Dataset Information

Interplay of Various Evolutionary Modes in Genome Diversification and Adaptive Evolution of the Family Sulfolobaceae.

ABSTRACT: Sulfolobaceae family, comprising diverse thermoacidophilic and aerobic sulfur-metabolizing Archaea from various geographical locations, offers an ideal opportunity to infer the evolutionary dynamics across the members of this family. Comparative pan-genomics coupled with evolutionary analyses has revealed asymmetric genome evolution within the Sulfolobaceae family. The trend of genome streamlining followed by periods of differential gene gains resulted in an overall genome expansion in some species of this family, whereas there was reduction in others. Among the core genes, both Sulfolobus islandicus and Saccharolobus solfataricus showed a considerable fraction of positively selected genes and also higher frequencies of gene acquisition. In contrast, Sulfolobus acidocaldarius genomes experienced substantial amount of gene loss and strong purifying selection as manifested by relatively lower genome size and higher genome conservation. Central carbohydrate metabolism and sulfur metabolism coevolved with the genome diversification pattern of this archaeal family. The autotrophic CO₂ fixation with three significant positively selected enzymes from S. islandicus and S. solfataricus was found to be more imperative than heterotrophic CO₂ fixation for Sulfolobaceae. Overall, our analysis provides an insight into the interplay of various genomic adaptation strategies including gene gain-loss, mutation, and selection influencing genome diversification of Sulfolobaceae at various taxonomic levels and geographical locations.

SUBMITTER: Banerjee R

PROVIDER: S-EPMC8267890 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The causes and mechanisms of evolutionary diversification are central issues in biology. Geographic isolation is the traditional explanation for diversification, but recent theoretical and empirical studies have shown that frequency-dependent selection can drive diversification without isolation and that adaptive diversification occurring in sympatry may be an important source of biological diversity. However, there are no empirical examples in which sympatric lineage splits have been understood at the genetic level, and it is unknown how predictable this process is-that is, whether similar ecological settings lead to parallel evolutionary dynamics of diversification. We documented the genetic basis and the evolutionary dynamics of adaptive diversification in three replicate evolution experiments, in which competition for two carbon sources caused initially isogenic populations of the bacterium Escherichia coli to diversify into two coexisting ecotypes representing different physiological adaptations in the central carbohydrate metabolism. Whole-genome sequencing of clones of each ecotype from different populations revealed many parallel and some unique genetic changes underlying the derived phenotypes, including changes to the same genes and sometimes to the same nucleotide. Timelines of allele frequencies extracted from the frozen "fossil" record of the three evolving populations suggest parallel evolutionary dynamics driven at least in part by a co-evolutionary process in which mutations causing one type of physiology changed the ecological environment, allowing the invasion of mutations causing an alternate physiology. This process closely corresponds to the evolutionary dynamics seen in mathematical models of adaptive diversification due to frequency-dependent ecological interactions. The parallel genetic changes underlying similar phenotypes in independently evolved lineages provide empirical evidence of adaptive diversification as a predictable evolutionary process.

Project description:Translation termination is accomplished by proteins of the Class I release factor family (RF) that recognize stop codons and catalyze the ribosomal release of the newly synthesized peptide. Bacteria have two canonical RFs: RF1 recognizes UAA and UAG, RF2 recognizes UAA and UGA. Despite that these two release factor proteins are sufficient for de facto translation termination, the eukaryotic organellar RF protein family, which has evolved from bacterial release factors, has expanded considerably, comprising multiple subfamilies, most of which have not been functionally characterized or formally classified. Here, we integrate multiple sources of information to analyze the remarkable differentiation of the RF family among organelles. We document the origin, phylogenetic distribution and sequence structure features of the mitochondrial and plastidial release factors: mtRF1a, mtRF1, mtRF2a, mtRF2b, mtRF2c, ICT1, C12orf65, pRF1, and pRF2, and review published relevant experimental data. The canonical release factors (mtRF1a, mtRF2a, pRF1, and pRF2) and ICT1 are derived from bacterial ancestors, whereas the others have resulted from gene duplications of another release factor. These new RF family members have all lost one or more specific motifs relevant for bona fide release factor function but are mostly targeted to the same organelle as their ancestor. We also characterize the subset of canonical release factor proteins that bear nonclassical PxT/SPF tripeptide motifs and provide a molecular-model-based rationale for their retained ability to recognize stop codons. Finally, we analyze the coevolution of canonical RFs with the organellar genetic code. Although the RF presence in an organelle and its stop codon usage tend to coevolve, we find three taxa that encode an RF2 without using UGA stop codons, and one reverse scenario, where mamiellales green algae use UGA stop codons in their mitochondria without having a mitochondrial type RF2. For the latter, we put forward a "stop-codon reinvention" hypothesis that involves the retargeting of the plastid release factor to the mitochondrion.

Dataset Information

Interplay of Various Evolutionary Modes in Genome Diversification and Adaptive Evolution of the Family Sulfolobaceae.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets