Evolutionary Approaches to the Study of Small Noncoding Regulatory RNA Pathways: A Dissertation

Short noncoding RNAs play roles in regulating nearly every biological process, in nearly every organism, yet the exact function and importance of these molecules remains a subject of some debate. In order to gain a better understanding of the contexts in which these regulators have evolved, I have undertaken a variety of approaches to study the evolutionary history of the components that make up these pathways, in the form of two main research efforts. In the first chapter, I have used a combination of population genetics and molecular evolution techniques to show that proteins involved in the piRNA pathway are rapidly evolving, and that different components of the pathway seem to be evolving rapidly on different timescales. These rapidly evolving piRNA pathway proteins can be loosely separated into two groups. The first group appears to evolve quickly at the species level, perhaps in response to transposons that invade across species lines, while the second group appears to evolve quickly at the level of individual populations, perhaps in response to transposons that are paternally present yet novel to the maternal genome. In the second chapter of my research, I have used molecular evolution techniques and carefully devised controls to show that the binding sites of well-conserved miRNAs are among the most slowly changing short motifs in the genome, consistent with a conserved function for these short RNAs in regulatory pathways that are ancient and extremely slow to change. I have additionally discovered a major flaw in an existing approach to motif turnover calculations, which may lead to systematic biases in the published literature toward the false inference of increased regulatory complexity over time. I have implemented a revised approach to motif turnover that addresses this flaw

Recent Progress in Polymorphism-Based Population Genetic Inference

The recent availability of whole-genome sequencing data affords tremendous power for statistical inference. With this, there has been great interest in the development of polymorphism-based approaches for the estimation of population genetic parameters. These approaches seek to estimate, for example, recently fixed or sweeping beneficial mutations, the rate of recurrent positive selection, the distribution of selection coefficients, and the demographic history of the population. Yet despite estimating similar parameters using similar data sets, results between methodologies are far from consistent. We here summarize the current state of the field, compare existing approaches, and attempt to reconcile emerging discrepancies. We also discuss the biases in selection estimators introduced by ignoring the demographic history of the population, discuss the biases in demographic estimators introduced by assuming neutrality, and highlight the important challenge to the field of achieving a true joint estimation procedure to circumvent these confounding effect

Evolutionary dynamics of microRNA target sites across vertebrate evolution.

MicroRNAs (miRNAs) control the abundance of the majority of the vertebrate transcriptome. The recognition sequences, or target sites, for bilaterian miRNAs are found predominantly in the 3' untranslated regions (3'UTRs) of mRNAs, and are amongst the most highly conserved motifs within 3'UTRs. However, little is known regarding the evolutionary pressures that lead to loss and gain of such target sites. Here, we quantify the selective pressures that act upon miRNA target sites. Notably, selective pressure extends beyond deeply conserved binding sites to those that have undergone recent substitutions. Our approach reveals that even amongst ancient animal miRNAs, which exert the strongest selective pressures on 3'UTR sequences, there are striking differences in patterns of target site evolution between miRNAs. Considering only ancient animal miRNAs, we find three distinct miRNA groups, each exhibiting characteristic rates of target site gain and loss during mammalian evolution. The first group both loses and gains sites rarely. The second group shows selection only against site loss, with site gains occurring at a neutral rate, whereas the third loses and gains sites at neutral or above expected rates. Furthermore, mutations that alter the strength of existing target sites are disfavored. Applying our approach to individual transcripts reveals variation in the distribution of selective pressure across the transcriptome and between miRNAs, ranging from strong selection acting on a small subset of targets of some miRNAs, to weak selection on many targets for other miRNAs. miR-20 and miR-30, and many other miRNAs, exhibit broad, deeply conserved targeting, while several other comparably ancient miRNAs show a lack of selective constraint, and a small number, including mir-146, exhibit evidence of rapidly evolving target sites. Our approach adds valuable perspective on the evolution of miRNAs and their targets, and can also be applied to characterize other 3'UTR regulatory motifs

Inferring the Evolutionary History of Primate microRNA Binding Sites: Overcoming Motif Counting Biases

The first microRNAs (miRNAs) were identified as essential, conserved regulators of gene expression, targeting the same genes across nearly all bilaterians. However, there are also prominent examples of conserved miRNAs whose functions appear to have shifted dramatically, sometimes over very brief periods of evolutionary time. To determine whether the functions of conserved miRNAs are stable or dynamic over evolutionary time scales, we have here defined the neutral turnover rates of short sequence motifs in predicted primate 3'-UTRs. We find that commonly used approaches to quantify motif turnover rates, which use a presence/absence scoring in extant lineages to infer ancestral states, are inherently biased to infer the accumulation of new motifs, leading to the false inference of continually increasing regulatory complexity over time. Using a maximum likelihood approach to reconstruct individual ancestral nucleotides, we observe that binding sites of conserved miRNAs in fact have roughly equal numbers of gain and loss events relative to ancestral states and turnover extremely slowly relative to nearly identical permutations of the same motif. Contrary to case studies showing examples of functional turnover, our systematic study of miRNA binding sites suggests that in primates, the regulatory roles of conserved miRNAs are strongly conserved. Our revised methodology may be used to quantify the mechanism by which regulatory networks evolve

Data from: Recurrent and recent selective sweeps in the piRNA pathway

Uncontrolled transposable element (TE) insertions and excisions can cause chromosome breaks and mutations with dramatic deleterious effects. The PIWI interacting RNA (piRNA) pathway functions as an adaptive TE silencing system during germline development. Several essential piRNA pathway proteins appear to be rapidly evolving, suggesting that TEs and the silencing machinery may be engaged in a classical “evolutionary arms race.” Using a variety of molecular evolutionary and population genetic approaches, we find that the piRNA pathway genes rhino, krimper, and aubergine show patterns suggestive of extensive recurrent positive selection across Drosophila species. We speculate that selection on these proteins reflects crucial roles in silencing unfamiliar elements during vertical and horizontal transmission of TEs into naïve populations and species, respectively

Recent Progress in Polymorphism-Based Population Genetic Inference

The recent availability of whole-genome sequencing data affords tremendous power for statistical inference. With this, there has been great interest in the development of polymorphism-based approaches for the estimation of population genetic parameters. These approaches seek to estimate, for example, recently fixed or sweeping beneficial mutations, the rate of recurrent positive selection, the distribution of selection coefficients, and the demographic history of the population. Yet despite estimating similar parameters using similar data sets, results between methodologies are far from consistent. We here summarize the current state of the field, compare existing approaches, and attempt to reconcile emerging discrepancies. We also discuss the biases in selection estimators introduced by ignoring the demographic history of the population, discuss the biases in demographic estimators introduced by assuming neutrality, and highlight the important challenge to the field of achieving a true joint estimation procedure to circumvent these confounding effects