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Noble LM, Chelo I, Guzella T, Afonso B, Riccardi DD, Ammerman P, Dayarian A, Carvalho S, Crist A, Pino-Querido A, Shraiman B, Rockman MV, Teotónio H. Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel. Genetics 2017; 207:1663-1685. [PMID: 29066469 PMCID: PMC5714472 DOI: 10.1534/genetics.117.300406] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 10/10/2017] [Indexed: 01/27/2023] Open
Abstract
Understanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity, and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty can be problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here, we report an advanced recombinant inbred line (RIL) quantitative trait locus mapping panel for the hermaphroditic nematode Caenorhabditis elegans, the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs at present, was created by hybridization of 16 wild isolates, experimental evolution for 140-190 generations, and inbreeding by selfing for 13-16 generations. The panel contains 22% of single-nucleotide polymorphisms known to segregate in natural populations, and complements existing C. elegans mapping resources by providing fine resolution and high nucleotide diversity across > 95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad-sense heritability in the CeMEE. While simulations show that we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits do not feature such alleles. We instead find that a significant fraction of trait variance, approaching 40% for fertility, can be explained by sign epistasis with main effects below the detection limit. In congruence, phenotype prediction from genomic similarity, while generally poor ([Formula: see text]), requires modeling epistasis for optimal accuracy, with most variance attributed to the rapidly evolving chromosome arms.
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Affiliation(s)
- Luke M Noble
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York 10003
| | - Ivo Chelo
- Instituto Gulbenkian de Ciência, P-2781-901 Oeiras, Portugal
| | - Thiago Guzella
- Institut de Biologie, École Normale Supérieure, Centre National de la Recherche Scientifique (CNRS) UMR 8197, Institut National de la Santé et de la Recherche Médicale (INSERM) U1024, F-75005 Paris, France
| | - Bruno Afonso
- Instituto Gulbenkian de Ciência, P-2781-901 Oeiras, Portugal
- Institut de Biologie, École Normale Supérieure, Centre National de la Recherche Scientifique (CNRS) UMR 8197, Institut National de la Santé et de la Recherche Médicale (INSERM) U1024, F-75005 Paris, France
| | - David D Riccardi
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York 10003
| | - Patrick Ammerman
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York 10003
| | - Adel Dayarian
- Kavli Institute for Theoretical Physics, University of California, Santa Barbara, California 93106
| | - Sara Carvalho
- Instituto Gulbenkian de Ciência, P-2781-901 Oeiras, Portugal
| | - Anna Crist
- Institut de Biologie, École Normale Supérieure, Centre National de la Recherche Scientifique (CNRS) UMR 8197, Institut National de la Santé et de la Recherche Médicale (INSERM) U1024, F-75005 Paris, France
| | | | - Boris Shraiman
- Kavli Institute for Theoretical Physics, University of California, Santa Barbara, California 93106
- Department of Physics, University of California, Santa Barbara, California 93106
| | - Matthew V Rockman
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York 10003
| | - Henrique Teotónio
- Institut de Biologie, École Normale Supérieure, Centre National de la Recherche Scientifique (CNRS) UMR 8197, Institut National de la Santé et de la Recherche Médicale (INSERM) U1024, F-75005 Paris, France
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Teotónio H, Estes S, Phillips PC, Baer CF. Experimental Evolution with Caenorhabditis Nematodes. Genetics 2017; 206:691-716. [PMID: 28592504 PMCID: PMC5499180 DOI: 10.1534/genetics.115.186288] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2016] [Accepted: 03/07/2017] [Indexed: 12/17/2022] Open
Abstract
The hermaphroditic nematode Caenorhabditis elegans has been one of the primary model systems in biology since the 1970s, but only within the last two decades has this nematode also become a useful model for experimental evolution. Here, we outline the goals and major foci of experimental evolution with C. elegans and related species, such as C. briggsae and C. remanei, by discussing the principles of experimental design, and highlighting the strengths and limitations of Caenorhabditis as model systems. We then review three exemplars of Caenorhabditis experimental evolution studies, underlining representative evolution experiments that have addressed the: (1) maintenance of genetic variation; (2) role of natural selection during transitions from outcrossing to selfing, as well as the maintenance of mixed breeding modes during evolution; and (3) evolution of phenotypic plasticity and its role in adaptation to variable environments, including host-pathogen coevolution. We conclude by suggesting some future directions for which experimental evolution with Caenorhabditis would be particularly informative.
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Affiliation(s)
- Henrique Teotónio
- Institut de Biologie de l´École Normale Supérieure (IBENS), Institut National de la Santé et de la Recherche Médicale U1024, Centre Nationnal de la Recherche Scientifique Unité Mixte de Recherche 8197, Paris Sciences et Lettres Research University, 75005 Paris, France
| | - Suzanne Estes
- Department of Biology, Portland State University, Oregon 97201
| | - Patrick C Phillips
- Institute of Ecology and Evolution, 5289 University of Oregon, Eugene, Oregon 97403, and
| | - Charles F Baer
- Department of Biology, and
- University of Florida Genetics Institute, University of Florida, Gainesville, Florida 32611
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Davies SK, Leroi A, Burt A, Bundy JG, Baer CF. The mutational structure of metabolism in Caenorhabditis elegans. Evolution 2016; 70:2239-2246. [PMID: 27465022 PMCID: PMC5050113 DOI: 10.1111/evo.13020] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2015] [Revised: 06/27/2016] [Accepted: 07/10/2016] [Indexed: 12/14/2022]
Abstract
A properly functioning organism must maintain metabolic homeostasis. Deleterious mutations degrade organismal function, presumably at least in part via effects on metabolic function. Here we present an initial investigation into the mutational structure of the Caenorhabditis elegans metabolome by means of a mutation accumulation experiment. We find that pool sizes of 29 metabolites vary greatly in their vulnerability to mutation, both in terms of the rate of accumulation of genetic variance (the mutational variance, VM) and the rate of change of the trait mean (the mutational bias, ΔM). Strikingly, some metabolites are much more vulnerable to mutation than any other trait previously studied in the same way. Although we cannot statistically assess the strength of mutational correlations between individual metabolites, principal component analysis provides strong evidence that some metabolite pools are genetically correlated, but also that there is substantial scope for independent evolution of different groups of metabolites. Averaged over mutation accumulation lines, PC3 is positively correlated with relative fitness, but a model in which metabolites are uncorrelated with fitness is nearly as good by Akaike's Information Criterion.
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Affiliation(s)
- Sarah K Davies
- Department of Life Sciences, Imperial College London, United Kingdom
- Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Armand Leroi
- Department of Life Sciences, Imperial College London, United Kingdom
| | - Austin Burt
- Department of Life Sciences, Imperial College London, United Kingdom
| | - Jacob G Bundy
- Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Charles F Baer
- Department of Biology, University of Florida, Gainesville, Florida.
- Genetics Institute, University of Florida, Gainesville, Florida.
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Mutation Is a Sufficient and Robust Predictor of Genetic Variation for Mitotic Spindle Traits in Caenorhabditis elegans. Genetics 2016; 203:1859-70. [PMID: 27334268 DOI: 10.1534/genetics.115.185736] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2015] [Accepted: 06/13/2016] [Indexed: 12/24/2022] Open
Abstract
Different types of phenotypic traits consistently exhibit different levels of genetic variation in natural populations. There are two potential explanations: Either mutation produces genetic variation at different rates or natural selection removes or promotes genetic variation at different rates. Whether mutation or selection is of greater general importance is a longstanding unresolved question in evolutionary genetics. We report mutational variances (VM) for 19 traits related to the first mitotic cell division in Caenorhabditis elegans and compare them to the standing genetic variances (VG) for the same suite of traits in a worldwide collection C. elegans Two robust conclusions emerge. First, the mutational process is highly repeatable: The correlation between VM in two independent sets of mutation accumulation lines is ∼0.9. Second, VM for a trait is a good predictor of VG for that trait: The correlation between VM and VG is ∼0.9. This result is predicted for a population at mutation-selection balance; it is not predicted if balancing selection plays a primary role in maintaining genetic variation.
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