scholarly journals Linkage mapping of yeast cross protection connects gene expression variation to a higher-order organismal trait

2017 ◽  
Author(s):  
Tara N. Stuecker ◽  
Amanda N. Scholes ◽  
Jeffrey A. Lewis
Keyword(s):  
Gene Expression ◽  
Natural Variation ◽  
Higher Order ◽  
Cross Protection ◽  
Ethanol Stress ◽  
Gene Expression Variation ◽  
Gene Expression Response ◽  
Expression Variation ◽  
Wild Strains ◽  
Stress Defense

AbstractGene expression variation is extensive in nature, and is hypothesized to play a major role in shaping phenotypic diversity. However, connecting differences in gene expression across individuals to higher-order organismal traits is not trivial. In many cases, gene expression variation may be evolutionarily neutral, and in other cases expression variation may only affect phenotype under specific conditions. To understand connections between gene expression variation and stress defense phenotypes, we have been leveraging extensive natural variation in the gene expression response to acute ethanol in laboratory and wild Saccharomyces cerevisiae strains. Previous work found that the genetic architecture underlying these expression differences included dozens of “hotspot” loci that affected many transcripts in trans. In the present study, we provide new evidence that one of these expression QTL hotspot loci is responsible for natural variation in one particular stress defense phenotype—ethanol-induced cross protection against severe doses of H2O2. The causative polymorphism is in the heme-activated transcription factor Hap1p, which we show directly impacts cross protection, but not the basal H2O2 resistance of unstressed cells. This provides further support that distinct cellular mechanisms underlie basal and acquired stress resistance. We also show that the Hap1p-dependent cross protection relies on novel regulation of cytosolic catalase T (Ctt1p) during ethanol stress in wild strains. Because ethanol accumulation precedes aerobic respiration and accompanying reactive oxygen species formation, wild strains with the ability to anticipate impending oxidative stress would likely be at an advantage. This study highlights how strategically chosen traits that better correlate with gene expression changes can improve our power to identify novel connections between gene expression variation and higher-order organismal phenotypes.

scholarly journals Natural variation of the cardiac transcriptome in humans

2020 ◽  
Author(s):  
Tatiana Domitrovic ◽  
Mariana H. Moreira ◽  
Rodolfo L. Carneiro ◽  
Marcelo Ribeiro-Alves ◽  
Fernando L. Palhano
Keyword(s):  
Gene Expression ◽  
Natural Variation ◽  
Pleiotropic Effect ◽  
Translation Efficiency ◽  
Mrna Levels ◽  
Healthy Individuals ◽  
Gene Expression Variation ◽  
Expression Variation ◽  
Disease Phenotypes ◽  
Healthy Donors

ABSTRACTWe investigated the gene-expression variation among humans by analyzing previously published mRNA-seq and ribosome footprint profiling (RP) of heart left-ventricles from healthy donors. We ranked the genes according to their coefficient of variation values and found that the top 5% most variable genes had special features compared to the rest of the genome, such as lower mRNA levels and shorter half-lives coupled to increased translation efficiency. We observed that these genes are mostly involved with immune response and have a pleiotropic effect on disease phenotypes, indicating that asymptomatic conditions contribute to the gene expression diversity of healthy individuals.

scholarly journals Massively parallel gene expression variation measurement of a synonymous codon library

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Alexander Schmitz ◽  
Fuzhong Zhang
Keyword(s):  
Gene Expression ◽  
Codon Usage ◽  
Single Cells ◽  
Massively Parallel ◽  
Protein Abundance ◽  
Translation Efficiency ◽  
Gene Expression Variation ◽  
Expression Variation ◽  
Change In Mean ◽  
Adaptation Index

Abstract Background Cell-to-cell variation in gene expression strongly affects population behavior and is key to multiple biological processes. While codon usage is known to affect ensemble gene expression, how codon usage influences variation in gene expression between single cells is not well understood. Results Here, we used a Sort-seq based massively parallel strategy to quantify gene expression variation from a green fluorescent protein (GFP) library containing synonymous codons in Escherichia coli. We found that sequences containing codons with higher tRNA Adaptation Index (TAI) scores, and higher codon adaptation index (CAI) scores, have higher GFP variance. This trend is not observed for codons with high Normalized Translation Efficiency Index (nTE) scores nor from the free energy of folding of the mRNA secondary structure. GFP noise, or squared coefficient of variance (CV2), scales with mean protein abundance for low-abundant proteins but does not change at high mean protein abundance. Conclusions Our results suggest that the main source of noise for high-abundance proteins is likely not originating at translation elongation. Additionally, the drastic change in mean protein abundance with small changes in protein noise seen from our library implies that codon optimization can be performed without concerning gene expression noise for biotechnology applications.

scholarly journals Gene expression variation increase in trisomy 21 tissues

2008 ◽  
Vol 19 (6) ◽  
pp. 398-405 ◽  
Author(s):  
Ching Yu Chou ◽  
Li Yu Liu ◽  
Chien Yu Chen ◽  
Cheng Hsien Tsai ◽  
Hsiao Lin Hwa ◽  
...  
Keyword(s):  
Gene Expression ◽  
Trisomy 21 ◽  
Gene Expression Variation ◽  
Expression Variation

Gene expression variation in natural populations of hexaploid and allododecaploid Spartina species (Poaceae)

2017 ◽  
Vol 303 (8) ◽  
pp. 1061-1079 ◽  
Author(s):  
Julie Ferreira de Carvalho ◽  
Julien Boutte ◽  
Pierre Bourdaud ◽  
Houda Chelaifa ◽  
Kader Ainouche ◽  
...  
Keyword(s):  
Gene Expression ◽  
Natural Populations ◽  
Gene Expression Variation ◽  
Expression Variation ◽  
Spartina Species

scholarly journals Population-scale long-read sequencing uncovers transposable elements contributing to gene expression variation and associated with adaptive signatures in Drosophila melanogaster

2021 ◽  
Author(s):  
Gabriel Rech ◽  
Santiago Radio ◽  
Sara Guirao-Rico ◽  
Laura Aguilera ◽  
Vivien Horvath ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Transposable Elements ◽  
Natural Populations ◽  
Gene Expression Variation ◽  
High Quality ◽  
Expression Variation ◽  
Climatic Regions ◽  
Genomic Studies ◽  
Reference Genomes

High quality reference genomes are crucial to understanding genome function, structure and evolution. The availability of reference genomes has allowed us to start inferring the role of genetic variation in biology, disease, and biodiversity conservation. However, analyses across organisms demonstrate that a single reference genome is not enough to capture the global genetic diversity present in populations. In this work, we generated 32 high-quality reference genomes for the well-known model species D. melanogaster and focused on the identification and analysis of transposable element variation as they are the most common type of structural variant. We showed that integrating the genetic variation across natural populations from five climatic regions increases the number of detected insertions by 58%. Moreover, 26% to 57% of the insertions identified using long-reads were missed by short-reads methods. We also identified hundreds of transposable elements associated with gene expression variation and new TE variants likely to contribute to adaptive evolution in this species. Our results highlight the importance of incorporating the genetic variation present in natural populations to genomic studies, which is essential if we are to understand how genomes function and evolve.

Sign in / Sign up

Export Citation Format

Share Document