Quantifying evolutionary constraints on B cell affinity maturation

The antibody repertoire of each individual is continuously updated by the evolutionary process of B cell receptor mutation and selection. It has recently become possible to gain detailed information concerning this process through high-throughput sequencing. Here, we develop modern statistical molecular evolution methods for the analysis of B cell sequence data, and then apply them to a very deep short-read data set of B cell receptors. We find that the substitution process is conserved across individuals but varies significantly across gene segments. We investigate selection on B cell receptors using a novel method that side-steps the difficulties encountered by previous work in differentiating between selection and motif-driven mutation; this is done through stochastic mapping and empirical Bayes estimators that compare the evolution of in-frame and out-of-frame rearrangements. We use this new method to derive a per-residue map of selection, which provides a more nuanced view of the constraints on framework and variable regions.Comment: Previously entitled "Substitution and site-specific selection driving B cell affinity maturation is consistent across individuals

Evolution at the Subgene Level: Domain Rearrangements in the Drosophila Phylogeny

Supplementary sections 1–13, tables S1–S10, and figures S1–S9 are available at Molecular Biology and Evolution online (http://www.mbe.oxfordjournals.org/).Although the possibility of gene evolution by domain rearrangements has long been appreciated, current methods for reconstructing and systematically analyzing gene family evolution are limited to events such as duplication, loss, and sometimes, horizontal transfer. However, within the Drosophila clade, we find domain rearrangements occur in 35.9% of gene families, and thus, any comprehensive study of gene evolution in these species will need to account for such events. Here, we present a new computational model and algorithm for reconstructing gene evolution at the domain level. We develop a method for detecting homologous domains between genes and present a phylogenetic algorithm for reconstructing maximum parsimony evolutionary histories that include domain generation, duplication, loss, merge (fusion), and split (fission) events. Using this method, we find that genes involved in fusion and fission are enriched in signaling and development, suggesting that domain rearrangements and reuse may be crucial in these processes. We also find that fusion is more abundant than fission, and that fusion and fission events occur predominantly alongside duplication, with 92.5% and 34.3% of fusion and fission events retaining ancestral architectures in the duplicated copies. We provide a catalog of ∼9,000 genes that undergo domain rearrangement across nine sequenced species, along with possible mechanisms for their formation. These results dramatically expand on evolution at the subgene level and offer several insights into how new genes and functions arise between species.National Science Foundation (U.S.) (Graduate Research Fellowship)National Science Foundation (U.S.) (CAREER award NSF 0644282

Evolutionary systems biology of virus-host interactions

The evolution of virus-host interactions occurs at multiple levels of biological complexity, such as organismal, genetic, and molecular levels. In the first part of this study, the evolution of associations between herpesviruses (HVs) and theirhosts are examined across more than 400 million years. Recent studies have been demonstrating that cospeciations are not always the main event driving HV evolution, asinterhost speciations and host switches also play important roles. The present study shows that more than topological incongruences, mismatches on divergence times are the main source of disagreements between host and viral phylogenies, which reveals host switches, intrahost speciations and viral losses along the evolution of HVs. Herpesviruses have large genomes encoding dozens of proteins. Apart from amino acid substitutions, these viruses also evolve by acquiring, duplicating and losing protein domains. Although the domain repertoires of HVs differ across species, a core set of domains is shared among all of them. This second part of this study reveals that 28 out 41 core domains encoded by HV ancestors are still found in present-day repertoires, which over time were expanded by domain gains and duplications. Distinct evolutionary strategies led HVs to developed very specific domain repertoires, which may explain their host range and tissue tropism, and provide hints on the origins of herpesviruses. Despite the fact that most mutations in proteins are deleterious, few of them end up improving viral fitness and defining how viruses interact with their hosts. By using an integrative approach, the third part of this study investigates the evolution of protein-protein interactions (PPIs) involving the membrane proteins Nectins, and the herpesviral envelope glycoproteins D/G. By means of ancestral sequence reconstruction and homology modelling, ancestral structures of these protein complexes were generated, and analysis of their interaction energies revealed important differences of binding affinity along their evolution.Open Acces

TrAp: a Tree Approach for Fingerprinting Subclonal Tumor Composition

Revealing the clonal composition of a single tumor is essential for identifying cell subpopulations with metastatic potential in primary tumors or with resistance to therapies in metastatic tumors. Sequencing technologies provide an overview of an aggregate of numerous cells, rather than subclonal-specific quantification of aberrations such as single nucleotide variants (SNVs). Computational approaches to de-mix a single collective signal from the mixed cell population of a tumor sample into its individual components are currently not available. Herein we propose a framework for deconvolving data from a single genome-wide experiment to infer the composition, abundance and evolutionary paths of the underlying cell subpopulations of a tumor. The method is based on the plausible biological assumption that tumor progression is an evolutionary process where each individual aberration event stems from a unique subclone and is present in all its descendants subclones. We have developed an efficient algorithm (TrAp) for solving this mixture problem. In silico analyses show that TrAp correctly deconvolves mixed subpopulations when the number of subpopulations and the measurement errors are moderate. We demonstrate the applicability of the method using tumor karyotypes and somatic hypermutation datasets. We applied TrAp to SNV frequency profile from Exome-Seq experiment of a renal cell carcinoma tumor sample and compared the mutational profile of the inferred subpopulations to the mutational profiles of twenty single cells of the same tumor. Despite the large experimental noise, specific co-occurring mutations found in clones inferred by TrAp are also present in some of these single cells. Finally, we deconvolve Exome-Seq data from three distinct metastases from different body compartments of one melanoma patient and exhibit the evolutionary relationships of their subpopulations