scholarly journals Gene regulatory effects of a large chromosomal inversion in highland maize

2019 ◽  
Author(s):  
Taylor Crow ◽  
James Ta ◽  
Saghi Nojoomi ◽  
M. Rocío Aguilar-Rangel ◽  
Jorge Vladimir Torres Rodríguez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Zea Mays ◽  
Large Scale ◽  
Chromosomal Inversion ◽  
Experimental Conditions ◽  
Chromosomal Inversions ◽  
Functional Variants ◽  
Original Manuscript ◽  
Locally Adaptive ◽  
Highland Maize

AbstractChromosomal inversions play an important role in local adaptation. Inversions can capture multiple locally adaptive functional variants in a linked block by repressing recombination. However, this recombination suppression makes it difficult to identify the genetic mechanisms that underlie an inversion’s role in adaption. In this study, we explore how large-scale transcriptomic data can be used to dissect the functional importance of a 13 Mb inversion locus (Inv4m) found almost exclusively in highland populations of maize (Zea mays ssp. mays). Inv4m introgressed into highland maize from the wild relative Zea mays ssp. mexicana, also present in the highlands of Mexico, and is thought to be important for the adaptation of these populations to cultivation in highland environments. First, using a large publicly available association mapping panel, we confirmed that Inv4m is associated with locally adaptive agronomic phenotypes, but only in highland fields. Second, we created two families segregating for standard and inverted haplotypess of Inv4m in a isogenic B73 background, and measured gene expression variation association with Inv4m across 9 tissues in two experimental conditions. With these data, we quantified both the global transcriptomic effects of the highland Inv4m haplotype, and the local cis-regulatory variation present within the locus. We found diverse physiological effects of Inv4m, and speculate that the genetic basis of its effects on adaptive traits is distributed across many separate functional variants.Author SummaryChromosomal inversions are an important type of genomic structural variant. However, mapping causal alleles within their boundaries is difficult because inversions suppress recombination between homologous chromosomes. This means that inversions, regardless of their size, are inherited as a unit. We leveraged the high-dimensional phenotype of gene expression as a tool to study the genetics of a large chromosomal inversion found in highland maize populations in Mexico - Inv4m. We grew plants carrying multiple versions of Inv4m in a common genetic background, and quantified the transcriptional reprogramming induced by alternative alleles at the locus. Inv4m has been shown in previous studies to have a large effect on flowering, but we show that the functional variation within Inv4m affects many developmental and physiological processes.Author ContributionsT. Crow, R. Rellan-Alvarez, R. Sawers and D. Runcie conceived and designed the experiment. M. Aguilar-Rangel, J. Rodrǵuez, R. Rellan-Alvarez and R. Sawers generated the segregating families. T. Crow, J. Ta, S. Nojoomi, M. Aguilar-Rangel, J. Rodrǵuez D. Gates, D. Runcie performed the experiment. T. Crow, D. Gates, D. Runcie analyzed the data. T. Crow, D. Runcie wrote the original manuscript, and R. Rellan-Alvarez and R. Sawers provided review and editing.

scholarly journals Gene regulatory effects of a large chromosomal inversion in highland maize

PLoS Genetics ◽  
2020 ◽  
Vol 16 (12) ◽  
pp. e1009213
Author(s):  
Taylor Crow ◽  
James Ta ◽  
Saghi Nojoomi ◽  
M. Rocío Aguilar-Rangel ◽  
Jorge Vladimir Torres Rodríguez ◽  
...  
Keyword(s):  
Zea Mays ◽  
Large Scale ◽  
Future Research ◽  
Recombination Suppression ◽  
Experimental Conditions ◽  
Functional Variants ◽  
Expression Of Genes ◽  
Highland Maize ◽  
Genetic Mechanisms ◽  
Regulatory Effects

Chromosomal inversions play an important role in local adaptation. Inversions can capture multiple locally adaptive functional variants in a linked block by repressing recombination. However, this recombination suppression makes it difficult to identify the genetic mechanisms underlying an inversion’s role in adaptation. In this study, we used large-scale transcriptomic data to dissect the functional importance of a 13 Mb inversion locus (Inv4m) found almost exclusively in highland populations of maize (Zea mays ssp. mays). Inv4m was introgressed into highland maize from the wild relative Zea mays ssp. mexicana, also present in the highlands of Mexico, and is thought to be important for the adaptation of these populations to cultivation in highland environments. However, the specific genetic variants and traits that underlie this adaptation are not known. We created two families segregating for the standard and inverted haplotypes of Inv4m in a common genetic background and measured gene expression effects associated with the inversion across 9 tissues in two experimental conditions. With these data, we quantified both the global transcriptomic effects of the highland Inv4m haplotype, and the local cis-regulatory variation present within the locus. We found diverse physiological effects of Inv4m across the 9 tissues, including a strong effect on the expression of genes involved in photosynthesis and chloroplast physiology. Although we could not confidently identify the causal alleles within Inv4m, this research accelerates progress towards understanding this inversion and will guide future research on these important genomic features.

scholarly journals Open TG-GATEs: a large-scale toxicogenomics database

2014 ◽  
Vol 43 (D1) ◽  
pp. D921-D927 ◽  
Author(s):  
Yoshinobu Igarashi ◽  
Noriyuki Nakatsu ◽  
Tomoya Yamashita ◽  
Atsushi Ono ◽  
Yasuo Ohno ◽  
...  
Keyword(s):  
Gene Expression ◽  
Drug Safety ◽  
Evaluation System ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Comprehensive Overview ◽  
Experimental Conditions ◽  
The Public ◽  
Target Organs

Abstract Toxicogenomics focuses on assessing the safety of compounds using gene expression profiles. Gene expression signatures from large toxicogenomics databases are expected to perform better than small databases in identifying biomarkers for the prediction and evaluation of drug safety based on a compound's toxicological mechanisms in animal target organs. Over the past 10 years, the Japanese Toxicogenomics Project consortium (TGP) has been developing a large-scale toxicogenomics database consisting of data from 170 compounds (mostly drugs) with the aim of improving and enhancing drug safety assessment. Most of the data generated by the project (e.g. gene expression, pathology, lot number) are freely available to the public via Open TG-GATEs (Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System). Here, we provide a comprehensive overview of the database, including both gene expression data and metadata, with a description of experimental conditions and procedures used to generate the database. Open TG-GATEs is available from https://toxico.nibiohn.go.jp/english/index.html.

scholarly journals Gene Expression Data Mining Reveals the Involvement of GPR55 and Its Endogenous Ligands in Immune Response, Cancer, and Differentiation

2021 ◽  
Vol 22 (24) ◽  
pp. 13328
Author(s):  
Artur Wnorowski ◽  
Jakub Wójcik ◽  
Maciej Maj
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Immune Cell ◽  
Cell Lineage ◽  
Expression Data ◽  
Experimental Conditions ◽  
Pathological Conditions ◽  
Pituitary Adenylate Cyclase ◽  
G Protein Coupled

G protein-coupled receptor 55 (GPR55) is a recently deorphanized lipid- and peptide-sensing receptor. Its lipidic endogenous agonists belong to lysoglycerophospholipids, with lysophosphatidylinositol (LPI) being the most studied. Peptide agonists derive from fragmentation of pituitary adenylate cyclase-activating polypeptide (PACAP). Although GPR55 and its ligands were implicated in several physiological and pathological conditions, their biological function remains unclear. Thus, the aim of the study was to conduct a large-scale re-analysis of publicly available gene expression datasets to identify physiological and pathological conditions affecting the expression of GPR55 and the production of its ligands. The study revealed that regulation of GPR55 occurs predominantly in the context of immune activation pointing towards the role of the receptor in response to pathogens and in immune cell lineage determination. Additionally, it was revealed that there is almost no overlap between the experimental conditions affecting the expression of GPR55 and those modulating agonist production. The capacity to synthesize LPI was enhanced in various types of tumors, indicating that cancer cells can hijack the motility-related activity of GPR55 to increase aggressiveness. Conditions favoring accumulation of PACAP-derived peptides were different than those for LPI and were mainly related to differentiation. This indicates a different function of the two agonist classes and possibly the existence of a signaling bias.

scholarly journals Local genetic effects on gene expression across 44 human tissues

2016 ◽  
Author(s):  
François Aguet ◽  
Andrew A. Brown ◽  
Stephane E. Castel ◽  
Joe R. Davis ◽  
Pejman Mohammadi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Large Scale ◽  
Genetic Diseases ◽  
Tissue Expression ◽  
Specific Expression ◽  
Tissue Specific ◽  
Regulatory Variation ◽  
Functional Variants ◽  
Trait Locus

AbstractExpression quantitative trait locus (eQTL) mapping provides a powerful means to identify functional variants influencing gene expression and disease pathogenesis. We report the identification of cis-eQTLs from 7,051 post-mortem samples representing 44 tissues and 449 individuals as part of the Genotype-Tissue Expression (GTEx) project. We find a cis-eQTL for 88% of all annotated protein-coding genes, with one-third having multiple independent effects. We identify numerous tissue-specific cis-eQTLs, highlighting the unique functional impact of regulatory variation in diverse tissues. By integrating large-scale functional genomics data and state-of-the-art fine-mapping algorithms, we identify multiple features predictive of tissue-specific and shared regulatory effects. We improve estimates of cis-eQTL sharing and effect sizes using allele specific expression across tissues. Finally, we demonstrate the utility of this large compendium of cis-eQTLs for understanding the tissue-specific etiology of complex traits, including coronary artery disease. The GTEx project provides an exceptional resource that has improved our understanding of gene regulation across tissues and the role of regulatory variation in human genetic diseases.

scholarly journals reComBat: Batch effect removal in large-scale, multi-source omics data integration

2021 ◽  
Author(s):  
Michael F. Adamer ◽  
Sarah C. Brueningk ◽  
Alejandro Tejada-Arranz ◽  
Fabienne Estermann ◽  
Marek Basler ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Integration ◽  
Empirical Bayes ◽  
Large Scale ◽  
Batch Effect ◽  
Data Driven ◽  
Design Matrix ◽  
Omics Data ◽  
Experimental Conditions ◽  
Batch Correction

With the steadily increasing abundance of omics data produced all over the world, sometimes decades apart and under vastly different experimental conditions residing in public databases, a crucial step in many data-driven bioinformatics applications is that of data integration. The challenge of batch effect removal for entire databases lies in the large number and coincide of both batches and desired, biological variation resulting in design matrix singularity. This problem currently cannot be solved by any common batch correction algorithm. In this study, we present reComBat, a regularised version of the empirical Bayes method to overcome this limitation. We demonstrate our approach for the harmonisation of public gene expression data of the human opportunistic pathogen Pseudomonas aeruginosa and study a several metrics to empirically demonstrate that batch effects are successfully mitigated while biologically meaningful gene expression variation is retained. reComBat fills the gap in batch correction approaches applicable to large scale, public omics databases and opens up new avenues for data driven analysis of complex biological processes beyond the scope of a single study.

scholarly journals Computational Assessment of the Regulation-Modulating Potential for Noncoding Variants

2019 ◽  
Author(s):  
Fang-Yuan Shi ◽  
Yu Wang ◽  
Dong Huang ◽  
Yu Liang ◽  
Nan Liang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Genetic Diseases ◽  
Superior Performance ◽  
Massive Datasets ◽  
Functional Variants ◽  
False Discovery ◽  
Genome Wide ◽  
Causal Variants ◽  
Higher Sensitivity

AbstractLarge-scale genome-wide association and expression quantitative trait loci studies have identified multiple noncoding variants associated with genetic diseases via affecting gene expression. However, effectively and efficiently pinpointing causal variants remains a serious challenge. Here, we developed CARMEN, a novel algorithm to identify functional noncoding expression-modulating variants. Multiple evaluations demonstrated CARMEN’s superior performance over state-of-the-art tools. Its higher sensitivity and low false discovery rate enable CARMEN to identify multiple causal expression-modulating variants that other tools simply missed. Meanwhile, benefitting from extensive annotations generated, CARMEN provides mechanism hints on predicted expression-modulating variants, enabling effectively characterizing functional variants involved in gene expression and disease-related phenotypes. CARMEN scales well with the massive datasets and is available online as a Web server at http://carmen.gao-lab.org.

Molecular Epidemiology and Biomarkers in Etiologic Cancer Research: The New in Light of the Old

2020 ◽  
Author(s):  
Lungwani Muungo
Keyword(s):  
Gene Expression ◽  
Cancer Research ◽  
Molecular Epidemiology ◽  
Exposure Assessment ◽  
Large Scale ◽  
First Generation ◽  
Cancer Epidemiology ◽  
Policy Changes ◽  
The Past ◽  
New Generation

The purpose of this review is to evaluate progress inmolecular epidemiology over the past 24 years in canceretiology and prevention to draw lessons for futureresearch incorporating the new generation of biomarkers.Molecular epidemiology was introduced inthe study of cancer in the early 1980s, with theexpectation that it would help overcome some majorlimitations of epidemiology and facilitate cancerprevention. The expectation was that biomarkerswould improve exposure assessment, document earlychanges preceding disease, and identify subgroupsin the population with greater susceptibility to cancer,thereby increasing the ability of epidemiologic studiesto identify causes and elucidate mechanisms incarcinogenesis. The first generation of biomarkers hasindeed contributed to our understanding of riskandsusceptibility related largely to genotoxic carcinogens.Consequently, interventions and policy changes havebeen mounted to reduce riskfrom several importantenvironmental carcinogens. Several new and promisingbiomarkers are now becoming available for epidemiologicstudies, thanks to the development of highthroughputtechnologies and theoretical advances inbiology. These include toxicogenomics, alterations ingene methylation and gene expression, proteomics, andmetabonomics, which allow large-scale studies, includingdiscovery-oriented as well as hypothesis-testinginvestigations. However, most of these newer biomarkershave not been adequately validated, and theirrole in the causal paradigm is not clear. There is a needfor their systematic validation using principles andcriteria established over the past several decades inmolecular cancer epidemiology.

scholarly journals Assessment of common housekeeping genes as reference for gene expression studies using RT-qPCR in mouse choroid plexus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kim Hoa Ho ◽  
Annarita Patrizi
Keyword(s):  
Gene Expression ◽  
Choroid Plexus ◽  
Sensory Deprivation ◽  
Housekeeping Genes ◽  
Housekeeping Gene ◽  
Experimental Conditions ◽  
Brain Repair ◽  
Expression Studies ◽  
Testing Algorithms ◽  
Gene Expression Studies

AbstractChoroid plexus (ChP), a vascularized secretory epithelium located in all brain ventricles, plays critical roles in development, homeostasis and brain repair. Reverse transcription quantitative real-time PCR (RT-qPCR) is a popular and useful technique for measuring gene expression changes and also widely used in ChP studies. However, the reliability of RT-qPCR data is strongly dependent on the choice of reference genes, which are supposed to be stable across all samples. In this study, we validated the expression of 12 well established housekeeping genes in ChP in 2 independent experimental paradigms by using popular stability testing algorithms: BestKeeper, DeltaCq, geNorm and NormFinder. Rer1 and Rpl13a were identified as the most stable genes throughout mouse ChP development, while Hprt1 and Rpl27 were the most stable genes across conditions in a mouse sensory deprivation experiment. In addition, Rpl13a, Rpl27 and Tbp were mutually among the top five most stable genes in both experiments. Normalisation of Ttr and Otx2 expression levels using different housekeeping gene combinations demonstrated the profound effect of reference gene choice on target gene expression. Our study emphasized the importance of validating and selecting stable housekeeping genes under specific experimental conditions.

scholarly journals The combined detection of Amphiregulin, Cyclin A1 and DDX20/Gemin3 expression predicts aggressive forms of oral squamous cell carcinoma

2021 ◽  
Author(s):  
Ekaterina Bourova-Flin ◽  
Samira Derakhshan ◽  
Afsaneh Goudarzi ◽  
Tao Wang ◽  
Anne-Laure Vitte ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell ◽  
Large Scale ◽  
Biomarker Discovery ◽  
Gene Expression Signature ◽  
Predictive Biomarkers ◽  
Specific Gene ◽  
Specific Expression ◽  
Intrinsic Nature ◽  
Independent Cohort

Abstract Background Large-scale genetic and epigenetic deregulations enable cancer cells to ectopically activate tissue-specific expression programmes. A specifically designed strategy was applied to oral squamous cell carcinomas (OSCC) in order to detect ectopic gene activations and develop a prognostic stratification test. Methods A dedicated original prognosis biomarker discovery approach was implemented using genome-wide transcriptomic data of OSCC, including training and validation cohorts. Abnormal expressions of silent genes were systematically detected, correlated with survival probabilities and evaluated as predictive biomarkers. The resulting stratification test was confirmed in an independent cohort using immunohistochemistry. Results A specific gene expression signature, including a combination of three genes, AREG, CCNA1 and DDX20, was found associated with high-risk OSCC in univariate and multivariate analyses. It was translated into an immunohistochemistry-based test, which successfully stratified patients of our own independent cohort. Discussion The exploration of the whole gene expression profile characterising aggressive OSCC tumours highlights their enhanced proliferative and poorly differentiated intrinsic nature. Experimental targeting of CCNA1 in OSCC cells is associated with a shift of transcriptomic signature towards the less aggressive form of OSCC, suggesting that CCNA1 could be a good target for therapeutic approaches.

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