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Landscape of gene transposition–duplication within the Brassicaceae family

We developed the CLfinder-OrthNet pipeline that detects co-linearity among multiple closely related genomes, finds orthologous gene groups, and encodes the evolutionary history of each orthologue group into a representative network (OrthNet). Using a search based on network topology, we identified 1...

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Detalles Bibliográficos
Autores principales: Oh, Dong-Ha, Dassanayake, Maheshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6379040/
https://www.ncbi.nlm.nih.gov/pubmed/30380026
http://dx.doi.org/10.1093/dnares/dsy035
Descripción
Sumario:We developed the CLfinder-OrthNet pipeline that detects co-linearity among multiple closely related genomes, finds orthologous gene groups, and encodes the evolutionary history of each orthologue group into a representative network (OrthNet). Using a search based on network topology, we identified 1,394 OrthNets that included gene transposition–duplication (tr–d) events, out of 17,432 identified in six Brassicaceae genomes. Occurrences of tr–d shared by subsets of Brassicaceae genomes mirrored the divergence times between the genomes and their repeat contents. The majority of tr–d events resulted in truncated open reading frames (ORFs) in the duplicated loci. However, the duplicates with complete ORFs were significantly more frequent than expected from random events. These were derived from older tr–d events and had a higher chance of being expressed. We also found an enrichment of tr–d events with complete loss of intergenic sequence conservation between the original and duplicated loci. Finally, we identified tr–d events uniquely found in two extremophytes among the six Brassicaceae genomes, including tr–d of SALT TOLERANCE 32 and ZINC TRANSPORTER 3 that relate to their adaptive evolution. CLfinder-OrthNet provides a flexible toolkit to compare gene order, visualize evolutionary paths among orthologues as networks, and identify gene loci that share an evolutionary history.