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Advances in sequencing technology have generated an enormous amount of data over the past decade. Equally advanced computational methods are needed to conduct comparative and functional genomic studies on these datasets, in particular tools that appropriately interpret indels within an evolutionary framework. The evolutionary history of indels is complex and

Advances in sequencing technology have generated an enormous amount of data over the past decade. Equally advanced computational methods are needed to conduct comparative and functional genomic studies on these datasets, in particular tools that appropriately interpret indels within an evolutionary framework. The evolutionary history of indels is complex and often involves repetitive genomic regions, which makes identification, alignment, and annotation difficult. While previous studies have found that indel lengths in both deoxyribonucleic acid and proteins obey a power law, probabilistic models for indel evolution have rarely been explored due to their computational complexity. In my research, I first explore an application of an expectation-maximization algorithm for maximum-likelihood training of a codon substitution model. I demonstrate the training accuracy of the expectation-maximization on my substitution model. Then I apply this algorithm on a published 90 pairwise species dataset and find a negative correlation between the branch length and non-synonymous selection coefficient. Second, I develop a post-alignment fixation method to profile each indel event into three different phases according to its codon position. Because current codon-aware models can only identify the indels by placing the gaps between codons and lead to the misalignment of the sequences. I find that the mouse-rat species pair is under purifying selection by looking at the proportion difference of the indel phases. I also demonstrate the power of my sliding-window method by comparing the post-aligned and original gap positions. Third, I create an indel-phase moore machine including the indel rates of three phases, length distributions, and codon substitution models. Then I design a gillespie simulation that is capable of generating true sequence alignments. Next I develop an importance sampling method within the expectation-maximization algorithm that can successfully train the indel-phase model and infer accurate parameter estimates from alignments. Finally, I extend the indel phase analysis to the 90 pairwise species dataset across three alignment methods, including Mafft+sw method developed in chapter 3, coati-sampling methods applied in chapter 4, and coati-max method. Also I explore a non-linear relationship between the dN/dS and Zn/(Zn+Zs) ratio across 90 species pairs.
ContributorsZhu, Ziqi (Author) / Cartwright, Reed A (Thesis advisor) / Taylor, Jay (Committee member) / Wideman, Jeremy (Committee member) / Mangone, Marco (Committee member) / Arizona State University (Publisher)
Created2022
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Persistent cooperation between unrelated conspecifics rarely occurs in mature eusocial insect societies. In this dissertation, I present evidence of non-kin cooperation in the Nearctic honey ant Myrmecocystus mendax. Using microsatellite markers, I show that mature colonies in the Sierra Ancha Mountain of central Arizona contain multiple unrelated matrilines, an observation

Persistent cooperation between unrelated conspecifics rarely occurs in mature eusocial insect societies. In this dissertation, I present evidence of non-kin cooperation in the Nearctic honey ant Myrmecocystus mendax. Using microsatellite markers, I show that mature colonies in the Sierra Ancha Mountain of central Arizona contain multiple unrelated matrilines, an observation that is consistent with primary polygyny. In contrast, similar analyses suggest that colonies in the Chiricahua Mountains of southeastern Arizona are primarily monogynous. These interpretations are consistent with field and laboratory observations. Whereas cooperative colony founding was observed frequently among groups of Sierra Ancha foundresses, founding in the Chiricahua population was restricted to individual foundresses. Furthermore, Sierra Ancha foundresses successfully established incipient laboratory colonies without undergoing queen culling following emergence of the first workers. Multi-queen laboratory Sierra Ancha colonies also produced more workers and repletes than haplometrotic colonies, and when brood raiding was induced between colonies, queens of those with more workers had a higher survival probability.

Microsatellite analyses of additional locations within the M. mendax range suggest that polygyny is also present in some other populations, especially in central-northern Arizona, albeit at lower frequencies than that in the Sierra Anchas. In addition, analyses of multiple types of genetic data, including microsatellites, the mitochondrial barcoding region, and over 2000 nuclear ultra-conserved elements indicate that M. mendax populations within the southwestern U.S. and northwestern Mexico are geographically structured, with strong support for the existence of two or more divergent clades as well as isolation-by-distance within clades. This structure is further shown to correlate with variation in queen number and hair length, a diagnostic taxonomic feature used to distinguish honey ant species.

Together, these findings suggest that regional ecological pressures (e.g. colony density , climate) may have acted on colony founding and social strategy to select for increasing workforce size and, along with genetic drift, have driven geographically isolated M. mendax populations to differentiate genetically and morphologically. The presence of colony fusion in the laboratory and life history traits in honey ant that are influenced by colony size, including repletism, brood raiding, and tournament, support this evolutionary scenario.
ContributorsEriksson, Ti (Author) / Gadau, Jürgen (Thesis advisor) / Taylor, Jay (Thesis advisor) / Fewell, Jennifer (Committee member) / Hӧlldobler, Bert (Committee member) / Johnson, Robert (Committee member) / Pratt, Stephen (Committee member) / Arizona State University (Publisher)
Created2018