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Abstract Detail

Borrowed Chloroplasts: Secondary Endosymbiosis and the Chromalveolates

Boore, Jeffrey [1].

Detecting evolutionary transfer of genes using PhIGs.

PhIGs (Phylogenetically Inferred Groups; http://PhIGs.org) is a set of databases and web tools for whole genome evolutionary analysis. PhIGs takes as input gene sets of completely sequenced genomes, builds clusters of genes using a novel, graph-based approach that respects the evolutionary relationships among the organisms, and uses maximum likelihood phylogenetic analysis to reconstruct the evolutionary relationships among all gene families. Scripts automatically reconstruct the patterns of gene duplications and losses and assign orthology, providing the most accurate tool available for inferring gene function from sequence data. The user can view and download the sequence alignments, compare intron-exon structures, and follow links to functional genomic databases. Currently, PhIGs contains 652,756 genes from 45 genomes grouped into 61,059 gene families. Queries can be made using keywords, similarity searching, or hidden Markov models. Graphical displays are provided for the relative positions of these genes in the various genomes.
We have used this to detect the evolutionary transfer of hundreds of genes from both cyanobacteria and red algae into oomycete nuclear genomes. Even though oomycetes do not have plastids, this reveals that their ancestors did, and that they split only after the engulfment of a red alga that led to the secondary acquisition of plastids by chromalveolates. PhIGs will be applied to many other cases of possible gene transfers, including those from cyanobacteria into the glaucophyte Cyanophora paradoxa, once the sequence is available later this year.

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Related Links:
PhIGs, for whole genome evolutionary analysis

1 - SymBio and UC Berkeley, 1455 Adams Drive, Menlo Park, CA, 94025, USA


Presentation Type: Symposium or Colloquium Presentation
Session: SY15
Location: Waldorf Room/Hilton
Date: Wednesday, July 11th, 2007
Time: 8:30 AM
Number: SY15002
Abstract ID:2067

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