Bing Ren, Ph.D. - US grants

DESCRIPTION: (provided by applicant) The readout of genome information is controlled by transcriptional regulatory elements, but a comprehensive view of the combinatorial control by these DNA sequences, which bind regulatory protein and/or the modified histones in regulating gene transcription, is clearly preliminary. We propose an experimental strategy for comprehensive determination of such functional elements in human DNA. This strategy is based on our extensive knowledge of the transcriptional regulatory proteins, and the demonstrated utility of a method that we previously developed to identify genomic binding sites for DNA-binding proteins in living cells. The method, known as genome-wide location analysis or ChiP-on-Chip, involves immunoprecipitation of the DNA associated with a particular protein from cross-linked cells, followed by quantitative amplification and simultaneous detection of the enriched sequences with DNA microarray technologies. Our experimental strategy to map transcriptional regulatory elements involves the application of genome-wide location analysis to a panel of well-characterized regulatory proteins and histones with specific modifications, known to generally associate with transcriptional regulatory elements in vivo. Identification of their genomic binding sites will allow us to determine the sequence features in the human genome that carry out transcriptional regulatory function. To demonstrate the feasibility of this strategy to the genomic sequences specified by the ENCODE project, we will first design and produce DNA microarrays to represent all the non-repetitive sequences in these genomic regions to map three types of transcriptional regulatory elements in three model cell types. We will identify gene promoters by mapping the genomic sequences associated with RNA polymerase II and the general transcription factor TFIID in cells, and identify enhancer elements by mapping the genomic sequences associated with transcriptional co-activators, acetylated histones H3 and H4 in cells, and identify the repressed and/or silenced DNA by mapping the genomic sequences associated with the heterochromatin binding protein HP1, tri-methylated histone H3 (lysine 9), and transcriptional co-repressors in cells. We will integrate results from our studies with genome-wide expression profiles, comparative genomics analyses and external data sets to gain a comprehensive view of the transcriptional regulatory elements in human DNA. We expect to elucidate the general principles that govern the genomic distribution of transcriptional regulatory elements, and understand the molecular mechanisms that control genome expression in human cells.

A large number of transcription factors have been impliacted in tumorigenesis, yet little is known about their genomic binding sites under normal and pathological conditions. In order to understand the molecular mechanisms whereby abnormal functions of these factors lead to cancer, we propose to develop a genome wide location analysis (GWLA) technique that allows the rapid identification of direct in vivo targets for transcription factors. This approach involves formaldehyde fixation of cells, immunoprecipitation of crosslinked chromatin DNA fragments, and detection of enriched transcription factor binding sites with DNA microarray technologies. The GWLA technique has several distinct advantages over existing ones: First, the method directly examines the in vivo protein-DNA interactions throughout the genome, and can reveal functions of a transcription factor under both normal and diseased states. Second, this unbiased approach : does not require prior knowledge of a transcription factor's function, therefore can uncover its never biological properties. Third, the method has broad applications and can also be applied to discovery of DNA methylation patterns or mapping of other functional elements in the genome relevant to tumorigenesis. Through extensive preliminary experiments, we have verified the utility and exquisite sensitivity of this method with many transcription factors in both yeast and human cells. In the R21 phase studies, we will develop quantitative measures to assess the robustness and reliability of this method. In addition, we will demonstrate that this method can be used to map transcription factor binding sites in mouse genome, in the R33 phase, we will further develop and fully implement a GWLA system to identify targets for human and mouse transcription factors. Because a vast majority of known transcription factors bind close to gene promoters, our GWLA system will be focused on examination of promoter occupancy by specific : transcription factors in cells. We will first annotate gene promoters in the human or mouse genome, and then build DNA microarrays to represent these regions. We will also establish a standard protocol for target identification, and validate the performance of our system using a number of cancer-related transcription factors. This system should prove to be a powerful tool in mechanistic studies as welt as cancer diagnosis.

DESCRIPTION (provided by applicant): The human embryonic stem cells (hESCs) are a unique model system for investigating the mechanisms of human development due to their ability to replicate indefinitely while retaining the capacity to differentiate into a host of functionally distinct cell types. In addition, these cells could be potentially used as therapeutic agents in regenerative medicine. Differentiation of hESCs involves selective activation or silencing of genes, a process controlled in part by the epigenetic state of the cell. In order to gain a better understanding of the epigenetic mechanisms regulating differentiation of hESCs, and produce general reference epigenome maps of the human cells, we propose to establish an Epigenome Center in San Diego. Our center will be focused on both undifferentiated hESC and four hESC-derived early embryonic cell lineages including extraembryonic endoderm, trophoblast, mesendoderm (a common precursor to mesodermal and endodermal lineages), and mesenchymal cells (a specific mesoderm derivative). We have developed and validated high throughput technologies for mapping the state of DNA methylation and chromatin modifications throughout the genome, and will use these methods to generate high-resolution maps of the reference epigenomes. Specifically, we will grow and differentiate hESCs into multiple lineages, and map DNA methylation sites using a newly developed technology that combines bisulfite conversion and whole genome shotgun sequencing. We will also determine the histone modification status in the genome by performing both ChlP-chip and ChlP-Seq analysis. We will develop advanced statistical and algorithmic solutions to facilitate high-throughput sequencing data analysis, and establish an informatics pipeline for collecting, storage, and distribution of epigenome maps. Finally, we will perform integrated data analysis to identify new epigenetic patterns in the genome that could provide insights in mechanisms of epigenetic regulation.

DESCRIPTION (provided by applicant): Temporal and tissue-specific gene expression in mammals depends on complex interactions between transcriptional regulatory proteins and cis-elements such as promoter, enhancers and insulators. Previous large-scale efforts have produced an excellent catalog of transcriptional start sites for most mammalian genes but the mechanisms that control the activation of each promoter in specific cell types remains largely unknown. To better understand the regulatory mechanisms of tissue- and cell type-specific gene expression, it is important to characterize the activities of each promoter in specific cell types, and identify the cis-regulatory elements including enhancers and insulators for each gene. Here, we propose to use the laboratory mouse as a model system and conduct genome-wide analysis of active promoters, enhancers and insulator elements in a panel of embryonic and adult tissues with medical relevance. Specifically, we will (1) identify the active promoters in the mouse genome in a representative set of embryonic and adult tissues;(2) identify potential enhancers and insulator elements in the mouse genome in the same embryonic and adult tissues;(3) identify and characterize tissue-specific promoters and enhancers in the mouse genome;and (4) validate the function of a select set of identified promoters and enhancers. The proposed study, if completed, will result in a comprehensive map of promoters, potential enhancers and insulators throughout the mouse genome. The resource will provide a foundation for analyzing the gene regulatory networks in the mouse cells, and guide the functional annotation of the mouse genome. The results will also help understand the evolution of cis-regulatory sequences, when compared to similar results to be made available as the human ENCODE project progresses. The laboratory mouse represents an important model system for understanding human biology and the molecular basis of human diseases. As a reference to the human genome, the mouse genome sequence has proved extremely valuable in gene annotation. The utility of the laboratory mouse as a model system is currently limited by the lack of understanding of gene regulatory mechanisms that control both common and species-specific gene expression programs in mouse cells. In this project, we propose to define the set of genomic sequences known as cis-regulatory elements in the mouse genome. These regulatory DNA consists of promoters, enhancers, insulators and other regulatory sequences. As a key step towards understanding the gene regulatory mechanisms in mammalian cells, we will produce a comprehensive map of promoters, enhancers and insulators in the mouse genome. We will use a newly developed, high throughput experimental strategy to identify these sequences that are engaged in gene activation in the mouse embryonic stem cells, embryonic fibroblasts, and a panel of embryonic and adult tissues. We will identify tissue specific promoters and enhancers, and characterize the regulatory mechanisms that control the gene expression programs in the specific tissues. Completion of the proposed research is expected to improve our knowledge of the gene regulatory mechanisms in mammalian cells, and provide a reference for understanding the same process in human beings.

"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)"


Abstract
The objective of this research is to study fundamental electronic, photonic, chemical, and bio-logical behaviors of nanoscale structures relevant to future applications in next generation storage, energy harvesting, communications and computing, quantum communication and information proc-essing, superconductivity, and biomedical and biochemical sensing. The approach is to utilize nano-scale e-beam lithography in conjunction with other nanomanufacturing technologies to fabricate and characterize nanometer scale metamaterials, devices, and subsystems in which these new behaviors are expected to manifest themselves most clearly and can be exploited.
Intellectual merit: The proposed acquisition will enable investigation of smaller structures, finer features, and larger patterns than can be experimentally accessed today. Electronic and spin dif-fusion, a variety of magnetic behaviors, structural and chemical changes, superconducting decoher-ence, and many other phenomena that occur at nanometric length scales in common materials will be explored. Research projects are also planned in the areas of nanophotonics, metamaterials, quantum optics, quantum information, and nanomedicine.
Broader Impact: The creation of wealth through advances in nanoscale science and technol-ogy is at the heart of the 21st century economy. The impacts span multiple technical fields, including information systems, health care, energy, pollution monitoring, and chemical threat and explosive detection for homeland security applications. The UCSD Nano3 facility is serving a wide area of Southern California, and the proposed tool will benefit users throughout this geographic area. The project will also play a significant role in promoting education and development of human resources in science and engineering at the graduate and undergraduate levels, diversity and outreach.

Complete annotation of all functional sequences in the human genome remains a major challenge a decade after its initial sequencing. This pertains in particular to gene regulatory elements, many of which are located far away from their target genes, but play fundamental roles in human biology. Significant progress towards annotation of the gene regulatory architecture has been made in recent years predominantly using cultured human cells. However, large-scale studies in mice, as well as anecdotal examples identified in human studies, have indicated the existence of large populations of gene regulatory sequences with very restricted temporal and tissue-specific activity during mammalian development. Despite their critical importance in human development and disease, this set of regulatory sequences will likely be missed by approaches restricted to cell lines or adult tissues. To fill this gap, the major objective for this U54 application is to generate catalogs of developmentally active gene regulatory sequences using existing high throughput data production pipelines for genomic approaches including ChlP-Seq, MethylC-Seq and RNA-Seq on embryonic tissues. Performing such studies directly on human tissues is not feasible due to limited availability of human embryos at relevant stages of development. We will therefore in this study exploit the laboratory mouse, a widely used animal model that shares a similar embryonic developmental program and gene regulatory architecture with humans. In addition to embryonic development, our studies will also generate a complementary reference dataset from postnatal and adult mice to better understand the dynamics of gene regulation over time. Furthermore, we will assess the biological authenticity of identified regulatory sequences by in-depth functional validation using an established transgenic mouse pipeline. It is anticipated that generation of these datasets will fill a major void in the functional annotation o a mammalian genome and help to complete the catalog of gene regulatory sequences in the human genome.

DESCRIPTION (provided by applicant): The NIH Roadmap Epigenome Consortium has generated comprehensive epigenome profiles for over 100 cell types and tissues. While these maps have provided many novel insights into the epigenetic processes and helped annotate the cis-regulatory elements in the human genome, in-depth analysis of these epigenome maps is confounded by the fact that each epigenome dataset actually contains a mixture of two haploid epigenomes, and there are substantial differences between the two. To address this problem we propose to incorporate haplotype information into the analysis of epigenomes of diverse human cell-types or tissues. We have developed a new strategy to reconstruct chromosome-span haplotypes by combining proximity-ligation and ultrahigh throughput sequencing, and have been able to reconstruct haploid genomes corresponding to 368 Roadmap epigenome datasets from over 25 cell-types or tissues. We will perform integrative analysis to achieve three specific aims: First, we will generate haplotype-resolved epigenomes for 25 cell-types and tissues from seven individuals, and identify genomic regions that demonstrate allelic bias in transcription, chromatin modification or DNA methylation in these tissues or cell types. Second, we will investigate allelic gene expression and long-range control mechanisms in human H1 ES cells and four ES-cell-derived early embryonic lineages, to determine whether allele-specific states of enhancers or promoters correspond to allelic transcription of target genes during differentiation of human ES cells. Third, we will investigate allelic gene expression and epigenetic modifications in diverse human tissues and cell types, and identify sequence variants that contribute to allelic gene expression. We expect these analyses will substantially advance our knowledge of epigenomic landscape and gene regulatory mechanisms in human cells.

PROJECT SUMMARY/ABSTRACT One of the fundamental questions in human biology is how one genome sequence can direct the cellular response to so many developmental and environmental cues. The answer lies, at least in part, in the intricate regulation of transcription such that different cues elicit different programs of gene expression. It is now clear that 3D genome organization is a key factor in the regulation of gene expression. In this component, we propose to generate a robust foundation of 3D interactome datasets that can support a paradigm shift in the study of the structure and function of our genome. The work proposed here will address major gaps in our knowledge of 3D genome organization by first mapping 3D interactions at high resolution in a diverse set of human cell types using improved methodology and data analysis strategies. In Aim 1, we plan to focus on the differentiation of human embryonic stem cells to pancreatic progenitor cells, a multi-stage process that offers the opportunity for systematic assessment of the dynamics of chromatin organization and the functional relationship between chromatin architecture and lineage-specific gene expression. These high-resolution interactome maps will be analyzed together with complementary trasncriptome and epigenome datasets to illuminate the relationship between 3D genome organization and genome function. In Aim 2, we will characterize chromatin organization at high resolution in a diverse panel of 30 primary human cell types, and leverage rich datasets of public transcriptome and epigenome data to illuminate the relationship between genome organization and lineage-specific gene expression. The proposed research, if completed, will help uncover functional interactions between cis-regulatory elements across a diverse panel of human cell types. Such datasets will be able to link distal regulatory regions to putative target genes, which will be of major value to the broader biomedical research community and will be useful in furthering our understanding of the mechanisms of distal disease associated regulatory variants in our genome.

? DESCRIPTION (provided by applicant): Recent technological developments have significantly advanced our understanding of the three-dimensional organization of the nucleus. It has also become increasingly clear that the 3D nucleome plays an important role in regulating gene expression. Large cohorts of data are being generated to investigate the impact of the temporal changes of nuclear organization (the 4D nucleome) to normal development and disease processes. The primary goal of this proposal is the creation of an effective organizational hub and web portal for the 4D nucleome. We also propose to develop an effective coordination structure for the 4D nucleome activities. First, we will develop and organize effective networking methods and consortium meetings for establishing protocols and standards. We will develop a framework for coordination of the funded 4D nucleome projects. We will organize annual consortium-wide grantees meeting. We will utilize the professional organizers who have previously worked with the PIs and the premium conference venues at Atkinson Hall in UCSD (http://www.calit2.net). Two major activities will be organized during the annual meeting. Second, we will develop an adaptable, scalable, and user-friendly 4DN web portal. We will build the 4DN Network community web portal and a Virtual Resource Repository. This portal will be an integrated, versatile, and inter-operable data management, retrieval, analysis, and visualization system. We will leverage the ENCODE Comparative Browser (http://encode.cepbrowser.org) for developing the 4D network portal. In addition, the portal will incorporate data generated from outside the consortium, publish E-manuals for the consortium-agreed protocols, and provide the most up-to-date information on the data clearance. Third, we will coordinate and manage the 4DN Network Opportunity Pool. The opportunity pool of funds will be distributed and managed with 100% transparency. Competitive distribution with the funds will be coordinated by a professional manager with extensive experience in managing Center and Training Grants. Fourth, we will develop a comprehensive strategy for training and outreach. The proposed unit will aim to regularly train and update 4DN research network members and collaborators in several key areas including: 1) new technologies; 2) data/sample collection protocols; 3) data analysis methods; 4) data submission protocols; 5) data retrieval methods; 6) data QA/QC; 7) data exchange standards and data ontologies; 8) the contents of different 4DN and public databases; 9) data privacy and 10) data dissemination.

? DESCRIPTION: The complete sequencing of the human genome has provided an unprecedented opportunity for the study of the structure and function of the human genome. While our genome has historically been viewed as a linear sequence of bases, it has progressively become clear that this is an inadequate way to represent our genetic information. Notably, research over the last 30 years has begun to shed light on the fact that the higher-order, 3-dimensional organization of our genome plays a critical role in the interpretation of the genetic information encoded in our genome. The structure of our genome in the nucleus has been clearly demonstrated to play influential roles in diverse nuclear processes including DNA replication and gene expression. Despite this, our understanding of the structure of our genome within the nucleus remains incomplete. The reasons for this include limitations in the resolution and throughput of existing tools in chromatin topology mapping, a scarcity of the analytical tools for studying genome structure datasets, and the difficulty to relate the nuclear structure to function. Due to recent advancements in molecular methods based on high-throughput DNA sequencing, single cell analytical approaches, and high-resolution microscopy, the time for breaking through these previous limitations has come. We will establish a highly collaborative, innovative team in order to develop the tools necessary to transform our understanding of chromatin architecture and function in mammalian cells. We will begin by developing datasets that establish gold standards for the study of nuclear structure and function using genetic, biochemical and imaging approaches. We will optimize current existing technologies for mapping genome wide chromatin interactions, while also developing novel, complementary approaches for studying chromatin structure. We will also develop innovative analytical methods to interpret the chromatin structural data, unraveling principles of structural- and temporal- chromatin organization. Our highly collaborative team will draw on the diverse experiences of its members to provide a synergistic environment to push the limits of our understanding of nuclear structure. We expect that the tools and datasets generated through the proposed research will dramatically advance our understanding of the chromatin structure and function in human cells.

? DESCRIPTION (provided by applicant): The genome of each individual harbors millions of nucleotide variants, and a major challenge is to understand how these variants contribute to phenotypic variations in the population. We propose a combined computational and experimental framework for identifying non-coding variants that affect cellular and physiological traits, with the goal to establish computational models that can predict the probability of exhibiting a physiological trait from the sequences of non-coding genomic regions. This framework involves iterative refinement of model assumptions and parameters with experimentation. To develop the framework and validate the predictive models, we will focus on the disease Age-related Macular Degeneration (AMD), the leading cause of blindness among the elderly in the country. Previous studies have identified a number of sequence variants strongly associated with AMD. We will develop computational models to predict (or narrow down) the set of non-coding sequence variants that contribute to the disease phenotype. As experimental assessment, we will perform genome editing in patient-derived induced pluripotent stem cells (iPSC) to test the consequence of removing or introducing such sequence variants on molecular and cellular phenotypes in cell culture and in rodent models. While the proposed method is developed for AMD, the general approach is expected to apply to other genetic diseases.

PROJECT SUMMARY/ABSTRACT The 3-dimensional organization of our genome has emerged as an important regulator of diverse nuclear processes, ranging from gene expression to DNA replication. A wide variety of tools have been useful for the genome-wide study of the 3D genome organization, and these assays generally resolve chromatin topology by detecting the frequency of ligation between proximal genomic fragments in the formaldehyde fixed cells. While these techniques have uncovered general features of chromatin organization in eukaryotic cells, they also produced widely different results that have clouded our view of chromatin organization. In addition, the modest resolution and the biases introduced by restriction digestion and ligation complicate the data interpretation. Here, we propose innovative solutions to address each of these barriers. In aim 1, we will combine genetics, biochemistry and microscopy to develop a gold standard dataset for evaluating and optimizing technologies mapping chromatin topology. Specifically, we will assess long-range chromatin interactions at ~100 pairs of enhancer/promoter loci in an experimental model cell system, with the use of genome editing tools, locus- specific 4C and 3D-FISH, to establish a set of positive and negative controls. In aim 2, we will optimize and refine existing genome wide approaches for assessing high-resolution chromatin structure, guided by the gold standard data generated in aim 1. In aim 3, we will develop and refine a complementary method, termed Genome Architecture Mapping (GAM), that can probe chromatin structure genome-wide without the need for restriction and ligation. This method avoids the potential bias of previous methodologies and also offers the opportunity for analysis of chromatin structure in single nuclei. If successful, the tools and resources developed through this component will transform our ability to study chromatin topology in mammalian cells.

? DESCRIPTION (provided by applicant): More than 27 million Americans suffer from Type 2 diabetes (T2D). GWAS have identified 128 lead SNPs associated with T2D and/or fasting hyperglycemia, but little is known about how these variants contribute to T2D pathogenesis. A major challenge in functionally characterizing variants found in GWAS is that each lead SNP directly associated with a trait is in LD with a collection of additional variants, and thus identifying the precise variant(s) underlying the association requires extensive computational and experimental analyses. Additionally, the majority of the associated SNPs are located within non-coding regions, where inferring functional consequences of sequence variants remains challenging. Finally, when associated SNPs are identified as candidate regulatory variants, functional testing is frequently hampered by a lack of appropriate experimental models. To address these challenges we have assembled a team of highly accomplished researchers in genomics (Frazer), epigenomics (Ren) and T2D biology (Sander). We propose to combine state-of-the-field computational methods, high throughput molecular assays, and disease modeling in human embryonic stem cells to comprehensively annotates T2D GWAS data and test variants for their gene regulatory function. In Aim 1 we will analyze 5,150 whole-genomes for variants in T2D and fasting hyperglycemia GWAS risk-associated loci. We estimate that these analyses will identify ~1,000,000 variants with a MAF > 1% in the intervals of interest. Additionally, we will identify rare variants that are enriched in T2D patients. We estimate that intersecting these data with existing epigenomic datasets will identify ~99,000 variants in putative regulatory elements in T2D-relevant tissues. In Aim 2 we will use three high throughput molecular assays to characterize these 99,000 candidate regulatory variants in T2D-relevant cell types. First, we will carry out massively parallel reporter assays (MPRA) to test the potentia of each SNP-harboring sequence element to act as a transcriptional enhancer, and if so, whether enhancer activity is affected by the candidate variant. Second, we will carry out a high throughput in vitro binding assay (SELEX) to determine whether the candidate variants affect DNA binding of relevant transcription factors. Third, we will predict target genes of the candidate variants using high throughput chromosome conformation capture (Hi-C) assays. In Aim 3, results from Aim 1 and Aim 2 will be integrated to prioritize 20 beta cell-relevant SNPs for functional validation. Key criteria include: (1) the variant resides in an active beta cell enhance, (2) disrupts transcription factor binding, and (3) targets T2D-relevant genes in Hi-C assays. We will validate these variants by (1) genetic engineering of an embryonic stem cell-derived cell model of human beta cells, testing how deletion of the cis-regulatory element or introduction of the risk variant affects target gene expression; (2) genetic engineering of mouse models, testing whether candidate enhancer/target gene pairs control glucose metabolism in vivo. The proposed study will provide key insights into the underpinnings of regulatory variants identified through GWAS in T2D etiology.

PROJECT SUMMARY/ABSTRACT Technologies for mapping genome wide chromatin structure are generating tremendous amounts of data on the 3D organization of genomes. The size of these datasets and the unique data structure necessitate development of new data analysis tools. Major challenges include how to use the static information contained in these datasets to infer dynamic 3D chromatin organization in vivo, identify chromatin interactions, and gain an understanding of spatiotemporal chromatin organization. Here, we propose to develop a variety of novel analytical methodologies for processing various chromatin topology datasets, extracting biophysical properties of chromatin fibers, and gain an in-depth understanding of the chromatin architecture. In aim 1, we will development a new statistical method using hidden Markov random fields to identify chromatin contacts from the genome-wide chromatin interaction maps. In aim 2, we will develop analytical methods for analyzing data from Genome Architecture Mapping (GAM) experiment, a novel experimental methodology that we will develop and refine as a part of the mapping component. We will further develop statistical framework to reconstruct 3D chromatin structural models from both chromatin contacts and GAM datasets. In aim 3, we will develop predictive models from non-equilibrium statistical mechanics and polymer physics that will link chromatin dynamics in live cells to the static molecular interactions maps. Together, these analytical methods will provide comprehensive view of chromatin structural organization and dynamic properties.

? DESCRIPTION (provided by applicant): Biology is increasingly becoming an information-driven science. To harness the opportunities of the post-genomic era in furthering health sciences research and improving health care, there is an enormous demand for biologists who are trained in mathematics and computer science and can think quantitatively. However, current disciplinary graduate training programs are not designed to accommodate these rapid changes in the biological research perspective. This need serves as the motivation for the development of specialized graduate training programs that will train students at the interface between biology, engineering and computer science. To address this need, UCSD established an interdisciplinary Graduate Program in Bioinformatics in 2001 under the directorship of Dr. Shankar Subramaniam. In 2008, it was renamed Graduate Program in Bioinformatics and Systems Biology and reorganized. The current directors are Dr. Vineet Bafna and Dr. Bing Ren, and the continued guidance from Dr. Subramaniam and an active steering committee containing representative faculty from all five participating UCSD schools and academic divisions. The primary objectives of this renewal application of the Training Grant by the three co-PIs are to continue and expand this premier Graduate Program, support the highest quality students in their truly interdisciplinary training which blends biomedicine, computer science and engineering. The Program will continue to evolve the curriculum (including online offerings) and develop and offer electives that will prepare students for the challenges of big data and computational biomedical research. The program will continue its mode of training that begins with a set of research rotations in laboratories of faculty members, and continues through doctoral research work under the supervision of a PhD advisor and co-advisor who provide complementary interdisciplinary expertise. The Program will also continue a recently established weekly Colloquium, the student Journal Club, and annual retreat. In the course of their training, program students have contributed important discoveries and impactful advances in health sciences research. Alumni of the program are placed in leading positions in Academia and industry. Given the extraordinary number and quality of applicants, the capacity and eagerness of the Program faculty to train the Program's students, and the institutional support for the Program, this application seeks to increase the number of trainee slots to 10. Following Training Grant support of Graduate students during their course work education and initial research training, all graduate students will be supported by their thesis advisors for the duration of thei PhD studies.

Project Summary The overarching goal of the proposed study is to functionally characterize a large number of candidate functional elements in the mammalian genome. The ENCODE projects have revealed millions of putative regulatory elements across more than one hundred cell types and tissues. While these maps have significantly expanded our knowledge of non-coding sequences, there are still large gaps between having descriptive maps of functional elements and understanding the biology of these elements underlying gene regulation. These include: (a) few candidate functional elements predicted by the ENCODE experiments are functionally validated; (b) Epigenomic studies have not given/revealed information on the target genes of candidate functional elements. Therefore, it is still a challenge to interpret the biological functions of non-coding DNA sequences. To address these issues, the objective of this UM1 application is to perform large scale functional characterization of candidate functional elements in their native chromatin context. We will first identify candidate regulatory elements utilizing ENCODE data and generate reporter tagged genes of interest in cell lines utilizing a high throughput, automated platform. Second, we will interrogate candidate functional elements in their native chromatin contexts utilizing two complementary high throughput CRIPSR/Cas9 mediated genome editing approaches. We anticipate these analyses will significantly advance our knowledge of the biological functions of candidate regulatory regions and gene regulation in mammalian cells.

Project Summary / Abstract Alzheimer?s disease (AD) is the most common cause of progressive dementia (memory and cognitive loss) in older adults. Presently, more than 5.5 million Americans may have dementia caused by AD. There is no cure for this debilitating condition. It is increasingly critical that we develop better early diagnostic tools and new treatment strategies for this neurodegenerative disease. Previous gene expression studies using brain tissue and cross-sectional design identify genes whose expression correlates with AD progression. Gene expression is regulated by the cell?s epigenome comprising of DNA methylation, histone modification and non- coding RNAs. We propose to characterize the epigenome of key cell types in neural circuits responsible for learning and memory. Our goal is to determine how the epigenome shapes hippocampal circuit activity and behaviors during AD progression, using the latest single cell genomic technologies coupled with functional circuit mapping and behavioral analysis. We will use two AD mouse models that recapitulate neuropathological features and functional defects observed in human Alzheimer?s. Our guiding hypothesis is that AD neurodegeneration causes significant alterations in the epigenome of cells, including maladaptive changes in accessible chromatin landscape and gene expression programs in disease relevant cell types. This in turn causes defects in specific neural circuit functionality during AD pathogenesis. In Aim 1, we will generate a comprehensive epigenome- and transcription-based cell atlas for hippocampal CA1 and subiculum, and identify epigenomic changes that accompany AD progression in each cell type in AD model mice and age-matched control mice. Single nucleus ATAC-seq (snATAC-seq), single nucleus RNA-seq (snRNA-seq) and the newly developed Methyl-HI in single cells for joint mapping of DNA methylation and chromatin contacts will be key approaches. The proposed work will allow for creation of the first single cell multi-omics atlas of the hippocampal circuits, and will allow us to track the epigenomic changes exhibited by multiple specific cell populations at different AD-like neurodegeneration stages. In Aims 2 and 3, we will investigate the cell subtype specific epigenomic and gene expression basis of neural circuit activities and related memory behaviors in AD model mice of middle age. We will measure epigenomic and behavioral changes in response to genetically targeted ontogenetic hippocampal circuit manipulation and histone deacetylase inhibition. Further, we will determine the beneficial effects of simple behavioral interventions via physical exercise on AD-related epigenomic signatures in Aim 3. Together, our proposed research will provide a new framework to study the molecular underpinnings of neural circuit activities affected during the course of AD pathogenesis. It will also lead to the identification of new therapeutic targets and molecular biomarkers for early detection and better treatment of AD.

PROJECT SUMMARY/ABSTRACT Alzheimer's disease (AD) is the most common form of dementia in the elderly, affecting more than 5 million Americans, as well as their families and caregivers. Unfortunately, aging of the global population is only worsening the AD ?epidemic?, as incidence is projected to triple by 2050. Despite intense research, there is currently no cure for this devastating neurodegenerative disorder. Thus, understanding the intrinsic molecular mechanisms that drive AD pathology and progression is critical to devising effective treatments. Postmortem examination of human brains has revealed that AD-associated neuropathologies, such as neurofibrillary tangles (NFTs) and neurodegeneration, generally arise in a conserved spatio-temporal pattern, affecting transentorhinal regions first, and later extending to limbic and isocortical areas. The molecular and neurochemical bases for such selective neuronal vulnerability (SNV) have long been pursued, as they underlie disease progression and may hold the key to understanding the molecular underpinnings of neurodegeneration, but to date these mechanisms remain elusive. Here, cutting-edge, single-cell technologies will be used to generate a comprehensive, multi-omic atlas of cell types within AD-vulnerable brain regions across different stages of disease. The hypothesis is that specific cell types most dramatically affected by AD pathology within susceptible brain regions are characterized by distinct molecular pathways (transcription factors, signaling cascades, gene networks) that drive SNV. Moreover, that these pathways are executed in a sequential spatio-temporal pattern by changes in chromatin architecture and gene regulatory elements. Tracking the molecular changes exhibited by these neuronal cell populations in the continuum of AD pathology will better define AD onset and progression, and potentially indicate new therapeutic targets. Postmortem brain samples will be obtained from healthy controls, or patients who at death exhibited different stages of AD pathology, namely early (Braak III/IV), or late (Braak V/VI). Changes occurring at different stages of AD progression will be analyzed to identify the cell types and molecular pathways most critical for the initiation and spread of AD-related pathology. Regions analyzed will be hippocampus (CA1/sub), inferior temporal cortex (BA20), frontal cortex (BA9), and visual cortex (an AD- resistant region). In Aim 1, samples from control subject will be subjected to single cell analyses to characterize the methylome and chromatin architecture jointly (sn-m3C-seq), as well as chromatin accessibility together with transcriptome (Paired-seq), of cell types within AD-vulnerable brain regions. Integration of these datasets will create a multi-omic atlas of relevant cell types that will serve as the foundation for understanding AD onset and progression. In Aim 2, these analyses will be extended to AD patients. Comparing data sets across brain regions and disease stages will reveal the specific cell types most affected in AD, as well as the molecular pathways (based on changes in methylation patterns, chromatin architecture, etc.) that drive SNV in AD (Aim3).

PROJECT SUMMARY  Brain  cells  exhibit  profound  molecular  and  cellular  changes  during  aging.  Epigenomic  marks  such  as  DNA  methylation are associated  with age  in  multiple human  tissues,  suggesting an  alteration  of  transcriptional  regulation during aging.  However,  age-­associated  epigenomic  signatures  have  not  been determined  with  cell-­ type  specificity  in  the  brain.  Single-­cell  epigenomic  strategies,  such  as  single-­cell  DNA  methylation  and  open  chromatin  profiling  assays,  are  powerful  strategies  for  de  novo  identification  of  cell-­type  specific  epigenome  landscapes in heterogeneous tissues. At the same time, these strategies uniquely allow the identification of cell-­ type specific regulatory elements that control gene expression patterns in complex tissues. The proposed project  will  complement  and  build  upon  current  NIH-­supported  BRAIN  Initiative  efforts  to  produce  an  epigenomic  cell  atlas  of  the  aging  mouse brain  at  the  single-­cell  level.   Single-­cell  DNA  methylome  and  chromatin accessibility  data will be generated to allow identification of cell types and cell-­type specific regulatory elements in the brains  of  middle-­aged  (9  month  old)  and  aged  (18  month  old)  mice,  and  in  brains  of  aged  mice  subject  to  caloric  restriction.  Aging-­associated  epigenomic  signatures  will  be  identified  through  comparison  to  single-­cell  epigenomic data generated from young mice generated by a BICCN U19 Center for Epigenomics of the Mouse  Brain Atlas  (CEMBA).  Through  generation of a  comprehensive epigenome-­based brain  cell  reference atlas  of  the aging mouse brain, the proposed research will provide invaluable resources for the aging-­research field.    

Abstract: The overarching goal of this proposal is to understand the molecular pathology of inherited retinal degeneration (IRD) by (a) generating maps of human retinal cell type-specific regulatory elements, (b) utilizing these maps to identify non-coding IRD causative mutations within retinal regulatory elements, and (c) gaining insight into the molecular underpinnings of pathological non-coding IRD mutations using cellular and animal models. IRDs are the most common cause of irreversible blindness in young individuals affecting 1 in 3000 individuals. Mutations in coding and splice site sequences in known IRD associated genes contribute to about 60%-65% of cases while the remaining 40%-35% of cases are currently unresolved. Mutations in non-coding or regulatory sequences are suggested to be responsible for a large proportion of these unresolved cases. Although the ENCODE and Roadmap Epigenomics projects have generated detailed maps of regulatory elements for the majority of body tissues, retina is left out. Lack of these maps is a major limitation in identifying IRD causative mutations involving regulatory sequences in retinal cells. We have analyzed the whole genome sequence (WGS) of 125 pedigrees with IRD; of these, 49 remain unresolved with no candidate causative nucleotide changes or structural variants (SVs) in coding or splice site sequences. This leads us to hypothesize the involvement of non-coding variants in pathology. We also have access to more than 391 additional IRD pedigrees that remained unresolved after WGS analysis. In this application we propose to test the hypothesis that non-coding sequence changes are involved in IRD pathology for the majority of these unresolved pedigrees. We will conduct the following studies: Aim 1, establish human retinal cell type specific maps of regulatory elements using innovative single cell genomics methodologies we developed, Aim 2, rank prioritize candidate causative variants using the retinal cell type-specific regulatory element maps and WGS of unresolved pedigrees, Aim 3, validate the impact of high ranking non-coding candidate disease causing variants in the context of the genome architecture of retinal cell types by developing patient iPSC-derived retinal cell models and mouse models. These studies will result in the establishment of retinal cell type-specific high-resolution multi-omic maps and will potentially identify, for the first time, non-coding variants involved in the pathology of IRD. The outcomes of these studies will (1) significantly enhance our understanding of the architecture of retinal cell type-specific regulatory networks, (2) reveal the molecular pathology underlying IRD, (3) establish a highly valuable, publicly-available data set of cis-regulatory elements relevant to retinal degenerative diseases as a resource for retinal disease research, (4) improve mutation detection in patients, and (5) facilitate discovery and development of novel therapies for IRD. We have assembled a multidisciplinary team of outstanding investigators with expertise in epigenetics (Ren), genome sciences (Frazer) and IRD genetics and disease modeling (Ayyagari) who are well positioned to complete this ambitious project.

PROJECT SUMMARY/ABSTRACT Pancreatic beta cells secrete insulin in order to maintain blood glucose homeostasis. Insulin secretion is tightly regulated by glucose and modulated by numerous environmental signals, including other nutrients, hormones, and inflammatory cytokines. Exposure of beta cells to environmental signals affects gene regulatory programs within hours, and these signal-dependent changes serve to adapt insulin secretion to changes in organismal states. Genetic variants associated with measures of insulin secretion are strongly enriched in genomic elements active in beta cells, and many of these variants are also associated with risk of diabetes. Beta cells therefore possess characteristics that make them an ideal cellular model for studying signal-dependent gene regulatory processes relevant to human health and disease. However, the specific genomic programs that drive signal- induced state changes in beta cells remain poorly characterized. Recent advances in the development of human pluripotent stem cell (hPSC)-derived multi-cellular islet organoid models by us and others provide a genetically tractable beta cell model for linking genomic activity to cellular phenotypes. Our group has further pioneered the development of numerous single cell assays, including chromatin accessibility, ultra-high-throughput paired chromatin accessibility and gene expression, and paired 3D chromatin interactions and DNA methylation; methods that we have successfully applied to both primary human islets and hPSC-islet organoids. We have further developed machine learning and network-based approaches for variant interpretation including from single cell RNA and epigenetic data. In this proposal we will develop novel gene regulatory network (GRN) models to predict network-level relationships among genomic elements, genes, and phenotypes derived from single cell multiomic maps charting signal- and time-dependent changes in hPSC-islet organoids. In Sections B and C we will measure genomic element activity, gene expression, and insulin secretion in hPSC-islet organoids exposed to ten different secretory signals each across four time points using paired single nucleus accessible chromatin and gene expression and paired single cell DNA methylation and 3D chromatin architecture assays. In Section D we will generate a GRN from these data, use machine learning to infer element-gene and element-phenotype relationships and use the trained models to refine the GRN. From the resulting GRN we will predict the effects of genetic variants in specific genomic elements on target gene expression, gene network activity, and cellular phenotype. In Section E we will validate and refine models by using medium-scale CRISPR interference of genomic elements individually and in combination as well as allele-specific gene editing of selected glucose-associated variants in hPSC-islet organoids and measuring gene expression changes in cis and trans. Together, the results, data, and methods from this project using a model of a cell type which both rapidly responds to environmental signals and has a quantifiable phenotypic output will be widely applicable to the community studying the dynamics of genomic regulation.

Project Summary / Abstract Age-related cognitive decline is an important concern in the United States, as approximately 20% of the US population is expected to be age 65 or older by year 2030. Understanding the molecular mechansims of brain aging to prolong healthy cognitive function is therefore increasingly important as the population ages and older people remain in the work force. Brain cells exhibit profound and heterogeneous changes during aging at molecular and cellular levels. The simple intervention of physical exercise has emerged as a major positive modulator of cognitive function in aging. In response to RFA-RM-20-005, we have formed an interdisciplinary team with expertise in single-cell genomics, neural circuitry, and aging, to investigate age- and physical activity- related changes of 4D nucleome in post-mortem human brain hippocampus cells across the lifespan with single- cell resolution. We hypothesize that cell-type-specific re-organization of nucleome occurs in the human hippocampal brain region during aging and with physical activity. The changes in nucleome in turn control brain epigenome and transcriptome, modulating neural circuit functionality. The ?Methyl-HiC?, a new approach for joint profiling of DNA methylation and chromatin contacts in single cells, combined with ?Paired-seq?, an ultra- high-throughput method for single-cell joint analysis of open chromatin and transcriptome, will be used to interrogate the chromatin architecture along with DNA methylation, chromatin accessibility and gene expression in the human hippocampus. In Aim 1, we will determine changes in nucleome in major cell types of post-mortem human hippocampus across the life-span with 4 age ranges (20?39, 40?59, 60?79, and 80?99 years old). We will further correlate these changes in nucleome with epigenome and transcriptome in each cell type, to identify vulnerable cell types during aging, and uncover potential gene regulatory programs that could be impacted by aging. In Aim 2, we will determine how physical activity modifies and restores nucleome in specific human hippocampal cell types. We will study two age-matched cognitively?healthy cohorts (70-99 years old) with either high level or low level physical activity, as measured by wearable activity monitors. We will correlate restorative effects on nucleome with epigenome and transcriptome. In Aim 3, we will map how aging and exercise alter nucleome in specific hippocampal cell types with highly controlled quantifiable physical activity in the mouse model, for comparison with human data. These mouse studies allow the exercise variable to be investigated in isolation from effects of other lifestyle factors that can affect hippocampal nucleome, which is not possible with human subjects. The proposed research will help to transform our ability to understand the mechanisms of chromatin organization and function in the context of human brain aging.

Project Summary / Abstract Alzheimer's disease (AD) is the most common cause of human dementia that progressively worsens with age. Sporadic late-onset AD accounts for more than 90 percent of Alzheimer?s cases without clear documented familial history of the disease. However, the vast majority of existing transgenic and knock-in models incorporate disease-causing familial mutations in one or more genes associated with dementias, representing a major limitation. The RFA-AG-21-003 [New/Unconventional Animal Models of Alzheimer?s Disease] highlights the need to develop and characterize naturally occurring ?non-murine models of AD that may represent improved translational potential by better replicating pathological features of the human disease?. We respond to the RFA to apply single cell epigenomic and transcriptomic technologies developed by our team to create cell-type- specific epigenome and transcriptome maps in frontal cortex and hippocampus that are associated with AD-like pathogenesis in two naturally occurring AD animal models: Octodon degus and Canis familiaris. These animals show age-dependent neuropathology and cognitive impairment similar to those observed in human AD, thus they are natural AD models. As both degus and mice are rodents, the studies of long-lived degus will be particularly valuable for a within-mammalian order comparison of which AD gene regulatory pathways are common to spontaneous AD-like features in degus versus different transgenic mouse models. While we generate the resources in alignment with the RFA goals, the proposed research will allow us to develop a comparative analysis to determine conserved epigenetic alterations in the unconventional animal models and bridge our existing databases of mouse models and humans. Maladaptive changes in accessible chromatin accessibility, chromatin organization and gene expression in disease relevant cell types will reveal species- specific and cross-species conserved mechanisms of AD pathogenesis, as well as new targets for AD prevention and treatment. This will provide new insights into the mechanisms of AD pathogenesis in humans. In addition to genome data sharing at the designated NIH depository, resources will be shared and curated at our UCI Center for Neural Circuit Mapping.

The transcriptional regulatory sequences communicate with each other dynamically in the 3D nuclear space to direct cell type specific gene expression. Currently, a major barrier to understanding the transcriptional regulatory programs is the lack of tools, models and maps to explore the chromatin architecture in diverse cell types and physiological contexts. We will address this pressing need by deploying transformative technologies to study the chromatin architecture in mammalian cells at an unprecedented resolution and scale. Specifically, we will generate navigable, cell-type-specific reference maps of chromatin architecture in the mouse, macaque and human brains by integrating high resolution and high throughput imaging and orthogonal single-cell-based genomic methods. We will also dissect the role of chromatin architecture in gene regulation through a set of controlled perturbation experiments in the mouse ES cells (ESC) and ESC-derived neural progenitor cells (NPC). We will develop structural models of chromatin organization with advanced polymer physics and statistical learning methods, and validate their predictive power in embryonic stem cells and in ex vivo brain slices. Finally, we will make the reference maps, analytical tools, visualization methods and structural models available to the broader community. The proposed research project will dramatically transform our ability to analyze the 4D Nucleome of complex tissues, and produce the much-needed maps, tools and models for understanding the gene regulatory programs encoded in the linear genome sequences.