A Screen for Retrotransposed Imprinted Genes Reveals an Association between X Chromosome Homology and Maternal Germ-Line Methylation

Imprinted genes undergo epigenetic modifications during gametogenesis, which lead to transcriptional silencing of either the maternally or the paternally derived allele in the subsequent generation. Previous work has suggested an association between imprinting and the products of retrotransposition, but the nature of this link is not well defined. In the mouse, three imprinted genes have been described that originated by retrotransposition and overlap CpG islands which undergo methylation during oogenesis. Nap1l5, U2af1-rs1, and Inpp5f_v2 are likely to encode proteins and share two additional genetic properties: they are located within introns of host transcripts and are derived from parental genes on the X chromosome. Using these sequence features alone, we identified Mcts2, a novel candidate imprinted retrogene on mouse Chromosome 2. Mcts2 has been validated as imprinted by demonstrating that it is paternally expressed and undergoes promoter methylation during oogenesis. The orthologous human retrogenes NAP1L5, INPP5F_V2, and MCTS2 are also shown to be paternally expressed, thus delineating novel imprinted loci on human Chromosomes 4, 10, and 20. The striking correlation between imprinting and X chromosome provenance suggests that retrotransposed elements with homology to the X chromosome can be selectively targeted for methylation during mammalian oogenesis

Thamodaran. P

Not AvailableUsually, most of the genes are biallelically expressed but imprinted gene exhibit monoallelic expression based on their parental origin. Genomic imprinting exhibit differences in control between flowering plants and mammals, for instance, imprinted gene are specifically activated by demethylation, rather than targeted for silencing in plants and imprinted gene expression in plant which occur in endosperm. It also displays sexual dimorphism like differential timing in imprint establishment and RNA based silencing mechanism in paternally repressed imprinted gene. Within imprinted regions, the unusual occurrence and distribution of various types of repetitive elements may act as genomic imprinting signatures. Imprinting regulation probably at many loci involves insulator protein dependent and higher-order chromatin interaction, and/or non-coding RNAs mediated mechanisms. However, placentaspecific imprinting involves repressive histone modifications and non-coding RNAs. The higher-order chromatin interaction involves differentially methylated domains (DMDs) exhibiting sex-specific methylation that act as scaffold for imprinting, regulate allelic-specific imprinted gene expression. The paternally methylated differentially methylated regions (DMRs) contain less CpGs than the maternally methylated DMRs. The non-coding RNAs mediated mechanisms include C/D RNA and microRNA, which are invovled in RNA-guided post-transcriptional RNA modifications and RNA-mediated gene silencing, respectively. The maintenance and reprogramming of imprinting are not significantly affected by reduced expression of Dicer1 and the evolution of imprinting might be related to acquisition of DNMT3L (de novo methyltransferase 3L) by a common ancestor of eutherians and marsupials. The common feature among diverse imprinting control elements and evolutionary significance of imprinting need to be identified.Not Availabl

Maternal disruption of Ube3a leads to increased expression of Ube3a-ATS in trans

Angelman syndrome (AS) is a neurogenetic disorder characterized by severe mental retardation, ‘puppet-like’ ataxic gait with jerky arm movements, seizures, EEG abnormalities, hyperactivity and bouts of inappropriate laughter. Individuals with AS fail to inherit a normal active maternal copy of the gene encoding ubiquitin protein ligase E3A (UBE3A). UBE3A is transcribed predominantly from the maternal allele in brain, but is expressed from both alleles in most other tissues. It has been proposed that brain-specific silencing of the paternal UBE3A allele is mediated by a large (>500 kb) paternal non-coding antisense transcript (UBE3A-ATS). There are several other examples of imprinting regulation involving antisense transcripts that share two main properties: (i) the sense transcript is repressed by antisense and (ii) the interaction between sense and antisense occurs in cis. We show here that, in a mouse model of AS, maternal transmission of Ube3a mutation leads to increased expression of the paternal Ube3a-ATS, suggesting that the antisense is modulated by sense rather than the reciprocal mode of regulation. Our observation that Ube3a regulates expression of Ube3a-ATS in trans is in contrast to the other cases of sense–antisense epigenetic cis-interactions and argues against a major role for Ube3a-ATS in the imprinting of Ube3a

At Least Ten Genes Define the Imprinted Dlk1-Dio3 Cluster on Mouse Chromosome 12qF1

Background: Genomic imprinting is an exception to Mendelian genetics in that imprinted genes are expressed monoallelically, dependent on parental origin. In mammals, imprinted genes are critical in numerous developmental and physiological processes. Aberrant imprinted gene expression is implicated in several diseases including Prader-Willi/ Angelman syndromes and cancer. Methodology/Principal Findings: To identify novel imprinted genes, transcription profiling was performed on two uniparentally derived cell lines, androgenetic and parthenogenetic primary mouse embryonic fibroblasts. A maternally expressed transcript termed Imprinted RNA near Meg3/Gtl2 (Irm) was identified and its expression studied by Northern blotting and whole mounts in situ hybridization. The imprinted region that contains Irm has a parent of origin effect in three mammalian species, including the sheep callipyge locus. In mice and humans, both maternal and paternal uniparental disomies (UPD) cause embryonic growth and musculoskeletal abnormalities, indicating that both alleles likely express essential genes. To catalog all imprinted genes in this chromosomal region, twenty-five mouse mRNAs in a 1.96Mb span were investigated for allele specific expression. Conclusions/Significance: Ten imprinted genes were elucidated. The imprinting of three paternally expressed protein coding genes (Dlk1, Peg11, and Dio3) was confirmed. Seven noncoding RNAs (Meg3/Gtl2, Anti-Peg11, Meg8, Irm/‘‘Rian’’

The Role of Genomic Imprints in Placental Biology

Genomic imprinting is a process by which heritable epigenetic marks at a subset of genomic loci are established in a sex-specific manner in parental gametes and then maintained in nascent offspring. This study probes the poorly understood function of genomic imprints in placental biology. Genomic imprints are responsible for the regulation of parent-of-origin specific monoallelic expression of clusters of imprinted genes. The primary epigenetic mark that distinguishes parental alleles at imprinted loci is 5-methylcytosine in the context of cytosine-guanine (CpG) dinucleotides within differentially methylated domains (DMDs). The Dnmt1 gene encodes the maintenance DNA methyltransferase, an enzyme responsible for replicating CpG methylation that is critical throughout the process of genomic imprinting. Genetic disruption of the oocyte specific isoform of Dnmt1 (Dnmt1o) results in partial and wide-spread loss of DMD methylation during preimplantation development and has strong effects on embryonic and extraembryonic development. In this dissertation the morphology of DNMT1o-deficient placentas is examined and their abnormal phenotypes correlated with loss of methylation at specific DMDs. A strong association between loss of methylation at the Kcnq1 DMD and accumulation of trophoblast giant cells was made. In addition, an association between loss of methylation at the Peg10 DMD and loss of fetal viability and placental labyrinthine volume was made. In conjunction with my study of the Dnmt1Δ1o model, I have engineered a novel targeted deletion of the imprinted Klf14 gene and found it has an effect on placental growth. My thesis unambiguously shows that genomic imprints are essential for placental development

Spatial organisation of the immunoglobulin heavy chain locus and inter-chromosomal gene networks driving B cell development

B lymphocytes produce a wide array of antibodies to recognize a countless number of antigens. This highly diverse repertoire is produced during B cell development in the bone marrow from the immunoglobulin heavy chain (Igh) and light chain (Igk and Igl) loci. The mouse Igh is a large (~3Mb) multigene locus that contains 195 variable (V), 10 diversity (D) and 4 joining (J) genes that undergo developmentally regulated V(D)J recombination to produce the variable region of the antibody. Gene expression depends on spatial organisation of chromatin. To ensure that all V genes have a chance to recombine, they are brought into physical proximity to the D-J region by locus contraction and DNA looping. Not all V genes recombine with equal frequencies and we aim to investigate how dynamic changes in 3D structure of the Igh locus facilitate V(D)J recombination. Chromosome conformation capture techniques have revolutionised studies of genome conformation. I have applied a novel form of enriched Hi-C to study both intra-locus (cis) and genome-wide (trans) interactions of the immunoglobulin loci in pro-B and pre-B cells. This method provides a higher resolution than Hi-C and is less biased than 4C and 5C. I have mapped all cis interactions within the Igh locus to produce a comprehensive view of the structure of the locus prior to recombination. This approach has shown that the 3’ superanchor (3’CBEs) and the Intergenic Control Region 1 (IGCR1) containing CTCF sites are the two most interacting regions in the locus making long-range contacts with all V genes. A second major conformational feature is that the distal V genes form a large tightly looped domain forming the centre of mass of the locus to which the 3’CBEs and IGCR1 loop. Thanks to a collaboration on polymer modelling, 5000 single conformations were simulated based on the ensemble Hi-C data. This showed that every structure is different, supporting a model of dynamic and flexible organisation of the locus rather than hierarchical subdomains therein. Moreover, there is only a slight trend for V genes interacting more often with the D-J region to have higher recombination scores, supporting an ‘equal opportunity for all’ model in which participation of V genes in V(D)J recombination is not constrained by linear genomic distance from the DJ region. Nevertheless, CTCF binding level does contribute to V gene recombination frequency. I have also discovered that Igh and Igk loci participate in a highly specialised network of genome-wide (trans) interactions involving genes encoding B cell-specific factors essential for activation and maintenance of B cell identity, including Pax5, Foxo1, Ebf1, and Runx1. I have validated these by 3D DNA FISH and found that at the pro-B cell stage the Igh is involved in many trans interactions, whereas Igk does not make any contacts. In contrast, Igk gains numerous trans interactions at the pre-B cell stage, many of which overlap with the interactions Igh participates in at both developmental stages. Together, these findings reveal a complex developmentally regulated orchestration of genome conformation changes that underpins B cell development.MR

Identifizierung von Biomarkersignaturen zur Diskriminierung der Pneumokokken-Pneumonie von der Staphylokokken-Pneumonie

Bacterial pneumonia is still a major cause of morbidity and mortality worldwide. One of the reasons for this may be the lack of accurate diagnostic tests that results in delayed identification of the causative agent and subsequent delay in initiating appropriate therapy. In this regard, the objective of this thesis was the identification of host biomarkers which could discriminate between pneumococcal pneumonia and staphylococcal pneumonia in experimental murine infection models using transcriptomics, metabolomics and lipidomics. A genome-wide gene expression profile was determined in the lungs and blood of mice intranasally infected with S. pneumoniae or with S. aureus using RNA-Sequencing. PCA identified the transcriptional signature for staphylococcal infection including the expression of Arg1, Defb3, Cxcl3, Ccr3, Cycs and Ear6 in lung tissue and various small nucleolar RNAs and mitochondrially encoded RNA genes as well as Nrxn3 in peripheral blood. S. pneumonia-specific transcriptional signature in the lungs and in peripheral blood comprises the expression of IFN-induced genes. Metabolic profiling was performed in lung tissue and plasma of infected mice using a targeted metabolomics approach. ROC curve analysis identified 18 metabolites with an AUC of 1 in lung tissue. Predictive models were built to identify optimal combinations of lung and blood metabolites for classifying samples as belonging to either S. pneumoniae or S. aureus infection. In plasma samples a optimal combination of 25 metabolites including 3 acetylcarnitines (C3, C8, C3-DC C4-OH), 1 phosphatidylcholine (PC), 4 lysoPCs, 5 amino acids (Ile, Leu, Met, Tyr, Val), 1 biogenic amine and 1 sphingolipid with the highest average importances was predicted to discriminate S. pneumoniae from S. aureus infection. ROC curve analysis of single plasma lipids that could discriminate between S. pneumoniae and S. aureus lung infection provided a list of 14 lipids. On the other hand, a combination of 25 lipids including 5 lysoPCs, 4 lysophosphatidylethanolamine, 3 phosphatidylinositols, 1 TAG, 1 PCs and 1 cholesterol ester with the highest average importances was predicted as optimal to discriminate S. pneumoniae from S. aureus infection. Overall, this study shows the utility of multi-omics data to identify signatures that can be used to differentiate between S. pneumoniae and S. aureus. Further studies with human samples will be needed to validate the identified pathogen-specific signatures.Bakterielle Pneumonie ist eine der Hauptursachen für Morbidität und Mortalität weltweit. Einer der Gründe liegt im Fehlen genauer diagnostischer Tests, die zu einer verzögerten Identifizierung des verursachenden Erregers und Initiierung einer nicht-geeigneten Therapie führen. Ziel dieser Arbeit war die Identifizierung von Wirts-Biomarkern, die Pneumokokken-Pneumonie von Staphylokokken-Pneumonie in einem experimentellen Maus-Infektionsmodell unter Verwendung von Transkriptomik, Metabolomik und Lipidomik unterscheiden können. Zu diesem Zweck wurde das transkriptionale Profil im Lungengewebe und peripheren Blut von S. pneumoniae und S. aureus infizierten Mäusen mittels RNA-Sequenzierung bestimmt. Mittels Hauptkomponentenanalyse identifizierte die Faktorladung der ersten Hauptkomponente die transkriptionale Staphylokokken Signatur mit der Expression von Arg1, Defb3, CXCL3, CCR3, Cycs und Ear6 in Lungengewebe und verschiedene kleine nukleoläre RNAs und mitochondrial kodierte RNA-Gene sowie Nrxn3 im peripheren Blut. Im Gegensatz dazu umfasst die S. pneumoniae-spezifische transkriptionale Signatur in der Lunge und im peripheren Blut Interferon induzierte Gene. Die Grenzwertoptimierungskurvenanalyse (ROC) identifizierte 18 Lungenmetabolite mit einer Fläche unter der ROC-Kurve (AUC) von 1. Mit Hilfe multivariater statistischer Methoden wurden verschiedene Vorhersagemodelle generiert, um die optimale Kombination von Metaboliten für die Klassifizierung nach Infektionserregern (S. pneumoniae oder S. aureus) zu identifizieren. Das beste Vorhersagemodell für Lungengewebe mit 5 Metaboliten und einer AUC von 1 setzte sich zusammen aus 3 Carnitinen (C2, C3, C4), Histamin und die Summe von Hexosen (H1). Für Plasmaproben bestand das optimale Vorhersagemodell aus 25 Metaboliten, darunter 3 Acylcarnitine (C3, C8, C3-DC C4-OH), 4 lysoPCs, 5 Aminosäuren (Ile, Leu, Met, Tyr und Val), 1 PC, 1 biogenes Amine und 1 Sphingolipid mit der höchsten Gewichtigkeit für das Modell. Die ROC-Kurvenanalyse zwischen S. pneumoniae und S. aureus infizierten Plasmaproben identifizierte 14 Lipide. Das optimale Vorhersagemodell bestand aus 25 Metaboliten, darunter 5 lysoPCs, 4 lysoPE, 3 Phosphatidylinositols, 1 TAG, 1 PCs und 1 Cholesterinester mit der höchsten Gewichtigkeit für das Modell. Die aktuelle Studie liefert zusätzliche Hinweise darauf, dass die transkriptionale und metabolische Signatur bei einer Infektion zur Differenzierung zwischen S. pneumoniae und S. aureus verwendet werden kann