Robert W. Williams - US grants

The principal aim of this proposal is to provide a complete structural analysis of ganglion cell growth cones and their contactss with other fibers and glial cells in the optic pathway of the fetal primate. No such analysis of growth cones exists yet in any species. This work is an essential prerequisite if we are to identify an understand the morphological substrates and ultimately, the molecular interactions that guide the growth of optic axons. The explicit objectives are to: 1. Compare and contrast the form and fine structure of growth cones in the nasal and temporal halves of retina, in the optic nerve, chiasm, and trast, and in target nuclei at several stages of development. The analysis will be based on 3- deimensioanla reconstructions from serial sections. 2. Characterize and quantify the local and global distribution growth cones in the optic pathway and their contact relations with different classes of glial and neuronal processes from the time when growth cones first enter the optic stalk through to the end of axon ingrowth. 3. Experimentally test the hypothesis that interactions between growth cones in the optic chiasm or optic tract regulate the development of the unique pattern of partial decussation that characterizes the primate visual system. Anterograde and retrograde tracer transport methods will be used to label specific populations of ganglion cells, their axons, and their growth cones. In recent studies I have identified and characterized growth cones in the optic nerve of the cat and monkey at the ultrastructural level, and I have demonstrated that growth cones are remarkabley variable in form, ultrastructure, and position. In collaboration with my colleagues, I developed new analytic techniques that now make possible a far more comprehensive study of growth cones The quantitative in situ analysis of growth cone should answer several outstanding questions, among them: How do the shape and ultrastructure of growth cones change in response to their environment? Are there structural differences between growth cones that have different destinations? How are the earliest pioneers in the optic pathway different from growth cones that follow? Do growth cones express an affinity for glial surfaces or basal lamina, and if so, do these preferences change with age or position? What interactions are there between growth cones and pre-existing axons that may help explain global patterns of axonal growth? How stable are these interactions and relations? Although fundamental, these issues have not been studied in any detail in any species and have not been studied at all in primates. The results of this work should have a direct bearing on several important hypotheses concerning the growth of axons and should result in new insights into the development of the visual system that will be of theoretical and clinical importance.

tissue mosaicism; developmental neurobiology; histogenesis; retina; cell growth regulation; cell type; species difference; autoradiography; genetically modified animals; laboratory mouse; in situ hybridization;

We propose to continue studies of a remarkable mutation of the mammalian visual system in which the entire retinal projection is uncrossed. This drastic inborn error is associated with a marked and persistent nystagmus. A systematic analysis of the visual system of these achiasmatic animals is important for at least two reasons. First, the mutation provides us with a unique natural experiment that is ideal for testing important ideas about the major processes that guide retinal axons at the optic chiasm early in development. We will determine how, when, and why axons fail to cross the midline in mutants. Both light and electron microscopy and several tract tracing methods will be used to perform a systematic structural analysis of the embryonic retina, optic stalk, and chiasm. The analysis should provide insight into the genesis of the norma mammalian chiasm, as well as into the genesis of the severe, decussation error seen in human albinos. This developmental analysis should also provide us with a critical test of the hypothesis that pigmentation controls pathways chosen by retinal axons early in development. The second important reason to study this mutation is that it provides us with a unique system in which to test many current ideas about the formation of topographic representations in the CNS. In particular, the mutation provides a superb model with which to validate, reject, or modify hypotheses about the role of axon-target interactions, nasal-temporal rivalry, and binocular competition in partitioning visual nuclei and the visual cortex into sets of visuotopic representations. We will use physiological recording methods and complementary tract tracing methods to determine the functional and structural repercussions that result from the drastic decussation error. In specific, we will determine how nasal and temporal retinal axons from the same retina organize themselves in two retinorecipient nuclei-the dorsal lateral geniculate nucleus and the superior colliculus. This will be followed by high resolution mapping studies of visuotopic representations in the primary visual cortex of mutants. This systematic analysis of retinotopy in mutants will provide us with a way to assess the plasticity of visual maps and will also provide us a way to critically test several important hypotheses regarding the formation of topographic representations. In summary, the achiasmatic mutant provides us with a powerful means to test influential ideas regarding the development, function, and plasticity of the vertebrate visual system. In addition, this mutation shows great promise as an animal model for congenital nystagmus in humans. The mutants may ultimately help us in developing and testing new methods to treat oculomotor disturbances in humans.

DESCRIPTION: Neurons in the brains of different mammals are almost indistinguishable in structure and function, but their numbers vary by more than three orders of magnitude. This variation has part of its origins in a set of undefined genes that control rates of cell proliferation and cell death in different pools of neural precursor cells. Some genes must have global effects and control the scale of the entire CNS. Other genes must have specific effects on specific cell populations. collectively, these genes are not only at the root of brain evolution, but they are very likely to be key genes that control the normal development of the brain. Major technical advances now make it practical for the first time to map genes responsible for complex neuronal traits. These advances include (1) a quadrupling of the density of the genetic map, (2) the ease of genotyping marker loci distributed across the entire genome, (3) biometric methods to map quantitative trait loci (QTLs), and (4) novel magnetic resonance imaging methods that can generate precise quantitative data on many different parts of the brain. The project proposed by the applicant will use these new tools to map putative genes that contribute to the regulation of cell number in various CNS structures. The applicant proposes three specific ways to approach this problem. In the first, he will analyze two sets of recombinant-inbred mouse strains (BXD and BXH) to determine the number and location of genes controlling retinal ganglion cell number in mouse. This effort has already yielded a locus on chromosome 11 (Rcn-1) that is responsible for the majority of the genetic differences in the two parental strains. In year three the applicant proposes to repeat this analysis on brains from F2 intercross progeny of (CAST/Ei x BALB/cJ)F1s. Part of this first aim will be to do a developmental analysis of the highest and lowest strains in order to determine whether the differences arise from cell death or cell division. The second aim will be to expand this study to the target of the retinal ganglion cells, namely the lateral geniculate nucleus. Counts of both source and target neurons will be made in large numbers of animals and the variations will be correlated with each other as well as with segregating loci in two diverse strains, BALB/cJ and C57BL/Ks as well as F2 intercross progeny of (CAST/Ei x BALB/cJ)F1s as well as various BXD recombinant inbred lines. The third specific aim will be similar in approach but instead of using cell counts of neurons in the visual pathway, volumetric measurements will be taken using a customized MRI radio frequency coil to analyze fixed brain tissue. The analysis will be done on different RI lines as well as mice from the (CAST/Ei x BALB/cJ)F1 intercross.

DESCRIPTION (Adapted from applicant's abstract): We propose to refine and extend several efficient morphometric and physiological measurements from eyes and retinas of common inbred and recombinant inbred strain of mice. One emphasis of this work is to develop significantly faster ways to carry out unbiased and reliable quantitative analyses of murine retinas. To explore the genetic basis of eye disease, we are acquiring data from mice belonging to over 100 strains and crosses. Some of these strains have already proved to be valuable models for studing serious diseases that compromise human vision--glaucoma, myopia, diabetic retinopathy, and retinitis pigmentosa. We now are adapting efficient clinical diagnostic procedures (cryostat sectioning) and video-enhanced DIC microscopy to carry out a comprehensive biometric survey of the range of variation in eye, retinal, and optic nerve architecture. Data are acquired from mice of both sexes and a wide range of ages. Electroretinograms, pupillary reflexes, and optical measurement of eyes will also be obtained to assess functional aspects of vision in numerous and diverse strains. All of these data are being integrated into a sophisticated and universally accessible database available on the World Wide Web at nervenet.org.

SUBPROJECT ABSTRACT NOT AVAILABLE

DESCRIPTION (Adapted from applicant's abstract): Myopia is an extremely pervasive abnormality of vision that is usually caused by excessive growth of the posterior part of the eye relative to the optical power of the cornea and lens. The cumulative cost of myopia and its treatment is huge. The onset and progression of myopia are strongly influenced by environmental factors, but the risk of becoming myopic is clearly influenced by genes. The central aim of this work is to determine what genes and molecules normally regulate the growth of different parts of the mammalian eye and to then assess whether any of these same genes contribute to optical abnormality in humans. The first aim of this project is to systematically map genes that selectively influence the growth of the eye, the lens, the cornea, and the retina of mice. Using novel quantitative trait locus (QTL) interval mapping methods, more than 10 gene loci that selectively affect the growth of different parts of the eye will be mapped with F2 intercrosses. As part of the second aim, these QTLs will be mapped with far greater precision (a critical region of 1‑2 cM) using special mapping resources‑advanced intercrosses and reciprocal congenic lines. Complementary methods will then be used to evaluate the most promising candidate genes linked with particular QTLs. The third aim is a developmental study of the mekics of eye growth in several important strains, and in specially engineered congenic strains. This work will test ideas about how genes and environmental factors affect the optics of eye development. Understanding how different QTLs affect different parts of the eye will ultimately contribute to a far better understanding of molecular and developmental mechanisms associated with eye growth in humans.

DESCRIPTION (provided by applicant): Numerous non-genetic variables interact with gene variants to influence alcohol use, dependence, and relapse. One key influence is a complex mix of stressors. In common with other components of this INIA application, this project explores genetic, molecular, and cellular substrates of alcohol consumption in response to stress. Our focus is on using new high-resolution gene mapping resources and methods to dissect genetic interactions between alcohol, stress, and forebrain-midbrain anatomy. We use well characterized behavioral paradigm that are combined for the first time with sophisticated stereology and immunohistochemical analysis of the amygdala and key neuromodulatory inputs to the forebrain. Data from the molecular and structural analyses will be combined with EtOH-stress interaction measures to define shared and unique genetic determinants. The first aim is to systematically apply new quantitative trait locus (QTL) mapping methods to fine map alcohol and stress-related genes in mice. More than ten loci are being mapped and remapped with high precision (a critical region of 1-2 cM) using a set of -100 new types of recombinant inbred (RI) strains, an novel RI intercross (RIX) method, and interval-specific congenic lines. In parallel with these genetic studies, we will explore genetic and epigenetic interactions and codeterrninants of stress and alcohol consumption. We intend to systematically map genes that influence the number and distribution of three major neurotransmitter systems that modulate basal forebrain physiology serotoninergic cells in the dorsal raphe, noradrenergic neurons in the locus coeruleus, and dopaminergic cells in the midbrain. This aim links our analysis closely to the other transmitter-related components of the INIA. We will use unbiased stereological methods. We anticipate that the synergy between the structural and functional analysis will allow us to far more efficiently generate candidate genes that influence the development of alcoholism in humans.

DESCRIPTION (provided by applicant): Environmental factors interact with gene variants to influence patterns of alcohol use, abuse, adaptation, addiction, withdrawal, and relapse. Ethanol is a highly soluble small molecule that has subtle allosteric effects on many molecular processes in the CNS and not all of its many targets are known. Individual differences in how humans respond to ethanol are also not well understood. This project leverages the broad expertise of INIA to explore and test genetic, molecular, synaptic, cellular, and behavioral causes of alcohol consumption and the increased vulnerability following stressors. Our focus is on exploiting new high-resolution genomic resources (sequence data, SNPs, mRNA microarrays) to model networks of molecular and synaptic interactions in forebrain regions that have important roles in alcoholism. To ensure robust results we use two large genetic reference populations of rodents (BXD mice and HXB rats) and apply sophisticated statistical methods to generate hypotheses that are then subjected to rigorous experimental testing. We combine data from our own work with data from numerous other published studies using a systems genetics approach. This combined approach is made possible by our use of well studied genetic reference populations. We will define shared and unique genetic and synaptic factors that modulate ethanol use and the convergent effects of stress on ethanol addiction and relapse. In Aim 1 (Data Generation) we generate normative expression data and networks for four key forebrain regions (medial prefrontal cortex, nucleus accumbens, bed nucleus of the stria terminalis, and the basolateral amygdala) from complementary genetic reference populations with different genetic structures (inbred Rl and hybrid RIX lines). We are acquiring gene expression data for 48 brain regions in C57BU6J and DBA/2J lines. Our goal is to extract robust networks that are cross-validated and that have strong prospects of generalizing to admixed human populations. Data will be made publicly available on the GeneNetwork (GN) site (www.genenetwork.org). In Aim 2 (Model Construction) we develop open source programs and standard operating procedures to produce well defined and testable hypotheses. The INIA Models Work Group will be responsible for developing, testing, and using the INIA GeneNetwork (GN) and this software to construct explicit process diagrams and statistical models. We will integrate these models into GN for use and critique by INIA and NIAAA researchers. In Aim 3 (Predictive Validation), members of INIA will experimentally manipulate sets of isogenic lines (BXD and RIX), predicting whether they will be high or low responders using INIA standard operating protocols. The synergy among genetic, transcriptome, electrophysiological, and experimental studies and data sets will allow us to test the role of complex interactions in the mesocorticolimbic system that contribute to alcoholism and maladaptive stress response.

The objectives of this project are to develop and apply statistical methods for the analysis of data collected across multiple phenotypic domains from collaborative cross (CC) strains and their derivatives. These include a diallel cross among the eight founder strains of the CC and a recombinant inbred intercross (RIX) population consisting of the F1 progeny of CC strains. The use of genetically reproducible but outbred RIX animals will enable the integration of data across multiple phenotypic domains in animals with natural levels of heterozygosity. Analysis of this novel cross design will require new methodology development. We will implement analysis tools in the general statistical software package R. Performanceof new methodology will be assessed and validated using simulations and in applications to the experimental data. Integrated analysis of genetic, environmental and physiological variables will provide new insights into the role of stressors on whole organism biology. Specific Aim 1: We will develop and apply statistical methods for genetic mapping analysis of the collaborative cross recombinant inbred strains and their derivatives. The objective of these analyses will be to identify genetic factors that interact with experimentally defined stressors in their effects on mean and covariance of measuredphenotypes. Specific Aim 2: We will develop and apply statistical methods to conduct an integrated analysis of collaborative cross data across multiple phenotypic domains. We will focus on the application of graphical models that capture interactions among these phenotypes using intuitive visual representations.

DESCRIPTION (provided by applicant): A key objective of the INIA programs is to transform research on causes, prevention, and treatment of alcoholism. Integration of data sets and analytic methods across a broad spectrum of research is critical to success. This INIA UOI Core application is built on the success of several powerful INIA web services and data resources, including GeneNetwork, WebGestalt, and the Ontological Discovery Environment (ODE). However, our aims in this renewal are a direct outgrowth of rapid changes in genomics and neuroscience, in particular, next-generation sequencing. A theme of this core is innovation by integration. The far more pervasive use of web services in neuroscience over the last five years - Allen Brain Atlas, DAVID, ODE, Galaxy, GeneNetwork, GeneWiki, KEGG, and the Neuroscience Information Framework - represents a great research opportunity for our INIA teams. But these resources often have a steep learning curve and are difficult to use together. One of our goals is to assemble these resources together with large new data sets in a context useful to NIAAA researchers. The INIA Translational Web Services core has these aims: (1) Process, analyze, and distribute massive array and next-generation data sets for both INIA consortia; (2) Integrate INIA consortia data sets from rodents, non-human primates, and humans into GeneNetwork and significantly enhance tools for bidirectional translational queries; (3) Provide database support, training, and documentation in bioinformatics, genetics, and next-gen genomic tools to other INIA projects and cores.

DESCRIPTION (provided by applicant): Ethanol and stress exert a wide spectrum of neuropharmacological and neurophysiological effects that leave both molecular and cellular imprints in the CNS. While some targets of ethanol and stress in the brain have been defined, particularly shifts in neurotransmitter tone, much of the influence of ethanol is mediated by subtle and non-specific modification of allosteric interactions and downstream events that will remain hard to pinpoint and manipulate. The joint effects of ethanol and stress also vary a great deal depending on genetic differences. In this INIA renewal we will use new genomic methods to understand much more about differential vulnerability to alcohol and stress and molecular targets. We exploit a diverse group of strains of mice (BXDs) that model many aspects of human genetic complexity. In Aim 1 we evaluate predisposing differences in gene expression and splicing and the effects that individual differences have on responses to stress and to eventual alcohol consumption. In aim 2 we will study the effects of chronic intermittent ethanol exposure (and animal model of binge drinking) on voluntary alcohol consumption. Here we are asking how the combination of stress and alcohol alters gene expression patterns in an almost permanent way to induce quick relapse when access to ethanol is provided. In aim 3 we will integrate, test, and translate our results from aims 1 and 2 to understand more about the complex molecular and cellular networks that contribute to both vulnerability and allostatic changes in brain function. We will exploit extensive human data sets to test the translational relevance of finding in murine populations.

DESCRIPTION (provided by applicant): Disturbances of metabolism, often linked to mitochondrial function, have a major impact on disease risk and healthspan among human populations. Type 2 diabetes mellitus, non-alcoholic fatty liver disease, hypertension, hyperlipidemia, and cardiovascular diseases are all linked to major changes in metabolic and mitochondrial function. A complex set of genetic and environmental factors-including diet-underlie individual differences in the risk and severity of metabolic syndrome. This project is focused on the complex gene-by- environmental interactions (GXE) that contribute to mitochondrial and metabolic syndrome, and that reduce healthy lifespan. We use a new integrative systems genetics approach to study effects of a high fat Western diet. This work relies on a large family of isogenic and genetically diverse murine lines-including F1 hybrids- that serve as a translational and mechanistic bridge between reductionist and integrative approaches. Identical cohorts will be studied as a function of age on markedly different diets. In Aim 1, we study lifespan using BXD strains and non-inbred but isogenic F1 cohorts of females under high and low fat diets. We map and quantify novel GXE-type modifier loci, candidate genes, and molecular networks that modulate healthspan and longevity. In Aim 2 we generate deep molecular, mitochondrial, and metabolic biomarker data as a function of age and diet. We expect that gene variants and diet will be causally linked to mitochondrial function and to metabolism in key organs and tissues. In Aim 3 we model complex and integrative molecular and cellular networks that define differences in vitality and healthspan. We use sophisticated bioinformatic and statistical frameworks (eQTL analysis, ANOVA, and structural equation modeling). Finally, in Aim 4 we validate and translate networks involved in metabolism, mitochondria, and healthspan. We test candidate genes using gain- and loss-of-function strategies in C. elegans. We evaluate translational relevance of candidate genes and biomarkers by testing for associations in a remarkably well studied cohort of 161,000 postmenopausal women (Women's Health Initiative data sets). The WHI is an ideal translation companion to test effects of diet. This project will (1) identify high impact variants and molecular/metabolic networks involved in metabolic diseases and healthspan, and (2) provide an experimental and predictive systems biology framework that links genotype and environmental factors to disease risk in human populations.

We are developing and improving powerful statistical and genetic tools to analyze and integrate massive omics data sets jointly with information on disease risk and severity. This work will enable far better use and re-use of complex and massive omics data sets and software by a wide community of users?ranging from students, researchers, and clinical scientists to expert data scientists and statisticians. We are building modular high- performance computational resources as part of a web services framework called GeneNetwork 2 (GN2). GN2 provides efficient data uploading and access and a suite of QC and analysis code that can be used or adapted for any species. Code is written in Python, C++, and R, and is supported by a relational database (MySQL) that incorporates the largest coherent collection of expression quantitative trait locus (eQTL) data. GN2 is optimized to handle a new generation of complex genetic crosses, including heterogeneous stock, hybrid diversity panels, GWAS cohorts, and sets of recombinant inbred strains such as the BXD and Collaborative Cross. GN2 includes new code for comparative and translational analysis of eQTL data sets and network graphs. In this grant we extend GN2 in four specific ways: far more capable data entry and export APIs and workflows, QC, and simulation routines (Aim 1); new high performance tools for the analysis of complex cross populations, comparative and translational analysis of systems genetics data sets (Aim 2), a new plug-in application programming interface (API) architecture with backend use of GPU web service systems (Aim 3), and statistical methods for correlated high dimensional data and predictive Bayesian modelling (Aim 4). We anticipate that this open and scalable architecture and modular code will become a core resource for both molecular biologists and data scientists, particularly those working in predictive modeling and precision medicine. All members of our team work closely with the systems genetics community and are training the next generation of young scientists interested in scalable integrative models of disease risk and treatment.

Addiction is a highly complex disease with risk factors that include genetic variants and differences in development, sex, and environment. The long term potential of precision medicine to improve drug treatment and prevention depends on gaining a much better understanding how genetics, drugs, brain cells, and neuronal circuitry interact to influence behavior. There are serious technical barriers that prevent researchers and clinicians from incorporating more powerful computational and predictive methods in addiction research. The purpose of the NIDA P30 Core Center of Excellence in Omics, Systems Genetics, and the Addictome is to empower and train researchers supported by NIH, NIDA, NIAAA, and other federal and state institutions to use more quantitative and testable ways to analyze genetic, epigenetic, and the environmental factors that influence drug abuse risk and treatment. The Administrative Core manages relations among research cores, groups of users, trainees, and pilot program participants. The Transcriptome Informatics and Mechanisms research core assembles and analyzes hundreds of large genome (DNA) and transcriptome (RNA) datasets for experimental rodent (rat) models of addiction. The Systems Analytics and Modeling research core, is using innovative systems genetics methods (gene mapping) to understand the linkage between DNA differences, environmental risks such as stress, and the differential risk of drug abuse and relapse. The Pilot core is catalyzing new collaborations among young investigator in the field of addiction research. In sum the Center is a national resource for more reproducible research in addiction. We are centralizing, archiving, distributing, analyzing and integrating high quality data, metadata, using open software systems in collaboration with many other teams of researchers. Our goal is to help build toward an NIDA Addictome Portal that will include all genomic research relevant to addiction research.

Addiction is a highly complex disease with risk factors that include genetic variants and differences in development, sex, and environment. The long term potential of precision medicine to improve drug treatment and prevention depends on gaining a much better understanding how genetics, drugs, brain cells, and neuronal circuitry interact to influence behavior. There are serious technical barriers that prevent researchers and clinicians from incorporating more powerful computational and predictive methods in addiction research. The purpose of the NIDA P30 Core Center of Excellence in Omics, Systems Genetics, and the Addictome is to empower and train researchers supported by NIH, NIDA, NIAAA, and other federal and state institutions to use more quantitative and testable ways to analyze genetic, epigenetic, and the environmental factors that influence drug abuse risk and treatment. In the Transcriptome Informatics and Mechanisms research core we assemble and upgrade hundreds of large genome (DNA) and transcriptome (RNA) datasets for experimental rodent (rat) models of addiction. In the Systems Analytics and Modeling research core, we are using innovative systems genetics methods (gene mapping) to understand the linkage between DNA differences, environmental risks such as stress, and the differential risk of drug abuse and relapse. Our Pilot core is catalyzing new collaborations among young investigator in the field of addiction research. In sum the Center is a national resource for more reproducible research in addiction. We are centralizing, archiving, distributing, analyzing and integrating high quality data, metadata, using open software systems in collaboration with many other teams of researchers. Our goal is to help build toward an NIDA Addictome Portal that will include all genomic research relevant to addiction research.

Addiction is a highly complex disease with risk factors that include genetic variants and differences in development, sex, and environment. The long term potential of precision medicine to improve drug treatment and prevention depends on gaining a much better understanding how genetics, drugs, brain cells, and neuronal circuitry interact to influence behavior. There are serious technical barriers that prevent researchers and clinicians from incorporating more powerful computational and predictive methods in addiction research. The purpose of the NIDA P30 Core Center of Excellence in Omics, Systems Genetics, and the Addictome is to empower and train researchers supported by NIH, NIDA, NIAAA, and other federal and state institutions to use more quantitative and testable ways to analyze genetic, epigenetic, and the environmental factors that influence drug abuse risk and treatment. Our Pilot core is catalyzing new collaborations among early career investigators in the field of addiction research. In sum the Center is a national resource for reproducible research in addiction. We are centralizing, archiving, distributing, analyzing and integrating high quality data, metadata, using open software systems in collaboration with many other teams of researchers. Our goal is to help build toward an NIDA Addictome Portal that will include all genomic research relevant to addiction research.

The steady rise in prescription opioids such as oxycodone has led to widespread abuse and deaths in the US. importance of drug pharmacokinetics in determining abuse potential, we have designed an oral operant rat self-administration (SA) procedure to model the pattern of drug intake of most human users/abusers of oxycodone, who initiate using oral tablets. Although genetic variants play important roles in susceptibility to opioid addiction, very limited data are available regarding specific genes and sequence variants that predispose to opioid addiction, and under what conditions. Given the We propose to use an innovative hybrid rat diversity panel (HRDP), which consists of 91 diverse rat genomes, to identify genetic variants influencing operant oxycodone intake in rats. The HRDP is unique in that it: 1) contains a high level of genetic diversity similar to that of human populations; 2) provides a way to control oxycodone exposure and to systematically study gene-by-environment and gene-by-drug interactions; and 3) integrates multi-omics addictome data: from genetics to epigenomics to brain connectomes to treatments. We have three aims: Aim 1: We will analyze whole genome sequencing data to define virtually all sequence variants that underlie heritable variations. De novo assemblies will be conducted using linked-reads data for selected high impact strains. Hi-C data (Dovetail Genomics) will be generated to further improve the quality of these assemblies. We will also generate RNA-seq data for key brain regions to obtain mechanistic insights into oxycodone intake. Aim 2: Using the HRDP (both sexes), we will phenotype oral oxycodone SA with a unique behavioral model. Rats will also be tested for sensitivity to pain, social behaviors, and anxiety-like traits - all signs of oxycodone withdrawal. Critically, we estimated the heritability (h2) of oxycodone intake in the range of 0.3 ? 0.4. When using n=6/sex, the effective h2 is ~0.8 ?sufficient for high precision mapping. Aim 3: We will use systems genetics methods to map and integrate behavioral phenotypes with sequence and transcriptome data. Both forward (QTL) and reverse (PheWAS) genetic methods will be used. We use new linear mixed models to map and test candidate genes with key cofactors using the GeneNetwork2 platform. Finally, we evaluate the translational relevance of candidate genes and biomarkers by comparison to GWAS cohorts and longitudinal reports of addiction in humans. Technical and conceptual advances that underlie this application are: new genomic methods combined with highly diverse rat populations allow us to quickly define novel gene variants that modulate key phases of opiate addiction. It is highly likely that a subset of variants and molecular networks we define will provide key components of a predictive framework linking sequence differences to human opioid addiction and potential treatments. This project uses new systems genetics approaches, open source genomic data and software, and a new type of hybrid rodent mapping panel to precisely define causal linkages between DNA variation and voluntary oxycodone intake.

Age-related cognitive decline (ARCD), Alzheimer disease (AD), and late-onset AD-related pathologies are linked to changes in brain structure, cell populations, synapse densities and connections, inflammation, protein aggregation and mitochondrial stress. However, we do not understand the complex causal networks and mechanisms of ARCD and AD. In this neurogenetics imaging program we quantify the impact of human familial AD (FAD) gene variants on brain structure and function using a highly diverse cohort of aging mouse hybrids that combine human genes variants with the BXD family. In Aims 1 and 2 we generate high resolution whole brain MRI DTI data and connectomes for each of 40 sex-matched sets of transgenic and aging control hybrids at ~6 and ~14 months using state-of-the art analysis workflows. We generate matched behavioral data, as well as light-sheet immunohistochemistry for entire brains taken from subsets of cases with the most outstanding phenotypes?lines that are highly susceptible to cognitive loss and those that are most resilient. Light-sheet, MRI-DTI and fMRI connectomes is merged with MI-DTI in Aim 3. All work exploits systems genetics and mapping methods we have developed and embedded in the GeneNetwork web service. A crucial facet of Aim 3 is integrating extensive behavioral data on age-related cognitive and other behavioral and CNS changes generated from AD-BXD and many other models. This allows us to define loci, candidate genes, and mechanisms modulating ARCD and AD, and to systematically test for associations with age, sex, and linked changes in structure, connectivity, and cell types. Finally, we integrate omics data we have for BXD and other genomes (e.g., hippocampal RNA-seq and proteomes) with comprehensive human AD GWAS, imaging, and omics data. All results are shared openly using robust internet services?GeneWeaver, CIVM server, NIF, Mouse Phenome Database, and the AMP-AD Knowledge Portal. Data and workflows will be FAIR-compliant. Key deliverables are (1) far more quantitative, unbiased, global, and replicable data on genetic, molecular, cellular, and system-wide processes linked to cognitive loss and AD. We also deliver causal molecular and mechanistic models of that incorporate realistically high levels of genetic diversity?6 million DNA variants. This work empowers in-depth unbiased analyses of age-related functional decline in ARCD and AD that translate to human populations. Success will enable faster and more robust preclinical testing of interventions and drug treatments for ARCD and AD.

The rat is the most commonly used model organism for behavioral studies of addiction. We propose to establish an innovative hybrid rat diversity panel (HRDP) in this work. The HRDP is unique in that it integrates: 1) a high level of genetic diversity similar to that of admixed human populations; 2) a way to control drug exposures and to systematically study gene-by-environment and gene-by-drug interactions; and 3) a way to integrate addictome data across scale: from genetics, genomics, and other molecular data together with key addiction related risks. This work will be a step toward developing experimental resources for precision medicine. The HRDP consists of 91 highly diverse genomes of rats that are all open access and can be used by any investigators to study facet of addiction and in different environments or under different treatments. We will use the HRDP to identify sequence variants that control motivational effects of nicotine with a menthol cue. Approximately 25% of smokers prefer mentholated cigarettes. Clinical studies have shown that menthol facilitates initiation, enhances dependence and makes quitting more difficult. Given the large sample size needed in human studies to identify key sequence variants associated with drug addiction, we argue that animal models provide an efficient means to define and test genetic and molecular mechanisms that contribute to the addiction-enhancing effects of menthol. We developed a rat model of nicotine i.v. self-administration (IVSA) with an oral menthol cue. We found that 1) menthol facilitates the acquisition of nicotine IVSA, 2) rats that receive the menthol cue for nicotine show a strong extinction burst, a model for drug craving, and 3) these rats also demonstrate a strong cue-induced reinstatement, a model of relapse. We also showed that the cooling sensation of menthol functions as a conditioned cue for nicotine reward, and that oral menthol treatment increases brain nicotine accumulation. Critically, in the context of this U01 mechanism, we estimate that heritability of these traits are greater than 0.6. We have three aims: In Aim 1 we conduct whole genome sequencing of the HRDP. We will define all sequence variants that underlie heritable variation using innovative linked-read libraries and de novo assemblies. In Aim 2 we phenotype nicotine IVSA with a menthol cue in adolescent HRDP animals of both sexes with deep replication. We will phenotype nicotine IVSA with a visual cue as a control. Effects of oral menthol on brain nicotine level will be measured. In Aim 3 we use systems genetics methods to map and integrated behavioral phenotypes. Both forward (QTL) and reverse (PheWAS) genetic methods will be used. We will use new linear mixed models to map and test candidate genes with key cofactors (i.e., different cues). Finally, we evaluate the translational relevance of candidate genes and biomarkers by comparison to GWAS cohorts and longitudinal reports of addiction in humans. This U01 will define high impact variants and molecular networks, and will provide a predictive and expandable experimental framework to link sequence differences to critical aspects of human nicotine addiction.