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Khosrovyan A, Doria HB, Kahru A, Pfenninger M. Polyamide microplastic exposure elicits rapid, strong and genome-wide evolutionary response in the freshwater non-biting midge Chironomus riparius. CHEMOSPHERE 2022; 299:134452. [PMID: 35367228 DOI: 10.1016/j.chemosphere.2022.134452] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 03/20/2022] [Accepted: 03/25/2022] [Indexed: 06/14/2023]
Abstract
Susceptibility to hazardous materials and contamination is largely determined by genetic make-up and evolutionary history of affected organisms. Yet evolutionary adaptation and microevolutionary processes triggered by contaminants are rarely considered in ecotoxicology. Using an evolve and resequencing approach, we investigated genome-wide responses of the midge C. riparius exposed to virgin polyamide microplastics (0-180 μm size range, at concentration 1 g kg-1) during seven consecutive generations. The results were integrated to a parallel life-cycle experiment ran under the same exposure conditions. Emergence, life-cycle trait, showed first a substantial reduction in larval survival, followed by a rapid recovery within three generations. On the genomic level, we observed substantial selectively driven allele frequency changes (mean 0.566 ± 0.0879) within seven generations, associated with a mean selection coefficient of 0.322, indicating very strong selection pressure. Putative selection targets were mainly connected to oxidative stress in the microplastics exposed C. riparius population. This is the first multigenerational study on chironomids to provide evidence that upon exposure to polyamide microplastic there are changes on the genomic level, providing basis to rapid adaptation of aquatic organisms to microplastics.
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Affiliation(s)
- Alla Khosrovyan
- National Institute of Chemical Physics and Biophysics, Laboratory of Environmental Toxicology, 23 Akadeemia Tee, 12618, Tallinn, Estonia.
| | - Halina Binde Doria
- Dept. Molecular Ecology, Senckenberg Biodiversity and Climate Research Centre, Georg-Voigt-Str. 14-16, D-60325, Frankfurt am Main, Germany; LOEWE Centre for Translational Biodiversity Genomics, Senckenberg Biodiversity and Climate Research Centre, Senckenberganlage 25, 60325, Frankfurt am Main, Germany.
| | - Anne Kahru
- National Institute of Chemical Physics and Biophysics, Laboratory of Environmental Toxicology, 23 Akadeemia Tee, 12618, Tallinn, Estonia; Estonian Academy of Sciences, 6 Kohtu, 10130, Tallinn, Estonia
| | - Markus Pfenninger
- Dept. Molecular Ecology, Senckenberg Biodiversity and Climate Research Centre, Georg-Voigt-Str. 14-16, D-60325, Frankfurt am Main, Germany; LOEWE Centre for Translational Biodiversity Genomics, Senckenberg Biodiversity and Climate Research Centre, Senckenberganlage 25, 60325, Frankfurt am Main, Germany; Institute for Molecular and Organismic Evolution, Johannes Gutenberg University, Johann-Joachim-Becher-Weg 7, 55128, Mainz, Germany
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2
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McHugh KM, Burke MK. From microbes to mammals: The experimental evolution of aging and longevity across species. Evolution 2022; 76:692-707. [PMID: 35112358 DOI: 10.1111/evo.14442] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/09/2021] [Accepted: 12/01/2021] [Indexed: 01/21/2023]
Abstract
Senescence, the functional deterioration of cells or organisms associated with increased age, is pervasive across the tree of life. Yet our understanding of the genetic and physiological basis underlying age-related declines in health and reproduction remains limited. Experimental evolution allows empirical examination of the question of why aging occurs; imposing selection for age-specific fitness traits shifts patterns of aging in experimental populations, enabling investigations of the variation underlying senescence and the mechanisms governing it. Whole-genome sequencing of experimentally evolved populations may reveal candidate genomic variants underlying particular aging patterns; unfortunately, most study systems suffer from limitations that weaken associations between genotypes and phenotypes. In this review, we provide a survey of experimental evolution studies that have altered population-level patterns of reproductive timing and senescence in a variety of species. We discuss the specific selection conditions that have increased longevity, the phenotypic responses and trade-offs that accompany these increases, and examine genomic data collected from these experiments. Additionally, we consider how selected field studies complement laboratory experiments on life-history evolution. Finally, we address the strengths and weaknesses of existing study systems, and evaluate which model organisms appear most promising for future genomic investigations of the evolutionary biology of aging.
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Affiliation(s)
- Kaitlin M McHugh
- Department of Integrative Biology, Oregon State University, Corvallis, Oregon, 97331
| | - Molly K Burke
- Department of Integrative Biology, Oregon State University, Corvallis, Oregon, 97331
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Galewski P, Funk A, McGrath JM. Select and Sequence of a Segregating Sugar Beet Population Provides Genomic Perspective of Host Resistance to Seedling Rhizoctonia solani Infection. FRONTIERS IN PLANT SCIENCE 2022; 12:785267. [PMID: 35095959 PMCID: PMC8793884 DOI: 10.3389/fpls.2021.785267] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/12/2021] [Indexed: 05/15/2023]
Abstract
Understanding the genetic basis of polygenic traits is a major challenge in agricultural species, especially in non-model systems. Select and sequence (SnS) experiments carried out within existing breeding programs provide a means to simultaneously identify the genomic background of a trait while improving the mean phenotype for a population. Using pooled whole genome sequencing (WGS) of selected and unselected bulks derived from a synthetic outcrossing sugar beet population EL57 (PI 663212), which segregates for seedling rhizoctonia resistance, we identified a putative genomic background involved in conditioning a resistance phenotype. Population genomic parameters were estimated to measure fixation (He), genome divergence (F ST ), and allele frequency changes between bulks (DeltaAF). We report on the genome wide patterns of variation resulting from selection and highlight specific genomic features associated with resistance. Expected heterozygosity (He) showed an increased level of fixation in the resistant bulk, indicating a greater selection pressure was applied. In total, 1,311 biallelic loci were detected as significant FST outliers (p < 0.01) in comparisons between the resistant and susceptible bulks. These loci were detected in 206 regions along the chromosomes and contained 275 genes. We estimated changes in allele frequency between bulks resulting from selection for resistance by leveraging the allele frequencies of an unselected bulk. DeltaAF was a more stringent test of selection and recovered 186 significant loci, representing 32 genes, all of which were also detected using FST. Estimates of population genetic parameters and statistical significance were visualized with respect to the EL10.2 physical map and produced a candidate gene list that was enriched for function in cell wall metabolism and plant disease resistance, including pathogen perception, signal transduction, and pathogen response. Specific variation associated with these genes was also reported and represents genetic markers for validation and prediction of resistance to Rhizoctonia. Select and sequence experiments offer a means to characterize the genetic base of sugar beet, inform selection within breeding programs, and prioritize candidate variation for functional studies.
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Affiliation(s)
- Paul Galewski
- United States Department of Agriculture – Agricultural Research Service (USDA-ARS) Northwest Irrigation and Soils Research Laboratory, Kimberly, ID, United States
- Department of Plant, Soil, and Microbial Science, Plant Breeding, Genetics, and Biotechnology Program, Michigan State University, East Lansing, MI, United States
| | - Andrew Funk
- Department of Plant, Soil, and Microbial Science, Plant Breeding, Genetics, and Biotechnology Program, Michigan State University, East Lansing, MI, United States
- United States Department of Agriculture – National Institute of Food and Agriculture (USDA-NIFA) Institute of Food Production and Sustainability, Kansas City, MO, United States
| | - J. Mitchell McGrath
- United States Department of Agriculture – Agricultural Research Service (USDA-ARS) Sugar Beet and Bean Research Unit USDA-ARS, East Lansing, MI, United States
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4
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Albecker MA, Wilkins LGE, Krueger-Hadfield SA, Bashevkin SM, Hahn MW, Hare MP, Kindsvater HK, Sewell MA, Lotterhos KE, Reitzel AM. Does a complex life cycle affect adaptation to environmental change? Genome-informed insights for characterizing selection across complex life cycle. Proc Biol Sci 2021; 288:20212122. [PMID: 34847763 PMCID: PMC8634620 DOI: 10.1098/rspb.2021.2122] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Complex life cycles, in which discrete life stages of the same organism differ in form or function and often occupy different ecological niches, are common in nature. Because stages share the same genome, selective effects on one stage may have cascading consequences through the entire life cycle. Theoretical and empirical studies have not yet generated clear predictions about how life cycle complexity will influence patterns of adaptation in response to rapidly changing environments or tested theoretical predictions for fitness trade-offs (or lack thereof) across life stages. We discuss complex life cycle evolution and outline three hypotheses—ontogenetic decoupling, antagonistic ontogenetic pleiotropy and synergistic ontogenetic pleiotropy—for how selection may operate on organisms with complex life cycles. We suggest a within-generation experimental design that promises significant insight into composite selection across life cycle stages. As part of this design, we conducted simulations to determine the power needed to detect selection across a life cycle using a population genetic framework. This analysis demonstrated that recently published studies reporting within-generation selection were underpowered to detect small allele frequency changes (approx. 0.1). The power analysis indicates challenging but attainable sampling requirements for many systems, though plants and marine invertebrates with high fecundity are excellent systems for exploring how organisms with complex life cycles may adapt to climate change.
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Affiliation(s)
- Molly A Albecker
- Department of Biology, Utah State University, Logan, UT 84321, USA
| | - Laetitia G E Wilkins
- Max Planck Institute for Marine Microbiology (MPIMM), Celsiusstrasse 1, 28209 Bremen, Germany
| | - Stacy A Krueger-Hadfield
- Department of Biology, University of Alabama at Birmingham, 1300 University Blvd, Birmingham, AL 35294, USA
| | - Samuel M Bashevkin
- Delta Science Program, Delta Stewardship Council, 715 P Street 15-300, Sacramento, CA 95814, USA
| | - Matthew W Hahn
- Department of Biology and Department of Computer Science, Indiana University, 1001 E. 3rd St., Bloomington, IN 47405, USA
| | - Matthew P Hare
- Department of Natural Resources and the Environment, Cornell University, 205 Fernow Hall, Ithaca, NY 14853, USA
| | - Holly K Kindsvater
- Department of Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
| | - Mary A Sewell
- School of Biological Sciences, University of Auckland, Auckland 1010, New Zealand
| | - Katie E Lotterhos
- Northeastern University Marine Science Center, 430 Nahant Rd., Nahant, MA 01918, USA
| | - Adam M Reitzel
- University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223, USA
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5
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Burny C, Nolte V, Dolezal M, Schlötterer C. Highly Parallel Genomic Selection Response in Replicated Drosophila melanogaster Populations with Reduced Genetic Variation. Genome Biol Evol 2021; 13:evab239. [PMID: 34694407 PMCID: PMC8599828 DOI: 10.1093/gbe/evab239] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/21/2021] [Indexed: 12/12/2022] Open
Abstract
Many adaptive traits are polygenic and frequently more loci contributing to the phenotype are segregating than needed to express the phenotypic optimum. Experimental evolution with replicated populations adapting to a new controlled environment provides a powerful approach to study polygenic adaptation. Because genetic redundancy often results in nonparallel selection responses among replicates, we propose a modified evolve and resequence (E&R) design that maximizes the similarity among replicates. Rather than starting from many founders, we only use two inbred Drosophila melanogaster strains and expose them to a very extreme, hot temperature environment (29 °C). After 20 generations, we detect many genomic regions with a strong, highly parallel selection response in 10 evolved replicates. The X chromosome has a more pronounced selection response than the autosomes, which may be attributed to dominance effects. Furthermore, we find that the median selection coefficient for all chromosomes is higher in our two-genotype experiment than in classic E&R studies. Because two random genomes harbor sufficient variation for adaptive responses, we propose that this approach is particularly well-suited for the analysis of polygenic adaptation.
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Affiliation(s)
- Claire Burny
- Institut für Populationsgenetik, Vetmeduni Vienna, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Austria
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Austria
| | - Marlies Dolezal
- Plattform Bioinformatik und Biostatistik, Vetmeduni Vienna, Wien, Austria
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Langmüller AM, Dolezal M, Schlötterer C. Fine Mapping without Phenotyping: Identification of Selection Targets in Secondary Evolve and Resequence Experiments. Genome Biol Evol 2021; 13:6311659. [PMID: 34190980 PMCID: PMC8358229 DOI: 10.1093/gbe/evab154] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/24/2021] [Indexed: 12/19/2022] Open
Abstract
Evolve and Resequence (E&R) studies investigate the genomic selection response of populations in an Experimental Evolution setup. Despite the popularity of E&R, empirical studies in sexually reproducing organisms typically suffer from an excess of candidate loci due to linkage disequilibrium, and single gene or SNP resolution is the exception rather than the rule. Recently, so-called "secondary E&R" has been suggested as promising experimental follow-up procedure to confirm putatively selected regions from a primary E&R study. Secondary E&R provides also the opportunity to increase mapping resolution by allowing for additional recombination events, which separate the selection target from neutral hitchhikers. Here, we use computer simulations to assess the effect of different crossing schemes, population size, experimental duration, and number of replicates on the power and resolution of secondary E&R. We find that the crossing scheme and population size are crucial factors determining power and resolution of secondary E&R: A simple crossing scheme with few founder lines consistently outcompetes crossing schemes where evolved populations from a primary E&R experiment are mixed with a complex ancestral founder population. Regardless of the experimental design tested, a population size of at least 4,800 individuals, which is roughly five times larger than population sizes in typical E&R studies, is required to achieve a power of at least 75%. Our study provides an important step toward improved experimental designs aiming to characterize causative SNPs in Experimental Evolution studies.
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Affiliation(s)
- Anna Maria Langmüller
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria.,Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna, Austria
| | - Marlies Dolezal
- Plattform Bioinformatik und Biostatistik, Vetmeduni Vienna, Vienna, Austria
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Langmüller AM, Schlötterer C. Low concordance of short-term and long-term selection responses in experimental Drosophila populations. Mol Ecol 2020; 29:3466-3475. [PMID: 32762052 PMCID: PMC7540288 DOI: 10.1111/mec.15579] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 07/27/2020] [Accepted: 07/28/2020] [Indexed: 12/15/2022]
Abstract
Experimental evolution is becoming a popular approach to study the genomic selection response of evolving populations. Computer simulation studies suggest that the accuracy of the signature increases with the duration of the experiment. Since some assumptions of the computer simulations may be violated, it is important to scrutinize the influence of the experimental duration with real data. Here, we use a highly replicated Evolve and Resequence study in Drosophila simulans to compare the selection targets inferred at different time points. At each time point, approximately the same number of SNPs deviates from neutral expectations, but only 10% of the selected haplotype blocks identified from the full data set can be detected after 20 generations. Those haplotype blocks that emerge already after 20 generations differ from the others by being strongly selected at the beginning of the experiment and display a more parallel selection response. Consistent with previous computer simulations, our results demonstrate that only Evolve and Resequence experiments with a sufficient number of generations can characterize complex adaptive architectures.
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Affiliation(s)
- Anna Maria Langmüller
- Vienna Graduate School of Population GeneticsViennaAustria
- Institut für PopulationsgenetikVetmeduni ViennaViennaAustria
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8
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Fox DT, Soltis DE, Soltis PS, Ashman TL, Van de Peer Y. Polyploidy: A Biological Force From Cells to Ecosystems. Trends Cell Biol 2020; 30:688-694. [PMID: 32646579 DOI: 10.1016/j.tcb.2020.06.006] [Citation(s) in RCA: 122] [Impact Index Per Article: 24.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 06/15/2020] [Accepted: 06/16/2020] [Indexed: 12/20/2022]
Abstract
Polyploidy, resulting from the duplication of the entire genome of an organism or cell, greatly affects genes and genomes, cells and tissues, organisms, and even entire ecosystems. Despite the wide-reaching importance of polyploidy, communication across disciplinary boundaries to identify common themes at different scales has been almost nonexistent. However, a critical need remains to understand commonalities that derive from shared polyploid cellular processes across organismal diversity, levels of biological organization, and fields of inquiry - from biodiversity and biocomplexity to medicine and agriculture. Here, we review the current understanding of polyploidy at the organismal and suborganismal levels, identify shared research themes and elements, and propose new directions to integrate research on polyploidy toward confronting interdisciplinary grand challenges of the 21st century.
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Affiliation(s)
- Donald T Fox
- Department of Pharmacology and Cancer Biology, Duke University, Durham, NC 27710, USA.
| | - Douglas E Soltis
- Florida Museum of Natural History, University of Florida, Gainesville, FL 32611, USA; Department of Biology, University of Florida, Gainesville, FL 32611, USA.
| | - Pamela S Soltis
- Florida Museum of Natural History, University of Florida, Gainesville, FL 32611, USA.
| | - Tia-Lynn Ashman
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA.
| | - Yves Van de Peer
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium; VIB Center for Plant Systems Biology, Ghent, Belgium; Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, South Africa; College of Horticulture, Nanjing Agricultural University, Nanjing, China.
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