↓ Skip to main content

Homoplasy in genome-wide analysis of rare amino acid replacements: the molecular-evolutionary basis for Vavilov's law of homologous series

Overview of attention for article published in Biology Direct, March 2008
Altmetric Badge

Citations

dimensions_citation
65 Dimensions

Readers on

mendeley
42 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Homoplasy in genome-wide analysis of rare amino acid replacements: the molecular-evolutionary basis for Vavilov's law of homologous series
Published in
Biology Direct, March 2008
DOI 10.1186/1745-6150-3-7
Pubmed ID
Authors

Igor B Rogozin, Karen Thomson, Miklós Csürös, Liran Carmel, Eugene V Koonin

Abstract

Rare genomic changes (RGCs) that are thought to comprise derived shared characters of individual clades are becoming an increasingly important class of markers in genome-wide phylogenetic studies. Recently, we proposed a new type of RGCs designated RGC_CAMs (after Conserved Amino acids-Multiple substitutions) that were inferred using genome-wide identification of amino acid replacements that were: i) located in unambiguously aligned regions of orthologous genes, ii) shared by two or more taxa in positions that contain a different, conserved amino acid in a much broader range of taxa, and iii) require two or three nucleotide substitutions. When applied to animal phylogeny, the RGC_CAM approach supported the coelomate clade that unites deuterostomes with arthropods as opposed to the ecdysozoan (molting animals) clade. However, a non-negligible level of homoplasy was detected.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 7%
Spain 1 2%
Russia 1 2%
Brazil 1 2%
Unknown 36 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 31%
Researcher 13 31%
Professor 4 10%
Student > Master 3 7%
Student > Postgraduate 2 5%
Other 3 7%
Unknown 4 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 71%
Biochemistry, Genetics and Molecular Biology 3 7%
Business, Management and Accounting 1 2%
Chemical Engineering 1 2%
Computer Science 1 2%
Other 1 2%
Unknown 5 12%