Spatial clustering and common regulatory elements correlate with coordinated gene expression

Reveal the mechanism of hepatic oxidative stress in mice induced by photo-oxidation milk using multi-omics analysis techniques

INTRODUCTION

Photo-oxidation is recognized as a contributor to the deterioration of milk quality, posing potential safety hazards to human health. However, there has been limited investigation into the impact of consuming photo-oxidized milk on health.

OBJECTIVES

This study employs multi-omics analysis techniques to elucidate the mechanisms by which photo-oxidized milk induces oxidative stress in the liver.

METHODS

Mouse model was used to determine the effect of the gavage administration of milk with varying degrees of photo-oxidation on the mouse liver. The damage degree was established by measuring serum markers indicative of oxidative stress, and with a subsequent histopathological examination of liver tissues. In addition, comprehensive metabolome, lipidome, and transcriptome analyses were conducted to elucidate the underlying molecular mechanisms of hepatic damage caused by photo-oxidized milk.

RESULTS

A significant elevation in the oxidative stress levels and the presence of hepatocellular swelling and inflammation subsequent to the gavage administration of photo-oxidized milk to mice. Significant alterations in the levels of metabolites such as lumichrome, all-trans-retinal, L-valine, phosphatidylglycerol, and phosphatidylcholine within the hepatic tissue of mice. Moreover, photo-oxidized milk exerted a pronounced detrimental impact on the glycerophospholipid metabolism of mice liver. The peroxisome proliferator-activated receptors (PPAR) signaling pathway enrichment appreciated in the animals that consumed photo-oxidized milk further supports the substantial negative influence of photo-oxidized milk on hepatic lipid metabolism. Gene set enrichment and interaction analyses revealed that photo-oxidized milk inhibited the cytochrome P450 pathway in mice, while also affecting other pathways associated with cellular stress response and lipid biosynthesis.

CONCLUSION

This comprehensive study provides significant evidence regarding the potential health risks associated with photo-oxidized milk, particularly in terms of hepatic oxidative damage. It establishes a scientific foundation for assessing the safety of such milk and ensuring the quality of dairy products.

Comparative analyses of dynamic transcriptome profiles highlight key response genes and dominant isoforms for muscle development and growth in chicken

BACKGROUND

Modern breeding strategies have resulted in significant differences in muscle mass between indigenous chicken and specialized broiler. However, the molecular regulatory mechanisms that underlie these differences remain elusive. The aim of this study was to identify key genes and regulatory mechanisms underlying differences in breast muscle development between indigenous chicken and specialized broiler.

RESULTS

Two time-series RNA-sequencing profiles of breast muscles were generated from commercial Arbor Acres (AA) broiler (fast-growing) and Chinese indigenous Lushi blue-shelled-egg (LS) chicken (slow-growing) at embryonic days 10, 14, and 18, and post-hatching day 1 and weeks 1, 3, and 5. Principal component analysis of the transcriptome profiles showed that the top four principal components accounted for more than 80% of the total variance in each breed. The developmental axes between the AA and LS chicken overlapped at the embryonic stages but gradually separated at the adult stages. Integrative investigation of differentially-expressed transcripts contained in the top four principal components identified 44 genes that formed a molecular network associated with differences in breast muscle mass between the two breeds. In addition, alternative splicing analysis revealed that genes with multiple isoforms always had one dominant transcript that exhibited a significantly higher expression level than the others. Among the 44 genes, the TNFRSF6B gene, a mediator of signal transduction pathways and cell proliferation, harbored two alternative splicing isoforms, TNFRSF6B-X1 and TNFRSF6B-X2. TNFRSF6B-X1 was the dominant isoform in both breeds before the age of one week. A switching event of the dominant isoform occurred at one week of age, resulting in TNFRSF6B-X2 being the dominant isoform in AA broiler, whereas TNFRSF6B-X1 remained the dominant isoform in LS chicken. Gain-of-function assays demonstrated that both isoforms promoted the proliferation of chicken primary myoblasts, but only TNFRSF6B-X2 augmented the differentiation and intracellular protein content of chicken primary myoblasts.

CONCLUSIONS

For the first time, we identified several key genes and dominant isoforms that may be responsible for differences in muscle mass between slow-growing indigenous chicken and fast-growing commercial broiler. These findings provide new insights into the regulatory mechanisms underlying breast muscle development in chicken.

Polymer folding through active processes recreates features of genome organization

From proteins to chromosomes, polymers fold into specific conformations that control their biological function. Polymer folding has long been studied with equilibrium thermodynamics, yet intracellular organization and regulation involve energy-consuming, active processes. Signatures of activity have been measured in the context of chromatin motion, which shows spatial correlations and enhanced subdiffusion only in the presence of adenosine triphosphate. Moreover, chromatin motion varies with genomic coordinate, pointing toward a heterogeneous pattern of active processes along the sequence. How do such patterns of activity affect the conformation of a polymer such as chromatin? We address this question by combining analytical theory and simulations to study a polymer subjected to sequence-dependent correlated active forces. Our analysis shows that a local increase in activity (larger active forces) can cause the polymer backbone to bend and expand, while less active segments straighten out and condense. Our simulations further predict that modest activity differences can drive compartmentalization of the polymer consistent with the patterns observed in chromosome conformation capture experiments. Moreover, segments of the polymer that show correlated active (sub)diffusion attract each other through effective long-ranged harmonic interactions, whereas anticorrelations lead to effective repulsions. Thus, our theory offers nonequilibrium mechanisms for forming genomic compartments, which cannot be distinguished from affinity-based folding using structural data alone. As a first step toward exploring whether active mechanisms contribute to shaping genome conformations, we discuss a data-driven approach.

Temporal and regulatory dynamics of the inner ear transcriptome during development in mice

The inner ear controls hearing and balance, while the temporal molecular signatures and transcriptional regulatory dynamics underlying its development are still unclear. In this study, we investigated time-series transcriptome in the mouse inner ear from embryonic day 11.5 (E11.5) to postnatal day 7 (P7) using bulk RNA-Seq. A total of 10,822 differentially expressed genes were identified between pairwise stages. We identified nine significant temporal expression profiles using time-series expression analysis. The constantly down-regulated profiles throughout the development are related to DNA activity and neurosensory development, while the constantly upregulated profiles are related to collagen and extracellular matrix. Further co-expression network analysis revealed that several hub genes, such as Pnoc, Cd9, and Krt27, are related to the neurosensory development, cell adhesion, and keratinization. We uncovered three important transcription regulatory paths during mice inner ear development. Transcription factors related to Hippo/TGFβ signaling induced decreased expressions of genes related to the neurosensory and inner ear development, while a series of INF genes activated the expressions of genes in immunoregulation. In addition to deepening our understanding of the temporal and regulatory mechanisms of inner ear development, our transcriptomic data could fuel future multi-species comparative studies and elucidate the evolutionary trajectory of auditory development.

A global high-density chromatin interaction network reveals functional long-range and trans-chromosomal relationships

BACKGROUND

Chromatin contacts are essential for gene-expression regulation; however, obtaining a high-resolution genome-wide chromatin contact map is still prohibitively expensive owing to large genome sizes and the quadratic scale of pairwise data. Chromosome conformation capture (3C)-based methods such as Hi-C have been extensively used to obtain chromatin contacts. However, since the sparsity of these maps increases with an increase in genomic distance between contacts, long-range or trans-chromatin contacts are especially challenging to sample.

RESULTS

Here, we create a high-density reference genome-wide chromatin contact map using a meta-analytic approach. We integrate 3600 human, 6700 mouse, and 500 fly Hi-C experiments to create species-specific meta-Hi-C chromatin contact maps with 304 billion, 193 billion, and 19 billion contacts in respective species. We validate that meta-Hi-C contact maps are uniquely powered to capture functional chromatin contacts in both cis and trans. We find that while individual dataset Hi-C networks are largely unable to predict any long-range coexpression (median 0.54 AUC), meta-Hi-C networks perform comparably in both cis and trans (0.65 AUC vs 0.64 AUC). Similarly, for long-range expression quantitative trait loci (eQTL), meta-Hi-C contacts outperform all individual Hi-C experiments, providing an improvement over the conventionally used linear genomic distance-based association. Assessing between species, we find patterns of chromatin contact conservation in both cis and trans and strong associations with coexpression even in species for which Hi-C data is lacking.

CONCLUSIONS

We have generated an integrated chromatin interaction network which complements a large number of methodological and analytic approaches focused on improved specificity or interpretation. This high-depth "super-experiment" is surprisingly powerful in capturing long-range functional relationships of chromatin interactions, which are now able to predict coexpression, eQTLs, and cross-species relationships. The meta-Hi-C networks are available at https://labshare.cshl.edu/shares/gillislab/resource/HiC/ .

Deciphering multi-way interactions in the human genome

Chromatin architecture, a key regulator of gene expression, can be inferred using chromatin contact data from chromosome conformation capture, or Hi-C. However, classical Hi-C does not preserve multi-way contacts. Here we use long sequencing reads to map genome-wide multi-way contacts and investigate higher order chromatin organization in the human genome. We use hypergraph theory for data representation and analysis, and quantify higher order structures in neonatal fibroblasts, biopsied adult fibroblasts, and B lymphocytes. By integrating multi-way contacts with chromatin accessibility, gene expression, and transcription factor binding, we introduce a data-driven method to identify cell type-specific transcription clusters. We provide transcription factor-mediated functional building blocks for cell identity that serve as a global signature for cell types.

Mapping higher order chromatin architecture is important. Here the authors use long sequencing reads to map genome-wide multi-way contacts and investigate higher order chromatin organisation; they use hypergraph theory for data representation and analysis, and apply this to different cell types.

Annotating regulatory elements by heterogeneous network embedding

MOTIVATION

Regulatory elements (REs), such as enhancers and promoters, are known as regulatory sequences functional in a heterogeneous regulatory network to control gene expression by recruiting transcription regulators and carrying genetic variants in a context specific way. Annotating those REs relies on costly and labor-intensive next-generation sequencing and RNA-guided editing technologies in many cellular contexts.

RESULTS

We propose a systematic Gene Ontology Annotation method for Regulatory Elements (RE-GOA) by leveraging the powerful word embedding in natural language processing. We first assemble a heterogeneous network by integrating context specific regulations, protein-protein interactions and gene ontology (GO) terms. Then we perform network embedding and associate regulatory elements with GO terms by assessing their similarity in a low dimensional vector space. With three applications, we show that RE-GOA outperforms existing methods in annotating TFs' binding sites from ChIP-seq data, in functional enrichment analysis of differentially accessible peaks from ATAC-seq data, and in revealing genetic correlation among phenotypes from their GWAS summary statistics data.

AVAILABILITY AND IMPLEMENTATION

The source code and the systematic RE annotation for human and mouse are available at https://github.com/AMSSwanglab/RE-GOA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Epithelial-to-mesenchymal transition proceeds through directional destabilization of multidimensional attractor

How a cell changes from one stable phenotype to another one is a fundamental problem in developmental and cell biology. Mathematically, a stable phenotype corresponds to a stable attractor in a generally multi-dimensional state space, which needs to be destabilized so the cell relaxes to a new attractor. Two basic mechanisms for destabilizing a stable fixed point, pitchfork and saddle-node bifurcations, have been extensively studied theoretically; however, direct experimental investigation at the single-cell level remains scarce. Here, we performed live cell imaging studies and analyses in the framework of dynamical systems theories on epithelial-to-mesenchymal transition (EMT). While some mechanistic details remain controversial, EMT is a cell phenotypic transition (CPT) process central to development and pathology. Through time-lapse imaging we recorded single cell trajectories of human A549/Vim-RFP cells undergoing EMT induced by different concentrations of exogenous TGF-β in a multi-dimensional cell feature space. The trajectories clustered into two distinct groups, indicating that the transition dynamics proceeds through parallel paths. We then reconstructed the reaction coordinates and the corresponding quasi-potentials from the trajectories. The potentials revealed a plausible mechanism for the emergence of the two paths where the original stable epithelial attractor collides with two saddle points sequentially with increased TGF-β concentration, and relaxes to a new one. Functionally, the directional saddle-node bifurcation ensures a CPT proceeds towards a specific cell type, as a mechanistic realization of the canalization idea proposed by Waddington.

Cells with the same genetic code can take on many different formss, or phenotypes, which have distinct roles and appearances. Sometimes cells switch from one phenotype to another as part of healthy growth or during disease. One such change is the epithelial-to-mesenchymal transition (EMT), which is involved in fetal development, wound healing and the spread of cancer cells.

During EMT, closely connected epithelial cells detach from one another and change into mesenchymal cells that are able to migrate. Cells undergo a number of changes during this transition; however, the path they take to reach their new form is not entirely clear. For instance, do all cells follow the same route, or are there multiple ways that cells can shift from one state to the next?

To address this question, Wang et al. studied individual lung cancer cells that had been treated with a protein that drives EMT. The cells were then imaged at regular intervals over the course of two to three days to see how they changed in response to different concentrations of protein. Using a mathematical analysis designed to study chemical reactions, Wang et al. showed that the cells transform into the mesenchymal phenotype through two main routes.

This result suggests that attempts to prevent EMT, in cancer treatment for instance, would require blocking both paths taken by the cells. This information could be useful for biomedical researchers trying to regulate the EMT process. The quantitative approach of this study could also help physicists and mathematicians study other types of transition that occur in biology.

The chemical defensome of five model teleost fish

How an organism copes with chemicals is largely determined by the genes and proteins that collectively function to defend against, detoxify and eliminate chemical stressors. This integrative network includes receptors and transcription factors, biotransformation enzymes, transporters, antioxidants, and metal- and heat-responsive genes, and is collectively known as the chemical defensome. Teleost fish is the largest group of vertebrate species and can provide valuable insights into the evolution and functional diversity of defensome genes. We have previously shown that the xenosensing pregnane x receptor (pxr, nr1i2) is lost in many teleost species, including Atlantic cod (Gadus morhua) and three-spined stickleback (Gasterosteus aculeatus), but it is not known if compensatory mechanisms or signaling pathways have evolved in its absence. In this study, we compared the genes comprising the chemical defensome of five fish species that span the teleosteii evolutionary branch often used as model species in toxicological studies and environmental monitoring programs: zebrafish (Danio rerio), medaka (Oryzias latipes), Atlantic killifish (Fundulus heteroclitus), Atlantic cod, and three-spined stickleback. Genome mining revealed evolved differences in the number and composition of defensome genes that can have implication for how these species sense and respond to environmental pollutants, but we did not observe any candidates of compensatory mechanisms or pathways in cod and stickleback in the absence of pxr. The results indicate that knowledge regarding the diversity and function of the defensome will be important for toxicological testing and risk assessment studies.

Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data

Recent advances in single-cell techniques catalyze an emerging field of studying how cells convert from one phenotype to another, in a step-by-step process. Two grand technical challenges, however, impede further development of the field. Fixed cell-based approaches can provide snapshots of high-dimensional expression profiles but have fundamental limits on revealing temporal information, and fluorescence-based live-cell imaging approaches provide temporal information but are technically challenging for multiplex long-term imaging. We first developed a live-cell imaging platform that tracks cellular status change through combining endogenous fluorescent labeling that minimizes perturbation to cell physiology and/or live-cell imaging of high-dimensional cell morphological and texture features. With our platform and an A549 VIM-RFP epithelial-to-mesenchymal transition (EMT) reporter cell line, live-cell trajectories reveal parallel paths of EMT missing from snapshot data due to cell-cell dynamic heterogeneity. Our results emphasize the necessity of extracting dynamical information of phenotypic transitions from multiplex live-cell imaging.

Cell Fate Forecasting: A Data-Assimilation Approach to Predict Epithelial-Mesenchymal Transition

Epithelial-mesenchymal transition (EMT) is a fundamental biological process that plays a central role in embryonic development, tissue regeneration, and cancer metastasis. Transforming growth factor-β (TGFβ) is a potent inducer of this cellular transition, which is composed of transitions from an epithelial state to intermediate or partial EMT state(s) to a mesenchymal state. Using computational models to predict cell state transitions in a specific experiment is inherently difficult for reasons including model parameter uncertainty and error associated with experimental observations. In this study, we demonstrate that a data-assimilation approach using an ensemble Kalman filter, which combines limited noisy observations with predictions from a computational model of TGFβ-induced EMT, can reconstruct the cell state and predict the timing of state transitions. We used our approach in proof-of-concept “synthetic” in silico experiments, in which experimental observations were produced from a known computational model with the addition of noise. We mimic parameter uncertainty in in vitro experiments by incorporating model error that shifts the TGFβ doses associated with the state transitions and reproduces experimentally observed variability in cell state by either shifting a single parameter or generating “populations” of model parameters. We performed synthetic experiments for a wide range of TGFβ doses, investigating different cell steady-state conditions, and conducted parameter studies varying properties of the data-assimilation approach including the time interval between observations and incorporating multiplicative inflation, a technique to compensate for underestimation of the model uncertainty and mitigate the influence of model error. We find that cell state can be successfully reconstructed and the future cell state predicted in synthetic experiments, even in the setting of model error, when experimental observations are performed at a sufficiently short time interval and incorporate multiplicative inflation. Our study demonstrates the feasibility and utility of a data-assimilation approach to forecasting the fate of cells undergoing EMT.

Functional characterization of an inducible bidirectional promoter from Fusarium oxysporum f. sp. cubense

Bidirectional promoters (BDPs) are regulatory DNA sequences (~1000 bp long) intervening two genes arranged on opposite strands with their 5' ends in close proximity. These genes are mostly co-expressed; but, instances of anti-correlation and independent transcription have been observed. In fungal systems, BDPs have shown to provide an improved genetic circuit by assembling and regulating transcription of different genes of a common metabolic pathway. We have identified an intergenic region (1063 bp) from the genome of Fusarium oxysporum f. sp. cubense (Foc), a banana root pathogen. This intergenic region regulates the expression of a gene pair required for the breakdown of hemicellulose. For characterization, it was cloned into pCSN44 vector backbone between two reporter genes, namely β-glucuronidase (GUS) and enhanced green fluorescent protein (EGFP). The newly formed vector was transformed into Foc and tested for its bidirectional expression activity. Using histochemical staining and fluorescence microscopy, the kinetics for both, GUS and EGFP expression were tested under different growth conditions respectively. The activity was differentially regulated by inducers such as xylan, arabinogalactan and pectin. This is the first report on the isolation of the intergenic region with inducible bidirectional promoter activity from Fusarium. Characterization of such BDPs will find applications in genetic engineering, metabolic engineering and synthetic biology using fungal systems.

Comprehensive analysis of PM20D1 QTL in Alzheimer's disease

Background

Alzheimer’s disease (AD) is a complex disorder caused by a combination of genetic and non-genetic risk factors. In addition, an increasing evidence suggests that epigenetic mechanisms also accompany AD. Genetic and epigenetic factors are not independent, but multiple loci show genetic-epigenetic interactions, the so-called quantitative trait loci (QTLs). Recently, we identified the first QTL association with AD, namely Peptidase M20 Domain Containing 1 (PM20D1). We observed that PM20D1 DNA methylation, RNA expression, and genetic background are correlated and, in turn, associated with AD. We provided mechanistic insights for these correlations and had shown that by genetically increasing and decreasing PM20D1 levels, AD-related pathologies were decreased and accelerated, respectively. However, since the PM20D1 QTL region encompasses also other genes, namely Nuclear Casein Kinase and Cyclin Dependent Kinase Substrate 1 (NUCKS1); RAB7, member RAS oncogene family-like 1 (RAB7L1); and Solute Carrier Family 41 Member 1 (SLC41A1), we investigated whether these genes might also contribute to the described AD association.

Results

Here, we report a comprehensive analysis of these QTL genes using a repertoire of in silico methods as well as in vivo and in vitro experimental approaches. First, we analyzed publicly available databases to pinpoint the major QTL correlations. Then, we validated these correlations using a well-characterized set of samples and locus-specific approaches—i.e., Sanger sequencing for the genotype, cloning/sequencing and pyrosequencing for the DNA methylation, and allele-specific and real-time PCR for the RNA expression. Finally, we defined the functional relevance of the observed alterations in the context of AD in vitro. Using this approach, we show that only PM20D1 DNA methylation and expression are significantly correlated with the AD-risk associated background. We find that the expression of SLC41A1 and PM20D1—but not NUCKS1 and RAB7L1—is increased in mouse models and human samples of AD, respectively. However, SLC41A1 and PM20D1 are differentially regulated by AD-related stressors, with only PM20D1 being upregulated by amyloid-β and reactive oxygen species, and with only PM20D1 being neuroprotective when overexpressed in cell and primary cultures.

Conclusions

Our findings reinforce PM20D1 as the most likely gene responsible of the previously reported PM20D1 QTL association with AD.

Integrative Transcriptomic Analysis Reveals a Multiphasic Epithelial-Mesenchymal Spectrum in Cancer and Non-tumorigenic Cells

Epithelial-mesenchymal transition (EMT), the conversion between rigid epithelial cells and motile mesenchymal cells, is a reversible cellular process involved in tumorigenesis, metastasis, and chemoresistance. Numerous studies have found that several types of tumor cells show a high degree of cell-to-cell heterogeneity in terms of their gene expression signatures and cellular phenotypes related to EMT. Recently, the prevalence and importance of partial or intermediate EMT states have been reported. It is unclear, however, whether there is a general pattern of cancer cell distribution in terms of the overall expression of epithelial-related genes and mesenchymal-related genes, and how this distribution is related to EMT process in normal cells. In this study, we performed integrative transcriptomic analysis that combines cancer cell transcriptomes, time course data of EMT in non-tumorigenic epithelial cells, and epithelial cells with perturbations of key EMT factors. Our statistical analysis shows that cancer cells are widely distributed in the EMT spectrum, and the majority of these cells can be described by an EMT path that connects the epithelial and the mesenchymal states via a hybrid expression region in which both epithelial genes and mesenchymal genes are highly expressed overall. We found that key patterns of this EMT path are observed in EMT progression in non-tumorigenic cells and that transcription factor ZEB1 plays a key role in defining this EMT path via diverse gene regulatory circuits connecting to epithelial genes. We performed Gene Set Variation Analysis to show that the cancer cells at hybrid EMT states also possess hybrid cellular phenotypes with both high migratory and high proliferative potentials. Our results reveal critical patterns of cancer cells in the EMT spectrum and their relationship to the EMT process in normal cells, and provide insights into the mechanistic basis of cancer cell heterogeneity and plasticity.

MOCHI enables discovery of heterogeneous interactome modules in 3D nucleome

The composition of the cell nucleus is highly heterogeneous, with different constituents forming complex interactomes. However, the global patterns of these interwoven heterogeneous interactomes remain poorly understood. Here we focus on two different interactomes, chromatin interaction network and gene regulatory network, as a proof of principle to identify heterogeneous interactome modules (HIMs), each of which represents a cluster of gene loci that is in spatial contact more frequently than expected and that is regulated by the same group of transcription factors. HIM integrates transcription factor binding and 3D genome structure to reflect “transcriptional niche” in the nucleus. We develop a new algorithm, MOCHI, to facilitate the discovery of HIMs based on network motif clustering in heterogeneous interactomes. By applying MOCHI to five different cell types, we found that HIMs have strong spatial preference within the nucleus and show distinct functional properties. Through integrative analysis, this work shows the utility of MOCHI to identify HIMs, which may provide new perspectives on the interplay between transcriptional regulation and 3D genome organization.

Multi-tissue transcriptome analyses identify genetic mechanisms underlying neuropsychiatric traits

The genetic architecture of psychiatric disorders is characterized by a large number of small-effect variants1 located primarily in non-coding regions, suggesting that the underlying causal effects may influence disease risk by modulating gene expression2-4. We provide comprehensive analyses using transcriptome data from an unprecedented collection of tissues to gain pathophysiological insights into the role of the brain, neuroendocrine factors (adrenal gland) and gastrointestinal systems (colon) in psychiatric disorders. In each tissue, we perform PrediXcan analysis and identify trait-associated genes for schizophrenia (n associations = 499; n unique genes = 275), bipolar disorder (n associations = 17; n unique genes = 13), attention deficit hyperactivity disorder (n associations = 19; n unique genes = 12) and broad depression (n associations = 41; n unique genes = 31). Importantly, both PrediXcan and summary-data-based Mendelian randomization/heterogeneity in dependent instruments analyses suggest potentially causal genes in non-brain tissues, showing the utility of these tissues for mapping psychiatric disease genetic predisposition. Our analyses further highlight the importance of joint tissue approaches as 76% of the genes were detected only in difficult-to-acquire tissues.