Ecophysiological significance of scale-dependent patterns in prokaryotic genomes unveiled by a combination of statistic and genometric analyses.
We combined genometric (DNA walks) and statistical (detrended fluctuation analysis) methods on 456 prokaryotic chromosomes from 309 different bacterial and archaeal species to look for specific patterns and long-range correlations along the genome and relate them to ecological lifestyles. The position of each nucleotide along the complete genome sequence was plotted on an orthogonal plane (DNA landscape), and fluctuation analysis applied to the DNA walk series showed a long-range correlation in contrast to the lack of correlation for artificially generated genomes. Different features in the DNA landscapes among genomes from different ecological and metabolic groups of prokaryotes appeared with the combined analysis. Transition from hyperthermophilic to psychrophilic environments could have been related to more complex structural adaptations in microbial genomes, whereas for other environmental factors such as pH and salinity this effect would have been smaller. Prokaryotes with domain-specific metabolisms, such as photoautotrophy in Bacteria and methanogenesis in Archaea, showed consistent differences in genome correlation structure. Overall, we show that, beyond the relative proportion of nucleotides, correlation properties derived from their sequential position within the genome hide relevant phylogenetic and ecological information. This can be studied by combining genometric and statistical physics methods, leading to a reduction of genome complexity to a few useful descriptors.
Garcia
Juan A L
JA
Department of Continental Ecology-Limnology, Centre d'Estudis Avançats de Blanes-CSIC, E-17300 Blanes, Girona, Spain.
Bartumeus
Frederic
F
Roche
David
D
Giraldo
Jesús
J
Stanley
H Eugene
HE
Casamayor
Emilio O
EO
D001105:Archaea / Q000235:genetics / Q000502:physiology*; D018407:Bacterial Physiological Phenomena; D019847:Chromosomes, Archaeal / Q000235:genetics; D002876:Chromosomes, Bacterial / Q000235:genetics; D003627:Data Interpretation, Statistical; D004463:Ecology; D014644:Genetic Variation; D020745:Genome, Archaeal; D016680:Genome, Bacterial; D010802:Phylogeny; D017422:Sequence Analysis, DNA / Q000379:methods* / Q000706:statistics & numerical data*