Evolutionary Conservation of Expression Profiles Between Human and Mouse Orthologous Genes

SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis

Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-efficient pipeline for single-cell RNA classification. We benchmark SIMS against datasets from different tissues and species. We demonstrate SIMS's efficacy in classifying cells in the brain, achieving high accuracy even with small training sets (<3,500 cells) and across different samples. SIMS accurately predicts neuronal subtypes in the developing brain, shedding light on genetic changes during neuronal differentiation and postmitotic fate refinement. Finally, we apply SIMS to single-cell RNA datasets of cortical organoids to predict cell identities and uncover genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets.

Evolution and genetics of accessory gland transcriptome divergence between Drosophila melanogaster and D. simulans

Studies of allele-specific expression in interspecific hybrids have provided important insights into gene-regulatory divergence and hybrid incompatibilities. Many such investigations in Drosophila have used transcriptome data from complex mixtures of many tissues or from gonads, however, regulatory divergence may vary widely among species, sexes, and tissues. Thus, we lack sufficiently broad sampling to be confident about the general biological principles of regulatory divergence. Here, we seek to fill some of these gaps in the literature by characterizing regulatory evolution and hybrid misexpression in a somatic male sex organ, the accessory gland, in F1 hybrids between Drosophila melanogaster and D. simulans. The accessory gland produces seminal fluid proteins, which play an important role in male and female fertility and may be subject to adaptive divergence due to male-male or male-female interactions. We find that trans differences are relatively more abundant than cis, in contrast to most of the interspecific hybrid literature, though large effect-size trans differences are rare. Seminal fluid protein genes have significantly elevated levels of expression divergence and tend to be regulated through both cis and trans divergence. We find limited misexpression (over- or underexpression relative to both parents) in this organ compared to most other Drosophila studies. As in previous studies, male-biased genes are overrepresented among misexpressed genes and are much more likely to be underexpressed. ATAC-Seq data show that chromatin accessibility is correlated with expression differences among species and hybrid allele-specific expression. This work identifies unique regulatory evolution and hybrid misexpression properties of the accessory gland and suggests the importance of tissue-specific allele-specific expression studies.

Identification of SOCS3 and PTGS2 as new biomarkers for the diagnosis of gout by cross-species comprehensive analysis

Background

Gout is the most common inflammatory arthritis in adults. Gout is an arthritic disease caused by the deposition of monosodium urate crystal (MSU) in the joints, which can lead to acute inflammation and damage adjacent tissue. Hyperuricemia is the main risk factor for MSU crystal deposition and gout. With the increasing burden of gout disease, the identification of potential biomarkers and novel targets for diagnosis is urgently needed.

Methods

For the analysis of this subject paper, we downloaded the human gout data set GSE160170 and the gout mouse model data set GSE190138 from the GEO database. To obtain the differentially expressed genes (DEGs), we intersected the two data sets. Using the cytohubba algorithm, we identified the key genes and enriched them through GO and KEGG. The gene expression trends of three subgroups (normal control group, intermittent gout group and acute gout attack group) were analyzed by Series Test of Cluster (STC) analysis, and the key genes were screened out, and the diagnostic effect was verified by ROC curve. The expression of key genes in dorsal root nerve and spinal cord of gout mice was analyzed. Finally, the clinical samples of normal control group, hyperuricemia group, intermittent gout group and acute gout attack group were collected, and the expression of key genes at protein level was verified by ELISA.

Result

We obtained 59 co-upregulated and 28 co-downregulated genes by comparing the DEGs between gout mouse model data set and human gout data set. 7 hub DEGs(IL1B, IL10, NLRP3, SOCS3, PTGS2) were screened out via Cytohubba algorithm. The results of both GO and KEGG enrichment analyses indicate that 7 hub genes play a significant role in regulating the inflammatory response, cytokine production in immune response, and the TNF signaling pathway. The most representative hub genes SOCS3 and PTGS2 were screened out by Series Test of Cluster, and ROC analysis results showed the AUC values were both up to 1.000. In addition, we found that PTGS2 expression was significantly elevated in the dorsal root ganglia and spinal cord in monosodium urate(MSU)-induced gout mouse model. The ELISA results revealed that the expression of SOCS3 and PTGS2 was notably higher in the acute gout attack and intermittent gout groups compared to the normal control group. This difference was statistically significant, indicating a clear distinction between the groups.

Conclusion

Through cross-species comprehensive analysis and experimental verification, SOCS3 and PTGS2 were proved to be new biomarkers for diagnosing gout and predicting disease progression.

Genic constraint against nonsynonymous variation across the mouse genome

BACKGROUND

Selective constraint, the depletion of variation due to negative selection, provides insights into the functional impact of variants and disease mechanisms. However, its characterization in mice, the most commonly used mammalian model, remains limited. This study aims to quantify mouse gene constraint using a new metric called the nonsynonymous observed expected ratio (NOER) and investigate its relationship with gene function.

RESULTS

NOER was calculated using whole-genome sequencing data from wild mouse populations (Mus musculus sp and Mus spretus). Positive correlations were observed between mouse gene constraint and the number of associated knockout phenotypes, indicating stronger constraint on pleiotropic genes. Furthermore, mouse gene constraint showed a positive correlation with the number of pathogenic variant sites in their human orthologues, supporting the relevance of mouse models in studying human disease variants.

CONCLUSIONS

NOER provides a resource for assessing the fitness consequences of genetic variants in mouse genes and understanding the relationship between gene constraint and function. The study's findings highlight the importance of pleiotropy in selective constraint and support the utility of mouse models in investigating human disease variants. Further research with larger sample sizes can refine constraint estimates in mice and enable more comprehensive comparisons of constraint between mouse and human orthologues.

Clustering pattern and evolution characteristic of microRNAs in grass carp (Ctenopharyngodon idella)

BACKGROUND

A considerable fraction of microRNAs (miRNAs) are highly conserved, and certain miRNAs correspond to genomic clusters. The clustering of miRNAs can be advantageous, possibly by allowing coordinated expression. However, little is known about the evolutionary forces responsible for the loss and acquisition of miRNA and miRNA clusters.

RESULTS

The results demonstrated that several novel miRNAs arose throughout grass carp evolution. Duplication and de novo production were critical strategies for miRNA cluster formation. Duplicates accounted for a smaller fraction of the expansion in the grass carp miRNA than de novo creation. Clustered miRNAs are more conserved and change slower, whereas unique miRNAs usually have high evolution rates and low expression levels. The expression level of miRNA expression in clusters is strongly correlated.

CONCLUSIONS

This study examines the genomic distribution, evolutionary background, and expression regulation of grass carp miRNAs. Our findings provide novel insights into the genesis and development of miRNA clusters in teleost.

Interspecific comparison of gene expression profiles using machine learning

Interspecific gene comparisons are the keystones for many areas of biological research and are especially important for the translation of knowledge from model organisms to economically important species. Currently they are hampered by the low resolution of methods based on sequence analysis and by the complex evolutionary history of eukaryotic genes. This is especially critical for plants, whose genomes are shaped by multiple whole genome duplications and subsequent gene loss. This requires the development of new methods for comparing the functions of genes in different species. Here, we report ISEEML (Interspecific Similarity of Expression Evaluated using Machine Learning)-a novel machine learning-based algorithm for interspecific gene classification. In contrast to previous studies focused on sequence similarity, our algorithm focuses on functional similarity inferred from the comparison of gene expression profiles. We propose novel metrics for expression pattern similarity-expression score (ES)-that is suitable for species with differing morphologies. As a proof of concept, we compare detailed transcriptome maps of Arabidopsis thaliana, the model species, Zea mays (maize) and Fagopyrum esculentum (common buckwheat), which are species that represent distant clades within flowering plants. The classifier resulted in an AUC of 0.91; under the ES threshold of 0.5, the specificity was 94%, and sensitivity was 72%.

The evolution of ovary-biased gene expression in Hawaiian Drosophila

With detailed data on gene expression accessible from an increasingly broad array of species, we can test the extent to which our developmental genetic knowledge from model organisms predicts expression patterns and variation across species. But to know when differences in gene expression across species are significant, we first need to know how much evolutionary variation in gene expression we expect to observe. Here we provide an answer by analyzing RNAseq data across twelve species of Hawaiian Drosophilidae flies, focusing on gene expression differences between the ovary and other tissues. We show that over evolutionary time, there exists a cohort of ovary specific genes that is stable and that largely corresponds to described expression patterns from laboratory model Drosophila species. Our results also provide a demonstration of the prediction that, as phylogenetic distance increases, variation between species overwhelms variation between tissue types. Using ancestral state reconstruction of expression, we describe the distribution of evolutionary changes in tissue-biased expression, and use this to identify gains and losses of ovary-biased expression across these twelve species. We then use this distribution to calculate the evolutionary correlation in expression changes between genes, and demonstrate that genes with known interactions in D. melanogaster are significantly more correlated in their evolution than genes with no or unknown interactions. Finally, we use this correlation matrix to infer new networks of genes that share evolutionary trajectories, and we present these results as a dataset of new testable hypotheses about genetic roles and interactions in the function and evolution of the Drosophila ovary.

Conserved hierarchical gene regulatory networks for drought and cold stress response in Myrica rubra

Stress response in plant is regulated by a large number of genes co-operating in diverse networks that serve multiple adaptive process. To understand how gene regulatory networks (GRNs) modulating abiotic stress responses, we compare the GRNs underlying drought and cold stresses using samples collected at 4 or 6 h intervals within 48 h in Chinese bayberry (Myrica rubra). We detected 7,583 and 8,840 differentially expressed genes (DEGs) under drought and cold stress respectively, which might be responsive to environmental stresses. Drought- and cold-responsive GRNs, which have been built according to the timing of transcription under both abiotic stresses, have a conserved trans-regulator and a common regulatory network. In both GRNs, basic helix-loop-helix family transcription factor (bHLH) serve as central nodes. MrbHLHp10 transcripts exhibited continuous increase in the two abiotic stresses and acts upstream regulator of ASCORBATE PEROXIDASE (APX) gene. To examine the potential biological functions of MrbHLH10, we generated a transgenic Arabidopsis plant that constitutively overexpresses the MrbHLH10 gene. Compared to wild-type (WT) plants, overexpressing transgenic Arabidopsis plants maintained higher APX activity and biomass accumulation under drought and cold stress. Consistently, RNAi plants had elevated susceptibility to both stresses. Taken together, these results suggested that MrbHLH10 mitigates abiotic stresses through the modulation of ROS scavenging.

HGD: an integrated homologous gene database across multiple species

Homology is fundamental to infer genes' evolutionary processes and relationships with shared ancestry. Existing homolog gene resources vary in terms of inferring methods, homologous relationship and identifiers, posing inevitable difficulties for choosing and mapping homology results from one to another. Here, we present HGD (Homologous Gene Database, https://ngdc.cncb.ac.cn/hgd), a comprehensive homologs resource integrating multi-species, multi-resources and multi-omics, as a complement to existing resources providing public and one-stop data service. Currently, HGD houses a total of 112 383 644 homologous pairs for 37 species, including 19 animals, 16 plants and 2 microorganisms. Meanwhile, HGD integrates various annotations from public resources, including 16 909 homologs with traits, 276 670 homologs with variants, 398 573 homologs with expression and 536 852 homologs with gene ontology (GO) annotations. HGD provides a wide range of omics gene function annotations to help users gain a deeper understanding of gene function.

Tissue Specificity of Gene Expression Evolves Across Mammal Species

Tissue specificity of gene expression sheds light on the tissue-selective manifestation of hereditary disease despite the same DNA across all tissues. The evolutionary path of such tissue specificity provides essential information about the tissue-specific function of genes and the validity of disease animal models. With recent improvements of the sequencing technology, more and more large-scale transcriptomics studies have been conducted among different species across multiple tissues. In this study, we exploit existing transcriptomics resources of humans, cynomolgus macaques, rats, mice, and dogs across 13 tissues. We find that although tissue specificity of homologous gene expression is largely well conserved across species, a total of 380 genes shift or are in the process of shifting their tissue specificity. The tissue-specificity-shifting genes are less conserved than those preserving their tissue specificity or housekeeping genes. Interestingly, tissue-specificity-shifting genes tend to be less conserved at the third codon positions, likely due to their relaxed synonymous codon usage bias. Moreover, compared with genes, cassette exons are more likely to shift their tissue specificity of splicing across the five species.

Transcriptional Divergence Underpinning Sexual Development in the Fungal Class Sordariomycetes

Gene expression divergence through evolutionary processes is thought to be important for achieving programmed development in multicellular organisms. To test this premise in filamentous fungi, we investigated transcriptional profiles of 3,942 single-copy orthologous genes (SCOGs) in five related sordariomycete species that have morphologically diverged in the formation of their flask-shaped perithecia. We compared expression of the SCOGs to inferred gene expression levels of the most recent common ancestor of the five species, ranking genes from their largest increases to smallest increases in expression during perithecial development in each of the five species. We found that a large proportion of the genes that exhibited evolved increases in gene expression were important for normal perithecial development in Fusarium graminearum. Many of these genes were previously uncharacterized, encoding hypothetical proteins without any known functional protein domains. Interestingly, the developmental stages during which aberrant knockout phenotypes appeared largely coincided with the elevated expression of the deleted genes. In addition, we identified novel genes that affected normal perithecial development in Magnaporthe oryzae and Neurospora crassa, which were functionally and transcriptionally diverged from the orthologous counterparts in F. graminearum. Furthermore, comparative analysis of developmental transcriptomes and phylostratigraphic analysis suggested that genes encoding hypothetical proteins are generally young and transcriptionally divergent between related species. This study provides tangible evidence of shifts in gene expression that led to acquisition of novel function of orthologous genes in each lineage and demonstrates that several genes with hypothetical function are crucial for shaping multicellular fruiting bodies. IMPORTANCE The fungal class Sordariomycetes includes numerous important plant and animal pathogens. It also provides model systems for studying fungal fruiting body development, as its members develop fruiting bodies with a few well-characterized tissue types on common growth media and have rich genomic resources that enable comparative and functional analyses. To understand transcriptional divergence of key developmental genes between five related sordariomycete fungi, we performed targeted knockouts of genes inferred to have evolved significant upward shifts in expression. We found that many previously uncharacterized genes play indispensable roles at different stages of fruiting body development, which have undergone transcriptional activation in specific lineages. These novel genes are predicted to be phylogenetically young and tend to be involved in lineage- or species-specific function. Transcriptional activation of genes with unknown function seems to be more frequent than ever thought, which may be crucial for rapid adaption to changing environments for successful sexual reproduction.

Integrated view and comparative analysis of baseline protein expression in mouse and rat tissues

The increasingly large amount of proteomics data in the public domain enables, among other applications, the combined analyses of datasets to create comparative protein expression maps covering different organisms and different biological conditions. Here we have reanalysed public proteomics datasets from mouse and rat tissues (14 and 9 datasets, respectively), to assess baseline protein abundance. Overall, the aggregated dataset contained 23 individual datasets, including a total of 211 samples coming from 34 different tissues across 14 organs, comprising 9 mouse and 3 rat strains, respectively. In all cases, we studied the distribution of canonical proteins between the different organs. The number of canonical proteins per dataset ranged from 273 (tendon) and 9,715 (liver) in mouse, and from 101 (tendon) and 6,130 (kidney) in rat. Then, we studied how protein abundances compared across different datasets and organs for both species. As a key point we carried out a comparative analysis of protein expression between mouse, rat and human tissues. We observed a high level of correlation of protein expression among orthologs between all three species in brain, kidney, heart and liver samples, whereas the correlation of protein expression was generally slightly lower between organs within the same species. Protein expression results have been integrated into the resource Expression Atlas for widespread dissemination.

No Expression Divergence despite Transcriptional Interference between Nested Protein-Coding Genes in Mammals

Nested protein-coding genes accumulated throughout metazoan evolution, with early analyses of human and Drosophila microarray data indicating that this phenomenon was simply due to the presence of large introns. However, a recent study employing RNA-seq data uncovered evidence of transcriptional interference driving rapid expression divergence between Drosophila nested genes, illustrating that accurate expression estimation of overlapping genes can enhance detection of their relationships. Hence, here I apply an analogous approach to strand-specific RNA-seq data from human and mouse to revisit the role of transcriptional interference in the evolution of mammalian nested genes. A genomic survey reveals that whereas mammalian nested genes indeed accrued over evolutionary time, they are retained at lower frequencies than in Drosophila. Though several properties of mammalian nested genes align with observations in Drosophila and with expectations under transcriptional interference, contrary to both, their expression divergence is not statistically different from that between unnested genes, and also does not increase after nesting. Together, these results support the hypothesis that lower selection efficiencies limit rates of gene expression evolution in mammals, leading to their reliance on immediate eradication of deleterious nested genes to avoid transcriptional interference.

Avoidance of protein unfolding constrains protein stability in long-term evolution

Every amino acid residue can influence a protein's overall stability, making stability highly susceptible to change throughout evolution. We consider the distribution of protein stabilities evolutionarily permittable under two previously reported protein fitness functions: flux dynamics and misfolding avoidance. We develop an evolutionary dynamics theory and find that it agrees better with an extensive protein stability data set for dihydrofolate reductase orthologs under the misfolding avoidance fitness function rather than the flux dynamics fitness function. Further investigation with ribonuclease H data demonstrates that not any misfolded state is avoided; rather, it is only the unfolded state. At the end, we discuss how our work pertains to the universal protein abundance-evolutionary rate correlation seen across organisms' proteomes. We derive a closed-form expression relating protein abundance to evolutionary rate that captures Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens experimental trends without fitted parameters.

SARS-CoV-2 Receptors and Entry Genes Are Expressed in the Human Olfactory Neuroepithelium and Brain

Reports indicate an association between COVID-19 and anosmia, as well as the presence of SARS-CoV-2 virions in the olfactory bulb. To test whether the olfactory neuroepithelium may represent a target of the virus, we generated RNA-seq libraries from human olfactory neuroepithelia, in which we found substantial expression of the genes coding for the virus receptor angiotensin-converting enzyme-2 (ACE2) and for the virus internalization enhancer TMPRSS2. We analyzed a human olfactory single-cell RNA-seq dataset and determined that sustentacular cells, which maintain the integrity of olfactory sensory neurons, express ACE2 and TMPRSS2. ACE2 protein was highly expressed in a subset of sustentacular cells in human and mouse olfactory tissues. Finally, we found ACE2 transcripts in specific brain cell types, both in mice and humans. Sustentacular cells thus represent a potential entry door for SARS-CoV-2 in a neuronal sensory system that is in direct connection with the brain.

SARS-CoV-2 Receptors and Entry Genes Are Expressed in the Human Olfactory Neuroepithelium and Brain

Reports indicate an association between COVID-19 and anosmia, as well as the presence of SARS-CoV-2 virions in the olfactory bulb. To test whether the olfactory neuroepithelium may represent a target of the virus, we generated RNA-seq libraries from human olfactory neuroepithelia, in which we found substantial expression of the genes coding for the virus receptor angiotensin-converting enzyme-2 (ACE2) and for the virus internalization enhancer TMPRSS2. We analyzed a human olfactory single-cell RNA-seq dataset and determined that sustentacular cells, which maintain the integrity of olfactory sensory neurons, express ACE2 and TMPRSS2. ACE2 protein was highly expressed in a subset of sustentacular cells in human and mouse olfactory tissues. Finally, we found ACE2 transcripts in specific brain cell types, both in mice and humans. Sustentacular cells thus represent a potential entry door for SARS-CoV-2 in a neuronal sensory system that is in direct connection with the brain.

Speciation and the developmental alarm clock

New species arise as the genomes of populations diverge. The developmental 'alarm clock' of speciation sounds off when sufficient divergence in genetic control of development leads hybrid individuals to infertility or inviability, the world awoken to the dawn of new species with intrinsic post-zygotic reproductive isolation. Some developmental stages will be more prone to hybrid dysfunction due to how molecular evolution interacts with the ontogenetic timing of gene expression. Considering the ontogeny of hybrid incompatibilities provides a profitable connection between 'evo-devo' and speciation genetics to better link macroevolutionary pattern, microevolutionary process, and molecular mechanisms. Here, we explore speciation alongside development, emphasizing their mutual dependence on genetic network features, fitness landscapes, and developmental system drift. We assess models for how ontogenetic timing of reproductive isolation can be predictable. Experiments and theory within this synthetic perspective can help identify new rules of speciation as well as rules in the molecular evolution of development.

Evolution and Functional Divergence of the Fructokinase Gene Family in Populus

New kinase has emerged throughout evolution, but how new kinase evolve while maintaining their functions and acquiring new functions remains unclear. Fructokinase (FRK), the gateway kinase to fructose metabolism, plays essential roles in plant development, and stress tolerance. Here, we explored the evolution of FRK gene family in 20 plant species (from green algae to angiosperms) and their functional roles in Populus. We identified 125 putative FRK genes in the 20 plant species with an average of 6 members per species. Phylogenetic analysis separated these 125 genes into 8 clades including 3 conserved clades and 5 specific clades, the 5 of which only exist in green algae or angiosperms. Evolutionary analysis revealed that FRK genes in ancient land plants have the largest number of functional domains with the longest amino acid sequences, and the length of FRK genes became shorter during the transition to vascular plants. This was accompanied by loss, acquisition, and diversification of functional domains. In Populus, segmental duplication appears to be the main mechanism for the expansion of FRK genes. Specially, most FRK genes duplicated in salicoids are regulated by Populus-specific microRNAs. Furthermore, compared with common FRKs, Populus-specific FRKs have showed higher expression specificity and are associated with fewer growth and wood property traits, which suggests that these FRKs may have undergone functional divergence. Our study explores the specific roles of FRKs in the Populus genome and provides new insights for functional investigation of this gene family.

Patterns of gene evolution following duplications and speciations in vertebrates

BACKGROUND

Eukaryotic genes typically form independent evolutionary lineages through either speciation or gene duplication events. Generally, gene copies resulting from speciation events (orthologs) are expected to maintain similarity over time with regard to sequence, structure and function. After a duplication event, however, resulting gene copies (paralogs) may experience a broader set of possible fates, including partial (subfunctionalization) or complete loss of function, as well as gain of new function (neofunctionalization). This assumption, known as the Ortholog Conjecture, is prevalent throughout molecular biology and notably plays an important role in many functional annotation methods. Unfortunately, studies that explicitly compare evolutionary processes between speciation and duplication events are rare and conflicting.

METHODS

To provide an empirical assessment of ortholog/paralog evolution, we estimated ratios of nonsynonymous to synonymous substitutions (ω = dN/dS) for 251,044 lineages in 6,244 gene trees across 77 vertebrate taxa.

RESULTS

Overall, we found ω to be more similar between lineages descended from speciation events (p < 0.001) than lineages descended from duplication events, providing strong support for the Ortholog Conjecture. The asymmetry in ω following duplication events appears to be largely driven by an increase along one of the paralogous lineages, while the other remains similar to the parent. This trend is commonly associated with neofunctionalization, suggesting that gene duplication is a significant mechanism for generating novel gene functions.

Using mouse genetics to understand human skeletal disease

Technological advances have enabled the study of the human genome in incredible detail with relative ease. However, our ability to interpret the functional significance of the millions of genetic variants present within each individual is limited. As a result, the confident assignment of disease-causing variant calls remains a significant challenge. Here we explore how mouse genetics can help address this deficit in functional genomic understanding. Underpinned by marked genetic correspondence, skeletal biology shows inter-species similarities which provide important opportunities to use data from mouse models to direct research into the genetic basis of skeletal pathophysiology. In this article we outline critical resources that may be used to establish genotype/phenotype relationships in skeletal tissue, identify genes with established skeletal effects and define the transcriptome of critical skeletal cell types. Finally, we outline how these mouse resources might be utilized to progress from a list of human sequence variants toward plausible gene candidates that contribute to skeletal disease.

Molecular evolution across developmental time reveals rapid divergence in early embryogenesis

Ontogenetic development hinges on the changes in gene expression in time and space within an organism, suggesting that the demands of ontogenetic growth can impose or reveal predictable pattern in the molecular evolution of genes expressed dynamically across development. Here, we characterize coexpression modules of the Caenorhabditis elegans transcriptome, using a time series of 30 points from early embryo to adult. By capturing the functional form of expression profiles with quantitative metrics, we find fastest evolution in the distinctive set of genes with transcript abundance that declines through development from a peak in young embryos. These genes are highly enriched for oogenic function and transient early zygotic expression, are nonrandomly distributed in the genome, and correspond to a life stage especially prone to inviability in interspecies hybrids. These observations conflict with the "early conservation model" for the evolution of development, although expression-weighted sequence divergence analysis provides some support for the "hourglass model." Genes in coexpression modules that peak toward adulthood also evolve fast, being hyper-enriched for roles in spermatogenesis, implicating a history of sexual selection and relaxation of selection on sperm as key factors driving rapid change to ontogenetically distinguishable coexpression modules of genes. We propose that these predictable trends of molecular evolution for dynamically expressed genes across ontogeny predispose particular life stages, early embryogenesis in particular, to hybrid dysfunction in the speciation process.

Genome structure predicts modular transcriptome responses to genetic and environmental conditions

Understanding the plasticity, robustness and modularity of transcriptome expression to genetic and environmental conditions is crucial to deciphering how organisms adapt in nature. To test how genome architecture influences transcriptome profiles, we quantified expression responses for distinct temperature-adapted genotypes of the nematode Caenorhabditis briggsae when exposed to chronic temperature stresses throughout development. We found that 56% of the 8,795 differentially expressed genes show genotype-specific changes in expression in response to temperature (genotype-by-environment interactions, GxE). Most genotype-specific responses occur under heat stress, indicating that cold vs. heat stress responses involve distinct genomic architectures. The 22 co-expression modules that we identified differ in their enrichment of genes with genetic vs. environmental vs. interaction effects, as well as their genomic spatial distributions, functional attributes and rates of molecular evolution at the sequence level. Genes in modules enriched for simple effects of either genotype or temperature alone tend to evolve especially rapidly, consistent with disproportionate influence of adaptation or weaker constraint on these subsets of loci. Chromosome-scale heterogeneity in nucleotide polymorphism, however, rather than the scale of individual genes predominates as the source of genetic differences among expression profiles, and natural selection regimes are largely decoupled between coding sequences and noncoding flanking sequences that contain cis-regulatory elements. These results illustrate how the form of transcriptome modularity and genome structure contribute to predictable profiles of evolutionary change.

Allele-specific expression and alternative splicing in horse×donkey and cattle×yak hybrids

Divergence of gene expression and alternative splicing is a crucial driving force in the evolution of species; to date, however the molecular mechanism remains unclear. Hybrids of closely related species provide a suitable model to analyze allele-specific expression (ASE) and allele-specific alternative splicing (ASS). Analysis of ASE and ASS can uncover the differences in cis-regulatory elements between closely related species, while eliminating interference of trans-regulatory elements. Here, we provide a detailed characterization of ASE and ASS from 19 and 10 transcriptome datasets across five tissues from reciprocal-cross hybrids of horse×donkey (mule/hinny) and cattle×yak (dzo), respectively. Results showed that 4.8%-8.7% and 10.8%-16.7% of genes exhibited ASE and ASS, respectively. Notably, lncRNAs and pseudogenes were more likely to show ASE than protein-coding genes. In addition, genes showing ASE and ASS in mule/hinny were found to be involved in the regulation of muscle strength, whereas those of dzo were involved in high-altitude adaptation. In conclusion, our study demonstrated that exploration of genes showing ASE and ASS in hybrids of closely related species is feasible for species evolution research.

Multitranscriptome analyses reveal prioritized genes specifically associated with liver fibrosis progression independent of etiology

Elimination or suppression of causative factors can raise the possibility of liver fibrosis regression. However, different injurious stimuli will give fibrosis from somewhat different etiologies, which, in turn, may hamper the discovery of liver fibrosis-specific therapeutic drugs. Therefore, the analogical cellular and molecular events shared by various etiology-evoked liver fibrosis should be clarified. Our present study systematically integrated five publicly available transcriptomic data sets regarding liver fibrosis with different etiologies from the Gene Expression Omnibus database and performed a series of bioinformatics analyses and experimental verifications. A total of 111 significantly upregulated and 16 downregulated genes were identified specific to liver fibrosis independent of any etiology. These genes were predominately enriched in some Kyoto Encyclopedia of Genes and Genomes pathways, including the "PI3K-AKT signaling pathway," "Focal adhesion," and "ECM-receptor interaction." Subsequently, five prioritized liver fibrosis-specific genes, including COL4A2, THBS2, ITGAV, LAMB1, and PDGFRA, were screened. These genes were positively associated with each other and liver fibrosis progression. In addition, they could robustly separate all stages of samples in both training and validation data sets with diverse etiologies when they were regarded as observed variables applied to principal component analysis plots. Expressions of all five genes were confirmed in activated primary mouse hepatic stellate cells (HSCs) and transforming growth factor β1-treated LX-2 cells. Moreover, THBS2 protein was enhanced in liver fibrosis rodent models, which could promote HSC activation and proliferation and facilitate NOTCH1/JAG1 expression in HSCs. Overall, our current study may provide potential targets for liver fibrosis therapy and aid to a deeper understanding of the molecular underpinnings of liver fibrosis. NEW & NOTEWORTHY Prioritized liver fibrosis-specific genes THBS2, COL4A2, ITGAV, LAMB1, and PDGFRA were identified and significantly associated with liver fibrosis progression and could be combined to discriminate liver fibrosis stages regardless of any etiology. Among the identified prioritized liver fibrosis-specific targets, THBS2 protein was confirmed to be enhanced in liver fibrosis rodent models, which could promote hepatic stellate cell (HSC) activation and proliferation and facilitate NOTCH1/JAG1 expression in HSCs.

Lineage-Specific Expression Divergence in Grasses Is Associated with Male Reproduction, Host-Pathogen Defense, and Domestication

Poaceae (grasses) is an agriculturally important and widely distributed family of plants with extraordinary phenotypic diversity, much of which was generated under recent lineage-specific evolution. Yet, little is known about the genes and functional modules involved in the lineage-specific divergence of grasses. Here, I address this question on a genome-wide scale by applying a novel branch-based statistic of lineage-specific expression divergence, LED, to RNA-seq data from nine tissues of the wild grass Brachypodium distachyon and its domesticated relatives Oryza sativa japonica (rice) and Sorghum bicolor (sorghum). I find that LED is generally smallest in B. distachyon and largest in O. sativa japonica, which underwent domestication earlier than S. bicolor, supporting the hypothesis that domestication may increase the rate of lineage-specific expression divergence in grasses. Moreover, in all three species, LED is positively correlated with protein-coding sequence divergence and tissue specificity, and negatively correlated with network connectivity. Further analysis reveals that genes with large LED are often primarily expressed in anther, implicating lineage-specific expression divergence in the evolution of male reproductive phenotypes. Gene ontology enrichment analysis also identifies an overrepresentation of terms related to male reproduction in the two domesticated grasses, as well as to those involved in host-pathogen defense in all three species. Last, examinations of genes with the largest LED reveal that their lineage-specific expression divergence may have contributed to antimicrobial functions in B. distachyon, to enhanced adaptation and yield during domestication in O. sativa japonica, and to defense against a widespread and devastating fungal pathogen in S. bicolor. Together, these findings suggest that lineage-specific expression divergence in grasses may increase under domestication and preferentially target rapidly evolving genes involved in male reproduction, host-pathogen defense, and the origin of domesticated phenotypes.

Comparative Transcriptomics in Two Bivalve Species Offers Different Perspectives on the Evolution of Sex-Biased Genes

Comparative genomics has become a central tool for evolutionary biology, and a better knowledge of understudied taxa represents the foundation for future work. In this study, we characterized the transcriptome of male and female mature gonads in the European clam Ruditapes decussatus, compared with that in the Manila clam Ruditapes philippinarum providing, for the first time in bivalves, information about transcription dynamics and sequence evolution of sex-biased genes. In both the species, we found a relatively low number of sex-biased genes (1,284, corresponding to 41.3% of the orthologous genes between the two species), probably due to the absence of sexual dimorphism, and the transcriptional bias is maintained in only 33% of the orthologs. The dN/dS is generally low, indicating purifying selection, with genes where the female-biased transcription is maintained between the two species showing a significantly higher dN/dS. Genes involved in embryo development, cell proliferation, and maintenance of genome stability show a faster sequence evolution. Finally, we report a lack of clear correlation between transcription level and evolutionary rate in these species, in contrast with studies that reported a negative correlation. We discuss such discrepancy and call into question some methodological approaches and rationales generally used in this type of comparative studies.

Conserved noncoding sequences conserve biological networks and influence genome evolution

Comparative genomics approaches have identified numerous conserved cis-regulatory sequences near genes in plant genomes. Despite the identification of these conserved noncoding sequences (CNSs), our knowledge of their functional importance and selection remains limited. Here, we used a combination of DNA methylome analysis, microarray expression analyses, and functional annotation to study these sequences in the model tree Populus trichocarpa. Methylation in CG contexts and non-CG contexts was lower in CNSs, particularly CNSs in the 5'-upstream regions of genes, compared with other sites in the genome. We observed that CNSs are enriched in genes with transcription and binding functions, and this also associated with syntenic genes and those from whole-genome duplications, suggesting that cis-regulatory sequences play a key role in genome evolution. We detected a significant positive correlation between CNS number and protein interactions, suggesting that CNSs may have roles in the evolution and maintenance of biological networks. The divergence of CNSs indicates that duplication-degeneration-complementation drives the subfunctionalization of a proportion of duplicated genes from whole-genome duplication. Furthermore, population genomics confirmed that most CNSs are under strong purifying selection and only a small subset of CNSs shows evidence of adaptive evolution. These findings provide a foundation for future studies exploring these key genomic features in the maintenance of biological networks, local adaptation, and transcription.

Cell-type- and tissue-specific transcriptomes of the white spruce (Picea glauca) bark unmask fine-scale spatial patterns of constitutive and induced conifer defense

Plant defenses often involve specialized cells and tissues. In conifers, specialized cells of the bark are important for defense against insects and pathogens. Using laser microdissection, we characterized the transcriptomes of cortical resin duct cells, phenolic cells and phloem of white spruce (Picea glauca) bark under constitutive and methyl jasmonate (MeJa)-induced conditions, and we compared these transcriptomes with the transcriptome of the bark tissue complex. Overall, ~3700 bark transcripts were differentially expressed in response to MeJa. Approximately 25% of transcripts were expressed in only one cell type, revealing cell specialization at the transcriptome level. MeJa caused cell-type-specific transcriptome responses and changed the overall patterns of cell-type-specific transcript accumulation. Comparison of transcriptomes of the conifer bark tissue complex and specialized cells resolved a masking effect inherent to transcriptome analysis of complex tissues, and showed the actual cell-type-specific transcriptome signatures. Characterization of cell-type-specific transcriptomes is critical to reveal the dynamic patterns of spatial and temporal display of constitutive and induced defense systems in a complex plant tissue or organ. This was demonstrated with the improved resolution of spatially restricted expression of sets of genes of secondary metabolism in the specialized cell types.

Systematic Analyses and Prediction of Human Drug Side Effect Associated Proteins from the Perspective of Protein Evolution

Identification of various factors involved in adverse drug reactions in target proteins to develop therapeutic drugs with minimal/no side effect is very important. In this context, we have performed a comparative evolutionary rate analyses between the genes exhibiting drug side-effect(s) (SET) and genes showing no side effect (NSET) with an aim to increase the prediction accuracy of SET/NSET proteins using evolutionary rate determinants. We found that SET proteins are more conserved than the NSET proteins. The rates of evolution between SET and NSET protein primarily depend upon their noncomplex (protein complex association number = 0) forming nature, phylogenetic age, multifunctionality, membrane localization, and transmembrane helix content irrespective of their essentiality, total druggability (total number of drugs/target), m-RNA expression level, and tissue expression breadth. We also introduced two novel terms—killer druggability (number of drugs with killing side effect(s)/target), essential druggability (number of drugs targeting essential proteins/target) to explain the evolutionary rate variation between SET and NSET proteins. Interestingly, we noticed that SET proteins are younger than NSET proteins and multifunctional younger SET proteins are candidates of acquiring killing side effects. We provide evidence that higher killer druggability, multifunctionality, and transmembrane helices support the conservation of SET proteins over NSET proteins in spite of their recent origin. By employing all these entities, our Support Vector Machine model predicts human SET/NSET proteins to a high degree of accuracy (∼86%).

Integrated analysis of microRNA and gene expression profiles reveals a functional regulatory module associated with liver fibrosis

BACKGROUND

Liver fibrosis, characterized with the excessive accumulation of extracellular matrix (ECM) proteins, represents the final common pathway of chronic liver inflammation. Ever-increasing evidence indicates microRNAs (miRNAs) dysregulation has important implications in the different stages of liver fibrosis. However, our knowledge of miRNA-gene regulation details pertaining to such disease remains unclear.

METHODS

The publicly available Gene Expression Omnibus (GEO) datasets of patients suffered from cirrhosis were extracted for integrated analysis. Differentially expressed miRNAs (DEMs) and genes (DEGs) were identified using GEO2R web tool. Putative target gene prediction of DEMs was carried out using the intersection of five major algorithms: DIANA-microT, TargetScan, miRanda, PICTAR5 and miRWalk. Functional miRNA-gene regulatory network (FMGRN) was constructed based on the computational target predictions at the sequence level and the inverse expression relationships between DEMs and DEGs. DAVID web server was selected to perform KEGG pathway enrichment analysis. Functional miRNA-gene regulatory module was generated based on the biological interpretation. Internal connections among genes in liver fibrosis-related module were determined using String database. MiRNA-gene regulatory modules related to liver fibrosis were experimentally verified in recombinant human TGFβ1 stimulated and specific miRNA inhibitor treated LX-2 cells.

RESULTS

We totally identified 85 and 923 dysregulated miRNAs and genes in liver cirrhosis biopsy samples compared to their normal controls. All evident miRNA-gene pairs were identified and assembled into FMGRN which consisted of 990 regulations between 51 miRNAs and 275 genes, forming two big sub-networks that were defined as down-network and up-network, respectively. KEGG pathway enrichment analysis revealed that up-network was prominently involved in several KEGG pathways, in which "Focal adhesion", "PI3K-Akt signaling pathway" and "ECM-receptor interaction" were remarked significant (adjusted p<0.001). Genes enriched in these pathways coupled with their regulatory miRNAs formed a functional miRNA-gene regulatory module that contains 7 miRNAs, 22 genes and 42 miRNA-gene connections. Gene interaction analysis based on String database revealed that 8 out of 22 genes were highly clustered. Finally, we experimentally confirmed a functional regulatory module containing 5 miRNAs (miR-130b-3p, miR-148a-3p, miR-345-5p, miR-378a-3p, and miR-422a) and 6 genes (COL6A1, COL6A2, COL6A3, PIK3R3, COL1A1, CCND2) associated with liver fibrosis.

CONCLUSIONS

Our integrated analysis of miRNA and gene expression profiles highlighted a functional miRNA-gene regulatory module associated with liver fibrosis, which, to some extent, may provide important clues to better understand the underlying pathogenesis of liver fibrosis.

Intra and Interspecific Variations of Gene Expression Levels in Yeast Are Largely Neutral: (Nei Lecture, SMBE 2016, Gold Coast)

It is commonly, although not universally, accepted that most intra and interspecific genome sequence variations are more or less neutral, whereas a large fraction of organism-level phenotypic variations are adaptive. Gene expression levels are molecular phenotypes that bridge the gap between genotypes and corresponding organism-level phenotypes. Yet, it is unknown whether natural variations in gene expression levels are mostly neutral or adaptive. Here we address this fundamental question by genome-wide profiling and comparison of gene expression levels in nine yeast strains belonging to three closely related Saccharomyces species and originating from five different ecological environments. We find that the transcriptome-based clustering of the nine strains approximates the genome sequence-based phylogeny irrespective of their ecological environments. Remarkably, only ∼0.5% of genes exhibit similar expression levels among strains from a common ecological environment, no greater than that among strains with comparable phylogenetic relationships but different environments. These and other observations strongly suggest that most intra and interspecific variations in yeast gene expression levels result from the accumulation of random mutations rather than environmental adaptations. This finding has profound implications for understanding the driving force of gene expression evolution, genetic basis of phenotypic adaptation, and general role of stochasticity in evolution.

Comparative transcriptomics in human and mouse

Cross-species comparisons of genomes, transcriptomes and gene regulation are now feasible at unprecedented resolution and throughput, enabling the comparison of human and mouse biology at the molecular level. Insights have been gained into the degree of conservation between human and mouse at the level of not only gene expression but also epigenetics and inter-individual variation. However, a number of limitations exist, including incomplete transcriptome characterization and difficulties in identifying orthologous phenotypes and cell types, which are beginning to be addressed by emerging technologies. Ultimately, these comparisons will help to identify the conditions under which the mouse is a suitable model of human physiology and disease, and optimize the use of animal models.

Differential subnetwork of chemokines/cytokines in human, mouse, and rat brain cells after oxygen-glucose deprivation

Mice and rats are the most commonly used animals for preclinical stroke studies, but it is unclear whether targets and mechanisms are always the same across different species. Here, we mapped the baseline expression of a chemokine/cytokine subnetwork and compared responses after oxygen-glucose deprivation in primary neurons, astrocytes, and microglia from mouse, rat, and human. Baseline profiles of chemokines (CX3CL1, CXCL12, CCL2, CCL3, and CXCL10) and cytokines (IL-1α, IL-1β, IL-6, IL-10, and TNFα) showed significant differences between human and rodents. The response of chemokines/cytokines to oxygen-glucose deprivation was also significantly different between species. After 4 h oxygen-glucose deprivation and 4 h reoxygenation, human and rat neurons showed similar changes with a downregulation in many chemokines, whereas mouse neurons showed a mixed response with up- and down-regulated genes. For astrocytes, subnetwork response patterns were more similar in rats and mice compared to humans. For microglia, rat cells showed an upregulation in all chemokines/cytokines, mouse cells had many down-regulated genes, and human cells showed a mixed response with up- and down-regulated genes. This study provides proof-of-concept that species differences exist in chemokine/cytokine subnetworks in brain cells that may be relevant to stroke pathophysiology. Further investigation of differential gene pathways across species is warranted.

The Evolution and Expression Pattern of Human Overlapping lncRNA and Protein-coding Gene Pairs

Long non-coding RNA overlapping with protein-coding gene (lncRNA-coding pair) is a special type of overlapping genes. Protein-coding overlapping genes have been well studied and increasing attention has been paid to lncRNAs. By studying lncRNA-coding pairs in human genome, we showed that lncRNA-coding pairs were more likely to be generated by overprinting and retaining genes in lncRNA-coding pairs were given higher priority than non-overlapping genes. Besides, the preference of overlapping configurations preserved during evolution was based on the origin of lncRNA-coding pairs. Further investigations showed that lncRNAs promoting the splicing of their embedded protein-coding partners was a unilateral interaction, but the existence of overlapping partners improving the gene expression was bidirectional and the effect was decreased with the increased evolutionary age of genes. Additionally, the expression of lncRNA-coding pairs showed an overall positive correlation and the expression correlation was associated with their overlapping configurations, local genomic environment and evolutionary age of genes. Comparison of the expression correlation of lncRNA-coding pairs between normal and cancer samples found that the lineage-specific pairs including old protein-coding genes may play an important role in tumorigenesis. This work presents a systematically comprehensive understanding of the evolution and the expression pattern of human lncRNA-coding pairs.

Maintenance and Function of a Plant Chromosome in Human Cells

Replication, segregation, gene expression, and inheritance are essential features of all eukaryotic chromosomes. To delineate the extent of conservation of chromosome functions between humans and plants during evolutionary history, we have generated the first human cell line containing an Arabidopsis chromosome. The Arabidopsis chromosome was mitotically stable in hybrid cells following cell division, and initially existed as a translocated chromosome. During culture, the translocated chromosomes then converted to two types of independent plant chromosomes without human DNA sequences, with reproducibility. One pair of localization signals of CENP-A, a marker of functional centromeres was detected in the Arabidopsis genomic region in independent plant chromosomes. These results suggest that the chromosome maintenance system was conserved between human and plants. Furthermore, the expression of plant endogenous genes was observed in the hybrid cells, implicating that the plant chromosomal region existed as euchromatin in a human cell background and the gene expression system is conserved between two organisms. The present study suggests that the essential chromosome functions are conserved between evolutionarily distinct organisms such as humans and plants. Systematic analyses of hybrid cells may lead to the production of a shuttle vector between animal and plant, and a platform for the genome writing.

Adaptive evolution and functional innovation of Populus-specific recently evolved microRNAs

Lineage-specific microRNAs (miRNAs) undergo rapid turnover during evolution; however, their origin and functional importance have remained controversial. Here, we examine the origin, evolution, and potential roles in local adaptation of Populus-specific miRNAs, which originated after the recent salicoid-specific, whole-genome duplication. RNA sequencing was used to generate extensive, comparable miRNA and gene expression data for six tissues. A natural population of Populus trichocarpa and closely related species were used to study the divergence rates, evolution, and adaptive variation of miRNAs. MiRNAs that originated in 5' untranslated regions had higher expression levels and their expression showed high correlation with their host genes. Compared with conserved miRNAs, a significantly higher proportion of Populus-specific miRNAs appear to target genes that were duplicated in salicoids. Examination of single nucleotide polymorphisms in Populus-specific miRNA precursors showed high amounts of population differentiation. We also characterized the newly emerged MIR6445 family, which could trigger the production of phased small interfering RNAs from NAC mRNAs, which encode a transcription factor with primary roles in a variety of plant developmental processes. Together, these observations provide evolutionary insights into the birth and potential roles of Populus-specific miRNAs in genome maintenance, local adaptation, and functional innovation.

Tissue-Specificity of Gene Expression Diverges Slowly between Orthologs, and Rapidly between Paralogs

The ortholog conjecture implies that functional similarity between orthologous genes is higher than between paralogs. It has been supported using levels of expression and Gene Ontology term analysis, although the evidence was rather weak and there were also conflicting reports. In this study on 12 species we provide strong evidence of high conservation in tissue-specificity between orthologs, in contrast to low conservation between within-species paralogs. This allows us to shed a new light on the evolution of gene expression patterns. While there have been several studies of the correlation of expression between species, little is known about the evolution of tissue-specificity itself. Ortholog tissue-specificity is strongly conserved between all tetrapod species, with the lowest Pearson correlation between mouse and frog at r = 0.66. Tissue-specificity correlation decreases strongly with divergence time. Paralogs in human show much lower conservation, even for recent Primate-specific paralogs. When both paralogs from ancient whole genome duplication tissue-specific paralogs are tissue-specific, it is often to different tissues, while other tissue-specific paralogs are mostly specific to the same tissue. The same patterns are observed using human or mouse as focal species, and are robust to choices of datasets and of thresholds. Our results support the following model of evolution: in the absence of duplication, tissue-specificity evolves slowly, and tissue-specific genes do not change their main tissue of expression; after small-scale duplication the less expressed paralog loses the ancestral specificity, leading to an immediate difference between paralogs; over time, both paralogs become more broadly expressed, but remain poorly correlated. Finally, there is a small number of paralog pairs which stay tissue-specific with the same main tissue of expression, for at least 300 million years.

Evolution-informed modeling improves outcome prediction for cancers

Despite wide applications of high-throughput biotechnologies in cancer research, many biomarkers discovered by exploring large-scale omics data do not provide satisfactory performance when used to predict cancer treatment outcomes. This problem is partly due to the overlooking of functional implications of molecular markers. Here, we present a novel computational method that uses evolutionary conservation as prior knowledge to discover bona fide biomarkers. Evolutionary selection at the molecular level is nature's test on functional consequences of genetic elements. By prioritizing genes that show significant statistical association and high functional impact, our new method reduces the chances of including spurious markers in the predictive model. When applied to predicting therapeutic responses for patients with acute myeloid leukemia and to predicting metastasis for patients with prostate cancers, the new method gave rise to evolution-informed models that enjoyed low complexity and high accuracy. The identified genetic markers also have significant implications in tumor progression and embrace potential drug targets. Because evolutionary conservation can be estimated as a gene-specific, position-specific, or allele-specific parameter on the nucleotide level and on the protein level, this new method can be extended to apply to miscellaneous "omics" data to accelerate biomarker discoveries.

Cross-Species Analysis of Gene Expression and Function in Prefrontal Cortex, Hippocampus and Striatum

Background

Mouse has been extensively used as a tool for investigating the onset and development of human neurological disorders. As a first step to construct a transgenic mouse model of human brain lesions, it is of fundamental importance to clarify the similarity and divergence of genetic background between non-diseased human and mouse brain tissues.

Methods

We systematically compared, based on large scale integrated microarray data, the transcriptomes of three anatomically distinct brain regions; prefrontal cortex (PFC), hippocampus (HIP) and striatum (STR), across human and mouse. The widely used DAVID web server was used to decipher the biological functions of the highly expressed genes that were identified using a previously reported approach. Venn analysis was used to depict the overlapping ratios of the notably enriched biological process (BP) terms (one-tailed Fisher’s exact test and Benjamini correction; adjusted p < 0.01) between two brain tissues. GOSemSim, an R package, was selected to perform GO semantic similarity analysis. Next, we adjusted signal intensities of orthologous genes by the total signals in all samples within species, and used one minus Pearson’s correlation coefficient to assess the expression distance. Hierarchical clustering and principal component analysis (PCA) were selected for expression pattern analysis. Lineage specific expressed orthologous genes were identified by comparison of the most extreme sub-datasets across species and further verified using reverse transcription PCR (RT-PCR) and quantitative real-time PCR (qRT-PCR).

Results

We found that the number of the significantly enriched BP terms of the highly expressed genes in human brain regions is larger than that in mouse corresponding brain regions. The mainly involved BP terms in human brain tissues associated with protein-membrane targeting and selenium metabolism are species-specific. The overlapping ratios of all the significantly enriched BP terms between any two brain tissues across species are lower than that within species, but the pairwise semantic similarities are very high between any two brain tissues from either human or mouse. Hierarchical clustering analysis shows the biological functions of the highly expressed genes in brain tissues are more consistent within species than interspecies; whereas it shows the expression patterns of orthologous genes are evidently conserved between human and mouse equivalent brain tissues. In addition, we identified four orthologous genes (COX5B, WIF1, SLC4A10 and PLA2G7) that are species-specific, which have been widely studied and confirmed to be closely linked with neuro- physiological and pathological functions.

Conclusion

Our study highlights the similarities and divergences in gene function and expression between human and mouse corresponding brain regions, including PFC, HIP and STR.

Gene-specific patterns of expression variation across organs and species

BACKGROUND

A comparison of transcriptional profiles derived from different tissues in a given species or among different species assumes that commonalities reflect evolutionarily conserved programs and that differences reflect species or tissue responses to environmental conditions or developmental program staging. Apparently conflicting results have been published regarding whether organ-specific transcriptional patterns dominate over species-specific patterns, or vice versa, making it unclear to what extent the biology of a given organism can be extrapolated to another. These studies have in common that they treat the transcriptomes monolithically, implicitly ignoring that each gene is likely to have a specific pattern of transcriptional variation across organs and species.

RESULTS

We use linear models to quantify this pattern. We find a continuum in the spectrum of expression variation: the expression of some genes varies considerably across species and little across organs, and simply reflects evolutionary distance. At the other extreme are genes whose expression varies considerably across organs and little across species; these genes are much more likely to be associated with diseases than are genes whose expression varies predominantly across species.

CONCLUSIONS

Whether transcriptomes, when considered globally, cluster preferentially according to one component or the other may not be a property of the transcriptomes, but rather a consequence of the dominant behavior of a subset of genes. Therefore, the values of the components of the variance of expression for each gene could become a useful resource when planning, interpreting, and extrapolating experimental data from mouse to humans.

Significant variations in alternative splicing patterns and expression profiles between human-mouse orthologs in early embryos

Human and mouse orthologs are expected to have similar biological functions; however, many discrepancies have also been reported. We systematically compared human and mouse orthologs in terms of alternative splicing patterns and expression profiles. Human-mouse orthologs are divergent in alternative splicing, as human orthologs could generally encode more isoforms than their mouse orthologs. In early embryos, exon skipping is far more common with human orthologs, whereas constitutive exons are more prevalent with mouse orthologs. This may correlate with divergence in expression of splicing regulators. Orthologous expression similarities are different in distinct embryonic stages, with the highest in morula. Expression differences for orthologous transcription factor genes could play an important role in orthologous expression discordance. We further detected largely orthologous divergence in differential expression between distinct embryonic stages. Collectively, our study uncovers significant orthologous divergence from multiple aspects, which may result in functional differences and dynamics between human-mouse orthologs during embryonic development.

Exploring novel candidate genes from the Mouse Genome Informatics database: Potential implications for avian migration research

To search for genes associated with migratory phenotypes in songbirds, we selected candidate genes through annotations from the Mouse Genome Informatics database and assembled an extensive candidate-gene library. Then, we implemented a next-generation sequencing approach to obtain DNA sequences from the Painted Bunting genome. We focused on those sequences that were conserved across avian species and that aligned with candidate genes in our mouse library. We genotyped short sequence repeats from the following candidate genes: ADRA1d, ANKRD17, CISH and MYH7. We studied the possible correlations between allelic variations occurring in these novel candidate migration genes and avian migratory phenotypes available from the published literature. We found that allele variation at MYH7 correlated with a calculated index of speed of migration (km/day) across 11 species of songbirds. We highlight the potential of the Mouse Genome Informatics database in providing new candidate genes that might play a crucial role in regulating migration in birds and possibly in other taxa. Our research effort shows the benefits and limitations of working with extensive genomic datasets and offers a snapshot of the challenges related to cross-species validation in behavioral and molecular ecology studies.

A comparison of human and mouse gene co-expression networks reveals conservation and divergence at the tissue, pathway and disease levels

Background

A deeper understanding of differences and similarities in transcriptional regulation between species can uncover important information about gene functions and the role of genes in disease. Deciphering such patterns between mice and humans is especially important since mice play an essential role in biomedical research.

Results

Here, in order to characterize evolutionary changes between humans and mice, we compared gene co-expression maps to evaluate the conservation of co-expression. We show that the conservation of co-expression connectivity of homologous genes is negatively correlated with molecular evolution rates, as expected. Then we investigated evolutionary aspects of gene sets related to functions, tissues, pathways and diseases. Genes expressed in the testis, eye and skin, and those associated with regulation of transcription, olfaction, PI3K signalling, response to virus and bacteria were more divergent between mice and humans in terms of co-expression connectivity. Surprisingly, a deeper investigation of the PI3K signalling cascade revealed that its divergence is caused by the most crucial genes of this pathway, such as mTOR and AKT2. On the other hand, our analysis revealed that genes expressed in the brain and in the bone, and those associated with cell adhesion, cell cycle, DNA replication and DNA repair are most strongly conserved in terms of co-expression network connectivity as well as having a lower rate of duplication events. Genes involved in lipid metabolism and genes specific to blood showed a signature of increased co-expression connectivity in the mouse. In terms of diseases, co-expression connectivity of genes related to metabolic disorders is the most strongly conserved between mice and humans and tumor-related genes the most divergent.

Conclusions

This work contributes to discerning evolutionary patterns between mice and humans in terms of gene interactions. Conservation of co-expression is a powerful approach to identify gene targets and processes with potential similarity and divergence between mice and humans, which has implications for drug testing and other studies employing the mouse as a model organism.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-015-0534-7) contains supplementary material, which is available to authorized users.

Serendipitous Meta-Transcriptomics: The Fungal Community of Norway Spruce (Picea abies)

After performing de novo transcript assembly of >1 billion RNA-Sequencing reads obtained from 22 samples of different Norway spruce (Picea abies) tissues that were not surface sterilized, we found that assembled sequences captured a mix of plant, lichen, and fungal transcripts. The latter were likely expressed by endophytic and epiphytic symbionts, indicating that these organisms were present, alive, and metabolically active. Here, we show that these serendipitously sequenced transcripts need not be considered merely as contamination, as is common, but that they provide insight into the plant’s phyllosphere. Notably, we could classify these transcripts as originating predominantly from Dothideomycetes and Leotiomycetes species, with functional annotation of gene families indicating active growth and metabolism, with particular regards to glucose intake and processing, as well as gene regulation.

Modular organization of the white spruce (Picea glauca) transcriptome reveals functional organization and evolutionary signatures

Transcript profiling has shown the molecular bases of several biological processes in plants but few studies have developed an understanding of overall transcriptome variation. We investigated transcriptome structure in white spruce (Picea glauca), aiming to delineate its modular organization and associated functional and evolutionary attributes. Microarray analyses were used to: identify and functionally characterize groups of co-expressed genes; investigate expressional and functional diversity of vascular tissue preferential genes which were conserved among Picea species, and identify expression networks underlying wood formation. We classified 22 857 genes as variable (79%; 22 coexpression groups) or invariant (21%) by profiling across several vegetative tissues. Modular organization and complex transcriptome restructuring among vascular tissue preferential genes was revealed by their assignment to coexpression groups with partially overlapping profiles and partially distinct functions. Integrated analyses of tissue-based and temporally variable profiles identified secondary xylem gene networks, showed their remodelling over a growing season and identified PgNAC-7 (no apical meristerm (NAM), Arabidopsis transcription activation factor (ATAF) and cup-shaped cotyledon (CUC) transcription factor 007 in Picea glauca) as a major hub gene specific to earlywood formation. Reference profiling identified comprehensive, statistically robust coexpressed groups, revealing that modular organization underpins the evolutionary conservation of the transcriptome structure.

What to compare and how: Comparative transcriptomics for Evo-Devo

Evolutionary developmental biology has grown historically from the capacity to relate patterns of evolution in anatomy to patterns of evolution of expression of specific genes, whether between very distantly related species, or very closely related species or populations. Scaling up such studies by taking advantage of modern transcriptomics brings promising improvements, allowing us to estimate the overall impact and molecular mechanisms of convergence, constraint or innovation in anatomy and development. But it also presents major challenges, including the computational definitions of anatomical homology and of organ function, the criteria for the comparison of developmental stages, the annotation of transcriptomics data to proper anatomical and developmental terms, and the statistical methods to compare transcriptomic data between species to highlight significant conservation or changes. In this article, we review these challenges, and the ongoing efforts to address them, which are emerging from bioinformatics work on ontologies, evolutionary statistics, and data curation, with a focus on their implementation in the context of the development of our database Bgee (http://bgee.org). J. Exp. Zool. (Mol. Dev. Evol.) 324B: 372–382, 2015. © 2015 The Authors. J. Exp. Zool. (Mol. Dev. Evol.) published by Wiley Periodicals, Inc.

Unraveling the association between mRNA expressions and mutant phenotypes in a genome-wide assessment of mice

High-throughput gene expression profiling has revealed substantial leaky and extraneous transcription of eukaryotic genes, challenging the perceptions that transcription is strictly regulated and that changes in transcription have phenotypic consequences. To assess the functional implications of mRNA transcription directly, we analyzed mRNA expression data derived from microarrays, RNA-sequencing, and in situ hybridization, together with phenotype data of mouse mutants as a proxy of gene function at the tissue level. The results indicated that despite the presence of widespread ectopic transcription, mRNA expression and mutant phenotypes of mammalian genes or tissues remain associated. The expression-phenotype association at the gene level was particularly strong for tissue-specific genes, and the association could be underestimated due to data insufficiency and incomprehensive phenotyping of mouse mutants; the strength of expression-phenotype association at the tissue level depended on tissue functions. Mutations on genes expressed at higher levels or expressed at earlier embryonic stages more often result in abnormal phenotypes in the tissues where they are expressed. The mRNA expression profiles that have stronger associations with their phenotype profiles tend to be more evolutionarily conserved, indicating that the evolution of transcriptome and the evolution of phenome are coupled. Therefore, mutations resulting in phenotypic aberrations in expressed tissues are more likely to occur in highly transcribed genes, tissue-specific genes, genes expressed during early embryonic stages, or genes with evolutionarily conserved mRNA expression profiles.

Three-dimensional eukaryotic genomic organization is strongly correlated with codon usage expression and function

It has been shown that the distribution of genes in eukaryotic genomes is not random; however, formerly reported relations between gene function and genomic organization were relatively weak. Previous studies have demonstrated that codon usage bias is related to all stages of gene expression and to protein function. Here we apply a novel tool for assessing functional relatedness, codon usage frequency similarity (CUFS), which measures similarity between genes in terms of codon and amino acid usage. By analyzing chromosome conformation capture data, describing the three-dimensional (3D) conformation of the DNA, we show that the functional similarity between genes captured by CUFS is directly and very strongly correlated with their 3D distance in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, mouse and human. This emphasizes the importance of three-dimensional genomic localization in eukaryotes and indicates that codon usage is tightly linked to genome architecture.