6,531 research outputs found
Unifying Parsimonious Tree Reconciliation
Evolution is a process that is influenced by various environmental factors,
e.g. the interactions between different species, genes, and biogeographical
properties. Hence, it is interesting to study the combined evolutionary history
of multiple species, their genes, and the environment they live in. A common
approach to address this research problem is to describe each individual
evolution as a phylogenetic tree and construct a tree reconciliation which is
parsimonious with respect to a given event model. Unfortunately, most of the
previous approaches are designed only either for host-parasite systems, for
gene tree/species tree reconciliation, or biogeography. Hence, a method is
desirable, which addresses the general problem of mapping phylogenetic trees
and covering all varieties of coevolving systems, including e.g., predator-prey
and symbiotic relationships. To overcome this gap, we introduce a generalized
cophylogenetic event model considering the combinatorial complete set of local
coevolutionary events. We give a dynamic programming based heuristic for
solving the maximum parsimony reconciliation problem in time O(n^2), for two
phylogenies each with at most n leaves. Furthermore, we present an exact
branch-and-bound algorithm which uses the results from the dynamic programming
heuristic for discarding partial reconciliations. The approach has been
implemented as a Java application which is freely available from
http://pacosy.informatik.uni-leipzig.de/coresym.Comment: Peer-reviewed and presented as part of the 13th Workshop on
Algorithms in Bioinformatics (WABI2013
Antigenic diversity is generated by distinct evolutionary mechanisms in African trypanosome species
Antigenic variation enables pathogens to avoid the host immune response by continual switching of surface proteins. The protozoan blood parasite Trypanosoma brucei causes human African trypanosomiasis ("sleeping sickness") across sub-Saharan Africa and is a model system for antigenic variation, surviving by periodically replacing a monolayer of variant surface glycoproteins (VSG) that covers its cell surface. We compared the genome of Trypanosoma brucei with two closely related parasites Trypanosoma congolense and Trypanosoma vivax, to reveal how the variant antigen repertoire has evolved and how it might affect contemporary antigenic diversity. We reconstruct VSG diversification showing that Trypanosoma congolense uses variant antigens derived from multiple ancestral VSG lineages, whereas in Trypanosoma brucei VSG have recent origins, and ancestral gene lineages have been repeatedly co-opted to novel functions. These historical differences are reflected in fundamental differences between species in the scale and mechanism of recombination. Using phylogenetic incompatibility as a metric for genetic exchange, we show that the frequency of recombination is comparable between Trypanosoma congolense and Trypanosoma brucei but is much lower in Trypanosoma vivax. Furthermore, in showing that the C-terminal domain of Trypanosoma brucei VSG plays a crucial role in facilitating exchange, we reveal substantial species differences in the mechanism of VSG diversification. Our results demonstrate how past VSG evolution indirectly determines the ability of contemporary parasites to generate novel variant antigens through recombination and suggest that the current model for antigenic variation in Trypanosoma brucei is only one means by which these parasites maintain chronic infections
Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?
The organization and mining of malaria genomic and post-genomic data is
highly motivated by the necessity to predict and characterize new biological
targets and new drugs. Biological targets are sought in a biological space
designed from the genomic data from Plasmodium falciparum, but using also the
millions of genomic data from other species. Drug candidates are sought in a
chemical space containing the millions of small molecules stored in public and
private chemolibraries. Data management should therefore be as reliable and
versatile as possible. In this context, we examined five aspects of the
organization and mining of malaria genomic and post-genomic data: 1) the
comparison of protein sequences including compositionally atypical malaria
sequences, 2) the high throughput reconstruction of molecular phylogenies, 3)
the representation of biological processes particularly metabolic pathways, 4)
the versatile methods to integrate genomic data, biological representations and
functional profiling obtained from X-omic experiments after drug treatments and
5) the determination and prediction of protein structures and their molecular
docking with drug candidate structures. Progresses toward a grid-enabled
chemogenomic knowledge space are discussed.Comment: 43 pages, 4 figures, to appear in Malaria Journa
Biological applications of the theory of birth-and-death processes
In this review, we discuss the applications of the theory of birth-and-death
processes to problems in biology, primarily, those of evolutionary genomics.
The mathematical principles of the theory of these processes are briefly
described. Birth-and-death processes, with some straightforward additions such
as innovation, are a simple, natural formal framework for modeling a vast
variety of biological processes such as population dynamics, speciation, genome
evolution, including growth of paralogous gene families and horizontal gene
transfer, and somatic evolution of cancers. We further describe how empirical
data, e.g., distributions of paralogous gene family size, can be used to choose
the model that best reflects the actual course of evolution among different
versions of birth-death-and-innovation models. It is concluded that
birth-and-death processes, thanks to their mathematical transparency,
flexibility and relevance to fundamental biological process, are going to be an
indispensable mathematical tool for the burgeoning field of systems biology.Comment: 29 pages, 4 figures; submitted to "Briefings in Bioinformatics
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Open Science principles for accelerating trait-based science across the Tree of Life.
Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges
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