Tuesday March 30

 

Parallel session 1: Phylogeny and Fungal Tree of Life

 

 

PS1.1

Pan-orthologs, phylogenetic informativeness and the fungal tree of life

Joseph Spatafora[1] Barbara Robbertse[1] Francesc Lopez[2] Jeffrey Townsend[2]

1Oregon State University, 2Yale University

spatafoj@science.oregonstate.edu

 

The Assembling the Fungal Tree of Life (AFTOL) project is a large multi-laboratory collaboration that is focused on analyzing large amounts of genomic sequence data to infer phylogenetic relationships within the Kingdom Fungi.  Our current research has identified a set of pan-orthologs that are distributed throughout the Fungi and are of suitable length and variability for phylogenetic analyses.  In addition to standard phylogenetic analyses, we have tested the phylogenetic informativeness of these loci and compared them to markers traditionally used in phylogenetic analyses.  Major findings from these analyses reveal that there exist numerous orthologous markers that are significantly more informative than standard loci currently in use in molecular phylogenetics and that individual markers vary in their level of informativeness based on the node or region of the phylogenetic tree in question.  To expand this sampling to lineages for which genomes have not been sequenced, we are developing high throughput sequencing strategies and bioinformatic tools for mining heterogeneous genomic data for the AFTOL pan-orthologs and their inclusion in phylogenetic analyses.  We will outline our bioinformatics pipeline, and present some preliminary data and findings concerning the evolution of plant-associated fungal lineages and major evolutionary trends in the Ascomycota.

 


PS1.2

AspGD comparative genomics pipelines and visualization tools

Jennifer Russo Wortman1, Jonathan Crabtree1, Marcus C. Chibucos1, Joshua Orvis1,  Martha B. Arnaud2, Maria C. Costanzo2, Diane O. Inglis2, Prachi Shah2, Marek S. Skrzypek2, and Gavin Sherlock2

1Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore MD

2Department of Genetics, Stanford University, Stanford, CA  

jwortman@som.umaryland.edu

 

The Aspergillus Genome Database (http://www.aspgd.org/) is an online genomic resource for Aspergillus genomics and molecular biology, with information curated from the literature and web-based research tools for exploration and analysis of these data.  With ten annotated genome sequences from eight Aspergillus species publicly available, and more on the way, our goals include leveraging comparative genomics for annotation improvement, and providing sophisticated querying and visualization tools to maximize the utility of these data. 

 

The Aspergillus genomes were annotated at different institutions using diverse methods over an extended time frame, during which available tools and datasets have evolved. Common annotation inconsistencies include missed gene calls, gene truncations, failure to predict small exons, and inappropriate gene merges.  We are developing a standard, optimized pipeline across all Aspergillus genomes, comprehensively incorporating new data as it becomes available and leveraging comparative genomics analyses to improve protein-coding gene prediction.  Resulting annotations will be integrated into AspGD, along with ortholog and synteny data linking knowledge across the Aspergilli.

 

Otholog and synteny data are currently available at the AspGD website through data downloads as well as interactively through the Sybil software infrastructure.  Sybil is an open source, web-based software package for visualizing and mining comparative genomics data (http://sybil.sf.net). Powered by a Chado relational database (http://www.gmod.org/schema), Sybil provides an extensive set of interfaces for interrogating multi-genome comparisons at varying levels of resolution from the whole genome scale to individual loci. 

 

Sybil allows users to search for genes, clusters or genomic regions and visualize the results in a comparative genomic context, along with syntenic relationships and annotated features of interest.   Configurable reports are available through the web interface, supporting the identification of core and accessory genes from all or a subset of available genomes.  Reports and displays are interactive and linked, allowing seamless navigation from a chromosome view, to a cluster report, to an individual protein page.  All of the data in AspGD are freely available to the public from http://www.aspgd.org/.  AspGD is supported by grant RO1 AI077599 from the NIAID at the NIH.

 

 


PS1.3

The evolution of pathways and gene functions: lessons from phylogenomics in fungi

Berend Snel

Theoretical Biology and Bioinformatics, Department of Biology, Science Faculty

Utrecht University

b.snel@uu.nl

 

The ever increasing amount of sequenced genomes potentially allows unprecedented insight into pathway evolution. However precise analyzes are hindered by incomplete knowledge on protein interactions and genome dynamics that obfuscate precise orthology. These processes include gene duplications, genome duplications, domain re-arrangements and gene loss. Small scale manual analyzes and careful large scale computational analyzes nevertheless allow for the elucidation of some fascinating evolutionary stories. In this talk I will present two stories that were uncovered using phylogenomic analysis of fungal genome sequences.

 

Firstly I will discuss the evolution of the pathway surrounding the small GTPase Ras. The genome sequences of primitive fungi show that in contrast to what was previously thought many features of this pathway are not animal specific but were present in the ancestor of the Fungi/Metazoa group. The phylogenetic profiles of individual orthologous groups in this pathway do not match well, but they do match near perfectly on the family level, providing a new twist to the phylogenetic profile method for function prediction and our understanding of the evolutionary forces constraining the co-evolution of interacting proteins. Secondly I will discuss the evolutionary implications of single gene duplications versus genome duplications in the evolution of protein complexes in S. cerevisiae.

 

 

 


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