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Protein structure and selection pressure in plants: using mutation to understand the functional importance of protein structure
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Abstract
Recent advances in protein structure prediction have opened new avenues for understanding the potential impact of genetic mutations and how they might affect protein structure. In this study, we analyzed the distribution and structural characteristics of mutations in four plant species: Arabidopsis, rice, sugar beet, and cassava. We integrated population genotype datasets with protein structure predictions to map mutation positions to their corresponding gene protein products and structural features. Our analysis reveals that high-effect mutations are more likely to occur in unstructured, disordered regions of proteins rather than in well-folded, conserved regions. This finding suggests that natural selection exerts greater pressure to conserve sequence integrity in folded regions, which are crucial for protein function. Conversely, disordered regions may tolerate higher variability exhibiting a higher frequency of impactful mutations. By providing a comprehensive overview of mutation distribution in relation to protein structure, this study enhances our understanding of the evolutionary pressures shaping plant proteomes. The insights gained from this research could inform future studies on protein function, evolutionary biology, and plant improvement strategies.
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · cited 1×
“Standard breeding practices take many years to achieve the introgression of specific AlphaFold [2], along with competitors such as ESM-fold [3], have enabled highly accurate protein structure prediction without requiring extensive X-ray crystallography experiments.”
Evolutionary-scale prediction of atomic level protein structure with a language model
Lin, Z., Akin, H., Rao, R., Hie, B., Zhu, Z., Lu, W., Smetanin, N., Verkuil, R., Kabeli, O., Shmueli, Y., et al. (2022) · doi:10.1101/2022.07.20.500902 · Cited by 5,990
Signatures of negative selection in the genetic architecture of human complex traits
Zeng, J., de Vlaming, R., Wu, Y., Robinson, M. R., Lloyd-Jones, L. R., Yengo, L., Yap, C. X., Xue, A., Sidorenko, J., McRae, A. F., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0101-4 · Cited by 391
Using AlphaFold to predict the impact of single mutations on protein stability and function
Pak, M. A., Markhieva, K. A., Novikova, M. S., Petrov, D. S., Vorobyev, I. S., Maksimova, E. S., Kondrashov, F. A., & Ivankov, D. N. (2023) · PLOS One · doi:10.1371/journal.pone.0282689 · Cited by 322 · cited 2×
“It is still yet unknown how well these in silico reconstruction of protein structures can be used to estimate effects of single point mutations [4], however, some studies have shown high correlations between AlphaFold predicted importance and disease pathogenicity of non-synonymous mutations [5].”
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Research works printed but not linked: 32
- Sedeek KE, Mahas A, Mahfouz M, Sedeek KE, Mahas A, Mahfouz M, Sedeek KE, Mahas A, Mahfouz M. Plant genome engineering for targeted improvement of crop traits. Front Plant Sci. 2019;10:114. · DOI
- Lin Z, Akin H, Rao R, Hie B, Zhu Z, Lu W, Lin Z, Akin H, Rao R, Hie B, Zhu Z, Lu W, Lin Z, Akin H, Rao R, Hie B, Zhu Z, Lu W, et al. Language models of protein sequences at the scale of evolution enable accurate structure prediction. BioRxiv. 2022;2022:500902.
- Keskin Karakoyun H, Yüksel ŞK, Amanoglu I, Naserikhojasteh L, Yeşilyurt A, Yakıcıer C, Karakoyun K, Yüksel H, Amanoglu ŞK, Naserikhojasteh I, Yeşilyurt L, Yakıcıer A, Keskin Karakoyun C, Yüksel H, Amanoglu ŞK, Naserikhojasteh I, Yeşilyurt L, Yakıcıer A, et al. Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer. Front Genet. 2023;14:1052383. · DOI
- Monroe JG, McKay JK, Weigel D, Flood PJ, Monroe JG, McKay JK, Weigel D, Flood PJ, Monroe JG, McKay JK, Weigel D, Flood PJ. The population genomics of adaptive loss of function. Heredity. 2021;126:383–95. · DOI
- Olson MV, Olson MV, Olson MV. When less is more: gene loss as an engine of evolutionary change. Am J Hum Genet. 1999;64:18–23. · DOI · Paper page
- Su T, Liu F, Gu P, Jin H, Chang Y, Wang Q, Su T, Liu F, Gu P, Jin H, Chang Y, Wang Q, Su T, Liu F, Gu P, Jin H, Chang Y, Wang Q, et al. A CRISPR-Cas9 assisted non-homologous end-joining strategy for one-step engineering of bacterial genome. Sci Rep. 2016;6:37895. · DOI
- Wang W, Mauleon R, Hu Z, Chebotarov D, Tai S, Wu Z, Wang W, Mauleon R, Hu Z, Chebotarov D, Tai S, Wu Z, Wang W, Mauleon R, Hu Z, Chebotarov D, Tai S, Wu Z, et al. Genomic variation in 3,010 diverse accessions of Asian cultivated rice. Nature. 2018;557:43–9. · DOI
- Alonso-Blanco C, Andrade J, Becker C, Bemm F, Bergelson J, Borgwardt KM, Alonso-Blanco C, Andrade J, Becker C, Bemm F, Bergelson J, Borgwardt KM, Alonso-Blanco C, Andrade J, Becker C, Bemm F, Bergelson J, Borgwardt KM, et al. 1,135 genomes reveal the global pattern of polymorphism in Arabidopsis thaliana. Cell. 2016;166:481–91. · DOI
- Zhao K, Long E, Sanchez F, Monier E, Chavarriaga P, Monroe G, Zhao K, Long E, Sanchez F, Monier E, Chavarriaga P, Monroe G, Zhao K, Long E, Sanchez F, Monier E, Chavarriaga P, Monroe G. Unlocking genetic diversity in Colombian cassava landraces for accelerated breeding. New Phytol. 202 6. https://doi.org/10.1111/nph.70918 · DOI
- Felkel S, Dohm JC, Himmelbauer H, Felkel S, Dohm JC, Himmelbauer H, Felkel S, Dohm JC, Himmelbauer H. Genomic variation in the genus Beta based on 656 sequenced beet genomes. Sci Rep. 2023;13:8654. · DOI
- Touw WG, Baakman C, Black J, Te Beek TA, Krieger E, Joosten RP, Touw WG, Baakman C, Black J, Te Beek TA, Krieger E, Joosten RP, Touw WG, Baakman C, Black J, Te Beek TA, Krieger E, Joosten RP, et al. A series of PDB-related databanks for everyday needs. Nucleic Acids Res. 2015;43:D364–8. · DOI
- Tien MZ, Meyer AG, Sydykova DK, Spielman SJ, Wilke CO, Tien MZ, Meyer AG, Sydykova DK, Spielman SJ, Wilke CO, Tien MZ, Meyer AG, Sydykova DK, Spielman SJ, Wilke CO. Maximum allowed solvent accessibilites of residues in proteins. PLoS ONE. 2013;8:e80635. · DOI
- Wang Q, Tang J, Han B, Huang X, Wang Q, Tang J, Han B, Huang X, Wang Q, Tang J, Han B, Huang X. Advances in genome-wide association studies of complex traits in rice. Theor Appl Genet. 2020;133:1415–25. · DOI
- Huang X, Zhao Y, Wei X, Li C, Wang A, Zhao Q, Huang X, Zhao Y, Wei X, Li C, Wang A, Zhao Q, Huang X, Zhao Y, Wei X, Li C, Wang A, Zhao Q, et al. Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm. Nat Genet. 2012;44:32–9. · DOI
- Cingolani P. Variant annotation and functional prediction: SnpEff. Variant calling: methods and protocols. Springer; 2012. pp. 289–314. · DOI
- Mészáros B, Erdős G, Dosztányi Z, Mészáros B, Erdős G, Dosztányi Z, Mészáros B, Erdős G, Dosztányi Z. IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding. Nucleic Acids Res. 2018;46:W329–37. · DOI
- Henikoff S, Henikoff JG, Henikoff S, Henikoff JG, Henikoff S, Henikoff JG. Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci. 1992;89:10915–9. · DOI · Paper page
- Benitez-Cantos MS, Yordanova MM, O’Connor PB, Zhdanov AV, Kovalchuk SI, Papkovsky DB, Benitez-Cantos MS, Yordanova MM, O’Connor PB, Zhdanov AV, Kovalchuk SI, Papkovsky DB, Benitez-Cantos MS, Yordanova MM, O’Connor PB, Zhdanov AV, Kovalchuk SI, Papkovsky DB, et al. Translation initiation downstream from annotated start codons in human mRNAs coevolves with the Kozak context. Genome Res. 2020;30:974–84. · DOI
- van der Lee R, Buljan M, Lang B, Weatheritt RJ, Daughdrill GW, Dunker AK, van der Lee R, Buljan M, Lang B, Weatheritt RJ, Daughdrill GW, Dunker AK. van der Lee R, Buljan M, Lang B, Weatheritt RJ, Daughdrill GW, Dunker AK, Classification of Intrinsically Disordered Regions and Proteins. Chem Rev. 2014;114:6589 – 631. Go to ISI://WOS:000338980600003 · DOI
- Lobley A, Swindells MB, Orengo CA, Jones DT, Lobley A, Swindells MB, Orengo CA, Jones DT, Lobley A, Swindells MB, Orengo CA, Jones DT. Inferring function using patterns of native disorder in proteins. PLoS Comput Biol. 2007;3:e162. · DOI
- Xue B, Li L, Meroueh SO, Uversky VN, Dunker AK, Xue B, Li L, Meroueh SO, Uversky VN, Dunker AK, Xue B, Li L, Meroueh SO, Uversky VN, Dunker AK. Analysis of structured and intrinsically disordered regions of transmembrane proteins. Mol Biosyst. 2009;5:1688–702. https://www.ncbi.nlm.nih.gov/pubmed/19585006. · DOI
- Magidovich E, Fleishman SJ, Yifrach O, Magidovich E, Fleishman SJ, Yifrach O, Magidovich E, Fleishman SJ, Yifrach O. Intrinsically disordered C-terminal segments of voltage-activated potassium channels: a possible fishing rod-like mechanism for channel binding to scaffold proteins. Bioinformatics. 2006;22:1546–50. · DOI
- Vuzman D, Azia A, Levy Y, Vuzman D, Azia A, Levy Y, Vuzman D, Azia A, Levy Y. Searching DNA via a Monkey Bar mechanism: the significance of disordered tails. J Mol Biol. 2010;396:674–84. · DOI
- De Kovel CGF, De Kovel CGF, De Kovel CGF. The power of allele frequency comparisons to detect the footprint of selection in natural and experimental situations. Genet Selection Evol. 2006;38:3–23. · DOI
- Long EM, Romay MC, Ramstein G, Buckler ES, Robbins KR, Long EM, Romay MC, Ramstein G, Buckler ES, Robbins KR, Long EM, Romay MC, Ramstein G, Buckler ES, Robbins KR. Utilizing evolutionary conservation to detect deleterious mutations and improve genomic prediction in cassava. Front Plant Sci. 2023;13:1041925. · DOI
- Ramstein GP, Buckler ES, Ramstein GP, Buckler ES, Ramstein GP, Buckler ES. Prediction of evolutionary constraint by genomic annotations improves functional prioritization of genomic variants in maize. Genome Biol. 2022;23:183. · DOI · Paper page
- Wu Y, Li D, Hu Y, Li H, Ramstein GP, Zhou S, Wu Y, Li D, Hu Y, Li H, Ramstein GP, Zhou S, Wu Y, Li D, Hu Y, Li H, Ramstein GP, Zhou S, et al. Phylogenomic discovery of deleterious mutations facilitates hybrid potato breeding. Cell. 2023;186:2313–28. e15. · DOI
- Zhai J, Gokaslan A, Schiff Y, Berthel A, Liu Z-Y, Lai W-Y, Zhai J, Gokaslan A, Schiff Y, Berthel A, Liu Z-Y, Lai W-Y, Zhai J, Gokaslan A, Schiff Y, Berthel A, Liu Z-Y, Lai W-Y, et al. Cross-species modeling of plant genomes at single-nucleotide resolution using a pretrained DNA language model. Proc Nat Acad Sci. 2025;122:e2421738122. · DOI
- Cano-Gamez E, Trynka G, Cano-Gamez E, Trynka G, Cano-Gamez E, Trynka G. From GWAS to function: using functional genomics to identify the mechanisms underlying complex diseases. Front Genet. 2020;11:424. Journal Abbreviation. · DOI · Paper page
- Alseekh S, Kostova D, Bulut M, Fernie AR, Alseekh S, Kostova D, Bulut M, Fernie AR, Alseekh S, Kostova D, Bulut M, Fernie AR. Genome-wide association studies: assessing trait characteristics in model and crop plants. Cell Mol Life Sci. 2021;78:5743–54. · DOI
- van Kempen M, Kim SS, Tumescheit C, Mirdita M, Gilchrist CL, Söding J, van Kempen M, Kim SS, Tumescheit C, Mirdita M, Gilchrist CL, Söding J, van Kempen M, Kim SS, Tumescheit C, Mirdita M, Gilchrist CL, Söding J et al. Foldseek: fast and accurate protein structure search. Biorxiv. 2022:2022.02:07.479398.
- Zhang Y, Skolnick J, Zhang Y, Skolnick J, Zhang Y, Skolnick J. TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res. 2005;33:2302–9. · DOI · Paper page
Metadata
- Authors
- Long, E., & Monroe, G.
- Affiliations
- Agricultural Research Service (US)
- Corresponding author
- Long, Evan
- ORCID
- Long, Evan
- Venue
- BMC Genomics
- Published
- 2026-02-24
- Volume
- 27
- Issue
- 1
- ISSN
- 1471-2164 (ISSN-L)
- PMC
- PMC13037108
- OpenAlex
- W7131270902
- Cited by
- 3
- References
- 4
- Citations by year
- 2026: 3
- FWCI
- 11.78
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Genomics (publishedVersion, cc-by)
- Research Square (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- University of California, Davis
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- protein structure, natural selection, plant mutation, intrinsically disordered regions, protein disorder, mutation effects, protein structure prediction, Arabidopsis, rice, sugar beet, cassava, population genomics
- MeSH terms
- Mutation, Plant Proteins, Plants, Protein Conformation, Oryza, Selection, Genetic, Arabidopsis, Protein Folding, Evolution, Molecular, Beta vulgaris
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