A novel role for vaping in mitochondrial gene dysregulation and inflammation fundamental to disease development

AbstractWe constructed and analyzed the whole transcriptome in leukocytes of healthy adult vapers (with/without a history of smoking), ‘exclusive’ cigarette smokers, and controls (non-users of any tobacco products). Furthermore, we performed single-gene validation of expression data, and biochemical validation of vaping/smoking status by plasma cotinine measurement. Computational modeling, combining primary analysis (age- and sex-adjusted limmaVoom) and sensitivity analysis (cumulative e-liquid- and pack-year modeling), revealed that ‘current’ vaping, but not ‘past’ smoking, is significantly associated with gene dysregulation in vapers. Comparative analysis of the gene networks and canonical pathways dysregulated in vapers and smokers showed strikingly similar patterns in the two groups, although the extent of transcriptomic changes was more pronounced in smokers than vapers. Of significance is the preferential targeting of mitochondrial genes in both vapers and smokers, concurrent with impaired functional networks, which drive mitochondrial DNA-related disorders. Equally significant is the dysregulation of immune response genes in vapers and smokers, modulated by upstream cytokines, including members of the interleukin and interferon family, which play a crucial role in inflammation. Our findings accord with the growing evidence on the central role of mitochondria as signaling organelles involved in immunity and inflammatory response, which are fundamental to disease development.

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Cosegregation of Single Genes Associated with Fertility Restoration and Transcript Processing of Sorghum Mitochondrial orf107 and urf209

Genetics ◽

10.1093/genetics/150.1.383 ◽

1998 ◽

Vol 150 (1) ◽

pp. 383-391 ◽

Cited By ~ 1

Author(s):

Hoang V Tang ◽

Ruying Chang ◽

Daryl R Pring

Keyword(s):

Fertility Restoration ◽

Mitochondrial Gene ◽

Pollen Viability ◽

Single Gene ◽

Dominant Gene ◽

Nuclear Gene ◽

Male Sterile ◽

Reading Frame ◽

Transcript Processing ◽

Backcross Populations

Abstract Defective nuclear-cytoplasmic interactions leading to aberrant microgametogenesis in sorghum carrying the IS1112C male-sterile cytoplasm occur very late in pollen maturation. Amelioration of this condition, the restoration of pollen viability, involves a novel two-gene gametophytic system, wherein genes designated Rf3 and Rf4 are required for viability of individual gametes. Rf3 is tightly linked to, or represents, a single gene that regulates a transcript processing activity that cleaves transcriptsof orf107, a chimeric mitochondrial open reading frame specific to IS1112C. The mitochondrial gene urf 209 is also subject to nucleus-specific enhanced transcript processing, 5′ to the gene, conferred by a single dominant gene designated Mmt1. Examinations of transcript patterns in F2 and two backcross populations indicated cosegregation of the augmented orf107 and urf209 processing activities in IS1112C. Several sorghum lines that do not restore fertility or confer orf107 transcript processing do exhibit urf209 transcript processing, indicating that the activities are distinguishable. We conclude that the nuclear gene(s) conferring enhanced orf107 and urf209 processing activities are tightly linked in IS1112C. Alternatively, the similarity in apparent regulatory action of the genes may indicate allelic differences wherein the IS1112C Rf3 allele may differ from alleles of maintainer lines by the capability to regulate both orf107 and urf209 processing activities.

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Multigene Combined Detection by RT-qPCR Using Cytological Specimens

Acta Cytologica ◽

10.1159/000514821 ◽

2021 ◽

pp. 1-10

Author(s):

Yang Ma ◽

Jingxia Zhao ◽

Yun Du ◽

Rui Wang ◽

Xiaokun Ji ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Smoking Status ◽

Single Gene ◽

Rna Extraction ◽

Pcr Amplification ◽

Driver Mutations ◽

Amplification Refractory Mutation System ◽

Driver Genes ◽

Mutation Status ◽

Pik3ca Mutations

Objective: The aim of the study was to investigate the mutation status of multiple driver genes by RT-qPCR and their significance in advanced lung adenocarcinoma using cytological specimens. Materials and Methods: 155 cytological specimens that had been diagnosed with lung adenocarcinoma in the Fourth Hospital of Hebei Medical University were selected from April to November 2019. The cytological specimens included serous cavity effusion and fine-needle aspiration biopsies. Among cytological specimens, 108 cases were processed by using the cell block method (CBM), and 47 cases were processed by the disposable membrane cell collector method (MCM) before DNA/RNA extraction. Ten drive genes of EGFR, ALK, ROS1, BRAF, KRAS, NRAS, HER2, RET, PIK3CA, and MET were combined detected at one step by the amplification refractory mutation system and ABI 7500 RT-qPCR. Results: The purity of RNA (p = 0.005) and DNA (p = 0.001) extracted by using the MCM was both significantly higher than that extracted by using the CBM. Forty-seven cases of fresh cell specimens processed by the MCM all succeeded in multigene detections, while of 108 specimens processed by the CBM, 6 cases failed in multigene detections. Among 149 specimens, single-gene mutation rates of EGFR, ALK, ROS1, RET, HER2, MET, KRAS, NRAS, BRAF, and PIK3CA mutations were 57.71%, 6.04%, 3.36%, 2.68%, 2.01%, 2.01%, 1.34%, 0.67%, 0% and 0% respectively, and 6 cases including 2 coexistence mutations. We found that mutation status was correlated with gender (p = 0.047), but not correlated with age (p = 0.141) and smoking status (p = 0.083). We found that the EGFR mutation status was correlated with gender (p = 0.003), age (p = 0.015) and smoking habits (p = 0.007), and ALK mutation status was correlated with age (p = 0.002). Conclusion: Compared with the CBM, the MCM can improve the efficiency of DNA/RNA extraction and PCR amplification by removing impurities and enriching tumor cells. And we speculate that the successful detection rate of fresh cytological specimens was higher than that of paraffin-embedded specimens. EGFR, ALK, and ROS1 mutations were the main driver mutations in patients with advanced lung adenocarcinoma. We speculate that EGFR and ALK are more prone to concomitant mutations, respectively. Targeted therapies for patients with coexisting mutations need further study.

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Biochemical validation of smoking status: Pros, cons, and data from four low-intensity intervention trials

Addictive Behaviors ◽

10.1016/0306-4603(93)90068-k ◽

1993 ◽

Vol 18 (5) ◽

pp. 511-527 ◽

Cited By ~ 109

Author(s):

Russell E. Glasgow ◽

John P. Mullooly ◽

Thomas M. Vogt ◽

Victor J. Stevens ◽

Edward Lichtenstein ◽

...

Keyword(s):

Smoking Status ◽

Low Intensity ◽

Biochemical Validation ◽

Intervention Trials

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From population genetics to phylogeny: Uses and limits of mitochondrial DNA

Australian Systematic Botany ◽

10.1071/sb9900111 ◽

1990 ◽

Vol 3 (1) ◽

pp. 111 ◽

Cited By ~ 9

Author(s):

RH Crozier

Keyword(s):

Mitochondrial Dna ◽

Mitochondrial Gene ◽

Single Gene ◽

Dna Amplification ◽

Species Tree ◽

Population Subdivision ◽

Evolutionary Divergence ◽

Gene Trees ◽

Species Trees ◽

Effective Population

Mitochondrial DNA (mtDNA) is clonally and maternally inherited in all animals and in most plants. Mitochondrial gene content is similar although not identical in all eukaryotes. Because of these characteristics, mtDNA has a number of features useful to systematists for all levels of evolutionary divergence. Clonal inheritance leads to unusual confidence in constructing gene trees which are useful in population-level studies, such as in the detection of population subdivision. Maternal inheritance presents the opportunity to distinguish paternal from maternal gene flow. The clonal, or single-gene, nature of mtDNA inheritance leads to consideration of the expected convergence between gene- and species-trees. For closely related populations or species, it is desirable to use several genes to be sure that the correct species-tree is discovered; this means that, although mtDNA will be the most precise guide to the species tree because of its lower effective population size, nuclear genes should also be used in such studies. Although restriction fragment length polymorphisms dominated the field until recently, sequencing following DNA amplification using the polymerase chain reaction is now easier and opens up the use of preserved specimens to molecular systematists. Because mitochondria1 genes evolve at different rates, one of appropriate rate can be selected for almost any phylogenetic problem.

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The Molecular Phylogeny of the New Zealand Endemic Genus Hadramphus and the Revival of the Genus Karocolens

Diversity ◽

10.3390/d10030088 ◽

2018 ◽

Vol 10 (3) ◽

pp. 88

Author(s):

Emily Fountain ◽

Robert Cruickshank ◽

Adrian Paterson

Keyword(s):

New Zealand ◽

Gene Sequence ◽

Mitochondrial Gene ◽

Single Gene ◽

Morphological Characteristics ◽

Nuclear Gene ◽

Similar Species ◽

Morphological Similarity ◽

Coalescent Approach ◽

Systematic Relationships

The delineation of species is important to the fields of evolution, ecology and conservation. The use of only a single line of evidence, e.g., morphology or a single gene sequence, may underestimate or overestimate the level of diversity within a taxon. This problem often occurs when organisms are morphologically similar but genetically different, i.e., for cryptic species. The Hadramphus genus contains four endangered, morphologically similar species of weevils, each endemic to a specific New Zealand region (Hadramphus spinipennis Chatham Islands, H. stilbocarpae Fiordland, H. tuberculatus McKenzie Country, H. pittospori Poor Knights Islands). The systematic relationships among these species are unclear. We used samples from these species and a closely related genus, Lyperobius huttoni, to obtain data from the mitochondrial gene cytochrome c oxidase subunit I and the nuclear gene internal transcribe spacer 2. In addition to the multi-locus coalescent approach, we modelled morphological characteristics combined with the genetic data. We found that H. spinipennis, H. tuberculatus and H. stilbocarpae were a closely related clade. Despite a strong morphological similarity, Hadramphus pittospori was found to be genetically distinct from the other Hadramphus species, which supports the resurrection of the monotypic genus Karocolens for this species.

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ECMarker: interpretable machine learning model identifies gene expression biomarkers predicting clinical outcomes and reveals molecular mechanisms of human disease in early stages

Bioinformatics ◽

10.1093/bioinformatics/btaa935 ◽

2020 ◽

Author(s):

Ting Jin ◽

Nam D Nguyen ◽

Flaminia Talos ◽

Daifeng Wang

Keyword(s):

Gene Expression ◽

Machine Learning ◽

Lung Cancer ◽

Cancer Patients ◽

Human Disease ◽

Gene Networks ◽

Regulatory Mechanisms ◽

Disease Development ◽

Lung Cancer Patients ◽

Machine Learning Model

Abstract Motivation Gene expression and regulation, a key molecular mechanism driving human disease development, remains elusive, especially at early stages. Integrating the increasing amount of population-level genomic data and understanding gene regulatory mechanisms in disease development are still challenging. Machine learning has emerged to solve this, but many machine learning methods were typically limited to building an accurate prediction model as a ‘black box’, barely providing biological and clinical interpretability from the box. Results To address these challenges, we developed an interpretable and scalable machine learning model, ECMarker, to predict gene expression biomarkers for disease phenotypes and simultaneously reveal underlying regulatory mechanisms. Particularly, ECMarker is built on the integration of semi- and discriminative-restricted Boltzmann machines, a neural network model for classification allowing lateral connections at the input gene layer. This interpretable model is scalable without needing any prior feature selection and enables directly modeling and prioritizing genes and revealing potential gene networks (from lateral connections) for the phenotypes. With application to the gene expression data of non-small-cell lung cancer patients, we found that ECMarker not only achieved a relatively high accuracy for predicting cancer stages but also identified the biomarker genes and gene networks implying the regulatory mechanisms in the lung cancer development. In addition, ECMarker demonstrates clinical interpretability as its prioritized biomarker genes can predict survival rates of early lung cancer patients (P-value < 0.005). Finally, we identified a number of drugs currently in clinical use for late stages or other cancers with effects on these early lung cancer biomarkers, suggesting potential novel candidates on early cancer medicine. Availabilityand implementation ECMarker is open source as a general-purpose tool at https://github.com/daifengwanglab/ECMarker. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

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Estrogen related receptors (ERRs): A new dawn in transcriptional control of mitochondrial gene networks

Mitochondrion ◽

10.1016/j.mito.2011.03.121 ◽

2011 ◽

Vol 11 (4) ◽

pp. 544-552 ◽

Cited By ~ 93

Author(s):

Lillian J. Eichner ◽

Vincent Giguère

Keyword(s):

Gene Networks ◽

Transcriptional Control ◽

Mitochondrial Gene

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WheatNet: A genome-scale functional network for hexaploid bread wheat, Triticum aestivum

10.1101/105098 ◽

2017 ◽

Author(s):

Tak Lee ◽

Sohyun Hwang ◽

Chan Yeong Kim ◽

Hongseok Shim ◽

Hyojin Kim ◽

...

Keyword(s):

Complex Traits ◽

Gene Networks ◽

Unique Feature ◽

Single Gene ◽

Functional Network ◽

System Level ◽

Edge Information ◽

Integrated Network ◽

A Genome ◽

Genome Scale

Gene networks provide a system-level overview of genetic organizations and enable the dissection of functional modules underlying complex traits. Here we report the generation of WheatNet, the first genome-scale functional network for T. aestivum and a companion web server (www.inetbio.org/wheatnet). WheatNet was constructed by integrating 20 distinct genomics datasets, including 156,000 wheat-specific co-expression links mined from 1,929 microarray data. A unique feature of WheatNet is that each network node represents either a single gene or a group of genes. We computationally partitioned gene groups mimicking homeologous genes by clustering 99,386 wheat genes, resulting in 20,248 gene groups comprising 63,401 genes and 35,985 individual genes. Thus, WheatNet was constructed using 56,233 nodes, and the final integrated network has 20,230 nodes and 567,000 edges. The edge information of the integrated WheatNet and all 20 component networks are available for download.

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PieParty: visualizing cells from scRNA-seq data as pie charts

Life Science Alliance ◽

10.26508/lsa.202000986 ◽

2021 ◽

Vol 4 (5) ◽

pp. e202000986

Author(s):

Stefan Kurtenbach ◽

James J Dollar ◽

Anthony M Cruz ◽

Michael A Durante ◽

Christina L Decatur ◽

...

Keyword(s):

Gene Expression ◽

Gene Networks ◽

Single Gene ◽

Cell Types ◽

Three Dimensions ◽

Research Fields ◽

Reduction Techniques ◽

Single Cell Rna Sequencing ◽

Pie Chart ◽

Simultaneous Visualization

Single-cell RNA sequencing (scRNA-seq) has been a transformative technology in many research fields. Dimensional reduction techniques such as UMAP and tSNE are used to visualize scRNA-seq data in two or three dimensions for cells to be clustered in biologically meaningful ways. Subsequently, gene expression is frequently mapped onto these plots to show the distribution of gene expression across the plots, for instance to distinguish cell types. However, plotting each cell with only a single color leads to repetitive and unintuitive representations. Here, we present PieParty, which allows scRNA-seq data to be plotted such that every cell is represented as a pie chart, and every slice in the pie charts corresponds to the gene expression of a single gene. This allows for the simultaneous visualization of the expression of multiple genes and gene networks. The resulting figures are information dense, space efficient, and highly intuitive. PieParty is publicly available on GitHub at https://github.com/harbourlab/PieParty.

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satuRn: Scalable Analysis of differential Transcript Usage for bulk and single-cell RNA-sequencing applications

10.1101/2021.01.14.426636 ◽

2021 ◽

Author(s):

Jeroen Gilis ◽

Kristoffer Vitting-Seerup ◽

Koen Van den Berge ◽

Lieven Clement

Keyword(s):

Rate Control ◽

Single Gene ◽

Experimental Designs ◽

Rna Seq ◽

Modelling Framework ◽

Gene Dysregulation ◽

False Discovery ◽

Generalized Linear Modelling ◽

Linear Modelling ◽

Scalable Analysis

AbstractAlternative splicing produces multiple functional transcripts from a single gene. Dysregulation of splicing is known to be associated with disease and as a hallmark of cancer. Existing tools for differential transcript usage (DTU) analysis either lack in performance, cannot account for complex experimental designs or do not scale to massive scRNA-seq data. We introduce satuRn, a fast and flexible quasi-binomial generalized linear modelling framework that is on par with the best performing DTU methods from the bulk RNA-seq realm, while providing good false discovery rate control, addressing complex experimental designs and scaling to scRNA-seq applications.

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