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Berdan EL, Barton NH, Butlin R, Charlesworth B, Faria R, Fragata I, Gilbert KJ, Jay P, Kapun M, Lotterhos KE, Mérot C, Durmaz Mitchell E, Pascual M, Peichel CL, Rafajlović M, Westram AM, Schaeffer SW, Johannesson K, Flatt T. How chromosomal inversions reorient the evolutionary process. J Evol Biol 2023; 36:1761-1782. [PMID: 37942504 DOI: 10.1111/jeb.14242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 09/13/2023] [Accepted: 10/05/2023] [Indexed: 11/10/2023]
Abstract
Inversions are structural mutations that reverse the sequence of a chromosome segment and reduce the effective rate of recombination in the heterozygous state. They play a major role in adaptation, as well as in other evolutionary processes such as speciation. Although inversions have been studied since the 1920s, they remain difficult to investigate because the reduced recombination conferred by them strengthens the effects of drift and hitchhiking, which in turn can obscure signatures of selection. Nonetheless, numerous inversions have been found to be under selection. Given recent advances in population genetic theory and empirical study, here we review how different mechanisms of selection affect the evolution of inversions. A key difference between inversions and other mutations, such as single nucleotide variants, is that the fitness of an inversion may be affected by a larger number of frequently interacting processes. This considerably complicates the analysis of the causes underlying the evolution of inversions. We discuss the extent to which these mechanisms can be disentangled, and by which approach.
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Affiliation(s)
- Emma L Berdan
- Bioinformatics Core, Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Marine Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Nicholas H Barton
- Institute of Science and Technology Austria (ISTA), Klosterneuburg, Austria
| | - Roger Butlin
- Department of Marine Sciences, University of Gothenburg, Gothenburg, Sweden
- Ecology and Evolutionary Biology, School of Bioscience, The University of Sheffield, Sheffield, UK
| | - Brian Charlesworth
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - Rui Faria
- CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Vairão, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Vairão, Portugal
| | - Inês Fragata
- CHANGE - Global Change and Sustainability Institute/Animal Biology Department, cE3c - Center for Ecology, Evolution and Environmental Changes, Faculty of Sciences, University of Lisbon, Lisbon, Portugal
| | | | - Paul Jay
- Center for GeoGenetics, University of Copenhagen, Copenhagen, Denmark
| | - Martin Kapun
- Center for Anatomy and Cell Biology, Medical University of Vienna, Vienna, Austria
- Central Research Laboratories, Natural History Museum of Vienna, Vienna, Austria
| | - Katie E Lotterhos
- Department of Marine and Environmental Sciences, Northeastern University, Boston, Massachusetts, USA
| | - Claire Mérot
- UMR 6553 Ecobio, Université de Rennes, OSUR, CNRS, Rennes, France
| | - Esra Durmaz Mitchell
- Department of Biology, University of Fribourg, Fribourg, Switzerland
- Functional Genomics & Metabolism Research Unit, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense M, Denmark
| | - Marta Pascual
- Departament de Genètica, Microbiologia i Estadística, Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, Spain
| | - Catherine L Peichel
- Division of Evolutionary Ecology, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland
| | - Marina Rafajlović
- Department of Marine Sciences, University of Gothenburg, Gothenburg, Sweden
- Linnaeus Centre for Marine Evolutionary Biology, University of Gothenburg, Gothenburg, Sweden
| | - Anja M Westram
- Institute of Science and Technology Austria (ISTA), Klosterneuburg, Austria
- Faculty of Biosciences and Aquaculture, Nord University, Bodø, Norway
| | - Stephen W Schaeffer
- Department of Biology, Pennsylvania State University, University Park, Pennsylvania, USA
| | - Kerstin Johannesson
- Linnaeus Centre for Marine Evolutionary Biology, University of Gothenburg, Gothenburg, Sweden
- Tjärnö Marine Laboratory, Department of Marine Sciences, University of Gothenburg, Strömstad, Sweden
| | - Thomas Flatt
- Department of Biology, University of Fribourg, Fribourg, Switzerland
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Li P, Li G, Zhang YW, Zuo JF, Liu JY, Zhang YM. A combinatorial strategy to identify various types of QTLs for quantitative traits using extreme phenotype individuals in an F 2 population. PLANT COMMUNICATIONS 2022; 3:100319. [PMID: 35576159 PMCID: PMC9251438 DOI: 10.1016/j.xplc.2022.100319] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 03/07/2022] [Accepted: 03/22/2022] [Indexed: 06/09/2023]
Abstract
Theoretical and applied studies demonstrate the difficulty of detecting extremely over-dominant and small-effect genes for quantitative traits via bulked segregant analysis (BSA) in an F2 population. To address this issue, we proposed an integrated strategy for mapping various types of quantitative trait loci (QTLs) for quantitative traits via a combination of BSA and whole-genome sequencing. In this strategy, the numbers of read counts of marker alleles in two extreme pools were used to predict the numbers of read counts of marker genotypes. These observed and predicted numbers were used to construct a new statistic, Gw, for detecting quantitative trait genes (QTGs), and the method was named dQTG-seq1. This method was significantly better than existing BSA methods. If the goal was to identify extremely over-dominant and small-effect genes, another reserved DNA/RNA sample from each extreme phenotype F2 plant was sequenced, and the observed numbers of marker alleles and genotypes were used to calculate Gw to detect QTGs; this method was named dQTG-seq2. In simulated and real rice dataset analyses, dQTG-seq2 could identify many more extremely over-dominant and small-effect genes than BSA and QTL mapping methods. dQTG-seq2 may be extended to other heterogeneous mapping populations. The significance threshold of Gw in this study was determined by permutation experiments. In addition, a handbook for the R software dQTG.seq, which is available at https://cran.r-project.org/web/packages/dQTG.seq/index.html, has been provided in the supplemental materials for the users' convenience. This study provides a new strategy for identifying all types of QTLs for quantitative traits in an F2 population.
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Affiliation(s)
- Pei Li
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Guo Li
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Ya-Wen Zhang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Jian-Fang Zuo
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Jin-Yang Liu
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; Jiangsu Key Laboratory for Horticultural Crop Genetic Improvement, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Yuan-Ming Zhang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
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Benowitz KM, Allan CW, Degain BA, Li X, Fabrick JA, Tabashnik BE, Carrière Y, Matzkin LM. Novel genetic basis of resistance to Bt toxin Cry1Ac in Helicoverpa zea. Genetics 2022; 221:6540856. [PMID: 35234875 PMCID: PMC9071530 DOI: 10.1093/genetics/iyac037] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 02/25/2022] [Indexed: 11/14/2022] Open
Abstract
Crops genetically engineered to produce insecticidal proteins from the bacterium Bacillus thuringiensis have advanced pest management, but their benefits are diminished when pests evolve resistance. Elucidating the genetic basis of pest resistance to Bacillus thuringiensis toxins can improve resistance monitoring, resistance management, and the design of new insecticides. Here, we investigated the genetic basis of resistance to Bacillus thuringiensis toxin Cry1Ac in the lepidopteran Helicoverpa zea, one of the most damaging crop pests in the United States. To facilitate this research, we built the first chromosome-level genome assembly for this species, which has 31 chromosomes containing 375 Mb and 15,482 predicted proteins. Using a genome-wide association study, fine-scale mapping, and RNA-seq, we identified a 250-kb quantitative trait locus on chromosome 13 that was strongly associated with resistance in a strain of Helicoverpa zea that had been selected for resistance in the field and lab. The mutation in this quantitative trait locus contributed to but was not sufficient for resistance, which implies alleles in more than one gene contributed to resistance. This quantitative trait locus contains no genes with a previously reported role in resistance or susceptibility to Bacillus thuringiensis toxins. However, in resistant insects, this quantitative trait locus has a premature stop codon in a kinesin gene, which is a primary candidate as a mutation contributing to resistance. We found no changes in gene sequence or expression consistently associated with resistance for 11 genes previously implicated in lepidopteran resistance to Cry1Ac. Thus, the results reveal a novel and polygenic basis of resistance.
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Affiliation(s)
- Kyle M Benowitz
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA,Department of Biology, Austin Peay State University, Clarksville, TN 37040, USA,Corresponding author: Department of Biology, Austin Peay State University, Sundquist Science Center, 681 Summer St., Clarksville, TN 37040, USA.
| | - Carson W Allan
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA
| | - Benjamin A Degain
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA
| | - Xianchun Li
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA
| | - Jeffrey A Fabrick
- U.S. Department of Agriculture, Agricultural Research Service, U.S. Arid Land Agricultural Research Center, Maricopa, AZ 85138, USA
| | - Bruce E Tabashnik
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA
| | - Yves Carrière
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA
| | - Luciano M Matzkin
- Department of Entomology, University of Arizona, Tucson, AZ 85721, USA,Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721, USA,Bio5 Institute, University of Arizona, Tucson, AZ 85721, USA
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Benowitz KM, Coleman JM, Allan CW, Matzkin LM. Contributions of cis- and trans-Regulatory Evolution to Transcriptomic Divergence across Populations in the Drosophila mojavensis Larval Brain. Genome Biol Evol 2021; 12:1407-1418. [PMID: 32653899 PMCID: PMC7495911 DOI: 10.1093/gbe/evaa145] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/06/2020] [Indexed: 12/22/2022] Open
Abstract
Natural selection on gene expression was originally predicted to result primarily in cis- rather than trans-regulatory evolution, due to the expectation of reduced pleiotropy. Despite this, numerous studies have ascribed recent evolutionary divergence in gene expression predominantly to trans-regulation. Performing RNA-seq on single isofemale lines from genetically distinct populations of the cactophilic fly Drosophila mojavensis and their F1 hybrids, we recapitulated this pattern in both larval brains and whole bodies. However, we demonstrate that improving the measurement of brain expression divergence between populations by using seven additional genotypes considerably reduces the estimate of trans-regulatory contributions to expression evolution. We argue that the finding of trans-regulatory predominance can result from biases due to environmental variation in expression or other sources of noise, and that cis-regulation is likely a greater contributor to transcriptional evolution across D. mojavensis populations. Lastly, we merge these lines of data to identify several previously hypothesized and intriguing novel candidate genes, and suggest that the integration of regulatory and population-level transcriptomic data can provide useful filters for the identification of potentially adaptive genes.
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Affiliation(s)
| | - Joshua M Coleman
- Department of Entomology, University of Arizona.,Department of Biological Sciences, University of Alabama in Huntsville
| | | | - Luciano M Matzkin
- Department of Entomology, University of Arizona.,Department of Ecology and Evolutionary Biology, University of Arizona.,BIO5 Institute, University of Arizona
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Ishikawa A, Sakaguchi M, Nagano AJ, Suzuki S. Genetic Architecture of Innate Fear Behavior in Chickens. Behav Genet 2020; 50:411-422. [PMID: 32770288 DOI: 10.1007/s10519-020-10012-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 07/29/2020] [Indexed: 01/12/2023]
Abstract
The genetic architecture of innate fear behavior in chickens is poorly understood. Here, we performed quantitative trait loci (QTL) analysis of innate responses to tonic immobility (TI) and open field (OF) fears in 242 newly hatched chicks of an F2 population between the native Japanese Nagoya breed and the White Leghorn breed using 881 single nucleotide polymorphism markers obtained by restriction site-associated DNA sequencing. At genome-wide 5% significance levels, four QTL for TI traits were revealed on chromosomes 1-3 and 24. Two of these loci had sex-specific effects on the traits. For OF traits, three QTL were revealed on chromosomes 2, 4 and 7. The TI and OF QTL identified showed no overlaps in genomic regions and different modes of inheritance. The three TI QTL and one OF QTL exerted antagonistic effects on the traits. The results demonstrated that context-dependent QTL underlie the variations in innate TI and OF behaviors.
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Affiliation(s)
- Akira Ishikawa
- Laboratory of Animal Genetics and Breeding, Graduate School of Bioagricultural Sciences, Nagoya University, Chikusa, Nagoya, 464-8601, Japan.
| | - Marina Sakaguchi
- Laboratory of Animal Genetics and Breeding, Graduate School of Bioagricultural Sciences, Nagoya University, Chikusa, Nagoya, 464-8601, Japan
| | - Atsushi J Nagano
- Faculty of Agriculture, Ryukoku University, Otsu, Shiga, 520-2194, Japan
| | - Sae Suzuki
- Laboratory of Animal Genetics and Breeding, Graduate School of Bioagricultural Sciences, Nagoya University, Chikusa, Nagoya, 464-8601, Japan
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