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Langmüller AM, Nolte V, Dolezal M, Schlötterer C. The genomic distribution of transposable elements is driven by spatially variable purifying selection. Nucleic Acids Res 2023; 51:9203-9213. [PMID: 37560917 PMCID: PMC10516647 DOI: 10.1093/nar/gkad635] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 07/10/2023] [Accepted: 07/18/2023] [Indexed: 08/11/2023] Open
Abstract
It is widely accepted that the genomic distribution of transposable elements (TEs) mainly reflects the outcome of purifying selection and insertion bias (1). Nevertheless, the relative importance of these two evolutionary forces could not be tested thoroughly. Here, we introduce an experimental system, which allows separating purifying selection from TE insertion bias. We used experimental evolution to study the TE insertion patterns in Drosophila simulans founder populations harboring 1040 insertions of an active P-element. After 10 generations at a large population size, we detected strong selection against P-element insertions. The exception were P-element insertions in genomic regions for which a strong insertion bias has been proposed (2-4). Because recurrent P-element insertions cannot explain this pattern, we conclude that purifying selection, with variable strength along the chromosomes, is the major determinant of the genomic distribution of P-elements. Genomic regions with relaxed purifying selection against P-element insertions exhibit normal levels of purifying selection against base substitutions. This suggests that different types of purifying selection operate on base substitutions and P-element insertions. Our results highlight the power of experimental evolution to understand basic evolutionary processes, which are difficult to infer from patterns of natural variation alone.
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Affiliation(s)
- Anna M Langmüller
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, 1210 Wien, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Veterinärplatz 1, 1210 Vienna, Austria
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, 1210 Wien, Austria
| | - Marlies Dolezal
- Plattform Bioinformatik und Biostatistik, Vetmeduni Vienna, Veterinärplatz 1, 1210 Vienna, Austria
| | - Christian Schlötterer
- Institut für Populationsgenetik, Vetmeduni Vienna, Veterinärplatz 1, 1210 Wien, Austria
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2
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Mazo-Vargas A, Langmüller AM, Wilder A, van der Burg KRL, Lewis JJ, Messer PW, Zhang L, Martin A, Reed RD. Deep cis-regulatory homology of the butterfly wing pattern ground plan. Science 2022; 378:304-308. [PMID: 36264807 DOI: 10.1126/science.abi9407] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Butterfly wing patterns derive from a deeply conserved developmental ground plan yet are diverse and evolve rapidly. It is poorly understood how gene regulatory architectures can accommodate both deep homology and adaptive change. To address this, we characterized the cis-regulatory evolution of the color pattern gene WntA in nymphalid butterflies. Comparative assay for transposase-accessible chromatin using sequencing (ATAC-seq) and in vivo deletions spanning 46 cis-regulatory elements across five species revealed deep homology of ground plan-determining sequences, except in monarch butterflies. Furthermore, noncoding deletions displayed both positive and negative regulatory effects that were often broad in nature. Our results provide little support for models predicting rapid enhancer turnover and suggest that deeply ancestral, multifunctional noncoding elements can underlie rapidly evolving trait systems.
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Affiliation(s)
- Anyi Mazo-Vargas
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA.,Department of Biological Sciences, The George Washington University, Washington, DC, USA
| | - Anna M Langmüller
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Alexis Wilder
- Department of Biological Sciences, The George Washington University, Washington, DC, USA
| | | | - James J Lewis
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA.,Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA
| | - Philipp W Messer
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Linlin Zhang
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA.,CAS and Shandong Province Key Laboratory of Experimental Marine Biology, Center for Ocean Mega-Science, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
| | - Arnaud Martin
- Department of Biological Sciences, The George Washington University, Washington, DC, USA
| | - Robert D Reed
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA
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Langmüller AM, Champer J, Lapinska S, Xie L, Metzloff M, Champer SE, Liu J, Xu Y, Du J, Clark AG, Messer PW. Fitness effects of CRISPR endonucleases in Drosophila melanogaster populations. eLife 2022; 11:e71809. [PMID: 36135925 PMCID: PMC9545523 DOI: 10.7554/elife.71809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 09/08/2022] [Indexed: 11/13/2022] Open
Abstract
Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 provides a highly efficient and flexible genome editing technology with numerous potential applications ranging from gene therapy to population control. Some proposed applications involve the integration of CRISPR/Cas9 endonucleases into an organism's genome, which raises questions about potentially harmful effects to the transgenic individuals. One example for which this is particularly relevant are CRISPR-based gene drives conceived for the genetic alteration of entire populations. The performance of such drives can strongly depend on fitness costs experienced by drive carriers, yet relatively little is known about the magnitude and causes of these costs. Here, we assess the fitness effects of genomic CRISPR/Cas9 expression in Drosophila melanogaster cage populations by tracking allele frequencies of four different transgenic constructs that allow us to disentangle 'direct' fitness costs due to the integration, expression, and target-site activity of Cas9, from fitness costs due to potential off-target cleavage. Using a maximum likelihood framework, we find that a model with no direct fitness costs but moderate costs due to off-target effects fits our cage data best. Consistent with this, we do not observe fitness costs for a construct with Cas9HF1, a high-fidelity version of Cas9. We further demonstrate that using Cas9HF1 instead of standard Cas9 in a homing drive achieves similar drive conversion efficiency. These results suggest that gene drives should be designed with high-fidelity endonucleases and may have implications for other applications that involve genomic integration of CRISPR endonucleases.
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Affiliation(s)
- Anna M Langmüller
- Department of Computational Biology, Cornell UniversityIthacaUnited States
- Institut für Populationsgenetik, Vetmeduni ViennaViennaAustria
- Vienna Graduate School of Population Genetics, Vetmeduni ViennaViennaAustria
| | - Jackson Champer
- Department of Computational Biology, Cornell UniversityIthacaUnited States
- Department of Molecular Biology and Genetics, Cornell UniversityIthacaUnited States
- Center for Bioinformatics, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking UniversityBeijingChina
| | - Sandra Lapinska
- Department of Computational Biology, Cornell UniversityIthacaUnited States
- Department of Molecular Biology and Genetics, Cornell UniversityIthacaUnited States
| | - Lin Xie
- Department of Computational Biology, Cornell UniversityIthacaUnited States
- Department of Molecular Biology and Genetics, Cornell UniversityIthacaUnited States
| | - Matthew Metzloff
- Department of Computational Biology, Cornell UniversityIthacaUnited States
- Department of Molecular Biology and Genetics, Cornell UniversityIthacaUnited States
| | - Samuel E Champer
- Department of Computational Biology, Cornell UniversityIthacaUnited States
| | - Jingxian Liu
- Department of Computational Biology, Cornell UniversityIthacaUnited States
- Department of Molecular Biology and Genetics, Cornell UniversityIthacaUnited States
| | - Yineng Xu
- Department of Computational Biology, Cornell UniversityIthacaUnited States
- Department of Molecular Biology and Genetics, Cornell UniversityIthacaUnited States
| | - Jie Du
- Center for Bioinformatics, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking UniversityBeijingChina
| | - Andrew G Clark
- Department of Computational Biology, Cornell UniversityIthacaUnited States
- Department of Molecular Biology and Genetics, Cornell UniversityIthacaUnited States
| | - Philipp W Messer
- Department of Computational Biology, Cornell UniversityIthacaUnited States
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Yang E, Metzloff M, Langmüller AM, Xu X, Clark AG, Messer PW, Champer J. A homing suppression gene drive with multiplexed gRNAs maintains high drive conversion efficiency and avoids functional resistance alleles. G3 (Bethesda) 2022; 12:jkac081. [PMID: 35394026 PMCID: PMC9157102 DOI: 10.1093/g3journal/jkac081] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 03/30/2022] [Indexed: 11/14/2022]
Abstract
Gene drives are engineered alleles that can bias inheritance in their favor, allowing them to spread throughout a population. They could potentially be used to modify or suppress pest populations, such as mosquitoes that spread diseases. CRISPR/Cas9 homing drives, which copy themselves by homology-directed repair in drive/wild-type heterozygotes, are a powerful form of gene drive, but they are vulnerable to resistance alleles that preserve the function of their target gene. Such resistance alleles can prevent successful population suppression. Here, we constructed a homing suppression drive in Drosophila melanogaster that utilized multiplexed gRNAs to inhibit the formation of functional resistance alleles in its female fertility target gene. The selected gRNA target sites were close together, preventing reduction in drive conversion efficiency. The construct reached a moderate equilibrium frequency in cage populations without apparent formation of resistance alleles. However, a moderate fitness cost prevented elimination of the cage population, showing the importance of using highly efficient drives in a suppression strategy, even if resistance can be addressed. Nevertheless, our results experimentally demonstrate the viability of the multiplexed gRNAs strategy in homing suppression gene drives.
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Affiliation(s)
- Emily Yang
- Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Matthew Metzloff
- Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Anna M Langmüller
- Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
- Institut für Populationsgenetik, Vetmeduni Vienna, 1210 Wien, Austria
- Vienna Graduate School of Population Genetics, 1210 Wien, Austria
| | - Xuejiao Xu
- Center for Bioinformatics, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
| | - Andrew G Clark
- Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Philipp W Messer
- Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
| | - Jackson Champer
- Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
- Center for Bioinformatics, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
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