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Quantifying transmission intensity and heterogeneity is crucial to ascertain the threat posed by infectious diseases and inform the design of interventions. Methods that jointly estimate the reproduction number R and the dispersion parameter k have however mainly remained limited to the analysis of epidemiological clusters or contact tracing data, whose collection often proves difficult. Here, we show that clusters of identical sequences are imprinted by the pathogen offspring distribution, and we derive an analytical formula for the distribution of the size of these clusters. We develop and evaluate an inference framework to jointly estimate the reproduction number and the dispersion parameter from the size distribution of clusters of identical sequences. We then illustrate its application across a range of epidemiological situations. Finally, we develop a hypothesis testing framework relying on clusters of identical sequences to determine whether a given pathogen genetic subpopulation is associated with increased or reduced transmissibility. Our work provides tools to estimate the reproduction number and transmission heterogeneity from pathogen sequences without building a phylogenetic tree, thus making it easily scalable to large pathogen genome datasets. [ABSTRACT FROM AUTHOR]

Chimeric genes, which form through the genomic fusion of two protein-coding genes, are a significant source of evolutionary novelty in Drosophila melanogaster. However, the propensity of chimeric genes to produce adaptive phenotypic changes is not fully understood. Here, we describe the chimeric gene Quetzalcoatl (Qtzl; CG31864), which formed in the recent past and swept to fixation in D. melanogaster. Qtzl arose through a duplication on chromosome 2L that united a portion of the mitochondrially targeted peptide CG12264 with a segment of the polycomb gene escl. The 3' segment of the gene, which is derived from escl, is inherited out of frame, producing a unique peptide sequence. Nucleotide diversity is drastically reduced and site frequency spectra are significantly skewed surrounding the duplicated region, a finding consistent with a selective sweep on the duplicate region containing Qtzl. Qtzl has an expression profile that largely resembles that of escl, with expression in early pupae, adult females, and male testes. However, expression patterns appear to have been decoupled from both parental genes during later embryonic development and in head tissues of adult males, indicating that Qtzl has developed a distinct regulatory profile through the rearrangement of different 5' and 3' regulatory domains. Furthermore, misexpression of Qtzl suppresses defects in the formation of the neuromuscular junction in larvae, demonstrating that Qtzl can produce phenotypic effects in cells. Together, these results show that chimeric genes can produce structural and regulatory changes in a single mutational step and may be a major factor in adaptive evolution. adaptation | new genes | regulatory evolution | frameshifts doi/ 10.1073/pnas.1006503107

It is generally assumed that stabilizing selection promoting a phenotypic optimum acts to shape variation in quantitative traits across individuals and species. Although gene expression represents an intensively studied molecular phenotype, the extent to which stabilizing selection limits divergence in gene expression remains contentious. In this study, we present a theoretical framework for the study of stabilizing and directional selection using data from between-species divergence of continuous traits. This framework, based upon Brownian motion, is analytically tractable and can be used in maximum-likelihood or Bayesian parameter estimation. We apply this model to gene-expression levels in 7 species of Drosophila, and find that gene-expression divergence is substantially curtailed by stabilizing selection. However, we estimate the selective effect, s, of gene-expression change to be very small, approximately equal to Ns for a change of one standard deviation, where N is the effective population size. These findings highlight the power of natural selection to shape phenotype, even when the fitness effects of mutations are in the nearly neutral range. evolution | nearly neutral | Ornstein-Uhlenbeck | phenotypic optima

Human influenza virus rapidly accumulates mutations in its major surface protein hemagglutinin (HA). The evolutionary success of influenza virus lineages depends on how these mutations affect HA's functionality and antigenicity. Here we experimentally measure the effects on viral growth in cell culture of all single amino acid mutations to the HA from a recent human H3N2 influenza virus strain. We show that mutations that are measured to be more favorable for viral growth are enriched in evolutionarily successful H3N2 viral lineages relative to mutations that are measured to be less favorable for viral growth. Therefore, despite the well-known caveats about cell-culture measurements of viral fitness, such measurements can still be informative for understanding evolution in nature.We also compare our measurements for H3 HA to similar data previously generated for a distantly related H1 HA and find substantial differences in which amino acids are preferred at many sites. For instance, the H3 HA has less disparity in mutational tolerance between the head and stalk domains than the H1 HA. Overall, our work suggests that experimental measurements of mutational effects can be leveraged to help understand the evolutionary fates of viral lineages in nature-but only when the measurements are made on a viral strain similar to the ones being studied in nature. [ABSTRACT FROM AUTHOR]

Human seasonal influenza viruses evolve rapidly, enabling the virus population to evade immunity and reinfect previously infected individuals. Antigenic properties are largely determined by the surface glycoprotein hemagglutinin (HA), and amino acid substitutions at exposed epitope sites in HA mediate loss of recognition by antibodies. Here, we show that antigenic differences measured through serological assay data are well described by a sum of antigenic changes along the path connecting viruses in a phylogenetic tree. This mapping onto the tree allows prediction of antigenicity from HA sequence data alone. The mapping can further be used to make predictions about the makeup of the future A(H3N2) seasonal influenza virus population, and we compare predictions between models with serological and sequence data. To make timely model output readily available, we developed a web browser-based application that visualizes antigenic data on a continuously updated phylogeny. [ABSTRACT FROM AUTHOR]