Michael J. Boland

Adult mice generated from induced pluripotent stem cells

Recent landmark experiments have shown that transient overexpression of a small number of transcription factors can reprogram differentiated cells into induced pluripotent stem (iPS) cells that resemble embryonic stem (ES) cells. These iPS cells hold great promise for medicine because they have the potential to generate patient-specific cell types for cell replacement therapy and produce in vitro models of disease, without requiring embryonic tissues or oocytes. Although current iPS cell lines resemble ES cells, they have not passed the most stringent test of pluripotency by generating full-term or adult mice in tetraploid complementation assays, raising questions as to whether they are sufficiently potent to generate all of the cell types in an organism. Whether this difference between iPS and ES cells reflects intrinsic limitations of direct reprogramming is not known. Here we report fertile adult mice derived entirely from iPS cells that we generated by inducible genetic reprogramming of mouse embryonic fibroblasts. Producing adult mice derived entirely from a reprogrammed fibroblast shows that all features of a differentiated cell can be restored to an embryonic level of pluripotency without exposure to unknown ooplasmic factors. Comparing these fully pluripotent iPS cell lines to less developmentally potent lines may reveal molecular markers of different pluripotent states. Furthermore, mice derived entirely from iPS cells will provide a new resource to assess the functional and genomic stability of cells and tissues derived from iPS cells, which is important to validate their utility in cell replacement therapy and research applications.

Epigenetic Regulation of Pluripotency and Differentiation

The precise, temporal order of gene expression during development is critical to ensure proper lineage commitment, cell fate determination, and ultimately, organogenesis. Epigenetic regulation of chromatin structure is fundamental to the activation or repression of genes during embryonic development. In recent years, there has been an explosion of research relating to various modes of epigenetic regulation, such as DNA methylation, post-translational histone tail modifications, noncoding RNA control of chromatin structure, and nucleosome remodeling. Technological advances in genome-wide epigenetic profiling and pluripotent stem cell differentiation have been primary drivers for elucidating the epigenetic control of cellular identity during development and nuclear reprogramming. Not only do epigenetic mechanisms regulate transcriptional states in a cell-type–specific manner but also they establish higher order genomic topology and nuclear architecture. Here, we review the epigenetic control of pluripotency and changes associated with pluripotent stem cell differentiation. We focus on DNA methylation, DNA demethylation, and common histone tail modifications. Finally, we briefly discuss epigenetic heterogeneity among pluripotent stem cell lines and the influence of epigenetic patterns on genome topology.

Characterization of Dnmt3b:thymine-DNA glycosylase interaction and stimulation of thymine glycosylase-mediated repair by DNA methyltransferase(s) and RNA.

Methylation of cytosine residues in CpG dinucleotides plays an important role in epigenetic regulation of gene expression and chromatin structure/stability in higher eukaryotes. DNA methylation patterns are established and maintained at CpG dinucleotides by DNA methyltransferases (Dnmt1, Dnmt3a, and Dnmt3b). In mammals and many other eukaryotes, the CpG dinucleotide is underrepresented in the genome. This loss is postulated to be the result of unrepaired deamination of cytosine and 5-methylcytosine to uracil and thymine, respectively. Two thymine glycosylases are believed to reduce the impact of 5-methylcytosine deamination. G/T mismatch-specific thymine-DNA glycosylase (Tdg) and methyl-CpG binding domain protein 4 can both excise uracil or thymine at U.G and T.G mismatches to initiate base excision repair. Here, we report the characterization of interactions between Dnmt3b and both Tdg and methyl-CpG binding domain protein 4. Our results demonstrate (1) that both Tdg and Dnmt3b are colocalized to heterochromatin and (2) reduction of T.G mismatch repair efficiency upon loss of DNA methyltransferase expression, as well as a requirement for an RNA component for correct T.G mismatch repair.

The Complete Genome Sequences, Unique Mutational Spectra, and Developmental Potency of Adult Neurons Revealed by Cloning

Somatic mutation in neurons is linked to neurologic disease and implicated in cell-type diversification. However, the origin, extent, and patterns of genomic mutation in neurons remain unknown. We established a nuclear transfer method to clonally amplify the genomes of neurons from adult mice for whole-genome sequencing. Comprehensive mutation detection and independent validation revealed that individual neurons harbor ∼100 unique mutations from all classes but lack recurrent rearrangements. Most neurons contain at least one gene-disrupting mutation and rare (0-2) mobile element insertions. The frequency and gene bias of neuronal mutations differ from other lineages, potentially due to novel mechanisms governing postmitotic mutation. Fertile mice were cloned from several neurons, establishing the compatibility of mutated adult neuronal genomes with reprogramming to pluripotency and development.

Molecular analyses of neurogenic defects in a human pluripotent stem cell model of fragile X syndrome

New research suggests that common pathways are altered in many neurodevelopmental disorders including autism spectrum disorder; however, little is known about early molecular events that contribute to the pathology of these diseases. The study of monogenic, neurodevelopmental disorders with a high incidence of autistic behaviours, such as fragile X syndrome, has the potential to identify genes and pathways that are dysregulated in autism spectrum disorder as well as fragile X syndrome. In vitro generation of human disease-relevant cell types provides the ability to investigate aspects of disease that are impossible to study in patients or animal models. Differentiation of human pluripotent stem cells recapitulates development of the neocortex, an area affected in both fragile X syndrome and autism spectrum disorder. We have generated induced human pluripotent stem cells from several individuals clinically diagnosed with fragile X syndrome and autism spectrum disorder. When differentiated to dorsal forebrain cell fates, our fragile X syndrome human pluripotent stem cell lines exhibited reproducible aberrant neurogenic phenotypes. Using global gene expression and DNA methylation profiling, we have analysed the early stages of neurogenesis in fragile X syndrome human pluripotent stem cells. We discovered aberrant DNA methylation patterns at specific genomic regions in fragile X syndrome cells, and identified dysregulated gene- and network-level correlates of fragile X syndrome that are associated with developmental signalling, cell migration, and neuronal maturation. Integration of our gene expression and epigenetic analysis identified altered epigenetic-mediated transcriptional regulation of a distinct set of genes in fragile X syndrome. These fragile X syndrome-aberrant networks are significantly enriched for genes associated with autism spectrum disorder, giving support to the idea that underlying similarities exist among these neurodevelopmental diseases.

meaRtools: an R package for the Comprehensive Analysis of Neuronal Networks Recorded on Multi-Electrode Arrays

Here we present an open-source R package ‘meaRtools’ that provides a platform for analyzing neuronal networks recorded on Microelectrode Arrays (MEAs). Cultured neuronal networks monitored with MEAs are now being widely used to characterize in vitro models of neurological disorders and to evaluate pharmaceutical compounds. meaRtools provides core algorithms for MEA spike train analysis, feature extraction, statistical analysis and plotting of multiple MEA recordings with multiple genotypes and treatments. meaRtools functionality covers novel solutions for spike train analysis, including algorithms to assess electrode cross-correlation using the spike train tiling coefficient (STTC), mutual information, synchronized bursts and entropy within cultured wells. Also integrated is a solution to account for bursts variability originating from mixed-cell neuronal cultures. The package provides a statistical platform built specifically for MEA data that can combine multiple MEA recordings and compare extracted features between different genetic models or treatments. We demonstrate the utilization of meaRtools to successfully identify epilepsy-like phenotypes in neuronal networks from Celf4 knockout mice. The package is freely available under the GPL license (GPL>=3) and is updated frequently on the CRAN web-server repository. The package, along with full documentation can be downloaded from: https://cran.r-project.org/web/packages/meaRtools/. Author summary Cultured neuronal networks are widely used to study and characterize neuronal network activity. Among the many uses of neuronal cultures are the capabilities to evaluate neurotoxicity and the effects of pharmacological compounds on cellular physiology. Multi-well microelectrode arrays (MEAs) can collect high-throughput data from multiple neuronal cultures simultaneously, and thereby make possible hypotheses-driven inquiries into neurobiology and neuropharmacology. The analysis of MEA-derived information presents many computational challenges. High frequency data recorded simultaneously from hundreds of electrodes can be difficult to handle. The need to compare network activity across various drug treatments or genotypes recorded on the same plate from experiments lasting several weeks presents another challenge. These challenges inspired us to develop meaRtools; an MEA data analysis package that contains new methods to characterize network activity patterns, which are illustrated here using examples from a genetic mouse model of epilepsy. Among the highlights of meaRtools are novel algorithms designed to characterize neuronal activity dynamics and network properties such as bursting and synchronization, options to combine multiple recordings and use a robust statistical framework to draw appropriate statistical inferences, and finally data visualizations and plots. In summary, meaRtools provides a platform for the analyses of singular and longitudinal MEA experiments.

T2. IDENTIFICATION OF PATHOGENIC VARIANTS IN PROTEIN CODING GENES

Background A central aim of precision medicine is to target treatments to the underlying causes of disease. To accurately target treatments we must be able to recognize pathogenic genetic variants. Current methods prioritize variants that directly alter protein sequence (missense and loss of function) but not variants that may cause disease by changing the processing of final transcripts. The difficulty in capturing this effect results in overlooking synonymous and intronic variants when searching for disease risk in sequenced genomes. Methods The TraP score was constructed using three main components: 1) Information acquisition – details of the harboring gene and it’s transcripts are gathered for each variant. 2) Feature calculation - possible changes to sequence motifs are evaluated, including changes to exon-intron boundaries, creation of cryptic splice sites, creations and disruptions of cis-acting binding sites for splicing regulatory proteins, interactions between selected features such as original and new splice sites and others. Overall, 42 features and 14 general properties (chromosome, strand, coordinate, etc.) are collected for each variant. 3) Modeling – the incorporation of selected features into a random forest model. The model is trained on a set of 75 pathogenic synonymous variants and 402 benign variants. Pathogenic variants are strongly associated with rare disease, whereas the 402 benign variants are de novo mutations identified from healthy individuals. Results The Transcript-inferred Pathogenicity score (TraP) presented here was constructed to reliably identify non-coding mutations that cause disease. Trap is strongly negatively correlated with allele frequency in both synonymous and intronic regions, suggesting that the higher the TraP score the stronger the selection against these variants in the population. Moreover, synonymous variants with high TraP scores have significantly lower minor allele frequencies than even missense variants, indicating that Trap identifies a subset of synonymous variants under stronger purifying selection. TraP identifies known pathogenic variants in synonymous and intronic ClinVar datasets (AUC = 0.88 and 0.83, respectively), dismissing benign variants with extremely high specificity of above 99%. Applied to exomes of 281 epilepsy family trios, TraP pinpoints synonymous de novo variants in known epilepsy genes. TraP’s high performance and specificity clearly outperforms existing methods and allows the prioritization of synonymous and intronic variants for use in gene discovery and the interpretation of personal genomes. Discussion Exome sequencing studies consider rare non-synonymous variants as disease candidates, while other variant types are mostly ignored. Some existing methods are able to prioritize synonymous and intronic variants, yet lack the specificity required for detection of causal variants. TraP discards over 99% of non-coding variants as benign while strongly identifying true pathogenic variants. TraP identifies pathogenic variants that are not conserved, yet have rare population frequencies. Doing so without prior population frequency information and in contrast to the GERP++ and CADD scores, suggests that TraP identifies pathogenic events that were not selected against during vertebrate evolution, but are selected against in human population. This conclusion is supported by the highest complexity of alternative splicing found in primates and by the species-specific nature of splicing regulation.