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BACKGROUND - Despite significant efforts from the research community, an extensive portion of the proteins encoded by human genes lack an assigned cellular function. Most metazoan proteins are composed of structural and/or functional domains, of which many appear in multiple proteins. Once a domain is characterized in one protein, the presence of a similar sequence in an uncharacterized protein serves as a basis for inference of function. Thus knowledge of a domain's function, or the protein within which it arises, can facilitate the analysis of an entire set of proteins.
DESCRIPTION - From the Pfam domain database, we extracted uncharacterized protein domains represented in proteins from humans, worms, and flies. A data centre was created to facilitate the analysis of the uncharacterized domain-containing proteins. The centre both provides researchers with links to dispersed internet resources containing gene-specific experimental data and enables them to post relevant experimental results or comments. For each human gene in the system, a characterization score is posted, allowing users to track the progress of characterization over time or to identify for study uncharacterized domains in well-characterized genes. As a test of the system, a subset of 39 domains was selected for analysis and the experimental results posted to the NovelFam3000 system. For 25 human protein members of these 39 domain families, detailed sub-cellular localizations were determined. Specific observations are presented based on the analysis of the integrated information provided through the online NovelFam3000 system.
CONCLUSION - Consistent experimental results between multiple members of a domain family allow for inferences of the domain's functional role. We unite bioinformatics resources and experimental data in order to accelerate the functional characterization of scarcely annotated domain families.
UNLABELLED - A genome-wide screen was conducted using a large white sample to identify QTLs for FNCS geometry. We found significant linkage of FNCS parameters to 20q12 and Xq25, plus significant epistatic interactions and sex-specific QTLs influencing FNCS geometry variation.
INTRODUCTION - Bone geometry, a highly heritable trait, is a critical component of bone strength that significantly determines osteoporotic fracture risk. Specifically, femoral neck cross-sectional (FNCS) geometry is significantly associated with hip fracture risk as well as genetic factors. However, genetic research in this respect is still in its infancy.
MATERIALS AND METHODS - To identify the underlying genomic regions influencing FNCS variables, we performed a remarkably large-scale whole genome linkage scan involving 3998 individuals from 434 pedigrees for four FNCS geometry parameters, namely buckling ratio (BR), cross-sectional area (CSA), cortical thickness (CT), and section modulus (Z). The major statistical approach adopted is the variance component method implemented in SOLAR.
RESULTS - Significant linkage evidence (threshold LOD = 3.72 after correction for tests of multiple phenotypes) was found in the regions of 20q12 and Xq25 for CT (LOD = 4.28 and 3.90, respectively). We also identified eight suggestive linkage signals (threshold LOD = 2.31 after correction for multiple tests) for the respective geometry traits. The above findings were supported by principal component linkage analysis. Of them, 20q12 was of particular interest because it was linked to multiple FNCS geometry traits and significantly interacted with five other genomic loci to influence CSA variation. The effects of 20q12 on FNCS geometry were present in both male and female subgroups. Subgroup analysis also revealed the presence of sex-specific quantitative trait loci (QTLs) for FNCS traits in the regions such as 2p14, 3q26, 7q21 and 15q21.
CONCLUSIONS - Our findings laid a foundation for further replication and fine-mapping studies as well as for positional and functional candidate gene studies, aiming at eventually finding the causal genetic variants and hidden mechanisms concerning FNCS geometry variation and the associated hip fractures.
Transforming growth factor-beta (TGF-beta) is the prototype of a large family of signaling molecules. TGF-beta signaling profoundly influences tumor development as demonstrated in several engineered mouse models. The present study was designed to identify differences by cDNA microarray and MALDI-TOF MS analyses in mammary carcinomas with and without TGF-beta signaling. The results demonstrate a significant potential for combination of profiling technologies to further understand the molecular mechanisms of breast cancer.
The presynaptic dopamine (DA) transporter (DAT) is a major determinant of synaptic DA inactivation, an important target for psychostimulants including cocaine and amphetamine, and a mediator of DA neuron vulnerability to the neurotoxins 6-hydroxydopamine (6-OHDA) and 1-methyl-4-phenylpyridinium ion. To exploit genetic approaches for the study of DATs and neural degeneration, we exploited the visibility of green fluorescent protein (GFP)-tagged DA neurons in transgenic nematodes to implement a forward genetic screen for suppressors of 6-OHDA sensitivity. In our initial effort, we identified three novel dat-1 alleles conferring 6-OHDA resistance. Two of the dat-1 alleles derive from point mutations in conserved glycine residues (G55, G90) in contiguous DAT-1 transmembrane domains (TM1 and TM2, respectively), whereas the third allele results in altered translation of the transporter's COOH terminus. Our studies reveal biosynthetic, trafficking and functional defects in the DAT-1 mutants, exhibited both in vitro and in vivo. These studies validate a forward genetic approach to the isolation of DA neuron-specific toxin suppressors and point to critical contributions of the mutated residues, as well as elements of the DAT-1 COOH terminus, to functional expression of catecholamine transporters in neurons.
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.