scholarly journals Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: evidence for “polygenic epistasis”

2019 ◽  
Author(s):  
Christoph D. Rau ◽  
Natalia M. Gonzales ◽  
Joshua S. Bloom ◽  
Danny Park ◽  
Julien Ayroles ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Statistical Tests ◽  
Inbred Mice ◽  
Statistical Test ◽  
Genetic Ancestry ◽  
Human Populations ◽  
Epistatic Interactions ◽  
Variable Effect ◽  
The Impact

AbstractBackgroundThe majority of quantitative genetic models used to map complex traits assume that alleles have similar effects across all individuals. Significant evidence suggests, however, that epistatic interactions modulate the impact of many alleles. Nevertheless, identifying epistatic interactions remains computationally and statistically challenging. In this work, we address some of these challenges by developing a statistical test for polygenic epistasis that determines whether the effect of an allele is altered by the global genetic ancestry proportion from distinct progenitors.ResultsWe applied our method to data from mice and yeast. For the mice, we observed 49 significant genotype-by-ancestry interaction associations across 14 phenotypes as well as over 1,400 Bonferroni-corrected genotype-by-ancestry interaction associations for mouse gene expression data. For the yeast, we observed 92 significant genotype-by-ancestry interactions across 38 phenotypes. Given this evidence of epistasis, we test for and observe evidence of rapid selection pressure on ancestry specific polymorphisms within one of the cohorts, consistent with epistatic selection.ConclusionsUnlike our prior work in human populations, we observe widespread evidence of ancestry-modified SNP effects, perhaps reflecting the greater divergence present in crosses using mice and yeast.Author SummaryMany statistical tests which link genetic markers in the genome to differences in traits rely on the assumption that the same polymorphism will have identical effects in different individuals. However, there is substantial evidence indicating that this is not the case. Epistasis is the phenomenon in which multiple polymorphisms interact with one another to amplify or negate each other’s effects on a trait. We hypothesized that individual SNP effects could be changed in a polygenic manner, such that the proportion of as genetic ancestry, rather than specific markers, might be used to capture epistatic interactions. Motivated by this possibility, we develop a new statistical test that allowed us to examine the genome to identify polymorphisms which have different effects depending on the ancestral makeup of each individual. We use our test in two different populations of inbred mice and a yeast panel and demonstrate that these sorts of variable effect polymorphisms exist in 14 different physical traits in mice and 38 phenotypes in yeast as well as in murine gene expression. We use the term “polygenic epistasis” to distinguish these interactions from the more conventional two- or multi-locus interactions.

scholarly journals Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for “polygenic epistasis”

PLoS Genetics ◽  
2020 ◽  
Vol 16 (10) ◽  
pp. e1009165
Author(s):  
Christoph D. Rau ◽  
Natalia M. Gonzales ◽  
Joshua S. Bloom ◽  
Danny Park ◽  
Julien Ayroles ◽  
...  
Keyword(s):  
Complex Traits ◽  
Selection Pressure ◽  
Statistical Test ◽  
Human Populations ◽  
Expression Data ◽  
Epistatic Interactions ◽  
Quantitative Genetic ◽  
Mouse Gene Expression ◽  
The Impact ◽  
Ancestry Proportion

Background The majority of quantitative genetic models used to map complex traits assume that alleles have similar effects across all individuals. Significant evidence suggests, however, that epistatic interactions modulate the impact of many alleles. Nevertheless, identifying epistatic interactions remains computationally and statistically challenging. In this work, we address some of these challenges by developing a statistical test for polygenic epistasis that determines whether the effect of an allele is altered by the global genetic ancestry proportion from distinct progenitors. Results We applied our method to data from mice and yeast. For the mice, we observed 49 significant genotype-by-ancestry interaction associations across 14 phenotypes as well as over 1,400 Bonferroni-corrected genotype-by-ancestry interaction associations for mouse gene expression data. For the yeast, we observed 92 significant genotype-by-ancestry interactions across 38 phenotypes. Given this evidence of epistasis, we test for and observe evidence of rapid selection pressure on ancestry specific polymorphisms within one of the cohorts, consistent with epistatic selection. Conclusions Unlike our prior work in human populations, we observe widespread evidence of ancestry-modified SNP effects, perhaps reflecting the greater divergence present in crosses using mice and yeast.

scholarly journals Genetic Variation in CNS Myelination and Functional Brain Connectivity in Recombinant Inbred Mice

Cells ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 2119
Author(s):  
Andrea Goudriaan ◽  
Maarten Loos ◽  
Sabine Spijker ◽  
August B. Smit ◽  
Mark H. G. Verheijen
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Recombinant Inbred ◽  
Brain Connectivity ◽  
Inbred Mice ◽  
Protein Composition ◽  
Human Populations ◽  
Neuronal Communication ◽  
The Impact ◽  
Myelin Gene

Myelination greatly increases the speed of action potential propagation of neurons, thereby enhancing the efficacy of inter-neuronal communication and hence, potentially, optimizing the brain’s signal processing capability. The impact of genetic variation on the extent of axonal myelination and its consequences for brain functioning remain to be determined. Here we investigated this question using a genetic reference panel (GRP) of mouse BXD recombinant inbred (RI) strains, which partly model genetic diversity as observed in human populations, and which show substantial genetic differences in a variety of behaviors, including learning, memory and anxiety. We found coherent differences in the expression of myelin genes in brain tissue of RI strains of the BXD panel, with the largest differences in the hippocampus. The parental C57BL/6J (C57) and DBA/2J (DBA) strains were on opposite ends of the expression spectrum, with C57 showing higher myelin transcript expression compared with DBA. Our experiments showed accompanying differences between C57 and DBA in myelin protein composition, total myelin content, and white matter conduction velocity. Finally, the hippocampal myelin gene expression of the BXD strains correlated significantly with behavioral traits involving anxiety and/or activity. Taken together, our data indicate that genetic variation in myelin gene expression translates to differences observed in myelination, axonal conduction speed, and possibly in anxiety/activity related behaviors.

scholarly journals Positive Selection Affects the Expression of Systemic Lupus Erythematosus Associated Loci in Human Populations

2021 ◽  
Author(s):  
Victoria Oberreiter ◽  
Tobias Goellner ◽  
David L. Morris ◽  
Helmut Schaschl
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Positive Selection ◽  
Lupus Erythematosus ◽  
Lifestyle Changes ◽  
Genetic Ancestry ◽  
Selection Function ◽  
Human Populations ◽  
Systemic Lupus ◽  
A Genome

Abstract Background: Systemic lupus erythematosus (SLE) shows marked population-specific disparities in disease prevalence, including substantial variation in manifestations and complications according to genetic ancestry. Several recent studies suggest that a substantial proportion of variation of gene expression shows genetic ancestry-associated differences in gene regulation on immune responses. Positive selection may act in a population-specific manner on expression quantitative trait loci (eQTLs) and thereby contributes to the difference in the differences of SLE prevalence and manifestation in human populations. We tested the hypothesises that some of the identified SLE risk polymorphisms display pleiotropic effects or polygenicity driven by positive selection. We performed a genome-wide scan for recent positive selection by using integrated Haplotype Score (iHS) statistics in different human populations. In addition, we estimated the timing of beneficial mutations to understand what possible selective pressures drive positive selection at SLE-associated loci. Results: We identified several SLE risk loci that are population-specifically under positive selection. Almost all SNPs that are under positive selection function as cis-eQTLs in different tissue types. We determined that adaptive eQTLs affect the expression of fewer genes than non-adaptive eQTLs, suggesting a limited range of effect of an eQTL at SLE risk sites that show signatures of positive selection. Furthermore, some positively selected SNPs are located in transcription factor binding sequences. The timing of positive selection for the studied loci suggests that both environmental and recent lifestyle changes during as well as after the Neolithic Transition may have become selectively effective. We propose a novel link between positively selected eQTLs at a certain SLE risk locus in Europeans and a physiological pathway not previously considered in SLE.Conclusions: We conclude that population-specific adaptive eQTLs contribute to the observed variation in specific manifestations and complications of SLE in different ethnicities. Our results suggest also that human populations adapt more rapidly to environmental and lifestyle stimuli via modification of gene expression without having to alter the genetic code.

scholarly journals Environmental perturbations lead to extensive directional shifts in RNA processing

2017 ◽  
Author(s):  
A. L. Richards ◽  
D. Watza ◽  
A. Findley ◽  
A. Alazizi ◽  
X. Wen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Rna Processing ◽  
Complex Traits ◽  
Intron Retention ◽  
Vast Number ◽  
Factor Binding ◽  
Environmental Perturbations ◽  
Exon Usage ◽  
The Impact

AbstractEnvironmental perturbations have large effects on both organismal and cellular traits, including gene expression, but the extent to which the environment affects RNA processing remains largely uncharacterized. Recent studies have identified a large number of genetic variants associated with variation in RNA processing that also have an important role in complex traits; yet we do not know in which contexts the different underlying isoforms are used. Here, we comprehensively characterized changes in RNA processing events across 89 environments in five human cell types and identified 15,300 event shifts (FDR = 15%) comprised of eight event types in over 4,000 genes. Many of these changes occur consistently in the same direction across conditions, indicative of global regulation by trans factors. Accordingly, we demonstrate that environmental modulation of splicing factor binding predicts shifts in intron retention, and that binding of transcription factors predicts shifts in AFE usage in response to specific treatments. We validated the mechanism hypothesized for AFE in two independent datasets. Using ATAC-seq, we found altered binding of 64 factors in response to selenium at sites of AFE shift, including ELF2 and other factors in the ETS family. We also performed AFE QTL mapping in 373 individuals and found an enrichment for SNPs predicted to disrupt binding of the ELF2 factor. Together, these results demonstrate that RNA processing is dramatically changed in response to environmental perturbations through specific mechanisms regulated by trans factors.Author SummaryChanges in a cell’s environment and genetic variation have been shown to impact gene expression. Here, we demonstrate that environmental perturbations also lead to extensive changes in alternative RNA processing across a large number of cellular environments that we investigated. These changes often occur in a non-random manner. For example, many treatments lead to increased intron retention and usage of the downstream first exon. We also show that the changes to first exon usage are likely dependent on changes in transcription factor binding. We provide support for this hypothesis by considering how first exon usage is affected by disruption of binding due to treatment with selenium. We further validate the role of a specific factor by considering the effect of genetic variation in its binding sites on first exon usage. These results help to shed light on the vast number of changes that occur in response to environmental stimuli and will likely aid in understanding the impact of compounds to which we are daily exposed.

scholarly journals Gene expression and survival analysis in cancer research using online open access platforms: a comparative analysis

2020 ◽  
Vol 17 (2) ◽  
pp. 1-19
Author(s):  
Sofia Ramos ◽  
Ana Sofia Fernandes ◽  
Nuno Saraiva
Keyword(s):  
Gene Expression ◽  
Survival Analysis ◽  
Open Access ◽  
Cancer Biology ◽  
Patient Survival ◽  
Statistical Tests ◽  
Expression Patterns ◽  
The Impact ◽  
Tumor Gene Expression ◽  
Tumor Gene

The development of genomics and transcriptomics and the potential associated with sharing data related with cancer, led to a growing understanding of cancer biology and to the identification of new biomarkers. Analysis of tumor gene expression and associated patient survival rate enables the dissection of the impact of certain genes in cancer patient ́s survival. For that purpose, it is essential to choose user-friendly platforms, where it is easy to analyze, compare and collect information for a certain set of genes. The goal of this article is to compare the content and utility of five open access online platforms for tumor gene expression and patient survival analysis from TCGA datasets – cBioPortal, USCS Xena, GEPIA, UALCAN and ONCOLNC. We explore these platforms from the point of view of a lay user, assessing their applicability to study differences in gene expression in tumor vs normal tissues, or according to cancer stage, and the impact of such expression patterns on patient survival. Although all five platforms are very intuitive and access to the data is easy, they vary in the information available, results visualization, and statistical tests performed. Therefore, the choice of a platform must take into account the study goals. For some purposes, a combination of platforms may be required.

scholarly journals Pengaruh Jus Bayam terhadap Peningkatan Kadar Hemoglobin Ibu Hamil Trimester I dan II

2021 ◽  
Vol 8 (2) ◽  
pp. 136-144
Author(s):  
Dian Zuiatna ◽  
Elvi Era Liesmayani ◽  
Reni Julia Tan
Keyword(s):  
Pregnant Women ◽  
Statistical Tests ◽  
Statistical Test ◽  
T Test ◽  
P Value ◽  
Paired Sample ◽  
The One ◽  
The Impact

One of the threats that can harm pregnant women and fetuses is anemia. In Indonesia, in light of the consequences of Riskesdas in 2013, the pervasiveness of weakness in pregnant ladies was 37.1%. The motivation behind this examination was to decide the impact of spinach juice on expanding hemoglobin levels in pregnant ladies in the first and second trimesters at the Niar Pratama center in 2020. The exploration plan in understanding with this investigation was a semi test utilizing the One Group Pretest Posttest approach. The study was conducted in September 2020. The sample in this study was 10 people. Analysis of this statistical test using the t test (Test Paired Sample T Test). The results of this study using statistical tests obtained a p-value of 0.000 <0.05, so that there is an effect between giving spinach juice to increasing hemoglobin levels in pregnant women in the second and second trimesters. In light of the aftereffects of examination on the effect of spinach juice on expanding hemoglobin levels in pregnant ladies in the first and second trimesters at the Niar Pratama Clinic in 2020, explicitly there is an impact between giving spinach juice to increment hemoglobin levels in pregnant ladies.   Keywords: Spinach Juice, Hb, Pregnant Women ABSTRAK   Salah satu ancaman yang dapat membahayakan ibu hamil dan janin adalah anemia. Di Indonesia, berdasarkan hasil Riskesdas tahun 2013, prevalensi anemia pada ibu hamil sebesar 37,1%. Tujuan penelitian ini adalah untuk mengetahui pengaruh jus bayam terhadap peningkatan kadar hemoglobin pada ibu hamil trimester I dan II di Klinik Pratama Niar tahun 2020. Desain penelitian yang sesuai dengan penelitian ini adalah Quasi Eksperimen dengan menggunakan pendekatan One Group Pretest Posttest. Penelitian dilakukan pada bulan September tahun 2020. Sampel  pada penelitian ini yaitu sebanyak 10 orang. Analisa uji statistik ini menggunakan uji t (Uji Paired Sampel T Test).  Hasil dari penelitian ini menggunakan uji statistik didapatkan nilai p-value sebesar 0,000 < 0,05, sehingga ada pengaruh antara pemberian jus bayam terhadap peningkatan kadar hemoglobin pada ibu hamil trimester I dan II. Berdasarkan hasil penelitian mengenai dampak jus bayam terhadap peningkatan kadar hemoglobin pada ibu hamil trimester I dan II di Klinik Pratama Niar tahun 2020, secara spesifik terdapat pengaruh antara pemberian jus bayam untuk meningkatkan kadar hemoglobin pada ibu hamil.   Kata Kunci: Jus Bayam, Hb, Ibu Hamil

scholarly journals The HapMap Resource is Providing New Insights into Ourselves and its Application to Pharmacogenomics

2008 ◽  
Vol 2 ◽  
pp. BBI.S455 ◽  
Author(s):  
Wei Zhang ◽  
Mark J. Ratain ◽  
M. Eileen Dolan
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Drug Response ◽  
Human Populations ◽  
International Hapmap Project ◽  
Hapmap Project ◽  
Phenotypic Data ◽  
Human Lymphoblastoid Cell ◽  
Human Lymphoblastoid Cell Lines ◽  
Japanese Ancestry

The exploration of quantitative variation in complex traits such as gene expression and drug response in human populations has become one of the major priorities for medical genetics. The International HapMap Project provides a key resource of genotypic data on human lymphoblastoid cell lines derived from four major world populations of European, African, Chinese and Japanese ancestry for researchers to associate with various phenotypic data to find genes affecting health, disease and response to drugs. Recent progress in dissecting genetic contribution to natural variation in gene expression within and among human populations and variation in drug response are two examples in which researchers have utilized the HapMap resource. The HapMap Project provides new insights into the human genome and has applicability to pharmacogenomics studies leading to personalized medicine.

scholarly journals Epistatic networks jointly influence phenotypes related to metabolic disease and gene expression in Diversity Outbred mice

2017 ◽  
Author(s):  
Anna L. Tyler ◽  
Bo Ji ◽  
Daniel M. Gatti ◽  
Steven C. Munger ◽  
Gary A. Churchill ◽  
...  
Keyword(s):  
Gene Expression ◽  
Body Composition ◽  
Complex Traits ◽  
Serum Biomarkers ◽  
Physiological Data ◽  
Epistatic Interactions ◽  
Multi Scale ◽  
Diversity Outbred ◽  
Trait Variance ◽  
Outbred Mice

ABSTRACTGenetic studies of multidimensional phenotypes can potentially link genetic variation, gene expression, and physiological data to create multi-scale models of complex traits. Multi-parent populations provide a resource for developing methods to understand these relationships. In this study, we simultaneously modeled body composition, serum biomarkers, and liver transcript abundances from 474 Diversity Outbred mice. This population contained both sexes and two dietary cohorts. Using weighted gene co-expression network analysis (WGCNA), we summarized transcript data into functional modules which we then used as summary phenotypes representing enriched biological processes. These module phenotypes were jointly analyzed with body composition and serum biomarkers in a combined analysis of pleiotropy and epistasis (CAPE), which inferred networks of epistatic interactions between quantitative trait loci that affect one or more traits. This network frequently mapped interactions between alleles of different ancestries, providing evidence of both genetic synergy and redundancy between haplotypes. Furthermore, a number of loci interacted with sex and diet to yield sex-specific genetic effects. We were also able to identify alleles that potentially protect individuals from the effects of a high-fat diet. Although the epistatic interactions explained small amounts of trait variance, the combination of directional interactions, allelic specificity, and high genomic resolution provided context to generate hypotheses for the roles of specific genes in complex traits. Our approach moves beyond the cataloging of single loci to infer genetic networks that map genetic etiology by simultaneously modeling all phenotypes.

scholarly journals A systematic review of the statistical scope of restoration ecology of invaded grassland ecosystems

2014 ◽  
Author(s):  
Amanda R Liczner
Keyword(s):  
Systematic Review ◽  
Impact Factor ◽  
Sample Size ◽  
Restoration Ecology ◽  
Statistical Tests ◽  
Citation Rate ◽  
Statistical Test ◽  
Experimental Designs ◽  
The Impact ◽  
Journal Impact

Restoration ecology is a rapidly growing field of research. The statistical analyses and experimental designs used in this field have likely also expanded. In this review, the statistical scope of the restoration ecology of invaded grasslands will be investigated. A systematic review was conducted on 103 articles to examine the types of statistical tests used and how they changed over time, if assumptions are tested, and how the number of statistical tests and the experimental design influence both the citation rate of articles and the impact factor of journals where these articles are published. ANOVAs have consistently been the dominant test. Statistical test diversity has increased since the year 2000. Most articles did test the assumptions of statistical analyses. The number of tests, and sample size of experiments are both positively correlated with the average citation rate of articles and the impact factor of the journal while the number of factors was negatively correlated. GLMs are recommended as a statistical test to be used more frequently in the future over ANOVAs. There is room for improvement in terms of reporting statistics accurately, including testing assumptions. When possible, sample sizes should be increased to both increase the quality of data, and the citation rate and the journal impact where articles are published. When possible and appropriate, sample sizes and the number of statistical tests should be increased. Adding factors in experimental designs should only be done so without compromising sample size as it has been shown to hinder the citation rate and journal impact.

scholarly journals Impact of polymorphic transposable elements on transcription in lymphoblastoid cell lines from public data

2019 ◽  
Vol 20 (S9) ◽  
Author(s):  
Giovanni Spirito ◽  
Damiano Mangoni ◽  
Remo Sanges ◽  
Stefano Gustincich
Keyword(s):  
Gene Expression ◽  
Transposable Elements ◽  
Cell Lines ◽  
Dna Sequences ◽  
Host Genome ◽  
Human Populations ◽  
Lymphoblastoid Cell Lines ◽  
Structural Variants ◽  
Public Data ◽  
The Impact

Abstract Background Transposable elements (TEs) are DNA sequences able to mobilize themselves and to increase their copy-number in the host genome. In the past, they have been considered mainly selfish DNA without evident functions. Nevertheless, currently they are believed to have been extensively involved in the evolution of primate genomes, especially from a regulatory perspective. Due to their recent activity they are also one of the primary sources of structural variants (SVs) in the human genome. By taking advantage of sequencing technologies and bioinformatics tools, recent surveys uncovered specific TE structural variants (TEVs) that gave rise to polymorphisms in human populations. When combined with RNA-seq data this information provides the opportunity to study the potential impact of TEs on gene expression in human. Results In this work, we assessed the effects of the presence of specific TEs in cis on the expression of flanking genes by producing associations between polymorphic TEs and flanking gene expression levels in human lymphoblastoid cell lines. By using public data from the 1000 Genome Project and the Geuvadis consortium, we exploited an expression quantitative trait loci (eQTL) approach integrated with additional bioinformatics data mining analyses. We uncovered human loci enriched for common, less common and rare TEVs and identified 323 significant TEV-cis-eQTL associations. SINE-R/VNTR/Alus (SVAs) resulted the TE class with the strongest effects on gene expression. We also unveiled differential functional enrichments on genes associated to TEVs, genes associated to TEV-cis-eQTLs and genes associated to the genomic regions mostly enriched in TEV-cis-eQTLs highlighting, at multiple levels, the impact of TEVs on the host genome. Finally, we also identified polymorphic TEs putatively embedded in transcriptional units, proposing a novel mechanism in which TEVs may mediate individual-specific traits. Conclusion We contributed to unveiling the effect of polymorphic TEs on transcription in lymphoblastoid cell lines.

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