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Robert W Williams

Publications and source records attributed to Robert W Williams.

At least 19 recordsLinked to original sources

Systems genetics approaches model the heritable architecture of polyendocrine metabolic ovarian syndrome.

Polyendocrine metabolic ovarian syndrome (PMOS), formerly known as polycystic ovary syndrome (PCOS), is the most common endocrine disorder in women and is closely associated with complex diseases such as cardiovascular disease and type 2 diabetes. However, the mechanistic links between PMOS and its comorbidities remain poorly understood. Here, we present an integrative systems genetics platform that leverages genetic diversity in both mice and humans to dissect the drivers of PMOS and its associated complications. This framework uncovered conserved genetic and environmental factors underlying PMOS, identified susceptible cell types and organs, and elucidated mechanisms linking PMOS to subsequent pathologies. For instance, we showed that increased ovarian area contributes to both PMOS susceptibility and ovarian cancer progression, while specific ovary-heart signaling circuits modulate cardiac function with aging. We further identified ovarian SF3B1-mediated alternative splicing as a key mechanistic link between PMOS and metabolic traits. Pharmacologic inhibition of SF3B1 in mice reduced circulating testosterone, insulin, and glucose levels as well as fat mass expansion. Transcriptomics analysis of ovaries from mice and experiments using human cell lines localized these effects to exon skipping events in granulosa cells. Together, this study offers a mechanistic framework for modeling the diversity of PMOS pathologies and uncovers SF3B1-mediated splicing as a link between ovary function and systemic metabolism.

Female↗

Meta-analysis for microarray studies of the genetics of complex traits.

In comparison to other complex disease traits, alcoholism and alcohol abuse are influenced by the combined effects of many genes that alter susceptibility, phenotypic expression and associated morbidity, respectively. Many genetic studies, in both animal models and humans, have identified genetic intervals containing genes that influence alcoholism or behavioral responses to ethanol. Concurrently, a growing number of microarray studies have identified gene expression differences related to ethanol drinking or other ethanol behaviors. However, concerns about the statistical power of these experiments, combined with the complexity of the underlying phenotypes, have greatly hampered the identification of candidate genes underlying ethanol behaviors. Meta-analysis approaches using recent compilations of large datasets of microarray, behavioral and genetic data promise improved statistical power for detecting the genes or gene networks affecting ethanol behaviors and other complex traits.

Alcohol Drinking↗

Genetic and structural analysis of the basolateral amygdala complex in BXD recombinant inbred mice.

The amygdala integrates and coordinates emotional and autonomic responses. The genetics that underlie variation in amygdala structure may be coupled to variation in levels of aggression, fear, anxiety, and affiliated behaviors. We systematically quantified the volume and cell populations of the basolateral amygdala complex (BLAc) across 35 BXD recombinant inbred (RI) lines, the parental strains--C57BL/6J (B6) and DBA/2J (D2)--and F1 hybrids (n cases=199, bilateral analysis). Neuron number and volume vary 1.7- to 2-fold among strains (e.g., neuron number ranged from 88,000 to 170,000). Glial and endothelial populations ranged more widely (5- to 8-fold), in part because of higher technical error. A quantitative trait locus (QTL) for the BLAc size is located on chromosome (Chr) 8 near the Large gene. This locus may also influence volume of other regions including hippocampus and cerebellum. Cell populations in the BLAc appear to be modulated more weakly by loci on Chrs 11 and 13. Candidate genes were selected on the basis of correlation with BLAc traits, chromosomal location, single nucleotide polymorphism (SNP) density, and expression patterns in the Allen Brain Atlas. Neurod2, a gene shown to be significant for the formation of the BLAc by knockout studies, is among the candidates genes. Other candidates include Large, and Thra. Responses to drugs of abuse and locomotor activity were the most notable behavioral correlates of the BLAc traits.

Amygdala↗

PolymiRTS Database: linking polymorphisms in microRNA target sites with complex traits.

Polymorphism in microRNA Target Site (PolymiRTS) database is a collection of naturally occurring DNA variations in putative microRNA target sites. PolymiRTSs may affect gene expression and cause variations in complex phenotypes. The database integrates sequence polymorphism, phenotype and expression microarray data, and characterizes PolymiRTSs as potential candidates responsible for the quantitative trait locus (QTL) effects. It is a resource for studying PolymiRTSs and their implications in phenotypic variations. PolymiRTS database can be accessed at http://compbio.utmem.edu/miRSNP/.

Animals↗

Combining gene expression QTL mapping and phenotypic spectrum analysis to uncover gene regulatory relationships.

Gene expression QTL (eQTL) mapping can suggest candidate regulatory relationships between genes. Recent advances in mammalian phenotype annotation such as mammalian phenotype ontology (MPO) enable systematic analysis of the phenotypic spectrum subserved by many genes. In this study we combined eQTL mapping and phenotypic spectrum analysis to predict gene regulatory relationships. Five pairs of genes with similar phenotypic effects and potential regulatory relationships suggested by eQTL mapping were identified. Lines of evidence supporting some of the predicted regulatory relationships were obtained from biological literature. A particularly notable example is that promoter sequence analysis and real-time PCR assays support the predicted regulation of protein kinase C epsilon (Prkce) by cAMP responsive element binding protein 1 (Creb1). Our results show that the combination of gene eQTL mapping and phenotypic spectrum analysis may provide a valuable approach to uncovering gene regulatory relations underlying mammalian phenotypes.

Animals↗

Prediction of cis-QTLs in a pair of inbred mouse strains with the use of expression and haplotype data from public databases.

Cis-QTLs are important candidates for any other trait that maps to the same locus. In this article we have used publicly available databases and a small microarray data set to "map" cis-QTLs in the ILS and ISS inbred mouse strains without the need to generate microarray data from an ILSXISS segregating population. Expression data were obtained from brains of C57BL/6, DBA/2, ILS, and ISS. Cis-QTLs were mapped for the 760 transcripts found to be differentially expressed between the C57BL/6 and DBA/2 using expression data previously obtained from the BXD RIs. The 469 detected cis-QTLs were then examined for SNP haplotypes and expression patterns that could relate the ILS and ISS to the C57BL/6 and DBA/2. Of the 338 cis-QTL transcripts that had informative haplotypes, 189 were significantly different between the ILS and ISS with 184 showing segregation of haplotype with expression. These were considered to be probable cis-QTLs in the ILS and ISS. There were almost certainly additional ILS/ISS cis-QTLs among the other transcripts with informative haplotypes, but in the absence of an ILS/ISS expression difference, the level of confidence was reduced. Several of the putative ILS/ISS cis-QTLs are considered important candidate genes because they are linked to ILS/ISS behavioral QTLs. A potential ascertainment bias related to strain-dependent target sequences was observed suggesting that as much as 35% of the cis-QTLs were hybridization artifacts. Nonetheless, the results suggest that this approach is an economical and widely applicable method for mapping cis-QTLs in a strain pair of interest.

Animals↗

How replicable are mRNA expression QTL?

Applying quantitative trait analysis methods to genome-wide microarray-derived mRNA expression phenotypes in segregating populations is a valuable tool in the attempt to link high-level traits to their molecular causes. The massive multiple-testing issues involved in analyzing these data make the correct level of confidence to place in mRNA abundance quantitative trait loci (QTL) a difficult problem. We use a unique resource to directly test mRNA abundance QTL replicability in mice: paired recombinant inbred (RI) and F(2) data sets derived from C57BL/6J (B6) and DBA/2J (D2) inbred strains and phenotyped using the same Affymetrix arrays. We have one forebrain and one striatum data set pair. We describe QTL replication at varying stringencies in these data. For instance, 78% of mRNA expression QTL (eQTL) with genome-wide adjusted p < or = 0.0001 in RI data replicate at a genome-wide adjusted p < 0.05 or better. Replicated QTL are disproportionately putatively cis-acting, and approximately 75% have higher apparent expression levels associated with B6 genotypes, which may be partly due to probe set generation using B6 sequence. Finally, we note that while trans-acting QTL do not replicate well between data sets in general, at least one cluster of trans-acting QTL on distal Chr 1 is notably preserved between data sets.

Animals↗

Expression genetics and the phenotype revolution.

Genetic analysis of variation demands large numbers of individuals and even larger numbers of genotypes. The identification of alleles associated with Mendelian disorders has involved sample sizes of a thousand or more. Pervasive and common diseases that afflict human populations--cancer, heart disease, diabetes, neurodegeneration, addiction--are all polygenic and are even more demanding of large numbers. DeCode Genetics (http://www.decode.com) has harnessed the human resources of Iceland to unravel genetic and molecular causes of complex disease. The UK BioBank project (http://www.ukbiobank.ac.uk/) will incorporate 500,000 adult volunteers. The murine Collaborative Cross is the experimental equivalent of these human populations and will consist of a panel of approximately 1000 recombinant strains, expandable by intercrossing to much larger numbers of isogenic but heterozygous F(1)s. Massive projects of these types require efficient technologies. We have made enormous progress on the genotyping front, and it is now important to focus energy on devising ultrahigh-throughput methods to phenotype. Molecular phenotyping of the transcriptome has matured, and it is now possible to acquire hundreds of thousands of mRNA phenotypes at a cost matching those of SNPs. Proteomic and cell-based assays are also maturing rapidly. The acquisition of a personal genome along with a personal molecular phenome will provide an effective foundation for personalized medicine. Rodent models will be essential to test our ability to predict susceptibility and disease outcome using SNP data, molecular phenomes, and environmental exposures. These models will also be essential to test new treatments in a robust systems context that accounts for genetic variation.

Animals↗

Probing the genetic basis for thyrotropin receptor antibodies and hyperthyroidism in immunized CXB recombinant inbred mice.

Immunization with adenovirus encoding the TSH receptor (TSHR) or its A-subunit induces Graves' hyperthyroidism in BALB/c and BALB/c x C57BL/6 offspring but not C57BL/6 mice. High-resolution genetic maps are available for 13 recombinant inbred CXB strains generated from BALB/c x C57BL/6 progeny by repeated brother x sister matings to establish fully inbred lines. CXB strains were studied before and after A-subunit adenovirus immunization for TSHR antibodies (TBI, inhibition of TSH binding), serum T4, and thyroid histology. All strains developed TBI activity (at variable levels), six strains became hyperthyroid, and one was overtly thyrotoxic. No low TBI responders became hyperthyroid, but high TBI did not predict hyperthyroidism. Preimmunization T4 levels varied in different CXB strains and was unrelated to subsequent T4 elevation. Linkage analysis indicated that different chromosomes were involved in generating TSHR antibodies and serum T4 before and after immunization. TBI activity was linked in part with major histocompatibility (MHC) genes on chromosome 17 (Chr 17) but induced Graves' disease involved non-MHC genes (Chr 19 and 10). The Chr 10 locus is close to the Trhde gene that encodes TSH-releasing hormone degrading enzyme. Expression of Trhde is controlled by thyroid hormones and linkage with a thyroid function-related gene is intriguing. Our data, the first genome scan in murine Graves' disease, provides insight into the role of MHC and non-MHC genes in human and murine Graves' disease. Finally, our study demonstrates the potential of recombinant inbred mice for discriminating between immune-response genes and thyroid function susceptibility genes in Graves' disease.

Adenoviridae↗

Combined expression trait correlations and expression quantitative trait locus mapping.

Coordinated regulation of gene expression levels across a series of experimental conditions provides valuable information about the functions of correlated transcripts. The consideration of gene expression correlation over a time or tissue dimension has proved valuable in predicting gene function. Here, we consider correlations over a genetic dimension. In addition to identifying coregulated genes, the genetic dimension also supplies us with information about the genomic locations of putative regulatory loci. We calculated correlations among approximately 45,000 expression traits derived from 60 individuals in an F2 sample segregating for obesity and diabetes. By combining the correlation results with linkage mapping information, we were able to identify regulatory networks, make functional predictions for uncharacterized genes, and characterize novel members of known pathways. We found evidence of coordinate regulation of 174 G protein-coupled receptor protein signaling pathway expression traits. Of the 174 traits, 50 had their major LOD peak within 10 cM of a locus on Chromosome 2, and 81 others had a secondary peak in this region. We also characterized a Riken cDNA clone that showed strong correlation with stearoyl-CoA desaturase 1 expression. Experimental validation confirmed that this clone is involved in the regulation of lipid metabolism. We conclude that trait correlation combined with linkage mapping can reveal regulatory networks that would otherwise be missed if we studied only mRNA traits with statistically significant linkages in this small cross. The combined analysis is more sensitive compared with linkage mapping alone.

Animals↗

Natural variation and genetic covariance in adult hippocampal neurogenesis.

Adult hippocampal neurogenesis is highly variable and heritable among laboratory strains of mice. Adult neurogenesis is also remarkably plastic and can be modulated by environment and activity. Here, we provide a systematic quantitative analysis of adult hippocampal neurogenesis in two large genetic reference panels of recombinant inbred strains (BXD and AXB/BXA, n = 52 strains). We combined data on variation in neurogenesis with a new transcriptome database to extract a set of 190 genes with expression patterns that are also highly variable and that covary with rates of (i) cell proliferation, (ii) cell survival, or the numbers of surviving (iii) new neurons, and (iv) astrocytes. Expression of a subset of these neurogenesis-associated transcripts was controlled in cis across the BXD set. These self-modulating genes are particularly interesting candidates to control neurogenesis. Among these were musashi (Msi1h) and prominin1/CD133 (Prom1), both of which are linked to stem-cell maintenance and division. Twelve neurogenesis-associated transcripts had significant cis-acting quantitative trait loci, and, of these, six had plausible biological association with adult neurogenesis (Prom1, Ssbp2, Kcnq2, Ndufs2, Camk4, and Kcnj9). Only one cis-acting candidate was linked to both neurogenesis and gliogenesis, Rapgef6, a downstream target of ras signaling. The use of genetic reference panels coupled with phenotyping and global transcriptome profiling thus allowed insight into the complexity of the genetic control of adult neurogenesis.

Animals↗

Independent quantitative trait loci influence ventral and dorsal hippocampal volume in recombinant inbred strains of mice.

Anatomical and functional studies support segregation of the hippocampus into ventral and dorsal components along its septotemporal axis. However, it is unknown whether the development of these two components of the hippocampus is influenced by common or separate genetic factors. In this study, we used recombinant inbred strains of mice to determine whether the same or different quantitative trait loci (QTL) influence ventral and dorsal hippocampal volume. Using two sets of strains of recombinant inbred mice (BXD and AXB/BXA), we identified separate QTLs for ventral and dorsal hippocampal volume. In BXD mice, suggestive QTLs for ventral hippocampus were identified on chromosomes 2, 8 and 13, and a significant QTL for dorsal hippocampal volume was identified on chromosome 15. There was also a suggestive QTL for dorsal hippocampal volume on chromosome 13. In AXB/BXA mice, there were no significant or suggestive QTLs for ventral hippocampal volume, but a significant QTL for dorsal hippocampus was identified on chromosome 5. These findings suggest that the development of the ventral and dorsal components of the hippocampus is influenced by separate genetic loci.

Age Factors↗

A high-resolution single nucleotide polymorphism genetic map of the mouse genome.

High-resolution genetic maps are required for mapping complex traits and for the study of recombination. We report the highest density genetic map yet created for any organism, except humans. Using more than 10,000 single nucleotide polymorphisms evenly spaced across the mouse genome, we have constructed genetic maps for both outbred and inbred mice, and separately for males and females. Recombination rates are highly correlated in outbred and inbred mice, but show relatively low correlation between males and females. Differences between male and female recombination maps and the sequence features associated with recombination are strikingly similar to those observed in humans. Genetic maps are available from http://gscan.well.ox.ac.uk/#genetic_map and as supporting information to this publication.

Animals↗

Integrative genetic analysis of transcription modules: towards filling the gap between genetic loci and inherited traits.

Genetic loci that regulate inherited traits are routinely identified using quantitative trait locus (QTL) mapping methods. However, the genotype-phenotype associations do not provide information on the gene expression program through which the genetic loci regulate the traits. Transcription modules are 'self-consistent regulatory units' and are closely related to the modular components of gene regulatory network [Ihmels, J., Friedlander, G., Bergmann, S., Sarig, O., Ziv, Y. and Barkai, N. (2002) Revealing modular organization in the yeast transcriptional network. Nat. Genet., 31, 370-377; Segal, E., Shapira, M., Regev, A., Pe'er, D., Botstein, D., Koller, D. and Friedman, N. (2003) Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. Nat. Genet., 34, 166-176]. We used genome-wide genotype and gene expression data of a genetic reference population that consists of mice of 32 recombinant inbred strains to identify the transcription modules and the genetic loci regulating them. Twenty-nine transcription modules defined by genetic variations were identified. Statistically significant associations between the transcription modules and 18 classical physiological and behavioral traits were found. Genome-wide interval mapping showed that major QTLs regulating the transcription modules are often co-localized with the QTLs regulating the associated classical traits. The association and the possible co-regulation of the classical trait and transcription module indicate that the transcription module may be involved in the gene pathways connecting the QTL and the classical trait. Our results show that a transcription module may associate with multiple seemingly unrelated classical traits and a classical trait may associate with different modules. Literature mining results provided strong independent evidences for the relations among genes of the transcription modules, genes in the regions of the QTLs regulating the transcription modules and the keywords representing the classical traits.

Animals↗

Genetic networks controlling retinal injury.

PURPOSE: The present study defines genomic loci underlying coordinate changes in gene expression following retinal injury. METHODS: A group of acute phase genes expressed in diverse nervous system tissues was defined by combining microarray results from injury studies from rat retina, brain, and spinal cord. Genomic loci regulating the brain expression of acute phase genes were identified using a panel of BXD recombinant inbred (RI) mouse strains. Candidate upstream regulators within a locus were defined using single nucleotide polymorphism databases and promoter motif databases. RESULTS: The acute phase response of rat retina, brain, and spinal cord was dominated by transcription factors. Three genomic loci control transcript expression of acute phase genes in brains of BXD RI mouse strains. One locus was identified on chromosome 12 and was highly correlated with the expression of classic acute phase genes. Within the locus we identified the inhibitor of DNA binding 2 (Id2) as a candidate upstream regulator. Id2 was upregulated as an acute phase transcript in injury models of rat retina, brain, and spinal cord. CONCLUSIONS: We defined a group of transcriptional changes associated with the retinal acute injury response. Using genetic linkage analysis of natural transcript variation, we identified regulatory loci and candidate regulators that control transcript levels of acute phase genes.

Acute-Phase Proteins↗

An ENU-induced mutation in Rs1h causes disruption of retinal structure and function.

PURPOSE: The 44TNJ mutant mouse was generated by the Tennessee Mouse Genome Consortium (TMGC) using an ENU-based mutagenesis screen to produce recessive mutations that affect the eye and brain. Herein we present its retinal phenotype and genetic basis. METHODS: Fourth generation offspring (G4) and confirmed mutants were examined using slit lamp biomicroscopy, funduscopy, histology, immunohistochemistry, and electroretinography (ERG). 44TNJ mutant mice were crossed to C3BLiA or DBA/2 mice for chromosomal mapping purposes. Linkage analysis by PCR-based microsatellite marker genotyping was used to identify the disease locus. The Rs1h cDNA and its genomic DNA were sequenced directly. RESULTS: The 44TNJ pedigree was the first mutant pedigree identified by the ocular phenotyping domain of the TMGC. Examination of the fundus revealed numerous small and homogeneous intraretinal microflecks in the peripapillary region, which became courser and more irregular in the periphery. Males were typically more affected than females. Histology and immunohistochemistry revealed a disruption of the lamination of the retina, particularly at both margins of the outer nuclear layer, along with reduced calbindin immunostaining. ERG analyses revealed reduced amplitudes of both a-waves and b-waves. Linkage analysis mapped the 44TNJ mutation to the X chromosome close to the marker DXMit117. Sequence analysis of the positional candidate gene Rs1h revealed a T->C exchange at the second base of intron 2 of the Rs1h gene. CONCLUSIONS: We have generated and characterized a mutant mouse line that was produced using ENU-based mutagenesis. The 44TNJ pedigree manifests with photoreceptor dysfunction and concurrent structural and functional aberrations at the post-receptoral level. Genetic analysis revealed a mutation in Rs1h, making this the first murine model of X-linked retinoschisis in which the gene is expressed.

Alkylating Agents↗

Computational, integrative, and comparative methods for the elucidation of genetic coexpression networks.

Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively co-regulated genes and their annotation using gene ontology analysis and cis-regulatory element discovery. The causal basis for co-regulation is detected through the use of quantitative trait locus mapping.

Journal Article↗

Quantitative trait locus analysis using recombinant inbred intercrosses: theoretical and empirical considerations.

We describe a new approach, called recombinant inbred intercross (RIX) mapping, that extends the power of recombinant inbred (RI) lines to provide sensitive detection of quantitative trait loci (QTL) responsible for complex genetic and nongenetic interactions. RIXs are generated by producing F1 hybrids between all or a subset of parental RI lines. By dramatically extending the number of unique, reproducible genomes, RIXs share some of the best properties of both the parental RI and F2 mapping panels. These attributes make the RIX method ideally suited for experiments requiring analysis of multiple parameters, under different environmental conditions and/or temporal sampling. However, since any pair of RIX genomes shares either one or no parental RIs, this cross introduces an unusual population structure requiring special computational approaches for analysis. Herein, we propose an efficient statistical procedure for QTL mapping with RIXs and describe a novel empirical permutation procedure to assess genome-wide significance. This procedure will also be applicable to diallel crosses. Extensive simulations using strain distribution patterns from CXB, AXB/BXA, and BXD mouse RI lines show the theoretical power of the RIX approach and the analysis of CXB RIXs demonstrates the limitations of this procedure when using small RI panels.

Animals↗