Arshad H. Khan

Mitochondrial Dysfunction, Oxidative Stress, and Apoptosis Revealed by Proteomic and Transcriptomic Analyses of the Striata in Two Mouse Models of Parkinson’s Disease

The molecular mechanisms underlying the changes in the nigrostriatal pathway in Parkinsons disease (PD) are not completely understood. Here, we use mass spectrometry and microarrays to study the proteomic and transcriptomic changes in the striatum of two mouse models of PD, induced by the distinct neurotoxins 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and methamphetamine (METH). Proteomic analyses resulted in the identification and relative quantification of 912 proteins with two or more unique peptides and 86 proteins with significant abundance changes following neurotoxin treatment. Similarly, microarray analyses revealed 181 genes with significant changes in mRNA, following neurotoxin treatment. The combined protein and gene list provides a clearer picture of the potential mechanisms underlying neurodegeneration observed in PD. Functional analysis of this combined list revealed a number of significant categories, including mitochondrial dysfunction, oxidative stress response, and apoptosis. These results constitute one of the largest descriptive data sets integrating protein and transcript changes for these neurotoxin models with many similar end point phenotypes but distinct mechanisms.

Gene networks associated with conditional fear in mice identified using a systems genetics approach

BackgroundOur understanding of the genetic basis of learning and memory remains shrouded in mystery. To explore the genetic networks governing the biology of conditional fear, we used a systems genetics approach to analyze a hybrid mouse diversity panel (HMDP) with high mapping resolution.ResultsA total of 27 behavioral quantitative trait loci were mapped with a false discovery rate of 5%. By integrating fear phenotypes, transcript profiling data from hippocampus and striatum and also genotype information, two gene co-expression networks correlated with context-dependent immobility were identified. We prioritized the key markers and genes in these pathways using intramodular connectivity measures and structural equation modeling. Highly connected genes in the context fear modules included Psmd6, Ube2a and Usp33, suggesting an important role for ubiquitination in learning and memory. In addition, we surveyed the architecture of brain transcript regulation and demonstrated preservation of gene co-expression modules in hippocampus and striatum, while also highlighting important differences. Rps15a, Kif3a, Stard7, 6330503K22RIK, and Plvap were among the individual genes whose transcript abundance were strongly associated with fear phenotypes.ConclusionApplication of our multi-faceted mapping strategy permits an increasingly detailed characterization of the genetic networks underlying behavior.

A genetic screen for novel behavioral mutations in mice

A genetic screen using mice was performed to identify dominant loci affecting behavior. Mice were mutagenized with ENU, then bred to examine their G1 offspring for behavioral abnormalities. Potentially mutant G1 pups were screened through a variety of behavioral assays, including tests of learning and memory, sensorimotor gating, fear and anxiety, nociception (pain perception) and locomotor activity. Mice falling outside the normal performance distribution in these tests were considered potential behavioral mutants and were bred for further analysis. Outliers included both animals with very discrete defects and animals with abnormal performance across a range of tests. To date, we have identified two confirmed mutants affecting sensorimotor gating. These results provide further impetus for the use of random mutagenesis screens as a tool for dissecting the genetic basis of brain and behavior.

A genome-wide panel of congenic mice reveals widespread epistasis of behavior quantitative trait loci

Understanding the genetics of behavioral variation remains a fascinating but difficult problem with considerable theoretical and practical implications. We used the genome-tagged mice (GTM) and an extensive test battery of well-validated behavioral assays to scan the genome for behavioral quantitative trait loci (QTLs). The GTM are a panel of ‘speed congenic’ mice consisting of over 60 strains spanning the entire autosomal genome. Each strain harbors a small (∼23 cM) DBA/2J donor segment on a uniform C57BL/6J background. The panel allows for mapping to regions as small as 5 cM and provides a powerful new tool for increasing mapping power and replicability in the analysis of QTLs. A total of 97 loci were mapped for a variety of complex behavioral traits including hyperactivity, anxiety, prepulse inhibition, avoidance and conditional fear. A larger number of loci were recovered than generally attained from standard mapping crosses. In addition, a surprisingly high proportion of loci, 63%, showed phenotypes unlike either of the parental strains. These data suggest that epistasis decreases sensitivity of locus detection in traditional crosses and demonstrate the utility of the GTM for mapping complex behavioral traits with high sensitivity and precision.

Fine mapping of regulatory loci for mammalian gene expression using radiation hybrids.

We mapped regulatory loci for nearly all protein-coding genes in mammals using comparative genomic hybridization and expression array measurements from a panel of mouse–hamster radiation hybrid cell lines. The large number of breaks in the mouse chromosomes and the dense genotyping of the panel allowed extremely sharp mapping of loci. As the regulatory loci result from extra gene dosage, we call them copy number expression quantitative trait loci, or ceQTLs. The −2log10P support interval for the ceQTLs was <150 kb, containing an average of <2–3 genes. We identified 29,769 trans ceQTLs with −log10P > 4, including 13 hotspots each regulating >100 genes in trans. Further, this work identifies 2,761 trans ceQTLs harboring no known genes, and provides evidence for a mode of gene expression autoregulation specific to the X chromosome.

High-resolution voxelation mapping of human and rodent brain gene expression

Voxelation allows high-throughput acquisition of multiple volumetric images of brain gene expression, similar to those obtained from biomedical imaging systems. To obtain these images, the method employs analysis of spatially registered voxels (cubes). For creation of high-resolution maps using voxelation, relatively small voxel sizes are necessary and instruments will be required for semiautomated harvesting of such voxels. Here, we describe two devices that allow spatially registered harvesting of voxels from the human and rodent brain, giving linear resolutions of 3.3 and 1 mm, respectively. Gene expression patterns obtained using these devices showed good agreement with known expression patterns. The voxelation instruments and their future iterations represent a valuable approach to the genome scale acquisition of gene expression patterns in the human and rodent brain.

Effects of genome-wide copy number variation on expression in mammalian cells

BackgroundThere is only a limited understanding of the relation between copy number and expression for mammalian genes. We fine mapped cis and trans regulatory loci due to copy number change for essentially all genes using a human-hamster radiation hybrid (RH) panel. These loci are called copy number expression quantitative trait loci (ceQTLs).ResultsUnexpected findings from a previous study of a mouse-hamster RH panel were replicated. These findings included decreased expression as a result of increased copy number for 30% of genes and an attenuated relationship between expression and copy number on the X chromosome suggesting an Xist independent form of dosage compensation. In a separate glioblastoma dataset, we found conservation of genes in which dosage was negatively correlated with gene expression. These genes were enriched in signaling and receptor activities. The observation of attenuated X-linked gene expression in response to increased gene number was also replicated in the glioblastoma dataset. Of 523 gene deserts of size > 600 kb in the human RH panel, 325 contained trans ceQTLs with -log10P > 4.1. Recently discovered genes, ultra conserved regions, noncoding RNAs and microRNAs explained only a small fraction of the results, suggesting a substantial portion of gene deserts harbor as yet unidentified functional elements.ConclusionRadiation hybrids are a useful tool for high resolution mapping of cis and trans loci capable of affecting gene expression due to copy number change. Analysis of two independent radiation hybrid panels show agreement in their findings and may serve as a discovery source for novel regulatory loci in noncoding regions of the genome.

Screening reveals conserved and nonconserved transcriptional regulatory elements including an E3/E4 allele-dependent APOE coding region enhancer.

We performed an unbiased experimental search for enhancers and silencers in a 153-kb region containing the human apolipoprotein (APO) E/C1/C4/C2 gene cluster using shotgun cloning into a luciferase vector. A continuum of transcriptional effect sizes was observed, possibly explaining the limited success of bioinformatics in identifying regulatory regions. We identified nine statistically significant enhancers and five silencers functional in either liver or astrocyte cells, including two previously known enhancers. Only two of the fourteen elements contained conserved noncoding sequences. Within the coding sequence of the APOE gene we identified an enhancer for the E4 allele associated with Alzheimers disease, but not E3. The single nucleotide polymorphism (SNP) causing the E4/E3 amino acid substitution was responsible for these variations, potentially explaining the higher expression levels of E4. Our results suggest a wider variety of mammalian transcriptional regulatory sequences than is currently recognized and that these may include coding region SNPs.

Identifying Loci for Behavioral Traits Using Genome-Tagged Mice

Identification of behavioral loci through complex trait mapping remains a widely employed approach but suffers from poor gene localization and low replicability. Genome‐tagged mice (GTMs) are overlapping sets of congenic strains spanning the whole genome and offer the possibilities of superior mapping power and reproducibility. In this study, three GTM strains each consisting of an average ∼27 cM DBA/2J genomic intervals introgressed onto a C57BL/6J background were employed for localization of behavioral traits. These GTMs were chosen because the corresponding chromosomal regions had been previously identified as containing loci for learning and memory. Analysis of the GTMs allowed confirmation of the learning and memory loci, and one on chromosome 3 was in addition fine mapped to an 8.8‐cM region of overlap between two of the GTMs. Moreover, loci for prepulse inhibition of the startle response, acoustic startle response, and spontaneous locomotor activity were also mapped. These results suggest that the GTMs should be a valuable resource for mapping and confirmation of loci contributing to complex behavioral traits in the mouse.

Mapping Behavioral Traits by Use of Genome-Tagged Mice

OBJECTIVE Complex trait mapping has been widely used to analyze the genetics of behavior. However, the approach has some disadvantages, including poor gene localization and low replicability. Genome-tagged mice (GTMs) are sets of congenic mouse strains that span the entire mouse genome and are a promising reagent for localization of genes contributing to behavior. METHODS In order to map behavioral loci of interest, a GTM was investigated in which the middle region of Chromosome 1 from DBA/2J was introgressed onto a C57BL/6J background. The GTM was analyzed for behaviors related to sensorimotor gating, anxiety, depression, pain sensitivity, and learning and memory. RESULTS The GTM was found to harbor a locus contributing to learning and memory, replicating results from complex trait analysis. CONCLUSIONS The GTMs should be a valuable resource for mapping and confirmation of loci contributing to complex behavioral traits in the mouse, with ultimate implications for human genomic-based research, as well.