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Arnce LR, Bubnell JE, Aquadro CF. Comparative Analysis of Drosophila Bam and Bgcn Sequences and Predicted Protein Structural Evolution. J Mol Evol 2025; 93:278-291. [PMID: 40178596 PMCID: PMC12006264 DOI: 10.1007/s00239-025-10245-9] [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: 12/17/2024] [Accepted: 03/24/2025] [Indexed: 04/05/2025]
Abstract
The protein encoded by the Drosophila melanogaster gene bag of marbles (bam) plays an essential role in early gametogenesis by complexing with the gene product of benign gonial cell neoplasm (bgcn) to promote germline stem cell daughter differentiation in males and females. Here, we compared the AlphaFold2 and AlphaFold Multimer predicted structures of Bam protein and the Bam:Bgcn protein complex between D. melanogaster, D. simulans, and D. yakuba, where bam is necessary in gametogenesis to that in D. teissieri, where it is not. Despite significant sequence divergence, we find very little evidence of significant structural differences in high confidence regions of the structures across the four species. This suggests that Bam structure is unlikely to be a direct cause of its functional differences between species and that Bam may simply not be integrated in an essential manner for GSC differentiation in D. teissieri. Patterns of positive selection and significant amino acid diversification across species is consistent with the Selection, Pleiotropy, and Compensation (SPC) model, where detected selection at bam is consistent with adaptive change in one major trait followed by positively selected compensatory changes for pleiotropic effects (in this case perhaps preserving structure). In the case of bam, we suggest that the major trait could be genetic interaction with the endosymbiotic bacteria Wolbachia pipientis. Following up on detected signals of positive selection and comparative structural analysis could provide insight into the distribution of a primary adaptive change versus compensatory changes following a primary change.
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Affiliation(s)
- Luke R Arnce
- Department of Molecular Biology and Genetics, Cornell University, 233 Biotechnology Building, 526 Campus Rd, Ithaca, NY, 14853, USA.
| | - Jaclyn E Bubnell
- Department of Molecular Biology and Genetics, Cornell University, 233 Biotechnology Building, 526 Campus Rd, Ithaca, NY, 14853, USA
| | - Charles F Aquadro
- Department of Molecular Biology and Genetics, Cornell University, 233 Biotechnology Building, 526 Campus Rd, Ithaca, NY, 14853, USA
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Arnce LR, Bubnell JE, Aquadro CF. Comparative Analysis of Drosophila Bam and Bgcn Sequences and Predicted Protein Structural Evolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.17.628990. [PMID: 39763920 PMCID: PMC11702778 DOI: 10.1101/2024.12.17.628990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/16/2025]
Abstract
The protein encoded by the Drosophila melanogaster gene bag of marbles (bam) plays an essential role in early gametogenesis by complexing with the gene product of benign gonial cell neoplasm (bgcn) to promote germline stem cell daughter differentiation in males and females. Here, we compared the AlphaFold2 and AlphaFold Multimer predicted structures of Bam protein and the Bam:Bgcn protein complex between D. melanogaster, D. simulans, and D. yakuba, where bam is necessary in gametogenesis to that in D. teissieri, where it is not. Despite significant sequence divergence, we find very little evidence of significant structural differences in high confidence regions of the structures across the four species. This suggests that Bam structure is unlikely to be a direct cause of its functional differences between species and that Bam may simply not be integrated in an essential manner for GSC differentiation in D. teissieri. Patterns of positive selection and significant amino acid diversification across species is consistent with the Selection, Pleiotropy, and Compensation (SPC) model, where detected selection at bam is consistent with adaptive change in one major trait followed by positively selected compensatory changes for pleiotropic effects (in this case perhaps preserving structure). In the case of bam, we suggest that the major trait could be genetic interaction with the endosymbiotic bacteria Wolbachia pipientis. Following up on detected signals of positive selection and comparative structural analysis could provide insight into the distribution of a primary adaptive change versus compensatory changes following a primary change.
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Affiliation(s)
- Luke R Arnce
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
| | - Jaclyn E Bubnell
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
| | - Charles F Aquadro
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, USA
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Ferreiro D, Branco C, Arenas M. Selection among site-dependent structurally constrained substitution models of protein evolution by approximate Bayesian computation. Bioinformatics 2024; 40:btae096. [PMID: 38374231 PMCID: PMC10914458 DOI: 10.1093/bioinformatics/btae096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 01/15/2024] [Accepted: 02/16/2024] [Indexed: 02/21/2024] Open
Abstract
MOTIVATION The selection among substitution models of molecular evolution is fundamental for obtaining accurate phylogenetic inferences. At the protein level, evolutionary analyses are traditionally based on empirical substitution models but these models make unrealistic assumptions and are being surpassed by structurally constrained substitution (SCS) models. The SCS models often consider site-dependent evolution, a process that provides realism but complicates their implementation into likelihood functions that are commonly used for substitution model selection. RESULTS We present a method to perform selection among site-dependent SCS models, also among empirical and site-dependent SCS models, based on the approximate Bayesian computation (ABC) approach and its implementation into the computational framework ProteinModelerABC. The framework implements ABC with and without regression adjustments and includes diverse empirical and site-dependent SCS models of protein evolution. Using extensive simulated data, we found that it provides selection among SCS and empirical models with acceptable accuracy. As illustrative examples, we applied the framework to analyze a variety of protein families observing that SCS models fit them better than the corresponding best-fitting empirical substitution models. AVAILABILITY AND IMPLEMENTATION ProteinModelerABC is freely available from https://github.com/DavidFerreiro/ProteinModelerABC, can run in parallel and includes a graphical user interface. The framework is distributed with detailed documentation and ready-to-use examples.
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Affiliation(s)
- David Ferreiro
- CINBIO, Universidade de Vigo, 36310 Vigo, Spain
- Department of Biochemistry, Genetics and Immunology, Universidade de Vigo, 36310 Vigo, Spain
| | - Catarina Branco
- CINBIO, Universidade de Vigo, 36310 Vigo, Spain
- Department of Biochemistry, Genetics and Immunology, Universidade de Vigo, 36310 Vigo, Spain
| | - Miguel Arenas
- CINBIO, Universidade de Vigo, 36310 Vigo, Spain
- Department of Biochemistry, Genetics and Immunology, Universidade de Vigo, 36310 Vigo, Spain
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Dutheil JY, Hamidi D, Pajot B. The Site/Group Extended Data Format and Tools. Genome Biol Evol 2024; 16:evae011. [PMID: 38252924 PMCID: PMC10849175 DOI: 10.1093/gbe/evae011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 01/12/2024] [Indexed: 01/24/2024] Open
Abstract
Comparative sequence analysis permits unraveling the molecular processes underlying gene evolution. Many statistical methods generate candidate positions within genes, such as fast or slowly evolving sites, coevolving groups of residues, sites undergoing positive selection, or changes in evolutionary rates. Understanding the functional causes of these evolutionary patterns requires combining the results of these analyses and mapping them onto molecular structures, a complex task involving distinct coordinate referential systems. To ease this task, we introduce the site/group extended data format, a simple text format to store (groups of) site annotations. We developed a toolset, the SgedTools, which permits site/group extended data file manipulation, creating them from various software outputs and translating coordinates between individual sequences, alignments, and three-dimensional structures. The package also includes a Monte-Carlo procedure to generate random site samples, possibly conditioning on site-specific features. This eases the statistical testing of evolutionary hypotheses, accounting for the structural properties of the encoded molecules.
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Affiliation(s)
- Julien Y Dutheil
- Research Group “Molecular Systems Evolution,” Department of Theoretical Biology, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Diyar Hamidi
- Research Group “Molecular Systems Evolution,” Department of Theoretical Biology, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
| | - Basile Pajot
- Research Group “Molecular Systems Evolution,” Department of Theoretical Biology, Max Planck Institute for Evolutionary Biology, Plön 24306, Germany
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Gu X, Li L, Li S, Shi W, Zhong X, Su Y, Wang T. Adaptive evolution and co-evolution of chloroplast genomes in Pteridaceae species occupying different habitats: overlapping residues are always highly mutated. BMC PLANT BIOLOGY 2023; 23:511. [PMID: 37880608 PMCID: PMC10598918 DOI: 10.1186/s12870-023-04523-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 10/13/2023] [Indexed: 10/27/2023]
Abstract
BACKGROUND The evolution of protein residues depends on the mutation rates of their encoding nucleotides, but it may also be affected by co-evolution with other residues. Chloroplasts function as environmental sensors, transforming fluctuating environmental signals into different physiological responses. We reasoned that habitat diversity may affect their rate and mode of evolution, which might be evidenced in the chloroplast genome. The Pteridaceae family of ferns occupy an unusually broad range of ecological niches, which provides an ideal system for analysis. RESULTS We conducted adaptive evolution and intra-molecular co-evolution analyses of Pteridaceae chloroplast DNAs (cpDNAs). The results indicate that the residues undergoing adaptive evolution and co-evolution were mostly independent, with only a few residues being simultaneously involved in both processes, and these overlapping residues tend to exhibit high mutations. Additionally, our data showed that Pteridaceae chloroplast genes are under purifying selection. Regardless of whether we grouped species by lineage (which corresponded with ecological niches), we determined that positively selected residues mainly target photosynthetic genes. CONCLUSIONS Our work provides evidence for the adaptive evolution of Pteridaceae cpDNAs, especially photosynthetic genes, to different habitats and sheds light on the adaptive evolution and co-evolution of proteins.
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Affiliation(s)
- Xiaolin Gu
- College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Lingling Li
- College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Sicong Li
- College of Natural Resources and Environment, South China Agricultural University, Guangzhou, 510642, China
| | - Wanxin Shi
- College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Xiaona Zhong
- College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China
| | - Yingjuan Su
- School of Life Sciences, Sun Yat-sen University, Guangzhou, 510275, China.
- Research Institute of Sun Yat-sen University in Shenzhen, Shenzhen, 518057, China.
| | - Ting Wang
- College of Life Sciences, South China Agricultural University, Guangzhou, 510642, China.
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