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X chromosome inactivation (XCI) silences transcription from one of the two X chromosomes in female mammalian cells to balance expression dosage between XX females and XY males. XCI is, however, incomplete in humans: up to one-third of X-chromosomal genes are expressed from both the active and inactive X chromosomes (Xa and Xi, respectively) in female cells, with the degree of 'escape' from inactivation varying between genes and individuals1,2. The extent to which XCI is shared between cells and tissues remains poorly characterized3,4, as does the degree to which incomplete XCI manifests as detectable sex differences in gene expression5 and phenotypic traits6. Here we describe a systematic survey of XCI, integrating over 5,500 transcriptomes from 449 individuals spanning 29 tissues from GTEx (v6p release) and 940 single-cell transcriptomes, combined with genomic sequence data. We show that XCI at 683 X-chromosomal genes is generally uniform across human tissues, but identify examples of heterogeneity between tissues, individuals and cells. We show that incomplete XCI affects at least 23% of X-chromosomal genes, identify seven genes that escape XCI with support from multiple lines of evidence and demonstrate that escape from XCI results in sex biases in gene expression, establishing incomplete XCI as a mechanism that is likely to introduce phenotypic diversity6,7. Overall, this updated catalogue of XCI across human tissues helps to increase our understanding of the extent and impact of the incompleteness in the maintenance of XCI.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016., This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections., Cataloged from student-submitted PDF version of thesis., Includes bibliographical references (pages 203-225)., One of the fundamental aims of biology is to determine what lies at the root of differences across individuals, species, diseases, and cell types. Furthermore, the sequencing of genomes has revolutionized the ways in which scientists can investigate biological processes and disease pathways; new genome-wide, high-throughput experiments require computer scientists with a biological understanding to analyze and interpret the data to improve our understanding about life science. This provides us with a key opportunity to use computational techniques for new biological discoveries. While genetic variation plays an important role in influence phenotype, sequence alone cannot account for all differences: for example, different types of cells in an individual have varying function and attributes, but identical genetic makeup. This highlights the importance of studying epigenetic changes, which are dynamic chemical changes to and around the DNA. While the DNA of every cell in an individual is the same, the epigenetic context for that DNA varies from cell to cell. In this way, these epigenetic differences play a crucial role in gene regulation, with epigenetic changes both causing and recording regulatory mechanisms. In this thesis, we combine the power of computational, statistical, and data science approaches with the new wave of epigenetic data at a genome-wide level in a number of ways. First, in chapter 2, we demonstrate the importance of computational analysis at an epigenomic level by identifying an epigenomic signature of the olfactory receptor gene family that gives insight into the mechanism behind monogenic gene regulation. Next, in chapter 3, we explain our development of ChromDiff, a novel statistical and information theoretic computational methodology to identify chromatin state differences in groups of samples. In our methodology, we use correction for external covariates to isolate the relevant signal, and as a result, we find that our method outperforms exis, by Angela Yen., Ph. D.

The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease., National Human Genome Research Institute (U.S.) (RC1HG005334), National Human Genome Research Institute (U.S.) (R01HG004037), National Human Genome Research Institute (U.S.) (R01HG004037-S1), National Human Genome Research Institute (U.S.) (RO1NS078839), National Science Foundation (U.S.) (CAREER Award 1254200)

The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease-and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease. © 2015 Macmillan Publishers Limited.

Epigenomic data sets provide critical information about the dynamic role of chromatin states in gene regulation, but a key question of how chromatin state segmentations vary under different conditions across the genome has remained unaddressed. Here we present ChromDiff, a group-wise chromatin state comparison method that generates an information-theoretic representation of epigenomes and corrects for external covariate factors to better isolate relevant chromatin state changes. By applying ChromDiff to the 127 epigenomes from the Roadmap Epigenomics and ENCODE projects, we provide novel group-wise comparative analyses across sex, tissue type, state and developmental age. Remarkably, we find that distinct sets of epigenomic features are maximally discriminative for different group-wise comparisons, in each case revealing distinct enriched pathways, many of which do not show gene expression differences. Our methodology should be broadly applicable for epigenomic comparisons and provides a powerful new tool for studying chromatin state differences at the genome scale., National Science Foundation (U.S.). Graduate Research Fellowship, National Institutes of Health (U.S.) (U54 HG006991), National Institutes of Health (U.S.) (U41 HG007000), National Institutes of Health (U.S.) (5U01ES017156), National Institutes of Health (U.S.) (RC1-HG005334), National Institutes of Health (U.S.) (HG004570), National Institutes of Health (U.S.) (HG006911), National Institutes of Health (U.S.) (R01 HG004037)

Constitutive heterochromatin is traditionally viewed as the static form of heterochromatin that silences pericentromeric and telomeric repeats in a cell cycle- and differentiation-independent manner. Here, we show that, in the mouse olfactory epithelium, olfactory receptor (OR) genes are marked in a highly dynamic fashion with the molecular hallmarks of constitutive heterochromatin, H3K9me3 and H4K20me3. The cell type and developmentally dependent deposition of these marks along the OR clusters are, most likely, reversed during the process of OR choice to allow for monogenic and monoallelic OR expression. In contrast to the current view of OR choice, our data suggest that OR silencing takes place before OR expression, indicating that it is not the product of an OR-elicited feedback signal. Our findings suggest that chromatin-mediated silencing lays a molecular foundation upon which singular and stochastic selection for gene expression can be applied., National Science Foundation (U.S.) (Fellowship), Brown University (Royce Fellowship), Pew Charitable Trusts (Pew Scholar of the Biomedical Sciences), McKnight Endowment Fund for Neuroscience, Rett Syndrome Research Trust, Hellman Family Foundation, National Institute on Deafness and Other Communication Disorders (U.S.) (R03 DC010273), National Institutes of Health (U.S.) (Director’s New Innovator Award Program (1DPOD006667))

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011., Cataloged from PDF version of thesis., Includes bibliographical references (p. 95-102)., In this thesis, I leveraged computational methods on biological data to better understand gene regulation and development of the human body, as well as of the model organisms mouse and yeast. Firstly, I tackled biological questions with machine learning techniques by studying pre-transcriptional gene regulation through nucleosome positioning, which resulted in the identification of function-specific factors and improved predictive performance. Next, computational analysis enabled the discovery of genome-wide epigenetic modifications that play a foundational role in silencing for the monoallelic and monogenic expression of olfactory receptor genes in mice. Lastly, signatures of functional, bound RNA regions provide insight into a potential protocol-specific bias and produce a new avenue for de novo discovery of functional regions., by Angela Yen., M.Eng.

Summary: Social context effects on young children's sex-typing were examined in two studies. In Study 1 sex-typed toy choices of 139 children aged 4 to 8 were assessed first for a solitary-play context, and then for three social contexts distinguished as to friendship status of a specified play partner (represented by a photo): best friend, acquaintance, and an unfamiliar peer. For each context, children selected preferred toys from photographs of a neutral toy paired with either a same- or opposite-sex toy. Results indicated social context effects for girls but not boys, in that girls tended to display more sex-typed toy choices in the solitary and best-friend than in the acquaintance or unfamiliar peer contexts. In general, however, girls approached same-sex toys less than boys, while both sexes avoided opposite-sex toys to a similar extent. In Study 2 subjects were 68 children aged 4 to 7. They were asked to imitate videotaped masculine, feminine, and neutral actions of a hand puppet. For different children, the puppet was designated (by name and photo display) as either a best friend or acquaintance, and it engaged in the sex-typed activities with either gender-congruent or incongruent affect (happy for same-sex actions and sad for opposite-sex actions, or the reverse). Friendship status and gender-affect congruency effects which varied with age level were evident for several memory measures. Incongruency promoted accurate imitative matching for the acquaintance context in younger children, and for the best-friend context in older children. In addition, best-friends' feminine actions were imitated more accurately than their masculine or neutral actions. Subject age and sex also interacted with activity gender type and gender-affect congruency to influence peer affect recall, with poorer recall of feminine-activity affect by boys in the incongruent condition. While social context had little impact upon boys' reported affect, girls' enjoyment was lower for masculi, Collection: FAU Electronic Theses and Dissertations Collection, Adviser: Louise C. Perry., Thesis (Ph.D.)--Florida Atlantic University, 1996.

Summary: Social cognitive factors in early sex-role development were studied by examining judgments of toy appropriateness for boys versus girls under both speeded and delayed response conditions, used as indices of automatic and reflective gender-schema processing, respectively. Subjects aged 3 to 7 viewed photographs of sex-typed and neutral toys and indicated either immediately or after a 2.8 sec. delay who usually plays with them. A toy choice task assessed the children's own sex-typed toy preferences. Flexibility judgments (number of neutral responses) increased in a linear fashion with age to neutral-toy stimuli. In contrast, flexibility with respect to sex-typed toys was generally low. The prediction that automatic-mode processing would be more strongly related to children's own sex-typing than is their reflective-mode processing was supported only for 3-year-old boys, in whom automatic-mode stereotyped judgments of feminine toys were linked to strength of sex-typed toy preferences., Collection: FAU Electronic Theses and Dissertations Collection, Thesis (M.A.)--Florida Atlantic University, 1993., Charles E. Schmidt College of Science