Andrey Ptitsyn1, Leonid L Moroz. 1. Whitney Laboratory for Marine Biosciences, University of Florida; 9505 Ocean Shore Blvd, Saint Augustine, FL 32080, USA. andrey.ptitsyn@whitney.ufl.edu
Abstract
BACKGROUND: Early evolution of animals led to profound changes in body plan organization, symmetry and the rise of tissue complexity including formation of muscular and nervous systems. This process was associated with massive restructuring of animal genomes as well as deletion, acquisition and rapid differentiation of genes from a common metazoan ancestor. Here, we present a simple but efficient workflow for elucidation of gene gain and gene loss within major branches of the animal kingdom. METHODS: We have designed a pipeline of sequence comparison, clustering and functional annotation using 12 major phyla as illustrative examples. Specifically, for the input we used sets of ab initio predicted gene models from the genomes of six bilaterians, three basal metazoans (Cnidaria, Placozoa, Porifera), two unicellular eukaryotes (Monosiga and Capsospora) and the green plant Arabidopsis as an out-group. Due to the large amounts of data the software required a high-performance Linux cluster. The final results can be imported into standard spreadsheet analysis software and queried for the numbers and specific sets of genes absent in specific genomes, uniquely present or shared among different taxons. RESULTS AND CONCLUSIONS: The developed software is open source and available free of charge on Open Source principles. It allows the user to address a number of specific questions regarding gene gain and gene loss in particular genomes, and user-defined groups of genomes can be formulated in a type of logical expression. For example, our analysis of 12 sequenced genomes indicated that these genomes possess at least 90,000 unique genes and gene families, suggesting enormous diversity of the genome repertoire in the animal kingdom. Approximately 9% of these gene families are shared universally (homologous) among all genomes, 53% are unique to specific taxa, and the rest are shared between two or more distantly related genomes.
BACKGROUND: Early evolution of animals led to profound changes in body plan organization, symmetry and the rise of tissue complexity including formation of muscular and nervous systems. This process was associated with massive restructuring of animal genomes as well as deletion, acquisition and rapid differentiation of genes from a common metazoan ancestor. Here, we present a simple but efficient workflow for elucidation of gene gain and gene loss within major branches of the animal kingdom. METHODS: We have designed a pipeline of sequence comparison, clustering and functional annotation using 12 major phyla as illustrative examples. Specifically, for the input we used sets of ab initio predicted gene models from the genomes of six bilaterians, three basal metazoans (Cnidaria, Placozoa, Porifera), two unicellular eukaryotes (Monosiga and Capsospora) and the green plant Arabidopsis as an out-group. Due to the large amounts of data the software required a high-performance Linux cluster. The final results can be imported into standard spreadsheet analysis software and queried for the numbers and specific sets of genes absent in specific genomes, uniquely present or shared among different taxons. RESULTS AND CONCLUSIONS: The developed software is open source and available free of charge on Open Source principles. It allows the user to address a number of specific questions regarding gene gain and gene loss in particular genomes, and user-defined groups of genomes can be formulated in a type of logical expression. For example, our analysis of 12 sequenced genomes indicated that these genomes possess at least 90,000 unique genes and gene families, suggesting enormous diversity of the genome repertoire in the animal kingdom. Approximately 9% of these gene families are shared universally (homologous) among all genomes, 53% are unique to specific taxa, and the rest are shared between two or more distantly related genomes.
Authors: Michele Clamp; Ben Fry; Mike Kamal; Xiaohui Xie; James Cuff; Michael F Lin; Manolis Kellis; Kerstin Lindblad-Toh; Eric S Lander Journal: Proc Natl Acad Sci U S A Date: 2007-11-26 Impact factor: 11.205
Authors: Eugene V Koonin; Natalie D Fedorova; John D Jackson; Aviva R Jacobs; Dmitri M Krylov; Kira S Makarova; Raja Mazumder; Sergei L Mekhedov; Anastasia N Nikolskaya; B Sridhar Rao; Igor B Rogozin; Sergei Smirnov; Alexander V Sorokin; Alexander V Sverdlov; Sona Vasudevan; Yuri I Wolf; Jodie J Yin; Darren A Natale Journal: Genome Biol Date: 2004-01-15 Impact factor: 13.583
Authors: Roman L Tatusov; Natalie D Fedorova; John D Jackson; Aviva R Jacobs; Boris Kiryutin; Eugene V Koonin; Dmitri M Krylov; Raja Mazumder; Sergei L Mekhedov; Anastasia N Nikolskaya; B Sridhar Rao; Sergei Smirnov; Alexander V Sverdlov; Sona Vasudevan; Yuri I Wolf; Jodie J Yin; Darren A Natale Journal: BMC Bioinformatics Date: 2003-09-11 Impact factor: 3.169
Authors: Leonid L Moroz; Kevin M Kocot; Mathew R Citarella; Sohn Dosung; Tigran P Norekian; Inna S Povolotskaya; Anastasia P Grigorenko; Christopher Dailey; Eugene Berezikov; Katherine M Buckley; Andrey Ptitsyn; Denis Reshetov; Krishanu Mukherjee; Tatiana P Moroz; Yelena Bobkova; Fahong Yu; Vladimir V Kapitonov; Jerzy Jurka; Yuri V Bobkov; Joshua J Swore; David O Girardo; Alexander Fodor; Fedor Gusev; Rachel Sanford; Rebecca Bruders; Ellen Kittler; Claudia E Mills; Jonathan P Rast; Romain Derelle; Victor V Solovyev; Fyodor A Kondrashov; Billie J Swalla; Jonathan V Sweedler; Evgeny I Rogaev; Kenneth M Halanych; Andrea B Kohn Journal: Nature Date: 2014-05-21 Impact factor: 49.962
Authors: Jonathan D Wren; Mikhail G Dozmorov; Dennis Burian; Rakesh Kaundal; Susan Bridges; Doris M Kupfer Journal: BMC Bioinformatics Date: 2012-09-11 Impact factor: 3.169