On Gene Age, Gene Origins, and Evolutionary Trends

Abstract

Novel genes are a contributor to species diversity and specialization. Determining when, how, and in which lineages novel genes formed is a major challenge in evolutionary biology. A key step in this process is identifying novel genes. Phylostratigraphy is a method developed to identify novel sequences. This method relies on the detection of homologs, existing sequences in different species which derive from a common ancestral sequence. This method uses homology detection programs, such as the BLAST suite of algorithms, to identify genes that are specific to a lineage and infer from there when this sequence arose. When done for large numbers of sequences, they can be grouped by age and trends with gene age can be identified. This methodology assumes that homology detection error—the failure of a homology detection program to accurately detect homologs—is negligible. I show that this is a faulty assumption. I demonstrate that homology detection error is more common than previously believed, and that it is non-random. Homology detection error is biased in a way that may produce spurious biological trends. I demonstrate that this kind of error has major influence on theories of gene emergence. I further develop a methodology which addresses and mitigates the effects of error on phylostratigraphy, and use this method to approach phylostratigraphic problems and produce novel biological insight. In total, this thesis demonstrates a major problem in phylostratigraphic methodology, produces a new methodology which addresses these limitations, and applies this methodology to investigate problems of gene age, the mechanisms by which genes emerge, and trends in evolution.