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Much of the research aimed at defining the pathogenesis of Staphylococcus aureus has been done with a limited number of strains, most notably the 8325-4 derivative RN6390. Several lines of evidence indicate that this strain is unique by comparison to clinical isolates of S. aureus. Based on this, we have focused our efforts on two clinical isolates (UAMS-1 and UAMS-601), both of which are hypervirulent in our animal models of musculoskeletal infection. In this study, we used comparative genomic hybridization to assess the genome content of these two isolates relative to RN6390 and each of seven sequenced S. aureus isolates. Our comparisons were done by using an amplicon-based microarray from the Pathogen Functional Genomics Resource Center and an Affymetrix GeneChip that collectively represent the genomes of all seven sequenced strains. Our results confirmed that UAMS-1 and UAMS-601 share specific attributes that distinguish them from RN6390. Potentially important differences included the presence of cna and the absence of isaB, sarT, sarU, and sasG in the UAMS isolates. Among the sequenced strains, the UAMS isolates were most closely related to the dominant European clone EMRSA-16. In contrast, RN6390, NCTC 8325, and COL formed a distinct cluster that, by comparison to the other four sequenced strains (Mu50, N315, MW2, and SANGER-476), was the most distantly related to the UAMS isolates and EMRSA-16.
Recently, we reported a whole genome scan on a sample of 630 Caucasian subjects from 53 human pedigrees. Several genomic regions were suggested to be linked to height. In an attempt to confirm the identified genomic regions, as well as to identify new genomic regions linked to height, we conducted a whole genome linkage study on an extended sample of 1,816 subjects from 79 pedigrees, which includes the 53 pedigrees containing the original 630 subjects from our previous whole genome study and an additional 128 new subjects, and 26 further pedigrees containing 1,058 subjects. Several regions achieved suggestive linkage signals, such as 9q22.32 [MLS (multipoint LOD score) = 2.74], 9q34.3 [MLS = 2.66], Xq24 [two-point LOD score = 2.64 at the marker DXS8067], and 7p14.2 [MLS = 2.05]. The importance of the above regions is supported either by other whole genome studies or by candidate genes within these regions relevant to linear growth or pathogenesis of short stature. In addition, this study has tentatively confirmed the Xq24 region's linkage to height, as this region was also detected in the previous whole genome study. To date, our study has achieved the largest sample size in the field of genetic linkage studies of human height. Together with the findings of other studies, the current study has further delineated the genetic basis of human stature.
BACKGROUND - Osteoporosis is a major public health problem, mainly quantified by low bone mineral density (BMD). The majority of BMD variation is determined by genetic effects. A pilot whole genome linkage scan (WGS) was previously reported in 53 white pedigrees with 630 subjects. Several genomic regions were suggested to be linked to BMD variation.
OBJECTIVE - To substantiate these previous findings and detect new genomic regions.
METHODS - A WGS was conducted on an extended sample where the size was almost tripled (1816 subjects from 79 pedigrees). All the subjects were genotyped with 451 microsatellite markers spaced approximately 8.1 cM apart across the human genome. Two point and multipoint linkage analyses were carried out using the variance component method.
RESULTS - The strongest linkage signal was obtained on Xq27 with two point LOD scores of 4.30 for wrist BMD, and 2.57 for hip BMD, respectively. Another important region was 11q23, which achieved a maximum LOD score of 3.13 for spine BMD in multipoint analyses, confirming the results on this region in two earlier independent studies. Suggestive linkage evidence was also found on 7p14 and 20p12.
CONCLUSIONS - Together with the findings from other studies, the current study has further delineated the genetic basis of bone mass and highlights the importance of increasing sample size to confirm linkage findings and to identify new regions of linkage.
The task of specific gene knockdown in vitro has been facilitated through the use of short interfering RNA (siRNA), which is now widely used for studying gene function, as well as for identifying and validating new drug targets. We explored the possibility of using siRNA for dissecting cellular pathways by siRNA-mediated gene silencing followed by gene expression profiling and systematic pathway analysis. We used siRNA to eliminate the Rb1 gene in human cells and determined the effects of Rb1 knockdown on the cell by using microarray-based gene expression profiling coupled with quantitative pathway analysis using the GenMapp and MappFinder software. Retinoblastoma protein is one of the key cell cycle regulators, which exerts its function through its interactions with E2F transcription factors. Rb1 knockdown affected G1/S and G2/M transitions of the cell cycle, DNA replication and repair, mitosis, and apoptosis, indicating that siRNA-mediated transient elimination of Rb1 mimics the control of cell cycle through Rb1 dissociation from E2F. Additionally, we observed significant effects on the processes of DNA damage response and epigenetic regulation of gene expression. Analysis of transcription factor binding sites was utilized to distinguish between putative direct targets and genes induced through other mechanisms. Our approach, which combines the use of siRNA-mediated gene silencing, mediated microarray screening and quantitative pathway analysis, can be used in functional genomics to elucidate the role of the target gene in intracellular pathways. The approach also holds significant promise for compound selection in drug discovery.
The increasing integration of patient-specific genomic data into clinical practice and research raises serious privacy concerns. Various systems have been proposed that protect privacy by removing or encrypting explicitly identifying information, such as name or social security number, into pseudonyms. Though these systems claim to protect identity from being disclosed, they lack formal proofs. In this paper, we study the erosion of privacy when genomic data, either pseudonymous or data believed to be anonymous, are released into a distributed healthcare environment. Several algorithms are introduced, collectively called RE-Identification of Data In Trails (REIDIT), which link genomic data to named individuals in publicly available records by leveraging unique features in patient-location visit patterns. Algorithmic proofs of re-identification are developed and we demonstrate, with experiments on real-world data, that susceptibility to re-identification is neither trivial nor the result of bizarre isolated occurrences. We propose that such techniques can be applied as system tests of privacy protection capabilities.
Recent studies describe new genome-wide mutagenesis strategies, coupled with phenotypic screening, and demonstrate the power of such approaches to provide new insights into the genetics of the immune response.
The plasma membrane transporters that clear extracellular serotonin (5-HT) and norepinephrine (NE), serotonin transporters (SERTs) and NE transporters (NETs), have received considerable attention over the past four decades because of their roles in amine neurotransmitter inactivation. In addition, they interact with many centrally active drugs, including multiple classes of antidepressants such as the serotonin-selective reuptake inhibitors, typified by fluoxetine (Prozac), and the more recently developed norepinephrine-selective transporter antagonists, such as reboxetine. The therapeutic utility of these agents supports biogenic amine theories of affective disorders and raises the question as to whether SERT and NET exhibit a functional genetic variation that could influence risk for behavioral disorders. Although evidence exists that a promoter polymorphism in SERT may influence behavioral states, this contention is not without complexity and its mechanism of action remains poorly understood. The identification of coding variants of NETs and SERTs would offer important opportunities to connect genotype to phenotype. However, given the limited frequency of transporter coding variations evident to date in general population surveys or in psychiatric genetic studies, the identification of informative functional variants of transporters will likely require refined phenotypes. In this regard, NET and SERT play critical roles in cardiovascular and gastrointestinal physiology, respectively. This perspective reviews recent human and mouse studies that suggest how peripheral autonomic phenotypes, linked to genetic disruption of NET and SERT function, can aid in the phenotypic segregation needed for advanced theories of biogenic amine dysfunction and pharmacogenetics.
Functional genomics, commonly applied to the genes and enzymes involved in metabolism of chemicals, can also be applied to enzymes involved in the metabolism of nutrients. Although in its infancy, genomics can be used to determine relationships between nutrition and toxicology, drug metabolism, and cancer.
The mouse and human genome sequences provide new opportunities to characterize mammalian gene functions on a genome-wide level. Toward this end, we have developed strategies for tagged-sequence mutagenesis in mice. Tagged-sequence mutagenesis has been used first, to analyze genes implicated in posttranscriptional gene regulation, and second, to identify genes important in immune cell development and function.