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Identification of Candidate Genes for Neuropathic Pain at the Pain1 Locus on Mouse Chromosome 15Elahipanah, Tina 31 December 2010 (has links)
Sciatic and saphenous neurectomy produces in mice a neuropathic pain-like behaviour (‘autotomy’). A/J mice express higher autotomy levels than C57BL6/J mice. A previous study used autotomy data for these strains and their 23 recombinant daughter inbred lines of the AXB-BXA set, to map a quantitative trait locus (QTL) for autotomy on chromosome 15. Since then, this QTL, named Pain1, was replicated twice. Since all three studies used a low-resolution genetic map based on microsatellites its confidence length precluded identification of candidate gene(s). To overcome this problem, I used a higher resolution SNP-based genetic map and refined Pain1’s peak location, identifying in it 80 candidate genes. But only Lynx1, Arc and Sharpin had sequence mismatches between A/J and C57BL6/J, known neural functions, and contrasting expression levels in DRGs and spinal cord of intact, sham-operated, and neurectomized mice of these lines. Meeting these criteria made them our best candidate genes for autotomy.
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Homologous Gene Finding with a Hidden Markov ModelXuefeng, Cui 20 December 2006 (has links)
The homology search problem and the gene finding problem are two fundamental problems in bioinformatics. The homology search problem is to find the homologous regions of two biological sequences; the gene finding problem is to find all the genes in both strands of a genomic sequence. Recently, gene finding research has demonstrated that homology search results can be used to improve the accuracy of gene finding. By combining the two problems, we define a new problem called the homologous gene finding problem. The homologous gene finding problem is to find homologous genes of a query gene in a target genomic sequence.
Consequently, we present a new homologous gene finding algorithm in this thesis. We borrow the idea of gene mapping and alignment algorithms, and apply existing seed-based homology search algorithms and hidden Markov model-based (HMM-based) gene finding algorithms to solve the homologous gene finding problem. After we find high-scoring segment pairs (HSPs) between the query gene and the target genomic sequence, we locate target regions that we believe contain a gene homologous to the query gene. Then, we extend existing HMM-based gene finding algorithms to find homologous gene candidates. To improve the accuracy of homologous gene finding, we train a HMM to be biased toward the query gene. We also introduce a new coding sequence (CDS) length penalty as a measure of how the CDS lengths of the query gene and its homologous gene vary to further improve the accuracy. We use the new CDS length penalty together with our enhanced Viterbi algorithm and our flexible finish condition to improve the speed of homologous gene fining without harming the accuracy. Finally, we use protein alignment to pick and rank the best homologous gene candidates.
In this thesis, we also describe several experiments to evaluate and support our homologous gene finding algorithm.
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Homologous Gene Finding with a Hidden Markov ModelCui, Xuefeng 11 January 2007 (has links)
The homology search problem and the gene finding problem are two fundamental problems in bioinformatics. The homology search problem is to find the homologous regions of two biological sequences; the gene finding problem is to find all the genes in both strands of a genomic sequence. Recently, gene finding research has demonstrated that homology search results can be used to improve the accuracy of gene finding. By combining the two problems, we define a new problem called the homologous gene finding problem. The homologous gene finding problem is to find homologous genes of a query gene in a target genomic sequence.
Consequently, we present a new homologous gene finding algorithm in this thesis. We borrow the idea of gene mapping and alignment algorithms, and apply existing seed-based homology search algorithms and hidden Markov model-based (HMM-based) gene finding algorithms to solve the homologous gene finding problem. After we find high-scoring segment pairs (HSPs) between the query gene and the target genomic sequence, we locate target regions that we believe contain a gene homologous to the query gene. Then, we extend existing HMM-based gene finding algorithms to find homologous gene candidates. To improve the accuracy of homologous gene finding, we train a HMM to be biased toward the query gene. We also introduce a new coding sequence (CDS) length penalty as a measure of how the CDS lengths of the query gene and its homologous gene vary to further improve the accuracy. We use the new CDS length penalty together with our enhanced Viterbi algorithm and our flexible finish condition to improve the speed of homologous gene fining without harming the accuracy. Finally, we use protein alignment to pick and rank the best homologous gene candidates.
In this thesis, we also describe several experiments to evaluate and support our homologous gene finding algorithm.
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Homologous Gene Finding with a Hidden Markov ModelXuefeng, Cui 20 December 2006 (has links)
The homology search problem and the gene finding problem are two fundamental problems in bioinformatics. The homology search problem is to find the homologous regions of two biological sequences; the gene finding problem is to find all the genes in both strands of a genomic sequence. Recently, gene finding research has demonstrated that homology search results can be used to improve the accuracy of gene finding. By combining the two problems, we define a new problem called the homologous gene finding problem. The homologous gene finding problem is to find homologous genes of a query gene in a target genomic sequence.
Consequently, we present a new homologous gene finding algorithm in this thesis. We borrow the idea of gene mapping and alignment algorithms, and apply existing seed-based homology search algorithms and hidden Markov model-based (HMM-based) gene finding algorithms to solve the homologous gene finding problem. After we find high-scoring segment pairs (HSPs) between the query gene and the target genomic sequence, we locate target regions that we believe contain a gene homologous to the query gene. Then, we extend existing HMM-based gene finding algorithms to find homologous gene candidates. To improve the accuracy of homologous gene finding, we train a HMM to be biased toward the query gene. We also introduce a new coding sequence (CDS) length penalty as a measure of how the CDS lengths of the query gene and its homologous gene vary to further improve the accuracy. We use the new CDS length penalty together with our enhanced Viterbi algorithm and our flexible finish condition to improve the speed of homologous gene fining without harming the accuracy. Finally, we use protein alignment to pick and rank the best homologous gene candidates.
In this thesis, we also describe several experiments to evaluate and support our homologous gene finding algorithm.
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Homologous Gene Finding with a Hidden Markov ModelCui, Xuefeng 11 January 2007 (has links)
The homology search problem and the gene finding problem are two fundamental problems in bioinformatics. The homology search problem is to find the homologous regions of two biological sequences; the gene finding problem is to find all the genes in both strands of a genomic sequence. Recently, gene finding research has demonstrated that homology search results can be used to improve the accuracy of gene finding. By combining the two problems, we define a new problem called the homologous gene finding problem. The homologous gene finding problem is to find homologous genes of a query gene in a target genomic sequence.
Consequently, we present a new homologous gene finding algorithm in this thesis. We borrow the idea of gene mapping and alignment algorithms, and apply existing seed-based homology search algorithms and hidden Markov model-based (HMM-based) gene finding algorithms to solve the homologous gene finding problem. After we find high-scoring segment pairs (HSPs) between the query gene and the target genomic sequence, we locate target regions that we believe contain a gene homologous to the query gene. Then, we extend existing HMM-based gene finding algorithms to find homologous gene candidates. To improve the accuracy of homologous gene finding, we train a HMM to be biased toward the query gene. We also introduce a new coding sequence (CDS) length penalty as a measure of how the CDS lengths of the query gene and its homologous gene vary to further improve the accuracy. We use the new CDS length penalty together with our enhanced Viterbi algorithm and our flexible finish condition to improve the speed of homologous gene fining without harming the accuracy. Finally, we use protein alignment to pick and rank the best homologous gene candidates.
In this thesis, we also describe several experiments to evaluate and support our homologous gene finding algorithm.
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Investigation of the role of target cell factors in retrovirus transductionKrishna, Delfi 23 November 2005 (has links)
Gene therapy is the intracellular delivery of genetic material for a therapeutic effect and is currently being used in clinical trials for the treatment of cancer, AIDS and vascular diseases. Recombinant retroviral vectors are one of the most commonly used gene delivery vectors in clinical trials because they can permanently integrate the therapeutic gene into the genome of the target cell resulting in persistent gene expression. However, recombinant retroviral vectors suffer from several limitations. The gene transfer efficiency is not high enough to produce a desired therapeutic effect and the vectors lack the ability to genetically modify target tissue without producing unpredictable side- effects on healthy bystander tissue. The focus of this thesis is to determine target cell factors that affect efficiency and specificity of gene transfer of recombinant retroviruses. Successful gene transfer by recombinant retroviruses is a multi-step process and we have focused our efforts on those target cell factors that affect virus entry into the target cell.
We have developed an experimental system to study the effect of pathway of virus entry and the intracellular trafficking itinerary of the targeted receptor, on the efficiency of gene transfer of targeted retroviruses. Our results indicate that interaction with a targeted receptor affects the efficiency of gene transfer of a targeted retrovirus by altering the residence time of the virus on the cell surface, by changing the region of the cell surface that the virus is exposed to, with respect to its natural receptor or by changing the pH that the virus is exposed to during intracellular transport.
We have examined if recombinant retroviruses are capable of inducing signaling events in target cells to overcome barriers to efficient gene transfer. We have found that retroviruses are capable of activating actin-regulating-GTPase Rac1 while entering target cells. We have found that retroviruses use non-envelope and non-receptor molecules to induce Rac1 activation. Rac1 activity is important for efficient fusion and intracellular trafficking of the virus and blocking mediators of Rac1 activity on target cells affects the efficiency of gene transfer of recombinant retroviruses. The implications of our findings on efficient retrovirus-cell interactions are discussed.
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The investigation of controlled release microchips, nanoparticles, and sirna for gene therapy in tissue engineering applicationsChern, Christina 15 May 2009 (has links)
The study of drug delivery for the treatment of illnesses and injuries is an
important area of pharmaceutical technology. A relatively new area of drug delivery
being explored is gene therapy, which utilizes the idea that genes can be used as an
alternative treatment. The exploration of gene delivery brought major advancements in
the treatment of cancers and tumors as well as many challenges. In this study, the
challenges of maintaining a stable vehicle for delivery, delivering genes into the cells,
and the efficacy of the gene delivery vehicle were explored.
Seven co-polymers of 12% (w/v) poly (D, L-lactic glycolide) (PDLG) were used
to find a biodegradable polymer composition as an implant that temporarily controls the
delivery of the genes. Of the formulations tested, 65/35 DL 3A and 50/50 DLG 4A were
observed to show degradation time frames that best fit our purposes.
Also, nanoparticles have been used to aid in the targeting of drugs to desired cells
in delivery. One drawback of using nanoparticles is the potential toxic side effects they
might cause. Zinc oxide nanoparticles coated with poly (vinyl pyrrolidone) (PVP) used
as drug carriers were observed to have an effect on cell viability in previous studies. The cytotoxic effects of ZnO nanoparticles and PVP have on NIH 3T3 mouse fibroblast cells
were investigated to see if there is a direct correlation between the level of PVP and zinc
nanoparticles to the amount of cell death. It was found that an increase in concentration
of ZnO nanoparticles correlates to a decrease in viability of the cells. It was also noted
that the method of cell death is likely to be apoptosis.
To confirm the efficacy of gene therapy through transfection, the transfection of
the serum response factor (SRF) gene plasmid DNA and short interfering RNA (siRNA)
were investigated. The efficiency of the transfection method were tested for both twodimensional
and three-dimensional transfection of the SRF plasmid and siRNA.
Experiments with two-dimensional transfection of the SRF plasmid and siRNA were
successful, and transfer of the gene in the three-dimensional environment was observed
with promising results with the siRNA.
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Identification of genetic loci and transcriptional networks that confer virulence and survival of Brucella melitensisWeeks, Jenni Nichole 15 May 2009 (has links)
Brucella melitensis is the etiological agent of brucellosis, a zoonotic
disease characterized by abortions in ruminant animals and a chronic
debilitating disease in humans. Despite genome sequencing, little is known
about the genetic elements behind Brucella s ability to survive and cause
disease. Regulatory networks provide the ability to adapt to changing
environments by initiating expression from specific regulons to provide
adjustments to metabolism and mechanisms that enhance survival. Little detail
is known about transcriptional networks that exist in Brucella, but are of great
interest because they could provide information about genetic loci that contribute
to virulence and intracellular survival.
Transposon mutagenesis identified gene loci that are indispensable for
the intracellular replication of B. melitensis, including virulence genes, metabolic
defects, and transcriptional regulators. Two transcriptional regulators of interest
were identified, MucR and VjbR. VjbR is a LuxR homologue and is associated with the regulation of virulence genes in a density dependent manner in a
number of bacterial pathogens, and is consistent with VjbR regulation of
virulence genes in B. melitensis. Microarray analysis of vjbR and a potential
activating signal C12-HSL revealed that both regulate numerous putative
virulence genes, including adhesins, proteases, protein secretion/translocation
components, potential effector proteins, lipoproteins, a hemolysin and stress
survival aids. This analysis also revealed that C12-HSL is not an activating signal
of VjbR, but instead acts to suppress VjbR activity.
MucR is a transcriptional regulator shown to regulate exopolysaccharide
synthesis in the closely related Rhizobiales. Microarray analysis of a mucR
mutant in B. melitensis suggested that MucR contributes to the regulation of
nitrogen metabolism and iron sequestering/storage. MucR was also found to
regulate genes involved in stress response, regulating several proteases that
may contribute to enhanced survival and virulence of the organism.
This work identified approximately 1,000 genetic loci that may be
important to the survival of B. melitensis, revealing potential virulence genes and
metabolic defects. Interruption of the VjbR regulon could be a potential
chemotherapeutic target for the treatment of brucellosis. Furthermore, this work
describes the functions of two gene deletions that are being evaluated as novel
attenuated vaccines.
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Gene Expression in the Stallion TestesLaughlin, Andy M. 2010 May 1900 (has links)
Understanding the genes that regulate spermatogenesis and steroidogenesis in the testis is critical for enhancement of stallion fertility. Stallion testicular samples were used to identify candidate genes by cDNA microarrays that simultaneously assessed expression levels of 9132 genes. First, gene expression was compared between light (spermatogenically active) and dark (spermatogenically inactive) testis tissue of 1.5-year-old horses (n = 3). Ninety-three genes were differentially expressed (35 light specific, 58 dark specific) in matched paired samples. Second, gene expression was compared between testicular tissue of two mature stallions, one with normal quality semen (fertile) and one with poor quality semen (subfertile). A total of 233 genes were differentially expressed (122 in fertile tissue, 111 in subfertile tissue). Of these, phosphodiesterase 3B (PDE3B), steroidogenic acute regulatory (StAR) protein, and outer dense fiber of sperm tails 2 (ODF2) mRNAs, were localized and quantified by in situ hybridization (ISH) in mature stallions and/or in unilateral cryptorchids. ISH revealed differences (P < 0.05) among mature stallions (n = 10) for PDE3B (localized to seminiferous tubules) and StAR protein (localized to interstitial spaces) mRNAs. A positive correlation coefficient (r = .556, p = .025) was found between StAR protein mRNA and plasma concentration of testosterone. Additionally, both gene products were evaluated in 1-year-old (n = 3) and 3-year-old (n = 3) unilateral cryptorchid stallions. Expression of both PDE3B and StAR protein gene was significantly higher in mature, descended testes compared to mature, retained testes and the descended and retained testes of immature, cryptorchid stallions. StAR protein gene demonstrated significantly higher expression in immature retained testes compared to immature descended testes. A precision-cut tissue slice (PCTS) in vitro culture system was evaluated as a potential tool to study equine testes function. Testes from immature stallions (n = 3) were cut into slices (mean slice weight = 13.85 +/- 0.20 mg; mean slice thickness = 515.00 +/- 2.33 ?m) and exposed to medium containing ovine luteinizing hormone (oLH) at concentrations of 0, 5, 50 and 500 ng/ml for 6 h at 32 degrees C. Medium content of testosterone and estradiol was increased 500% and 120%, respectively, by addition of oLH versus that observed for the testis tissue slices treated with 0 ng oLH (control). An oLH concentration-dependent increase in StAR protein mRNA in tissue slices was detected by in situ hybridization; whereas, differences for PDE3B and ODF2 mRNAs were not observed. Collectively, these results demonstrate that the stallion is an excellent model for studying male fertility due to the initiation of spermatogenesis, frequency of cryptorchidism, and routine castration providing useful tissue to use for studying gene expression.
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The Differential Expression of Bcl10 in the Tumor Cell LinesLin, James 16 August 2004 (has links)
Bcl10 is one of the apoptosis regulatory protein. It is located at 1p22,one site harbor tumor suppressor tumor gene. We screen Bcl10 expression in different tumor cell lines by reverse transcription-polymerase chain reaction(RT-PCR), western blot(WB) and immunohistochemistry(IHC).
The results showed Bcl10 genomic expression was found in U87, Astrocytoma and no expression in glioma , glioblastoma. There were cell lines with expressions in Bcl10 protein and NF-£eB including hepatocellular carcinoma, glioblastoma, and breast cancer, but increased in lung cancer cell line. In immunohistochemistry,we found the Bcl10 protein has positive finding in glioma U373, U251; oral cancer CA922, SAS, clinical patient VGH283; Lung cancer PC14, PC13; Hepatoma Huh7; Colon cancer SW 480; Cervical cancer HeLa.
The Bcl10 gene, unlike other tumor suppressor genes such as p53, may be selectively targeted by different human tumors. In our study, Bcl10 play a role in brain tumor, oral cancer and some tumor cell line had not been reported before.
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