A Genome-Wide, Mapped Algal Mutant Library Enables High-Throughput Genetic Studies in a Photosynthetic Eukaryote

2018 ◽  
Author(s):  
Xiaobo Li ◽  
Weronika Patena ◽  
Friedrich Fauser ◽  
Robert E. Jinkerson ◽  
Shai Saroussi ◽  
...  
Keyword(s):  
High Throughput ◽  
Mutant Library ◽  
Photosynthetic Eukaryote ◽  
Genetic Studies ◽  
Genome Wide ◽  
A Genome

scholarly journals Towards a Systems Approach in the Genetic Analysis of Archaea: Accelerating Mutant Construction and Phenotypic Analysis inHaloferax volcanii

Archaea ◽  
2010 ◽  
Vol 2010 ◽  
pp. 1-11 ◽  
Author(s):  
Ian K. Blaby ◽  
Gabriela Phillips ◽  
Crysten E. Blaby-Haas ◽  
Kevin S. Gulig ◽  
Basma El Yacoubi ◽  
...  
Keyword(s):  
High Throughput ◽  
Gene Deletion ◽  
Systems Approach ◽  
Essential Gene ◽  
Gene Knockout ◽  
Deletion Mutants ◽  
Mutant Library ◽  
Phenotypic Analysis ◽  
Genome Wide ◽  
A Genome

With the availability of a genome sequence and increasingly sophisticated genetic tools,Haloferax volcaniiis becoming a model for both Archaea and halophiles. In order forH. volcaniito reach a status equivalent toEscherichia coli, Bacillus subtilis, orSaccharomyces cerevisiae, a gene knockout collection needs to be constructed in order to identify the archaeal essential gene set and enable systematic phenotype screens. A streamlined gene-deletion protocol adapted for potential automation was implemented and used to generate 22H. volcaniideletion strains and identify several potentially essential genes. These gene deletion mutants, generated in this and previous studies, were then analyzed in a high-throughput fashion to measure growth rates in different media and temperature conditions. We conclude that these high-throughput methods are suitable for a rapid investigation of anH. volcaniimutant library and suggest that they should form the basis of a larger genome-wide experiment.

scholarly journals A genome-wide screen in the mouse liver reveals sex-specific and cell non-autonomous regulation of cell fitness

2021 ◽  
Author(s):  
Heather R. Keys ◽  
Kristin A. Knouse
Keyword(s):  
Functional Genomics ◽  
High Throughput ◽  
Mouse Liver ◽  
Ex Vivo ◽  
Screening Method ◽  
Living Organism ◽  
Cellular Processes ◽  
Autonomous Regulation ◽  
Genome Wide ◽  
A Genome

ABSTRACTOur ability to understand and modulate mammalian physiology and disease requires knowing how all genes contribute to any given phenotype in the organism. Genome-wide screening using CRISPR-Cas9 has emerged as a powerful method for the genetic dissection of cellular processes1,2, but the need to stably deliver single guide RNAs to millions of cells has restricted its implementation to ex vivo systems. These ex vivo systems cannot reproduce all of the cellular phenotypes observed in vivo nor can they recapitulate all of the factors that influence these phenotypes. There thus remains a pressing need for high-throughput functional genomics in a living organism. Here, we establish accessible genome-wide screening in the mouse liver and use this approach to uncover the complete regulation of cellular fitness in a living organism. We discover novel sex-specific and cell non-autonomous regulation of cell growth and viability. In particular, we find that the class I major histocompatibility complex is essential for preventing immune-mediated clearance of hepatocytes. Our approach provides the first comprehensive picture of cell fitness in a living organism and highlights the importance of investigating cellular phenomena in their native context. Our screening method is robust, scalable, and easily adapted to examine diverse cellular processes using any CRISPR application. We have hereby established a foundation for high-throughput functional genomics in a living mammal, enabling unprecedented insight into mammalian physiology and disease.

scholarly journals A Genome-Wide Arrayed cDNA Screen to Identify Functional Modulators of α7 Nicotinic Acetylcholine Receptors

2016 ◽  
Vol 22 (2) ◽  
pp. 155-165 ◽  
Author(s):  
Elizabeth B. Rex ◽  
Nikhil Shukla ◽  
Shenyan Gu ◽  
David Bredt ◽  
Daniel DiSepio
Keyword(s):  
Cdna Library ◽  
High Throughput ◽  
Protein Interactions ◽  
Nicotinic Acetylcholine Receptors ◽  
Calcium Flux ◽  
Functional Assay ◽  
Α7 Nicotinic Acetylcholine Receptor ◽  
Nicotinic Acetylcholine ◽  
Genome Wide ◽  
A Genome

Cellular signaling is in part regulated by the composition and subcellular localization of a series of protein interactions that collectively form a signaling complex. Using the α7 nicotinic acetylcholine receptor (α7nAChR) as a proof-of-concept target, we developed a platform to identify functional modulators (or auxiliary proteins) of α7nAChR signaling. The Broad cDNA library was transiently cotransfected with α7nAChR cDNA in HEK293T cells in a high-throughput fashion. Using this approach in combination with a functional assay, we identified positive modulators of α7nAChR activity. We identified known positive modulators/auxiliary proteins present in the cDNA library that regulate α7nAChR signaling, in addition to identifying novel modulators of α7nAChR signaling. These included NACHO, SPDYE11, TCF4, and ZC3H12A, all of which increased PNU-120596-mediated nicotine-dependent calcium flux. Importantly, these auxiliary proteins did not modulate GluR1(o)-mediated Ca flux. To elucidate a possible mechanism of action, we employed an α7nAChR-HA surface staining assay. NACHO enhanced α7nAChR surface expression; however, the mechanism responsible for the SPDYE11-, TCF4-, and ZC3H12A-dependent modulation of α7nAChR has yet to be defined. This report describes the development and validation of a high-throughput, genome-wide cDNA screening platform coupled to FLIPR functional assays in order to identify functional modulators of α7nAChR signaling.

scholarly journals A genome-wide algal mutant library and functional screen identifies genes required for eukaryotic photosynthesis

2019 ◽  
Vol 51 (4) ◽  
pp. 627-635 ◽  
Author(s):  
Xiaobo Li ◽  
Weronika Patena ◽  
Friedrich Fauser ◽  
Robert E. Jinkerson ◽  
Shai Saroussi ◽  
...  
Keyword(s):  
Mutant Library ◽  
Functional Screen ◽  
Genome Wide ◽  
A Genome

A Genome-Wide Mutant Library of Pseudomonas aeruginosa

Pseudomonas ◽  
2006 ◽  
pp. 121-138 ◽  
Author(s):  
Michael A. Jacobs ◽  
Colin Manoil
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Mutant Library ◽  
Genome Wide ◽  
A Genome

scholarly journals Review: Population Structure in Genetic Studies: Confounding Factors and Mixed Models

2016 ◽  
Author(s):  
Lana S. Martin ◽  
Eleazar Eskin
Keyword(s):  
Population Structure ◽  
Mixed Models ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Laboratory Mouse ◽  
Mouse Strains ◽  
Genetic Studies ◽  
The Past ◽  
Genome Wide ◽  
A Genome

AbstractA genome-wide association study (GWAS) seeks to identify genetic variants that contribute to the development and progression of a specific disease. Over the past 10 years, new approaches using mixed models have emerged to mitigate the deleterious effects of population structure and relatedness in association studies. However, developing GWAS techniques to effectively test for association while correcting for population structure is a computational and statistical challenge. Using laboratory mouse strains as an example, our review characterizes the problem of population structure in association studies and describes how it can cause false positive associations. We then motivate mixed models in the context of unmodeled factors.

scholarly journals Predicting Moisture Content During Maize Nixtamalization Using Machine Learning with NIR Spectroscopy

2021 ◽  
Author(s):  
Michael Burns ◽  
Jonathan Renk ◽  
David Eickholt ◽  
Amanda Gilbert ◽  
Travis Hattery ◽  
...  
Keyword(s):  
Machine Learning ◽  
Moisture Content ◽  
High Throughput ◽  
Genome Wide Association Study ◽  
Rank Correlation ◽  
Quantitative Measure ◽  
Support Vector ◽  
Environment Interaction ◽  
Genome Wide ◽  
A Genome

Lack of high throughput phenotyping systems for determining moisture content during the maize nixtamalization cooking process has led to difficulty in breeding for this trait. This study provides a high throughput, quantitative measure of kernel moisture content during nixtamalization based on NIR scanning of uncooked maize kernels. Machine learning was utilized to develop models based on the combination of NIR spectra and moisture content determined from a scaled-down benchtop cook method. A linear support vector machine (SVM) model with a Spearman's rank correlation coefficient of 0.852 between wet lab and predicted values was developed from 100 diverse temperate genotypes grown in replicate across two environments. This model was applied to NIR data from 501 diverse temperate genotypes grown in replicate in five environments. Analysis of variance revealed environment explained the highest percent of the variation (51.5%), followed by genotype (15.6%) and genotype-by-environment interaction (11.2%). A genome-wide association study identified 26 significant loci across five environments that explained between 5.04% and 16.01% (average = 10.41%). However, genome-wide markers explained 10.54% to 45.99% (average = 31.68%) of the variation, indicating the genetic architecture of this trait is likely complex and controlled by many loci of small effect. This study provides a high-throughput method to evaluate moisture content during nixtamalization that is feasible at the scale of a breeding program and provides important information about the factors contributing to variation of this trait for breeders and food companies to make future strategies to improve this important processing trait.

scholarly journals Genome-wide methylation data improves dissection of the effect of smoking on body mass index

PLoS Genetics ◽  
2021 ◽  
Vol 17 (9) ◽  
pp. e1009750
Author(s):  
Carmen Amador ◽  
Yanni Zeng ◽  
Michael Barber ◽  
Rosie M. Walker ◽  
Archie Campbell ◽  
...  
Keyword(s):  
Complex Traits ◽  
Genetic Basis ◽  
Environmental Changes ◽  
Total Contribution ◽  
Genetic Studies ◽  
Socioeconomic Changes ◽  
Genome Wide ◽  
A Genome ◽  
Causes Of Disease ◽  
Wide Perspective

Variation in obesity-related traits has a genetic basis with heritabilities between 40 and 70%. While the global obesity pandemic is usually associated with environmental changes related to lifestyle and socioeconomic changes, most genetic studies do not include all relevant environmental covariates, so the genetic contribution to variation in obesity-related traits cannot be accurately assessed. Some studies have described interactions between a few individual genes linked to obesity and environmental variables but there is no agreement on their total contribution to differences between individuals. Here we compared self-reported smoking data and a methylation-based proxy to explore the effect of smoking and genome-by-smoking interactions on obesity related traits from a genome-wide perspective to estimate the amount of variance they explain. Our results indicate that exploiting omic measures can improve models for complex traits such as obesity and can be used as a substitute for, or jointly with, environmental records to better understand causes of disease.

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