A high-throughput RNA-seq approach to profile transcriptional responses

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein coexpression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Transcriptional Signatures and Network-Based Approaches Identified Master Regulators Transcription Factors Involved in Experimental Periodontitis Pathogenesis

Periodontitis is a chronic inflammatory disease characterized by the progressive and irreversible destruction of the periodontium. Its aetiopathogenesis lies in the constant challenge of the dysbiotic biofilm, which triggers a deregulated immune response responsible for the disease phenotype. Although the molecular mechanisms underlying periodontitis have been extensively studied, the regulatory mechanisms at the transcriptional level remain unclear. To generate transcriptomic data, we performed RNA shotgun sequencing of the oral mucosa of periodontitis-affected mice. Since genes are not expressed in isolation during pathological processes, we disclose here the complete repertoire of differentially expressed genes (DEG) and co-expressed modules to build Gene Regulatory Networks (GRNs) and identify the Master Transcriptional Regulators of periodontitis. The transcriptional changes revealed 366 protein-coding genes and 42 non-coding genes differentially expressed and enriched in the immune response. Furthermore, we found 13 co-expression modules with different representation degrees and gene expression levels. Our GRN comprises genes from 12 gene clusters, 166 nodes, of which 33 encode Transcription Factors, and 201 connections. Finally, using these strategies, 26 master regulators of periodontitis were identified. In conclusion, combining the transcriptomic analyses with the regulatory network construction represents a powerful and efficient strategy for identifying potential periodontitis-therapeutic targets.

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein co-expression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3.6%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Highlights

At the level of individual genes, the abundance of transcripts and proteins is weakly correlated within a species ( ρ = 0.165). While the proteome is not imprinted by population structure, co-expression patterns recapitulate the cellular functional landscapeWild populations exhibit a higher abundance of respiration-related proteins compared to domesticated populationsLoci that influence protein abundance differ from those that impact transcript levels, likely because of protein turnover.

MAC-Seq: Coupling Low-Cost, High-Throughput RNA-Seq with Image-Based Phenotypic Screening in 2D and 3D Cell Models

Transcriptomic profiling has fundamentally influenced our understanding of cancer pathophysiology and response to therapeutic intervention and has become a relatively routine approach. However, standard protocols are usually low-throughput, single-plex assays and costs are still quite prohibitive. With the evolving complexity of in vitro cell model systems, there is a need for resource-efficient high-throughput approaches that can support detailed time-course analytics, accommodate limited sample availability, and provide the capacity to correlate phenotype to genotype at scale. MAC-seq (multiplexed analysis of cells) is a low-cost, ultrahigh-throughput RNA-seq workflow in plate format to measure cell perturbations and is compatible with high-throughput imaging. Here we describe the steps to perform MAC-seq in 384-well format and apply it to 2D and 3D cell cultures. On average, our experimental conditions identified over ten thousand expressed genes per well when sequenced to a depth of one million reads. We discuss technical aspects, make suggestions on experimental design, and document critical operational procedures. Our protocol highlights the potential to couple MAC-seq with high-throughput screening applications including cell phenotyping using high-content cell imaging.

Trends and Applications of Omics Technologies to Functional Characterisation of Enzymes and Protein Metabolites Produced by Fungi

Identifying and adopting industrial applications for proteins and enzymes derived from fungi strains have been at the focal point of several studies in recent times. To facilitate such studies, it is necessary that advancements and innovation in mycological and molecular characterisation are concomitant. This review aims to provide a detailed overview of the necessary steps employed in both qualitative and quantitative research using the omics technologies that are pertinent to fungi characterisation. This stems from the understanding that data provided from the functional characterisation of fungi and their metabolites is important towards the techno-economic feasibility of large-scale production of biological products. The review further describes how the functional gaps left by genomics, internal transcribe spacer (ITS) regions are addressed by transcriptomics and the various techniques and platforms utilised, including quantitive reverse transcription polymerase chain reaction (RT-qPCR), hybridisation techniques, and RNA-seq, and the insights such data provide on the effect of environmental changes on fungal enzyme production from an expressional standpoint. The review also offers information on the many available bioinformatics tools of analysis necessary for the analysis of the overwhelming data synonymous with the omics approach to fungal characterisation.

Functional dynamic genetic effects on gene regulation are specific to particular cell types and environmental conditions

Genetic effects on gene expression and splicing can be modulated by cellular and environmental factors; yet interactions between genotypes, cell type, and treatment have not been comprehensively studied together. We used an induced pluripotent stem cell system to study multiple cell types derived from the same individuals and exposed them to a large panel of treatments. Cellular responses involved different genes and pathways for gene expression and splicing and were highly variable across contexts. For thousands of genes, we identified variable allelic expression across contexts and characterized different types of gene-environment interactions, many of which are associated with complex traits. Promoter functional and evolutionary features distinguished genes with elevated allelic imbalance mean and variance. On average, half of the genes with dynamic regulatory interactions were missed by large eQTL mapping studies, indicating the importance of exploring multiple treatments to reveal previously unrecognized regulatory loci that may be important for disease.

Interpreting Coronary Artery Disease Risk Through Gene-Environment Interactions in Gene Regulation

GWAS and eQTL studies identified thousands of genetic variants associated with complex traits and gene expression. Despite the important role of environmental exposures in complex traits, only a limited number of environmental factors were measured in these studies. Measuring molecular phenotypes in tightly controlled cellular environments provides a more tractable setting to study gene-environment interactions in the absence of other confounding variables. We performed RNA-seq and ATAC-seq in endothelial cells exposed to retinoic acid, dexamethasone, caffeine, and selenium to model genetic and environmental effects on gene regulation in the vascular endothelium-a common site of pathology in cardiovascular disease. We found that genes near regions of differentially accessible chromatin were more likely to be differentially expressed [OR = (3.41, 6.52), [Formula: see text]]. Furthermore, we confirmed that environment-specific changes in transcription factor binding are a key mechanism for cellular response to environmental stimuli. Single nucleotide polymorphisms (SNPs) in these transcription response factor footprints for dexamethasone, caffeine, and retinoic acid were enriched in GTEx eQTLs from artery tissues, indicating that these environmental conditions are latently present in GTEx samples. Additionally, SNPs in footprints for response factors in caffeine are enriched in colocalized eQTLs for coronary artery disease (CAD), suggesting a role for caffeine in CAD risk. By combining GWAS, eQTLs, and response genes, we annotated environmental components that can increase or decrease disease risk through changes in gene expression in 43 genes. Interestingly, each treatment may amplify or buffer genetic risk for CAD, depending on the particular SNP or gene considered.

Gut Microbiota Has a Widespread and Modifiable Effect on Host Gene Regulation

The composition of the gut microbiome has been associated with various aspects of human health, but the mechanism of this interaction is still unclear. We utilized a cellular system to characterize the effect of the microbiome on human gene expression. We showed that some of these changes in expression may be mediated by changes in chromatin accessibility. Furthermore, we validate the role of a specific microbe and show that changes in its abundance can modify the host gene expression response. These results show an important role of gut microbiota in regulating host gene expression and suggest that manipulation of microbiome composition could be useful in future therapies.

Variation in gut microbiome is associated with wellness and disease in humans, and yet the molecular mechanisms by which this variation affects the host are not well understood. A likely mechanism is that of changing gene regulation in interfacing host epithelial cells. Here, we treated colonic epithelial cells with live microbiota from five healthy individuals and quantified induced changes in transcriptional regulation and chromatin accessibility in host cells. We identified over 5,000 host genes that change expression, including 588 distinct associations between specific taxa and host genes. The taxa with the strongest influence on gene expression alter the response of genes associated with complex traits. Using ATAC-seq, we showed that a subset of these changes in gene expression are associated with changes in host chromatin accessibility and transcription factor binding induced by exposure to gut microbiota. We then created a manipulated microbial community with titrated doses of Collinsella, demonstrating that manipulation of the composition of the microbiome under both natural and controlled conditions leads to distinct and predictable gene expression profiles in host cells. Taken together, our results suggest that specific microbes play an important role in regulating expression of individual host genes involved in human complex traits. The ability to fine-tune the expression of host genes by manipulating the microbiome suggests future therapeutic routes.

IMPORTANCE The composition of the gut microbiome has been associated with various aspects of human health, but the mechanism of this interaction is still unclear. We utilized a cellular system to characterize the effect of the microbiome on human gene expression. We showed that some of these changes in expression may be mediated by changes in chromatin accessibility. Furthermore, we validate the role of a specific microbe and show that changes in its abundance can modify the host gene expression response. These results show an important role of gut microbiota in regulating host gene expression and suggest that manipulation of microbiome composition could be useful in future therapies.

Cancer Cell Drug Response Transcriptomes in 3D

The relevance of different in vitro culture models of cancer cells is a hot topic, but few systematic and definitive analyses in this area exist. In this issue of Cell Chemical Biology, Senkowski et al. (2016) address this issue by studying the transcriptomic profiles of drug-treated cancer cells cultured in two-dimensional and three-dimensional cultures. They describe biological findings with potential therapeutic implications and provide a unique data resource to mine.

Environmental influences on RNA processing: Biochemical, molecular and genetic regulators of cellular response

RNA processing has emerged as a key mechanistic step in the regulation of the cellular response to environmental perturbation. Recent work has uncovered extensive remodeling of transcriptome composition upon environmental perturbation and linked the impacts of this molecular plasticity to health and disease outcomes. These isoform changes and their underlying mechanisms are varied-involving alternative sites of transcription initiation, alternative splicing, and alternative cleavage at the 3' end of the mRNA. The mechanisms and consequences of differential RNA processing have been characterized across a range of common environmental insults, including chemical stimuli, immune stimuli, heat stress, and cancer pathogenesis. In each case, there are perturbation-specific contributions of local (cis) regulatory elements or global (trans) factors and downstream consequences. Overall, it is clear that choices in isoform usage involve a balance between the usage of specific genetic elements (i.e., splice sites, polyadenylation sites) and the timing at which certain decisions are made (i.e., transcription elongation rate). Fine-tuned cellular responses to environmental perturbation are often dependent on the genetic makeup of the cell. Genetic analyses of interindividual variation in splicing have identified genetic effects on splicing that contribute to variation in complex traits. Finally, the increase in the number of tissue types and environmental conditions analyzed for RNA processing is paralleled by the need to develop appropriate analytical tools. The combination of large datasets, novel methods and conditions explored promises to provide a much greater understanding of the role of RNA processing response in human phenotypic variation. This article is categorized under: RNA Processing > RNA Editing and Modification RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Splicing Mechanisms RNA Processing > Splicing Regulation/Alternative Splicing.

CD40 ligand deficiency causes functional defects of peripheral neutrophils that are improved by exogenous IFN-γ

BACKGROUND

Patients with X-linked hyper-IgM syndrome caused by CD40 ligand (CD40L) deficiency often present with episodic, cyclic, or chronic neutropenia, suggesting abnormal neutrophil development in the absence of CD40L-CD40 interaction. However, even when not neutropenic and despite immunoglobulin replacement therapy, CD40L-deficient patients are susceptible to life-threatening infections caused by opportunistic pathogens, suggesting impaired phagocyte function and the need for novel therapeutic approaches.

OBJECTIVES

We sought to analyze whether peripheral neutrophils from CD40L-deficient patients display functional defects and to explore the in vitro effects of recombinant human IFN-γ (rhIFN-γ) on neutrophil function.

METHODS

We investigated the microbicidal activity, respiratory burst, and transcriptome profile of neutrophils from CD40L-deficient patients. In addition, we evaluated whether the lack of CD40L in mice also affects neutrophil function.

RESULTS

Neutrophils from CD40L-deficient patients exhibited defective respiratory burst and microbicidal activity, which were improved in vitro by rhIFN-γ but not soluble CD40L. Moreover, neutrophils from patients showed reduced CD16 protein expression and a dysregulated transcriptome suggestive of impaired differentiation. Similar to CD40L-deficient patients, CD40L knockout mice were found to have impaired neutrophil responses. In parallel, we demonstrated that soluble CD40L induces the promyelocytic cell line HL-60 to proliferate and mature by regulating the expression of genes of the same Gene Ontology categories (eg, cell differentiation) when compared with those dysregulated in peripheral blood neutrophils from CD40L-deficient patients.

CONCLUSION

Our data suggest a nonredundant role of CD40L-CD40 interaction in neutrophil development and function that could be improved in vitro by rhIFN-γ, indicating a potential novel therapeutic application for this cytokine.

Environmental perturbations lead to extensive directional shifts in RNA processing

Environmental perturbations have large effects on both organismal and cellular traits, including gene expression, but the extent to which the environment affects RNA processing remains largely uncharacterized. Recent studies have identified a large number of genetic variants associated with variation in RNA processing that also have an important role in complex traits; yet we do not know in which contexts the different underlying isoforms are used. Here, we comprehensively characterized changes in RNA processing events across 89 environments in five human cell types and identified 15,300 event shifts (FDR = 15%) comprised of eight event types in over 4,000 genes. Many of these changes occur consistently in the same direction across conditions, indicative of global regulation by trans factors. Accordingly, we demonstrate that environmental modulation of splicing factor binding predicts shifts in intron retention, and that binding of transcription factors predicts shifts in alternative first exon (AFE) usage in response to specific treatments. We validated the mechanism hypothesized for AFE in two independent datasets. Using ATAC-seq, we found altered binding of 64 factors in response to selenium at sites of AFE shift, including ELF2 and other factors in the ETS family. We also performed AFE QTL mapping in 373 individuals and found an enrichment for SNPs predicted to disrupt binding of the ELF2 factor. Together, these results demonstrate that RNA processing is dramatically changed in response to environmental perturbations through specific mechanisms regulated by trans factors.

RNA-sequencing Identifies Novel Pathways in Sarcoidosis Monocytes

Sarcoidosis is a complex systemic granulomatous disorder of unknown etiology. Genome-wide association studies have not been able to explain a causative role for nucleotide variation in its pathogenesis. The goal of the present study was to identify the gene expression profile and the cellular pathways altered in sarcoidosis monocytes via RNA-sequencing. Peripheral blood monocytes play a role in sarcoidosis inflammation. Therefore, we determined and compared the transcriptional signature of monocytes from peripheral blood from sarcoidosis patients and healthy controls via RNA-sequencing. We found 2,446 differentially expressed (DE) genes between sarcoidosis and healthy control monocytes. Analysis of these DE genes showed enrichment for ribosome, phagocytosis, lysosome, proteasome, oxidative phosphorylation and metabolic pathways. RNA-sequencing identified upregulation of genes involved in phagocytosis and lysosomal pathway in sarcoidosis monocytes, whereas genes involved in proteasome degradation and ribosomal pathways were downregulated. Further studies are needed to investigate the role of specific genes involved in the identified pathways and their possible interaction leading to sarcoidosis pathology.

High-throughput allele-specific expression across 250 environmental conditions

Gene-by-environment (GxE) interactions determine common disease risk factors and biomedically relevant complex traits. However, quantifying how the environment modulates genetic effects on human quantitative phenotypes presents unique challenges. Environmental covariates are complex and difficult to measure and control at the organismal level, as found in GWAS and epidemiological studies. An alternative approach focuses on the cellular environment using in vitro treatments as a proxy for the organismal environment. These cellular environments simplify the organism-level environmental exposures to provide a tractable influence on subcellular phenotypes, such as gene expression. Expression quantitative trait loci (eQTL) mapping studies identified GxE interactions in response to drug treatment and pathogen exposure. However, eQTL mapping approaches are infeasible for large-scale analysis of multiple cellular environments. Recently, allele-specific expression (ASE) analysis emerged as a powerful tool to identify GxE interactions in gene expression patterns by exploiting naturally occurring environmental exposures. Here we characterized genetic effects on the transcriptional response to 50 treatments in five cell types. We discovered 1455 genes with ASE (FDR < 10%) and 215 genes with GxE interactions. We demonstrated a major role for GxE interactions in complex traits. Genes with a transcriptional response to environmental perturbations showed sevenfold higher odds of being found in GWAS. Additionally, 105 genes that indicated GxE interactions (49%) were identified by GWAS as associated with complex traits. Examples include GIPR–caffeine interaction and obesity and include LAMP3–selenium interaction and Parkinson disease. Our results demonstrate that comprehensive catalogs of GxE interactions are indispensable to thoroughly annotate genes and bridge epidemiological and genome-wide association studies.

Genetic and transcriptional analysis of human host response to healthy gut microbiota

The study of host-microbiota interactions in humans is largely limited to identifying associations between microbial communities and host phenotypes. While these studies have generated important insights on the links between the microbiota and human disease, the assessment of cause-and-effect relationships has been challenging. Although this relationship can be studied in germfree mice, this system is costly, and it is difficult to accurately account for the effects of host genotypic variation and environmental effects seen in humans. Here, we have developed a novel approach to directly investigate the transcriptional changes induced by live microbial communities on human colonic epithelial cells and how these changes are modulated by host genotype. This method is easily scalable to large numbers of host genetic backgrounds and diverse microbiota and can be utilized to elucidate the mechanisms of host-microbiota interactions. Future extensions may also include colonic organoid cultures.

Many studies have demonstrated the importance of the gut microbiota in healthy and disease states. However, establishing the causality of host-microbiota interactions in humans is still challenging. Here, we describe a novel experimental system to define the transcriptional response induced by the microbiota for human cells and to shed light on the molecular mechanisms underlying host-gut microbiota interactions. In primary human colonic epithelial cells, we identified over 6,000 genes whose expression changed at various time points following coculturing with the gut microbiota of a healthy individual. Among the differentially expressed genes we found a 1.8-fold enrichment of genes associated with diseases that have been previously linked to the microbiome, such as obesity and colorectal cancer. In addition, our experimental system allowed us to identify 87 host single nucleotide polymorphisms (SNPs) that show allele-specific expression in 69 genes. Furthermore, for 12 SNPs in 12 different genes, allele-specific expression is conditional on the exposure to the microbiota. Of these 12 genes, 8 have been associated with diseases linked to the gut microbiota, specifically colorectal cancer, obesity, and type 2 diabetes. Our study demonstrates a scalable approach to study host-gut microbiota interactions and can be used to identify putative mechanisms for the interplay between host genetics and the microbiota in health and disease.

IMPORTANCE The study of host-microbiota interactions in humans is largely limited to identifying associations between microbial communities and host phenotypes. While these studies have generated important insights on the links between the microbiota and human disease, the assessment of cause-and-effect relationships has been challenging. Although this relationship can be studied in germfree mice, this system is costly, and it is difficult to accurately account for the effects of host genotypic variation and environmental effects seen in humans. Here, we have developed a novel approach to directly investigate the transcriptional changes induced by live microbial communities on human colonic epithelial cells and how these changes are modulated by host genotype. This method is easily scalable to large numbers of host genetic backgrounds and diverse microbiota and can be utilized to elucidate the mechanisms of host-microbiota interactions. Future extensions may also include colonic organoid cultures.

Integrated studies of organismal plasticity through physiological and transcriptomic approaches: examples from marine polar regions

Transcriptomic methods are now widely used in functional genomic research. The vast amount of information received from these studies comes along with the challenge of developing a precise picture of the functional consequences and the characteristic regulatory mechanisms. Here we assess recent studies in marine species and their adaptation to polar (and seasonal) cold and explore how they have been able to draw reliable conclusions from transcriptomic patterns on functional consequences in the organisms. Our analysis indicates that the interpretation of transcriptomic data suffers from insufficient understanding of the consequences for whole organism performance and fitness and comes with the risk of supporting only preliminary and superficial statements.We propose that the functional understanding of transcriptomic data may be improved by their tighter integration into overarching physiological concepts that support the more specific interpretation of the 'omics' data and, at the same time, can be developed further through embedding the transcriptomic phenomena observed. Such possibilities have not been fully exploited.In the context of thermal adaptation and limitation, we explore preliminary evidence that the concept of oxygen and capacity limited thermal tolerance (OCLTT) may provide sufficient complexity to guide the integration of such data and the development of associated functional hypotheses. At the same time, we identify a lack of methodological approaches linking genes and function to higher levels of integration, in terms of organism and ecosystem functioning, at temporal and geographical scales, to support more reliable conclusions and be predictive with respect to the effects of global changes.

Cofactor squelching: Artifact or fact?

Cofactor squelching is the term used to describe competition between transcription factors (TFs) for a limited amount of cofactors in a cell with the functional consequence that TFs in a given cell interfere with the activity of each other. Since cofactor squelching was proposed based primarily on reporter assays some 30 years ago, it has remained controversial, and the idea that it could be a physiologically relevant mechanism for transcriptional repression has not received much support. However, recent genome-wide studies have demonstrated that signal-dependent TFs are very often absent from the enhancers that are acutely repressed by those signals, which is consistent with an indirect mechanism of repression such as squelching. Here we review these recent studies in the light of the classical studies of cofactor squelching, and we discuss how TF cooperativity in so-called hotspots and super-enhancers may sensitize these to cofactor squelching.