Dissemin is shutting down on January 1st, 2025

Published in

Cold Spring Harbor Laboratory Press, Genome Research, 4(12), p. 567-583, 2002

DOI: 10.1101/gr.209402

Links

Tools

Export citation

Search in Google Scholar

Comparative Analysis of Chloroplast Genomes: Functional Annotation, Genome-Based Phylogeny, and Deduced Evolutionary Patterns

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Red circle
Postprint: archiving forbidden
Orange circle
Published version: archiving restricted
Data provided by SHERPA/RoMEO

Abstract

All protein sequences from 19 complete chloroplast genomes (cpDNA) have been studied using a new computational method able to analyze functional correlations among series of protein sequences contained in complete proteomes. First, all open reading frames (ORFs) from the cpDNAs, comprising a total of 2266 protein sequences, were compared against the 3168 proteins from Synechocystis PCC6803 complete genome to find functionally related orthologous proteins. Additionally, all cpDNA genomes were pairwise compared to find orthologous groups not present in cyanobacteria. Annotations in the cluster of othologous proteins database and CyanoBase were used as reference for the functional assignments. Following this protocol, new functional assignments were made for ORFs of unknown function and for ycfs (hypothetical chloroplast frames), which still lack a functional assignment. Using this information, a matrix of functional relationships was derived from profiles of the presence and/or absence of orthologous proteins; the matrix included 1837 proteins in 277 orthologous clusters. A factor analysis study of this matrix, followed by cluster analysis, allowed us to obtain accurate phylogenetic reconstructions and the detection of genes probably involved in speciation as phylogenetic correlates. Finally, by grouping common evolutionary patterns, we show that it is possible to determine functionally linked protein networks. This has allowed us to suggest putative associations for some unknown ORFs.