Systematic identification of ACE2 expression modulators reveals cardiomyopathy as a risk factor for mortality in COVID-19 patients

Abstract Background Angiotensin-converting enzyme 2 (ACE2) is the cell-entry receptor for SARS-CoV-2. It plays critical roles in both the transmission and the pathogenesis of COVID-19. Comprehensive profiling of ACE2 expression patterns could reveal risk factors of severe COVID-19 illness. While the expression of ACE2 in healthy human tissues has been well characterized, it is not known which diseases and drugs might be associated with ACE2 expression. Results We develop GENEVA (GENe Expression Variance Analysis), a semi-automated framework for exploring massive amounts of RNA-seq datasets. We apply GENEVA to 286,650 publicly available RNA-seq samples to identify any previously studied experimental conditions that could be directly or indirectly associated with ACE2 expression. We identify multiple drugs, genetic perturbations, and diseases that are associated with the expression of ACE2, including cardiomyopathy, HNF1A overexpression, and drug treatments with RAD140 and itraconazole. Our joint analysis of seven datasets confirms ACE2 upregulation in all cardiomyopathy categories. Using electronic health records data from 3936 COVID-19 patients, we demonstrate that patients with pre-existing cardiomyopathy have an increased mortality risk than age-matched patients with other cardiovascular conditions. GENEVA is applicable to any genes of interest and is freely accessible at http://genevatool.org. Conclusions This study identifies multiple diseases and drugs that are associated with the expression of ACE2. The effect of these conditions should be carefully studied in COVID-19 patients. In particular, our analysis identifies cardiomyopathy patients as a high-risk group, with increased ACE2 expression in the heart and increased mortality after SARS-COV-2 infection.

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Mining transcriptomics and clinical data reveals ACE2 expression modulators and identifies cardiomyopathy as a risk factor for mortality in COVID-19 patients

10.1101/2020.10.20.20216150 ◽

2020 ◽

Author(s):

Navchetan Kaur ◽

Boris Oskotsky ◽

Atul J. Butte ◽

Zicheng Hu

Keyword(s):

Meta Analysis ◽

Expression Patterns ◽

Rna Seq ◽

Experimental Conditions ◽

Healthy Human ◽

Angiotensin Converting Enzyme 2 ◽

Genetic Perturbations ◽

Drug Treatments ◽

Multiple Drugs ◽

Entry Receptor

AbstractAngiotensin-converting enzyme 2 (ACE2) is the cell-entry receptor for SARS-CoV-2. It plays critical roles in both the transmission and the pathogenesis of the coronavirus disease 2019 (COVID-19). Comprehensive profiling of ACE2 expression patterns will help researchers to reveal risk factors of severe COVID-19 illness. While the expression of ACE2 in healthy human tissues has been well characterized, it is not known which diseases and drugs might modulate the ACE2 expression. In this study, we developed GENEVA (GENe Expression Variance Analysis), a semi-automated framework for exploring massive amounts of RNA-seq datasets. We applied GENEVA to 28,6650 publicly available RNA-seq samples to identify any previously studied experimental conditions that could directly or indirectly modulate ACE2 expression. We identified multiple drugs, genetic perturbations, and diseases that modulate the expression of ACE2, including cardiomyopathy, HNF1A overexpression, and drug treatments with RAD140 and Itraconazole. Our unbiased meta-analysis of seven datasets confirms ACE2 up-regulation in all cardiomyopathy categories. Using electronic health records data from 3936 COVID19 patients, we demonstrate that patients with pre-existing cardiomyopathy have an increased mortality risk than age-matched patients with other cardiovascular conditions. GENEVA is applicable to any genes of interest and is freely accessible at http://genevatool.org.

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Integration of transcriptomic data identifies key hallmark genes in hypertrophic cardiomyopathy

BMC Cardiovascular Disorders ◽

10.1186/s12872-021-02147-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jing Xu ◽

Xiangdong Liu ◽

Qiming Dai

Keyword(s):

Machine Learning ◽

Hypertrophic Cardiomyopathy ◽

Heart Diseases ◽

Expression Patterns ◽

Support Vector ◽

Rna Seq ◽

Ppi Network ◽

Learning Methods ◽

Transcriptomic Data ◽

Machine Learning Methods

Abstract Background Hypertrophic cardiomyopathy (HCM) represents one of the most common inherited heart diseases. To identify key molecules involved in the development of HCM, gene expression patterns of the heart tissue samples in HCM patients from multiple microarray and RNA-seq platforms were investigated. Methods The significant genes were obtained through the intersection of two gene sets, corresponding to the identified differentially expressed genes (DEGs) within the microarray data and within the RNA-Seq data. Those genes were further ranked using minimum-Redundancy Maximum-Relevance feature selection algorithm. Moreover, the genes were assessed by three different machine learning methods for classification, including support vector machines, random forest and k-Nearest Neighbor. Results Outstanding results were achieved by taking exclusively the top eight genes of the ranking into consideration. Since the eight genes were identified as candidate HCM hallmark genes, the interactions between them and known HCM disease genes were explored through the protein–protein interaction (PPI) network. Most candidate HCM hallmark genes were found to have direct or indirect interactions with known HCM diseases genes in the PPI network, particularly the hub genes JAK2 and GADD45A. Conclusions This study highlights the transcriptomic data integration, in combination with machine learning methods, in providing insight into the key hallmark genes in the genetic etiology of HCM.

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Clustering Single-Cell RNA-Seq Data with Regularized Gaussian Graphical Model

Genes ◽

10.3390/genes12020311 ◽

2021 ◽

Vol 12 (2) ◽

pp. 311

Author(s):

Zhenqiu Liu

Keyword(s):

Single Cell ◽

Free Parameter ◽

Graphical Model ◽

Expression Patterns ◽

Information Criterion ◽

Log P ◽

Rna Seq ◽

Clustering Methods ◽

Wide Range ◽

Free Parameters

Single-cell RNA-seq (scRNA-seq) is a powerful tool to measure the expression patterns of individual cells and discover heterogeneity and functional diversity among cell populations. Due to variability, it is challenging to analyze such data efficiently. Many clustering methods have been developed using at least one free parameter. Different choices for free parameters may lead to substantially different visualizations and clusters. Tuning free parameters is also time consuming. Thus there is need for a simple, robust, and efficient clustering method. In this paper, we propose a new regularized Gaussian graphical clustering (RGGC) method for scRNA-seq data. RGGC is based on high-order (partial) correlations and subspace learning, and is robust over a wide-range of a regularized parameter λ. Therefore, we can simply set λ=2 or λ=log(p) for AIC (Akaike information criterion) or BIC (Bayesian information criterion) without cross-validation. Cell subpopulations are discovered by the Louvain community detection algorithm that determines the number of clusters automatically. There is no free parameter to be tuned with RGGC. When evaluated with simulated and benchmark scRNA-seq data sets against widely used methods, RGGC is computationally efficient and one of the top performers. It can detect inter-sample cell heterogeneity, when applied to glioblastoma scRNA-seq data.

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Transcriptome Analysis Reveals HgCl2 Induces Apoptotic Cell Death in Human Lung Carcinoma H1299 Cells through Caspase-3-Independent Pathway

International Journal of Molecular Sciences ◽

10.3390/ijms22042006 ◽

2021 ◽

Vol 22 (4) ◽

pp. 2006

Author(s):

Mi Jin Kim ◽

Jinhong Park ◽

Jinho Kim ◽

Ji-Young Kim ◽

Mi-Jin An ◽

...

Keyword(s):

Cell Cycle ◽

Cell Death ◽

Transcriptome Analysis ◽

Caspase 3 ◽

Apoptotic Cell ◽

Expression Patterns ◽

Nitrogen Compound ◽

Apoptotic Cell Death ◽

Mercury Chloride ◽

Rna Seq

Mercury is one of the detrimental toxicants that can be found in the environment and exists naturally in different forms; inorganic and organic. Human exposure to inorganic mercury, such as mercury chloride, occurs through air pollution, absorption of food or water, and personal care products. This study aimed to investigate the effect of HgCl2 on cell viability, cell cycle, apoptotic pathway, and alters of the transcriptome profiles in human non-small cell lung cancer cells, H1299. Our data show that HgCl2 treatment causes inhibition of cell growth via cell cycle arrest at G0/G1- and S-phase. In addition, HgCl2 induces apoptotic cell death through the caspase-3-independent pathway. Comprehensive transcriptome analysis using RNA-seq indicated that cellular nitrogen compound metabolic process, cellular metabolism, and translation for biological processes-related gene sets were significantly up- and downregulated by HgCl2 treatment. Interestingly, comparative gene expression patterns by RNA-seq indicated that mitochondrial ribosomal proteins were markedly altered by low-dose of HgCl2 treatment. Altogether, these data show that HgCl2 induces apoptotic cell death through the dysfunction of mitochondria.

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Identification and Expression Analysis of the Genes Involved in the Raffinose Family Oligosaccharides Pathway of Phaseolus vulgaris and Glycine max

Plants ◽

10.3390/plants10071465 ◽

2021 ◽

Vol 10 (7) ◽

pp. 1465

Author(s):

Ramon de Koning ◽

Raphaël Kiekens ◽

Mary Esther Muyoka Toili ◽

Geert Angenon

Keyword(s):

Common Bean ◽

Seed Development ◽

Expression Analysis ◽

De Novo ◽

Expression Patterns ◽

Gene Families ◽

Rna Seq ◽

Raffinose Family Oligosaccharides ◽

Specific Expression ◽

Raffinose Synthase

Raffinose family oligosaccharides (RFO) play an important role in plants but are also considered to be antinutritional factors. A profound understanding of the galactinol and RFO biosynthetic gene families and the expression patterns of the individual genes is a prerequisite for the sustainable reduction of the RFO content in the seeds, without compromising normal plant development and functioning. In this paper, an overview of the annotation and genetic structure of all galactinol- and RFO biosynthesis genes is given for soybean and common bean. In common bean, three galactinol synthase genes, two raffinose synthase genes and one stachyose synthase gene were identified for the first time. To discover the expression patterns of these genes in different tissues, two expression atlases have been created through re-analysis of publicly available RNA-seq data. De novo expression analysis through an RNA-seq study during seed development of three varieties of common bean gave more insight into the expression patterns of these genes during the seed development. The results of the expression analysis suggest that different classes of galactinol- and RFO synthase genes have tissue-specific expression patterns in soybean and common bean. With the obtained knowledge, important galactinol- and RFO synthase genes that specifically play a key role in the accumulation of RFOs in the seeds are identified. These candidate genes may play a pivotal role in reducing the RFO content in the seeds of important legumes which could improve the nutritional quality of these beans and would solve the discomforts associated with their consumption.

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Overexpression of a methyl-CpG-binding protein gene OsMBD707 leads to larger tiller angles and reduced photoperiod sensitivity in rice

BMC Plant Biology ◽

10.1186/s12870-021-02880-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Mengyu Qu ◽

Zhujian Zhang ◽

Tingmin Liang ◽

Peipei Niu ◽

Mingji Wu ◽

...

Keyword(s):

Expression Patterns ◽

Photoperiod Sensitivity ◽

Rna Seq ◽

Active Expression ◽

Binding Protein Gene ◽

Flowering Regulator ◽

Regulator Genes ◽

Mbd Protein ◽

Delayed Flowering ◽

Mbd Proteins

Abstract Background Methyl-CpG-binding domain (MBD) proteins play important roles in epigenetic gene regulation, and have diverse molecular, cellular, and biological functions in plants. MBD proteins have been functionally characterized in various plant species, including Arabidopsis, wheat, maize, and tomato. In rice, 17 sequences were bioinformatically predicted as putative MBD proteins. However, very little is known regarding the function of MBD proteins in rice. Results We explored the expression patterns of the rice OsMBD family genes and identified 13 OsMBDs with active expression in various rice tissues. We further characterized the function of a rice class I MBD protein OsMBD707, and demonstrated that OsMBD707 is constitutively expressed and localized in the nucleus. Transgenic rice overexpressing OsMBD707 displayed larger tiller angles and reduced photoperiod sensitivity—delayed flowering under short day (SD) and early flowering under long day (LD). RNA-seq analysis revealed that overexpression of OsMBD707 led to reduced photoperiod sensitivity in rice and to expression changes in flowering regulator genes in the Ehd1-Hd3a/RFT1 pathway. Conclusion The results of this study suggested that OsMBD707 plays important roles in rice growth and development, and should lead to further studies on the functions of OsMBD proteins in growth, development, or other molecular, cellular, and biological processes in rice.

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Annotation of snoRNA abundance across human tissues reveals complex snoRNA-host gene relationships

Genome Biology ◽

10.1186/s13059-021-02391-2 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Étienne Fafard-Couture ◽

Danny Bergeron ◽

Sonia Couture ◽

Sherif Abou-Elela ◽

Michelle S. Scott

Keyword(s):

Housekeeping Genes ◽

Host Gene ◽

Rna Modification ◽

Human Tissues ◽

Rna Seq ◽

Healthy Human ◽

Protein Coding ◽

Conservation Level ◽

Nucleolar Rnas ◽

Host Genes

Abstract Background Small nucleolar RNAs (snoRNAs) are mid-size non-coding RNAs required for ribosomal RNA modification, implying a ubiquitous tissue distribution linked to ribosome synthesis. However, increasing numbers of studies identify extra-ribosomal roles of snoRNAs in modulating gene expression, suggesting more complex snoRNA abundance patterns. Therefore, there is a great need for mapping the snoRNome in different human tissues as the blueprint for snoRNA functions. Results We used a low structure bias RNA-Seq approach to accurately quantify snoRNAs and compare them to the entire transcriptome in seven healthy human tissues (breast, ovary, prostate, testis, skeletal muscle, liver, and brain). We identify 475 expressed snoRNAs categorized in two abundance classes that differ significantly in their function, conservation level, and correlation with their host gene: 390 snoRNAs are uniformly expressed and 85 are enriched in the brain or reproductive tissues. Most tissue-enriched snoRNAs are embedded in lncRNAs and display strong correlation of abundance with them, whereas uniformly expressed snoRNAs are mostly embedded in protein-coding host genes and are mainly non- or anticorrelated with them. Fifty-nine percent of the non-correlated or anticorrelated protein-coding host gene/snoRNA pairs feature dual-initiation promoters, compared to only 16% of the correlated non-coding host gene/snoRNA pairs. Conclusions Our results demonstrate that snoRNAs are not a single homogeneous group of housekeeping genes but include highly regulated tissue-enriched RNAs. Indeed, our work indicates that the architecture of snoRNA host genes varies to uncouple the host and snoRNA expressions in order to meet the different snoRNA abundance levels and functional needs of human tissues.

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Combined Metabolome and Transcriptome Profiling Reveal Optimal Harvest Strategy Model Based on Different Production Purposes in Olive

Foods ◽

10.3390/foods10020360 ◽

2021 ◽

Vol 10 (2) ◽

pp. 360

Author(s):

Guodong Rao ◽

Jianguo Zhang ◽

Xiaoxia Liu ◽

Xue Li ◽

Chenhe Wang

Keyword(s):

Gene Expression ◽

Olive Oil ◽

Expression Patterns ◽

Transcriptome Profiling ◽

Minor Components ◽

Harvest Time ◽

Rna Seq ◽

Optimal Harvest ◽

Harvest Strategy ◽

Different Color

Olive oil has been favored as high-quality edible oil because it contains balanced fatty acids (FAs) and high levels of minor components. The contents of FAs and minor components are variable in olive fruits of different color at harvest time, which render it difficult to determine the optimal harvest strategy for olive oil producing. Here, we combined metabolome, Pacbio Iso-seq, and Illumina RNA-seq transcriptome to investigate the association between metabolites and gene expression of olive fruits at harvest time. A total of 34 FAs, 12 minor components, and 181 other metabolites (including organic acids, polyols, amino acids, and sugars) were identified in this study. Moreover, we proposed optimal olive harvesting strategy models based on different production purposes. In addition, we used the combined Pacbio Iso-seq and Illumina RNA-seq gene expression data to identify genes related to the biosynthetic pathways of hydroxytyrosol and oleuropein. These data lay the foundation for future investigations of olive fruit metabolism and gene expression patterns, and provide a method to obtain olive harvesting strategies for different production purposes.

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De novo gonad transcriptome analysis of the common littoral shrimp Palaemon serratus: novel insights into sex-related genes

BMC Genomics ◽

10.1186/s12864-019-6157-4 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 3

Author(s):

Inés González-Castellano ◽

Chiara Manfrin ◽

Alberto Pallavicini ◽

Andrés Martínez-Lage

Keyword(s):

Transcriptome Analysis ◽

De Novo ◽

Expression Patterns ◽

Gonadal Development ◽

Differentially Expressed ◽

Rna Seq ◽

Illumina Hiseq ◽

Specific Expression ◽

Development Processes ◽

The Common

Abstract Background The common littoral shrimp Palaemon serratus is an economically important decapod resource in some European communities. Aquaculture practices prevent the genetic deterioration of wild stocks caused by overfishing and at the same time enhance the production. The biotechnological manipulation of sex-related genes has the proved potential to improve the aquaculture production but the scarcity of genomic data about P. serratus hinders these applications. RNA-Seq analysis has been performed on ovary and testis samples to generate a reference gonadal transcriptome. Differential expression analyses were conducted between three ovary and three testis samples sequenced by Illumina HiSeq 4000 PE100 to reveal sex-related genes with sex-biased or sex-specific expression patterns. Results A total of 224.5 and 281.1 million paired-end reads were produced from ovary and testis samples, respectively. De novo assembly of ovary and testis trimmed reads yielded a transcriptome with 39,186 transcripts. The 29.57% of the transcriptome retrieved at least one annotation and 11,087 differentially expressed genes (DEGs) were detected between ovary and testis replicates. Six thousand two hundred seven genes were up-regulated in ovaries meanwhile 4880 genes were up-regulated in testes. Candidate genes to be involved in sexual development and gonadal development processes were retrieved from the transcriptome. These sex-related genes were discussed taking into account whether they were up-regulated in ovary, up-regulated in testis or not differentially expressed between gonads and in the framework of previous findings in other crustacean species. Conclusions This is the first transcriptome analysis of P. serratus gonads using RNA-Seq technology. Interesting findings about sex-related genes from an evolutionary perspective (such as Dmrt1) and for putative future aquaculture applications (Iag or vitellogenesis genes) are reported here. We provide a valuable dataset that will facilitate further research into the reproductive biology of this shrimp.

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Oogenesis and lipid metabolism in the deep-sea sponge Phakellia ventilabrum: an histological, lipidomic and transcriptomic approach

10.21203/rs.3.rs-608731/v1 ◽

2021 ◽

Author(s):

Vasiliki Koutsouveli ◽

David Balgoma ◽

Antonia Checa ◽

Mikael Hedeland ◽

Ana Riesgo ◽

...

Keyword(s):

Fatty Acid ◽

Lipid Metabolism ◽

Deep Sea ◽

Expression Patterns ◽

Rna Seq ◽

Beta Oxidation ◽

Animal Reproduction ◽

Physiological Processes ◽

Key Species ◽

Fatty Acid Beta Oxidation

Abstract Background Sponges contain an astounding diversity of lipids which serve in several biological functions, including yolk formation in their oocytes and the embryos. On animal reproduction, lipids constitute one of the main energy storage forms for the adult and the offspring. The study of lipid metabolism during reproduction can provide information on food-web dynamics and energetic needs of the populations in their habitats, however, there are no studies focusing on the lipid metabolism of sponges during seasonal reproduction. The deep-sea sponge Phakellia ventilabrum (Demospongiae, Bubarida) is a key species of North-Atlantic sponge grounds, but its reproductive biology is not known. In this study, we used histological sections, lipidome profiling (UHPLC-MS), and transcriptomic analysis (RNA-seq) with goal to i. assess the reproductive strategy and seasonality of this species, ii. examine the relative changes in the lipidome signal, and the gene expression patterns (RNA-seq) of enzymes participating in lipid metabolism in female specimens during gametogenesis.Results P. ventilabrum is an oviparous and most certainly gonochoristic species, reproducing in May and September in the different studied areas. Half of specimens were reproducing, generating two to five oocytes per mm2. Oocytes accumulated both protein and lipid droplets. As oogenesis progressed, the signal of most of the unsaturated and monounsaturated triacylglycerides increased, as well as of few other phospholipids. Most of the other lipids and especially those with > 3 unsaturations showed a decrease in signal during the oocyte maturation. In parallel, we detected upregulated genes in female tissues related to triacylglyceride biosynthesis and others related to fatty acid beta-oxidation.Conclusions Triacylglycerides are probably the main type of lipid forming the yolk since this lipid category has the most marked changes, while some other phospholipids may also have a role in oogenesis. In parallel, other lipid categories were oxidized, leading to fatty acid beta-oxidation to cover the energy requirements of female individuals during oogenesis. Variations in the signal of most lipids between the different locations and months suggest that sponges, apart from their own mechanisms of lipid biosynthesis, exploit the food availability in their surroundings to cover the energetic demands in their physiological processes.

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