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Wolf S, Melo D, Garske KM, Pallares LF, Lea AJ, Ayroles JF. Characterizing the landscape of gene expression variance in humans. PLoS Genet 2023; 19:e1010833. [PMID: 37410774 DOI: 10.1371/journal.pgen.1010833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 06/15/2023] [Indexed: 07/08/2023] Open
Abstract
Gene expression variance has been linked to organismal function and fitness but remains a commonly neglected aspect of molecular research. As a result, we lack a comprehensive understanding of the patterns of transcriptional variance across genes, and how this variance is linked to context-specific gene regulation and gene function. Here, we use 57 large publicly available RNA-seq data sets to investigate the landscape of gene expression variance. These studies cover a wide range of tissues and allowed us to assess if there are consistently more or less variable genes across tissues and data sets and what mechanisms drive these patterns. We show that gene expression variance is broadly similar across tissues and studies, indicating that the pattern of transcriptional variance is consistent. We use this similarity to create both global and within-tissue rankings of variation, which we use to show that function, sequence variation, and gene regulatory signatures contribute to gene expression variance. Low-variance genes are associated with fundamental cell processes and have lower levels of genetic polymorphisms, have higher gene-gene connectivity, and tend to be associated with chromatin states associated with transcription. In contrast, high-variance genes are enriched for genes involved in immune response, environmentally responsive genes, immediate early genes, and are associated with higher levels of polymorphisms. These results show that the pattern of transcriptional variance is not noise. Instead, it is a consistent gene trait that seems to be functionally constrained in human populations. Furthermore, this commonly neglected aspect of molecular phenotypic variation harbors important information to understand complex traits and disease.
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Affiliation(s)
- Scott Wolf
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
| | - Diogo Melo
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | - Kristina M Garske
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
| | - Luisa F Pallares
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
- Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany
| | - Amanda J Lea
- Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States of America
- Child and Brain Development, Canadian Institute for Advanced Research, Toronto, Canada
| | - Julien F Ayroles
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
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Pettersson ME, Carlborg O. Capacitating epistasis--detection and role in the genetic architecture of complex traits. Methods Mol Biol 2015; 1253:185-196. [PMID: 25403533 DOI: 10.1007/978-1-4939-2155-3_10] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Here, we discuss the potential role of capacitating epistasis in the genetic architecture of complex traits. Two alternative methods for identifying such gene-gene interactions in genetic association studies-mapping of variance controlling loci and the variance plane ratio (VPR) method-are introduced. An overview of the theoretical foundation of the methods is presented together with a discussion on their implementation and available software for performing these analyses. We conclude by highlighting a few examples of capacitating epistasis described in the literature and its potential impacts on the genetics of complex traits.
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Affiliation(s)
- Mats E Pettersson
- Division of Computational Genetics, Department of Clinical Sciences, Swedish University of Agricultural Sciences, Box 7078, SE-750 07, Uppsala, Sweden
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Shen X, De Jonge J, Forsberg SKG, Pettersson ME, Sheng Z, Hennig L, Carlborg Ö. Natural CMT2 variation is associated with genome-wide methylation changes and temperature seasonality. PLoS Genet 2014; 10:e1004842. [PMID: 25503602 PMCID: PMC4263395 DOI: 10.1371/journal.pgen.1004842] [Citation(s) in RCA: 96] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2014] [Accepted: 10/21/2014] [Indexed: 12/30/2022] Open
Abstract
As Arabidopsis thaliana has colonized a wide range of habitats across the world it is an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we used public data from two collections of A. thaliana accessions to associate genetic variability at individual loci with differences in climates at the sampling sites. We use a novel method to screen the genome for plastic alleles that tolerate a broader climate range than the major allele. This approach reduces confounding with population structure and increases power compared to standard genome-wide association methods. Sixteen novel loci were found, including an association between Chromomethylase 2 (CMT2) and temperature seasonality where the genome-wide CHH methylation was different for the group of accessions carrying the plastic allele. Cmt2 mutants were shown to be more tolerant to heat-stress, suggesting genetic regulation of epigenetic modifications as a likely mechanism underlying natural adaptation to variable temperatures, potentially through differential allelic plasticity to temperature-stress.
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Affiliation(s)
- Xia Shen
- Swedish University of Agricultural Sciences, Department of Clinical Sciences, Division of Computational Genetics, Uppsala, Sweden
- Karolinska Institutet, Department of Medical Epidemiology and Biostatistics, Stockholm, Sweden
- University of Edinburgh, MRC Institute of Genetics and Molecular Medicine, MRC Human Genetics Unit, Edinburgh, United Kingdom
| | - Jennifer De Jonge
- Swedish University of Agricultural Sciences, Department of Plant Biology, Uppsala, Sweden
| | - Simon K. G. Forsberg
- Swedish University of Agricultural Sciences, Department of Clinical Sciences, Division of Computational Genetics, Uppsala, Sweden
| | - Mats E. Pettersson
- Swedish University of Agricultural Sciences, Department of Clinical Sciences, Division of Computational Genetics, Uppsala, Sweden
| | - Zheya Sheng
- Swedish University of Agricultural Sciences, Department of Clinical Sciences, Division of Computational Genetics, Uppsala, Sweden
| | - Lars Hennig
- Swedish University of Agricultural Sciences, Department of Plant Biology, Uppsala, Sweden
| | - Örjan Carlborg
- Swedish University of Agricultural Sciences, Department of Clinical Sciences, Division of Computational Genetics, Uppsala, Sweden
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Lee CR, Anderson JT, Mitchell-Olds T. Unifying genetic canalization, genetic constraint, and genotype-by-environment interaction: QTL by genomic background by environment interaction of flowering time in Boechera stricta. PLoS Genet 2014; 10:e1004727. [PMID: 25340779 PMCID: PMC4207664 DOI: 10.1371/journal.pgen.1004727] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2014] [Accepted: 09/02/2014] [Indexed: 01/01/2023] Open
Abstract
Natural populations exhibit substantial variation in quantitative traits. A quantitative trait is typically defined by its mean and variance, and to date most genetic mapping studies focus on loci altering trait means but not (co)variances. For single traits, the control of trait variance across genetic backgrounds is referred to as genetic canalization. With multiple traits, the genetic covariance among different traits in the same environment indicates the magnitude of potential genetic constraint, while genotype-by-environment interaction (GxE) concerns the same trait across different environments. While some have suggested that these three attributes of quantitative traits are different views of similar concepts, it is not yet clear, however, whether they have the same underlying genetic mechanism. Here, we detect quantitative trait loci (QTL) influencing the (co)variance of phenological traits in six distinct environments in Boechera stricta, a close relative of Arabidopsis. We identified nFT as the QTL altering the magnitude of phenological trait canalization, genetic constraint, and GxE. Both the magnitude and direction of nFT's canalization effects depend on the environment, and to our knowledge, this reversibility of canalization across environments has not been reported previously. nFT's effects on trait covariance structure (genetic constraint and GxE) likely result from the variable and reversible canalization effects across different traits and environments, which can be explained by the interaction among nFT, genomic backgrounds, and environmental stimuli. This view is supported by experiments demonstrating significant nFT by genomic background epistatic interactions affecting phenological traits and expression of the candidate gene, FT. In contrast to the well-known canalization gene Hsp90, the case of nFT may exemplify an alternative mechanism: Our results suggest that (at least in traits with major signal integrators such as flowering time) genetic canalization, genetic constraint, and GxE may have related genetic mechanisms resulting from interactions among major QTL, genomic backgrounds, and environments.
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Affiliation(s)
- Cheng-Ruei Lee
- Department of Biology, Duke University, Durham, North Carolina, United States of America
| | - Jill T. Anderson
- Department of Biological Sciences, Environment and Sustainability Program, University of South Carolina, Columbia, South Carolina, United States of America
| | - Thomas Mitchell-Olds
- Department of Biology, Duke University, Durham, North Carolina, United States of America
- Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina, United States of America
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Moore BD, Andrew RL, Külheim C, Foley WJ. Explaining intraspecific diversity in plant secondary metabolites in an ecological context. THE NEW PHYTOLOGIST 2014; 201:733-750. [PMID: 24117919 DOI: 10.1111/nph.12526] [Citation(s) in RCA: 243] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2013] [Accepted: 08/22/2013] [Indexed: 05/10/2023]
Abstract
Plant secondary metabolites (PSMs) are ubiquitous in plants and play many ecological roles. Each compound can vary in presence and/or quantity, and the composition of the mixture of chemicals can vary, such that chemodiversity can be partitioned within and among individuals. Plant ontogeny and environmental and genetic variation are recognized as sources of chemical variation, but recent advances in understanding the molecular basis of variation may allow the future deployment of isogenic mutants to test the specific adaptive function of variation in PSMs. An important consequence of high intraspecific variation is the capacity to evolve rapidly. It is becoming increasingly clear that trait variance linked to both macro- and micro-environmental variation can also evolve and may respond more strongly to selection than mean trait values. This research, which is in its infancy in plants, highlights what could be a missing piece of the picture of PSM evolution. PSM polymorphisms are probably maintained by multiple selective forces acting across many spatial and temporal scales, but convincing examples that recognize the diversity of plant population structures are rare. We describe how diversity can be inherently beneficial for plants and suggest fruitful avenues for future research to untangle the causes and consequences of intraspecific variation.
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Affiliation(s)
- Ben D Moore
- Hawkesbury Institute for the Environment, University of Western Sydney, Locked Bag 1797, Penrith, 2751, NSW, Australia
| | - Rose L Andrew
- Department of Botany, University of British Columbia, 3529-6270 University Blvd, Vancouver, BC, V6T 1Z4, Canada
| | - Carsten Külheim
- Research School of Biology, Australian National University, Canberra, 0200, ACT, Australia
| | - William J Foley
- Research School of Biology, Australian National University, Canberra, 0200, ACT, Australia
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Nelson RM, Pettersson ME, Carlborg Ö. A century after Fisher: time for a new paradigm in quantitative genetics. Trends Genet 2013; 29:669-76. [PMID: 24161664 DOI: 10.1016/j.tig.2013.09.006] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2013] [Revised: 09/17/2013] [Accepted: 09/19/2013] [Indexed: 10/26/2022]
Abstract
Quantitative genetics traces its roots back through more than a century of theory, largely formed in the absence of directly observable genotype data, and has remained essentially unchanged for decades. By contrast, molecular genetics arose from direct observations and is currently undergoing rapid changes, making the amount of available data ever greater. Thus, the two disciplines are disparate both in their origins and their current states, yet they address the same fundamental question: how does the genotype affect the phenotype? The rapidly accumulating genomic data necessitate sophisticated analysis, but many of the current tools are adaptations of methods designed during the early days of quantitative genetics. We argue here that the present analysis paradigm in quantitative genetics is at its limits in regards to unraveling complex traits and it is necessary to re-evaluate the direction that genetic research is taking for the field to realize its full potential.
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Affiliation(s)
- Ronald M Nelson
- Swedish University of Agricultural Sciences, Department of Clinical Sciences, Division of Computational Genetics, Box 7078, SE-750 07 Uppsala, Sweden.
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Korte A, Farlow A. The advantages and limitations of trait analysis with GWAS: a review. PLANT METHODS 2013; 9:29. [PMID: 23876160 PMCID: PMC3750305 DOI: 10.1186/1746-4811-9-29] [Citation(s) in RCA: 790] [Impact Index Per Article: 71.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2013] [Accepted: 06/13/2013] [Indexed: 05/17/2023]
Abstract
Over the last 10 years, high-density SNP arrays and DNA re-sequencing have illuminated the majority of the genotypic space for a number of organisms, including humans, maize, rice and Arabidopsis. For any researcher willing to define and score a phenotype across many individuals, Genome Wide Association Studies (GWAS) present a powerful tool to reconnect this trait back to its underlying genetics. In this review we discuss the biological and statistical considerations that underpin a successful analysis or otherwise. The relevance of biological factors including effect size, sample size, genetic heterogeneity, genomic confounding, linkage disequilibrium and spurious association, and statistical tools to account for these are presented. GWAS can offer a valuable first insight into trait architecture or candidate loci for subsequent validation.
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Affiliation(s)
- Arthur Korte
- Gregor Mendel Institute of Molecular Plant Biology, Vienna, Austria
| | - Ashley Farlow
- Gregor Mendel Institute of Molecular Plant Biology, Vienna, Austria
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