Journal of Molecular Evolution最新文献

The principle of continuity demands the existence of prior molecular states and common ancestors responsible for extant macromolecular structure. Here, we focus on the emergence and evolution of loop prototypes – the elemental architects of protein domain structure. Phylogenomic reconstruction spanning superkingdoms and viruses generated an evolutionary chronology of prototypes with six distinct evolutionary phases defining a most parsimonious evolutionary progression of cellular life. Each phase was marked by strategic prototype accumulation shaping the structures and functions of common ancestors. The last universal common ancestor (LUCA) of cells and viruses and the last universal cellular ancestor (LUCellA) defined stem lines that were structurally and functionally complex. The evolutionary saga highlighted transformative forces. LUCA lacked biosynthetic ribosomal machinery, while the pivotal LUCellA lacked essential DNA biosynthesis and modern transcription. Early proteins therefore relied on RNA for genetic information storage but appeared initially decoupled from it, hinting at transformative shifts of genetic processing. Urancestral loop types suggest advanced folding designs were present at an early evolutionary stage. An exploration of loop geometric properties revealed gradual replacement of prototypes with α-helix and β-strand bracing structures over time, paving the way for the dominance of other loop types. AlphFold2-generated atomic models of prototype accretion described patterns of fold emergence. Our findings favor a ‛processual’ model of evolving stem lines aligned with Woese’s vision of a communal world. This model prompts discussing the ‘problem of ancestors’ and the challenges that lie ahead for research in taxonomy, evolution and complexity.

Hypothesizing that CpG codon dyads, formed by consecutive codons containing a cytosine-guanine pair (NNC-GNN), may play a crucial role in gene function, we conducted an extensive analysis to investigate their distribution and conservation within mammalian genes. Our findings reveal that genes characterized by a high density of CpG codon dyads are notably associated with homeobox domains and RNA polymerase II transcription factors. Conversely, genes exhibiting low CpG codon dyad density have links to DNA damage repair and mitosis. Importantly, our study identifies a re-markable increase in expressed genes that harbor CpG during embryonic development, suggesting their potential involvement in gene regulation at these developmental stages. These results under-score the functional significance of CpG codon dyads in DNA methylation and gene expression, fur-ther demonstrating the coevolution of consecutive codons and their contribution to codon usage bias.

The genus Macaca is widely distributed, occupies a variety of habitats, shows diverse phenotypic characteristics, and is one of the best-studied genera of nonhuman primates. Here, we reported five re-sequencing Macaca genomes, including one M. cyclopis, one M. fuscata, one M. thibetana, one M. silenus, and one M. sylvanus. Together with published genomes of other macaque species, we combined 20 genome sequences of 10 macaque species to investigate the gene introgression and genetic differences among the species. The network analysis of the SNV-fragment trees indicates a reticular phylogeny of macaque species. Combining the results from various analytical methods, we identified extensive ancient introgression events among macaque species. The multiple introgression signals between different species groups were also observed, such as between fascicularis group species and silenus group species. However, gene flow signals between fascicularis and sinica group were not as strong as those between fascicularis group and silenus group. On the other hand, the unidirect gene flow in M. arctoides probably occurred between the progenitor of M. arctoides and the common ancestor of fascicularis group. Our study also shows that the genetic backgrounds and genetic diversity of different macaques vary dramatically among species, even among populations of the same species. In conclusion, using whole genome sequences and multiple methods, we have studied the evolutionary history of the genus Macaca and provided evidence for extensive introgression among the species.

Ecological and evolutionary transitions offer an excellent opportunity to examine the molecular basis of adaptation. Fishes of the order Beloniformes include needlefishes, flyingfishes, halfbeaks, and allies, and comprise over 200 species occupying a wide array of habitats-from the marine epipelagic zone to tropical rainforest rivers. These fishes also exhibit a diversity of diets, including piscivory, herbivory, and zooplanktivory. We investigated how diet and habitat affected the molecular evolution of cone opsins, which play a key role in bright light and colour vision and are tightly linked to ecology and life history. We analyzed a targeted-capture dataset to reconstruct the evolutionary history of beloniforms and assemble cone opsin sequences. We implemented codon-based clade models of evolution to examine how molecular evolution was affected by habitat and diet. We found high levels of positive selection in medium- and long-wavelength beloniform opsins, with piscivores showing increased positive selection in medium-wavelength opsins and zooplanktivores showing increased positive selection in long-wavelength opsins. In contrast, short-wavelength opsins showed purifying selection. While marine/freshwater habitat transitions have an effect on opsin molecular evolution, we found that diet plays a more important role. Our study suggests that evolutionary transitions along ecological axes produce complex adaptive interactions that affect patterns of selection on genes that underlie vision.

Virtually all enzymes catalyse more than one reaction, a phenomenon known as enzyme promiscuity. It is unclear whether promiscuous enzymes are more often generalists that catalyse multiple reactions at similar rates or specialists that catalyse one reaction much more efficiently than other reactions. In addition, the factors that shape whether an enzyme evolves to be a generalist or a specialist are poorly understood. To address these questions, we follow a three-pronged approach. First, we examine the distribution of promiscuity in empirical enzymes reported in the BRENDA database. We find that the promiscuity distribution of empirical enzymes is bimodal. In other words, a large fraction of promiscuous enzymes are either generalists or specialists, with few intermediates. Second, we demonstrate that enzyme biophysics is not sufficient to explain this bimodal distribution. Third, we devise a constraint-based model of promiscuous enzymes undergoing duplication and facing selection pressures favouring subfunctionalization. The model posits the existence of constraints between the catalytic efficiencies of an enzyme for different reactions and is inspired by empirical case studies. The promiscuity distribution predicted by our constraint-based model is consistent with the empirical bimodal distribution. Our results suggest that subfunctionalization is possible and beneficial only in certain enzymes. Furthermore, the model predicts that conflicting constraints and selection pressures can cause promiscuous enzymes to enter a 'frustrated' state, in which competing interactions limit the specialisation of enzymes. We find that frustration can be both a driver and an inhibitor of enzyme evolution by duplication and subfunctionalization. In addition, our model predicts that frustration becomes more likely as enzymes catalyse more reactions, implying that natural selection may prefer catalytically simple enzymes. In sum, our results suggest that frustration may play an important role in enzyme evolution.

Cyanobacteria are recognised for their pivotal roles in aquatic ecosystems, serving as primary producers and major agents in diazotrophic processes. Currently, the primary focus of cyanobacterial research lies in gaining a more detailed understanding of these well-established ecosystem functions. However, their involvement and impact on other crucial biogeochemical cycles remain understudied. This knowledge gap is partially attributed to the challenges associated with culturing cyanobacteria in controlled laboratory conditions and the limited understanding of their specific growth requirements. This can be circumvented partially by the culture-independent methods which can shed light on the genomic potential of cyanobacterial species and answer more profound questions about the evolution of other key biogeochemical functions. In this study, we assembled 83 cyanobacterial genomes from metagenomic data generated from environmental DNA extracted from a brackish water lagoon (Chilika Lake, India). We taxonomically classified these metagenome-assembled genomes (MAGs) and found that about 92.77% of them are novel genomes at the species level. We then annotated these cyanobacterial MAGs for all the encoded functions using KEGG Orthology. Interestingly, we found two previously unreported functions in Cyanobacteria, namely, DNRA (Dissimilatory Nitrate Reduction to Ammonium) and DMSP (Dimethylsulfoniopropionate) synthesis in multiple MAGs using nirBD and dsyB genes as markers. We validated their presence in several publicly available cyanobacterial isolate genomes. Further, we identified incongruities between the evolutionary patterns of species and the marker genes and elucidated the underlying reasons for these discrepancies. This study expands our overall comprehension of the contribution of cyanobacteria to the biogeochemical cycling in coastal brackish ecosystems.

The proportions of A:T and G:C nucleotide pairs are often unequal and can vary greatly between animal species and along chromosomes. The causes and consequences of this variation are incompletely understood. The recent release of high-quality genome sequences from the Darwin Tree of Life and other large-scale genome projects provides an opportunity for GC heterogeneity to be compared across a large number of insect species. Here we analyse GC content along chromosomes, and within protein-coding genes and codons, of 150 insect species from four holometabolous orders: Coleoptera, Diptera, Hymenoptera, and Lepidoptera. We find that protein-coding sequences have higher GC content than the genome average, and that Lepidoptera generally have higher GC content than the other three insect orders examined. GC content is higher in small chromosomes in most Lepidoptera species, but this pattern is less consistent in other orders. GC content also increases towards subtelomeric regions within protein-coding genes in Diptera, Coleoptera and Lepidoptera. Two species of Diptera, Bombylius major and B. discolor, have very atypical genomes with ubiquitous increase in AT content, especially at third codon positions. Despite dramatic AT-biased codon usage, we find no evidence that this has driven divergent protein evolution. We argue that the GC landscape of Lepidoptera, Diptera and Coleoptera genomes is influenced by GC-biased gene conversion, strongest in Lepidoptera, with some outlier taxa affected drastically by counteracting processes.

Protein Protein low complexity regions (LCRs) are compositionally biased amino acid sequences, many of which have significant evolutionary impacts on the proteins which contain them. They are mutationally unstable experiencing higher rates of indels and substitutions than higher complexity regions. LCRs also impact the expression of their proteins, likely through multiple effects along the path from gene transcription, through translation, and eventual protein degradation. It has been observed that proteins which contain LCRs are associated with elevated transcript abundance (TAb), despite having lower protein abundance. We have gathered and integrated human data to investigate the co-evolution of TAb and LCRs through ancestral reconstructions and model inference using an approximate Bayesian calculation based method. We observe that on short evolutionary timescales TAb evolution is significantly impacted by changes in LCR length, with insertions driving TAb down. But in contrast, the observed data is best explained by indel rates in LCRs which are unaffected by shifts in TAb. Our work demonstrates a coupling between LCR and TAb evolution, and the utility of incorporating multiple responses into evolutionary analyses.

A recent publication in Nature has generated much heated discussion about evolution, its tendency towards increasing diversity and complexity, and its potential status above and beyond the known laws of fundamental physics. The argument at the heart of this controversy concerns assembly theory, a method to detect and quantify the influence of higher-level emergent causal constraints in computational worlds made of basic objects and their combinations. In this short essay, I briefly review the theory, its basic principles and potential applications. I then go on to critically examine its authors' assertions, concluding that assembly theory has merit but is not nearly as novel or revolutionary as claimed. It certainly does not provide any new explanation of biological evolution or natural selection, or a new grounding of biology in physics. In this regard, the presentation of the paper is starkly distorted by hype, which may explain some of the outrage it created.

Ancestral sequence reconstruction (ASR) is a phylogenetic method widely used to analyze the properties of ancient biomolecules and to elucidate mechanisms of molecular evolution. Despite its increasingly widespread application, the accuracy of ASR is currently unknown, as it is generally impossible to compare resurrected proteins to the true ancestors. Which evolutionary models are best for ASR? How accurate are the resulting inferences? Here we answer these questions using a cross-validation method to reconstruct each extant sequence in an alignment with ASR methodology, a method we term “extant sequence reconstruction” (ESR). We thus can evaluate the accuracy of ASR methodology by comparing ESR reconstructions to the corresponding known true sequences. We find that a common measure of the quality of a reconstructed sequence, the average probability, is indeed a good estimate of the fraction of correct amino acids when the evolutionary model is accurate or overparameterized. However, the average probability is a poor measure for comparing reconstructions from different models, because, surprisingly, a more accurate phylogenetic model often results in reconstructions with lower probability. While better (more predictive) models may produce reconstructions with lower sequence identity to the true sequences, better models nevertheless produce reconstructions that are more biophysically similar to true ancestors. In addition, we find that a large fraction of sequences sampled from the reconstruction distribution may have fewer errors than the single most probable (SMP) sequence reconstruction, despite the fact that the SMP has the lowest expected error of all possible sequences. Our results emphasize the importance of model selection for ASR and the usefulness of sampling sequence reconstructions for analyzing ancestral protein properties. ESR is a powerful method for validating the evolutionary models used for ASR and can be applied in practice to any phylogenetic analysis of real biological sequences. Most significantly, ESR uses ASR methodology to provide a general method by which the biophysical properties of resurrected proteins can be compared to the properties of the true protein.