Measuring gene expression divergence: the distance to keep

Phenotype prediction in plants is improved by integrating large-scale transcriptomic datasets

Research on the dynamic expression of genes in plants is important for understanding different biological processes. We used the large amounts of transcriptomic data from various plant sample sources that are publicly available to investigate whether the expression levels of a subset of highly variable genes (HVGs) can be used to accurately identify the phenotypes of plants. Using maize (Zea mays L.) as an example, we built machine learning (ML) models to predict phenotypes using a gene expression dataset of 21 612 bulk RNA sequencing samples. We showed that the ML models achieved excellent prediction accuracy using only the HVGs to identify different phenotypes, including tissue types, developmental stages, cultivars and stress conditions. By ML models, several important functional genes were found to be associated with different phenotypes. We performed a similar analysis in rice (Orzya sativa L.) and found that the ML models could be generalized across species. However, the models trained from maize did not perform well in rice, probably because of the expression divergence of the conserved HVGs between the two species. Overall, our results provide an ML framework for phenotype prediction using gene expression profiles, which may contribute to precision management of crops in agricultural practices.

Phytochemical fingerprint revealing antibacterial and antioxidant activities of endemic banana cultivars in Southeast Asia

This study explores the bioactive secondary metabolite profiles of the peels of three major cultivars of bananas (Musa acuminata and Musa balbisiana). These cultivars are primarily grown in Southeast Asia and are widely consumed due to their rich nutritional and fiber content. The research utilizes advanced analytical techniques, specifically HPLC-DAD-q-TOF-MS/MS, in conjunction with both univariate and multivariate statistical analyses, to analyze the ethanolic extracts of the banana peels. This study identifies phenolic acids, flavonoids, and proanthocyanidins as significant contributors to the differentiation of the cultivars. The secondary metabolites rutin, chlorogenic acid, and gentisic acid are pinpointed as the key discriminants. Moreover, the research demonstrates a synergistic contribution of certain phytochemicals to the antioxidant and antibacterial properties of the banana peel extracts. The fingerprint profiling tools introduced in this study offer a reliable method for identifying metabolite biomarkers for the discrimination of banana cultivars.

Initiation of a ZAKα-dependent ribotoxic stress response by the innate immunity endoribonuclease RNase L

RNase L is an endoribonuclease of higher vertebrates that functions in antiviral innate immunity. Interferons induce oligoadenylate synthetase enzymes that sense double-stranded RNA of viral origin leading to the synthesis of 2',5'-oligoadenylate (2-5A) activators of RNase L. However, it is unknown precisely how RNase L remodels the host cell transcriptome. To isolate effects of RNase L from other effects of double-stranded RNA or virus, 2-5A is directly introduced into cells. Here, we report that RNase L activation by 2-5A causes a ribotoxic stress response involving the MAP kinase kinase kinase (MAP3K) ZAKα, MAP2Ks, and the stress-activated protein kinases JNK and p38α. RNase L activation profoundly alters the transcriptome by widespread depletion of mRNAs associated with different cellular functions but also by JNK/p38α-stimulated induction of inflammatory genes. These results show that the 2-5A/RNase L system triggers a protein kinase cascade leading to proinflammatory signaling and apoptosis.

Overcoming the impossibility of age-balanced harvest

In many countries, sustainability targets for managed fisheries are often expressed in terms of a fixed percentage of the carrying capacity. Despite the appeal of such a simple quantitative target, an unintended consequence may be a significant tilting of the proportions of biomass across different ages, from what they would have been under harvest-free conditions. Within the framework of a widely used age-structured model, we propose a novel quantitative definition of "age-balanced harvest" that considers the age-class composition relative to that of the unfished population. We show that achieving a perfectly age-balanced policy is impossible if we harvest any fish whatsoever. However, every non-trivial harvest policy has a special structure that favours the young. To quantify the degree of age-imbalance, we propose a cross-entropy function. We formulate an optimisation problem that aims to attain an "age-balanced steady state", subject to adequate yield. We demonstrate that near balanced harvest policies are achievable by sacrificing a small amount of yield. These findings have important implications for sustainable fisheries management by providing insights into trade-offs and harvest policy recommendations.

Initiation of a ZAKα-dependent Ribotoxic Stress Response by the Innate Immunity Endoribonuclease RNase L

RNase L is a regulated endoribonuclease in higher vertebrates that functions in antiviral innate immunity. Interferons induce OAS enzymes that sense double-stranded RNA of viral origin leading to synthesis of 2',5'-oligoadenylate (2-5A) activators of RNase L. However, it is unknown precisely how RNase L inhibits viral infections. To isolate effects of RNase L from other effects of double-stranded RNA or virus, 2-5A was directly introduced into cells. Here we report that RNase L activation by 2-5A causes a ribotoxic stress response that requires the ribosome-associated MAP3K, ZAKα. Subsequently, the stress-activated protein kinases (SAPK) JNK and p38α are phosphorylated. RNase L activation profoundly altered the transcriptome by widespread depletion of mRNAs associated with different cellular functions, but also by SAPK-dependent induction of inflammatory genes. Our findings show that 2-5A is a ribotoxic stressor that causes RNA damage through RNase L triggering a ZAKα kinase cascade leading to proinflammatory signaling and apoptosis.

Extensive intratumor regional epigenetic heterogeneity in clear cell renal cell carcinoma targets kidney enhancers and is associated with poor outcome

BACKGROUND

Clear cell renal cell cancer (ccRCC), the 8th leading cause of cancer-related death in the US, is challenging to treat due to high level intratumoral heterogeneity (ITH) and the paucity of druggable driver mutations. CcRCC is unusual for its high frequency of epigenetic regulator mutations, such as the SETD2 histone H3 lysine 36 trimethylase (H3K36me3), and low frequency of traditional cancer driver mutations. In this work, we examined epigenetic level ITH and defined its relationships with pathologic features, aspects of tumor biology, and SETD2 mutations.

RESULTS

A multi-region sampling approach coupled with EPIC DNA methylation arrays was conducted on a cohort of normal kidney and ccRCC. ITH was assessed using DNA methylation (5mC) and CNV-based entropy and Euclidian distances. We found elevated 5mC heterogeneity and entropy in ccRCC relative to normal kidney. Variable CpGs are highly enriched in enhancer regions. Using intra-class correlation coefficient analysis, we identified CpGs that segregate tumor regions according to clinical phenotypes related to tumor aggressiveness. SETD2 wild-type tumors overall possess greater 5mC and copy number ITH than SETD2 mutant tumor regions, suggesting SETD2 loss contributes to a distinct epigenome. Finally, coupling our regional data with TCGA, we identified a 5mC signature that links regions within a primary tumor with metastatic potential.

CONCLUSION

Taken together, our results reveal marked levels of epigenetic ITH in ccRCC that are linked to clinically relevant tumor phenotypes and could translate into novel epigenetic biomarkers.

Ribosome profiling reveals the translational landscape and allele-specific translational efficiency in rice

Translational regulation is a critical step in the process of gene expression and governs the synthesis of proteins from mRNAs. Many studies have revealed translational regulation in plants in response to various environmental stimuli. However, there have been no studies documenting the comprehensive landscape of translational regulation and allele-specific translational efficiency in multiple plant tissues, especially those of rice, a main staple crop that feeds nearly half of the world's population. Here we used RNA sequencing and ribosome profiling data to analyze the transcriptome and translatome of an elite hybrid rice, Shanyou 63 (SY63), and its parental varieties Zhenshan 97 and Minghui 63. The results revealed that gene expression patterns varied more among tissues than among varieties at the transcriptional and translational levels. We identified 3392 upstream open reading frames (uORFs), and the uORF-containing genes were enriched in transcription factors. Only 668 of 13 492 long non-coding RNAs could be translated into peptides. Finally, we discovered numerous genes with allele-specific translational efficiency in SY63 and demonstrated that some cis-regulatory elements may contribute to allelic divergence in translational efficiency. Overall, these findings may improve our understanding of translational regulation in rice and provide information for molecular breeding research.

Immune Cell Networks Uncover Candidate Biomarkers of Melanoma Immunotherapy Response

The therapeutic activation of antitumour immunity by immune checkpoint inhibitors (ICIs) is a significant advance in cancer medicine, not least due to the prospect of long-term remission. However, many patients are unresponsive to ICI therapy and may experience serious side effects; companion biomarkers are urgently needed to help inform ICI prescribing decisions. We present the IMMUNETS networks of gene coregulation in five key immune cell types and their application to interrogate control of nivolumab response in advanced melanoma cohorts. The results evidence a role for each of the IMMUNETS cell types in ICI response and in driving tumour clearance with independent cohorts from TCGA. As expected, ‘immune hot’ status, including T cell proliferation, correlates with response to first-line ICI therapy. Genes regulated in NK, dendritic, and B cells are the most prominent discriminators of nivolumab response in patients that had previously progressed on another ICI. Multivariate analysis controlling for tumour stage and age highlights CIITA and IKZF3 as candidate prognostic biomarkers. IMMUNETS provide a resource for network biology, enabling context-specific analysis of immune components in orthogonal datasets. Overall, our results illuminate the relationship between the tumour microenvironment and clinical trajectories, with potential implications for precision medicine.

Parallel subgenome structure and divergent expression evolution of allo-tetraploid common carp and goldfish

How two subgenomes in allo-tetraploids adapt to coexistence and coordinate through structure and expression evolution requires extensive studies. In the present study, we report an improved genome assembly of allo-tetraploid common carp, an updated genome annotation of allo-tetraploid goldfish and the chromosome-scale assemblies of a progenitor-like diploid Puntius tetrazona and an outgroup diploid Paracanthobrama guichenoti. Parallel subgenome structure evolution in the allo-tetraploids was featured with equivalent chromosome components, higher protein identities, similar transposon divergence and contents, homoeologous exchanges, better synteny level, strong sequence compensation and symmetric purifying selection. Furthermore, we observed subgenome expression divergence processes in the allo-tetraploids, including inter-/intrasubgenome trans-splicing events, expression dominance, decreased expression levels, dosage compensation, stronger expression correlation, dynamic functionalization and balancing of differential expression. The potential disorders introduced by different progenitors in the allo-tetraploids were hypothesized to be alleviated by increasing structural homogeneity and performing versatile expression processes. Resequencing three common carp strains revealed two major ecotypes and uncovered candidate genes relevant to growth and survival rate.

Tissue- and stage-specific landscape of the mouse translatome

The current understanding of how overall principles of translational control govern the embryo-to-adult transition in mammals is still far from comprehensive. Herein we profiled the translatomes and transcriptomes of six tissues from the mice at embryonic and adult stages and presented the first report of tissue- and stage-specific translational landscape in mice. We quantified the extent of gene expression divergence among different expression layers, tissues and stages, detected significant changes in gene composition and function underlying these divergences and revealed the changing architecture of translational regulation. We further showed that dynamic translational regulation can be largely achieved via modulation of translational efficiency. Translational efficiency could be altered by alternative splicing (AS), upstream and downstream open reading frames (uORFs and dORFs). We revealed AS-mediated translational repression that was exerted in an event type-dependent manner. uORFs and dORFs exhibited mutually exclusive usage and the opposing effects of translational regulation. Furthermore, we discovered many novel microproteins encoded by long noncoding RNAs and demonstrated their regulatory potential and functional relevance. Our data and analyses will facilitate a better understanding of the complexity of translation and translational regulation across tissue and stage spectra and provide an important resource to the translatome research community.

Transcriptomic responses to silver nanoparticles in the freshwater unicellular eukaryote Tetrahymena thermophila

Currently, silver nanoparticles (AgNPs) are being increasingly used as biocides in various consumer products and if released in the environment they can affect non-target organisms. Therefore, understanding the toxicity mechanism is crucial for both the design of more efficient nano-antimicrobials and for the design of nanomaterials that are biologically and environmentally benign throughout their life-cycle. Here, the ciliate Tetrahymena thermophila was used to elucidate the mechanisms of action of AgNPs by analysing the gene expression profile by RNA-seq and the transcriptomic effects of AgNPs were compared to those induced by soluble silver salt, AgNO₃. Exposure to AgNPs at sublethal concentrations for 24 h induced phagocytosis, transport pathways, response to oxidative stress, glutathione peroxidase activity, response to stimulus, oxidation-reduction, proteolysis, and nitrogen metabolism process. Based on gene set enrichment analysis (GSEA), some biological processes appeared targets of both toxicants. In addition to many similarities in affected genes, some effects were triggered only by NPs, like phagocytosis, glutathione peroxidase activity, response to stimulus, protein phosphorylation and nitrogen metabolism process. This research provides evidence that AgNPs compared to AgNO₃ at the same concentration of dissolved silver ions dysregulate a higher number of cellular pathways. These findings confirm that AgNPs can induce toxicity not only due to soluble silver ions released from the particles but also to particle intrinsic features.

Prokaryotic Virus Orthologous Groups (pVOGs): a resource for comparative genomics and protein family annotation

Viruses are the most abundant and diverse biological entities on earth, and while most of this diversity remains completely unexplored, advances in genome sequencing have provided unprecedented glimpses into the virosphere. The Prokaryotic Virus Orthologous Groups (pVOGs, formerly called Phage Orthologous Groups, POGs) resource has aided in this task over the past decade by using automated methods to keep pace with the rapid increase in genomic data. The uses of pVOGs include functional annotation of viral proteins, identification of genes and viruses in uncharacterized DNA samples, phylogenetic analysis, large-scale comparative genomics projects, and more. The pVOGs database represents a comprehensive set of orthologous gene families shared across multiple complete genomes of viruses that infect bacterial or archaeal hosts (viruses of eukaryotes will be added at a future date). The pVOGs are constructed within the Clusters of Orthologous Groups (COGs) framework that is widely used for orthology identification in prokaryotes. Since the previous release of the POGs, the size has tripled to nearly 3000 genomes and 300 000 proteins, and the number of conserved orthologous groups doubled to 9518. User-friendly webpages are available, including multiple sequence alignments and HMM profiles for each VOG. These changes provide major improvements to the pVOGs database, at a time of rapid advances in virus genomics. The pVOGs database is hosted jointly at the University of Iowa at http://dmk-brain.ecn.uiowa.edu/pVOGs and the NCBI at ftp://ftp.ncbi.nlm.nih.gov/pub/kristensen/pVOGs/home.html.

Host gene constraints and genomic context impact the expression and evolution of human microRNAs

Increasing evidence has shown that recent miRNAs tend to emerge within coding genes. Here we conjecture that human miRNA evolution is tightly influenced by the genomic context, especially by host genes. Our findings show a preferential emergence of intragenic miRNAs within old genes. We found that miRNAs within old host genes are significantly more broadly expressed than those within young ones. Young miRNAs within old genes are more broadly expressed than their intergenic counterparts, suggesting that young miRNAs have an initial advantage by residing in old genes, and benefit from their hosts' expression control and from the exposure to diverse cellular contexts and target genes. Our results demonstrate that host genes may provide stronger expression constraints to intragenic miRNAs in the long run. We also report associated functional implications, highlighting the genomic context and host genes as driving factors for the expression and evolution of human miRNAs.

Recent miRNAs tend to emerge within coding genes. Here, by analysing miRNA expression data from six species and comparing genomes from 13 species, the authors report that host genes may provide stronger expression constraints to intragenic miRNAs in the long run.

Integrated analysis of the Plasmodium species transcriptome

The genome sequence available for different Plasmodium species is a valuable resource for understanding malaria parasite biology. However, comparative genomics on its own cannot fully explain all the species-specific differences which suggests that other genomic aspects such as regulation of gene expression play an important role in defining species-specific characteristics. Here, we developed a comprehensive approach to measure transcriptional changes of the evolutionary conserved syntenic orthologs during the intraerythrocytic developmental cycle across six Plasmodium species. We show significant transcriptional constraint at the mid-developmental stage of Plasmodium species while the earliest stages of parasite development display the greatest transcriptional variation associated with critical functional processes. Modeling of the evolutionary relationship based on changes in transcriptional profile reveal a phylogeny pattern of the Plasmodium species that strictly follows its mammalian hosts. In addition, the work shows that transcriptional conserved orthologs represent potential future targets for anti-malaria intervention as they would be expected to carry out key essential functions within the parasites. This work provides an integrated analysis of orthologous transcriptome, which aims to provide insights into the Plasmodium evolution thereby establishing a framework to explore complex pathways and drug discovery in Plasmodium species with broad host range.

•

Comparison of variations in mRNA abundance across six different Plasmodium species.

•

Transcriptional conservation and divergence of Plasmodium syntenic orthologs.

•

Pattern of Plasmodium transcriptome evolution are established.

•

Transcriptionally conserved orthologs represent attractive intervention targets.

Malaria remains a major public health concern despite global efforts in the fight against this disease. The intraerythrocytic stage of the malaria parasites is currently in the spotlight for anti-malarial intervention and vaccine targets. The primary goal of this study is to generate a comprehensive and directly comparable transcriptome dataset across multiple Plasmodium species originating from different hosts. We establish that specific pathways and intraerythrocytic stages are more transcriptionally diverged than others, reflecting transcriptional evolutionary diversity. We further propose a panel of transcriptionally conserved genes as potential drug targets.

Accumulation of CTCF-binding sites drives expression divergence between tandemly duplicated genes in humans

Background

During eukaryotic genome evolution, tandem gene duplication is the most frequent event giving rise to clustered gene families. However, how expression divergence between tandemly duplicated genes has emerged and maintained remain unclear. In particular, it is unknown if epigenetic regulators have been involved in the process.

Results

We demonstrate that CCCTC-binding factor (CTCF), the master epigenetic regulator and the only known insulator protein in humans, has played a predominant role in generating divergence in both expression profiles and expression levels between adjacent paralogs in the human genome. This phenomenon was not observed for non-paralogous adjacent genes. After tandem duplication events, CTCF-binding sites gradually accumulate between paralogs. This trend was more prominent for genes involved in particular functions.

Conclusions

The accumulation of CTCF-binding sites drives expression divergence of tandemly duplicated genes. This process is likely targeted by natural selection. Our study reveals the importance of CTCF to the evolution of animal diversity and complexity.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-S1-S8) contains supplementary material, which is available to authorized users.

Investigating host dependence of xylose utilization in recombinant Saccharomyces cerevisiae strains using RNA-seq analysis

BACKGROUND

Xylose-based ethanol production by recombinant S. cerevisiae is of great interest to basic and applied bioenergy research. By expressing three different fungal pathways in two S. cerevisiae hosts respectively, we found that the xylose utilization efficiency by recombinant S. cerevisiae depends not only on the choice of xylose pathway but also on the choice of host, exhibiting an obvious host or context dependence. To investigate molecular mechanisms of this context dependence, we applied RNA-seq analysis in this study for a systematic characterization of the xylose utilization via different pathways in different S. cerevisiae hosts.

RESULTS

Based on the RNA-seq analysis, the transcripts that were regulated during xylose utilization have been identified. Three transcription factors involved in regulation of amino acid metabolism, responses to oxidative stresses, and degradation of aggregated proteins, respectively, were found to participate in xylose metabolism regulation regardless of which pathway was expressed and which host the xylose pathway was expressed in. Nine transcription factors, involved in homeostasis, regulation of amino acid metabolism, and stress responses, were identified as the key modules responsible for the host-specific responses to the same xylose pathway. In addition, the transcriptional regulations of xylose utilization in different yeast hosts were compared to two reference regulation patterns, which indicated that diverse regulation strategies were adopted by different hosts for improved xylose utilization.

CONCLUSIONS

This study provides the first transcriptomic study of the host dependence of xylose utilization in S. cerevisiae. Both the conserved regulatory modules for xylose metabolism and the key modules responsible for host dependence were identified. As indicated by the functions of the conserved transcription factors involved in xylose metabolism regulation, the xylose utilization in recombinant S. cerevisiae may be affected by both carbohydrate metabolism regulation and stress responses. Based on the comparison of transcriptional regulation patterns, the metabolic optimizations of xylose utilization in different hosts went toward different directions, which may explain the host dependence observed in this study. The knowledge revealed by this study could provide valuable insights towards the improvement of metabolic engineering strategies for cellulosic ethanol production.

Next-generation qPCR for the high-throughput measurement of gene expression in multiple leukocyte subsets

Clinical studies of gene expression are increasingly using the whole blood, peripheral blood mononuclear cells, and leukocyte subsets involved in the innate and adaptive immune responses. However, the small amount of RNA available in the clinical setting is a limitation for commonly used methods such as quantitative polymerase chain reactions (qPCR) and microarrays. Our aim was to design 96 gene assays to simultaneously measure gene expression in the whole blood and seven leukocyte subsets using a new-generation qPCR method--high-throughput nanofluidic reverse transcription qPCR (HT RT-qPCR). The leukocyte subset purity was 94% to 98% for seven subsets and was less for the γδ T-cell receptor subset (80%). The HT RT-qPCR replicate sample measurements were highly reproducible (r = 0.997, p < 2.2 × 10(-16)), and the ΔΔCt values from HT RT-qPCR correlated significantly with those from qPCR. The control genes were differentially expressed across the eight leukocyte subsets in the control subjects (p = 1.3 × 10(-5), analysis of variance). Two analytical methods, absolute and relative, gave concordant results and were significantly correlated (p = 1.9 × 10(-9)). HT RT-qPCR permits the rapid, reproducible, and quantitative measurement of multiple transcripts using minimal sample amounts. The protocol described yielded leukocyte subsets of high purity and identified two analytic methods for use.

Heterogeneity of tumor-induced gene expression changes in the human metabolic network

Reprogramming of cellular metabolism is an emerging hallmark of neoplastic transformation. However, it is not known how metabolic gene expression in tumors differs from that in normal tissues, or whether different tumor types exhibit similar metabolic changes. Here we compare expression patterns of metabolic genes across 22 diverse types of human tumors. Overall, the metabolic gene expression program in tumors is similar to that in the corresponding normal tissues. Although expression changes of some metabolic pathways (e.g., up-regulation of nucleotide biosynthesis and glycolysis) are frequently observed across tumors, expression changes of other pathways (e.g., oxidative phosphorylation and the tricarboxylic acid (TCA) cycle) are very heterogeneous. Our analysis also suggests that the expression changes of major metabolic processes across tumors can be rationalized in terms of several principal components. On the level of individual biochemical reactions, many hundreds of metabolic isoenzymes show significant and tumor-specific expression changes. These isoenzymes are potential targets for anticancer therapy.