Gene Order Comparisons for Phylogenetic Inference: Evolution of the Mitochondrial Genome

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 89; no. 14; pp. 6575 - 6579
• Main Authors: Sankoff, David, Leduc, Guillaume, Antoine, Natalie, Paquin, Bruno, Lang, B. Franz, Cedergren, Robert
• Format: Journal Article
• Language: English
• Published: Washington, DC National Academy of Sciences of the United States of America 15.07.1992; National Acad Sciences; National Academy of Sciences
• Subjects: Biological and medical sciences; Biological Evolution; Classical genetics, quantitative genetics, hybrids; DNA, Fungal - genetics; DNA, Mitochondrial - genetics; Evolution; Fundamental and applied biological sciences. Psychology; Fungi; Gene order; Gene Rearrangement; Genes; Genetic transposition; Genetics; Genetics of eukaryotes. Biological and molecular evolution; Genomes; Mathematical sequences; Methods, theories and miscellaneous; Phylogenetics; Phylogeny; Term weighting; Genetic mapping; Genome organization; Gene; Nucleotide sequence; Biological evolution; Mitochondrial DNA; Method; Phylogeny; Algorithm
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.89.14.6575

Detailed knowledge of gene maps or even complete nucleotide sequences for small genomes leads to the feasibility of evolutionary inference based on the macrostructure of entire genomes, rather than on the traditional comparison of homologous versions of a single gene in different organisms. The mathematical modeling of evolution at the genomic level, however, and the associated inferential apparatus are qualitatively different from the usual sequence comparison theory developed to study evolution at the level of individual gene sequences. We describe the construction of a database of 16 mitochondrial gene orders from fungi and other eukaryotes by using complete or nearly complete genomic sequences; propose a measure of gene order rearrangement based on the minimal set of chromosomal inversions, transpositions, insertions, and deletions necessary to convert the order in one genome to that of the other; report on algorithm design and the development of the DERANGE software for the calculation of this measure; and present the results of analyzing the mitochondrial data with the aid of this tool.