA-Methylierung, dem bekanntesten epigenetischen Phänomen. Die BiQ Analyzer Software wird vorgestellt, und die Ergebnisse einer bioinformatischen Analyse des "National Methylome Project for Chromosome 21"-Datensatzes werden beschrieben, zu dessen Generierung der BiQ Analyzer einen fundamentalen Beitrag leisten konnte. Den Abschluss dieses Teils bildet die statistische Modellierung von DNA-Methylierungs-Variation und eine Analyse ihrer Bedeutung für die DNA-Methylierungs-Kartierung einer großen Anzahl menschlicher Individuen. Der vierte Teil beschreibt zwei Pilotprojekte, in denen die bioinformatischen Konzepte dieser Arbeit in der Krebs-Epigenetik angewandt werden. Zum einen werden epigenomische Datensätze im Hinblick auf Interaktionen zwischen DNA-Methylierung und Polycomb- Bindestellen untersucht — eine Beziehung, die vermutlich bei der epigenetischen Deregulierung von Krebszellen eine Rolle spielt. Zum anderen wird ein Biomarker für die Verxiii wendung unter klinischen Bedingungen optimiert und validiert, der eine krebsspezifische Veränderung der DNA-Methylierung detektieren kann. Das vielleicht interessanteste Ergebnis dieser Dissertation ist eine unerwartet hohe Korrelation zwischen Genom und Epigenom, die mit mehreren Methoden und für verschiedenste Epigenom-Datensätze nachgewiesen werden konnte. Dieses Ergebnis legt nahe, dass der regulatorische Einfluss des Genoms auf das Epigenom bisher nicht ausreichend gewürdigt wurde, und es unterstreicht die Wichtigkeit einer integrierten Analyse von Genom und Epigenom. Der EpiGRAPH-Webservice bietet sich als Werkzeug für eine genauere Untersuchung dieser bemerkenswerten Interaktion an

Neuroanatomical and gene expression features of the rabbit accessory olfactory system. Implications of pheromone communication in reproductive behaviour and animal physiology

Mainly driven by the vomeronasal system (VNS), pheromone communication is involved in many species-specific fundamental innate socio-sexual behaviors such as mating and fighting, which are essential for animal reproduction and survival. Rabbits are a unique model for studying chemocommunication due to the discovery of the rabbit mammary pheromone, but paradoxically there has been a lack of knowledge regarding its VNS pathway. In this work, we aim at filling this gap by approaching the system from an integrative point of view, providing extensive anatomical and genomic data of the rabbit VNS, as well as pheromone-mediated reproductive and behavioural studies. Our results build strong foundation for further translational studies which aim at implementing the use of pheromones to improve animal production and welfare

Functional analysis of DNA methylation and hydroxymethylation during eye development

DNA methylation is an epigenetic mechanism known to play roles in regulating gene expression in various developmental and disease contexts. However, little is known about its function during eye development. Two types of methylation marks, 5- methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), are thought to serve as silencing and activating signals for gene regulation, respectively. De novo methyltransferases (dnmt3 family) are responsible for the establishment of 5mC, while cytosine dioxygenases (tet family) convert 5mC into 5hmC, a stable epigenetic mark that can either remain on the genome or undergo subsequent demethylation. Here I performed gene expression and functional tests to elucidate the roles for both of these cytosine-modifying enzyme families during development, with an emphasis on the eye. All dnmt3-family and tet-family genes are expressed tissue-specifically in relevant domains during eye development. Single and double mutants for genes within dnmt3 family develop normally without any overt eye phenotype, indicating that these genes possess redundant functions during eye development. In contrast, in tet2-/-;tet3-/- mutants, retinal neurons are specified but most fail to terminally differentiate. Retinal ganglion cells lack a proper retino-tectal projection, and photoreceptors fail to generate outer segments. Mechanistically, mosaic analyses revealed a surprising cell non-autonomous requirement for tet activity during retinal neurogenesis. Through a combination of candidate gene analysis, transcriptomics and pharmacological manipulations, I identified candidate cell-extrinsic pathways regulated by tet2 and tet3. Additionally, genome-wide 5mC and 5hmC distribution profiles for retinal progenitor cells (RPCs) and differentiated retinal neurons are still currently unknown. To this end, I performed parallel bisulfite and oxidative bisulfite reactions followed by next-generation sequencing (BS/OXBS-seq) to generate the first nucleotide-resolution combined methylome/hydroxymethylome map of retinal cells during development and correlated these with gene expression. This genome- wide approach revealed expected 5mC/5hmC profiles of candidate retinal developmental genes, and identified several novel, uncharacterized genes with potential roles during RPC differentiation. These genes are candidates for further investigation to determine their functions during retinal neurogenesis. Data presented in this Dissertation uncover the role of DNA methylation and hydroxymethylation during eye development and provide the first epigenomic maps of 5mC/5hmC dynamics during retina formation.Cellular and Molecular Biolog