Matching Items (2)
Filtering by

Clear all filters

155158-Thumbnail Image.png
Description
MicroRNAs (miRNAs) are short non-coding RNAs that play key roles during metazoan development, and are frequently misregulated in human disease. MiRNAs regulate gene output by targeting degenerate elements primarily in the 3´ untranslated regions of mRNAs. MiRNAs are often deeply conserved, but have undergone drastic expansions in higher metazoans, leading

MicroRNAs (miRNAs) are short non-coding RNAs that play key roles during metazoan development, and are frequently misregulated in human disease. MiRNAs regulate gene output by targeting degenerate elements primarily in the 3´ untranslated regions of mRNAs. MiRNAs are often deeply conserved, but have undergone drastic expansions in higher metazoans, leading to families of miRNAs with highly similar sequences. The evolutionary advantage of maintaining multiple copies of duplicated miRNAs is not well understood, nor has the distinct functions of miRNA family members been systematically studied. Furthermore, the unbiased and high-throughput discovery of targets remains a major challenge, yet is required to understand the biological function of a given miRNA.

I hypothesize that duplication events grant miRNA families with enhanced regulatory capabilities, specifically through distinct targeting preferences by family members. This has relevance for our understanding of vertebrate evolution, as well disease detection and personalized medicine. To test this hypothesis, I apply a conjunction of bioinformatic and experimental approaches, and design a novel high-throughput screening platform to identify human miRNA targets. Combined with conventional approaches, this tool allows systematic testing for functional targets of human miRNAs, and the identification of novel target genes on an unprecedented scale.

In this dissertation, I explore evolutionary signatures of 62 deeply conserved metazoan miRNA families, as well as the targeting preferences for several human miRNAs. I find that constraints on miRNA processing impact sequence evolution, creating evolutionary hotspots within families that guide distinct target preferences. I apply our novel screening platform to two cancer-relevant miRNAs, and identify hundreds of previously undescribed targets. I also analyze critical features of functional miRNA target sites, finding that each miRNA recognizes surprisingly distinct features of targets. To further explore the functional distinction between family members, I analyze miRNA expression patterns in multiple contexts, including mouse embryogenesis, RNA-seq data from human tissues, and cancer cell lines. Together, my results inform a model that describes the evolution of metazoan miRNAs, and suggests that highly similar miRNA family members possess distinct functions. These findings broaden our understanding of miRNA function in vertebrate evolution and development, and how their misexpression contributes to human disease.
ContributorsWolter, Justin M (Author) / Mangone, Marco (Thesis advisor) / LaBaer, Joshua (Committee member) / Kusumi, Kenro (Committee member) / Anderson, Karen (Committee member) / Arizona State University (Publisher)
Created2016
155234-Thumbnail Image.png
Description
At the interface of developmental biology and evolutionary biology, the very

criteria of scientific knowledge are up for grabs. A central issue is the status of evolutionary genetics models, which some argue cannot coherently be used with complex gene regulatory network (GRN) models to explain the same evolutionary phenomena. Despite those

At the interface of developmental biology and evolutionary biology, the very

criteria of scientific knowledge are up for grabs. A central issue is the status of evolutionary genetics models, which some argue cannot coherently be used with complex gene regulatory network (GRN) models to explain the same evolutionary phenomena. Despite those claims, many researchers use evolutionary genetics models jointly with GRN models to study evolutionary phenomena.

How do those researchers deploy those two kinds of models so that they are consistent and compatible with each other? To address that question, this dissertation closely examines, dissects, and compares two recent research projects in which researchers jointly use the two kinds of models. To identify, select, reconstruct, describe, and compare those cases, I use methods from the empirical social sciences, such as digital corpus analysis, content analysis, and structured case analysis.

From those analyses, I infer three primary conclusions about projects of the kind studied. First, they employ an implicit concept of gene that enables the joint use of both kinds of models. Second, they pursue more epistemic aims besides mechanistic explanation of phenomena. Third, they don’t work to create and export broad synthesized theories. Rather, they focus on phenomena too complex to be understood by a common general theory, they distinguish parts of the phenomena, and they apply models from different theories to the different parts. For such projects, seemingly incompatible models are synthesized largely through mediated representations of complex phenomena.

The dissertation closes by proposing how developmental evolution, a field traditionally focused on macroevolution, might fruitfully expand its research agenda to include projects that study microevolution.
ContributorsElliott, Steve (Author) / Creath, Richard (Thesis advisor) / Laubichler, Manfred D. (Thesis advisor) / Armendt, Brad (Committee member) / Forber, Patrick (Committee member) / Pratt, Stephen (Committee member) / Arizona State University (Publisher)
Created2017