Post-embryonic hourglass patterns mark ontogenetic transitions in plant development

Post-embryonic hourglass patterns mark ontogenetic transitions in plant development

Hajk-Georg Drost, Julia Bellstaedt, Diarmuid O’Maoileidigh, Anderson Silva, Alexander Gabel, Claus Weinholdt, Patrick Ryan, Bas Dekkers, Leonie Bentsink, Henk Hilhorst, Wilco Ligterink, Frank Wellmer, Ivo Grosse, Marcel Quint
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A Relaxed Drift Diffusion Model for Phylogenetic Trait Evolution

A Relaxed Drift Diffusion Model for Phylogenetic Trait Evolution
Mandev S. Gill, Lam Si Tung Ho, Guy Baele, Philippe Lemey, Marc A. Suchard

Understanding the processes that give rise to quantitative measurements associated with molecular sequence data remains an important issue in statistical phylogenetics. Examples of such measurements include geographic coordinates in the context of phylogeography and phenotypic traits in the context of comparative studies. A popular approach is to model the evolution of continuously varying traits as a Brownian diffusion process. However, standard Brownian diffusion is quite restrictive and may not accurately characterize certain trait evolutionary processes. Here, we relax one of the major restrictions of standard Brownian diffusion by incorporating a nontrivial estimable drift into the process. We introduce a relaxed drift diffusion model for the evolution of multivariate continuously varying traits along a phylogenetic tree via Brownian diffusion with drift. Notably, the relaxed drift model accommodates branch-specific variation of drift rates while preserving model identifiability. We implement the relaxed drift model in a Bayesian inference framework to simultaneously reconstruct the evolutionary histories of molecular sequence data and associated multivariate continuous trait data, and provide tools to visualize evolutionary reconstructions. We illustrate our approach in three viral examples. In the first two, we examine the spatiotemporal spread of HIV-1 in central Africa and West Nile virus in North America and show that a relaxed drift approach uncovers a clearer, more detailed picture of the dynamics of viral dispersal than standard Brownian diffusion. Finally, we study antigenic evolution in the context of HIV-1 resistance to three broadly neutralizing antibodies. Our analysis reveals evidence of a continuous drift at the HIV-1 population level towards enhanced resistance to neutralization by the VRC01 monoclonal antibody over the course of the epidemic.

Early Recognition of Emerging Flu Strain Clusters

Early Recognition of Emerging Flu Strain Clusters
A. Li, J. C. Phillips, M. W. Deem

Minimizing time delays in manufacturing vaccines appropriate to rapidly mutating viruses is the key step for improving vaccine effectiveness. The vaccine for the H3N2 flu type has failed for the last two years (~ 15% effective). Here we summarize the state of the predictive art and report the most current results for H3N2 flu vaccine design. Using a 2006 model of dimensional reduction of viral mutational complexity, we show that this model can reduce vaccine time delays by a year or more in some cases.

Purifying selection and drift, not life history or RNAi, determine transposable element evolution

Purifying selection and drift, not life history or RNAi, determine transposable element evolution

Amir Szitenberg, Soyeon Cha, Charles H Opperman, David M Bird, Mark Blaxter, David H Lunt

Whole-genome sequencing uncovers cryptic and hybrid species among Atlantic and Pacific cod-fish

Whole-genome sequencing uncovers cryptic and hybrid species among Atlantic and Pacific cod-fish

Katrín Halldórsdóttir, Einar Árnason

Genomic Bayesian Prediction Model for Count Data with Genotype × Environment Interaction

Genomic Bayesian Prediction Model for Count Data with Genotype × Environment Interaction

Abelardo Montesinos-Lopez, Osval Montesinos-Lopez, Jose Crossa, Juan Burgueno, Kent Eskridge, Esteban Falconi-Castillo, Xingyao He, Pawan Singh, Karen Cichy

A reference panel of 64,976 haplotypes for genotype imputation

A reference panel of 64,976 haplotypes for genotype imputation

Shane McCarthy, Sayantan Das, Warren Kretzschmar, Richard Durbin, Goncalo Abecasis, Jonathan Marchini