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- All Subjects: Transcriptomics
- Creators: Keats, Jonathan
- Creators: Kellom, Matthew
Description
The greatest barrier to understanding how life interacts with its environment is the complexity in which biology operates. In this work, I present experimental designs, analysis methods, and visualization techniques to overcome the challenges of deciphering complex biological datasets. First, I examine an iron limitation transcriptome of Synechocystis sp. PCC 6803 using a new methodology. Until now, iron limitation in experiments of Synechocystis sp. PCC 6803 gene expression has been achieved through media chelation. Notably, chelation also reduces the bioavailability of other metals, whereas naturally occurring low iron settings likely result from a lack of iron influx and not as a result of chelation. The overall metabolic trends of previous studies are well-characterized but within those trends is significant variability in single gene expression responses. I compare previous transcriptomics analyses with our protocol that limits the addition of bioavailable iron to growth media to identify consistent gene expression signals resulting from iron limitation. Second, I describe a novel method of improving the reliability of centroid-linkage clustering results. The size and complexity of modern sequencing datasets often prohibit constructing distance matrices, which prevents the use of many common clustering algorithms. Centroid-linkage circumvents the need for a distance matrix, but has the adverse effect of producing input-order dependent results. In this chapter, I describe a method of cluster edge counting across iterated centroid-linkage results and reconstructing aggregate clusters from a ranked edge list without a distance matrix and input-order dependence. Finally, I introduce dendritic heat maps, a new figure type that visualizes heat map responses through expanding and contracting sequence clustering specificities. Heat maps are useful for comparing data across a range of possible states. However, data binning is sensitive to clustering cutoffs which are often arbitrarily introduced by researchers and can substantially change the heat map response of any single data point. With an understanding of how the architectural elements of dendrograms and heat maps affect data visualization, I have integrated their salient features to create a figure type aimed at viewing multiple levels of clustering cutoffs, allowing researchers to better understand the effects of environment on metabolism or phylogenetic lineages.
ContributorsKellom, Matthew (Author) / Raymond, Jason (Thesis advisor) / Anbar, Ariel (Committee member) / Elser, James (Committee member) / Shock, Everett (Committee member) / Walker, Sarah (Committee member) / Arizona State University (Publisher)
Created2017
Description
Multiple myeloma is a genetically heterogeneous disease, which can be divided into several genetic subtypes based upon gene expression profiles and chromosomal abnormalities. Unlike older techniques employed in myeloma research, such as cytogenetics, FISH, and microarray technologies, RNA sequencing offers a unique approach to examine the aforementioned genetic characteristics in that it allows for gene expression profiling and the detection of novel fusion transcripts arising from chromosomal rearrangements. This study utilized RNA sequencing to analyze the transcriptomes of 84 multiple myeloma patients and 69 human myeloma cell lines. FCHSD2 was found to be involved in five novel fusion events along with known oncogenes, MMSET and MYC, as well as three previously unreported genes in myeloma, including CHMP4B, NCF2, and CARNS1. An analysis of FCHSD2 expression within myeloma cell lines indicated that it is highly expressed in comparison to other tissues, suggesting that FCHSD2 translocations could lead to promoter replacement events in which the expression of partnering genes is dysregulated. The presence of the five FCHSD2 hybrid transcripts was confirmed by reverse transcription-PCR and Sanger sequencing. Overexpression of the FCHSD2 fusion transcripts in HEK293 cells resulted in the production of N-terminally truncated fusion partner proteins and a novel FCHSD2-CARNS1 fusion protein.
ContributorsMurray, Christopher William (Author) / Wilson-Rawls, Jeanne (Thesis director) / Carpten, John (Committee member) / Keats, Jonathan (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2014-05