scholarly journals Evolution of phenotypic variance provides insights into the genetic basis of adaption

2021 ◽  
Author(s):  
Wei-Yun Lai ◽  
Viola Nolte ◽  
Ana Marija Jakšić ◽  
Christian Schlötterer
Keyword(s):  
Gene Expression ◽  
Experimental Evolution ◽  
Genomic Data ◽  
Phenotypic Variance ◽  
Variance Change ◽  
Adaptive Architecture ◽  
Powerful Approach ◽  
Adaptive Architectures ◽  
Before And After ◽  
Change In Mean

AbstractMost traits are polygenic and the contributing loci can be identified by GWAS. Their adaptive architecture is, however, poorly characterized. Here, we propose a new approach to study the adaptive architecture, which does not depend on genomic data. Relying on experimental evolution we measure the phenotypic variance in replicated populations during adaptation to a new environment. Extensive computer simulations show that the evolution of phenotypic variance in a replicated experimental evolution setting is a powerful approach to distinguish between oligogenic and polygenic adaptive architectures. We apply this new method to gene expression variance in male Drosophila simulans before and after 100 generations of adaptation to a novel hot environment. The variance change in gene expression was indistinguishable for genes with and without a significant change in mean expression after 100 generations of evolution. We conclude that adaptive gene expression evolution is best explained by a highly polygenic adaptive architecture. We propose that the evolution of phenotypic variance provides a powerful approach to characterize the adaptive architecture, in particular when combined with genomic data.

scholarly journals Evolution of gene expression variance during adaptation to high temperature in Drosophila

2021 ◽  
Author(s):  
Wei-Yun Lai ◽  
Christian Schlötterer
Keyword(s):  
Gene Expression ◽  
Natural Populations ◽  
Selection Response ◽  
Phenotypic Variance ◽  
Adaptive Responses ◽  
Genetic Redundancy ◽  
Before And After ◽  
Polygenic Adaptation ◽  
The Impact ◽  
Expression Variance

AbstractShifts in trait means are widely considered as evidence for adaptive responses, but the impact on phenotypic variance remains largely unexplored. Here, we studied gene expression variance of Drosophila simulans males before and after 100 generations of adaptation to a novel hot laboratory environment. In each of the two independently evolved replicate populations the variance of about 150 genes changed significantly (mostly reduction). Although different genes were affected in both replicates, these genes are related to digestion in the gut. This non-parallel selection response on the gene level in combination with a convergent response at a higher phenotypic level reflects genetic redundancy, a characteristic hallmark of polygenic adaptation. We propose that the constant and simple food source in the laboratory resulted in selection for reduced variance in digestive genes. In natural populations adaptation to diverse types of food may be beneficial, resulting in higher phenotypic variance. This empirical evidence of phenotypic variance being the direct target of selection during adaptation has important implications for strategies to identify selection signatures.

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 Correcting for experiment-specific variability in expression compendia can remove underlying signals

GigaScience ◽  
2020 ◽  
Vol 9 (11) ◽  
Author(s):  
Alexandra J Lee ◽  
YoSon Park ◽  
Georgia Doing ◽  
Deborah A Hogan ◽  
Casey S Greene
Keyword(s):  
Gene Expression ◽  
Large Scale ◽  
Original Signal ◽  
Batch Effects ◽  
Technical Variability ◽  
The Past ◽  
Statistical Correction ◽  
Before And After ◽  
Data Collections ◽  
Biological Patterns

Abstract Motivation In the past two decades, scientists in different laboratories have assayed gene expression from millions of samples. These experiments can be combined into compendia and analyzed collectively to extract novel biological patterns. Technical variability, or "batch effects," may result from combining samples collected and processed at different times and in different settings. Such variability may distort our ability to extract true underlying biological patterns. As more integrative analysis methods arise and data collections get bigger, we must determine how technical variability affects our ability to detect desired patterns when many experiments are combined. Objective We sought to determine the extent to which an underlying signal was masked by technical variability by simulating compendia comprising data aggregated across multiple experiments. Method We developed a generative multi-layer neural network to simulate compendia of gene expression experiments from large-scale microbial and human datasets. We compared simulated compendia before and after introducing varying numbers of sources of undesired variability. Results The signal from a baseline compendium was obscured when the number of added sources of variability was small. Applying statistical correction methods rescued the underlying signal in these cases. However, as the number of sources of variability increased, it became easier to detect the original signal even without correction. In fact, statistical correction reduced our power to detect the underlying signal. Conclusion When combining a modest number of experiments, it is best to correct for experiment-specific noise. However, when many experiments are combined, statistical correction reduces our ability to extract underlying patterns.

scholarly journals Transcriptomic analysis identifies differences in gene expression in actinic keratoses after treatment with imiquimod and between responders and non responders

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Megan H. Trager ◽  
Emanuelle Rizk ◽  
Sharon Rose ◽  
Kuixi Zhu ◽  
Branden Lau ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Distinct Pattern ◽  
Study Endpoint ◽  
Inflammatory Gene Expression ◽  
Immune Modulators ◽  
Actinic Keratoses ◽  
Before And After ◽  
Pre Treatment

AbstractThe presence of actinic keratoses (AKs) increases a patient’s risk of developing squamous cell carcinoma by greater than six-fold. We evaluated the effect of topical treatment with imiquimod on the tumor microenvironment by measuring transcriptomic differences in AKs before and after treatment with imiquimod 3.75%. Biopsies were collected prospectively from 21 patients and examined histologically. RNA was extracted and transcriptomic analyses of 788 genes were performed using the nanoString assay. Imiquimod decreased number of AKs by study endpoint at week 14 (p < 0.0001). Post-imiquimod therapy, levels of CDK1, CXCL13, IL1B, GADPH, TTK, ILF3, EWSR1, BIRC5, PLAUR, ISG20, and C1QBP were significantly lower (adjusted p < 0.05). Complete responders (CR) exhibited a distinct pattern of inflammatory gene expression pre-treatment relative to incomplete responders (IR), with alterations in 15 inflammatory pathways (p < 0.05) reflecting differential expression of 103 genes (p < 0.05). Presence of adverse effects was associated with improved treatment response. Differences in gene expression were found between pre-treatment samples in CR versus IR, suggesting that higher levels of inflammation pre-treament may play a part in regression of AKs. Further characterization of the immune micro-environment in AKs may help develop biomarkers predictive of response to topical immune modulators and may guide therapy.

Gene expression signature pathways in the human uterine cervix before and after spontaneous term parturition

2006 ◽  
Vol 195 (6) ◽  
pp. S30
Author(s):  
Sonia Hassan ◽  
Roberto Romero ◽  
Adi L. Tarca ◽  
Sorin Draghici ◽  
Nahla Khalek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Uterine Cervix ◽  
Gene Expression Signature ◽  
Expression Signature ◽  
Before And After

scholarly journals Identification of novel regulators of hematopoietic stem cell development through refinement of stem cell localization and expression profiling

Blood ◽  
2009 ◽  
Vol 114 (21) ◽  
pp. 4645-4653 ◽  
Author(s):  
Maria I. Mascarenhas ◽  
Aimée Parker ◽  
Elaine Dzierzak ◽  
Katrin Ottersbach
Keyword(s):  
Gene Expression ◽  
Stem Cell ◽  
Expression Profiling ◽  
Gene Expression Analysis ◽  
Kinase Inhibitor ◽  
Cyclin Dependent Kinase ◽  
Hematopoietic Stem ◽  
Cyclin Dependent Kinase Inhibitor ◽  
Cell Localization ◽  
Before And After

Abstract The first adult-repopulating hematopoietic stem cells (HSCs) are detected starting at day 10.5 of gestation in the aorta-gonads-mesonephros (AGM) region of the mouse embryo. Despite the importance of the AGM in initiating HSC production, very little is currently known about the regulators that control HSC emergence in this region. We have therefore further defined the location of HSCs in the AGM and incorporated this information into a spatial and temporal comparative gene expression analysis of the AGM. The comparisons included gene expression profiling (1) in the newly identified HSC-containing region compared with the region devoid of HSCs, (2) before and after HSC emergence in the AGM microenvironment, and (3) on populations enriched for HSCs and their putative precursors. Two genes found to be up-regulated at the time and place where HSCs are first detected, the cyclin-dependent kinase inhibitor p57Kip2/Cdkn1c and the insulin-like growth factor 2, were chosen for further analysis. We demonstrate here that they play a novel role in AGM hematopoiesis. Interestingly, many genes involved in the development of the tissues surrounding the dorsal aorta are also up-regulated during HSC emergence, suggesting that the regulation of HSC generation occurs in coordination with the development of other organs.

Assessment of cancer prevention effect of exercise

2021 ◽  
pp. 1-6
Author(s):  
Reza Vafaee ◽  
Mostafa Rezaei Tavirani ◽  
Sina Rezaei Tavirani ◽  
Mohammadreza Razzaghi
Keyword(s):  
Gene Expression ◽  
Cancer Prevention ◽  
Human Health ◽  
Expression Profiles ◽  
Vastus Lateralis ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Vastus Lateralis Muscle ◽  
Before And After ◽  
Exercise Training Intervention

There are many documents about benefits of exercise on human health. However, evidences indicate to positive effect of exercise on disease prevention, understanding of many aspects of this mechanism need more investigations. Determination of critical genes which effect human health. GSE156249 including 12 gene expression profiles of healthy individual biopsy from vastus lateralis muscle before and after 12-week combined exercise training intervention were extracted from gene expression omnibus (GEO) database. The significant DEGs were included in interactome unit by Cytoscape software and STRING database. The network was analyzed to find the central nodes subnetwork clusters. The nodes of prominent cluster were assessed via gene ontology by using ClueGO. Number of 8 significant DEGs and 100 first neighbors analyzed via network analysis. The network includes 2 clusters and COL3A1, BGN, and LOX were determined as central DEGs. The critical DEGs were involved in cancer prevention process.

scholarly journals Effects of 30 min of aerobic exercise on gene expression in human neutrophils

2008 ◽  
Vol 104 (1) ◽  
pp. 236-243 ◽  
Author(s):  
Shlomit Radom-Aizik ◽  
Frank Zaldivar ◽  
Szu-Yun Leu ◽  
Pietro Galassetti ◽  
Dan M. Cooper
Keyword(s):  
Gene Expression ◽  
Mononuclear Cells ◽  
Cycle Ergometer ◽  
Human Neutrophils ◽  
Peripheral Blood Mononuclear ◽  
False Discovery ◽  
Ergometer Exercise ◽  
Before And After ◽  
Ease Score ◽  
Repair Genes

Relatively brief bouts of exercise alter gene expression in peripheral blood mononuclear cells (PBMCs), but whether exercise changes gene expression in circulating neutrophils (whose numbers, like PBMCs, increase) is not known. We hypothesized that exercise would activate neutrophil genes involved in apoptosis, inflammation, and cell growth and repair, since these functions in leukocytes are known to be influenced by exercise. Blood was sampled before and immediately after 30 min of constant, heavy (∼80% peak O2uptake) cycle ergometer exercise in 12 healthy men (19–29 yr old) of average fitness. Neutrophils were isolated using density gradients; RNA was hybridized to Affymetrix U133+2 Genechip arrays. With false discovery rate (FDR) <0.05 with 95% confidence, a total of 526 genes were differentially expressed between before and after exercise. Three hundred and sixteen genes had higher expression after exercise. The Jak/STAT pathway, known to inhibit apoptosis, was significantly activated (EASE score, P < 0.005), but 14 genes were altered in a way likely to accelerate apoptosis as well. Similarly, both proinflammatory (e.g., IL-32, TNFSF8, and CCR5) and anti-inflammatory (e.g., ANXA1) were affected. Growth and repair genes like AREG and FGF2 receptor genes (involved in angiogenesis) were also activated. Finally, a number of neutrophil genes known to be involved in pathological conditions like asthma and arthritis were altered by exercise, suggesting novel links between physical activity and disease or its prevention. In summary, brief heavy exercise leads to a previously unknown substantial and significant alteration in neutrophil gene expression.

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