Joseph P. Bielawski

Statistical methods for detecting molecular adaptation.

Abstract The past few years have seen the development of powerful statistical methods for detecting adaptive molecular evolution. These methods compare synonymous and nonsynonymous substitution rates in protein-coding genes, and regard a nonsynonymous rate elevated above the synonymous rate as evidence for darwinian selection. Numerous cases of molecular adaptation are being identified in various systems from viruses to humans. Although previous analyses averaging rates over sites and time have little power, recent methods designed to detect positive selection at individual sites and lineages have been successful. Here, we summarize recent statistical methods for detecting molecular adaptation, and discuss their limitations and possible improvements.

Ancestral polymorphism and adaptive evolution in the trichothecene mycotoxin gene cluster of phytopathogenic Fusarium

Filamentous fungi within the Fusarium graminearum species complex (Fg complex) are the primary etiological agents of Fusarium head blight (scab) of wheat and barley. Scab is an economically devastating plant disease that greatly limits grain yield and quality. In addition, scabby grain is often contaminated with trichothecene mycotoxins that act as virulence factors on some hosts, and pose a serious threat to animal health and food safety. Strain-specific differences in trichothecene metabolite profiles (chemotypes) are not well correlated with the Fg complex phylogeny based on genealogical concordance at six single-copy nuclear genes. To examine the basis for this discord between species and toxin evolution, a 19-kb region of the trichothecene gene cluster was sequenced in 39 strains chosen to represent the global genetic diversity of species in the Fg complex and four related species of Fusarium. Phylogenetic analyses demonstrated that polymorphism within these virulence-associated genes is transspecific and appears to have been maintained by balancing selection acting on chemotype differences that originated in the ancestor of this important group of plant pathogens. Chemotype-specific differences in selective constraint and evidence of adaptive evolution within trichothecene genes are also reported.

A maximum likelihood method for detecting functional divergence at individual codon sites, with application to gene family evolution

The tailoring of existing genetic systems to new uses is called genetic co-option. Mechanisms of genetic co-option have been difficult to study because of difficulties in identifying functionally important changes. One way to study genetic co-option in protein-coding genes is to identify those amino acid sites that have experienced changes in selective pressure following a genetic co-option event. In this paper we present a maximum likelihood method useful for measuring divergent selective pressures and identifying the amino acid sites affected by divergent selection. The method is based on a codon model of evolution and uses the nonsynonymous-to-synonymous rate ratio (ω) as a measure of selection on the protein, with ω = 1, <1, and >1 indicating neutral evolution, purifying selection, and positive selection, respectively. The model allows variation in ω among sites, with a fraction of sites evolving under divergent selective pressures. Divergent selection is indicated by different ω’s between clades, such as between paralogous clades of a gene family. We applied the codon model to duplication followed by functional divergence of (i) the ε and γ globin genes and (ii) the eosinophil cationic protein (ECP) and eosinophil-derived neurotoxin (EDN) genes. In both cases likelihood ratio tests suggested the presence of sites evolving under divergent selective pressures. Results of the ε and γ globin analysis suggested that divergent selective pressures might be a consequence of a weakened relationship between fetal hemoglobin and 2,3-diphosphoglycerate. We suggest that empirical Bayesian identification of sites evolving under divergent selective pressures, combined with structural and functional information, can provide a valuable framework for identifying and studying mechanisms of genetic co-option. Limitations of the new method are discussed.

Maximum likelihood methods for detecting adaptive evolution after gene duplication.

The rapid accumulation of genomic sequences in public databases will finally allow large scale studies of gene family evolution, including evaluation of the role of positive Darwinian selection following a duplication event. This will be possible because recent statistical methods of comparing synonymous and nonsynonymous substitution rates permit reliable detection of positive selection at individual amino acid sites and along evolutionary lineages. Here, we summarize maximum-likelihood based methods, and present a framework for their application to analysis of gene families. Using these methods, we investigated the role of positive Darwinian selection in the ECP-EDN gene family of primates and the Troponin C gene family of vertebrates. We also comment on the limitations of these methods and discuss directions for further improvements.

Widespread adaptive evolution in the human immunodeficiency virus type 1 genome.

We investigated variable selective pressures among amino acid sites in HIV-1 genes. Selective pressure at the amino acid level was measured by using the nonsynonymous/synonymous substitution rate ratio (ω = dN/dS). To identify amino acid sites under positive selection with ω > 1, we applied maximum likelihood models that allow variable ω ratios among sites to analyze genomic sequences of 26 HIV-1 lineages including subtypes A, B, and C. Likelihood ratio tests detected sites under positive selection in each of the major genes in the genome: env, gag, pol, vif, and vpr. Positive selection was also detected in nef, tat, and vpu, although those genes are very small. The majority of positive selection sites is located in gp160. Positive selection was not detected if ω was estimated as an average across all sites, indicating the lack of power of the averaging approach. Candidate positive selection sites were mapped onto the available protein tertiary structures and immunogenic epitopes. We measured the physiochemical properties of amino acids and found that those at positive selection sites were more diverse than those at variable sites. Furthermore, amino acid residues at exposed positive selection sites were more physiochemically diverse than at buried positive selection sites. Our results demonstrate genomewide diversifying selection acting on the HIV-1.

Gene conversion and functional divergence in the beta-globin gene family

Different models of gene family evolution have been proposed to explain the mechanism whereby gene copies created by gene duplications are maintained and diverge in function. Ohta proposed a model which predicts a burst of nonsynonymous substitutions following gene duplication and the preservation of duplicates through positive selection. An alternative model, the duplication–degeneration–complementation (DDC) model, does not explicitly require the action of positive Darwinian selection for the maintenance of duplicated gene copies, although purifying selection is assumed to continue to act on both copies. A potential outcome of the DDC model is heterogeneity in purifying selection among the gene copies, due to partitioning of subfunctions which complement each other. By using the dN/dS (ω) rate ratio to measure selection pressure, we can distinguish between these two very different evolutionary scenarios. In this study we investigated these scenarios in the β-globin family of genes, a textbook example of evolution by gene duplication. We assembled a comprehensive dataset of 72 vertebrate β-globin sequences. The estimated phylogeny suggested multiple gene duplication and gene conversion events. By using different programs to detect recombination, we confirmed several cases of gene conversion and detected two new cases. We tested evolutionary scenarios derived from Ohta’s model and the DDC model by examining selective pressures along lineages in a phylogeny of β-globin genes in eutherian mammals. We did not find significant evidence for an increase in the ω ratio following major duplication events in this family. However, one exception to this pattern was the duplication of γ-globin in simian primates, after which a few sites were identified to be under positive selection. Overall, our results suggest that following gene duplications, paralogous copies of β-globin genes evolved under a nonepisodic process of functional divergence.

Bayesian Inference of Microbial Community Structure from Metagenomic Data Using BioMiCo

Microbial samples taken from an environment often represent mixtures of communities, where each community is composed of overlapping assemblages of species. Such data represent a serious analytical challenge, as the community structures will be present as complex mixtures, there will be very large numbers of component species, and the species abundance will often be sparse over samples. The structure and complexity of these samples will vary according to both biotic and abiotic factors, and classical methods of data analysis will have a limited value in this setting. A novel Bayesian modeling framework, called BioMiCo, was developed to meet this challenge. BioMiCo takes abundance data derived from environmental DNA, and models each sample by a two-level mixture, where environmental OTUs contribute community structures, and those structures are related to the known biotic and abiotic features of each sample. The model is constrained by Dirichlet priors, which induces compact structures, minimizes variance, and maximizes model interpretability. BioMiCo is trained on a portion of the data, and once trained a BioMiCo model can be employed to make predictions about the features of new samples. This chapter provides a set of protocols that illustrate the application of BioMiCo to real inference problems. Each protocol is designed around the analysis of a real dataset, which was carefully chosen to illustrate specific aspects of real data analysis. With these protocols, users of BioMiCo will be able to undertake basic research into the properties of complex microbial systems, as well as develop predictive models for applied microbiomics.

DOP007 Crohn's disease exclusion diet and partial enteral nutrition (CDED+PEN) vs exclusive enteral nutrition (EEN). Microbiome changes of a randomized clinical trial (RCT) in pediatric CD: remission is associated with similar structural + functional profiles

Background: EEN is able to induce remission in CD patients, but can be difficult to maintain. A novel dietary intervention that combines partial enteral nutrition with an exclusion diet, that excludes foods proposed to trigger dysbiosis and inflammation (CDED+PEN) has been shown effective. We aim to