Matching Items (8)
Filtering by

Clear all filters

136174-Thumbnail Image.png
Description
Schizophrenia affects 1.1% of the population worldwide. Schizophrenia is a complex, multifactorial disorder. Stress can trigger psychotic episodes and exacerbate schizophrenic symptoms. For humans, one gene implicated in stress and schizophrenia in humans is the early growth response 3 (EGR3). Patients with genomic variations in EGR3 have reduced levels of

Schizophrenia affects 1.1% of the population worldwide. Schizophrenia is a complex, multifactorial disorder. Stress can trigger psychotic episodes and exacerbate schizophrenic symptoms. For humans, one gene implicated in stress and schizophrenia in humans is the early growth response 3 (EGR3). Patients with genomic variations in EGR3 have reduced levels of EGR3 in the prefrontal brain region compared with healthy patients. Schizophrenic patients also have less serotonin 2A receptor (5HT2AR), which is coded by the gene Htr2a, in their prefrontal cortex. Mice that are Egr3-deficient also have decreased levels of 5HT2AR, suggesting that Egr3 may be involved in the regulation of 5HT2AR. The purpose of the experiment is to determine if EGR3 binds to the Htr2a gene promoter region by using a Chromatin immunoprecipitation (ChIP) assay. We will use ECS to increase EGR3 expression. Previously we have identified two upstream sites of interest where EGR3 potentially binds to the Htr2a gene, one which is distal and one proximal to the transcription start site. After ECS, increased binding is seen in the Htr2a distal region with EGR3 via the ChIP assay. Increased binding was not observed at either of the promoter sites; however, the t-test comparing the distal site of the ECS and the No ECS groups to have a p-value of 0.056, suggesting that increasing the number of animals (n=7) could possibly give a more accurate representation to test our hypothesis. However, the experiment still suggests increased expression and that EGR3 may bind to the distal site of Htr2a. Keywords: stress, environment, genetics, schizophrenia, EGR3, chromatin immunoprecipitation
ContributorsMishra, Abhinav (Author) / Buetow, Kenneth (Thesis director) / Gallitano, Amelia (Committee member) / Zhao, Xiuli (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / School of Life Sciences (Contributor)
Created2015-05
135041-Thumbnail Image.png
Description
The advent of big data analytics tools and frameworks has allowed for a plethora of new approaches to research and analysis, making data sets that were previously too large or complex more accessible and providing methods to collect, store, and investigate non-traditional data. These tools are starting to be applied

The advent of big data analytics tools and frameworks has allowed for a plethora of new approaches to research and analysis, making data sets that were previously too large or complex more accessible and providing methods to collect, store, and investigate non-traditional data. These tools are starting to be applied in more creative ways, and are being used to improve upon traditional computation methods through distributed computing. Statistical analysis of expression quantitative trait loci (eQTL) data has classically been performed using the open source tool PLINK - which runs on high performance computing (HPC) systems. However, progress has been made in running the statistical analysis in the ecosystem of the big data framework Hadoop, resulting in decreased run time, reduced storage footprint, reduced job micromanagement and increased data accessibility. Now that the data can be more readily manipulated, analyzed and accessed, there are opportunities to use the modularity and power of Hadoop to further process the data. This project focuses on adding a component to the data pipeline that will perform graph analysis on the data. This will provide more insight into the relation between various genetic differences in individuals with breast cancer, and the resulting variation - if any - in gene expression. Further, the investigation will look to see if there is anything to be garnered from a perspective shift; applying tools used in classical networking contexts (such as the Internet) to genetically derived networks.
ContributorsRandall, Jacob Christopher (Author) / Buetow, Kenneth (Thesis director) / Meuth, Ryan (Committee member) / Almalih, Sara (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
155019-Thumbnail Image.png
Description
In species with highly heteromorphic sex chromosomes, the degradation of one of the sex chromosomes can result in unequal gene expression between the sexes (e.g., between XX females and XY males) and between the sex chromosomes and the autosomes. Dosage compensation is a process whereby genes on the sex chromosomes

In species with highly heteromorphic sex chromosomes, the degradation of one of the sex chromosomes can result in unequal gene expression between the sexes (e.g., between XX females and XY males) and between the sex chromosomes and the autosomes. Dosage compensation is a process whereby genes on the sex chromosomes achieve equal gene expression which prevents deleterious side effects from having too much or too little expression of genes on sex chromsomes. The green anole is part of a group of species that recently underwent an adaptive radiation. The green anole has XX/XY sex determination, but the content of the X chromosome and its evolution have not been described. Given its status as a model species, better understanding the green anole genome could reveal insights into other species. Genomic analyses are crucial for a comprehensive picture of sex chromosome differentiation and dosage compensation, in addition to understanding speciation.

In order to address this, multiple comparative genomics and bioinformatics analyses were conducted to elucidate patterns of evolution in the green anole and across multiple anole species. Comparative genomics analyses were used to infer additional X-linked loci in the green anole, RNAseq data from male and female samples were anayzed to quantify patterns of sex-biased gene expression across the genome, and the extent of dosage compensation on the anole X chromosome was characterized, providing evidence that the sex chromosomes in the green anole are dosage compensated.

In addition, X-linked genes have a lower ratio of nonsynonymous to synonymous substitution rates than the autosomes when compared to other Anolis species, and pairwise rates of evolution in genes across the anole genome were analyzed. To conduct this analysis a new pipeline was created for filtering alignments and performing batch calculations for whole genome coding sequences. This pipeline has been made publicly available.
ContributorsRupp, Shawn Michael (Author) / Wilson Sayres, Melissa A (Thesis advisor) / Kusumi, Kenro (Committee member) / DeNardo, Dale (Committee member) / Arizona State University (Publisher)
Created2016
135515-Thumbnail Image.png
Description
Hepatocellular carcinoma (HCC) is the most common type of liver cancer and has been shown to have genetic factors that contribute to cancer susceptibility. These genetic factors can be studied using Genome-Wide association studies (GWAS), which allow for the assessment of associations between specific biologic markers. Through GWAS, associations can

Hepatocellular carcinoma (HCC) is the most common type of liver cancer and has been shown to have genetic factors that contribute to cancer susceptibility. These genetic factors can be studied using Genome-Wide association studies (GWAS), which allow for the assessment of associations between specific biologic markers. Through GWAS, associations can be analyzed to identify genetic components that contribute to the onset of HCC. This study uses an extended version of Pathways of Distinction analysis (PoDA) to identify the subset of SNPs within the Antigen Presentation and Processing Pathway that distinguish cases from controls. Further analysis was performed to explore SNP-SNP association differences between HCC cases and controls using R-squared values and p-values. Three SNPs show significant inter-SNP associations in both HCC cases and controls. Additionally, 4 SNPs showed significant SNP-SNP associations exclusively in the control data set, possibly suggesting that control pathways have a greater degree of genetic regulation and robustness that is lost in carcinogenesis. This result suggests that these SNP associations may contribute to HCC susceptibility.
ContributorsAghili, Ardesher Joshua (Author) / Buetow, Kenneth (Thesis director) / Wilson Sayres, Melissa (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
187436-Thumbnail Image.png
Description
Course-based undergraduate research experiences (CUREs) are strategically designed to advance novel research and integrate future professionals into the scientific community by making relevant discoveries through iteration, communication, and collaboration. With Universities also expanding online undergraduate degree programs that incorporate students who are otherwise unable to attend college, there is a

Course-based undergraduate research experiences (CUREs) are strategically designed to advance novel research and integrate future professionals into the scientific community by making relevant discoveries through iteration, communication, and collaboration. With Universities also expanding online undergraduate degree programs that incorporate students who are otherwise unable to attend college, there is a demand for online asynchronous courses to train online students in authentic research, thereby leading to a more skilled, diverse, and inclusive workforce. In this case-study, a pilot CURE leveraging the data-intensive field of genomics was presented as an inclusive opportunity for asynchronous, online students to increase their research experience without having to commit to in person or extra-curricular assignments. This online CURE was designed to investigate the effects of trimming software on high-throughput sequencing data when analyzing sex differential gene expression. Project-based objectives were developed to asynchronously teach (1) the biology behind the research, (2) the coding needed to conduct the research, and (3) professional development tools to communicate research findings. Course effectiveness was evaluated qualitatively and quantitatively using weekly, open-response progress reports and an assessment administered before and after term completion. This pilot study exhibited that students can be successful in remote research experiences that incorporate channels for communication, bespoke and accessible learning materials, and open-response reports to monitor challenges and coping strategies. In this iteration, remote students demonstrated improved learning outcomes and self-reported improved confidence as researchers. In addition, students gained more realistic expectations to self-assess computational research skill-levels and self-identified adaptive coping strategies that are transferrable to future research projects. Overall, this framework for an online asynchronous CURE effectively taught students computational skills to conduct genomics research in addition to professional skills to transition to and thrive in the workforce.
ContributorsAlarid, Danielle Olga (Author) / Wilson, Melissa A (Thesis advisor) / Buetow, Kenneth (Committee member) / Cooper, Katelyn (Committee member) / Arizona State University (Publisher)
Created2023
132350-Thumbnail Image.png
Description
Cancer is a disease in which abnormal cells divide uncontrollably and destroy body tissue, and currently plagues today’s world. Carcinomas are cancers derived from epithelial cells and include breast and prostate cancer. Breast cancer is a type of carcinoma that forms in breast tissue cells. The tumor cells can be

Cancer is a disease in which abnormal cells divide uncontrollably and destroy body tissue, and currently plagues today’s world. Carcinomas are cancers derived from epithelial cells and include breast and prostate cancer. Breast cancer is a type of carcinoma that forms in breast tissue cells. The tumor cells can be further categorized after testing the cells for the presence of certain molecules. Hormone receptor positive breast cancer includes the tumor cells with receptors that respond to the steroid hormones, estrogen and progesterone, or the peptide hormone, HER2. These forms of cancer respond well to chemotherapy and endocrine therapy. On the other hand, triple negative breast cancer (TNBC) is characterized by the lack of hormone receptor expression and tends to have a worse prognosis in women. Prostate cancer forms in the cells of the prostate gland and has been attributed to mutations in androgen receptor ligand specificity. In a subset of triple negative breast cancer, genetic expression profiling has found a luminal androgen receptor that is dependent on androgen signaling. TNBC has also been found to respond well to enzalutamide, a an androgen receptor inhibitor. As the gene of the androgen receptor, AR, is located on the X chromosome and expressed in a variety of tissues, the responsiveness of TNBC to androgen receptor inhibition could be due to the differential usage of isoforms - different gene mRNA transcripts that produce different proteins. Thus, this study analyzed differential gene expression and differential isoform usage between TNBC cancers – that do and do not express the androgen receptor – and prostate cancer in order to better understand the underlying mechanism behind the effectiveness of androgen receptor inhibition in TNBC. Through the analysis of differential gene expression between the TNBC AR+ and AR- conditions, it was found that seven genes are significantly differentially expressed between the two types of tissues. Genes of significance are AR and EN1, which was found to be a potential prognostic marker in a subtype of TNBC. While some genes are differentially expressed between the TNBC AR+ and AR- tissues, the differences in isoform expression between the two tissues do not reflect the difference in gene expression. We discovered 11 genes that exhibited significant isoform switching between AR+ and AR- TNBC and have been found to contribute to cancer characteristics. The genes CLIC1 and RGS5 have been found to help the rapid, uncontrolled growth of cancer cells. HSD11B2, IRAK1, and COL1Al have been found to contribute to general cancer characteristics and metastasis in breast cancer. PSMA7 has been found to play a role in androgen receptor activation. Finally, SIDT1 and GLYATL1 are both associated with breast and prostate cancers. Overall, through the analysis of differential isoform usage between AR+ and AR- samples, we uncovered differences that were not detected by a gene level differential expression analysis. Thus, future work will focus on analyzing differential gene and isoform expression across all types of breast cancer and prostate cancer to better understand the responsiveness of TNBC to androgen receptor inhibition.
ContributorsDeshpande, Anagha J (Author) / Wilson-Sayres, Melissa (Thesis director) / Buetow, Kenneth (Committee member) / Natri, Heini (Committee member) / School of Human Evolution & Social Change (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The regulation of gene expression, timing, location, and amount of a given project, ultimately affects the cellular structure and function. More broadly, gene regulation is the basis for cellular differentiation and development. However, gene expression is not uniform among individuals and varies greatly between genetic males and females. Males are

The regulation of gene expression, timing, location, and amount of a given project, ultimately affects the cellular structure and function. More broadly, gene regulation is the basis for cellular differentiation and development. However, gene expression is not uniform among individuals and varies greatly between genetic males and females. Males are hemizygous for the X chromosome, whereas females have two X chromosome copies. Contributing to the sex differences in gene expression between males and females are the sex chromosomes, X and Y. Gene expression differences on the autosomes and the X chromosome between males (46, XY) and females (46, XX) may help inform on the mechanisms of sex differences in human health and disease. For example, XX females are more likely to suffer from autoimmune diseases, and genetic XY males are more likely to develop cancer. Characterizing sex-specific gene expression among human tissues will help inform the molecular mechanisms driving sex differences in human health and disease. This dissertation covers a range of critical aspects in gene expression. In chapter 1, I will introduce a method to align RNA-Seq reads to a sex chromosome complement informed reference genome that considers the X and Y chromosomes' shared evolutionary history. Using this approach, I show that more genes are called as sex differentially expressed in several human adult tissues compared to a default reference alignment. In chapter 2, I characterize gene expression in an early formed tissue, the human placenta. The placenta is the DNA of the developing fetus and is typically XY male or XX female. There are well-documented sex differences in pregnancy complications, yet, surprisingly, there is no observable sex difference in expression of innate immune genes, suggesting expression of these genes is conserved. In chapter 3, I investigate gene expression in breast cancer cell lines. Cancer arises in part due to the disruption of gene expression. Here I show 19 tumor suppressor genes become upregulated in response to a synthetic protein treatment. In chapter 4, I discuss gene and allele-specific expression in Nasonia jewel wasp. Chapter 4 is a replication and extension study and discusses the importance of reproducibility.
ContributorsOlney, Kimberly (Author) / Wilson, Melissa A (Thesis advisor) / Hinde, Katherine (Committee member) / Buetow, Kenneth (Committee member) / Banovich, Nicholas (Committee member) / Arizona State University (Publisher)
Created2021
161497-Thumbnail Image.png
Description
The Pathways of Distinction Analysis (PoDA) program calculates relationships between a given group of genes contained within a pathway, and a disease state. It was used here to investigate liver cancer, and to explore how genetic variability may contribute to the different rates of development of the disease in males

The Pathways of Distinction Analysis (PoDA) program calculates relationships between a given group of genes contained within a pathway, and a disease state. It was used here to investigate liver cancer, and to explore how genetic variability may contribute to the different rates of development of the disease in males and females. The goal of the study was to identify germline variation that differs by sex in hepatocellular carcinoma. Using the program, multiple pathways and genes were identified to have significant differences in their relationship to liver cancer in males and females. In animal studies, the genes which were identified using the PoDA analysis have been shown to impact liver cancer, often with different results for males and females. While these genes are often the focus in animal models, they are absent from current Genome Wide Association Studies (GWAS) catalogs for humans. By working to bridge the results of animal studies and human studies, the results help to identify the causes of liver cancer, and more specifically, the reason the disease affects males at much higher rates. The differences in pathways identified to be significant for the two sexes indicate the germline variance may play sex-specific roles in the development of hepatocellular carcinoma. Additionally, these results reinforce the capacity of the PoDA analysis to identify genes that may be missed by more traditional GWAS methods. This study lays the groundwork for further investigations into the identified genes and pathways, and how they behave differently within males and females.
ContributorsOlson, Erik Jon (Author) / Buetow, Kenneth (Thesis advisor) / Wilson, Melissa (Committee member) / Cartwright, Reed (Committee member) / Arizona State University (Publisher)
Created2021