scholarly journals Zebrafish larvae as a model system for systematic characterization of drugs and genes in dyslipidemia and atherosclerosis

2018 ◽  
Author(s):  
Manoj K Bandaru ◽  
Anastasia Emmanouilidou ◽  
Petter Ranefall ◽  
Benedikt von der Heyde ◽  
Eugenia Mazzaferro ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Large Scale ◽  
Early Stage ◽  
Model System ◽  
Concomitant Treatment ◽  
Induced Mutations ◽  
Zebrafish Model ◽  
Disease Etiology ◽  
Causal Genes

AbstractBackgroundHundreds of loci have been robustly associated with circulating lipids, atherosclerosis and coronary artery disease; but for most loci the causal genes and mechanisms remain uncharacterized.MethodsWe developed a semi-automated experimental pipeline for systematic, quantitative, large-scale characterization of mechanisms, drugs and genes associated with dyslipidemia and atherosclerosis in a zebrafish model system. We validated our pipeline using a dietary (n>2000), drug treatment (n>1000), and genetic intervention (n=384), and used it to characterize three candidate genes in a GWAS-identified pleiotropic locus on chr 19p13.11 (n>500).ResultsOur results show that five days of overfeeding and cholesterol supplementation had independent pro-atherogenic effects, which could be diminished by concomitant treatment with atorvastatin and ezetimibe. CRISPR-Cas9-induced mutations in orthologues of proof-of-concept genes resulted in higher LDL cholesterol levels (apoea), and more early stage atherosclerosis (apobb.1). Finally, our pipeline helped identify putative causal genes for circulating lipids and early-stage atherosclerosis (LPAR2andGATAD2A).ConclusionsIn summary, our pipeline facilitates systematic,in vivocharacterization of drugs and candidate genes to increase our understanding of disease etiology, and can likely help identify novel targets for therapeutic intervention.

scholarly journals Integrating co-expression networks with GWAS to prioritize causal genes in maize

2017 ◽  
Author(s):  
Robert J. Schaefer ◽  
Jean-Michel Michno ◽  
Joseph Jeffers ◽  
Owen Hoekenga ◽  
Brian Dilkes ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Large Scale ◽  
Association Studies ◽  
Strong Dependence ◽  
Genome Wide Association Studies ◽  
Functional Annotations ◽  
Maize Seeds ◽  
Causal Genes ◽  
Mutant Phenotypes ◽  
Molecular Components

AbstractBackgroundGenome wide association studies (GWAS) have identified thousands of loci linked to hundreds of traits in many different species. However, because linkage equilibrium implicates a broad region surrounding each identified locus, the causal genes often remain unknown. This problem is especially pronounced in non-human, non-model species where functional annotations are sparse and there is frequently little information available for prioritizing candidate genes.ResultsTo address this issue, we developed a computational approach called Camoco (Co-Analysis of Molecular Components) that systematically integrates loci identified by GWAS with gene co-expression networks to prioritize putative causal genes. We applied Camoco to prioritize candidate genes from a large-scale GWAS examining the accumulation of 17 different elements in maize seeds. Camoco identified statistically significant subnetworks for the majority of traits examined, producing a prioritized list of high-confidence causal genes for several agronomically important maize traits. Two candidate genes identified by our approach were validated through analysis of mutant phenotypes. Strikingly, we observed a strong dependence in the performance of our approach on the type of co-expression network used: expression variation across genetically diverse individuals in a relevant tissue context (in our case, maize roots) outperformed other alternatives.ConclusionsOur study demonstrates that co-expression networks can provide a powerful basis for prioritizing candidate causal genes from GWAS loci, but suggests that the success of such strategies can highly depend on the gene expression data context. Both the Camoco software and the lessons on integrating GWAS data with co-expression networks generalize to species beyond maize.

Large-scale identification and characterization of genetic variants in asthma candidate genes

2005 ◽  
Vol 57 (9) ◽  
pp. 636-643 ◽  
Author(s):  
Jae-Jung Kim ◽  
Hyun-Hee Kim ◽  
Joo-Hyun Park ◽  
Ha-Jung Ryu ◽  
JuYoung Kim ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Genetic Variants ◽  
Large Scale ◽  
Identification And Characterization

Time for a paradigm shift in the use of plant genetic resources

Genome ◽  
2020 ◽  
Vol 63 (3) ◽  
pp. 189-194
Author(s):  
François Belzile ◽  
Amina Abed ◽  
Davoud Torkamaneh
Keyword(s):  
Genetic Diversity ◽  
Molecular Markers ◽  
Candidate Genes ◽  
Paradigm Shift ◽  
Large Scale ◽  
Plant Genetic Resources ◽  
Phenotypic Characterization ◽  
Novel Traits ◽  
The World

For all major crops, sizeable genebanks are maintained across the world and serve as repositories of genetic diversity and key sources of novel traits used in breeding. Although molecular markers have been used to characterize diversity in a broad sense, the most common approach to exploring these resources has been through phenotypic characterization of subsets of these large collections. With the advent of affordable large-scale genotyping technologies and the increasing body of candidate genes for traits of interest, we argue here that it is time for a paradigm shift in the way that we explore and exploit these considerable and highly useful resources. By combining dense genotypic information in and around candidate genes, it is possible to classify accessions based on their haplotype, something approximating the actual alleles at these genes of interest.

scholarly journals Characterization of Cotton ARF Factors and the Role of GhARF2b in Fiber Development

2020 ◽  
Author(s):  
Xiufang Zhang ◽  
Junfeng Cao ◽  
Chaochen Huang ◽  
Zishou Zheng ◽  
Xia Liu ◽  
...  
Keyword(s):  
Cotton Fiber ◽  
Regulatory Network ◽  
Early Stage ◽  
Model System ◽  
Fiber Development ◽  
Auxin Response ◽  
Cotton Fiber Development ◽  
Cotton Species

Abstract Background: Cotton fiber is a model system for studying plant cell development. At present, our understanding of cotton fiber development and the regulatory network is still primitive. Results: Here, we identify auxin response factor (ARF) genes in three cotton species: the tetraploid upland cotton G. hirsutum, which has 73 ARF genes, and its putative extent parental diploids G. arboreum and G. raimondii, which have 36 and 35 ARFs, respectively. Ka and Ks analyses revealed that in G. hirsutum ARF genes have undergone asymmetric evolution in the two subgenomes. The cotton ARFs can be classified into four phylogenetic clades and are actively expressed in young tissues. We demonstrate that GhARF2b, a homolog of the Arabidopsis AtARF2, was preferentially expressed in developing ovules and fibers. Overexpression of GhARF2b by a fiber specific promoter inhibited fiber cell elongation but promoted initiation and, conversely, its downregulation by RNAi of resulted in fewer but longer fiber. Conclusion: Our results uncover an important role of the ARF factor in modulating cotton fiber development at the early stage.

Some applications of electron beam microanalysis techniques in VLSI process evaluation

1983 ◽  
Vol 41 ◽  
pp. 160-161
Author(s):  
Simon Thomas
Keyword(s):  
Integrated Circuits ◽  
Process Evaluation ◽  
Large Scale ◽  
Technology Development ◽  
Analytical Techniques ◽  
Successful Implementation ◽  
Analysis Of Failures ◽  
Characterization Of Materials ◽  
Circuits Vlsi

Trends in the technology development of very large scale integrated circuits (VLSI) have been in the direction of higher density of components with smaller dimensions. The scaling down of device dimensions has been not only laterally but also in depth. Such efforts in miniaturization bring with them new developments in materials and processing. Successful implementation of these efforts is, to a large extent, dependent on the proper understanding of the material properties, process technologies and reliability issues, through adequate analytical studies. The analytical instrumentation technology has, fortunately, kept pace with the basic requirements of devices with lateral dimensions in the micron/ submicron range and depths of the order of nonometers. Often, newer analytical techniques have emerged or the more conventional techniques have been adapted to meet the more stringent requirements. As such, a variety of analytical techniques are available today to aid an analyst in the efforts of VLSI process evaluation. Generally such analytical efforts are divided into the characterization of materials, evaluation of processing steps and the analysis of failures.

Characterization of seawater reverse osmosis fouled membranes from large scale commercial desalination plant

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Reverse Osmosis ◽  
Large Scale ◽  
Retention Rate ◽  
Local Level ◽  
Microscopic Analysis ◽  
Transmembrane Pressure ◽  
Hydraulic Permeability ◽  
Seawater Reverse Osmosis ◽  
A Chain

The objective of this work is to study the ageing state of a used reverse osmosis (RO) membrane taken in Algeria from the Benisaf Water Company seawater desalination unit. The study consists of an autopsy procedure used to perform a chain of analyses on a membrane sheet. Wear of the membrane is characterized by a degradation of its performance due to a significant increase in hydraulic permeability (25%) and pressure drop as well as a decrease in salt retention (10% to 30%). In most cases the effects of ageing are little or poorly known at the local level and global measurements such as (flux, transmembrane pressure, permeate flow, retention rate, etc.) do not allow characterization. Therefore, a used RO (reverse osmosis) membrane was selected at the site to perform the membrane autopsy tests. These tests make it possible to analyze and identify the cause as well as to understand the links between performance degradation observed at the macroscopic scale and at the scale at which ageing takes place. External and internal visual observations allow seeing the state of degradation. Microscopic analysis of the used membranes surface shows the importance of fouling. In addition, quantification and identification analyses determine a high fouling rate in the used membrane whose foulants is of inorganic and organic nature. Moreover, the analyses proved the presence of a biofilm composed of protein.

Characterization of Interconnect Defects Using Scanning Thermal Conductivity Microscopy

2004 ◽  
Author(s):  
H.W. Ho ◽  
J.C.H. Phang ◽  
A. Altes ◽  
L.J. Balk
Keyword(s):  
Thermal Conductivity ◽  
Integrated Circuits ◽  
Large Scale

Abstract In this paper, scanning thermal conductivity microscopy is used to characterize interconnect defects due to electromigration. Similar features are observed both in the temperature and thermal conductivity micrographs. The key advantage of the thermal conductivity mode is that specimen bias is not required. This is an important advantage for the characterization of defects in large scale integrated circuits. The thermal conductivity micrographs of extrusion, exposed and subsurface voids are presented and compared with the corresponding topography and temperature micrographs.

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