Macroecology of the Genome and Co-occurrence Patterns in Genomic Communities

Macroecology assesses species distributions and abundances from a broad-scale approach across large taxonomic, spatial, or temporal scales. This perspective can provide important insights into how transposable elements (TEs) are distributed across and within genomes. In this chapter, I examined TE abundance distributions in seventy mammalian genomes by fitting rank-abundance distributions to four common distribution models: the broken-stick, lognormal, log series, and geometric series. All genomic communities best fit the lognormal model when considering all TEs and older TEs. Most middle-aged and younger TE communities also fit the lognormal model, with a few genomic communities fitting the log series and geometric series models best. Many traditional ecologists use deviations from the lognormal as an indicator of disturbance (Matthews & Whittaker, 2015). Out of the 280 genomic communities (70 genomes with four age classes), 261 best fit the lognormal model. One possibility is that TEs in these communities have reached a balance with host defense strategies and TE counter-defense mechanisms. Since the lognormal distribution was the best fit for most genomic communities, future research should investigate what processes (if any) are contributing to the structural differences in communities that best fit the log series or geometric series. I also tested for correlations between TE abundance indices (diversity, skewness, and kurtosis) with host life-history traits (host body-size, longevity, and diet). After correcting for phylogenetic autocorrelation, only diet had a significant relationship with abundance indices with insectivores having lower diversity that other consumers. This could be due to horizontal transfer of TEs from consuming large amounts of insects. In the next section, I analyzed co-occurrence patterns in genomic communities. Co-occurrence patterns can indicate what mechanisms could potentially be structuring communities. Significant aggregation patterns in which two species are found more frequently than what expected by random chance can be caused by mutualism, facilitation, or having similar habitat preferences. Segregation patterns where two species are found together less than expected are structured by competition, dispersal limitations, or differences in habitat preferences. To understand what processes could be structuring genomic communities, I analyzed co-occurrence patterns for TE communities across sixty-three diverse mammalian genomes. The majority of TE pairs were randomly distributed in relation to each other, yet many nonrandom patterns were identified. For nonrandom TE pairs, I examined differences in genomic environmental variables that influence TE insertions, specifically guanine-cytosine content, TE density, and gene density, to determine whether these patterns were due to habitat preferences. Approximately 1% of nonrandom patterns were not linked to differences in genomic habitat preferences. Aggregation patterns may result from the tendency of some TEs to insert into other elements, a phenomenon known as nesting. In the case of segregated patterns, this may be due to dispersal limitations, particularly for DNA transposons, which are restricted in dispersal distance because of their insertion mechanisms. Another possibility is that some TEs might be competing for genomic space, wherein an element could alter the genomic landscape through histone modification or three-dimensional folding to prevent a competitor from inserting nearby (Choudhary et al., 2023; Ye et al., 2005). More detailed research into the insertion mechanisms of some of these segregating pairs may provide insight into whether competition is actually occurring. In the final chapter, I analyzed the genetic diversity and population structure of the endangered bat, Myotis septentrionalis, which has suffered severe population declines due to a fungal infection known as white-nose syndrome (WNS). Samples were taken from 81 individuals across seven states: Kentucky, Louisiana, Michigan, Minnesota, North Carolina, Oklahoma, and Wisconsin. All individuals exhibited similar genetic diversity and no discernible population structure. This is potentially due to the bats’ vagility, male dispersal, and random mating. All samples were collected either before the WNS invasion or at its early stages; therefore, WNS likely had not yet impacted the genetics of this species. This will serve as an important baseline for comparison in future studies to determine how WNS affects the population genetics of bats in North America.