Assessing The Monophyly Of Red Algae And Green Plants Via Core Conserved Informational Genes
For well over a century the existence of a monophyletic relationship between red algae and green plants has been debated. Many scholars have sought to address this issue, however, a consistent solution to the problem has not been found. Addressing a monophyletic relationship of red algae and green plants is important for understanding early eukaryotic evolution. Elucidating this relationship will allow for a more in depth evaluation of the origin and spread of photosynthesis in eukaryotes, and will further develop an understanding of the evolution of primary producers, which are of paramount importance in supporting the earth's ecosystems. The goal of this project is to apply a method that provides an accurate and consistent way to classify more ancient phylogenetic relationships. Although a great deal of work has been done in the past on this question, the need for a more consistent method that is minimally affected by phylogenetic artifacts has never been greater. This is because of the rapid increase in the amount of available sequence data, as well as the number of new taxa that are being sequenced. By providing a more accurate methodology for investigating broad scale relationships we hope to ameliorate some of the issues seen previously in evaluations of deep phylogenetic relationships. The first goal of this project was to develop a set of core conserved genes related to information processing in cells that span the broad range of eukaryotic life to circumvent known issues from previous studies where selection of markers was problematic. These genes perform highly conserved functions in the cell and, therefore, are less likely to be negatively influenced by problems that create phylogenetic discontinuities. For example, all living organisms must transcribe and translate their genes into proteins. As such, the transcriptional and transitional machinery required to accomplish this task is highly conserved across all forms of life. Although they are responsible for functioning of the central dogma of molecular biology, this research shows that universal conservation of many of these genes across the broad range of eukaryotic life is uncertain. Thorough analyses of 47 conserved genes indicated that the most reliable markers for ancient phylogenetic inferences are core subunits of DNA-dependent RNA polymerases. Genes encoding the two largest subunits of each of three eukaryotic RNA polymerases were recovered from a list of organisms that span eukaryotic diversity via BLAST searches of two major bioinformatics databases National Center for Biotechnology Information (NCBI) and the Department of Energy's Joint Genomics Institute (JGI). The sequences were aligned using multiple sequence alignment software packages, edited by hand, and then used as input into phylogenetic analysis programs. The resulting alignments recovered a polyphyletic relationship among red algae and green plants. Statistical analyses were applied to each tree, allowing for a clear determination that polyphyly was strongly supported by these data. The further hope is that this project will provide a method that is useful, not only for addressing red/green monophyletic issues, but also for future problematic phylogenies.
Perry, Justin. (January 2015). Assessing The Monophyly Of Red Algae And Green Plants Via Core Conserved Informational Genes (Master's Thesis, East Carolina University). Retrieved from the Scholarship. (http://hdl.handle.net/10342/5026.)
Perry, Justin. Assessing The Monophyly Of Red Algae And Green Plants Via Core Conserved Informational Genes. Master's Thesis. East Carolina University, January 2015. The Scholarship. http://hdl.handle.net/10342/5026. April 26, 2019.
Perry, Justin, “Assessing The Monophyly Of Red Algae And Green Plants Via Core Conserved Informational Genes” (Master's Thesis., East Carolina University, January 2015).
Perry, Justin. Assessing The Monophyly Of Red Algae And Green Plants Via Core Conserved Informational Genes [Master's Thesis]. Greenville, NC: East Carolina University; January 2015.
East Carolina University