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Cryo-EM structures of herpes simplex virus type 1 portal vertex and packaged genome.
Herpesviruses are enveloped viruses that are prevalent in the human population and are responsible for diverse pathologies, including cold sores, birth defects and cancers. They are characterized by a highly pressurized pseudo-icosahedral capsid-with triangulation number (T) equal to 16-encapsidating a tightly packed double-stranded DNA (dsDNA) genome1-3. A key process in the herpesvirus life cycle involves the recruitment of an ATP-driven terminase to a unique portal vertex to recognize, package and cleave concatemeric dsDNA, ultimately giving rise to a pressurized, genome-containing virion4,5. Although this process has been studied in dsDNA phages6-9-with which herpesviruses bear some similarities-a lack of high-resolution in situ structures of genome-packaging machinery has prevented the elucidation of how these multi-step reactions, which require close coordination among multiple actors, occur in an integrated environment. To better define the structural basis of genome packaging and organization in herpes simplex virus type 1 (HSV-1), we developed sequential localized classification and symmetry relaxation methods to process cryo-electron microscopy (cryo-EM) images of HSV-1 virions, which enabled us to decouple and reconstruct hetero-symmetric and asymmetric elements within the pseudo-icosahedral capsid. Here we present in situ structures of the unique portal vertex, genomic termini and ordered dsDNA coils in the capsid spooled around a disordered dsDNA core. We identify tentacle-like helices and a globular complex capping the portal vertex that is not observed in phages, indicative of herpesvirus-specific adaptations in the DNA-packaging process. Finally, our atomic models of portal vertex elements reveal how the fivefold-related capsid accommodates symmetry mismatch imparted by the dodecameric portal-a longstanding mystery in icosahedral viruses-and inform possible DNA-sequence recognition and headful-sensing pathways involved in genome packaging. This work showcases how to resolve symmetry-mismatched elements in a large eukaryotic virus and provides insights into the mechanisms of herpesvirus genome packaging
Genome-scale phylogenetic analysis finds extensive gene transfer among Fungi
Although the role of lateral gene transfer is well recognized in the
evolution of bacteria, it is generally assumed that it has had less influence
among eukaryotes. To explore this hypothesis we compare the dynamics of genome
evolution in two groups of organisms: Cyanobacteria and Fungi. Ancestral
genomes are inferred in both clades using two types of methods. First, Count, a
gene tree unaware method that models gene duplications, gains and losses to
explain the observed numbers of genes present in a genome. Second, ALE, a more
recent gene tree-aware method that reconciles gene trees with a species tree
using a model of gene duplication, loss, and transfer. We compare their merits
and their ability to quantify the role of transfers, and assess the impact of
taxonomic sampling on their inferences. We present what we believe is
compelling evidence that gene transfer plays a significant role in the
evolution of Fungi
Viral population estimation using pyrosequencing
The diversity of virus populations within single infected hosts presents a
major difficulty for the natural immune response as well as for vaccine design
and antiviral drug therapy. Recently developed pyrophosphate based sequencing
technologies (pyrosequencing) can be used for quantifying this diversity by
ultra-deep sequencing of virus samples. We present computational methods for
the analysis of such sequence data and apply these techniques to pyrosequencing
data obtained from HIV populations within patients harboring drug resistant
virus strains. Our main result is the estimation of the population structure of
the sample from the pyrosequencing reads. This inference is based on a
statistical approach to error correction, followed by a combinatorial algorithm
for constructing a minimal set of haplotypes that explain the data. Using this
set of explaining haplotypes, we apply a statistical model to infer the
frequencies of the haplotypes in the population via an EM algorithm. We
demonstrate that pyrosequencing reads allow for effective population
reconstruction by extensive simulations and by comparison to 165 sequences
obtained directly from clonal sequencing of four independent, diverse HIV
populations. Thus, pyrosequencing can be used for cost-effective estimation of
the structure of virus populations, promising new insights into viral
evolutionary dynamics and disease control strategies.Comment: 23 pages, 13 figure
Using Avida to test the effects of natural selection on phylogenetic reconstruction methods
Phylogenetic trees group organisms by their ancestral relationships. There are a number of distinct algorithms used to reconstruct these trees from molecular sequence data, but different methods sometimes give conflicting results. Since there are few precisely known phylogenies, simulations are typically used to test the quality of reconstruction algorithms. These simulations randomly evolve strings of symbols to produce a tree, and then the algorithms are run with the tree leaves as inputs. Here we use Avida to test two widely used reconstruction methods, which gives us the chance to observe the effect of natural selection on tree reconstruction. We find that if the organisms undergo natural selection between branch points, the methods will be successful even on very large time scales. However, these algorithms often falter when selection is absent
How to understand the cell by breaking it: network analysis of gene perturbation screens
Modern high-throughput gene perturbation screens are key technologies at the
forefront of genetic research. Combined with rich phenotypic descriptors they
enable researchers to observe detailed cellular reactions to experimental
perturbations on a genome-wide scale. This review surveys the current
state-of-the-art in analyzing perturbation screens from a network point of
view. We describe approaches to make the step from the parts list to the wiring
diagram by using phenotypes for network inference and integrating them with
complementary data sources. The first part of the review describes methods to
analyze one- or low-dimensional phenotypes like viability or reporter activity;
the second part concentrates on high-dimensional phenotypes showing global
changes in cell morphology, transcriptome or proteome.Comment: Review based on ISMB 2009 tutorial; after two rounds of revisio
The inference of gene trees with species trees
Molecular phylogeny has focused mainly on improving models for the
reconstruction of gene trees based on sequence alignments. Yet, most
phylogeneticists seek to reveal the history of species. Although the histories
of genes and species are tightly linked, they are seldom identical, because
genes duplicate, are lost or horizontally transferred, and because alleles can
co-exist in populations for periods that may span several speciation events.
Building models describing the relationship between gene and species trees can
thus improve the reconstruction of gene trees when a species tree is known, and
vice-versa. Several approaches have been proposed to solve the problem in one
direction or the other, but in general neither gene trees nor species trees are
known. Only a few studies have attempted to jointly infer gene trees and
species trees. In this article we review the various models that have been used
to describe the relationship between gene trees and species trees. These models
account for gene duplication and loss, transfer or incomplete lineage sorting.
Some of them consider several types of events together, but none exists
currently that considers the full repertoire of processes that generate gene
trees along the species tree. Simulations as well as empirical studies on
genomic data show that combining gene tree-species tree models with models of
sequence evolution improves gene tree reconstruction. In turn, these better
gene trees provide a better basis for studying genome evolution or
reconstructing ancestral chromosomes and ancestral gene sequences. We predict
that gene tree-species tree methods that can deal with genomic data sets will
be instrumental to advancing our understanding of genomic evolution.Comment: Review article in relation to the "Mathematical and Computational
Evolutionary Biology" conference, Montpellier, 201
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