We have produced yeast artificial chromosome (YAC) transgenic mice expressing normal (YAC18) and mutant (YAC46 and YAC72) huntingtin (htt) in a developmental and tissue-specific manner identical to that observed in Huntington's disease (HD). YAC46 and YAC72 mice show early electrophysiological abnormalities, indicating cytoplasmic dysfunction prior to observed nuclear inclusions or neurodegeneration. By 12 months of age, YAC72 mice have a selective degeneration of medium spiny neurons in the lateral striatum associated with the translocation of N-terminal htt fragments to the nucleus. Neurodegeneration can be present in the absence of macro- or microaggregates, clearly showing that aggregates are not essential to initiation of neuronal death. These mice demonstrate that initial neuronal cytoplasmic toxicity is followed by cleavage of htt, nuclear translocation of htt N-terminal fragments, and selective neurodegeneration.

The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography–Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications.

A mouse model for Down syndrome, Ts1Cje, has been developed. This model has made possible a step in the genetic dissection of the learning, behavioral, and neurological abnormalities associated with segmental trisomy for the region of mouse chromosome 16 homologous with the socalled ''Down syndrome region'' of human chromosome segment 21q22. Tests of learning in the Morris water maze and assessment of spontaneous locomotor activity reveal distinct learning and behavioral abnormalities, some of which are indicative of hippocampal dysfunction. The triplicated region in Ts1Cje, from Sod1 to Mx1, is smaller than that in Ts65Dn, another segmental trisomy 16 mouse, and the learning deficits in Ts1Cje are less severe than those in Ts65Dn. In addition, degeneration of basal forebrain cholinergic neurons, which was observed in Ts65Dn, was absent in Ts1Cje.

Inverse source reconstruction is the most challenging aspect of bioluminescence tomography (BLT) because of its ill-posedness. Although many efforts have been devoted to this problem, so far, there is no generally accepted method. Due to the ill-posedness property of the BLT inverse problem, the regularization method plays an important role in the inverse reconstruction. In this paper, six reconstruction algorithms based on l p regularization are surveyed. The effects of the permissible source region, measurement noise, optical properties, tissue specificity and source locations on the performance of the reconstruction algorithms are investigated using a series of single source experiments. In order to further inspect the performance of the reconstruction algorithms, we present the double sources and the in vivo mouse experiments to study their resolution ability and potential for a practical heterogeneous mouse experiment. It is hoped to provide useful guidance on algorithm development and application in the related fields.

Using Down syndrome as a model for complex trait analysis, we sought to identify loci from chromosome 21q22.2 which, when present in an extra dose, contribute to learning abnormalities. We generated low-copy-number transgenic mice, containing four different yeast artificial chromosomes (YACs) that together cover approximately 2 megabases (Mb) of contiguous DNA from 21q22.2. We subjected independent lines derived from each of these YAC transgenes to a series of behavioural and learning assays. Two of the four YACs caused defects in learning and memory in the transgenic animals, while the other two YACs had no effect. The most severe defects were caused by a 570-kb YAC; the interval responsible for these defects was narrowed to a 180-kb critical region as a consequence of YAC fragmentation. This region contains the human homologue of a Drosophila gene, minibrain, and strongly implicates it in learning defects associated with Down syndrome.