Matching Items (10)

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A review of pathway-based visualization and quantification analysis tools using microarray data

Description

Pathway analysis helps researchers gain insight into the biology behind gene expression-based data. By applying this data to known biological pathways, we can learn about mutations or other changes in

Pathway analysis helps researchers gain insight into the biology behind gene expression-based data. By applying this data to known biological pathways, we can learn about mutations or other changes in cellular function, such as those seen in cancer. There are many tools that can be used to analyze pathways; however, it can be difficult to find and learn about the which tool is optimal for use in a certain experiment. This thesis aims to comprehensively review four tools, Cytoscape, PaxtoolsR, PathOlogist, and Reactome, and their role in pathway analysis. This is done by applying a known microarray data set to each tool and testing their different functions. The functions of these programs will then be analyzed to determine their roles in learning about biology and assisting new researchers with their experiments. It was found that each tools holds a very unique and important role in pathway analysis. Visualization pathways have the role of exploring individual pathways and interpreting genomic results. Quantification pathways use statistical tests to determine pathway significance. Together one can find pathways of interest and then explore areas of interest.

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Date Created
  • 2020-05

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Characterizing Primary Mesothelioma Cell Lines by Exome Sequencing

Description

Malignant Pleural Mesothelioma is a type of lung cancer usually discovered at an advanced stage at which point there is no cure. Six primary MPM cell lines were used to

Malignant Pleural Mesothelioma is a type of lung cancer usually discovered at an advanced stage at which point there is no cure. Six primary MPM cell lines were used to conduct in vitro research to make conclusions about specific gene mutations associated with Mesothelioma. DNA exome sequencing, a time efficient and inexpensive technique, was used for identifying specific DNA mutations. Computational analysis of exome sequencing data was used to make conclusions about copy number variation among common MPM genes. Results show a CDKN2A gene heterozygous deletion in Meso24 cell line. This data is validated by a previous CRISPR-Cas9 outgrowth screen for Meso24 where the knocked-out gene caused increased Meso24 growth.

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Date Created
  • 2020-05

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Evaluating variant calling best practices

Description

Analyzing human DNA sequence data allows researchers to identify variants associated with disease, reconstruct the demographic histories of human populations, and further understand the structure and function of the genome.

Analyzing human DNA sequence data allows researchers to identify variants associated with disease, reconstruct the demographic histories of human populations, and further understand the structure and function of the genome. Identifying variants in whole genome sequences is a crucial bioinformatics step in sequence data processing and can be performed using multiple approaches. To investigate the consistency between different bioinformatics methods, we compared the accuracy and sensitivity of two genotyping strategies, joint variant calling and single-sample variant calling. Autosomal and sex chromosome variant call sets were produced by joint and single-sample calling variants for 10 female individuals. The accuracy of variant calls was assessed using SNP array genotype data collected from each individual. To compare the ability of joint and single-sample calling to capture low-frequency variants, folded site frequency spectra were constructed from variant call sets. To investigate the potential for these different variant calling methods to impact downstream analyses, we estimated nucleotide diversity for call sets produced using each approach. We found that while both methods were equally accurate when validated by SNP array sites, single-sample calling identified a greater number of singletons. However, estimates of nucleotide diversity were robust to these differences in the site frequency spectrum between call sets. Our results suggest that despite single-sample calling’s greater sensitivity for low-frequency variants, the differences between approaches have a minimal effect on downstream analyses. While joint calling may be a more efficient approach for genotyping many samples, in situations that preclude large sample sizes, our study suggests that single-sample calling is a suitable alternative.

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Date Created
  • 2020-05

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Investigating Psychosocial Adjustment in Women with Mayer-Rokitansky-Küster-Hauser

Description

Mayer-Rokitansky-Küster-Hauser (MRKH) is a rare Disorder of Sexual Development (DSD) that results in the lack of a uterus and vagina in women. Receiving this diagnosis during adolescence can cause various

Mayer-Rokitansky-Küster-Hauser (MRKH) is a rare Disorder of Sexual Development (DSD) that results in the lack of a uterus and vagina in women. Receiving this diagnosis during adolescence can cause various forms of psychological distress in patients and families.<br/>Specifically, this condition could affect a women’s gender identity, body image, romantic relationships, family relationships, and psychological wellbeing. Parents are also put in a stressful<br/>position as they now have to navigate the healthcare system, disclosure, and the relationship with their child. This study aims to expand the knowledge of psychosocial adjustment by studying body<br/>image, gender identity, and mental health in individuals living with MRKH as well as parental disclosure, parental support systems, and parental perceptions of their child’s mental health.

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Date Created
  • 2021-05

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Alzheimer's Disease in Latinos

Description

Alzheimer’s disease is a disease that can affect cognition, perception and behavior and is currently untreatable. It was discovered in the early 20th century and while significant scientific advancements have

Alzheimer’s disease is a disease that can affect cognition, perception and behavior and is currently untreatable. It was discovered in the early 20th century and while significant scientific advancements have occurred, there is ambiguity that remains to be researched and understood. Latinos are the largest ethnic minority in the United States and while data still needs to be uncovered, possible risk factors for developing Alzheimer’s include heart issues, poverty and obesity, age and education level, to name a few. Poverty is linked to obesity, diabetes and a low education level, which in turn have been found to have an impact on Alzheimer’s and all factors impact cardiovascular and vascular health. Due to the collectivistic culture that is deeply rooted in Latinos, there is a strong sense of family that is upheld when caring for relatives who are afflicted and may be hesitant to receive the care that is needed. Other barriers include financial stability, linguistic and cultural barriers, underutilizing resources and health literacy. There are still research gaps that are yet to be filled like brain health and longitudinal studies for Latinos, but current treatments like diet and culturally competent professionals can help with the prognosis. Alzheimer’s is a complex disease, but with the numerous efforts made thus far, such as creating the LatinosAgainstAlzheimer’s Network, it will soon be able to be understood and hopefully eradicated.

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Date Created
  • 2021-05

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Evaluating Efficacy of Repurposed Drugs in Treatment of Glioblastoma

Description

Glioblastoma (GBM) is the most aggressive adult brain tumor with a devastating median survival time of about fourteen months post-surgery and standard of care therapy with radiation and temozolomide. The

Glioblastoma (GBM) is the most aggressive adult brain tumor with a devastating median survival time of about fourteen months post-surgery and standard of care therapy with radiation and temozolomide. The low incidence of GBM, cost of developing novel therapeutics, and time cost of clinical trials are dis-incentives to develop novel therapies. To overcome that obstacle, we investigated the efficacy of repurposing four FDA approved drugs known to cross the blood brain barrier (BBB), minocycline, propranolol, chlorpromazine, and metformin, to inhibit signaling and metabolism in GBM cells.
Minocycline is a tetracycline class broad spectrum antibiotic commonly used to treat severe acne and other skin infections. Propranolol is a beta blocker type heart medication primarily used to treat high blood pressure and irregular heartbeat. Chlorpromazine is a phenothiazine antipsychotic usually used for schizophrenia. Metformin is the most widely used first-line oral treatment for type-2 diabetes. Based on a literature survey, minocycline is expected to prevent the phosphorylation of STAT3, a transcription factor downstream of EGFR; propranolol is expected to disrupt EGFR trafficking; chlorpromazine is expected to target the PI3K/mTOR/Akt signaling pathway; metformin is believed to exploit vulnerabilities in cancer cell metabolism, as well as upregulate AMPK against the PI3K/mTOR/Akt pathway.
Efficacy of minocycline in inhibiting EGFR-driven STAT3 activation was investigated using western blot analysis. Our results demonstrate that Minocycline effectively inhibits activation of EGFR-driven STAT3 in U373 glioma cells at 100μM. The ability of chlorpromazine to inhibit the PI3K/mTOR/Akt pathway was similarly tested via western blot, which showed inhibition of phosphorylated Akt and S6 at 10μM. Efficacy of propranolol in perturbing EGFR trafficking was evaluated using flow cytometry and immunofluorescence, which failed to depict altered membrane-associated EGFR abundance. Finally, concentration-dependent inhibition of colony formation was tested for all four drugs. Propranolol and minocycline showed potential biphasic stimulatory effects at 10μM, but all drugs inhibited cell growth at 50μM and higher. Efficacy of these drugs in the treatment of GBM is being further evaluated using in vitro neurosphere cultures from patients identified as having the cellular vulnerabilities potentially targeted by these drugs. Successful completion of this project will lead to in vivo efficacy testing of these four drugs in orthotopic GBM PDX models.

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Date Created
  • 2019-05

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Patterns of Sex-Biased Gene Expression in the Human Brain

Description

Schizophrenia is a disease that affects 15.2/100,000 US citizens, with about 0.6-1.9% of the total population being afflicted with some range of severity of the disease. A lot of research

Schizophrenia is a disease that affects 15.2/100,000 US citizens, with about 0.6-1.9% of the total population being afflicted with some range of severity of the disease. A lot of research has been done on the progression of the disease and its differences between males and females; however, the true underlying cause of the disease remains unknown. In the literature, however, there is a lot of indication that a genetic cause for schizophrenia is the primary origin for the disorder. In order to establish a foundation in differential gene expression and isoform expression between males and females, we utilized the Genotype-Tissue Expression Project data set (which contains samples from healthy individuals at their time of death) for the amygdala, anterior cingulate cortex, and frontal cortex. We performed quality control on the data with Trimmomatic and visualized it with FastQC and MultiQC. We then aligned to a sex-specific reference genome with Hisat2. Finally, we performed a differential expression analysis dthrough the limma/voom package with inputs from featureCounts. An isoform level analysis was run on the anterior cingulate cortex with the IsoformSwitchAnalyzeR package. We were able to identify a few differentially expressed genes in the three tissue sites, which included XIST and other highly conserved, Y-linked genes. As for the isoform level analysis, we were able to identify 13 genes with significant levels of differential isoform usage and expression, two of which have clinical relevance (DAB1 and PACRG). These findings will allow for a comparison to be made by future studies on gene expression in brain tissue samples from patients that had been diagnosed with schizophrenia in their life. By identifying any unique genes in these patients, gene therapies can be developed to target and correct any misexpression that may be occurring.

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Date Created
  • 2019-05

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Methods for Detecting Mutations in Non-model Organisms

Description

Next-generation sequencing is a powerful tool for detecting genetic variation. How-ever, it is also error-prone, with error rates that are much larger than mutation rates.
This can make mutation detection

Next-generation sequencing is a powerful tool for detecting genetic variation. How-ever, it is also error-prone, with error rates that are much larger than mutation rates.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.

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Date Created
  • 2020

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DNA methylation and gene expression profiling for Parkinson's biomarker discovery

Description

Parkinson’s disease (PD) is a progressive neurodegenerative disorder, diagnosed late in

the disease by a series of motor deficits that manifest over years or decades. It is characterized by degeneration of

Parkinson’s disease (PD) is a progressive neurodegenerative disorder, diagnosed late in

the disease by a series of motor deficits that manifest over years or decades. It is characterized by degeneration of mid-brain dopaminergic neurons with a high prevalence of dementia associated with the spread of pathology to cortical regions. Patients exhibiting symptoms have already undergone significant neuronal loss without chance for recovery. Analysis of disease specific changes in gene expression directly from human patients can uncover invaluable clues about a still unknown etiology, the potential of which grows exponentially as additional gene regulatory measures are questioned. Epigenetic mechanisms are emerging as important components of neurodegeneration, including PD; the extent to which methylation changes correlate with disease progression has not yet been reported. This collection of work aims to define multiple layers of PD that will work toward developing biomarkers that not only could improve diagnostic accuracy, but also push the boundaries of the disease detection timeline. I examined changes in gene expression, alternative splicing of those gene products, and the regulatory mechanism of DNA methylation in the Parkinson’s disease system, as well as the pathologically related Alzheimer’s disease (AD). I first used RNA sequencing (RNAseq) to evaluate differential gene expression and alternative splicing in the posterior cingulate cortex of patients with PD and PD with dementia (PDD). Next, I performed a longitudinal genome-wide methylation study surveying ~850K CpG methylation sites in whole blood from 189 PD patients and 191 control individuals obtained at both a baseline and at a follow-up visit after 2 years. I also considered how symptom management medications could affect the regulatory mechanism of DNA methylation. In the last chapter of this work, I intersected RNAseq and DNA methylation array datasets from whole blood patient samples for integrated differential analyses of both PD and AD. Changes in gene expression and DNA methylation reveal clear patterns of pathway dysregulation that can be seen across brain and blood, from one study to the next. I present a thorough survey of molecular changes occurring within the idiopathic Parkinson’s disease patient and propose candidate targets for potential molecular biomarkers.

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Date Created
  • 2019

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A search for parent-of-origin effects in the parasitoid jewel wasp Nasonia vitripennis

Description

In most diploid cells, autosomal genes are equally expressed from the paternal and maternal alleles resulting in biallelic expression. However, as an exception, there exists a small number of genes

In most diploid cells, autosomal genes are equally expressed from the paternal and maternal alleles resulting in biallelic expression. However, as an exception, there exists a small number of genes that show a pattern of monoallelic or biased-allele expression based on the allele’s parent-of-origin. This phenomenon is termed genomic imprinting and is an evolutionary paradox. The best explanation for imprinting is David Haig's kinship theory, which hypothesizes that monoallelic gene expression is largely the result of evolutionary conflict between males and females over maternal involvement in their offspring. One previous RNAseq study has investigated the presence of parent-of-origin effects, or imprinting, in the parasitic jewel wasp Nasonia vitripennis (N. vitripennis) and its sister species Nasonia giraulti (N. giraulti) to test the predictions of kinship theory in a non-eusocial species for comparison to a eusocial one. In order to continue to tease apart the connection between social and eusocial Hymenoptera, this study proposed a similar RNAseq study that attempted to reproduce these results in unique samples of reciprocal F1 Nasonia hybrids. Building a pseudo N. giraulti reference genome, differences were observed when aligning RNAseq reads to a N. vitripennis reference genome compared to aligning reads to a pseudo N. giraulti reference. As well, no evidence for parent-of-origin or imprinting patterns in adult Nasonia were found. These results demonstrated a species-of-origin effect. Importantly, the study continued to build a repository of support with the aim to elucidate the mechanisms behind imprinting in an excellent epigenetic model species, as it can also help with understanding the phenomenon of imprinting in complex human diseases.

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Date Created
  • 2019