GenOrigin: A comprehensive protein-coding gene origination database on the evolutionary timescale of life

Constraint of accessible chromatins maps regulatory loci involved in maize speciation and domestication

Comparative genomic studies can identify genes under evolutionary constraint or specialized for trait innovation. Growing evidence suggests that evolutionary constraint also acts on non-coding regulatory sequences, exerting significant impacts on fitness-related traits, although it has yet to be thoroughly explored in plants. Using the assay for transposase-accessible chromatin by sequencing (ATAC-seq), we profile over 80,000 maize accessible chromatin regions (ACRs), revealing that ACRs evolve faster than coding genes, with about one-third being maize-specific and regulating genes associated with speciation. We highlight the role of transposable elements (TEs) in driving intraspecific innovation of ACRs and identify hundreds of candidate ACRs potentially involved in transcriptional rewiring during maize domestication. Additionally, we demonstrate the importance of accessible chromatin in maintaining subgenome dominance and controlling complex trait variations. This study establishes a framework for analyzing the evolutionary trajectory of plant regulatory sequences and offers candidate loci for downstream exploration and application in maize breeding.

Metabolomic and gene networks approaches reveal the role of mitochondrial membrane proteins in response of human melanoma cells to THz radiation

Terahertz (THz) radiation has gained attention due to technological advancements, but its biological effects remain unclear. We investigated the impact of 2.3 THz radiation on SK-MEL-28 cells using metabolomic and gene network analysis. Forty metabolites, primarily related to purine, pyrimidine synthesis and breakdown pathways, were significantly altered post-irradiation. Lipids, such as ceramides and phosphatidylcholines, were also affected. Gene network reconstruction and analysis identified key regulators of the enzymes involved in biosynthesis and degradation of significantly altered metabolites. Mitochondrial membrane components, such as the respiratory chain complex, the proton-transporting ATP synthase complex, and components of lipid rafts reacted to THz radiation. We propose that THz radiation induces reversible disruption of the lipid raft macromolecular structure, thereby altering mitochondrial molecule transport while maintaining protein integrity, which explains the high cell survival rate. Our findings enhance the understanding of THz biological effects and emphasize the role of membrane components in the cellular response to THz radiation.

Cross-species comparative single-cell transcriptomics highlights the molecular evolution and genetic basis of male infertility

In male animals, spermatogonia in testes differentiate into sperm, one of the most diverse cell types across species. Despite the evolutionary retention of key genes essential for spermatogenesis, the extent of their conservation remains unclear. To explore the genetic basis of spermatogenesis under strong selective pressure, we compare single-cell RNA sequencing (scRNA-seq) datasets from the testes of humans, mice, and fruit flies. Our analysis identifies conserved genes involved in key molecular programs, such as post-transcriptional regulation, meiosis, and energy metabolism. We perform gene knockout experiments of 20 candidate genes, three of which, when mutated in fruit flies, result in reduced male fertility, emphasizing the conservation of sperm centriole and steroid lipid processes across mammals and Drosophila. Additionally, deep-learning analysis uncovers potential transcriptional mechanisms driving gene-expression evolution. These findings establish a core genetic foundation for spermatogenesis, offering insights into sperm-phenotype evolution and the underlying mechanisms of male infertility.

Single-cell phylotranscriptomics of developmental and cell type evolution

Single-cell phylotranscriptomics is an emerging tool to reveal the molecular and cellular mechanisms of evolution. We summarize its utility in studying the hourglass pattern of ontogenetic evolution and for understanding the evolutionary history of cell types. The developmental hourglass model suggests that the mid-embryonic stage is the most conserved period of development across species, which is supported by morphological and molecular studies. Single-cell phylotranscriptomic analysis has revealed previously underappreciated heterogeneity in transcriptome ages among lineages and cell types throughout development, and has identified the lineages and tissues that drive the whole-organism hourglass pattern. Single-cell transcriptome age analyses also provide important insights into the origin of germ layers, the different selective forces on tissues during adaptation, and the evolutionary relationships between cell types.

Parallel gene size and isoform expansion of ancient neuronal genes

How nervous systems evolved is a central question in biology. A diversity of synaptic proteins is thought to play a central role in the formation of specific synapses leading to nervous system complexity. The largest animal genes, often spanning hundreds of thousands of base pairs, are known to be enriched for expression in neurons at synapses and are frequently mutated or misregulated in neurological disorders and diseases. Although many of these genes have been studied independently in the context of nervous system evolution and disease, general principles underlying their parallel evolution remain unknown. To investigate this, we directly compared orthologous gene sizes across eukaryotes. By comparing relative gene sizes within organisms, we identified a distinct class of large genes with origins predating the diversification of animals and, in many cases, the emergence of neurons as dedicated cell types. We traced this class of ancient large genes through evolution and found orthologs of the large synaptic genes potentially driving the immense complexity of metazoan nervous systems, including in humans and cephalopods. Moreover, we found that while these genes are evolving under strong purifying selection, as demonstrated by low dN/dS ratios, they have simultaneously grown larger and gained the most isoforms in animals. This work provides a new lens through which to view this distinctive class of large and multi-isoform genes and demonstrates how intrinsic genomic properties, such as gene length, can provide flexibility in molecular evolution and allow groups of genes and their host organisms to evolve toward complexity.

Dynamic remodeling of Escherichia coli interactome in response to environmental perturbations

Proteins play an essential role in the vital biological processes governing cellular functions. Most proteins function as members of macromolecular machines, with the network of interacting proteins revealing the molecular mechanisms driving the formation of these complexes. Profiling the physiology-driven remodeling of these interactions within different contexts constitutes a crucial component to achieving a comprehensive systems-level understanding of interactome dynamics. Here, we apply co-fractionation mass spectrometry and computational modeling to quantify and profile the interactions of ∼2000 proteins in the bacterium Escherichia coli cultured under 10 distinct culture conditions. The resulting quantitative co-elution patterns revealed large-scale condition-dependent interaction remodeling among protein complexes involved in diverse biochemical pathways in response to the unique environmental challenges. The network-level analysis highlighted interactome-wide biophysical properties and structural patterns governing interaction remodeling. Our results provide evidence of the local and global plasticity of the E. coli interactome along with a rigorous generalizable framework to define protein interaction specificity. We provide an accompanying interactive web application to facilitate the exploration of these rewired networks.

Analysis and Prediction of Pathogen Nucleic Acid Specificity for Toll-like Receptors in Vertebrates

Identification of key sequence, expression and function related features of nucleic acid-sensing host proteins is of fundamental importance to understand the dynamics of pathogen-specific host responses. To meet this objective, we considered toll-like receptors (TLRs), a representative class of membrane-bound sensor proteins, from 17 vertebrate species covering mammals, birds, reptiles, amphibians, and fishes in this comparative study. We identified the molecular signatures of host TLRs that are responsible for sensing pathogen nucleic acids or other pathogen-associated molecular patterns (PAMPs), and potentially play important roles in host defence mechanism. Interestingly, our findings reveal that such host-specific features are directly related to the strand (single or double) specificity of nucleic acid from pathogens. However, during host-pathogen interactions, such features were unable to explain the pathogenic PAMP (i.e., DNA, RNA or other) selectivity, suggesting a more complex mechanism. Using these features, we developed a number of machine learning models, of which Random Forest achieved a high performance (94.57% accuracy) to predict strand specificity of TLRs from protein-derived features. We applied the trained model to propose strand specificity of some previously uncharacterized distinct fish-specific novel TLRs (TLR18, TLR23, TLR24, TLR25, TLR27).

Ancient origins of complex neuronal genes

How nervous systems evolved is a central question in biology. An increasing diversity of synaptic proteins is thought to play a central role in the formation of specific synapses leading to nervous system complexity. The largest animal genes, often spanning millions of base pairs, are known to be enriched for expression in neurons at synapses and are frequently mutated or misregulated in neurological disorders and diseases. While many of these genes have been studied independently in the context of nervous system evolution and disease, general principles underlying their parallel evolution remain unknown. To investigate this, we directly compared orthologous gene sizes across eukaryotes. By comparing relative gene sizes within organisms, we identified a distinct class of large genes with origins predating the diversification of animals and in many cases the emergence of dedicated neuronal cell types. We traced this class of ancient large genes through evolution and found orthologs of the large synaptic genes driving the immense complexity of metazoan nervous systems, including in humans and cephalopods. Moreover, we found that while these genes are evolving under strong purifying selection as demonstrated by low dN/dS scores, they have simultaneously grown larger and gained the most isoforms in animals. This work provides a new lens through which to view this distinctive class of large and multi-isoform genes and demonstrates how intrinsic genomic properties, such as gene length, can provide flexibility in molecular evolution and allow groups of genes and their host organisms to evolve toward complexity.

Integrating massive RNA-seq data to elucidate transcriptome dynamics in Drosophila melanogaster

The volume of ribonucleic acid (RNA)-seq data has increased exponentially, providing numerous new insights into various biological processes. However, due to significant practical challenges, such as data heterogeneity, it is still difficult to ensure the quality of these data when integrated. Although some quality control methods have been developed, sample consistency is rarely considered and these methods are susceptible to artificial factors. Here, we developed MassiveQC, an unsupervised machine learning-based approach, to automatically download and filter large-scale high-throughput data. In addition to the read quality used in other tools, MassiveQC also uses the alignment and expression quality as model features. Meanwhile, it is user-friendly since the cutoff is generated from self-reporting and is applicable to multimodal data. To explore its value, we applied MassiveQC to Drosophila RNA-seq data and generated a comprehensive transcriptome atlas across 28 tissues from embryogenesis to adulthood. We systematically characterized fly gene expression dynamics and found that genes with high expression dynamics were likely to be evolutionarily young and expressed at late developmental stages, exhibiting high nonsynonymous substitution rates and low phenotypic severity, and they were involved in simple regulatory programs. We also discovered that human and Drosophila had strong positive correlations in gene expression in orthologous organs, revealing the great potential of the Drosophila system for studying human development and disease.

Genetic robustness control of auxin output in priming organ initiation

Auxin signaling is essential for organ initiation in plants. How genetic robustness controls auxin output during organ initiation is largely unknown. Here, we identified DORNROSCHEN-LIKE (DRNL) as a target of MONOPTEROS (MP) that plays essential roles in organ initiation. We demonstrate that MP physically interacts with DRNL to inhibit cytokinin accumulation by directly activating ARABIDOPSIS HISTIDINE PHOSPHOTRANSFER PROTEIN 6 and CYTOKININ OXIDASE 6. DRN, the paralogous gene of DRNL, acts redundantly with DRNL but is not coexpressed with DRNL in the organ founder cells in which DRNL is expressed. We demonstrate that DRNL directly inhibits DRN expression in the peripheral zone, whereas DRN transcripts are ectopically activated in drnl mutants and fully restore the functional deficiency of drnl in organ initiation. Our results provide a mechanistic framework for the robust control of auxin signaling in organ initiation through paralogous gene-triggered spatial gene compensation effects.

Evolution and function of developmentally dynamic pseudogenes in mammals

BACKGROUND

Pseudogenes are excellent markers for genome evolution, which are emerging as crucial regulators of development and disease, especially cancer. However, systematic functional characterization and evolution of pseudogenes remain largely unexplored.

RESULTS

To systematically characterize pseudogenes, we date the origin of human and mouse pseudogenes across vertebrates and observe a burst of pseudogene gain in these two lineages. Based on a hybrid sequencing dataset combining full-length PacBio sequencing, sample-matched Illumina sequencing, and public time-course transcriptome data, we observe that abundant mammalian pseudogenes could be transcribed, which contribute to the establishment of organ identity. Our analyses reveal that developmentally dynamic pseudogenes are evolutionarily conserved and show an increasing weight during development. Besides, they are involved in complex transcriptional and post-transcriptional modulation, exhibiting the signatures of functional enrichment. Coding potential evaluation suggests that 19% of human pseudogenes could be translated, thus serving as a new way for protein innovation. Moreover, pseudogenes carry disease-associated SNPs and conduce to cancer transcriptome perturbation.

CONCLUSIONS

Our discovery reveals an unexpectedly high abundance of mammalian pseudogenes that can be transcribed and translated, and these pseudogenes represent a novel regulatory layer. Our study also prioritizes developmentally dynamic pseudogenes with signatures of functional enrichment and provides a hybrid sequencing dataset for further unraveling their biological mechanisms in organ development and carcinogenesis in the future.

Genomic signatures associated with maintenance of genome stability and venom turnover in two parasitoid wasps

Parasitoid wasps are rapidly developing as a model for evolutionary biology. Here we present chromosomal genomes of two Anastatus wasps, A. japonicus and A. fulloi, and leverage these genomes to study two fundamental questions-genome size evolution and venom evolution. Anastatus shows a much larger genome than is known among other wasps, with unexpectedly recent bursts of LTR retrotransposons. Importantly, several genomic innovations, including Piwi gene family expansion, ubiquitous Piwi expression profiles, as well as transposable element-piRNA coevolution, have likely emerged for transposable element silencing to maintain genomic stability. Additionally, we show that the co-option evolution arose by expression shifts in the venom gland plays a dominant role in venom turnover. We also highlight the potential importance of non-venom genes that are coexpressed with venom genes during venom evolution. Our findings greatly advance the current understanding of genome size evolution and venom evolution, and these genomic resources will facilitate comparative genomics studies of insects in the future.