scholarly journals An integrated approach to identify environmental modulators of genetic risk factors for complex traits

2021 ◽  
Author(s):  
Brunilda Balliu ◽  
Ivan Carcamo -Orive ◽  
Michael J. Gloudemans ◽  
Daniel C. Nachun ◽  
Matthew G. Durrant ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Complex Traits ◽  
Metabolic Regulation ◽  
Large Scale ◽  
Integrated Approach ◽  
Multiple Traits ◽  
Transcriptional Responses ◽  
Environmentally Responsive ◽  
Transcriptional Changes ◽  
Scale Characterization

AbstractComplex traits and diseases can be influenced by both genetics and environment. However, given the large number of environmental stimuli and power challenges for gene-by-environment testing, it remains a critical challenge to identify and prioritize specific disease-relevant environmental exposures. We propose a novel framework for leveraging signals from transcriptional responses to environmental perturbations to identify disease-relevant perturbations that can modulate genetic risk for complex traits and inform the functions of genetic variants associated with complex traits. We perturbed human skeletal muscle, fat, and liver relevant cell lines with 21 perturbations affecting insulin resistance, glucose homeostasis, and metabolic regulation in humans and identified thousands of environmentally responsive genes. By combining these data with GWAS from 31 distinct polygenic traits, we show that heritability of multiple traits is enriched in regions surrounding genes responsive to specific perturbations and, further, that environmentally responsive genes are enriched for associations with specific diseases and phenotypes from the GWAS catalogue. Overall, we demonstrate the advantages of large-scale characterization of transcriptional changes in diversely stimulated and pathologically relevant cells to identify disease-relevant perturbations.

scholarly journals Phenome-wide Heritability Analysis of the UK Biobank

2016 ◽  
Author(s):  
Tian Ge ◽  
Chia-Yen Chen ◽  
Benjamin M. Neale ◽  
Mert R. Sabuncu ◽  
Jordan W. Smoller
Keyword(s):  
Complex Traits ◽  
Large Scale ◽  
Prediction Models ◽  
Population Characteristics ◽  
Uk Biobank ◽  
Multiple Traits ◽  
Common Genetic Variants ◽  
Heritability Estimation ◽  
Heritability Analysis ◽  
The Uk

Heritability estimation provides important information about the relative contribution of genetic and environmental factors to phenotypic variation, and provides an upper bound for the utility of genetic risk prediction models. Recent technological and statistical advances have enabled the estimation of additive heritability attributable to common genetic variants (SNP heritability) across a broad phenotypic spectrum. However, assessing the comparative heritability of multiple traits estimated in different cohorts may be misleading due to the population-specific nature of heritability. Here we report the SNP heritability for 551 complex traits derived from the large-scale, population-based UK Biobank, comprising both quantitative phenotypes and disease codes, and examine the moderating effect of three major demographic variables (age, sex and socioeconomic status) on the heritability estimates. Our study represents the first comprehensive phenome-wide heritability analysis in the UK Biobank, and underscores the importance of considering population characteristics in comparing and interpreting heritability.

Seasonally hibernating phenotype assessed through transcript screening

2006 ◽  
Vol 24 (1) ◽  
pp. 13-22 ◽  
Author(s):  
Daryl R. Williams ◽  
L. Elaine Epperson ◽  
Weizhong Li ◽  
Margaret A. Hughes ◽  
Ruth Taylor ◽  
...  
Keyword(s):  
Large Scale ◽  
Cardiac Tissue ◽  
Rna Binding ◽  
Transcriptional Responses ◽  
Spermophilus Lateralis ◽  
Cellular Processes ◽  
New Genes ◽  
Molecular Events ◽  
Unbiased Gene ◽  
Transcriptional Changes

Hibernation is a seasonally entrained and profound phenotypic transition to conserve energy in winter. It involves significant biochemical reprogramming, although our understanding of the underpinning molecular events is fragmentary and selective. We have conducted a large-scale gene expression screen of the golden-mantled ground squirrel, Spermophilus lateralis, to identify transcriptional responses associated specifically with the summer-winter transition and the torpid-arousal transition in winter. We used 112 cDNA microarrays comprising 12,288 probes that cover at least 5,109 genes. In liver, the profiles of torpid and active states in the winter were almost identical, although we identified 102 cDNAs that were differentially expressed between winter and summer, 90% of which were downregulated in the winter states. By contrast, in cardiac tissue, 59 and 115 cDNAs were elevated in interbout arousal and torpor, respectively, relative to the summer active condition, but only 7 were common to both winter states, and during arousal none was downregulated. In brain, 78 cDNAs were found to change in winter, 44 of which were upregulated. Thus transcriptional changes associated with hibernation are qualitatively modest and, since these changes are generally less than twofold, also quantitatively modest. Unbiased Gene Ontology profiling of the transcripts suggests a winter switch to β-oxidation of lipids in liver and heart, a reduction in metabolism of toxic compounds and the urea cycle in liver, and downregulated electron transport in the brain. We identified just one strongly winter-induced transcript common to all tissues, namely an RNA-binding protein, RBM3. This analysis clearly differentiates responses of the principal tissues, identifies a large number of new genes undergoing regulation, and broadens our understanding of affected cellular processes that, in part, account for the winter-adaptive hibernating phenotype.

scholarly journals Metatranscriptomic Analysis of the Response of River Biofilms to Pharmaceutical Products, Using Anonymous DNA Microarrays

2010 ◽  
Vol 76 (16) ◽  
pp. 5432-5439 ◽  
Author(s):  
Etienne Yergeau ◽  
John R. Lawrence ◽  
Marley J. Waiser ◽  
Darren R. Korber ◽  
Charles W. Greer
Keyword(s):  
Large Scale ◽  
Dna Microarrays ◽  
Domestic Wastewater ◽  
Microarray Platform ◽  
Pharmaceutical Products ◽  
Ecosystem Dynamics ◽  
Transcriptional Responses ◽  
Domestic Wastewater Treatment ◽  
Low Concentrations ◽  
Transcriptional Changes

ABSTRACT Pharmaceutical products are released at low concentrations into aquatic environments following domestic wastewater treatment. Such low concentrations have been shown to induce transcriptional responses in microorganisms, which could have consequences on aquatic ecosystem dynamics. In order to test if these transcriptional responses could also be observed in complex river microbial communities, biofilm reactors were inoculated with water from two rivers of differing trophic statuses and subsequently treated with environmentally relevant doses (ng/liter to μg/liter range) of four pharmaceuticals (erythromycin [ER], gemfibrozil [GM], sulfamethazine [SN], and sulfamethoxazole [SL]). To monitor functional gene expression, we constructed a 9,600-feature anonymous DNA microarray platform onto which cDNA from the biofilms was hybridized. Pharmaceutical treatments induced both positive and negative transcriptional responses from biofilm microorganisms. For instance, ER induced the transcription of several stress, transcription, and replication genes, while GM, a lipid regulator, induced transcriptional responses from several genes involved in lipid metabolism. SN caused shifts in genes involved in energy production and conversion, and SL induced responses from a range of cell membrane and outer envelope genes, which in turn could affect biofilm formation. The results presented here demonstrate for the first time that low concentrations of small molecules can induce transcriptional changes in a complex microbial community. The relevance of these results also demonstrates the usefulness of anonymous DNA microarrays for large-scale metatranscriptomic studies of communities from differing aquatic ecosystems.

scholarly journals Sex-specific transcriptional responses of the zebrafish (Danio rerio) brain selenoproteome to acute sodium selenite supplementation

2013 ◽  
Vol 45 (15) ◽  
pp. 653-666 ◽  
Author(s):  
Maia J. Benner ◽  
Matt L. Settles ◽  
Gordon K. Murdoch ◽  
Ronald W. Hardy ◽  
Barrie D. Robison
Keyword(s):  
Danio Rerio ◽  
Sodium Selenite ◽  
Large Scale ◽  
Transcriptional Response ◽  
Nutritional Intervention ◽  
Transcriptional Responses ◽  
Qrt Pcr ◽  
Short Period ◽  
Transcriptional Changes ◽  
The Brain

The potential benefits of selenium (Se) supplementation are currently under investigation for prevention of certain cancers and treatment of neurological disorders. However, little is known concerning the response of the brain to increased dietary Se under conditions of Se sufficiency, despite the majority of Se supplementation trials occurring in healthy, Se sufficient subjects. We evaluated the transcriptional response of Se-dependent genes, selenoproteins and the genes necessary for their synthesis (the selenoproteome), in the zebrafish ( Danio rerio) brain to supplementation with nutritionally relevant levels of dietary Se (sodium selenite) during conditions of assumed Se sufficiency. We first used a microarray approach to analyze the response of the brain selenoproteome to dietary Se supplementation for 14 days and then assessed the immediacy and time-scale transcriptional response of the brain selenoproteome to 1, 7, and 14 days of Se supplementation by quantitative real-time PCR (qRT-PCR). The microarray approach did not indicate large-scale influences of Se on the brain transcriptome as a whole or the selenoproteome specifically; only one nonselenoproteome gene (si:ch73-44m9.2) was significantly differentially expressed. Our qRT-PCR results, however, indicate that increases of dietary Se cause small, but significant transcriptional changes within the brain selenoproteome, even after only 1 day of supplementation. These responses were dynamic over a short period of supplementation in a manner highly dependent on sex and the duration of Se supplementation. In nutritional intervention studies, it may be necessary to utilize methods such as qRT-PCR, which allow larger sample sizes, for detecting subtle transcriptional changes in the brain.

scholarly journals An integrated approach to identify environmental modulators of genetic risk factors for complex traits

2021 ◽  
Author(s):  
Brunilda Balliu ◽  
Ivan Carcamo-Orive ◽  
Michael J. Gloudemans ◽  
Daniel C. Nachun ◽  
Matthew G. Durrant ◽  
...  
Keyword(s):  
Risk Factors ◽  
Genetic Risk ◽  
Complex Traits ◽  
Integrated Approach ◽  
Genetic Risk Factors

scholarly journals Contrasting the genetic architecture of 30 complex traits from summary association data

2016 ◽  
Author(s):  
Huwenbo Shi ◽  
Gleb Kichaev ◽  
Bogdan Pasaniuc
Keyword(s):  
Complex Traits ◽  
Variance Components ◽  
Genetic Architecture ◽  
Large Scale ◽  
Multiple Traits ◽  
New Methods ◽  
Large Sets ◽  
High Contribution ◽  
Association Data ◽  
Summary Data

Variance components methods that estimate the aggregate contribution of large sets of variants to the heritability of complex traits have yielded important insights into the disease architecture of common diseases. Here, we introduce new methods that estimate the total variance in trait explained by a single locus in the genome (local heritability) from summary GWAS data while accounting for linkage disequilibrium (LD) among variants. We apply our new estimator to ultra large-scale GWAS summary data of 30 common traits and diseases to gain insights into their local genetic architecture. First, we find that common SNPs have a high contribution to the heritability of all studied traits. Second, we identify traits for which the majority of the SNP heritability can be confined to a small percentage of the genome. Third, we identify GWAS risk loci where the entire locus explains significantly more variance in the trait than the GWAS reported variants. Finally, we identify 55 loci that explain a large proportion of heritability across multiple traits.

DESIGN AND IMPLEMENTATION OF THE OCEANOGRAPHIC MODELING AND OBSERVATION NETWORK (REMO) FOR PHYSICAL OCEANOGRAPHY STUDIES AND OCEAN FORECASTING

2014 ◽  
Vol 31 (2) ◽  
Author(s):  
Jose Antonio Moreira Lima
Keyword(s):  
Atlantic Ocean ◽  
Large Scale ◽  
North Pacific Ocean ◽  
Integrated Approach ◽  
Sea Surface ◽  
Global Ocean ◽  
Height Anomaly ◽  
The North ◽  
Observation Network ◽  
Ocean Forecasting

This paper is concerned with the planning, implementation and some results of the Oceanographic Modeling and Observation Network, named REMO, for Brazilian regional waters. Ocean forecasting has been an important scientific issue over the last decade due to studies related to climate change as well as applications related to short-range oceanic forecasts. The South Atlantic Ocean has a deficit of oceanographic measurements when compared to other ocean basins such as the North Atlantic Ocean and the North Pacific Ocean. It is a challenge to design an ocean forecasting system for a region with poor observational coverage of in-situ data. Fortunately, most ocean forecasting systems heavily rely on the assimilation of surface fields such as sea surface height anomaly (SSHA) or sea surface temperature (SST), acquired by environmental satellites, that can accurately provide information that constrain major surface current systems and their mesoscale activity. An integrated approach is proposed here in which the large scale circulation in the Atlantic Ocean is modeled in a first step, and gradually nested into higher resolution regional models that are able to resolve important processes such as the Brazil Current and associated mesoscale variability, continental shelf waves, local and remote wind forcing, and others. This article presents the overall strategy to develop the models using a network of Brazilian institutions and their related expertise along with international collaboration. This work has some similarity with goals of the international project Global Ocean Data Assimilation Experiment OceanView (GODAE OceanView).

scholarly journals Remote Sensing Methods for the Biophysical Characterization of Protected Areas Globally: Challenges and Opportunities

2021 ◽  
Vol 10 (6) ◽  
pp. 384
Author(s):  
Javier Martínez-López ◽  
Bastian Bertzky ◽  
Simon Willcock ◽  
Marine Robuchon ◽  
María Almagro ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Protected Areas ◽  
Large Scale ◽  
Anthropogenic Activities ◽  
Global Scale ◽  
Area Network ◽  
Biophysical Characterization ◽  
Challenges And Opportunities ◽  
Scale Characterization

Protected areas (PAs) are a key strategy to reverse global biodiversity declines, but they are under increasing pressure from anthropogenic activities and concomitant effects. Thus, the heterogeneous landscapes within PAs, containing a number of different habitats and ecosystem types, are in various degrees of disturbance. Characterizing habitats and ecosystems within the global protected area network requires large-scale monitoring over long time scales. This study reviews methods for the biophysical characterization of terrestrial PAs at a global scale by means of remote sensing (RS) and provides further recommendations. To this end, we first discuss the importance of taking into account the structural and functional attributes, as well as integrating a broad spectrum of variables, to account for the different ecosystem and habitat types within PAs, considering examples at local and regional scales. We then discuss potential variables, challenges and limitations of existing global environmental stratifications, as well as the biophysical characterization of PAs, and finally offer some recommendations. Computational and interoperability issues are also discussed, as well as the potential of cloud-based platforms linked to earth observations to support large-scale characterization of PAs. Using RS to characterize PAs globally is a crucial approach to help ensure sustainable development, but it requires further work before such studies are able to inform large-scale conservation actions. This study proposes 14 recommendations in order to improve existing initiatives to biophysically characterize PAs at a global scale.

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