Genomic Complexity Places Less Restrictions on the Evolution of Young Coexpression Networks than Protein-Protein Interactions

Network properties constrain natural selection on gene expression in Caenorhabditis elegans

Gene regulatory networks (GRNs) integrate genetic and environmental signals to coordinate complex phenotypes and evolve through a balance of selection and drift. Using publicly available datasets from Caenorhabditis elegans, we investigated the extent of natural selection on transcript abundance by linking population-scale variation in gene expression to fecundity, a key fitness component. While the expression of most genes covaried only weakly with fitness, which is typical for polygenic traits, we identified seven transcripts under significant directional selection. These included nhr-114 and feh-1, implicating variation in nutrient-sensing and metabolic pathways as impacting fitness. Stronger directional selection on tissue-specific and older genes highlighted the germline and nervous system as focal points of adaptive change. Network position further constrained selection on gene expression; high-connectivity genes faced stronger stabilizing and directional selection, highlighting GRN architecture as a key factor in microevolutionary dynamics. The activity of transcription factors such as zip-3, which regulates mitochondrial stress responses, emerged as targets of selection, revealing potential links between energy homeostasis and fitness. Our findings demonstrate how GRNs mediate the interplay between selection and drift, shaping microevolutionary trajectories of gene expression and phenotypic diversity.

Subcellular Enrichment Patterns of New Genes in Drosophila Evolution

The evolutionary patterns of proteins within subcellular compartments underlie the innovation and diversification foundation of the living eukaryotic organism. The location of proteins in subcellular compartments promotes the formation of network interaction modules, which in turn reshape the architecture of higher-level protein-protein interaction networks. Here, we conducted the most up-to-date gene age dating of Drosophila melanogaster by employing recently available long-read sequencing genomes as references. We found that an elevated gene fixation in the most recent common ancestor of Drosophila genus predated the divergence between two Drosophila subgenera, and a significant tendency of these genes in D. melanogaster encode proteins that localize to the extracellular matrix, accompanying the adaptive radiation of Drosophila species. Proteins encoded by genes located in the extracellular space exhibit higher sequence divergence, suggesting a rapid evolutionary process. We also observed that proteins encoded by genes originating from the same evolutionary branches tend to co-localize in the same subcellular compartments, and proteins in the same subcellular compartment tend to interact with each other. The proteins encoded by genes that have persisted through deeper branches exhibit broader localization across multiple subcellular compartments, enhancing the likelihood of their integration into various protein or gene regulatory networks, thereby increasing functional diversity. These evolutionary patterns not only contribute to understanding the evolution of subcellular localization in proteins encoded by genes originating from different branches, but also provide insights into the evolution of protein-protein networks driven by the emergence of new genes.

Comparative Analyses of Gene Co-expression Networks: Implementations and Applications in the Study of Evolution

Similarities and differences in the associations of biological entities among species can provide us with a better understanding of evolutionary relationships. Often the evolution of new phenotypes results from changes to interactions in pre-existing biological networks and comparing networks across species can identify evidence of conservation or adaptation. Gene co-expression networks (GCNs), constructed from high-throughput gene expression data, can be used to understand evolution and the rise of new phenotypes. The increasing abundance of gene expression data makes GCNs a valuable tool for the study of evolution in non-model organisms. In this paper, we cover motivations for why comparing these networks across species can be valuable for the study of evolution. We also review techniques for comparing GCNs in the context of evolution, including local and global methods of graph alignment. While some protein-protein interaction (PPI) bioinformatic methods can be used to compare co-expression networks, they often disregard highly relevant properties, including the existence of continuous and negative values for edge weights. Also, the lack of comparative datasets in non-model organisms has hindered the study of evolution using PPI networks. We also discuss limitations and challenges associated with cross-species comparison using GCNs, and provide suggestions for utilizing co-expression network alignments as an indispensable tool for evolutionary studies going forward.

Function, dynamics and evolution of network motif modules in integrated gene regulatory networks of worm and plant

Gene regulatory networks (GRNs) consist of different molecular interactions that closely work together to establish proper gene expression in time and space. Especially in higher eukaryotes, many questions remain on how these interactions collectively coordinate gene regulation. We study high quality GRNs consisting of undirected protein–protein, genetic and homologous interactions, and directed protein–DNA, regulatory and miRNA–mRNA interactions in the worm Caenorhabditis elegans and the plant Arabidopsis thaliana. Our data-integration framework integrates interactions in composite network motifs, clusters these in biologically relevant, higher-order topological network motif modules, overlays these with gene expression profiles and discovers novel connections between modules and regulators. Similar modules exist in the integrated GRNs of worm and plant. We show how experimental or computational methodologies underlying a certain data type impact network topology. Through phylogenetic decomposition, we found that proteins of worm and plant tend to functionally interact with proteins of a similar age, while at the regulatory level TFs favor same age, but also older target genes. Despite some influence of the duplication mode difference, we also observe at the motif and module level for both species a preference for age homogeneity for undirected and age heterogeneity for directed interactions. This leads to a model where novel genes are added together to the GRNs in a specific biological functional context, regulated by one or more TFs that also target older genes in the GRNs. Overall, we detected topological, functional and evolutionary properties of GRNs that are potentially universal in all species.

Old and young duplicate genes reveal different responses to environmental changes in Arachis duranensis

Old and young duplicate genes have been reported in some organisms. However, little is known about the properties of old and young duplicate genes in Arachis. Here, we have identified old and young duplicate genes in Arachis duranensis, and analyzed the evolution, gene complexity, gene expression pattern, and functional divergence between old and young duplicate genes. Our results showed different evolutionary, gene complexity and gene expression patterns, as well as differing correlations between old and young duplicate genes. Gene ontology results showed that old duplicate genes play a crucial role in lipid and amino acid biosynthesis and the oxidation-reduction process and that young duplicate genes are preferentially involved in photosynthesis and response to biotic stimulus. Transcriptome data sets revealed that most old and young duplicate genes had asymmetric function, and only a few duplicate genes exhibited symmetric function under drought and nematode stress. We found that old duplicate genes are preferentially involved in lipid and amino acid metabolism and response to abiotic stress, while young duplicate genes are likely to participate in photosynthesis and response to biotic stress. This work provides a better understanding of the evolution and functional divergence of old and young duplicate genes in A. duranensis.

Co-adaption of tRNA gene copy number and amino acid usage influences translation rates in three life domains

Although more and more entangled participants of translation process were realized, how they cooperate and co-determine the final translation efficiency still lacks details. Here, we reasoned that the basic translation components, tRNAs and amino acids should be consistent to maximize the efficiency and minimize the cost. We firstly revealed that 310 out of 410 investigated genomes of three domains had significant co-adaptions between the tRNA gene copy numbers and amino acid compositions, indicating that maximum efficiency constitutes ubiquitous selection pressure on protein translation. Furthermore, fast-growing and larger bacteria are found to have significantly better co-adaption and confirmed the effect of this pressure. Within organism, highly expressed proteins and those connected to acute responses have higher co-adaption intensity. Thus, the better co-adaption probably speeds up the growing of cells through accelerating the translation of special proteins. Experimentally, manipulating the tRNA gene copy number to optimize co-adaption between enhanced green fluorescent protein (EGFP) and tRNA gene set of Escherichia coli indeed lifted the translation rate (speed). Finally, as a newly confirmed translation rate regulating mechanism, the co-adaption reflecting translation rate not only deepens our understanding on translation process but also provides an easy and practicable method to improve protein translation rates and productivity.

Protein intrinsic disorder negatively associates with gene age in different eukaryotic lineages

The emergence of new protein-coding genes in a specific lineage or species provides raw materials for evolutionary adaptations. Until recently, the biology of new genes emerging particularly from non-genic sequences remained unexplored. Although the new genes are subjected to variable selection pressure and face rapid deletion, some of them become functional and are retained in the gene pool. To acquire functional novelties, new genes often get integrated into the pre-existing ancestral networks. However, the mechanism by which young proteins acquire novel interactions remains unanswered till date. Since structural orientation contributes hugely to the mode of proteins' physical interactions, in this regard, we put forward an interesting question - Do new genes encode proteins with stable folds? Addressing the question, we demonstrated that the intrinsic disorder inversely correlates with the evolutionary gene ages - i.e. young proteins are richer in intrinsic disorder than the ancient ones. We further noted that young proteins, which are initially poorly connected hubs, prefer to be structurally more disordered than well-connected ancient proteins. The phenomenon strikingly defies the usual trend of well-connected proteins being highly disordered in structure. We justified that structural disorder might help poorly connected young proteins to undergo promiscuous interactions, which provides the foundation for novel protein interactions. The study focuses on the evolutionary perspectives of young proteins in the light of structural adaptations.