A comparison of whole-genome shotgun-derived mouse chromosome 16 and the human genome

The diploid genome sequence of an individual human

Presented here is a genome sequence of an individual human. It was produced from approximately 32 million random DNA fragments, sequenced by Sanger dideoxy technology and assembled into 4,528 scaffolds, comprising 2,810 million bases (Mb) of contiguous sequence with approximately 7.5-fold coverage for any given region. We developed a modified version of the Celera assembler to facilitate the identification and comparison of alternate alleles within this individual diploid genome. Comparison of this genome and the National Center for Biotechnology Information human reference assembly revealed more than 4.1 million DNA variants, encompassing 12.3 Mb. These variants (of which 1,288,319 were novel) included 3,213,401 single nucleotide polymorphisms (SNPs), 53,823 block substitutions (2-206 bp), 292,102 heterozygous insertion/deletion events (indels)(1-571 bp), 559,473 homozygous indels (1-82,711 bp), 90 inversions, as well as numerous segmental duplications and copy number variation regions. Non-SNP DNA variation accounts for 22% of all events identified in the donor, however they involve 74% of all variant bases. This suggests an important role for non-SNP genetic alterations in defining the diploid genome structure. Moreover, 44% of genes were heterozygous for one or more variants. Using a novel haplotype assembly strategy, we were able to span 1.5 Gb of genome sequence in segments >200 kb, providing further precision to the diploid nature of the genome. These data depict a definitive molecular portrait of a diploid human genome that provides a starting point for future genome comparisons and enables an era of individualized genomic information.

Detecting polymorphic regions in Arabidopsis thaliana with resequencing microarrays

Whole-genome oligonucleotide resequencing arrays have allowed the comprehensive discovery of single nucleotide polymorphisms (SNPs) in eukaryotic genomes of moderate to large size. With this technology, the detection rate for isolated SNPs is typically high. However, it is greatly reduced when other polymorphisms are located near a SNP as multiple mismatches inhibit hybridization to arrayed oligonucleotides. Contiguous tracts of suppressed hybridization therefore typify polymorphic regions (PRs) such as clusters of SNPs or deletions. We developed a machine learning method, designated margin-based prediction of polymorphic regions (mPPR), to predict PRs from resequencing array data. Conceptually similar to hidden Markov models, the method is trained with discriminative learning techniques related to support vector machines, and accurately identifies even very short polymorphic tracts (<10 bp). We applied this method to resequencing array data previously generated for the euchromatic genomes of 20 strains (accessions) of the best-characterized plant, Arabidopsis thaliana. Nonredundantly, 27% of the genome was included within the boundaries of PRs predicted at high specificity ( approximately 97%). The resulting data set provides a fine-scale view of polymorphic sequences in A. thaliana; patterns of polymorphism not apparent in SNP data were readily detected, especially for noncoding regions. Our predictions provide a valuable resource for evolutionary genetic and functional studies in A. thaliana, and our method is applicable to similar data sets in other species. More broadly, our computational approach can be applied to other segmentation tasks related to the analysis of genomic variation.

An imputed genotype resource for the laboratory mouse

We have created a high-density SNP resource encompassing 7.87 million polymorphic loci across 49 inbred mouse strains of the laboratory mouse by combining data available from public databases and training a hidden Markov model to impute missing genotypes in the combined data. The strong linkage disequilibrium found in dense sets of SNP markers in the laboratory mouse provides the basis for accurate imputation. Using genotypes from eight independent SNP resources, we empirically validated the quality of the imputed genotypes and demonstrated that they are highly reliable for most inbred strains. The imputed SNP resource will be useful for studies of natural variation and complex traits. It will facilitate association study designs by providing high-density SNP genotypes for large numbers of mouse strains. We anticipate that this resource will continue to evolve as new genotype data become available for laboratory mouse strains. The data are available for bulk download or query at http://cgd.jax.org /.

Applying gene expression, proteomics and single-nucleotide polymorphism analysis for complex trait gene identification

Previous quantitative trait locus (QTL) analysis of an intercross involving the inbred mouse strains NZB/BlNJ and SM/J revealed QTL for a variety of complex traits. Many QTL have large intervals containing hundreds of genes, and methods are needed to rapidly sort through these genes for probable candidates. We chose nine QTL: the three most significant for high-density lipoprotein (HDL) cholesterol, gallstone formation, and obesity. We searched for candidate genes using three different approaches: mRNA microarray gene expression technology to assess >45,000 transcripts, publicly available SNPs to locate genes that are not identical by descent and that contain nonsynonymous coding differences, and a mass-spectrometry-based proteomics technology to interrogate nearly 1000 proteins for differential expression in the liver of the two parental inbred strains. This systematic approach reduced the number of candidate genes within each QTL from hundreds to a manageable list. Each of the three approaches selected candidates that the other two approaches missed. For example, candidate genes such as Apoa2 and Acads had differential protein levels although the mRNA levels were similar. We conclude that all three approaches are important and that focusing on a single approach such as mRNA expression may fail to identify a QTL gene.

Fine haplotype structure of a chromosome 17 region in the laboratory and wild mouse

Extensive linkage disequilibrium among classical laboratory strains represents an obstacle in the high-resolution haplotype mapping of mouse quantitative trait loci (QTL). To determine the potential of wild-derived mouse strains for fine QTL mapping, we constructed a haplotype map of a 250-kb region of the t-complex on chromosome 17 containing the Hybrid sterility 1 (Hst1) gene. We resequenced 33 loci from up to 80 chromosomes of five mouse (sub)species. Trans-species single-nucleotide polymorphisms (SNPs) were rare between Mus m. musculus (Mmmu) and Mus m. domesticus (Mmd). The haplotypes in Mmmu and Mmd differed and therefore strains from these subspecies should not be combined for haplotype-associated mapping. The haplotypes of t-chromosomes differed from all non-t Mmmu and Mmd haplotypes. Half of the SNPs and SN indels but only one of seven longer rearrangements found in classical laboratory strains were useful for haplotype mapping in the wild-derived M. m. domesticus. The largest Mmd haplotype block contained three genes of a highly conserved synteny. The lengths of the haplotype blocks deduced from 36 domesticus chromosomes were in tens of kilobases, suggesting that the wild-derived Mmd strains are suitable for fine interval-specific mapping.

Systems biology and its potential role in radiobiology

About a century ago, Conrad Röentgen discovered X-rays, and Henri Becquerel discovered a new phenomenon, which Marie and Pierre Curie later coined as radio-activity. Since their seminal work, we have learned much about the physical properties of radiation and its effects on living matter. Alas, the more we discover, the more we appreciate the complexity of the biological processes that are triggered by radiation exposure and eventually lead (or do not lead) to disease. Equipped with modern biological methods of high-throughput experimentation, imaging, and vastly increased computational prowess, we are now entering an era where we can piece some of the multifold aspects of radiation exposure and its sequelae together, and develop a more systemic understanding of radiogenic effects such as radio-carcinogenesis than has been possible in the past. It is evident from the complexity of even the known processes that such an understanding can only be gained if it is supported by mathematical models. At this point, the construction of comprehensive models is hampered both by technical inadequacies and a paucity of appropriate data. Nonetheless, some initial steps have been taken already and the generally increased interest in systems biology may be expected to speed up future progress. In this context, we discuss in this article examples of relatively small, yet very useful models that elucidate selected aspects of the effects of exposure to ionizing radiation and may shine a light on the path before us.

SeqAn an efficient, generic C++ library for sequence analysis

Background

The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome [1] would not have been possible without advanced assembly algorithms. However, owing to the high speed of technological progress and the urgent need for bioinformatics tools, there is a widening gap between state-of-the-art algorithmic techniques and the actual algorithmic components of tools that are in widespread use.

Results

To remedy this trend we propose the use of SeqAn, a library of efficient data types and algorithms for sequence analysis in computational biology. SeqAn comprises implementations of existing, practical state-of-the-art algorithmic components to provide a sound basis for algorithm testing and development. In this paper we describe the design and content of SeqAn and demonstrate its use by giving two examples. In the first example we show an application of SeqAn as an experimental platform by comparing different exact string matching algorithms. The second example is a simple version of the well-known MUMmer tool rewritten in SeqAn. Results indicate that our implementation is very efficient and versatile to use.

Conclusion

We anticipate that SeqAn greatly simplifies the rapid development of new bioinformatics tools by providing a collection of readily usable, well-designed algorithmic components which are fundamental for the field of sequence analysis. This leverages not only the implementation of new algorithms, but also enables a sound analysis and comparison of existing algorithms.

Gene duplication and paleopolyploidy in soybean and the implications for whole genome sequencing

BACKGROUND

Soybean, Glycine max (L.) Merr., is a well documented paleopolyploid. What remains relatively under characterized is the level of sequence identity in retained homeologous regions of the genome. Recently, the Department of Energy Joint Genome Institute and United States Department of Agriculture jointly announced the sequencing of the soybean genome. One of the initial concerns is to what extent sequence identity in homeologous regions would have on whole genome shotgun sequence assembly.

RESULTS

Seventeen BACs representing approximately 2.03 Mb were sequenced as representative potential homeologous regions from the soybean genome. Genetic mapping of each BAC shows that 11 of the 20 chromosomes are represented. Sequence comparisons between homeologous BACs shows that the soybean genome is a mosaic of retained paleopolyploid regions. Some regions appear to be highly conserved while other regions have diverged significantly. Large-scale "batch" reassembly of all 17 BACs combined showed that even the most homeologous BACs with upwards of 95% sequence identity resolve into their respective homeologous sequences. Potential assembly errors were generated by tandemly duplicated pentatricopeptide repeat containing genes and long simple sequence repeats. Analysis of a whole-genome shotgun assembly of 80,000 randomly chosen JGI-DOE sequence traces reveals some new soybean-specific repeat sequences.

CONCLUSION

This analysis investigated both the structure of the paleopolyploid soybean genome and the potential effects retained homeology will have on assembling the whole genome shotgun sequence. Based upon these results, homeologous regions similar to those characterized here will not cause major assembly issues.

Gene duplication and paleopolyploidy in soybean and the implications for whole genome sequencing

BACKGROUND

Soybean, Glycine max (L.) Merr., is a well documented paleopolyploid. What remains relatively under characterized is the level of sequence identity in retained homeologous regions of the genome. Recently, the Department of Energy Joint Genome Institute and United States Department of Agriculture jointly announced the sequencing of the soybean genome. One of the initial concerns is to what extent sequence identity in homeologous regions would have on whole genome shotgun sequence assembly.

RESULTS

Seventeen BACs representing approximately 2.03 Mb were sequenced as representative potential homeologous regions from the soybean genome. Genetic mapping of each BAC shows that 11 of the 20 chromosomes are represented. Sequence comparisons between homeologous BACs shows that the soybean genome is a mosaic of retained paleopolyploid regions. Some regions appear to be highly conserved while other regions have diverged significantly. Large-scale "batch" reassembly of all 17 BACs combined showed that even the most homeologous BACs with upwards of 95% sequence identity resolve into their respective homeologous sequences. Potential assembly errors were generated by tandemly duplicated pentatricopeptide repeat containing genes and long simple sequence repeats. Analysis of a whole-genome shotgun assembly of 80,000 randomly chosen JGI-DOE sequence traces reveals some new soybean-specific repeat sequences.

CONCLUSION

This analysis investigated both the structure of the paleopolyploid soybean genome and the potential effects retained homeology will have on assembling the whole genome shotgun sequence. Based upon these results, homeologous regions similar to those characterized here will not cause major assembly issues.

A sequence-based variation map of 8.27 million SNPs in inbred mouse strains

A dense map of genetic variation in the laboratory mouse genome will provide insights into the evolutionary history of the species and lead to an improved understanding of the relationship between inter-strain genotypic and phenotypic differences. Here we resequence the genomes of four wild-derived and eleven classical strains. We identify 8.27 million high-quality single nucleotide polymorphisms (SNPs) densely distributed across the genome, and determine the locations of the high (divergent subspecies ancestry) and low (common subspecies ancestry) SNP-rate intervals for every pairwise combination of classical strains. Using these data, we generate a genome-wide haplotype map containing 40,898 segments, each with an average of three distinct ancestral haplotypes. For the haplotypes in the classical strains that are unequivocally assigned ancestry, the genetic contributions of the Mus musculus subspecies--M. m. domesticus, M. m. musculus, M. m. castaneus and the hybrid M. m. molossinus--are 68%, 6%, 3% and 10%, respectively; the remaining 13% of haplotypes are of unknown ancestral origin. The considerable regional redundancy of the SNP data will facilitate imputation of the majority of these genotypes in less-densely typed classical inbred strains to provide a complete view of variation in additional strains.

Moving toward a system genetics view of disease

Testing hundreds of thousands of DNA markers in human, mouse, and other species for association to complex traits like disease is now a reality. However, information on how variations in DNA impact complex physiologic processes flows through transcriptional and other molecular networks. In other words, DNA variations impact complex diseases through the perturbations they cause to transcriptional and other biological networks, and these molecular phenotypes are intermediate to clinically defined disease. Because it is also now possible to monitor transcript levels in a comprehensive fashion, integrating DNA variation, transcription, and phenotypic data has the potential to enhance identification of the associations between DNA variation and diseases like obesity and diabetes, as well as characterize those parts of the molecular networks that drive these diseases. Toward that end, we review methods for integrating expression quantitative trait loci (eQTLs), gene expression, and clinical data to infer causal relationships among gene expression traits and between expression and clinical traits. We further describe methods to integrate these data in a more comprehensive manner by constructing coexpression gene networks that leverage pairwise gene interaction data to represent more general relationships. To infer gene networks that capture causal information, we describe a Bayesian algorithm that further integrates eQTLs, expression, and clinical phenotype data to reconstruct whole-gene networks capable of representing causal relationships among genes and traits in the network. These emerging network approaches, aimed at processing high-dimensional biological data by integrating data from multiple sources, represent some of the first steps in statistical genetics to identify multiple genetic perturbations that alter the states of molecular networks and that in turn push systems into disease states. Evolving statistical procedures that operate on networks will be critical to extracting information related to complex phenotypes like disease, as research goes beyond a single-gene focus. The early successes achieved with the methods described herein suggest that these more integrative genomics approaches to dissecting disease traits will significantly enhance the identification of key drivers of disease beyond what could be achieved by genetic association studies alone.

Comparison of vascular relaxation, lipolysis and glucose uptake by peroxisome proliferator-activated receptor-gamma activation in +db/+m and +db/+db mice

In this study, we determined the in vitro effect of peroxisome proliferator-activated receptor-gamma (PPAR-gamma) activation on the aortic relaxation, lipolysis and insulin-induced [(3)H]-glucose uptake of the abdominal (omental) adipocytes of the non-diabetic (+db/+m) and obese/diabetic (+db/+db) mice. The expression of PPAR-gamma (mRNA and protein) in aorta and adipose tissues was evaluated and compared. Cumulative application of ciglitazone, pioglitazone and troglitazone (PPAR-gamma agonists) caused a concentration-dependent aortic relaxation (sensitive to 2-chloro-5-nitro-N-phenylbenzamide (GW9662) (1 microM, a selective PPAR-gamma antagonist) and N(omega)-nitro-l-arginine methyl ester (l-NAME) (20 microM, a nitric oxide synthase inhibitor)) with a maximum relaxation of approximately 30% (3 microM) in +db/+m mice, whereas no relaxation was observed in +db/+db mice. All PPAR-gamma agonists examined did not alter the basal lipolysis of both species, but forskolin caused a concentration-dependent lipolysis, with a greater magnitude observed in +db/+m mice. Insulin (0.1 and 1 microM) caused an enhancement of [(3)H]-glucose uptake into adipocytes with a greater magnitude in +db/+m mice. In contrast, none of the PPAR-gamma agonists tested (0.1, 1 and 10 microM) altered the basal and the insulin (0.1 microM)-induced [(3)H]-glucose uptake into adipocytes of both species. In addition, there was no difference in PPAR-gamma expression (mRNA and protein) in the aorta and adipose tissues between the species. In conclusion, our results demonstrate that PPAR-gamma is present in the abdominal (omental) adipose tissue and thoracic aorta. An acute activation of PPAR-gamma produced a small ( approximately 30%) aortic relaxation (nitric oxide/endothelium-dependent) of +db/+m mice. However, all PPAR-gamma agonists examined have no acute effect on lipolysis and the insulin-induced glucose uptake into adipocytes of both +db/+m and +db/+db mice.

Diversifying selection and host adaptation in two endosymbiont genomes

BACKGROUND

The endosymbiont Wolbachia pipientis infects a broad range of arthropod and filarial nematode hosts. These diverse associations form an attractive model for understanding host:symbiont coevolution. Wolbachia's ubiquity and ability to dramatically alter host reproductive biology also form the foundation of research strategies aimed at controlling insect pests and vector-borne disease. The Wolbachia strains that infect nematodes are phylogenetically distinct, strictly vertically transmitted, and required by their hosts for growth and reproduction. Insects in contrast form more fluid associations with Wolbachia. In these taxa, host populations are most often polymorphic for infection, horizontal transmission occurs between distantly related hosts, and direct fitness effects on hosts are mild. Despite extensive interest in the Wolbachia system for many years, relatively little is known about the molecular mechanisms that mediate its varied interactions with different hosts. We have compared the genomes of the Wolbachia that infect Drosophila melanogaster, wMel and the nematode Brugia malayi, wBm to that of an outgroup Anaplasma marginale to identify genes that have experienced diversifying selection in the Wolbachia lineages. The goal of the study was to identify likely molecular mechanisms of the symbiosis and to understand the nature of the diverse association across different hosts.

RESULTS

The prevalence of selection was far greater in wMel than wBm. Genes contributing to DNA metabolism, cofactor biosynthesis, and secretion were positively selected in both lineages. In wMel there was a greater emphasis on DNA repair, cell division, protein stability, and cell envelope synthesis.

CONCLUSION

Secretion pathways and outer surface protein encoding genes are highly affected by selection in keeping with host:parasite theory. If evidence of selection on various cofactor molecules reflects possible provisioning, then both insect as well as nematode Wolbachia may be providing substances to hosts. Selection on cell envelope synthesis, DNA replication and repair machinery, heat shock, and two component switching suggest strategies insect Wolbachia may employ to cope with diverse host and intra-host environments.

The genetic landscape of type 2 diabetes in mice

Inbred mouse strains provide genetic diversity comparable to that of the human population. Like humans, mice have a wide range of diabetes-related phenotypes. The inbred mouse strains differ in the response of their critical physiological functions, such as insulin sensitivity, insulin secretion, beta-cell proliferation and survival, and fuel partitioning, to diet and obesity. Most of the critical genes underlying these differences have not been identified, although many loci have been mapped. The dramatic improvements in genomic and bioinformatics resources are accelerating the pace of gene discovery. This review describes how mouse genetics can be used to discover diabetes-related genes, summarizes how the mouse strains differ in their diabetes-related phenotypes, and describes several examples of how loci identified in the mouse may directly relate to human diabetes.

Mouse SNP Miner: an annotated database of mouse functional single nucleotide polymorphisms

Background

The mapping of quantitative trait loci in rat and mouse has been extremely successful in identifying chromosomal regions associated with human disease-related phenotypes. However, identifying the specific phenotype-causing DNA sequence variations within a quantitative trait locus has been much more difficult. The recent availability of genomic sequence from several mouse inbred strains (including C57BL/6J, 129X1/SvJ, 129S1/SvImJ, A/J, and DBA/2J) has made it possible to catalog DNA sequence differences within a quantitative trait locus derived from crosses between these strains. However, even for well-defined quantitative trait loci (<10 Mb) the identification of candidate functional DNA sequence changes remains challenging due to the high density of sequence variation between strains.

Description

To help identify functional DNA sequence variations within quantitative trait loci we have used the Ensembl annotated genome sequence to compile a database of mouse single nucleotide polymorphisms (SNPs) that are predicted to cause missense, nonsense, frameshift, or splice site mutations (available at ). For missense mutations we have used the PolyPhen and PANTHER algorithms to predict whether amino acid changes are likely to disrupt protein function.

Conclusion

We have developed a database of mouse SNPs predicted to cause missense, nonsense, frameshift, and splice-site mutations. Our analysis revealed that 20% and 14% of missense SNPs are likely to be deleterious according to PolyPhen and PANTHER, respectively, and 6% are considered deleterious by both algorithms. The database also provides gene expression and functional annotations from the Symatlas, Gene Ontology, and OMIM databases to further assess candidate phenotype-causing mutations. To demonstrate its utility, we show that Mouse SNP Miner successfully finds a previously identified candidate SNP in the taste receptor, Tas1r3, that underlies sucrose preference in the C57BL/6J strain. We also use Mouse SNP Miner to derive a list of candidate phenotype-causing mutations within a previously uncharacterized QTL for response to morphine in the 129/Sv strain.

Searching the genomes of inbred mouse strains for incompatibilities that reproductively isolate their wild relatives

Identification of the genes that underlie reproductive isolation provides important insights into the process of speciation. According to the Dobzhansky-Muller model, these genes suffer disrupted interactions in hybrids due to independent divergence in separate populations. In hybrid populations, natural selection acts to remove the deleterious heterospecific combinations that cause these functional disruptions. When selection is strong, this process can maintain multilocus associations, primarily between conspecific alleles, providing a signature that can be used to locate incompatibilities. We applied this logic to populations of house mice that were formed by hybridization involving two species that show partial reproductive isolation, Mus domesticus and Mus musculus. Using molecular markers likely to be informative about species ancestry, we scanned the genomes of 1) classical inbred strains and 2) recombinant inbred lines for pairs of loci that showed extreme linkage disequilibria. By using the same set of markers, we identified a list of locus pairs that displayed similar patterns in both scans. These genomic regions may contain genes that contribute to reproductive isolation between M. domesticus and M. musculus. This hypothesis can now be tested using laboratory crosses and surveys of introgression in the wild.

Sequence analyses to study the evolutionary history and cis-regulatory elements of Hedgehog genes

Sequence analysis and comparative genomics are powerful tools to gain knowledge on multiple aspects of gene and protein regulation and function. These have been widely used to understand the evolutionary history and the biochemistry of Hedgehog (Hh) proteins, and the molecular control of Hedgehog gene expression. Here, we report on some of the methods available to retrieve protein and genomic sequences. We describe how protein sequence comparison can produce information on the evolutionary history of Hh proteins. Moreover, we describe the use of genomic sequence analysis including phylogenetic footprinting and transcription factor-binding site search tools, techniques that allow for the characterization of cis-regulatory elements of developmental genes such as the Hedgehog genes.

Sequencing of a new target genome: the Pediculus humanus humanus (Phthiraptera: Pediculidae) genome project

The human body louse, Pediculus humanus humanus (L.), and the human head louse, Pediculus humanus capitis, belong to the hemimetabolous order Phthiraptera. The body louse is the primary vector that transmits the bacterial agents of louse-borne relapsing fever, trench fever, and epidemic typhus. The genomes of the bacterial causative agents of several of these aforementioned diseases have been sequenced. Thus, determining the body louse genome will enhance studies of host-vector-pathogen interactions. Although not important as a major disease vector, head lice are of major social concern. Resistance to traditional pesticides used to control head and body lice have developed. It is imperative that new molecular targets be discovered for the development of novel compounds to control these insects. No complete genome sequence exists for a hemimetabolous insect species primarily because hemimetabolous insects often have large (2000 Mb) to very large (up to 16,300 Mb) genomes. Fortuitously, we determined that the human body louse has one of the smallest genome sizes known in insects, suggesting it may be a suitable choice as a minimal hemimetabolous genome in which many genes have been eliminated during its adaptation to human parasitism. Because many louse species infest birds and mammals, the body louse genome-sequencing project will facilitate studies of their comparative genomics. A 6-8X coverage of the body louse genome, plus sequenced expressed sequence tags, should provide the entomological, evolutionary biology, medical, and public health communities with useful genetic information.

Cis-regulatory variations: a study of SNPs around genes showing cis-linkage in segregating mouse populations

Background

Changes in gene expression are known to be responsible for phenotypic variation and susceptibility to diseases. Identification and annotation of the genomic sequence variants that cause gene expression changes is therefore likely to lead to a better understanding of the cause of disease at the molecular level. In this study we investigate the pattern of single nucleotide polymorphisms (SNPs) in genes for which the mRNA levels show cis-genetic linkage (gene expression quantitative trait loci mapping in cis, or cis-eQTLs) in segregating mouse populations. Such genes are expected to have polymorphisms near their physical location (cis-variations) that affect their mRNA levels by altering one or more of the cis-regulatory elements. This led us to characterize the SNPs in promoter (5 Kb upstream) and non-coding gene regions (introns and 5 Kb downstream) (cis-SNPs) and the effects they may have on putative transcription factor binding sites.

Results

We demonstrate that the cis-eQTL genes (CEGs) have a significantly higher frequency of cis-SNPs compared to non-CEGs (when both sets are taken from the non-IBD regions, i.e. regions not identical by descent). Most CEGs having cis-SNPs do not contain these SNPs in the phylogenetically conserved regions. In those CEGs that contain cis-SNPs in the phylogenetically conserved regions, enrichment of cis-SNPs occurs both within and outside of the conserved sequences. A higher fraction of CEGs are also seen to harbor cis-SNP that affect predicted transcription factor binding sites, a likely consequence of the higher cis-SNPs density in these genes.

Conclusion

This present study provides the first genome-wide investigation of the putative cis-regulatory variations in a large set of genes whose levels of expression give rise to cis-linkage in segregating mammalian populations. Our results provide insights into the challenges that exist in identifying polymorphisms regulating gene expression using bioinformatic sequence analysis approaches. The data provided herein should benefit future investigations in this area.

Impairment of the vascular relaxation and differential expression of caveolin-1 of the aorta of diabetic +db/+db mice

In this study, we compared the endothelium-dependent and -independent relaxation of the isolated thoracic aorta of control (+db/+m) and diabetic (+db/+db) (C57BL/KsJ) mice. The gene expression (mRNA and protein) level of the muscarinic M(3) receptors, endothelial nitric oxide synthase (eNOS) and caveolin-1 of the aorta was also evaluated. Acetylcholine caused a concentration-dependent, N(G)-nitro-L-arginine methyl-ester (20 microM)-sensitive relaxation, with approximately 100% relaxation at 10 microM, in +db/+m mice. In +db/+db mice, the acetylcholine-induced relaxation was significantly smaller (maximum relaxation: approximately 80%). The sodium nitroprusside-mediated relaxation was slightly diminished in +db/+db mice, compared to +db/+m mice. However, there was no significant difference in the isoprenaline- and cromakalim-induced relaxation observed in both species. The mRNA and protein expression levels of caveolin-1 were significantly higher in the aorta of +db/+db mice. In contrast, there was no difference in the mRNA and protein expression levels of eNOS and muscarinic M(3) receptors between these mice. Our results demonstrate that the impairment of the acetylcholine-induced, endothelium-dependent aortic relaxation observed in +db/+db mice was probably associated with an enhanced expression of caveolin-1 mRNA and protein.

A comprehensive mouse IBD database for the efficient localization of quantitative trait loci

Traditional fine-mapping approaches in mouse genetics that go from a linkage region to a candidate gene are very costly and time consuming. Shared ancestry regions, along with the combination of genetics and genomics approaches, provide a powerful tool to shorten the time and effort required to identify a causative gene. In this article we present a novel methodology that predicts IBD (identical by descent) regions between pairs of inbred strains using single nucleotide polymorphism (SNP) maps. We have validated this approach by comparing the IBD regions, estimated using different algorithms, to the results derived using the sequence information in the strains present in the Celera Mouse Database. We showed that based on the current publicly available SNP genotypes, large IBD regions (>1 Mb) can be identified successfully. By assembling a list of 21,514 SNPs in 61 common inbred strains, we inferred IBD regions between all pairs of strains and confirmed, for the first time, that existing quantitative trait genes (QTG) and susceptibility genes all lie outside of IBD regions. We also illustrated how knowledge of IBD structures can be applied to strain selection for future crosses. We have made our results available for data mining and download through a public website ( http://www.mouseibd.florida.scripps.edu ).

Elucidating the murine brain transcriptional network in a segregating mouse population to identify core functional modules for obesity and diabetes

Complex biological systems are best modeled as highly modular, fluid systems exhibiting a plasticity that allows them to adapt to a vast array of changing conditions. Here we highlight several novel network-based approaches to elucidate genetic networks underlying complex traits. These integrative genomic approaches combine large-scale genotypic and gene expression results in segregating mouse populations to reconstruct reliable genetic networks underlying complex traits such as disease or drug response. We apply these novel approaches to one of the most extensive surveys of gene expression studies ever undertaken in whole brain in a segregating mouse population. More than 23,000 genes were monitored in whole brain samples from more than 300 mice derived from an F2 intercross population and genotyped at over 1200 SNP markers uniformly spread over the entire genome. We explore the topological properties of the brain transcriptional network and highlight different approaches to inferring causal associations among genes by integrating genotypic and expression data. We demonstrate the utility of these approaches by identifying and experimentally validating brain gene expression traits predicted to respond to a strong expression quantitative trait locus (eQTL) for the pituitary tumor-transforming 1 gene (Pttg1) that coincides with the physical location of this gene (a cis eQTL). We identify core functional modules making up the brain transcriptional network in mice that are coherent for core biological processes associated with metabolic disease traits including obesity and diabetes.

Fluoxetine rescues deficient neurogenesis in hippocampus of the Ts65Dn mouse model for Down syndrome

The Ts65Dn mouse, an adult model of Down syndrome displays behavioral deficits consistent with a dysfunctional hippocampus, similar to that seen with DS. In looking for mechanisms underlying these performance deficits, we have assessed adult neurogenesis in the dentate gyrus of Ts65Dn. Under untreated conditions, Ts65Dn mice (2-5 months old) showed markedly fewer BrdU-labeled cells than euploid animals. Chronic antidepressant treatment for over 3 weeks with the serotonin selective reuptake inhibitor, fluoxetine, increased neurogenesis in the Ts65Dn to comparable levels seen in the euploid by augmenting both proliferation and survival of BrdU-labeled cells in the subgranular layer and granule cell layer of the hippocampus, respectively.

The fragile breakage versus random breakage models of chromosome evolution

For many years, studies of chromosome evolution were dominated by the random breakage theory, which implies that there are no rearrangement hot spots in the human genome. In 2003, Pevzner and Tesler argued against the random breakage model and proposed an alternative “fragile breakage” model of chromosome evolution. In 2004, Sankoff and Trinh argued against the fragile breakage model and raised doubts that Pevzner and Tesler provided any evidence of rearrangement hot spots. We investigate whether Sankoff and Trinh indeed revealed a flaw in the arguments of Pevzner and Tesler. We show that Sankoff and Trinh's synteny block identification algorithm makes erroneous identifications even in small toy examples and that their parameters do not reflect the realities of the comparative genomic architecture of human and mouse. We further argue that if Sankoff and Trinh had fixed these problems, their arguments in support of the random breakage model would disappear. Finally, we study the link between rearrangements and regulatory regions and argue that long regulatory regions and inhomogeneity of gene distribution in mammalian genomes may be responsible for the breakpoint reuse phenomenon.

Genomes are constantly changing. If a genome is compared to a continental landform, then one type of change—point mutations—is analogous to gradual changes in the landscape due to erosion by wind and water. A second type of change—genome rearrangements—comprises evolutionary “earthquakes” that dramatically change the landscape. A fundamental question in studies of chromosome evolution is whether these earthquakes are happening along evolutionary “faults” (hot spots of rearrangements) or at “random” genomic positions. For many years, studies of chromosome evolution were dominated by the random breakage theory, which implies that there are no rearrangement hot spots in the human genome. In 2003, Pevzner and Tesler argued against the random breakage model and proposed an alternative “fragile breakage” model of chromosome evolution. In 2004, Sankoff and Trinh performed a series of computational simulations that argued against the fragile breakage model and raised doubts that Pevzner and Tesler provided any evidence of rearrangement hot spots. The authors show that Sankoff and Trinh's simulation misidentifies synteny blocks, that it does not accurately simulate what Pevzner and Tesler (2003) did, and that the parameters of Sankoff and Trinh do not reflect the realities of the comparative genomic architecture of human and mouse.

An imprinted locus epistatically influences Nstr1 and Nstr2 to control resistance to nerve sheath tumors in a neurofibromatosis type 1 mouse model

Cancer is a complex disease in which cells acquire many genetic and epigenetic alterations. We have examined how three types of alterations, mutations in tumor suppressor genes, changes in an imprinted locus, and polymorphic loci, interact to affect tumor susceptibility in a mouse model of neurofibromatosis type 1 (NF1). Mutations in tumor suppressor genes such as TP53 and in oncogenes such as KRAS have major effects on tumorigenesis due to the central roles of these genes in cell proliferation and cell survival. Imprinted genes expressed from only one parental chromosome affect tumorigenesis if their monoallelic expression is lost or duplicated. Because imprinted loci are within regions deleted or amplified in cancer, the parental origin of genomic rearrangements could affect tumorigenesis. Gene polymorphisms can vary tumor incidence by affecting rate-limiting steps in tumorigenesis within tumor cells or surrounding stroma. In our mouse model of NF1, the incidence of tumors mutant for the tumor suppressor genes Nf1 and Trp53 is strongly modified by a linked imprinted locus acting epistatically on two unlinked polymorphic loci, Nstr1 and Nstr2. This interaction of an imprinted locus and polymorphic susceptibility loci has profound implications for human mapping studies where the parental contribution of alleles is often unknown.

A catalog of nonsynonymous polymorphism on mouse Chromosome 16

Numerous phenotypic traits differ among inbred mice, and the genetic diversity of inbred strains has been exploited in studies of quantitative trait loci (QTL). Sequencing the mouse genome has resulted in improved tools for the study of QTL, but a comprehensive catalog of sequence variants between strains would be of great value in identifying and testing potentially causative alleles. A/J DNA was included in the Celera shotgun sequence of the mouse genome and C57BL/6 DNA was sequenced by an international consortium. We have resequenced A/J and B6 DNA to cover nearly all of the protein-coding portions of mouse Chromosome 16, revealing that there are 106 nonsynonymous substitutions in 74 of the 779 genes on the chromosome. The pattern of substitution is more similar to the spectrum of benign polymorphism in the human population than it is to human disease-causing mutations. In mouse, polymorphic variants tend to be associated with one another on large haplotypes; this pattern also holds true for nonsynonymous polymorphism. However, sufficient fragmentation of haplotypes is present to suggest that only a very-high-resolution haplotype map will enable effective inference of alleles in additional strains.

Transposable elements, gene creation and genome rearrangement in flowering plants

Plant genome structure is largely derived from the differing specificities, abundances and activities of transposable elements. Recent studies indicate that both the amplification and the removal of transposons are rapid processes in plants, accounting for the general lack of intergenic homology between species that last shared a common ancestor more than 10 million years ago. Two newly discovered transposon varieties, Helitrons and Pack-MULEs, acquire and fuse fragments of plant genes, creating the raw material for the evolution of new genes and new genetic functions. Many of these recently assembled, chimeric gene-candidates are expressed, suggesting that some might escape epigenetic silencing and mutational decay, but a proven case of gene creation by any transposable element activity in plants remains to be demonstrated.

Assembly of polymorphic genomes: algorithms and application to Ciona savignyi

Whole-genome assembly is now used routinely to obtain high-quality draft sequence for the genomes of species with low levels of polymorphism. However, genome assembly remains extremely challenging for highly polymorphic species. The difficulty arises because two divergent haplotypes are sequenced together, making it difficult to distinguish alleles at the same locus from paralogs at different loci. We present here a method for assembling highly polymorphic diploid genomes that involves assembling the two haplotypes separately and then merging them to obtain a reference sequence. Our method was developed to assemble the genome of the sea squirt Ciona savignyi, which was sequenced to a depth of 12.7 x from a single wild individual. By comparing finished clones of the two haplotypes we determined that the sequenced individual had an extremely high heterozygosity rate, averaging 4.6% with significant regional variation and rearrangements at all physical scales. Applied to these data, our method produced a reference assembly covering 157 Mb, with N50 contig and scaffold sizes of 47 kb and 989 kb, respectively. Alignment of ESTs indicates that 88% of loci are present at least once and 81% exactly once in the reference assembly. Our method represented loci in a single copy more reliably and achieved greater contiguity than a conventional whole-genome assembly method.

Integrating QTL and high-density SNP analyses in mice to identify Insig2 as a susceptibility gene for plasma cholesterol levels

The use of inbred strains of mice to dissect the genetic complexity of common diseases offers a viable alternative to human studies, given the control over experimental parameters that can be exercised. Central to efforts to map susceptibility loci for common diseases in mice is a comprehensive map of DNA variation among the common inbred strains of mice. Here we present one of the most comprehensive high-density, single nucleotide polymorphism (SNP) maps of mice constructed to date. This map consists of 10,350 SNPs genotyped in 62 strains of inbred mice. We demonstrate the utility of these data via a novel integrative genomics approach to mapping susceptibility loci for complex traits. By integrating in silico quantitative trait locus (QTL) mapping with progressive QTL mapping strategies in segregating mouse populations that leverage large-scale mapping of the genetic determinants of gene expression traits, we not only facilitate identification of candidate quantitative trait genes, but also protect against spurious associations that can arise in genetic association studies due to allelic association among unlinked markers. Application of this approach to our high-density SNP map and two previously described F2 crosses between strains C57BL/6J (B6) and DBA/2J and between B6 ApoE(-/-) and C3H/HeJ ApoE(-/-) results in the identification of Insig2 as a strong candidate susceptibility gene for total plasma cholesterol levels.

Genetic variation in laboratory mice

Characterizing the patterns of genetic variation in an organism provides fundamental insight into the evolutionary history of the organism and defines the scope and nature of studies that must be designed to correlate genotype to phenotype. Given the pre-eminent role of the inbred mouse in biomedical research, considerable effort has been undertaken in recent years to describe more fully the nature and amount of genetic variation among the numerous strains of mice that are in widest use. Here, we discuss recent studies that have contributed to an emerging understanding of the unique variation patterns found in inbred strains of mice and how they have arisen through a combination of natural evolution and human-directed breeding. These preliminary results have ramifications for genetic research into complex biomedical traits and are the basis for the development of future variation resources.

Echoes from the past--are we still in an RNP world?

Availability of the human genome sequence and those of other species is unmeasured in their value for a comprehensive understanding of the architecture, function and evolution of genomes and cells. Various mechanisms keep genomes in flux and generate intra- and interspecies variation. The conversion of RNA modules into DNA and their more or less random integration into chromosomes (retroposition) is in many lineages including our own the most pervasive and perhaps the most enigmatic. The proclivity of such events in extant multicellular eukaryotes, even in more recent evolutionary times, gives the impression that the transition period from the RNP (ribonucleoprotein) world to the emergence of modern cells, where DNA became the predominant carrier of genetic information, has lasted billions of years and is an endlessly drawn-out process rather than the punctuated event one might expect. Apart from the impact of such RNA-mediated processes as retroposition, the role of RNA in a wide variety of cellular functions has only recently become more widely appreciated.

Restoration of DSCR1 to disomy in the trisomy 16 mouse model of Down syndrome does not correct cardiac or craniofacial development anomalies

The Down syndrome critical region 1 (DSCR1) gene is located in syntenic regions of human chromosome 21 and mouse chromosome 16 and encodes a regulatory protein in the calcineurin/NFAT pathway. DSCR1 expression in the embryonic brain, craniofacial structures, and heart is consistent with a role in contributing to Down syndrome developmental anomalies. In the trisomy 16 (Ts16) murine model of Down syndrome, expression of DSCR1 isoforms is elevated and NFAT transcriptional activity is decreased in the developing heart and brain. The individual contribution of DSCR1 to Down syndrome-related anomalies was examined by specific restoration of DSCR1 to disomic levels in Ts16 embryos. However, genetic restoration of DSCR1 did not rescue major morphological abnormalities in cardiac or craniofacial development. These data demonstrate that trisomy of DSCR1 alone does not significantly contribute to developmental defects in Ts16 mice and underscore the complexity of developmental anomalies associated with Down syndrome.

Finding anchors for genomic sequence comparison

Recent sequencing of the human and other mammalian genomes has brought about the necessity to align them, to identify and characterize their commonalities and differences. Programs that align whole genomes generally use a seed-and-extend technique, starting from exact or near-exact matches and selecting a reliable subset of these, called anchors, and then filling in the remaining portions between the anchors using a combination of local and global alignment algorithms, but their choices for the parameters so far have been primarily heuristic. We present a statistical framework and practical methods for selecting a set of matches that is both sensitive and specific and can constitute a reliable set of anchors for a one-to-one mapping of two genomes from which a whole-genome alignment can be built. Starting from exact matches, we introduce a novel per-base repeat annotation, the Z-score, from which noise and repeat filtering conditions are explored. Dynamic programming-based chaining algorithms are also evaluated as context-based filters. We apply the methods described here to the comparison of two progressive assemblies of the human genome, NCBI build 28 and build 34 (www.genome.ucsc.edu), and show that a significant portion of the two genomes can be found in selected exact matches, with very limited amount of sequence duplication.

Integrating genotypic and expression data in a segregating mouse population to identify 5-lipoxygenase as a susceptibility gene for obesity and bone traits

Forward genetic approaches to identify genes involved in complex traits such as common human diseases have met with limited success. Fine mapping of linkage regions and validation of positional candidates are time-consuming and not always successful. Here we detail a hybrid procedure to map loci involved in complex traits that leverages the strengths of forward and reverse genetic approaches. By integrating genotypic and expression data in a segregating mouse population, we show how clusters of expression quantitative trait loci linking to regions of the genome accurately reflect the underlying perturbation to the transcriptional network induced by DNA variations in genes that control the complex traits. By matching patterns of gene expression in a segregating population with expression responses induced by single-gene perturbation experiments, we show how genes controlling clusters of expression and clinical quantitative trait loci can be mapped directly. We demonstrate the utility of this approach by identifying 5-lipoxygenase as underlying previously identified quantitative trait loci in an F(2) cross between strains C57BL/6J and DBA/2J and showing that it has pleiotropic effects on body fat, lipid levels and bone density.

Conserved sequences and the evolution of gene regulatory signals

Studies of evolutionary conservation of gene regulatory signals have led to a paradox: extensive sequence similarity implies functional conservation in non-coding regions across mammalian species; however, this stands in contrast to our understanding of transcriptional regulatory sites composed of degenerate recognition sequences for transcription factors that can maintain functional equivalence despite considerable sequence divergence. The latter observation provides an explanation for the rapid evolution of new traits through the gain and loss of transcription factor binding sites that bring new genes under the control of an existing genetic regulatory network. The former observation might point to novel mechanisms of gene regulation and/or chromosome function that are currently unappreciated. Recent comparative genome analysis has highlighted extensive conserved sequences in mammalian genomes that are beginning to be functionally characterized.

Perinatal loss of Ts65Dn Down syndrome mice

Ts65Dn mice inherit a marker chromosome, T(17(16))65Dn, producing segmental trisomy for orthologs of about half of the genes on human chromosome 21. These mice display a number of phenotypes that are directly comparable to those in humans with trisomy 21 and are the most widely used animal model of Down syndrome (DS). However, the husbandry of Ts65Dn mice is complicated. Males are sterile, and only 20-40% of the offspring of Ts65Dn mothers are trisomic at weaning. The lower-than-expected frequency of trisomic offspring has been attributed to losses at meiosis, during gestation and at postnatal stages, but no systematic studies support any of these suppositions. We show that the T(17(16))65Dn marker chromosome is inherited at expected frequency and is fully compatible with development to midgestation. Disproportional loss of trisomic offspring occurs in late gestation and continues through birth to weaning. Different maternal H2 haplotypes are significantly associated with the frequency of trisomy at weaning in patterns different from those reported previously. The proportion of trisomic mice per litter decreases with age of the Ts65Dn mother. These results provide the first statistical and numerical evidence supporting the prenatal and perinatal pattern of loss in the Ts65Dn mouse model of DS.

Signatures of reproductive isolation in patterns of single nucleotide diversity across inbred strains of mice

Reproductive isolation is often caused by the disruption of genic interactions that evolve in geographically separate populations. Identifying the genomic regions and genes involved in these interactions, known as "Dobzhansky-Muller incompatibilities," can be challenging but is facilitated by the wealth of genetic markers now available in model systems. In recent years, the complete genome sequence and thousands of single nucleotide polymorphisms (SNPs) from laboratory mice, which are largely genetic hybrids between Mus musculus and M. domesticus, have become available. Here, we use these resources to locate genomic regions that may underlie reproductive isolation between these two species. Using genotypes from 332 SNPs that differ between wild-derived strains of M. musculus and M. domesticus, we identified several physically unlinked SNP pairs that show exceptional gametic disequilibrium across the lab strains. Conspecific alleles were associated in a disproportionate number of these cases, consistent with the action of natural selection against hybrid gene combinations. As predicted by the Dobzhansky-Muller model, this bias was differentially attributable to locus pairs for which one hybrid genotype was missing. We assembled a list of potential Dobzhansky-Muller incompatibilities from locus pairs that showed extreme associations (only three gametic types) among conspecific alleles. Two SNPs in this list map near known hybrid sterility loci on chromosome 17 and the X chromosome, allowing us to nominate partners for disrupted interactions involving these genomic regions for the first time. Together, these results indicate that patterns produced by speciation between M. musculus and M. domesticus are visible in the genomes of lab strains of mice, underscoring the potential of these genetic model organisms for addressing general questions in evolutionary biology.

A tool for analyzing mate pairs in assemblies (TAMPA)

The current generation of genome assembly programs uses distance and orientation relationships of paired end reads of clones (mate pairs) to order and orient contigs. Mate pair data can also be used to evaluate and compare assemblies after the fact. Earlier work employed a simple heuristic to detect assembly problems by scanning across an assembly to locate peak concentrations of unsatisfied mate pairs. TAMPA is a novel, computational geometry-based approach to detecting assembly breakpoints by exploiting constraints that mate pairs impose on each other. The method can be used to improve assemblies and determine which of two assemblies is correct in the case of sequence disagreement. Results from several human genome assemblies are presented.

A 6-Mb contig-based comparative gene and linkage map of the rat schwannoma tumor suppressor region at 10q32.3

Frequent genetic aberrations of malignant schwannomas induced by the alkylating agent N-ethyl-N-nitrosourea in hybrids from inbred BD rat strains include allelic imbalances of the telomeric 20 Mb of chromosome 5 (Dis-2) and of the telomeric 5 Mb of chromosome 10q32 (Dis-1) in 59 and 94% of the tumors, respectively. The Dis-1 minimal loss of heterozygosity consensus region extends from D10Rat4 to the telomere and harbors a putative tumor suppressor gene(s). We constructed a 6-Mb BAC/PAC contig containing more than 70 known genes, 18 mapped microsatellites, and further ESTs/reference RNAs. A continuous block of strongly conserved synteny with mouse chromosome 11E2 and human chromosome 17q25.3 was found. Combining the sequence information from the rat and closely related syntenic regions of different mammalian species produces nearly complete gene maps as a basis for a positional candidate approach and gives insight into mammalian genomic evolution.

Toward predictive models of mammalian cells

Progress in experimental and theoretical biology is likely to provide us with the opportunity to assemble detailed predictive models of mammalian cells. Using a functional format to describe the organization of mammalian cells, we describe current approaches for developing qualitative and quantitative models using data from a variety of experimental sources. Recent developments and applications of graph theory to biological networks are reviewed. The use of these qualitative models to identify the topology of regulatory motifs and functional modules is discussed. Cellular homeostasis and plasticity are interpreted within the framework of balance between regulatory motifs and interactions between modules. From this analysis we identify the need for detailed quantitative models on the basis of the representation of the chemistry underlying the cellular process. The use of deterministic, stochastic, and hybrid models to represent cellular processes is reviewed, and an initial integrated approach for the development of large-scale predictive models of a mammalian cell is presented.

In vivo assessment of absolute perfusion and intracapillary blood volume in the murine myocardium by spin labeling magnetic resonance imaging

The absolute perfusion and the intracapillary or regional blood volume (RBV) in murine myocardium were assessed in vivo by spin labeling magnetic resonance imaging. Pixel-based perfusion and RBV maps were calculated at a pixel resolution of 469 x 469 mum and a slice thickness of 2 mm. The T(1) imaging module was a segmented inversion recovery snapshot fast low angle shot sequence with velocity compensation in all three gradient directions. The group average myocardial perfusion at baseline was determined to be 701 +/- 53 mL (100 g . min)(-1) for anesthesia with isoflurane (N = 11) at a mean heart rate (HR) of 455 +/- 10 beats per minute (bpm). This value is in good agreement with perfusion values determined by invasive microspheres examinations. For i.v. administration of the anesthetic Propofol, the baseline perfusion decreased to 383 +/- 40 mL (100 g . min)(-1) (N = 17, P < 0.05 versus. isoflurane) at a mean heart rate of 261 +/- 13 bpm (P < 0.05 versus isoflurane). In addition, six mice with myocardial infarction were studied under isoflurane anesthesia (HR 397 +/- 7 bpm). The perfusion maps showed a clear decrease of the perfusion in the infarcted area. The perfusion in the remote myocardium decreased significantly to 476 +/- 81 mL (100 g . min)(-1) (P < 0.05 versus sham). Regarding the regional blood volume, a mean value of 11.8 +/- 0.8 vol % was determined for healthy murine myocardium under anesthesia with Propofol (N = 4, HR 233 +/- 17 bpm). In total, the presented techniques provide noninvasive in vivo assessment of the perfusion and the regional blood volume in the murine myocardium for the first time and seem to be promising tools for the characterization of mouse models in cardiovascular research.

Protective efficacy and immunogenicity of Escherichia coli K13 diphtheria toxoid conjugate against experimental ascending pyelonephritis

In the present study, protective efficacy of Escherichia coli capsular antigen, K13, was evaluated in a mouse model of pyelonephritis. Unconjugated capsular polysaccharide failed to provide any protection. However, coupling of K13 to diphtheria toxoid (DT) enhanced its immunogenicity and led to significant production of anticapsular antibodies in mice. Immunization of animals with K13-DT conjugate also caused significant improvement in cell-mediated immune response as indicated by an increase in lymphoblastogenic response and in the CD4+/CD8+ cell ratio of splenic lymphocytes. Significant decrease in bacterial load and renal severity scores were observed in K13-DT immunized animals. Suitability of K13-DT conjugate as an effective vaccine candidate against urinary tract infections caused by E. coli has been discussed.

A high-resolution multistrain haplotype analysis of laboratory mouse genome reveals three distinctive genetic variation patterns

Understanding of the structure and the origin of genetic variation patterns in the laboratory inbred mouse provides insight into the utility of the mouse model for studying human complex diseases and strategies for disease gene mapping. In order to address this issue, we have constructed a multistrain, high-resolution haplotype map for the 99-Mb mouse Chromosome 16 using approximately 70,000 single nucleotide polymorphism (SNP) markers derived from whole-genome shotgun sequencing of five laboratory inbred strains. We discovered that large polymorphic blocks (i.e., regions where only two haplotypes, thus one SNP conformation, are found in the five strains), large monomorphic blocks (i.e., regions where the five strains share the same haplotype), and fragmented blocks (i.e., regions of greater complexity not resembling at all the first two categories) span 50%, 18%, and 32% of the chromosome, respectively. The haplotype map has 98% accuracy in predicting mouse genotypes in two other studies. Its predictions are also confirmed by experimental results obtained from resequencing of 40-kb genomic sequences at 21 distinct genomic loci in 13 laboratory inbred strains and 12 wild-derived strains. We demonstrate that historic recombination, intra-subspecies variations and inter-subspecies variations have all contributed to the formation of the three distinctive genetic signatures. The results suggest that the controlled complexity of the laboratory inbred strains may provide a means for uncovering the biological factors that have shaped genetic variation patterns.

GMAP: a genomic mapping and alignment program for mRNA and EST sequences

MOTIVATION

We introduce GMAP, a standalone program for mapping and aligning cDNA sequences to a genome. The program maps and aligns a single sequence with minimal startup time and memory requirements, and provides fast batch processing of large sequence sets. The program generates accurate gene structures, even in the presence of substantial polymorphisms and sequence errors, without using probabilistic splice site models. Methodology underlying the program includes a minimal sampling strategy for genomic mapping, oligomer chaining for approximate alignment, sandwich DP for splice site detection, and microexon identification with statistical significance testing.

RESULTS

On a set of human messenger RNAs with random mutations at a 1 and 3% rate, GMAP identified all splice sites accurately in over 99.3% of the sequences, which was one-tenth the error rate of existing programs. On a large set of human expressed sequence tags, GMAP provided higher-quality alignments more often than blat did. On a set of Arabidopsis cDNAs, GMAP performed comparably with GeneSeqer. In these experiments, GMAP demonstrated a several-fold increase in speed over existing programs.

AVAILABILITY

Source code for gmap and associated programs is available at http://www.gene.com/share/gmap

SUPPLEMENTARY INFORMATION

http://www.gene.com/share/gmap.

Conserved non-genic sequences — an unexpected feature of mammalian genomes

Mammalian genomes contain highly conserved sequences that are not functionally transcribed. These sequences are single copy and comprise approximately 1-2% of the human genome. Evolutionary analysis strongly supports their functional conservation, although their potentially diverse, functional attributes remain unknown. It is likely that genomic variation in conserved non-genic sequences is associated with phenotypic variability and human disorders. So how might their function and contribution to human disorders be examined?

Large-scale mutagenesis of the mouse to understand the genetic bases of nervous system structure and function

N-ethyl-N-nitrosourea (ENU) mutagenesis is presented as a powerful approach to developing models for human disease. The efforts of three NIH Mutagenesis Centers established for the detection of neuroscience-related phenotypes are described. Each center has developed an extensive panel of phenotype screens that assess nervous system structure and function. In particular, these screens focus on complex behavioral traits from drug and alcohol responses to circadian rhythms to epilepsy. Each of these centers has developed a bioinformatics infrastructure to track the extensive number of transactions that are inherent in these large-scale projects. Over 100 new mouse mutant lines have been defined through the efforts of these three mutagenesis centers and are presented to the research community via the centralized Web presence of the Neuromice.org consortium (http://www.neuromice.org). This community resource provides visitors with the ability to search for specific mutant phenotypes, to view the genetic and phenotypic details of mutant mouse lines, and to order these mice for use in their own research program.

Contribution of Tamm–Horsfall protein to virulence of Pseudomonas aeruginosa in urinary tract infection

Tamm-Horsfall glycoprotein (THP) is the most abundant protein which is synthesized by renal tubular cells and excreted in urine. Its role in urinary tract infection has yet not been identified. In the present study, the contribution of THP towards adherence of Pseudomonas aeruginosa to uroepithelial cells and murine peritoneal macrophages was studied. Decreased adherence of THP-coated P. aeruginosa to UECs and phagocytes was observed in vitro. In vivo, P. aeruginosa showed increased renal bacterial load and tissue pathology in a mouse model of acute ascending pyelonephritis, when THP-coated P. aeruginosa was used to cause infection. This study shows that THP may not necessarily act as a host defense component; rather, it may help in renal colonization of P. aeruginosa in vivo.