THE JOINT DISTRIBUTION OF FITNESS EFFECTS OF WILD TOMATOES AND A BRIEF INTRODUCTION TO LINKAGE IN DFE INFERENCE

A single mutation by itself is not inherently good or bad, it could be beneficial if given the right context. Thus, a mutation in one environment could be beneficial, while it could be lethal in another environment. We know these factors exist, but most work dealing with the inference of the distribution of fitness effects (DFE) has been limited to one dimension. To address this, in this analysis we used a method for inferring a joint DFE which gives any one mutation two selection coefficients - one for each population. We applied this method of inference to wild tomatoes species involving a demographic history. We dicovered a lower level of correlation between the distributions of these tomatoes than that of humans or drosophila to which this method has been applied before. We also determined correlation coefficients in distinct functional groups between the populations - which yielded a wide range of values across the groups - as well as coefficients between segregated single nucleotide polymorphisms (SNPs) determined by how detrimental they were - these did not show a real difference. Additionally, linkage could have been the potential to alter frequencies of alleles in a way that does not follow the stochastic process of genetic drift, but does not have the full power of natural selection. It is often assumed to be negligible in the inference of the DFE, but is it truly? And how does this translate to its role in the inference of the 2D DFE? And to what extent does this role apply? We then used forward simulators to determine the spectra with assumed linkage so as to compare it with the spectra we inferred