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The YABBY gene family is one of the plant transcription factors present in all seed plants. The family members were extensively studied in various plants and shown to play important roles in plant growth and development, such as the polarity establishment in lateral organs, the formation and development of leaves and flowers, and the response to internal plant hormone and external environmental stress signals. In this study, a total of 364 YABBY genes were identified from 37 Brassicaceae genomes, of which 15 were incomplete due to sequence gaps, and nine were imperfect (missing C2C2 zinc-finger or YABBY domain) due to sequence mutations. Phylogenetic analyses resolved these YABBY genes into six compact clades except for a YAB3-like gene identified in Aethionema arabicum. Seventeen Brassicaceae species each contained a complete set of six basic YABBY genes (i.e., 1 FIL, 1 YAB2, 1 YAB3, 1 YAB5, 1 INO and 1 CRC), while 20 others each contained a variable number of YABBY genes (5–25) caused mainly by whole-genome duplication/triplication followed by gene losses, and occasionally by tandem duplications. The fate of duplicate YABBY genes changed considerably according to plant species, as well as to YABBY gene type. These YABBY genes were shown to be syntenically conserved across most of the Brassicaceae species, but their functions might be considerably diverged between species, as well as between paralogous copies, as demonstrated by the promoter and expression analysis of YABBY genes in two Brassica species (B. rapa and B. oleracea). Our study provides valuable insights for understanding the evolutionary story of YABBY genes in Brassicaceae and for further functional characterization of each YABBY gene across the Brassicaceae species.

Homocysteine methyltransferase (HMT) converts homocysteine to methionine using S-methylmethionine (SMM) or S-adenosylmethionine (SAM) as methyl donors in organisms, playing an important role in supplying methionine for the growth and the development of plants. To better understand the functions of the HMT genes in plants, we conducted a wide evolution and expression analysis of these genes. Reconstruction of the phylogenetic relationship showed that the HMT gene family was divided into Class 1 and Class 2. In Class 1, HMTs were only found in seed plants, while Class 2 presented in all land plants, which hinted that the HMT genes might have diverged in seed plants. The analysis of gene structures and selection pressures showed that they were relatively conserved during evolution. However, type I functional divergence had been detected in the HMTs. Furthermore, the expression profiles of HMTs showed their distinct expression patterns in different tissues, in which some HMTs were widely expressed in various organs, whereas the others were highly expressed in some specific organs, such as seeds or leaves. Therefore, according to our results in the evolution, functional divergence, and expression, the HMT genes might have diverged during evolution. Further analysis in the expression patterns of AthHMTs with their methyl donors suggested that the diverged HMTs might be related to supply methionine for the development of plant seeds.

Significance Genes with different expression between males and females (sex-biased genes) show rapid rates of sequence and expression divergence in a range of taxa. These characteristics have led many to assume that sex-biased genes are the product of sexual selection and sexual conflict, but this assumption remains to be rigorously tested. Using a phylogenetically controlled analysis of birds that exhibit diverse levels of sexual selection, we show a rapid turnover in sex-biased gene expression primarily through evolution of male expression levels and that the degree of sexual selection predicts the proportion of male-biased genes but does not account for rates of coding sequence evolution. We also discuss the impact of allometry on gene expression studies, an issue rarely discussed in the literature. The profound and pervasive differences in gene expression observed between males and females, and the unique evolutionary properties of these genes in many species, have led to the widespread assumption that they are the product of sexual selection and sexual conflict. However, we still lack a clear understanding of the connection between sexual selection and transcriptional dimorphism, often termed sex-biased gene expression. Moreover, the relative contribution of sexual selection vs. drift in shaping broad patterns of expression, divergence, and polymorphism remains unknown. To assess the role of sexual selection in shaping these patterns, we assembled transcriptomes from an avian clade representing the full range of sexual dimorphism and sexual selection. We use these species to test the links between sexual selection and sex-biased gene expression evolution in a comparative framework. Through ancestral reconstruction of sex bias, we demonstrate a rapid turnover of sex bias across this clade driven by sexual selection and show it to be primarily the result of expression changes in males. We use phylogenetically controlled comparative methods to demonstrate that phenotypic measures of sexual selection predict the proportion of male-biased but not female-biased gene expression. Although male-biased genes show elevated rates of coding sequence evolution, consistent with previous reports in a range of taxa, there is no association between sexual selection and rates of coding sequence evolution, suggesting that expression changes may be more important than coding sequence in sexual selection. Taken together, our results highlight the power of sexual selection to act on gene expression differences and shape genome evolution.

Background Gene expression differences between species are driven by both cis and trans effects. Whereas cis effects are caused by genetic variants located on the same DNA molecule as the target gene, trans effects are due to genetic variants that affect diffusible elements. Previous studies have mostly assessed the impact of cis and trans effects at the gene level. However, how cis and trans effects differentially impact regulatory elements such as enhancers and promoters remains poorly understood. Here, we use massively parallel reporter assays to directly measure the transcriptional outputs of thousands of individual regulatory elements in embryonic stem cells and measure cis and trans effects between human and mouse. Results Our approach reveals that cis effects are widespread across transcribed regulatory elements, and the strongest cis effects are associated with the disruption of motifs recognized by strong transcriptional activators. Conversely, we find that trans effects are rare but stronger in enhancers than promoters and are associated with a subset of transcription factors that are differentially expressed between human and mouse. While we find that cis - trans compensation is common within promoters, we do not see evidence of widespread cis - trans compensation at enhancers. Cis - trans compensation is inversely correlated with enhancer redundancy, suggesting that such compensation may often occur across multiple enhancers. Conclusions Our results highlight differences in the mode of evolution between promoters and enhancers in complex mammalian genomes and indicate that studying the evolution of individual regulatory elements is pivotal to understand the tempo and mode of gene expression evolution.

Differences between males and females are usually more subtle in dioecious plants than animals, but strong sexual dimorphism has evolved convergently in the South African Cape plant genus Leucadendron . Such sexual dimorphism in leaf size is expected largely to be due to differential gene expression between the sexes. We compared patterns of gene expression in leaves among 10 Leucadendron species across the genus. Surprisingly, we found no positive association between sexual dimorphism in morphology and the number or the percentage of sex-biased genes (SBGs). Sex bias in most SBGs evolved recently and was species specific. We compared rates of evolutionary change in expression for genes that were sex biased in one species but unbiased in others and found that SBGs evolved faster in expression than unbiased genes. This greater rate of expression evolution of SBGs, also documented in animals, might suggest the possible role of sexual selection in the evolution of gene expression. However, our comparative analysis clearly indicates that the more rapid rate of expression evolution of SBGs predated the origin of bias, and shifts towards bias were depleted in signatures of adaptation. Our results are thus more consistent with the view that sex bias is simply freer to evolve in genes less subject to constraints in expression level.

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking.

The biological activities of organisms are closely linked to seasonality. Phenology, the temporal orchestration of biological activities, is governed by gene expression, yet the evolutionary dynamics underlying seasonal gene expression remain unclear. To investigate these dynamics, we compared genome-wide expression dynamics (molecular phenology) in four dominant evergreen Fagaceae species in Asia ( Quercus glauca , Q. acuta , Lithocarpus edulis , and L. glaber ), using leaf and bud tissues over two seasonal cycles. We assembled high-quality reference genomes, identifying 11749 single-copy orthologous genes. Seasonal transcriptomic profiling of these orthologous genes revealed highly conserved gene expression across species in winter when temperatures fall below ~10 °C. Rhythmic gene expression with significant periodic oscillations was more prevalent in buds (51.9%) than in leaves (40.6%), with most rhythmic genes (78.4–92.0%) exhibiting annual periodicity, while a smaller fraction (1.2–11.9%) followed half-annual cycles. The seasonal peaks of rhythmic genes were highly synchronized across species in winter but diverged during the growing season, reflecting species-specific timing of leaf flushing and flowering. These findings suggest that the four species share a common molecular calendar in winter, which constrains the evolution of gene expression under seasonal environments.

Whole tissue RNASeq is the standard approach for studying gene expression divergence in evolutionary biology and provides a snapshot of the comprehensive transcriptome for a given tissue. However, whole tissues consist of diverse cell types differing in expression profiles, and the cellular composition of these tissues can evolve across species. Here, we investigate the effects of different cellular composition on whole tissue expression profiles. We compared gene expression from whole testes and enriched spermatogenesis populations in two species of house mice, Mus musculus musculus and M. m. domesticus, and their sterile and fertile F1 hybrids, which differ in both cellular composition and regulatory dynamics. We found that cellular composition differences skewed expression profiles and differential gene expression in whole testes samples. Importantly, both approaches were able to detect large-scale patterns such as disrupted X chromosome expression, although whole testes sampling resulted in decreased power to detect differentially expressed genes. We encourage researchers to account for histology in RNASeq and consider methods that reduce sample complexity whenever feasible. Ultimately, we show that differences in cellular composition between tissues can modify expression profiles, potentially altering inferred gene ontological processes, insights into gene network evolution, and processes governing gene expression evolution.

Key innovations provide ecological opportunity by enabling access to new resources, colonization of new environments, and are associated with adaptive radiation. The most well-known pattern associated with adaptive radiation is an early burst of phenotypic diversification. Venoms facilitate prey capture and are widely believed to be key innovations leading to adaptive radiation. However, few studies have estimated their evolutionary rate dynamics. Here, we test for patterns of adaptive evolution in venom gene expression data from 52 venomous snake species. By identifying shifts in tempo and mode of evolution along with models of phenotypic evolution, we show that snake venom exhibits the macroevolutionary dynamics expected of key innovations. Namely, all toxin families undergo shifts in their rates of evolution, likely in response to changes in adaptive optima. Furthermore, we show that rapid-pulsed evolution modelled as a Lévy process better fits snake venom evolution than conventional early burst or Ornstein–Uhlenbeck models. While our results support the idea of snake venom being a key innovation, the innovation of venom chemistry lacks clear mechanisms that would lead to reproductive isolation and thus adaptive radiation. Therefore, the extent to which venom directly influences the diversification process is still a matter of contention.

Background Evolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation of many enhancers, distal regulatory elements that control spatial and temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high. Results We present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that can predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Next, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss of regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity have a stronger tendency than the general population to have predicted lineage-specific open chromatin. Conclusion The framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements.