Accepted Posters

Category 'F'- Evolution'
Poster F01
Polar sidechains bridging to the backbone of proteins have conserved roles in their core
Catherine Worth- Charite - Universitätsmedizin Berlin
Tom Blundell (University of Cambridge, Biochemistry);
Short Abstract: Using both evolutionary and structural data from protein families we investigated the structural role that polar sidechains have on the backbones of proteins. Our analysis sheds light on the important stabilizing roles of these residues in protein architecture and provides further insight into factors influencing the evolution of protein families.
Long Abstract:Click Here

Poster F02
Genome-wide influence of indel substitutions on evolution of bacteria of the PVC super-phylum, revealed using a novel computational framework
Olga Kamneva- University of Wyoming
Naomi Ward (University of Wyoming, Molecular Biology); David Liberles (University of Wyoming, Molecular Biology);
Short Abstract: We developed a new computational approach to analyze genome-wide patterns of selective constraints on indel substitutions. We applied our framework to 17 genomes of the bacterial PVC super-phylum, which includes organisms with unique cell biology and diverse lifestyles. Our study sheds light on mechanisms and evolutionary implications of indels.
Long Abstract:Click Here

Poster F03
An enzyme’s position in the human metabolic network predicts its degree of selective constraint
Corey Hudson- University of Missouri
Corey Hudson (University of Missouri, Informatics Institute); Gavin Conant (University of Missouri, Animal Sciences);
Short Abstract: We developed a novel orthology inference tool that uses sequence similarity and gene synteny to infer orthologous gene groups across 8 species of mammal. Using these orthologs, we estimated the selective constraint on genes in an optimized human metabolic network and compared this to the betweenness centrality of each enzyme.
Long Abstract:Click Here

Poster F04
Phylogenetic detection of numerous gene duplications shared by animals, fungi and plants
XIAOFAN ZHOU- The Pennsylvania State University
Zhenguo Lin (the University of Chicago, Department of Ecology and Evolution); Hong Ma (The Pennsylvania State University, Department of Biology);
Short Abstract: To understand the contribution of gene duplication to early eukaryotic evolution, we studied gene duplications in early eukaryotes by phylogenetic relative dating. We found that at least 300 out of 2600 orthogroups still retain duplication that occurred before the plants-animals/fungi split. Many such duplications were also share by protists.
Long Abstract:Click Here

Poster F05
Phylogenomic inference of functional divergence
brian caffrey- trinity college dublin
Tom A. Williams (trinity college dublin, genetics); Xiaowei Jiang (trinity college dublin, genetics); Christina Toft (Uppsala University, Department of Molecular Evolution); Mario Fares (trinity college dublin, genetics);
Short Abstract: Protein structure and function is inherent in sequence information. Analysis of amino acid substitution can give much insight into the functional divergence of amino acid sites. We have developed a method to identify convergent patterns of functional divergence in bacteria from a complete set of orthologous genes across 750 species
Long Abstract:Click Here

Poster F06
Understanding evolution at the SCOP family level via combined phylogenetics of sequence, structure and function.
Ralph Pethica- University of Bristol
Julian Gough (University of Bristol, Department of Computer Science);
Short Abstract: To better understand the evolutionary significance of SCOP families, phylogenetic trees created based on sequence, structure and function were compared to SCOP topologies. Analysis of trees combined with investigation of sequence distance, and functional diversity, provide strong evidence for common ancestry and increasing sequence identity at the SCOP family level.
Long Abstract:Click Here

Poster F07
Automatic dichotomy and polytomy classification and conversion
Guan Ning Lin- University of Missouri
Guan Ning Lin (University of Missouri, Informatics Institute); Dong Xu (University of Missouri, Computer Science);
Short Abstract: We have developed a classification algorithm to automatically create polytomy branches from bifurcating phylogenetic trees using Bayesian logistic regression, and recursively convert these dichotomies into polytomies as how NCBI taxonomy presents. We can also combine multiple bifurcating trees to achieve the final multifurcating tree through a supertree reconciliation approach.
Long Abstract:Click Here

Poster F08
Statistical phylogenetic tree analysis using differences of means
David Haws- University of Kentucky
Elissaveta Arnaoudova (University of Kentucky, Computer Science); Peter Huggins (Carnegie Mellon, Lane Center for Computational Biology); Jerzy Jaromczyk (University of Kentucky, Computer Science); Chris Schardl (University of Kentucky, Plant Pathology); Ruriko Yoshida (University of Kentucky, Statistics);
Short Abstract: We propose a statistical method which tests whether two trees are significantly incongruent to each other, using differences of means (instead of point estimations) to compare two distributions of phylogenetic trees. We present simulation results, and applications of our method to gopher-louse data sets and grass-endophyte data sets.
Long Abstract:Click Here

Poster F09
Simulations of microbial evolution in fluctuating environments
Vadim Mozhayskiy- University of California, Davis
Ilias Tagkopoulos (UC Davis, Computer Science);
Short Abstract: Microbes engage in a sophisticated repertoire of individual (stochastic switching, persistence, bet-hedging) and social (symbiosis, cooperation) strategies. We utilized mathematical models and large-scale simulations to investigate the effect of horizontal gene transfer to the evolution of microbial behaviors and their underlying networks.
Long Abstract:Click Here

Poster F10
Evolutionary fingerprinting of genes
Konrad Scheffler- University of Stellenbosch
Sergei Kosakovsky Pond ( University of California, San Diego, Department of Medicine); Michael Gravenor (University of Swansea, Swansea, Wales, United Kingdom, School of Medicine); Art Poon ( University of California, San Diego, Department of Pathology); Simon Frost (University of Cambridge, Cambridge, Department of Veterinary Medicine);
Short Abstract: "Evolutionary fingerprints" can be used to cluster genes with similar
evolutionary patterns in a way that is analogous to clustering
approaches based on sequence similarity, such as BLAST. We show that
this approach identifies protein-coding genes with similar protein structure
and/or function, but which need not be homologous.
Long Abstract:Click Here

Poster F11
A comparative analysis of functional maps across diverse organisms
Aaron Wong- Princeton University
Curtis Huttenhower (Harvard School of Public Health, Biostatistics); Olga Troyanskaya (Princeton University, Computer Science);
Short Abstract: Functional networks which synthesize diverse biological data, have been constructed in the major model organisms. In this study, we applied a comparative analysis of functional networks across multiple organisms. We use a previously described method that extends networks of gene relationships to maps of gene function to compare evolutionary differences in various functional groups.
Long Abstract:Click Here

Poster F12
Evolution of Structurally Disordered Regions
Jessica Liberles- University of Wyoming
No additional authors
Short Abstract: Protein structure is generally more conserved than sequence, but for structurally disordered regions that can adopt different structures in different environments, does this hold true? We have investigated the evolutionary dynamics of structurally disordered regions in proteins families containing both orthologs and paralogs. Selected examples from protein families are presented.
Long Abstract:Click Here

Poster F13
Inferring Genome Rearrangement Phylogeny based on Maximum Likelihood of Gene Adjacencies
Jijun Tang- University of South Carolina
Fei Hu (University of South Carolina, Conputer Science); Haiwei Luo (University of South Carolina, Biological Sciences); Jian Shi (University of South Carolina, Computer Science); Yiwei Zhang (University of South Carolina, Computer Science);
Short Abstract: We provide a simple yet very accurate phylogenetic reconstruction method based on binary encoding that for the first time applied maximum likelihood criteria to gene order data analysis. This new method is called Maximum Likelihood on Binary Encoding (MLBE).
Long Abstract:Click Here

Poster F14
The Evolution and Structure Prediction of Coiled Coils Across All Genomes
Julian Gough- University of Bristol
Owen Rackham (University of Bristol, Complexity Sciences); Dek Woolfson (University of Bristol, Chemistry); Craig Armstrong (University of Bristol, Chemistry); Tom Vincent (University of Bristol, Complexity Sciences);
Short Abstract: We present an evolutionary analysis of coiled coils and their various oligomeric states based on a new resource/method: SpiriCoil. Spiricoil uses HMMs to provide predictions and models of coiled coils and their oligomeric state in all sequences in completely sequenced genomes.
Long Abstract:Click Here

Poster F15
Protein Interaction Evolution of the Yeast SH3 Domain
Mark Sun- University of Toronto
Martin Sikora (University of Toronto, Terrence Donnelly Centre for Cellular and Biomolecular Research ); Philip M. Kim (University of Toronto, Molecular Genetics and Computer Science);
Short Abstract: We show protein interactions involving Src homolog 3 (SH3) domain of Saccharomyces cerevisiae evolve at a rate slower than that of transcription factors, but faster than phosphoregulation evolution. We find SH3 domains from different classes bind the same peptide region to form clusters, whose size is correlated with interaction conservation.
Long Abstract:Click Here

Poster F16
Filtering of Environmental Metagenomic Sequences (FEMS): a phylogenetic focus group-based framework for molecular evolution research
Jeffrey Blanchard- University of Massachusetts Amherst
Jinghua Hu (University of Massachusetts, Electrical and Computer Engineering); Weibo Gong (University of Massachusetts, Electrical and Computer Engineering);
Short Abstract: Filtering of Environmental Metagenomic Sequences (FEMS) is a sequence filtering framework based on a phylogenetic focus group. It incorporates multiple factors and prior knowledge to better characterize sequence similarities between the focus group and metagenomic data, enabling effective extraction of population level genomic data to facilitate microbial genome evolution study.
Long Abstract:Click Here

Poster F17
Evolutionary dynamics of CRISPR systems in the Ocean metagenome
Irena Artamonova- Vavilov Institute Of General Genetics RAS
Valery Sorokin (M.V. Lomonosov Moscow State University, Vorobievy Gory 1-73, Moscow, Faculty of Bioengineering and Bioinformatics); Mikhail Gelfand (A.A. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Bolshoi Karetny pereulok 19, Moscow, Research and Training Center on Bioinformatics);
Short Abstract: Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) are a recently characterized type of prokaryotic anti-phage defense systems. They have been studied in experiments on selected bacterial or archaeal species, and, computationally, in completely sequenced genomes. However, these studies did not address the prokaryotic population diversity and phage-host interaction dynamics. This gap can be filled by using metagenomic datasets such as the Global Ocean Sampling expedition data.
The application of three available CRISPR-recognition programs to this metagenome produced numerous false positives. To address this problem, a filtering procedure was designed, yielding 192 reliable CRISPR-cassettes. Fragments of DNA similar to the cassette spacers tended to share the geographic origin with the cassette-containing contigs. Hence, CRISPR cassettes retain the memory of the local virus population at a particular ocean location. We developed a catalogue of elementary CRISPR-forming events and reconstructed the evolutionary history of cassettes with similar spacers.
Long Abstract:Click Here

Poster F18
Bayesian Gene-tree Reconstruction and Learning in Phylogenomics
Matthew Rasmussen- Massachusetts Institute of Technology Computer Science and Artificial Intelligence
Manolis Kellis (MIT, Computer Science and Artificial Intelligence);
Short Abstract: Here, we present SPIMAP a new Bayesian method for gene tree reconstruction that incorporates within a unified framework models for gene duplication and loss, gene- and species-specific rate variation, and sequence substitution. We extensively test its accuracy compared to other phylogenetic methods on 16 fungal and 12 Drosophila genomes.
Long Abstract:Click Here

Poster F19
A New Methodology for Inferring Events in the History of a Multidomain Gene Family
Maureen Stolzer- Carnegie Mellon University
Ravi Chinoy (Carnegie Mellon University, Biology); Benjamin Vernot (Carnegie Mellon University, Biology); Dannie Durand (Carnegie Mellon University, Biology);
Short Abstract: We present a method for inferring the evolutionary history of
multidomain families that evolve by domain shuffling: insertion,
deletion, and duplication of domains. Our method compares domain
and gene trees to infer the most parsimonious history of domain
shuffling events, as well as the ancestral domain architectures in
the family.
Long Abstract:Click Here

Poster F20
Investigating Homology Between Proteins Using Energetic Profiles
James Wrabl- University of Texas Medical Branch
Vincent Hilser (Johns Hopkins University, Biology and Biophysics);
Short Abstract: Thermodynamics are fundamental to protein structure, function, and evolution. Residue-specific descriptors of stability, enthalpy, and entropy were computed for a diverse sample of protein domains. Generally, homologous domains exhibited correlated descriptors. However, interesting exceptions were observed that could indicate novel thermodynamically-mediated processes of functional adaptation or evolutionary fold change.
Long Abstract:Click Here

Poster F21
Analysis of functional profiles of eukaryotic genomes reveals strong trends related to morphological complexity
Christian Zmasek- Sanford-Burnham Medical Research Institute
Qing Zhang (Sanford-Burnham Medical Research Institute, Bioinformatics and Systems Biology); Adam Godzik (Sanford-Burnham Medical Research Institute, Bioinformatics and Systems Biology);
Short Abstract: In this work we investigate the question of the genomic manifestation of the highly variable morphological complexity of eukaryotes, such as the difference between Trichoplax adhaerens that only has 4 different cell types and mammals with around 210 different cell types, and its evolutionary origins and causes. For this purpose, we used more than one-hundred completely sequenced eukaryotic genomes to reconstruct the genome content of putative ancestral species at all major divergence points, including the last eukaryotic common ancestor (LECA), on the level of protein domains defined by the Pfam database. We show that the numbers of distinct protein domains are remarkably constant over large parts of the eukaryotic tree of life and, counter-intuitively, in general domain losses outnumber domain gains. Only at the root of the animal sub-tree and at the root of the vertebrate sub-tree do we see domain gains consistently outnumbering domain losses. Functionally, domains involved in regulation are predominantly gained during animal evolution at the cost of domains with metabolic functions. In contrast, other groups of eukaryotes with the potential of multicellularity, plants and fungi, do not exhibit such an increase in regulatory domains. We show that clustering of genomes according to their functional profiles results in an organization remarkably similar to the eukaryotic tree of life. Finally, we show that it is likely that metabolic functions lost during animal evolution are being replaced ('outsourced') by the metabolic capabilities of symbiotic organisms (such as gut microbes).
Long Abstract:Click Here

Accepted Posters


View Posters By Category
Search Posters:
Poster Number Matches
Last Name
Co-Authors Contains
Title
Abstract Contains






↑ TOP