The evolutionary dynamics of eukaryotic gene order

Phylogenomic and synteny analysis of BAHD and SCP/SCPL gene families reveal their evolutionary histories in plant specialized metabolism

Plant chemical diversity is largely owing to a number of enzymes which catalyse reactions involved in the assembly, and in the subsequent chemical modifications, of the core structures of major classes of plant specialized metabolites. One such reaction is acylation. With this in mind, to study the deep evolutionary history of BAHD and the serine-carboxypeptidase-like (SCPL) acyltransferase genes, we assembled phylogenomic synteny networks based on a large-scale inference analysis of orthologues across whole-genome sequences of 126 species spanning Stramenopiles and Archaeplastida, including Arabidopsis thaliana, tomato (Solanum lycopersicum) and maize (Zea mays). As such, this study combined the study of genomic location with changes in gene sequences. Our analyses revealed that serine-carboxypeptidase (SCP)/serine-carboxypeptidase-like (SCPL) genes had a deeper evolutionary origin than BAHD genes, which expanded massively on the transition to land and with the development of the vascular system. The two gene families additionally display quite distinct patterns of copy number variation across phylogenies as well as differences in cross-phylogenetic syntenic network components. In unlocking the above observations, our analyses demonstrate the possibilities afforded by modern phylogenomic (syntenic) networks, but also highlight their current limitations, as demonstrated by the inability of phylogenetic methods to separate authentic SCPL acyltransferases from standard SCP peptide hydrolases.This article is part of the theme issue 'The evolution of plant metabolism'.

Are there conserved biosynthetic genes in lichens? Genome-wide assessment of terpene biosynthetic genes suggests ubiquitous distribution of the squalene synthase cluster

Lichen-forming fungi (LFF) are prolific producers of functionally and structurally diverse secondary metabolites, most of which are taxonomically exclusive and play lineage-specific roles. To date, widely distributed, evolutionarily conserved biosynthetic pathways in LFF are not known. However, this idea stems from polyketide derivatives, since most biochemical research on lichens has concentrated on polyketide synthases (PKSs). Here, we present the first systematic identification and comparison of terpene biosynthetic genes of LFF using all the available Lecanoromycete reference genomes and 22 de novo sequenced ones (111 in total, representing 60 genera and 23 families). We implemented genome mining and gene networking approaches to identify and group the biosynthetic gene clusters (BGCs) into networks of similar BGCs. Our large-scale analysis led to the identification of 724 terpene BGCs with varying degrees of pairwise similarity. Most BGCs in the dataset were unique with no similarity to a previously known fungal or bacterial BGC or among each other. Remarkably, we found two BGCs that were widely distributed in LFF. Interestingly, both conserved BGCs contain the same core gene, i.e., putatively a squalene/phytoene synthase (SQS), involved in sterol biosynthesis. This indicates that early gene duplications, followed by gene losses/gains and gene rearrangement are the major evolutionary factors shaping the composition of these widely distributed SQS BGCs across LFF. We provide an in-depth overview of these BGCs, including the transmembrane, conserved, variable and LFF-specific regions. Our study revealed that lichenized fungi do have a highly conserved BGC, providing the first evidence that a biosynthetic gene may constitute essential genes in lichens.

CLOCI: unveiling cryptic fungal gene clusters with generalized detection

Gene clusters are genomic loci that contain multiple genes that are functionally and genetically linked. Gene clusters collectively encode diverse functions, including small molecule biosynthesis, nutrient assimilation, metabolite degradation, and production of proteins essential for growth and development. Identifying gene clusters is a powerful tool for small molecule discovery and provides insight into the ecology and evolution of organisms. Current detection algorithms focus on canonical 'core' biosynthetic functions many gene clusters encode, while overlooking uncommon or unknown cluster classes. These overlooked clusters are a potential source of novel natural products and comprise an untold portion of overall gene cluster repertoires. Unbiased, function-agnostic detection algorithms therefore provide an opportunity to reveal novel classes of gene clusters and more precisely define genome organization. We present CLOCI (Co-occurrence Locus and Orthologous Cluster Identifier), an algorithm that identifies gene clusters using multiple proxies of selection for coordinated gene evolution. Our approach generalizes gene cluster detection and gene cluster family circumscription, improves detection of multiple known functional classes, and unveils non-canonical gene clusters. CLOCI is suitable for genome-enabled small molecule mining, and presents an easily tunable approach for delineating gene cluster families and homologous loci.

Single-cell new RNA sequencing reveals principles of transcription at the resolution of individual bursts

Analyses of transcriptional bursting from single-cell RNA-sequencing data have revealed patterns of variation and regulation in the kinetic parameters that could be inferred. Here we profiled newly transcribed (4-thiouridine-labelled) RNA across 10,000 individual primary mouse fibroblasts to more broadly infer bursting kinetics and coordination. We demonstrate that inference from new RNA profiles could separate the kinetic parameters that together specify the burst size, and that the synthesis rate (and not the transcriptional off rate) controls the burst size. Importantly, transcriptome-wide inference of transcriptional on and off rates provided conclusive evidence that RNA polymerase II transcribes genes in bursts. Recent reports identified examples of transcriptional co-bursting, yet no global analyses have been performed. The deep new RNA profiles we generated with allelic resolution demonstrated that co-bursting rarely appears more frequently than expected by chance, except for certain gene pairs, notably paralogues located in close genomic proximity. Altogether, new RNA single-cell profiling critically improves the inference of transcriptional bursting and provides strong evidence for independent transcriptional bursting of mammalian genes.

Cellular control of protein levels: A systems biology perspective

How cells regulate protein levels is a central question of biology. Over the past decades, molecular biology research has provided profound insights into the mechanisms and the molecular machinery governing each step of the gene expression process, from transcription to protein degradation. Recent advances in transcriptomics and proteomics have complemented our understanding of these fundamental cellular processes with a quantitative, systems-level perspective. Multi-omic studies revealed significant quantitative, kinetic and functional differences between the genome, transcriptome and proteome. While protein levels often correlate with mRNA levels, quantitative investigations have demonstrated a substantial impact of translation and protein degradation on protein expression control. In addition, protein-level regulation appears to play a crucial role in buffering protein abundances against undesirable mRNA expression variation. These findings have practical implications for many fields, including gene function prediction and precision medicine.

Annotation of nuclear lncRNAs based on chromatin interactions

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Some specific nuclear lncRNAs have been shown to be important regulatory components acting locally. As RNA-chromatin interaction and Hi-C chromatin conformation data showed that chromatin interactions of nuclear lncRNAs are determined by the local chromatin 3D conformation, we used Hi-C data to identify potential target genes of lncRNAs. RNA-protein interaction data suggested that nuclear lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. Nuclear lncRNAs may therefore play a role in directing regulatory factors to locations spatially close to the lncRNA gene. We provide the analysis results through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

A Genome-Wide Analysis of the CEP Gene Family in Cotton and a Functional Study of GhCEP46-D05 in Plant Development

C-TERMINALLY ENCODED PEPTIDEs (CEPs) are a class of peptide hormones that have been shown in previous studies to play an important role in regulating the development and response to abiotic stress in model plants. However, their role in cotton is not well understood. In this study, we identified 54, 59, 34, and 35 CEP genes from Gossypium hirsutum (2n = 4x = 52, AD1), G. barbadense (AD2), G. arboreum (2n = 2X = 26, A2), and G. raimondii (2n = 2X = 26, D5), respectively. Sequence alignment and phylogenetic analyses indicate that cotton CEP proteins can be categorized into two subgroups based on the differentiation of their CEP domain. Chromosomal distribution and collinearity analyses show that most of the cotton CEP genes are situated in gene clusters, suggesting that segmental duplication may be a critical factor in CEP gene expansion. Expression pattern analyses showed that cotton CEP genes are widely expressed throughout the plant, with some genes exhibiting specific expression patterns. Ectopic expression of GhCEP46-D05 in Arabidopsis led to a significant reduction in both root length and seed size, resulting in a dwarf phenotype. Similarly, overexpression of GhCEP46-D05 in cotton resulted in reduced internode length and plant height. These findings provide a foundation for further investigation into the function of cotton CEP genes and their potential role in cotton breeding.

A DNA circuit that records molecular events

Characterizing the relative onset time, strength, and duration of molecular signals is critical for understanding the operation of signal transduction and genetic regulatory networks. However, detecting multiple such molecules as they are produced and then quickly consumed is challenging. A MER can encode information about transient molecular events as stable DNA sequences and are amenable to downstream sequencing or other analysis. Here, we report the development of a de novo molecular event recorder that processes information using a strand displacement reaction network and encodes the information using the primer exchange reaction, which can be decoded and quantified by DNA sequencing. The event recorder was able to classify the order at which different molecular signals appeared in time with 88% accuracy, the concentrations with 100% accuracy, and the duration with 75% accuracy. This simultaneous and highly programmable multiparameter recording could enable the large-scale deciphering of molecular events such as within dynamic reaction environments, living cells, or tissues.

Functional and Evolutionary Integration of a Fungal Gene With a Bacterial Operon

Siderophores are crucial for iron-scavenging in microorganisms. While many yeasts can uptake siderophores produced by other organisms, they are typically unable to synthesize siderophores themselves. In contrast, Wickerhamiella/Starmerella (W/S) clade yeasts gained the capacity to make the siderophore enterobactin following the remarkable horizontal acquisition of a bacterial operon enabling enterobactin synthesis. Yet, how these yeasts absorb the iron bound by enterobactin remains unresolved. Here, we demonstrate that Enb1 is the key enterobactin importer in the W/S-clade species Starmerella bombicola. Through phylogenomic analyses, we show that ENB1 is present in all W/S clade yeast species that retained the enterobactin biosynthetic genes. Conversely, it is absent in species that lost the ent genes, except for Starmerella stellata, making this species the only cheater in the W/S clade that can utilize enterobactin without producing it. Through phylogenetic analyses, we infer that ENB1 is a fungal gene that likely existed in the W/S clade prior to the acquisition of the ent genes and subsequently experienced multiple gene losses and duplications. Through phylogenetic topology tests, we show that ENB1 likely underwent horizontal gene transfer from an ancient W/S clade yeast to the order Saccharomycetales, which includes the model yeast Saccharomyces cerevisiae, followed by extensive secondary losses. Taken together, these results suggest that the fungal ENB1 and bacterial ent genes were cooperatively integrated into a functional unit within the W/S clade that enabled adaptation to iron-limited environments. This integrated fungal-bacterial circuit and its dynamic evolution determine the extant distribution of yeast enterobactin producers and cheaters.

A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms

Traditional gene set enrichment analysis falters when applied to large genomic domains, where neighboring genes often share functions. This spatial dependency creates misleading enrichments, mistaking mere physical proximity for genuine biological connections. Here we present Spatial Adjusted Gene Ontology (SAGO), a novel cyclic permutation-based approach, to tackle this challenge. SAGO separates enrichments due to spatial proximity from genuine biological links by incorporating the genes' spatial arrangement into the analysis. We applied SAGO to various datasets in which the identified genomic intervals are large, including replication timing domains, large H3K9me3 and H3K27me3 domains, HiC compartments and lamina-associated domains (LADs). Intriguingly, applying SAGO to prostate cancer samples with large copy number alteration (CNA) domains eliminated most of the enriched GO terms, thus helping to accurately identify biologically relevant gene sets linked to oncogenic processes, free from spatial bias.

Chromatin gene-gene loops support the cross-regulation of genes with related function

Chromatin loops between gene pairs have been observed in diverse contexts in both flies and vertebrates. Combining high-resolution Capture-C, DNA fluorescence in situ hybridization, and genetic perturbations, we dissect the functional role of three loops between genes with related function during Drosophila embryogenesis. By mutating the loop anchor (but not the gene) or the gene (but not loop anchor), we disentangle loop formation and gene expression and show that the 3D proximity of paralogous gene loci supports their co-regulation. Breaking the loop leads to either an attenuation or enhancement of expression and perturbs their relative levels of expression and cross-regulation. Although many loops appear constitutive across embryogenesis, their function can change in different developmental contexts. Taken together, our results indicate that chromatin gene-gene loops act as architectural scaffolds that can be used in different ways in different contexts to fine-tune the coordinated expression of genes with related functions and sustain their cross-regulation.

Evidence of Nonrandom Patterns of Functional Chromosome Organization in Danaus plexippus

Our understanding on the interplay between gene functionality and gene arrangement at different chromosome scales relies on a few Diptera and the honeybee, species with quality reference genome assemblies, accurate gene annotations, and abundant transcriptome data. Using recently generated 'omic resources in the monarch butterfly Danaus plexippus, a species with many more and smaller chromosomes relative to Drosophila species and the honeybee, we examined the organization of genes preferentially expressed at broadly defined developmental stages (larva, pupa, adult males, and adult females) at both fine and whole-chromosome scales. We found that developmental stage-regulated genes do not form more clusters, but do form larger clusters, than expected by chance, a pattern consistent across the gene categories examined. Notably, out of the 30 chromosomes in the monarch genome, 12 of them, plus the fraction of the chromosome Z that corresponds to the ancestral Z in other Lepidoptera, were found enriched for developmental stage-regulated genes. These two levels of nonrandom gene organization are not independent as enriched chromosomes for developmental stage-regulated genes tend to harbor disproportionately large clusters of these genes. Further, although paralogous genes were overrepresented in gene clusters, their presence is not enough to explain two-thirds of the documented cases of whole-chromosome enrichment. The composition of the largest clusters often included paralogs from more than one multigene family as well as unrelated single-copy genes. Our results reveal intriguing patterns at the whole-chromosome scale in D. plexippus while shedding light on the interplay between gene expression and chromosome organization beyond Diptera and Hymenoptera.

Dynamics and Epigenetics of the Epidermal Differentiation Complex

Epidermis is the outer skin layer built of specialized cells called keratinocytes. Keratinocytes undergo a unique differentiation process, also known as cornification, during which their gene expression pattern, morphology and other properties change remarkably to the effect that the terminally differentiated, cornified cells can form a physical barrier, which separates the underlying tissues from the environment. Many genes encoding proteins that are important for epidermal barrier formation are located in a gene cluster called epidermal differentiation complex (EDC). Recent data provided valuable information on the dynamics of the EDC locus and the network of interactions between EDC gene promoters, enhancers and other regions, during keratinocytes differentiation. These data, together with results concerning changes in epigenetic modifications, provide a valuable insight into the mode of regulation of EDC gene expression.

KNeXT: a NetworkX-based topologically relevant KEGG parser

Automating the recreation of gene and mixed gene-compound networks from Kyoto Encyclopedia of Genes and Genomes (KEGG) Markup Language (KGML) files is challenging because the data structure does not preserve the independent or loosely connected neighborhoods in which they were originally derived, referred to here as its topological environment. Identical accession numbers may overlap, causing neighborhoods to artificially collapse based on duplicated identifiers. This causes current parsers to create misleading or erroneous graphical representations when mixed gene networks are converted to gene-only networks. To overcome these challenges we created a python-based KEGG NetworkX Topological (KNeXT) parser that allows users to accurately recapitulate genetic networks and mixed networks from KGML map data. The software, archived as a python package index (PyPI) file to ensure broad application, is designed to ingest KGML files through built-in APIs and dynamically create high-fidelity topological representations. The utilization of NetworkX's framework to generate tab-separated files additionally ensures that KNeXT results may be imported into other graph frameworks and maintain programmatic access to the original x-y axis positions to each node in the KEGG pathway. KNeXT is a well-described Python 3 package that allows users to rapidly download and aggregate specific KGML files and recreate KEGG pathways based on a range of user-defined settings. KNeXT is platform-independent, distinctive, and it is not written on top of other Python parsers. Furthermore, KNeXT enables users to parse entire local folders or single files through command line scripts and convert the output into NCBI or UniProt IDs. KNeXT provides an ability for researchers to generate pathway visualizations while persevering the original context of a KEGG pathway. Source code is freely available at https://github.com/everest-castaneda/knext.

Pathogenicity analysis and comparative genomics reveal the different infection strategies between the generalist Metarhizium anisopliae and the specialist Metarhizium acridum

BACKGROUND

The fungal genera Metarhizium contain many important multiple species that are used as biocontrol agents and as model organisms for exploring insect-fungal interactions. Metarhizium spp. exhibit different traits of pathogenicity, suggesting that the pathogenesis can be quite distinctive. However, the underlying differences in their pathogenesis remain poorly understood.

RESULTS

Pathogenicity analysis showed that Metarhizium anisopliae (strain CQMa421) displayed higher virulence against oriental migratory locusts, Locusta migratoria manilensis (Meyen), than the acridid-specific specie Metarhizium acridum (strain CQMa102). Relative to M. acridum, M. anisopliae possessed a higher conidial hydrophobicity, increased ability to penetrate the host, accelerated growth under hypoxia and enhanced ability for the utilization of different carbon sources. Different distributions of carbohydrate epitopes at cell wall surface of M. anisopliae might also contribute to successful evasion of host immune defenses. Comparative genomics showed that M. anisopliae has 98 more virulence-related secreted proteins (133) than M. acridum (35), which can be functionally classified as hydrolases, virulence effectors, cell wall degradation and stress tolerance-related proteins, and helpful to the cuticle penetration and host internal environment adaption. In addition, differences in genomic clusters specifically related to secondary metabolites, including the clusters of Indole-NRPS hybrid, T1PKS-NRPS like hybrid, Betalactone, Fungal-Ripp and NRPS-Terpene hybrid, may lead to differences in core virulence-related secondary metabolite genes in M. acridum (18) and M. anisopliae (36).

CONCLUSION

The comparative study provided new insights into the different infection strategies between M. anisopliae and M. acridum, and further facilitate the identification of virulence-related genes for the improvement of mycoinsecticides. © 2023 Society of Chemical Industry.

Computational inference of eIF4F complex function and structure in human cancers

The canonical eukaryotic initiation factor 4F (eIF4F) complex, composed of eIF4G1, eIF4A1, and the cap-binding protein eIF4E, plays a crucial role in cap-dependent translation initiation in eukaryotic cells. An alternative cap-independent initiation can occur, involving only eIF4G1 and eIF4A1 through internal ribosome entry sites (IRESs). This mechanism is considered complementary to cap-dependent initiation, particularly in tumors under stress conditions. However, the selection and molecular mechanism of specific translation initiation remains poorly understood in human cancers. Thus, we analyzed gene copy number variations (CNVs) in TCGA tumor samples and found frequent amplification of genes involved in translation initiation. Copy number gains in EIF4G1 and EIF3E frequently co-occur across human cancers. Additionally, EIF4G1 expression strongly correlates with genes from cancer cell survival pathways including cell cycle and lipogenesis, in tumors with EIF4G1 amplification or duplication. Furthermore, we revealed that eIF4G1 and eIF4A1 protein levels strongly co-regulate with ribosomal subunits, eIF2, and eIF3 complexes, while eIF4E co-regulates with 4E-BP1, ubiquitination, and ESCRT proteins. Utilizing Alphafold predictions, we modeled the eIF4F structure with and without eIF4E binding. For cap-dependent initiation, our modeling reveals extensive interactions between the N-terminal eIF4E-binding domain of eIF4G1 and eIF4E. Furthermore, the eIF4G1 HEAT-2 domain positions eIF4E near the eIF4A1 N-terminal domain (NTD), resulting in the collaborative enclosure of the RNA binding cavity within eIF4A1. In contrast, during cap-independent initiation, the HEAT-2 domain directly binds the eIF4A1-NTD, leading to a stronger interaction between eIF4G1 and eIF4A1, thus closing the mRNA binding cavity without the involvement of eIF4E.

Hold out the genome: a roadmap to solving the cis-regulatory code

Gene expression is regulated by transcription factors that work together to read cis-regulatory DNA sequences. The 'cis-regulatory code' - how cells interpret DNA sequences to determine when, where and how much genes should be expressed - has proven to be exceedingly complex. Recently, advances in the scale and resolution of functional genomics assays and machine learning have enabled substantial progress towards deciphering this code. However, the cis-regulatory code will probably never be solved if models are trained only on genomic sequences; regions of homology can easily lead to overestimation of predictive performance, and our genome is too short and has insufficient sequence diversity to learn all relevant parameters. Fortunately, randomly synthesized DNA sequences enable testing a far larger sequence space than exists in our genomes, and designed DNA sequences enable targeted queries to maximally improve the models. As the same biochemical principles are used to interpret DNA regardless of its source, models trained on these synthetic data can predict genomic activity, often better than genome-trained models. Here we provide an outlook on the field, and propose a roadmap towards solving the cis-regulatory code by a combination of machine learning and massively parallel assays using synthetic DNA.

Examination of Large Chromosomal Inversions in the Genome of Erwinia amylovora Strains Reveals Worldwide Distribution and North America-Specific Types

Erwinia amylovora is a relatively homogeneous species with low genetic diversity at the nucleotide level. However, phenotypic differences and genomic structural variations among E. amylovora strains have been documented. In this study, we identified 10 large chromosomal inversion (LCI) types in the Spiraeoideae-infecting (SI) E. amylovora strains by combining whole genome sequencing and PCR-based molecular markers. It was found that LCIs were mainly caused by homologous recombination events among seven rRNA operons (rrns) in SI E. amylovora strains. Although ribotyping results identified inter- and intra-variations in the internal transcribed spacer (ITS1 and ITS2) regions among rrns, LCIs tend to occur between rrns transcribed in the opposite directions and with the same tRNA content (tRNA-Glu or tRNA-Ile/Ala) in ITS1. Based on the LCI types, physical/estimated replichore imbalance (PRI/ERI) was examined and calculated. Among the 117 SI strains evaluated, the LCI types of Ea1189, CFBP1430, and Ea273 were the most common, with ERI values at 1.31, 7.87, and 4.47°, respectively. These three LCI types had worldwide distribution, whereas the remaining seven LCI types were restricted to North America (or certain regions of the United States). Our results indicated ongoing chromosomal recombination events in the SI E. amylovora population and showed that LCI events are mostly symmetrical, keeping the ERI less than 15°. These findings provide initial evidence about the prevalence of certain LCI types in E. amylovora strains, how LCI occurs, and its potential evolutionary advantage and history, which might help track the movement of the pathogen.

Functional and evolutionary integration of a fungal gene with a bacterial operon

Siderophores are crucial for iron-scavenging in microorganisms. While many yeasts can uptake siderophores produced by other organisms, they are typically unable to synthesize siderophores themselves. In contrast, Wickerhamiella/Starmerella (W/S) clade yeasts gained the capacity to make the siderophore enterobactin following the remarkable horizontal acquisition of a bacterial operon enabling enterobactin synthesis. Yet, how these yeasts absorb the iron bound by enterobactin remains unresolved. Here, we demonstrate that Enb1 is the key enterobactin importer in the W/S-clade species Starmerella bombicola. Through phylogenomic analyses, we show that ENB1 is present in all W/S clade yeast species that retained the enterobactin biosynthetic genes. Conversely, it is absent in species that lost the ent genes, except for Starmerella stellata, making this species the only cheater in the W/S clade that can utilize enterobactin without producing it. Through phylogenetic analyses, we infer that ENB1 is a fungal gene that likely existed in the W/S clade prior to the acquisition of the ent genes and subsequently experienced multiple gene losses and duplications. Through phylogenetic topology tests, we show that ENB1 likely underwent horizontal gene transfer from an ancient W/S clade yeast to the order Saccharomycetales, which includes the model yeast Saccharomyces cerevisiae, followed by extensive secondary losses. Taken together, these results suggest that the fungal ENB1 and bacterial ent genes were cooperatively integrated into a functional unit within the W/S clade that enabled adaptation to iron-limited environments. This integrated fungal-bacterial circuit and its dynamic evolution determines the extant distribution of yeast enterobactin producers and cheaters.

Gene communities in co-expression networks across different tissues

With the recent availability of tissue-specific gene expression data, e.g., provided by the GTEx Consortium, there is interest in comparing gene co-expression patterns across tissues. One promising approach to this problem is to use a multilayer network analysis framework and perform multilayer community detection. Communities in gene co-expression networks reveal groups of genes similarly expressed across individuals, potentially involved in related biological processes responding to specific environmental stimuli or sharing common regulatory variations. We construct a multilayer network in which each of the four layers is an exocrine gland tissue-specific gene co-expression network. We develop methods for multilayer community detection with correlation matrix input and an appropriate null model. Our correlation matrix input method identifies five groups of genes that are similarly co-expressed in multiple tissues (a community that spans multiple layers, which we call a generalist community) and two groups of genes that are co-expressed in just one tissue (a community that lies primarily within just one layer, which we call a specialist community). We further found gene co-expression communities where the genes physically cluster across the genome significantly more than expected by chance (on chromosomes 1 and 11). This clustering hints at underlying regulatory elements determining similar expression patterns across individuals and cell types. We suggest that KRTAP3-1, KRTAP3-3, and KRTAP3-5 share regulatory elements in skin and pancreas. Furthermore, we find that CELA3A and CELA3B share associated expression quantitative trait loci in the pancreas. The results indicate that our multilayer community detection method for correlation matrix input extracts biologically interesting communities of genes.

Chromosome-level genome assembly of Niphotrichum japonicum provides new insights into heat stress responses in mosses

With a diversity of approximately 22,000 species, bryophytes (hornworts, liverworts, and mosses) represent a major and diverse lineage of land plants. Bryophytes can thrive in many extreme environments as they can endure the stresses of drought, heat, and cold. The moss Niphotrichum japonicum (Grimmiaceae, Grimmiales) can subsist for extended periods under heat and drought conditions, providing a good candidate for studying the genetic basis underlying such high resilience. Here, we de novo assembled the genome of N. japonicum using Nanopore long reads combined with Hi-C scaffolding technology to anchor the 191.61 Mb assembly into 14 pseudochromosomes. The genome structure of N. japonicum's autosomes is mostly conserved and highly syntenic, in contrast to the sparse and disordered genes present in its sex chromosome. Comparative genomic analysis revealed the presence of 10,019 genes exclusively in N. japonicum. These genes may contribute to the species-specific resilience, as demonstrated by the gene ontology (GO) enrichment. Transcriptome analysis showed that 37.44% (including 3,107 unique genes) of the total annotated genes (26,898) exhibited differential expression as a result of heat-induced stress, and the mechanisms that respond to heat stress are generally conserved across plants. These include the upregulation of HSPs, LEAs, and reactive oxygen species (ROS) scavenging genes, and the downregulation of PPR genes. N. japonicum also appears to have distinctive thermal mechanisms, including species-specific expansion and upregulation of the Self-incomp_S1 gene family, functional divergence of duplicated genes, structural clusters of upregulated genes, and expression piggybacking of hub genes. Overall, our study highlights both shared and species-specific heat tolerance strategies in N. japonicum, providing valuable insights into the heat tolerance mechanism and the evolution of resilient plants.

Computational inference of eIF4F complex function and structure in human cancers

The canonical eukaryotic initiation factor 4F (eIF4F) complex, composed of eIF4G1, eIF4A1, and the cap-binding protein eIF4E, plays a crucial role in cap-dependent translation initiation in eukaryotic cells (1). However, cap-independent initiation can occur through internal ribosomal entry sites (IRESs), involving only eIF4G1 and eIF4A1 present, which is considered to be a complementary process to cap-dependent initiation in tumors under stress conditions (2). The selection and molecular mechanism of specific translation initiation in human cancers remains poorly understood. Thus, we analyzed gene copy number variations (CNVs) in TCGA tumor samples and found frequent amplification of genes involved in translation initiation. Copy number gains in EIF4G1 and EIF3E frequently co-occur across human cancers. Additionally, EIF4G1 expression strongly correlates with genes from cancer cell survival pathways including cell cycle and lipogenesis, in tumors with EIF4G1 amplification or duplication. Furthermore, we revealed that eIF4G1 and eIF4A1 protein levels strongly co-regulate with ribosomal subunits, eIF2, and eIF3 complexes, while eIF4E co-regulates with 4E-BP1, ubiquitination, and ESCRT proteins. Using Alphafold predictions, we modeled the eIF4F structure with and without eIF4G1-eIF4E binding. The modeling for cap-dependent initiation suggests that eIF4G1 interacts with eIF4E through its N-terminal eIF4E-binding domain, bringing eIF4E near the eIF4A1 mRNA binding cavity and closing the cavity with both eIF4G1 HEAT-2 domain and eIF4E. In the cap-independent mechanism, α-helix 5 of eIF4G1 HEAT-2 domain instead directly interacts with the eIF4A1 N-terminal domain to close the mRNA binding cavity without eIF4E involvement, resulting in a stronger interaction between eIF4G1 and eIF4A1.

Significance Statement

Translation initiation is primarily governed by eIF4F, employing a "cap-dependent" mechanism, but eIF4F dysregulation may lead to a "cap-independent" mechanism in stressed cancer cells. We found frequent amplification of translation initiation genes, and co-occurring copy number gains of EIF4G1 and EIF3E genes in human cancers. EIF4G1 amplification or duplication may be positively selected for its beneficial impact on the overexpression of cancer survival genes. The co-regulation of eIF4G1 and eIF4A1, distinctly from eIF4E, reveals eIF4F dysregulation favoring cap-independent initiation. Alphafold predicts changes in the eIF4F complex assembly to accommodate both initiation mechanisms. These findings have significant implications for evaluating cancer cell vulnerability to eIF4F inhibition and developing treatments that target cancer cells with dependency on the translation initiation mechanism.

3D organization of regulatory elements for transcriptional regulation in Arabidopsis

BACKGROUND

Although spatial organization of compartments and topologically associating domains at large scale is relatively well studied, the spatial organization of regulatory elements at fine scale is poorly understood in plants.

RESULTS

Here we perform high-resolution chromatin interaction analysis using paired-end tag sequencing approach. We map chromatin interactions tethered with RNA polymerase II and associated with heterochromatic, transcriptionally active, and Polycomb-repressive histone modifications in Arabidopsis. Analysis of the regulatory repertoire shows that distal active cis-regulatory elements are linked to their target genes through long-range chromatin interactions with increased expression of the target genes, while poised cis-regulatory elements are linked to their target genes through long-range chromatin interactions with depressed expression of the target genes. Furthermore, we demonstrate that transcription factor MYC2 is critical for chromatin spatial organization, and propose that MYC2 occupancy and MYC2-mediated chromatin interactions coordinately facilitate transcription within the framework of 3D chromatin architecture. Analysis of functionally related gene-defined chromatin connectivity networks reveals that genes implicated in flowering-time control are functionally compartmentalized into separate subdomains via their spatial activity in the leaf or shoot apical meristem, linking active mark- or Polycomb-repressive mark-associated chromatin conformation to coordinated gene expression.

CONCLUSION

The results reveal that the regulation of gene transcription in Arabidopsis is not only by linear juxtaposition, but also by long-range chromatin interactions. Our study uncovers the fine scale genome organization of Arabidopsis and the potential roles of such organization in orchestrating transcription and development.

Exploring inbreeding dynamics by considering reproductive bound and polygyny

Inbreeding is a clinically significant measure of a population dependent on human social structures including the population size or the cultural traits. Here, we propose an expanded and elaborate model to analyze the inbreeding within a population where explicit polygyny and inbreeding bounds are taken into account. Unlike the models presented so far, we implemented biologically realistic assumptions that there is the disproportionate probability of males to reproduce (polygyny) and female reproduction is bounded. Using the proposed model equations, we changed the parameters that represent the polygyny degree, the female reproductive bound correlated to the mutation rate, and the total population size. The disappearance of the polygyny that numerous human societies experienced results in the long-lasting effect of the decreasing inbreeding coefficient. Decreased female reproductive bound correlated with a higher mutation rate reveals similar results. After the effect of each factor is analyzed, we modeled the dynamics of the inbreeding coefficient throughout an imaginary human population where polygyny disappears and late marriage becomes prevalent. In this group, the population size gradually and exponentially increases reflecting the traits of prehistoric human society and rising agricultural productivity. To observe how late and less marriage, the feature of the modern developed society, affects the inbreeding dynamics, the female reproductive bound and the population size were assumed to decrease after the population upsurge. The model can explain the decreasing trend of the prehistoric inbreeding coefficient of the actual human population and predict how the trend will be shifted when traits of modern societies continue.

Diffusion-enhanced characterization of 3D chromatin structure reveals its linkage to gene regulatory networks and the interactome

The interactome networks at the DNA, RNA, and protein levels are crucial for cellular functions, and the diverse variations of these networks are heavily involved in the establishment of different cell states. We have developed a diffusion-based method, Hi-C to geometry (CTG), to obtain reliable geometric information on the chromatin from Hi-C data. CTG produces a consistent and reproducible framework for the 3D genomic structure and provides a reliable and quantitative understanding of the alterations of genomic structures under different cellular conditions. The genomic structure yielded by CTG serves as an architectural blueprint of the dynamic gene regulatory network, based on which cell-specific correspondence between gene-gene and corresponding protein-protein physical interactions, as well as transcription correlation, is revealed. We also find that gene fusion events are significantly enriched between genes of short CTG distances and are thus close in 3D space. These findings indicate that 3D chromatin structure is at least partially correlated with downstream processes such as transcription, gene regulation, and even regulatory networking through affecting protein-protein interactions.

Multidimensional conservation analysis decodes the expression of conserved long noncoding RNAs

Although long noncoding RNAs (lncRNAs) experience weaker evolutionary constraints and exhibit lower sequence conservation than coding genes, they can still conserve their features in various aspects. Here, we used multiple approaches to systemically evaluate the conservation between human and mouse lncRNAs from various dimensions including sequences, promoter, global synteny, and local synteny, which led to the identification of 1,731 conserved lncRNAs with 427 high-confidence ones meeting multiple criteria. Conserved lncRNAs, compared with non-conserved ones, generally have longer gene bodies, more exons and transcripts, stronger connections with human diseases, and are more abundant and widespread across different tissues. Transcription factor (TF) profile analysis revealed a significant enrichment of TF types and numbers in the promoters of conserved lncRNAs. We further identified a set of TFs that preferentially bind to conserved lncRNAs and exert stronger regulation on conserved than non-conserved lncRNAs. Our study has reconciled some discrepant interpretations of lncRNA conservation and revealed a new set of transcriptional factors ruling the expression of conserved lncRNAs.

Predicting gene expression divergence between single-copy orthologs in two species

Predicting gene expression divergence is integral to understanding the emergence of new biological functions and associated traits. Whereas several sophisticated methods have been developed for this task, their applications are either limited to duplicate genes or require expression data from more than two species. Thus, here we present PiXi, the first machine learning framework for predicting gene expression divergence between single-copy orthologs in two species. PiXi models gene expression evolution as an Ornstein-Uhlenbeck process, and overlays this model with multi-layer neural network, random forest, and support vector machine architectures for making predictions. It outputs the predicted class "conserved" or "diverged" for each pair of orthologs, as well as their predicted expression optima in the two species. We show that PiXi has high power and accuracy in predicting gene expression divergence between single-copy orthologs, as well as high accuracy and precision in estimating their expression optima in the two species, across a wide range of evolutionary scenarios, with the globally best performance achieved by a multi-layer neural network. Moreover, application of our best performing PiXi predictor to empirical gene expression data from single-copy orthologs residing at different loci in two species of Drosophila reveals that approximately 23% underwent expression divergence after positional relocation. Further analysis shows that several of these "diverged" genes are involved in the electron transport chain of the mitochondrial membrane, suggesting that new chromatin environments may impact energy production in Drosophila. Thus, by providing a toolkit for predicting gene expression divergence between single-copy orthologs in two species, PiXi can shed light on the origins of novel phenotypes across diverse biological processes and study systems.

The Operon as a Conundrum of Gene Dynamics and Biochemical Constraints: What We Have Learned from Histidine Biosynthesis

Operons represent one of the leading strategies of gene organization in prokaryotes, having a crucial influence on the regulation of gene expression and on bacterial chromosome organization. However, there is no consensus yet on why, how, and when operons are formed and conserved, and many different theories have been proposed. Histidine biosynthesis is a highly studied metabolic pathway, and many of the models suggested to explain operons origin and evolution can be applied to the histidine pathway, making this route an attractive model for the study of operon evolution. Indeed, the organization of his genes in operons can be due to a progressive clustering of biosynthetic genes during evolution, coupled with a horizontal transfer of these gene clusters. The necessity of physical interactions among the His enzymes could also have had a role in favoring gene closeness, of particular importance in extreme environmental conditions. In addition, the presence in this pathway of paralogous genes, heterodimeric enzymes and complex regulatory networks also support other operon evolution hypotheses. It is possible that histidine biosynthesis, and in general all bacterial operons, may result from a mixture of several models, being shaped by different forces and mechanisms during evolution.

Promoter-pervasive transcription causes RNA polymerase II pausing to boost DOG1 expression in response to salt

Eukaryotic genomes are pervasively transcribed by RNA polymerase II. Yet, the molecular and biological implications of such a phenomenon are still largely puzzling. Here, we describe noncoding RNA transcription upstream of the Arabidopsis thaliana DOG1 gene, which governs salt stress responses and is a key regulator of seed dormancy. We find that expression of the DOG1 gene is induced by salt stress, thereby causing a delay in seed germination. We uncover extensive transcriptional activity on the promoter of the DOG1 gene, which produces a variety of lncRNAs. These lncRNAs, named PUPPIES, are co-directionally transcribed and extend into the DOG1 coding region. We show that PUPPIES RNAs respond to salt stress and boost DOG1 expression, resulting in delayed germination. This positive role of pervasive PUPPIES transcription on DOG1 gene expression is associated with augmented pausing of RNA polymerase II, slower transcription and higher transcriptional burst size. These findings highlight the positive role of upstream co-directional transcription in controlling transcriptional dynamics of downstream genes.

EvolClustDB: Exploring Eukaryotic Gene Clusters with Evolutionarily Conserved Genomic Neighbourhoods

Conservation of gene neighbourhood over evolutionary distances is generally indicative of shared regulation or functional association among genes. This concept has been broadly exploited in prokaryotes but its use on eukaryotic genomes has been limited to specific functional classes, such as biosynthetic gene clusters. We here used an evolutionary-based gene cluster discovery algorithm (EvolClust) to pre-compute evolutionarily conserved gene neighbourhoods, which can be searched, browsed and downloaded in EvolClustDB. We inferred ∼35,000 cluster families in 882 different species in genome comparisons of five taxonomically broad clades: Fungi, Plants, Metazoans, Insects and Protists. EvolClustDB allows browsing through the cluster families, as well as searching by protein, species, identifier or sequence. Visualization allows inspecting gene order per species in a phylogenetic context, so that relevant evolutionary events such as gain, loss or transfer, can be inferred. EvolClustDB is freely available, without registration, at http://evolclustdb.org/.

Genetic and epigenetic control of the plant metabolome

Plant metabolites are mainly produced through chemical reactions catalysed by enzymes encoded in the genome. Mutations in enzyme-encoding or transcription factor-encoding genes can alter the metabolome by changing the enzyme's catalytic activity or abundance, respectively. Insertion of transposable elements into non-coding regions has also been reported to affect transcription and ultimately metabolite content. In addition to genetic mutations, transgenerational epigenetic variations have also been found to affect metabolic content by controlling the transcription of metabolism-related genes. However, the majority of cases reported so far, in which epigenetic mechanisms are associated with metabolism, are non-transgenerational, and are triggered by developmental signals or environmental stress. Although, accumulating research has provided evidence of strong genetic control of the metabolome, epigenetic control has been largely untouched. Here, we provide a review of the genetic and epigenetic control of metabolism with a focus on epigenetics. We discuss both transgenerational and non-transgenerational epigenetic marks regulating metabolism as well as prospects of the field of metabolic control where intricate interactions between genetics and epigenetics are involved.

Uncovering a miltiradiene biosynthetic gene cluster in the Lamiaceae reveals a dynamic evolutionary trajectory

The spatial organization of genes within plant genomes can drive evolution of specialized metabolic pathways. Terpenoids are important specialized metabolites in plants with diverse adaptive functions that enable environmental interactions. Here, we report the genome assemblies of Prunella vulgaris, Plectranthus barbatus, and Leonotis leonurus. We investigate the origin and subsequent evolution of a diterpenoid biosynthetic gene cluster (BGC) together with other seven species within the Lamiaceae (mint) family. Based on core genes found in the BGCs of all species examined across the Lamiaceae, we predict a simplified version of this cluster evolved in an early Lamiaceae ancestor. The current composition of the extant BGCs highlights the dynamic nature of its evolution. We elucidate the terpene backbones generated by the Callicarpa americana BGC enzymes, including miltiradiene and the terpene (+)-kaurene, and show oxidization activities of BGC cytochrome P450s. Our work reveals the fluid nature of BGC assembly and the importance of genome structure in contributing to the origin of metabolites.

The first embryo, the origin of cancer and animal phylogeny. I. A presentation of the neoplastic process and its connection with cell fusion and germline formation

The decisive role of Embryology in understanding the evolution of animal forms is founded and deeply rooted in the history of science. It is recognized that the emergence of multicellularity would not have been possible without the formation of the first embryo. We speculate that biophysical phenomena and the surrounding environment of the Ediacaran ocean were instrumental in co-opting a neoplastic functional module (NFM) within the nucleus of the first zygote. Thus, the neoplastic process, understood here as a biological phenomenon with profound embryologic implications, served as the evolutionary engine that favored the formation of the first embryo and cancerous diseases and allowed to coherently create and recreate body shapes in different animal groups during evolution. In this article, we provide a deep reflection on the Physics of the first embryogenesis and its contribution to the exaptation of additional NFM components, such as the extracellular matrix. Knowledge of NFM components, structure, dynamics, and origin advances our understanding of the numerous possibilities and different innovations that embryos have undergone to create animal forms via Neoplasia during evolutionary radiation. The developmental pathways of Neoplasia have their origins in ctenophores and were consolidated in mammals and other apical groups.

A novel sugar beet cyst nematode effector 2D01 targets the Arabidopsis HAESA receptor-like kinase

Plant-parasitic cyst nematodes use a stylet to deliver effector proteins produced in oesophageal gland cells into root cells to cause disease in plants. These effectors are deployed to modulate plant defence responses and developmental programmes for the formation of a specialized feeding site called a syncytium. The Hg2D01 effector gene, coding for a novel 185-amino-acid secreted protein, was previously shown to be up-regulated in the dorsal gland of parasitic juveniles of the soybean cyst nematode Heterodera glycines, but its function has remained unknown. Genome analyses revealed that Hg2D01 belongs to a highly diversified effector gene family in the genomes of H. glycines and the sugar beet cyst nematode Heterodera schachtii. For functional studies using the model Arabidopsis thaliana-H. schachtii pathosystem, we cloned the orthologous Hs2D01 sequence from H. schachtii. We demonstrate that Hs2D01 is a cytoplasmic effector that interacts with the intracellular kinase domain of HAESA (HAE), a cell surface-associated leucine-rich repeat (LRR) receptor-like kinase (RLK) involved in signalling the activation of cell wall-remodelling enzymes important for cell separation during abscission and lateral root emergence. Furthermore, we show that AtHAE is expressed in the syncytium and, therefore, could serve as a viable host target for Hs2D01. Infective juveniles effectively penetrated the roots of HAE and HAESA-LIKE2 (HSL2) double mutant plants; however, fewer nematodes developed on the roots, consistent with a role for this receptor family in nematode infection. Taken together, our results suggest that the Hs2D01-AtHAE interaction may play an important role in sugar beet cyst nematode parasitism.

A widespread inversion polymorphism conserved among Saccharomyces species is caused by recurrent homogenization of a sporulation gene family

Saccharomyces genomes are highly collinear and show relatively little structural variation, both within and between species of this yeast genus. We investigated the only common inversion polymorphism known in S. cerevisiae, which affects a 24-kb 'flip/flop' region containing 15 genes near the centromere of chromosome XIV. The region exists in two orientations, called reference (REF) and inverted (INV). Meiotic recombination in this region is suppressed in crosses between REF and INV orientation strains such as the BY x RM cross. We find that the inversion polymorphism is at least 17 million years old because it is conserved across the genus Saccharomyces. However, the REF and INV isomers are not ancient alleles but are continually being re-created by re-inversion of the region within each species. Inversion occurs due to continual homogenization of two almost identical 4-kb sequences that form an inverted repeat (IR) at the ends of the flip/flop region. The IR consists of two pairs of genes that are specifically and strongly expressed during the late stages of sporulation. We show that one of these gene pairs, YNL018C/YNL034W, codes for a protein that is essential for spore formation. YNL018C and YNL034W are the founder members of a gene family, Centroid, whose members in other Saccharomycetaceae species evolve fast, duplicate frequently, and are preferentially located close to centromeres. We tested the hypothesis that Centroid genes are a meiotic drive system, but found no support for this idea.

An evolutionarily conserved coronin-dependent pathway defines cell population size

Maintenance of cell population size is fundamental to the proper functioning of multicellular organisms. Here, we describe a cell-intrinsic cell density–sensing pathway that enabled T cells to reach and maintain an appropriate population size. This pathway operated “kin-to-kin” or between identical or similar T cell populations occupying a niche within a tissue or organ, such as the lymph nodes, spleen, and blood. We showed that this pathway depended on the cell density–dependent abundance of the evolutionarily conserved protein coronin 1, which coordinated prosurvival signaling with the inhibition of cell death until the cell population reached threshold densities. At or above threshold densities, coronin 1 expression peaked and remained stable, thereby resulting in the initiation of apoptosis through kin-to-kin intercellular signaling to return the cell population to the appropriate cell density. This cell population size-controlling pathway was conserved from amoeba to humans, thus providing evidence for the existence of a coronin-regulated, evolutionarily conserved mechanism by which cells are informed of and coordinate their relative population size.

Co-depletion of NIPBL and WAPL balance cohesin activity to correct gene misexpression

The relationship between cohesin-mediated chromatin looping and gene expression remains unclear. NIPBL and WAPL are two opposing regulators of cohesin activity; depletion of either is associated with changes in both chromatin folding and transcription across a wide range of cell types. However, a direct comparison of their individual and combined effects on gene expression in the same cell type is lacking. We find that NIPBL or WAPL depletion in human HCT116 cells each alter the expression of ~2,000 genes, with only ~30% of the genes shared between the conditions. We find that clusters of differentially expressed genes within the same topologically associated domain (TAD) show coordinated misexpression, suggesting some genomic domains are especially sensitive to both more or less cohesin. Finally, co-depletion of NIPBL and WAPL restores the majority of gene misexpression as compared to either knockdown alone. A similar set of NIPBL-sensitive genes are rescued following CTCF co-depletion. Together, this indicates that altered transcription due to reduced cohesin activity can be functionally offset by removal of either its negative regulator (WAPL) or the physical barriers (CTCF) that restrict loop-extrusion events.

Co-depletion of NIPBL and WAPL balance cohesin activity to correct gene misexpression

The relationship between cohesin-mediated chromatin looping and gene expression remains unclear. NIPBL and WAPL are two opposing regulators of cohesin activity; depletion of either is associated with changes in both chromatin folding and transcription across a wide range of cell types. However, a direct comparison of their individual and combined effects on gene expression in the same cell type is lacking. We find that NIPBL or WAPL depletion in human HCT116 cells each alter the expression of ~2,000 genes, with only ~30% of the genes shared between the conditions. We find that clusters of differentially expressed genes within the same topologically associated domain (TAD) show coordinated misexpression, suggesting some genomic domains are especially sensitive to both more or less cohesin. Finally, co-depletion of NIPBL and WAPL restores the majority of gene misexpression as compared to either knockdown alone. A similar set of NIPBL-sensitive genes are rescued following CTCF co-depletion. Together, this indicates that altered transcription due to reduced cohesin activity can be functionally offset by removal of either its negative regulator (WAPL) or the physical barriers (CTCF) that restrict loop-extrusion events.

Core circadian clock and light signaling genes brought into genetic linkage across the green lineage

The circadian clock is conserved at both the level of transcriptional networks as well as core genes in plants, ensuring that biological processes are phased to the correct time of day. In the model plant Arabidopsis (Arabidopsis thaliana), the core circadian SHAQKYF-type-MYB (sMYB) genes CIRCADIAN CLOCK ASSOCIATED 1 (CCA1) and REVEILLE (RVE4) show genetic linkage with PSEUDO-RESPONSE REGULATOR 9 (PRR9) and PRR7, respectively. Leveraging chromosome-resolved plant genomes and syntenic ortholog analysis enabled tracing this genetic linkage back to Amborella trichopoda, a sister lineage to the angiosperm, and identifying an additional evolutionarily conserved genetic linkage in light signaling genes. The LHY/CCA1-PRR5/9, RVE4/8-PRR3/7, and PIF3-PHYA genetic linkages emerged in the bryophyte lineage and progressively moved within several genes of each other across an array of angiosperm families representing distinct whole-genome duplication and fractionation events. Soybean (Glycine max) maintained all but two genetic linkages, and expression analysis revealed the PIF3-PHYA linkage overlapping with the E4 maturity group locus was the only pair to robustly cycle with an evening phase, in contrast to the sMYB-PRR morning and midday phase. While most monocots maintain the genetic linkages, they have been lost in the economically important grasses (Poaceae), such as maize (Zea mays), where the genes have been fractionated to separate chromosomes and presence/absence variation results in the segregation of PRR7 paralogs across heterotic groups. The environmental robustness model is put forward, suggesting that evolutionarily conserved genetic linkages ensure superior microhabitat pollinator synchrony, while wide-hybrids or unlinking the genes, as seen in the grasses, result in heterosis, adaptation, and colonization of new ecological niches.

Shared regulation and functional relevance of local gene co-expression revealed by single cell analysis

Most human genes are co-expressed with a nearby gene. Previous studies have revealed this local gene co-expression to be widespread across chromosomes and across dozens of tissues. Yet, so far these studies used bulk RNA-seq, averaging gene expression measurements across millions of cells, thus being unclear if this co-expression stems from transcription events in single cells. Here, we leverage single cell datasets in >85 individuals to identify gene co-expression across cells, unbiased by cell-type heterogeneity and benefiting from the co-occurrence of transcription events in single cells. We discover >3800 co-expressed gene pairs in two human cell types, induced pluripotent stem cells (iPSCs) and lymphoblastoid cell lines (LCLs) and (i) compare single cell to bulk RNA-seq in identifying local gene co-expression, (ii) show that many co-expressed genes – but not the majority – are composed of functionally related genes and (iii) using proteomics data, provide evidence that their co-expression is maintained up to the protein level. Finally, using single cell RNA-sequencing (scRNA-seq) and single cell ATAC-sequencing (scATAC-seq) data for the same single cells, we identify gene-enhancer associations and reveal that >95% of co-expressed gene pairs share regulatory elements. These results elucidate the potential reasons for co-expression in single cell gene regulatory networks and warrant a deeper study of shared regulatory elements, in view of explaining disease comorbidity due to affecting several genes. Our in-depth view of local gene co-expression and regulatory element co-activity advances our understanding of the shared regulatory architecture between genes.

Using single-cell data from cell lines, the co-expression of genes and co-activity of regulatory elements is analyzed, providing insight into shared architecture and regulation between genes.

Genomic insights into the evolution of plant chemical defense

Plant trait evolution can be impacted by common mechanisms of genome evolution, including whole-genome and small-scale duplication, rearrangement, and selective pressures. With the increasing accessibility of genome sequencing for non-model species, comparative studies of trait evolution among closely related or divergent lineages have supported investigations into plant chemical defense. Plant defensive compounds include major chemical classes, such as terpenoids, alkaloids, and phenolics, and are used in primary and secondary plant functions. These include the promotion of plant health, facilitation of pollination, defense against pathogens, and responses to a rapidly changing climate. We discuss mechanisms of genome evolution and use examples from recent studies to impress a stronger understanding of the link between genotype and phenotype as it relates to the evolution of plant chemical defense. We conclude with considerations for how to leverage genomics, transcriptomics, metabolomics, and functional assays for studying the emergence and evolution of chemical defense systems.

Gene function prediction in five model eukaryotes exclusively based on gene relative location through machine learning

The function of most genes is unknown. The best results in automated function prediction are obtained with machine learning-based methods that combine multiple data sources, typically sequence derived features, protein structure and interaction data. Even though there is ample evidence showing that a gene's function is not independent of its location, the few available examples of gene function prediction based on gene location rely on sequence identity between genes of different organisms and are thus subjected to the limitations of the relationship between sequence and function. Here we predict thousands of gene functions in five model eukaryotes (Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus and Homo sapiens) using machine learning models exclusively trained with features derived from the location of genes in the genomes to which they belong. Our aim was not to obtain the best performing method to automated function prediction but to explore the extent to which a gene's location can predict its function in eukaryotes. We found that our models outperform BLAST when predicting terms from Biological Process and Cellular Component Ontologies, showing that, at least in some cases, gene location alone can be more useful than sequence to infer gene function.

Pan-Cancer Analysis Reveals the Prognostic Potential of the THAP9/THAP9-AS1 Sense-Antisense Gene Pair in Human Cancers

Human THAP9, which encodes a domesticated transposase of unknown function, and lncRNA THAP9-AS1 (THAP9-antisense1) are arranged head-to-head on opposite DNA strands, forming a sense and antisense gene pair. We predict that there is a bidirectional promoter that potentially regulates the expression of THAP9 and THAP9-AS1. Although both THAP9 and THAP9-AS1 are reported to be involved in various cancers, their correlative roles on each other's expression has not been explored. We analyzed the expression levels, prognosis, and predicted biological functions of the two genes across different cancer datasets (TCGA, GTEx). We observed that although the expression levels of the two genes, THAP9 and THAP9-AS1, varied in different tumors, the expression of the gene pair was strongly correlated with patient prognosis; higher expression of the gene pair was usually linked to poor overall and disease-free survival. Thus, THAP9 and THAP9-AS1 may serve as potential clinical biomarkers of tumor prognosis. Further, we performed a gene co-expression analysis (using WGCNA) followed by a differential gene correlation analysis (DGCA) across 22 cancers to identify genes that share the expression pattern of THAP9 and THAP9-AS1. Interestingly, in both normal and cancer samples, THAP9 and THAP9-AS1 often co-express; moreover, their expression is positively correlated in each cancer type, suggesting the coordinated regulation of this H2H gene pair.

Neighbours matter: Effects of genomic organization on gene expression plasticity in response to environmental stresses during biological invasions

Gene expression regulation has been widely recognized as an important molecular mechanism underlying phenotypic plasticity in environmental adaptation. However, it remains largely unexplored on the effects of genomic organization on gene expression plasticity under environmental stresses during biological invasions. Here, we use an invasive model ascidian, Ciona robusta, to investigate how genomic organization affects gene expression in response to salinity stresses during range expansions. Our study showed that neighboring genes were co-expressed and approximately 30% of stress responsive genes were physically clustered on chromosomes. Such coordinated expression was substantially affected by the physical distance and orientation of genes. Interestingly, the overall expression correlation of neighboring genes was significantly decreased under high salinity stresses, illustrating that the co-expression regulation could be disrupted by salinity challenges. Furthermore, the clustering of genes was associated with their function constraints and expression patterns - operon genes enriched in gene expression machinery had the highest transcriptional activity and expression stability. Notably, our analyses showed that the tail-to-tail genes, mainly involved in biological functions related to phosphorylation, homeostatic process, and ion transport, exhibited higher intrinsic expression variability and greater response to salinity challenges. Altogether, the results obtained here provide new insights into the effects of gene organization on gene expression plasticity under environmental challenges, hence improving our knowledge on mechanisms of rapid environmental adaptation during biological invasions.

An orthologous gene coevolution network provides insight into eukaryotic cellular and genomic structure and function

The evolutionary rates of functionally related genes often covary. We present a gene coevolution network inferred from examining nearly 3 million orthologous gene pairs from 332 budding yeast species spanning ~400 million years of evolution. Network modules provide insight into cellular and genomic structure and function. Examination of the phenotypic impact of network perturbation using deletion mutant data from the baker's yeast Saccharomyces cerevisiae, which were obtained from previously published studies, suggests that fitness in diverse environments is affected by orthologous gene neighborhood and connectivity. Mapping the network onto the chromosomes of S. cerevisiae and Candida albicans revealed that coevolving orthologous genes are not physically clustered in either species; rather, they are often located on different chromosomes or far apart on the same chromosome. The coevolution network captures the hierarchy of cellular structure and function, provides a roadmap for genotype-to-phenotype discovery, and portrays the genome as a linked ensemble of genes.

Imbalanced segregation of recombinant haplotypes in hybrid populations reveals inter- and intrachromosomal Dobzhansky-Muller incompatibilities

Dobzhansky-Muller incompatibilities (DMIs) are a major component of reproductive isolation between species. DMIs imply negative epistasis and are exposed when two diverged populations hybridize. Mapping the locations of DMIs has largely relied on classical genetic mapping. Approaches to date are hampered by low power and the challenge of identifying DMI loci on the same chromosome, because strong initial linkage of parental haplotypes weakens statistical tests. Here, we propose new statistics to infer negative epistasis from haplotype frequencies in hybrid populations. When two divergent populations hybridize, the variance in heterozygosity at two loci decreases faster with time at DMI loci than at random pairs of loci. When two populations hybridize at near-even admixture proportions, the deviation of the observed variance from its expectation becomes negative for the DMI pair. This negative deviation enables us to detect intermediate to strong negative epistasis both within and between chromosomes. In practice, the detection window in hybrid populations depends on the demographic scenario, the recombination rate, and the strength of epistasis. When the initial proportion of the two parental populations is uneven, only strong DMIs can be detected with our method unless migration prevents parental haplotypes from being lost. We use the new statistics to infer candidate DMIs from three hybrid populations of swordtail fish. We identify numerous new DMI candidates, some of which are inferred to interact with several loci within and between chromosomes. Moreover, we discuss our results in the context of an expected enrichment in intrachromosomal over interchromosomal DMIs.

Making sense of the linear genome, gene function and TADs

BACKGROUND

Topologically associating domains (TADs) are thought to act as functional units in the genome. TADs co-localise genes and their regulatory elements as well as forming the unit of genome switching between active and inactive compartments. This has led to the speculation that genes which are required for similar processes may fall within the same TADs, allowing them to share regulatory programs and efficiently switch between chromatin compartments. However, evidence to link genes within TADs to the same regulatory program is limited.

RESULTS

We investigated the functional similarity of genes which fall within the same TAD. To do this we developed a TAD randomisation algorithm to generate sets of "random TADs" to act as null distributions. We found that while pairs of paralogous genes are enriched in TADs overall, they are largely depleted in TADs with CCCTC-binding factor (CTCF) ChIP-seq peaks at both boundaries. By assessing gene constraint as a proxy for functional importance we found that genes which singly occupy a TAD have greater functional importance than genes which share a TAD, and these genes are enriched for developmental processes. We found little evidence that pairs of genes in CTCF bound TADs are more likely to be co-expressed or share functional annotations than can be explained by their linear proximity alone.

CONCLUSIONS

These results suggest that algorithmically defined TADs consist of two functionally different groups, those which are bound by CTCF and those which are not. We detected no association between genes sharing the same CTCF TADs and increased co-expression or functional similarity, other than that explained by linear genome proximity. We do, however, find that functionally important genes are more likely to fall within a TAD on their own suggesting that TADs play an important role in the insulation of these genes.

A CTCF-Binding Element and Histone Deacetylation Cooperatively Maintain Chromatin Loops, Linking to Long-Range Gene Regulation in Cancer Genomes

Background

Genes spanning long chromosomal domains are coordinately regulated in human genome, which contribute to global gene dysregulation and carcinogenesis in cancer. It has been noticed that epigenetic modification and chromatin architecture may participate in the regulation process. However, the regulation patterns and functional elements of long-range gene regulation are unclear.

Methods

Based on the clinical transcriptome data from different tumor sets, a novel expressional correlation analysis pipeline was performed to classify the co-regulated regions and subsets of intercorrelated regions. The GLAM2 program was used to predict conserved DNA elements that enriched in regions. Two conserved elements were selected to delete in Ishikawa and HeLa cells by CRISPR-Cas9. SAHA treatment and HDAC knockdown were used to change the histone acetylation status. Using qPCR, MTT, and scratch healing assay, we evaluate the effect on gene expression and cancer cell phenotype. By DNA pull-down and ChIP, the element-binding proteins were testified. 3C and 3D-FISH were performed to depict the alteration in chromatin architecture.

Results

In multiple cancer genomes, we classified subsets of coordinately regulated regions (sub-CRRs) that possibly shared the same regulatory mechanisms and exhibited similar expression patterns. A new conserved DNA element (CRE30) was enriched in sub-CRRs and associated with cancer patient survival. CRE30 could restrict gene regulation in sub-CRRs and affect cancer cell phenotypes. DNA pull-down showed that multiple proteins including CTCF were recruited on the CRE30 locus, and ChIP assay confirmed the CTCF-binding signals. Subsequent results uncovered that as an essential element, CRE30 maintained chromatin loops and mediated a compact chromatin architecture. Moreover, we found that blocking global histone deacetylation induced chromatin loop disruption and CTCF dropping in the region containing CRE30, linked to promoted gene regulation. Additionally, similar effects were observed with CRE30 deletion in another locus of chromosome 8.

Conclusions

Our research clarified a new functional element that recruits CTCF and collaborates with histone deacetylation to maintain high-order chromatin organizations, linking to long-range gene regulation in cancer genomes. The findings highlight a close relationship among conserved DNA element, epigenetic modification, and chromatin architecture in long-range gene regulation process.

Repurposing of the enhancer-promoter communication underlies the compensation of Mesp2 by Mesp1

Organisms are inherently equipped with buffering systems against genetic perturbations. Genetic compensation, the compensatory response by upregulating another gene or genes, is one such buffering mechanism. Recently, a well-conserved compensatory mechanism was proposed: transcriptional adaptation of homologs under the nonsense-mediated mRNA decay pathways. However, this model cannot explain the onset of all compensatory events. We report a novel genetic compensation mechanism operating over the Mesp gene locus. Mesp1 and Mesp2 are paralogs located adjacently in the genome. Mesp2 loss is partially rescued by Mesp1 upregulation in the presomitic mesoderm (PSM). Using a cultured PSM induction system, we reproduced the compensatory response in vitro and found that the Mesp2-enhancer is required to promote Mesp1. We revealed that the Mesp2-enhancer directly interacts with the Mesp1 promoter, thereby upregulating Mesp1 expression upon the loss of Mesp2. Of note, this interaction is established by genomic arrangement upon PSM development independently of Mesp2 disruption. We propose that the repurposing of this established enhancer-promoter communication is the mechanism underlying this compensatory response for the upregulation of the adjacent gene.

Genetic compensation, the compensatory response by upregulating another gene or genes, is one of the inherent mechanisms against gene disruption to confer cellular fitness. However, the regulatory mechanisms are largely unknown. Nonsense-mediated mutant mRNA degradation was recently proposed as a conserved mechanism across species to upregulate homologous genes to compensate for a disrupted gene, but this cannot explain compensation events with no mutant mRNA. This study investigated the compensation mechanism operating over adjacent paralogs, Mesp1 and Mesp2, in the genome. Mesp genes encode essential transcription factors in the presomitic mesoderm for development. In general, an enhancer is considered to activate a target gene when it physically interacts with the target. The communication of the Mesp2-enhancer with the Mesp1 promoter is established upon differentiation of the presomitic mesoderm, but this communication activates Mesp1 only when Mesp2 is disrupted, leading to compensation. We revealed a novel compensation mechanism depending on the repurposing of this enhancer-promoter communication by gene disruption. Our study also provides new insight into transcriptional regulation by providing the concept that an enhancer changes its target even among its physically interacting genes in a context-dependent manner.

Three chromosome-scale Papaver genomes reveal punctuated patchwork evolution of the morphinan and noscapine biosynthesis pathway

For millions of years, plants evolve plenty of structurally diverse secondary metabolites (SM) to support their sessile lifestyles through continuous biochemical pathway innovation. While new genes commonly drive the evolution of plant SM pathway, how a full biosynthetic pathway evolves remains poorly understood. The evolution of pathway involves recruiting new genes along the reaction cascade forwardly, backwardly, or in a patchwork manner. With three chromosome-scale Papaver genome assemblies, we here reveal whole-genome duplications (WGDs) apparently accelerate chromosomal rearrangements with a nonrandom distribution towards SM optimization. A burst of structural variants involving fusions, translocations and duplications within 7.7 million years have assembled nine genes into the benzylisoquinoline alkaloids gene cluster, following a punctuated patchwork model. Biosynthetic gene copies and their total expression matter to morphinan production. Our results demonstrate how new genes have been recruited from a WGD-induced repertoire of unregulated enzymes with promiscuous reactivities to innovate efficient metabolic pathways with spatiotemporal constraint.