Megan K. Mulligan

A promoter polymorphism in the Per3 gene is associated with alcohol and stress response

The period homolog genes Per1, Per2 and Per3 are important components of the circadian clock system. In addition to their role in maintaining circadian rhythm, these genes have been linked to mood disorders, stress response and vulnerability to addiction and alcoholism. In this study, we combined high-resolution sequence analysis and quantitative trait locus (QTL) mapping of gene expression and behavioral traits to identify Per3 as a compelling candidate for the interaction between circadian rhythm, alcohol and stress response. In the BXD family of mouse strains, sequence variants in Per3 have marked effects on steady-state mRNA and protein levels. As a result, the transcript maps as a cis-acting expression QTL (eQTL). We found that an insertion/deletion (indel) variant in a putative stress response element in the promoter region of Per3 causes local control of transcript abundance. This indel results in differences in protein binding affinities between the two alleles through the Nrf2 transcriptional activator. Variation in Per3 is also associated with downstream differences in the expression of genes involved in circadian rhythm, alcohol, stress response and schizophrenia. We found that the Per3 locus is linked to stress/anxiety traits, and that the basal expression of Per3 is also correlated with several anxiety and addiction-related phenotypes. Treatment with alcohol results in increased expression of Per3 in the hippocampus, and this effect interacts with acute restraint stress. Our data provide strong evidence that variation in the Per3 transcript is causally associated with and also responsive to stress and alcohol.

Alcohol trait and transcriptional genomic analysis of C57BL/6 substrains

C57BL/6 inbred mice have been widely used as research models; however, widespread demand has led to the creation of several B6 substrains with markedly different phenotypes. In this study, we report that two substrains of C57BL/6 mice, C57BL/6J (B6J) and C57BL/6NCrl (B6C), separated over 50 years ago at two different breeding facilities differ significantly in alcohol consumption and alcohol preference. The genomes of these two substrains are estimated to differ by only 1–2% of all gene loci, providing a unique opportunity to extract particular expression signatures between these substrains that are associated with quantifiable behavioral differences. Expression profiling of the cortex and striatum, hippocampus, cerebellum and the ventral brain region from alcohol‐naïve B6C and B6J mice showed intervals on three chromosomes that are enriched in clusters of coregulated transcripts significantly divergent between the substrains. Additional analysis identified two genomic regions containing putative copy number differences between the substrains. One such region on chromosome 14 contained an estimated 3n copy number in the B6J genome compared with B6C. Within this interval, a gene of unknown function, D14Ertd449e, was found to be both associated with alcohol preference and vary in copy number across several inbred strain lineages. H2afz, Psen1, Wdfy1 and Clu were also identified as candidate genes that may be involved in influencing alcohol consumption.

Joint mouse-human phenome-wide association to test gene function and disease risk

Phenome-wide association is a novel reverse genetic strategy to analyze genome-to-phenome relations in human clinical cohorts. Here we test this approach using a large murine population segregating for ∼5 million sequence variants, and we compare our results to those extracted from a matched analysis of gene variants in a large human cohort. For the mouse cohort, we amassed a deep and broad open-access phenome consisting of ∼4,500 metabolic, physiological, pharmacological and behavioural traits, and more than 90 independent expression quantitative trait locus (QTL), transcriptome, proteome, metagenome and metabolome data sets—by far the largest coherent phenome for any experimental cohort (www.genenetwork.org). We tested downstream effects of subsets of variants and discovered several novel associations, including a missense mutation in fumarate hydratase that controls variation in the mitochondrial unfolded protein response in both mouse and Caenorhabditis elegans, and missense mutations in Col6a5 that underlies variation in bone mineral density in both mouse and human.

A Transposon in Comt Generates mRNA Variants and Causes Widespread Expression and Behavioral Differences among Mice

Background Catechol-O-methyltransferase (COMT) is a key enzyme responsible for the degradation of dopamine and norepinephrine. COMT activity influences cognitive and emotional states in humans and aggression and drug responses in mice. This study identifies the key sequence variant that leads to differences in Comt mRNA and protein levels among mice, and that modulates synaptic function and pharmacological and behavioral traits. Methodology/Principal Findings We examined Comt expression in multiple tissues in over 100 diverse strains and several genetic crosses. Differences in expression map back to Comt and are generated by a 230 nt insertion of a B2 short interspersed element (B2 SINE) in the proximal 3′ UTR of Comt in C57BL/6J. This transposon introduces a premature polyadenylation signal and creates a short 3′ UTR isoform. The B2 SINE is shared by a subset of strains, including C57BL/6J, A/J, BALB/cByJ, and AKR/J, but is absent in others, including DBA/2J, FVB/NJ, SJL/J, and wild subspecies. The short isoform is associated with increased protein expression in prefrontal cortex and hippocampus relative to the longer ancestral isoform. The Comt variant causes downstream differences in the expression of genes involved in synaptic function, and also modulates phenotypes such as dopamine D1 and D2 receptor binding and pharmacological responses to haloperidol. Conclusions/Significance We have precisely defined the B2 SINE as the source of variation in Comt and demonstrated that a transposon in a 3′ UTR can alter mRNA isoform use and modulate behavior. The recent fixation of the variant in a subset of strains may have contributed to the rapid divergence of inbred strains.

Complex Control of GABA(A) Receptor Subunit mRNA Expression: Variation, Covariation, and Genetic Regulation

GABA type-A receptors are essential for fast inhibitory neurotransmission and are critical in brain function. Surprisingly, expression of receptor subunits is highly variable among individuals, but the cause and impact of this fluctuation remains unknown. We have studied sources of variation for all 19 receptor subunits using massive expression data sets collected across multiple brain regions and platforms in mice and humans. Expression of Gabra1, Gabra2, Gabrb2, Gabrb3, and Gabrg2 is highly variable and heritable among the large cohort of BXD strains derived from crosses of fully sequenced parents—C57BL/6J and DBA/2J. Genetic control of these subunits is complex and highly dependent on tissue and mRNA region. Remarkably, this high variation is generally not linked to phenotypic differences. The single exception is Gabrb3, a locus that is linked to anxiety. We identified upstream genetic loci that influence subunit expression, including three unlinked regions of chromosome 5 that modulate the expression of nine subunits in hippocampus, and that are also associated with multiple phenotypes. Candidate genes within these loci include, Naaa, Nos1, and Zkscan1. We confirmed a high level of coexpression for subunits comprising the major channel—Gabra1, Gabrb2, and Gabrg2—and identified conserved members of this expression network in mice and humans. Gucy1a3, Gucy1b3, and Lis1 are novel and conserved associates of multiple subunits that are involved in inhibitory signaling. Finally, proximal and distal regions of the 3′ UTRs of single subunits have remarkably independent expression patterns in both species. However, corresponding regions of different subunits often show congruent genetic control and coexpression (proximal-to-proximal or distal-to-distal), even in the absence of sequence homology. Our findings identify novel sources of variation that modulate subunit expression and highlight the extraordinary capacity of biological networks to buffer 4–100 fold differences in mRNA levels.

High-throughput sequencing of the DBA/2J mouse genome

BackgroundThe DBA/2J mouse is not only the oldest inbred strain,but also one of the most widely used strains. DBA/2Jexhibits many unique anatomical, physiological, andbehavior traits. In addition, DBA/2J is one parent of thelarge BXD family of recombinant inbred strains [1]. Thegenome of the other parent of this BXD family—C57BL/6J—has been sequenced and serves as themouse reference genome [2]. We sequenced the gen-ome of DBA/2J using SOLiD and Illumina highthroughput short read protocols to generate a compre-hensive set of ~5 million sequence variants segregatingin the BXD family that ultimately cause developmental,anatomical, functional and behavioral differences amongthese 80+ strains.ResultsWe generated approximately 13.2 and 38.9× whole-gen-ome short reads of DBA/2J females using Illumina GA2and ABI SOLiD massively parallel DNA sequencingplatforms. Comparing to the C57BL/6J reference gen-ome sequence, we identified over 4.5 million singlenucleotide polymorphisms (SNPs), including 84 non-sense and ~11,000 missense mutations, 78% of whichare novel. We also detected ~568,000 insertions anddeletions (indels) within single short reads and ~9,400between mate-paired reads. Approximately 300 inver-sions were detected by SOLiD mate-pair reads, 46 ofwhich span at least one exon. In addition, we identified~22,000 copy number variants (CNVs) in the range of1 Kb to 100 Kb (Figure 1).ConclusionOur study generates the first consensus sequence for theDBA/2J and creates a compendium of sequence andstructural variations that will be used by the communityof researchers who study complex traits in mouse mod-els.Thesequencedataprovideanovelresourcewithwhich to initiate reverse genetic analysis of complex

Genetic regulation of Nrnx1 expression: an integrative cross-species analysis of schizophrenia candidate genes

Neurexin 1 (NRXN1) is a large presynaptic transmembrane protein that has complex and variable patterns of expression in the brain. Sequence variants in NRXN1 are associated with differences in cognition, and with schizophrenia and autism. The murine Nrxn1 gene is also highly polymorphic and is associated with significant variation in expression that is under strong genetic control. Here, we use co-expression analysis, high coverage genomic sequence, and expression quantitative trait locus (eQTL) mapping to study the regulation of this gene in the brain. We profiled a family of 72 isogenic progeny strains of a cross between C57BL/6J and DBA/2J (the BXD family) using exon arrays and massively parallel RNA sequencing. Expression of most Nrxn1 exons have high genetic correlation (r>0.6) because of the segregation of a common trans eQTL on chromosome (Chr) 8 and a common cis eQTL on Chr 17. These two loci are also linked to murine phenotypes relevant to schizophrenia and to a novel human schizophrenia candidate gene with high neuronal expression (Pleckstrin and Sec7 domain containing 3). In both human and mice, NRXN1 is co-expressed with numerous synaptic and cell signaling genes, and known schizophrenia candidates. Cross-species co-expression and protein interaction network analyses identified glycogen synthase kinase 3 beta (GSK3B) as one of the most consistent and conserved covariates of NRXN1. By using the Molecular Genetics of Schizophrenia data set, we were able to test and confirm that markers in NRXN1 and GSK3B have epistatic interactions in human populations that can jointly modulate risk of schizophrenia.

Expression, covariation, and genetic regulation of miRNA biogenesis genes in brain supports their role in addiction, psychiatric disorders, and disease

The role of miRNA and miRNA biogenesis genes in the adult brain is just beginning to be explored. In this study we have performed a comprehensive analysis of the expression, genetic regulation, and co-expression of major components of the miRNA biogenesis pathway using human and mouse data sets and resources available on the GeneNetwork web site (genenetwork.org). We found a wide range of variation in expression in both species for key components of the pathway—Drosha, Pasha, and Dicer. Across species, tissues, and expression platforms all three genes are generally well-correlated. No single genetic locus exerts a strong and consistent influence on the expression of these key genes across murine brain regions. However, in mouse striatum, many members of the miRNA pathway are correlated—including Dicer, Drosha, Pasha, Ars2 (Srrt), Eif2c1 (Ago1), Eif2c2 (Ago2), Zcchc11, and Snip1. The expression of these genes may be partly influenced by a locus on Chromosome 9 (105.67–106.32 Mb). We explored ~1500 brain phenotypes available for the C57BL/6J × DBA/2J (BXD) genetic mouse population in order to identify miRNA biogenesis genes correlated with traits related to addiction and psychiatric disorders. We found a significant association between expression of Dicer and Drosha in several brain regions and the response to many drugs of abuse, including ethanol, cocaine, and methamphetamine. Expression of Dicer, Drosha, and Pasha in most of the brain regions explored is strongly correlated with the expression of key members of the dopamine system. Drosha, Pasha, and Dicer expression is also correlated with the expression of behavioral traits measuring depression and sensorimotor gating, impulsivity, and anxiety, respectively. Our study provides a global survey of the expression and regulation of key miRNA biogenesis genes in brain and provides preliminary support for the involvement of these genes and their product miRNAs in addiction and psychiatric disease processes.

GeneNetwork: A Toolbox for Systems Genetics.

The goal of systems genetics is to understand the impact of genetic variation across all levels of biological organization, from mRNAs, proteins, and metabolites, to higher-order physiological and behavioral traits. This approach requires the accumulation and integration of many types of data, and also requires the use of many types of statistical tools to extract relevant patterns of covariation and causal relations as a function of genetics, environment, stage, and treatment. In this protocol we explain how to use the GeneNetwork web service, a powerful and free online resource for systems genetics. We provide workflows and methods to navigate massive multiscalar data sets and we explain how to use an extensive systems genetics toolkit for analysis and synthesis. Finally, we provide two detailed case studies that take advantage of human and mouse cohorts to evaluate linkage between gene variants, addiction, and aging.

Genetic Variation in the Social Environment Contributes to Health and Disease

Assessing the impact of the social environment on health and disease is challenging. As social effects are in part determined by the genetic makeup of social partners, they can be studied from associations between genotypes of one individual and phenotype of another (social genetic effects, SGE, also called indirect genetic effects). For the first time we quantified the contribution of SGE to more than 100 organismal phenotypes and genome-wide gene expression measured in laboratory mice. We find that genetic variation in cage mates (i.e. SGE) contributes to variation in organismal and molecular measures related to anxiety, wound healing, immune function, and body weight. Social genetic effects explained up to 29% of phenotypic variance, and for several traits their contribution exceeded that of direct genetic effects (effects of an individual’s genotypes on its own phenotype). Importantly, we show that ignoring SGE can severely bias estimates of direct genetic effects (heritability). Thus SGE may be an important source of “missing heritability” in studies of complex traits in human populations. In summary, our study uncovers an important contribution of the social environment to phenotypic variation, sets the basis for using SGE to dissect social effects, and identifies an opportunity to improve studies of direct genetic effects.