Molecular evolution of the granule-bound starch synthase in flowering plants

Molecular evolution of the granule-bound starch synthase in flowering plants | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Molecular evolution of the granule-bound starch synthase in flowering plants Elvis Santos Leonardo, Kauê Santana, Thiago André This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4778293/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Feb, 2025 Read the published version in Plant Molecular Biology Reporter → Version 1 posted 11 You are reading this latest preprint version Abstract Starch is the main storage carbohydrate in plants and, as well as being a natural resource of global importance for human consumption, serves as a raw material for some industries. Granule-bound starch synthase (GBSS) is the key enzyme in starch synthesis. However, the evolution of structural diversity of this enzyme in flowering plants remains poorly understood. This study applied a comprehensive phylogenetic analysis of genes encoding the GBSS enzyme to better understand its evolutionary history and used homology modeling to determine the enzyme's structure by identifying important protein domains and motifs. The gene encoding the GBSS enzyme was highly conserved in angiosperms and phylogenetic analysis confirmed the evolution of two isoforms, GBSSI and GBSSII. This molecular diversification could be linked to duplication events in plant genomes. Although the two isoforms share similarities, they showed structural variances and amino acid substitutions. Furthermore, the occurrence of destabilizing mutations in key residues in binding sites and conserved domains were under greater influence of purifying selection, maintaining the stability of the protein. This study provides a more comprehensive understanding of the evolutionary and structural history of the main enzymes involved in starch synthesis, which could support future studies that aim to increase our understanding of starch biosynthesis and the evolutionary and functional divergence of GBSS in plants. We highlight that attention regarding isoforms is required when using GBSS to reconstruct phylogenetic trees. starch synthesis angiosperms plant storage organs evolutionary analyses carbohydrate storage. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Starch is the main storage carbohydrate produced by plants. It is widely used for human nutrition and is one of the main constituents of cereals, tubers, legumes, and fruits (Miao et al. 2014; do Carmo et al. 2020; Seung et al. 2020). Starch exists in the form of semi-crystalline insoluble granules and is composed of two types of polymers: amylose and amylopectin (Cheng et al. 2012; Miao et al. 2014; do Carmo et al. 2020; Seung et al. 2020); the relative proportions of which vary in different organs. Amylose is a linear polymer formed by glucose residues that are linked by α-1,4 bonds. Amylopectin also contains linear chains with α-1,4 bonds, in addition to branched chains with α-1,6 bonds (Kato et al. 2019; Seung et al. 2020). Amylopectin is the main polymer of starch forming part of the semi-crystalline matrix of the granule, with the adjacent chains forming double helices that pack into semicrystalline lamellae, while the branching points give rise to amorphous lamellae (Seung 2020). However, the role of amylose in plant growth and survival remains unclear (Seung et al. 2020). The synthesis of amylose is catalyzed by granule-bound starch synthase (GBSS), which transfers glucose residues from ADP-glucose to produce long chains of amylose and amylopectin (Cheng et al. 2012). In most cereals studied to date, GBSS consists of two isoforms: GBSSI and GBSSII. GBSSI is expressed mostly in storage tissues such as the endosperm and seed embryos, whereas GBSSII expression is linked mostly to leaves, stems, roots, and pericarps (Vrinten and Nakamura 2000; Dian et al. 2003; Cheng et al. 2012). In addition, there may be a difference in the expression profiles of further isoforms: GBSSIa and GBSSIb. For instance, in cereals, other plants (Vrinten and Nakamura 2000; Dian et al. 2003; Cheng et al. 2012) and peas ( Psium sativum ), GBSSIa is highly expressed in embryos and GBSSIb is highly expressed in leaves (Edwards et al. 2002). The isoenzymes involved in starch synthesis have been widely reported in monocots and dicots. During starch synthesis, the Waxy gene encodes GBSS (Miao et al. 2014; Li et al. 2019). Phylogenetic analysis of the GBSS gene showed that monocots contain the GBSSI isoform and form a group separate from the dicots, which contain the GBSSII isoform (Lu et al. 2012). This suggests a divergence in the enzymes responsible for starch synthesis in plants. Another study that evaluated the variation in GBSSI in a group of Poaceae showed the conservation of exons and introns (Shapter et al. 2009). Characterization of a new gene ( CrGBSSIb ) in Amaranthus cruentus and its phylogenetic analyses also revealed that monocots are grouped under GBSSI while dicots are grouped under GBSSII, which is consistent with previous studies (Cheng et al. 2012; Park et al. 2017). Moreover, a study on the evolution of GBSS genes in angiosperms revealed the occurrence of a duplication event 251 million years ago(Lu et al. 2012; Cheng et al. 2012). Other studies involving GBSS and other genes that participate in starch synthesis have indicated that there were one or two gene duplication processes before the grasses diverged (Cheng et al. 2012). Furthermore, there are structural similarities between GBSS and soluble starch synthases, which may be attributed to common ancestry and duplication events (Qu et al. 2018). The molecular evolution of enzymes involved in starch synthesis in plants has been extensively studied to understand the evolutionary relationships that permeate starch evolution and the functional aspects of their molecular mechanisms (Saha et al. 2014; Banerjee and Deshpande. 2016; Almeida de Jesus et al. 2022). Previous studies have reported the presence of genes encoding the GBSS enzyme in P. sativum (Edwards et al. 2002), rice ( Oryza sativa ) (Momma and Fujimoto. 2012), barley ( Hordeum vulgare ) (Cuesta-Seijo et al. 2013; Li et al. 2019), and banana ( Musa acuminata ) (Miao et al. 2014). Owing to the low number of copies of the gene encoding GBSS, it has been widely used to study phylogenetic and evolutionary relationships in plants (Cheng et al. 2012). However, most of these studies have focused on small phylogenetic groups (Cheng et al. 2012; Li et al. 2012) and no comprehensive phylogenetic studies involving angiosperms as a whole, to our knowledge, have been reported to date. Further, only a few computational studies on the structural aspects of this enzyme have been reported (Cuesta-seijo et al. 2013; Momma and Fujimoto. 2012), limiting a better understanding of its function. Evolutionary analyses have provided new insights into the evolutionary history of this enzyme, allowing us to better understand its structural and functional diversification (Saha et al. 2014; Banerjee and Deshpande 2016; Almeida de Jesus et al. 2022a). In this study, we used homology modeling to determine the enzyme structural diversity by identifying important protein domains and motifs. For that, we performed a comprehensive phylogenetic analysis of genes encoding the GBSS enzyme. Material and Methods DNA Sequence Recovery The coding sequences of two genes that encode the GBSS enzyme were obtained through the NCBI GenBank database (//www.ncbi.nlm.nih.gov/) (Benson et al. 1990). A thorough search was conducted using the BLASTn tool to identify the maximum number of available taxa in the database (Altschul et al. 1997). Two reference sequences were selected for the GBSSI isoform: NM103023.4 from Arabidopsis thaliana and FJ804468.1 from Oryza sativa . For the GBSSII isoform, the sequences chosen were GQ150862.1 from Oryza sativa and AF109395.1 from Triticum aestivum . These accession codes were selected due to their complete sequence annotation in the database. Sequences with identities above 80% were included in subsequent analyses. In addition, a sequence search was conducted throughout the GenBank database using the name of the enzyme ‘ granule-bound starch synthase ’ to retrieve sequences that may not have been captured through Blastn. The coding sequences (CDSs) of GBSS were obtained from GenBank and only complete CDSs were selected for analysis. To complement the information obtained from the database, we recovered sequences of taxa with unannotated genomes by performing an optimized BLASTn search using the same reference sequence, NM103023.4 and FJ804468.1 for GBSSI, to isoform GBSSII GQ150862.1 and AF109395.1. In this case, only the genomes of taxa without any representatives recovered in the first search were obtained. To annotate the coding and non-coding regions, exons, and introns of the recovered genome fragments, we used the AUGUSTUS program (Stanke and Waack 2003), which is used for gene prediction using genomic fragments (https://bioinf.uni-greifswald.de/augustus/) (Stanke et al. 2004). AUGUSTUS performs ab initio and alignment-based gene prediction (Stanke et al. 2006, 2008). All the predicted genes were validated against the GenBank database using the BLASTn algorithm to verify their similarity to other GBSS genes deposited in the database. A total of 732 accessions were obtained, including the CDSs of GBSSI and GBSSII and 101 genes obtained from unannotated genomes. We also applied a filter to eliminate repeat data, very short sequences (< 500 bp), and non-GBSS genes. Finally, we obtained 376 GBSS gene sequences that were used in the subsequent analyses. Phylogenetic analyses First, multiple sequence alignment was performed using the MUSCLE algorithm (Edgar 2004), implemented in Geneious Prime® version 20221.1 (https://www.geneious.com/prime/) using the default settings. Then, phylogenetic analyses were performed using the W-IQ-TREE web server(Trifinopoulos et al. 2016). The construction of the phylogenetic tree was based on the maximum likelihood method (Felsenstein 1981), in which the substitution model was automated with an ultrafast bootstrap with a value of 3,000 and maximum of 2,000 iterations. The minimum correlation coefficient was set at 0.99. To support the branches, the SH-aLRT test was used with 2,000 replicates (Guindon et al. 2010) along with the approximate Bayes test (Anisimova et al. 2011). The best nucleotide substitution model for the sequence dataset was the GTR+F+I+G4. Calculation of dN/dS rates The analysis of positive selection which is indicative of adaptive evolutionary changes was carried out through the Datamokey webserver (https://www.datamonkey.org) (Kosakovsky Pond and Frost 2005; Delport et al. 2010; Weaver et al. 2018). The aBSREL test, implemented on a server, is a fundamental approach to infer the presence of positive selection in molecular sequences (Kosakovsky Pond et al. 2011; Smith et al. 2015). The aBSREL test expands the Branch-Site Random Effects (BSREL) model, allowing for the assessment of the rate of evolution (ꙍ = dN/dS) among different branches of the phylogenetic tree. Using the Likelihood Ratio Test (LRT), a null model (lack of positive selection) is compared to an alternative model on the branches, while the adjusted p-value test is applied to control false positives and determine the statistical significance of the results (Smith et al. 2015). Before submitting the alignment of the coding GBSS sequences to the web server, the data was prepared by removing all stop codons using the HyPhy 2.5.57 program. (Kosakovsky Pond et al. 2020). Subsequently, the sequences were aligned with the MUSCLE algorithm, implemented in the MEGA program version 11.0.13 (Kumar et al. 2018), using the following sets: gap open: -2.90; gap extend: -0.20; hydrophobicity multiplier: 1.20; using 1,000 iterations. The remaining settings were kept as default. The resulting alignment was checked to ensure the correct alignment of reading frames. In silico structural modeling The structures of the GBSS isoforms were modeled using the Swiss-Model web server (Arnold et al. 2006; Kiefer et al. 2009; Biasini et al. 2014) (https://swissmodel.expasy.org/). The alignment search for template structures was carried out on the web server and two structures were identified, one for each isoform see Supplementary Material S1. The selection of the protein sequences for modeling was determined using aBSREL analysis to detect positive selection, focusing on Oryza brachyantha, Sorghum bicolor, and Sorghum leiocladum . Additional taxa were selected to encompass representatives of major groups like Commelinids, Superrosids, and Superasterids, all of which share both isoforms. This approach aimed to identify structural patterns between the two isoforms within each classification group (Table 1). Table 1 . Taxa used for the in silico structural modeling of the granule-bound starch synthase (GBSS) I and II. Species Order Higher-classification Musa acuminata GBSSII Zingiberales Coomelinids Monocots Musa acuminata GBSSI Oryza sativa GBSSI Poales Oryza brachyantha GBSSI Oryza brachyantha GBSSII Sorghum leiocladum GBSSI Sorghum bicolor GBSSII Prunus avium GBSSI Rosales Superrosids Eudicots Prunus avium GBSSII Glycine soja GBSSI Fabales Glycine soja GBSSII Solanum tuberosum GBSSI Solanales Superrasterids Solanum tuberosum GBSSII Arabdopsis thalianna GBSSI Brasicales Coffea euginoides GBSSI Gentianales Coffea euginoides GBSSI We used the homolog structure of Oryza sativa japonica (PDB ID:3VUE, chain A, resolution 2.7 Å) and Hordeum vulgare (PDB ID:4HLN, chain A, resolution 2.7 Å). All structures modeled had loop regions refined using a script from the Modeller program (Webb and Sali 2017). In general, the structure of Oryza sativa was used as a template for the GBSSI isoform of the taxa, while the structure of Hordeum vulgare was used as a template for the GBSSII isoform. The taxa Oryza brachyantha , Sorghum bicolor , and Sorghum leiocladum for GBSSI and GBSSII isoforms were modeled using the protein structure of Oryza sativa as a template. For more details verify the Supplementary Material S1. The theoretical models were validated by stereochemical analysis using the Ramachandran plot (Lovell et al. 2003) on a Swiss-Model server (Arnold et al. 2006; Biasini et al. 2014). The quality of the stereochemistry of the models was determined as a function of their phi and psi angles. Structural validation of the modeled protein structure was performed using the QMEAN plot (Benkert et al. 2008, 2011), which is a composite score that employs average strength statistical potential (Sippl 1993). To verify possible errors in the structures, an analysis was performed on the ProSa-Web server (Wiederstein and Sippl 2007) (https://prosa.services.came.sbg.ac.at/prosa.php), which is a widely used tool for checking errors in three-dimensional protein structures, and allows error recognition for both theoretically and experimentally elucidated structures (Wiederstein and Sippl 2007). The theoretical structures of the GBSS enzyme were aligned using the USCF Chimera version 1.17 (Pettersen et al. 2004). To perform the structural alignment, we selected the modeled structures of Prunus avium GBSSI and Musa acuminata GBSSII. This selection was based on the lowest mean squared deviation of α-carbons (RMSD-Cα) obtained between the two structures. Structural comparisons allowed us to analyze the similarities and differences of conserved and non-conserved structural motifs for both protein isoforms. We also inferred relevant structural aspects of the molecular function, such as the residue composition and conformation of their binding sites. The InterPro database, available in the EMBL database from the European Institute of Bioinformatics, was used to identify protein families and domains (Goujon et al. 2010; McWilliam et al. 2013). The MOTIF tool available in GenomeNet was used to perform a functional search using the amino acid sequence to identify structural motifs (Kanehisa 2002). We used all sequences applied in the comparative modeling (Table 1) and all sequences were aligned and compared to verify the conserved regions. Mutational analysis of protein structures We conducted mutation analysis of ObGBSSI and MaGBSSII to determine which amino acids significantly affect structural stability. An alanine scan was performed using the FoldX 5.0 program (Delgado et al. 2019). The FoldX toolkit was created to evaluate the effect of mutations on protein structure stability (Guerois et al. 2002; Schymkowitz et al. 2005) The software uses a linear combination of different empirical terms to calculate the free energy (ΔG). The empirical terms included electrostatic interactions, Coulomb terms, van der Waals terms, hydrophobic and solvation forces, hydrogen bonds, and other types of interactions. The result was interpreted using mutational analysis (ΔΔGfold) and expressed as the difference between the free energy of the wild-type structure (ΔGwt) and the mutant structure (ΔGmut) (kcal.mol-1) according to Equation 1: where ΔG fold,wt is the change in free energy of the wild-type structure and ΔG fold,mut is the change in the mutant structure. When ΔΔG 0, the mutation is considered destabilizing. To better understand the effects of mutations on the structures, we classified the ΔΔG values into five categories: highly stabilizing (ΔΔG < -1.84 kcal mol -1 ), mildly stabilizing (-1.84 kcal mol -1 ≤ ΔΔG < -0.46 kcal mol -1 ), neutral (-0.46 kcal mol -1 < ΔΔG ≤ +0.46 kcal mol-1), mildly destabilizing (+0.46 kcal mol -1 +1.84 kcal mol -1 ) (Almeida de Jesus et al. 2022b). Results Phylogenetic analyses Multiple sequence alignments performed using the MUSCLE algorithm resulted in an alignment matrix of 14,457 bp of coding regions, comprising 13 exons. Phylogenetic analysis, considering the already well-known classification of angiosperms, provided evidence that GBSS virtually represents the evolution of angiosperms, particularly the monocot (branch support with 100% bootstrap) and eudicot (branch support with 100% bootstrap) lineages, in addition to the major classification groups, such as Commelinids, Fabids, Superasterids, Superrosids, and Rosids (all with bootstrap values above 90%) (Figure 1). The results showed evidence of GBSSI duplication in eudicots of the Superasterid and Superrosid groups, which is probably a consequence of a genome duplication event that may have occurred in these lineage histories, as indicated by some studies (Cheng et al. 2012; Qu et al. 2018). In general, GBSSII is nested within the eudicotyledon (tricolpate) clade; however, monocot taxa were observed within this classification, specifically Musa acuminata and Phoenix dactylifera , which present the GBSSII isoform, indicating evolutionary convergence. The structures of the isoforms of Musa acuminata (among monocots) and Prunus avium (among eudicots) showed that the structures of GBSSI were more similar to each other than to those of GBSSII, which represents a group that diversified from eudicots. In principle, these results indicated that the GBSS gene possessed an ancestral GBSSI lineage from which the GBSSII lineage evolved and that the genes encoding GBSSII are not exclusive to eudicots. The complete phylogeny with the classification of groups and taxa is shown in Supplementary Material S2. dN/dS Rates According to the aBSREL analysis, out of the 512 branches analyzed, 43 were identified in the ω2 class, suggesting positive selection in these branches due to a high ω rate. On the other hand, 188 branches were classified in the ω1 class, indicating a lower ω rate, which suggests the predominance of purifying selection in these branches. Therefore, there is evidence that a greater number of taxa and sites are under purifying selection rather than positive selection. All results showed high statistical significance, as evidenced by the p-values and significant results of the LRT test. For additional details, please see the Supplementary Table S3. In silico structural modeling The structural isoforms of the enzyme GBSS are closely related due to their low RMSD-Cα value. The theoretical structures of GBSSI generally exhibited 16 β sheets and 18 α helices. The GBSSI from Oryza brachyantha and Solanum tuberosum showed 17 β sheet structures, Sorghum leiocladum had 15 β sheet structures, while the isoform GBSSII structures showed 18 β sheets and a variation in the number of α helices ranging from 18 to 23 structures among the modeled taxa. The GBSSSII structures of Musa acuminata and Solanum tuberosum showed 23 α helices and Prunus avium showed 24 α helix structures. Research in the InterPro and GenomeNet databases of the modeled structures revealed that all belonged to the glycogen synthase family of bacteria/plants (InterPro: IPR011835) and contained two domains: the starch synthesis domain (InterPro: IPR013534) and the glycosyltransferase domain, family 1 (InterPro: IPR001296). The GBSSII isoform differs from GBSSI in its secondary structure and exhibits numerous loop regions. Its ATP binding site is situated externally. In contrast, the GBSSI isoform features a cavity between its N-terminal and C-terminal regions, forming a pit (Figures 2 and 3). Overall, 15 structural models were generated, all showing stereochemistry values exceeding 92%, approximate z-score values consistent with experimental models, and energy plots reflecting satisfactory values (see Supplementary Material S1). The structural alignment resulted in low RMSD-Cα values for the theoretical GBSSI structures compared with the protein structure of Oryza sativa japonica (PDB ID: 3VUE), showing that the structures are structurally well correlated. Further, there was a low RMSD-Cα between the theoretical GBSSII structures and the starch synthase I (PDB ID:4HLN) in the model of Hordeum vulgare , showing an excellent structural relationship. The RMSD between the structures of the GBSSI and GBSSII isoforms showed higher values (Table 2) due to their structural differences, such as those in the number of β-sheets and α-helices. The modeled structures of Oryza brachyantha , Solanum tuberosum, and Sorghum leiocladum present a lower RMSD value and their structures are more similar to the structure used as a reference from Oryza sativa japonica (PDB ID: 3VUE). Table 2. RMSD-Cα values resulting from structural alignment between target modeled structures and their respective reference structures applied in the comparative modeling. Targets + GBSSI (3VUF) 1 Enzyme RMSD (Å) 2 Targets + SSI (4HLN) 3 RMSD (Å) Arabidopsis thaliana GBSSI 0.340 Arabidopsis thaliana 0.884 Coffea eugenioides GBSSI 0.344 Coffea eugenioides 0.883 Coffea eugenioides GBSSII 0.961 Coffea eugenioides 0.259 Glycine soja GBSSI 0.360 Glycine soja 0.854 Glycine soja GBSSII 0.910 Glycine soja 0.388 Hordeum vulgare 4HLN SSI 0.903 Oryza sativa Japonica 0.903 Musa acuminata GBSSI 0.345 Musa acuminata 0.862 Musa acuminata GBSSII 0.894 Musa acuminata 0.204 Oryza brachyantha GBSSI 0.083 Oryza brachyantha 1.804 Oryza brachyantha GBSSII 0.134 Oryza brachyantha 1.797 Prunus avium GBSSI 0.34 Prunus avium 0.838 Prunus avium GBSSII 0.910 Prunus avium 0.220 Solanum tuberosum GBSSI 0.365 Solanum tuberosum 0.867 Solanum tuberosum GBSSII 0.948 Solanum tuberosum 0.466 Sorghum bicolor GBSSII 0.253 Sorghum bicolor 1.791 Sorghum leiocladum GBSSI 0.084 Sorghum leiocladum 1.804 1 GBSS1(3VUF) - Structural model used as a model for the GBSS1 isoforms 2 RMSD – Root Mean Square Derivation of Cα atoms in the structural alignment 3 SSI (4HLN) – Structural model used as a model for the GBSS2 isoforms Here, we present the theoretical structure of the Oryza brachyantha GBSSI (ObGBSSI) enzyme. This enzyme consists of 504 amino acids and two structural domains and belongs to the bacteria/plant glycogen synthesizer family (InterPro: IPR011835). The starch synthesis domain (IPR013534) corresponds to residues 94 to 354 in the N-terminal region, while the glycosyltransferase domain family 1 (IPR001296) corresponds to residues 408 to 524 in the C-terminal region, as compared to the structure of Oryza sativa japonica GBSSI (OsGBSSI), in which the domains exhibited a good structural overlap (Figure 2). Both domains showed overlapping β-α-β structures. The structural alignment showed that ADP-binding residues were conserved in ObGBSSI (Figure 3). This structural overlap shows the conservation of amino acids at the binding site; the position and chemical nature are maintained and most likely the form of complexation of the PaGBSSI structure with the ADP ligand is the same. All residues that bind to ADP in OsGBSSI were observed to be conserved at the same position. The theoretical structure of the GBSS II enzyme from Musa acuminata (MaGBSSII) contains 473 amino acid residues and belongs to the bacteria/plant glycogen synthesizer family (InterPro: IPR011835). The enzyme contains the two domains present in the ObGBSSI protein: the starch synthesis domain (IPR013534), found in the N-terminal region and comprising the residues 285–530, and the glycosyl transferase domain, family 1 (IPR001296), found in the C-terminal region and comprising residues 567–697. The structural alignment of the MaGBSSII with the SSI of Hordeum vulgare (HvSSI) showed a good overlap of the two structural domains (RMSD = 0.204 Å) (Figure 4). The structural comparison showed that the HvSSI residues were conserved in the MaGBSSII structure and that the structure is bound to maltopentaose (Figure 5). All amino acid residues were found to be conserved, except for a change from Thr564 in HvSSI to Asn710 in MaGBSSII. Hypothetically, the form of interaction between maltopentaose and GBSSII enzyme from Musa acuminata should be similar if not identical. The two main HvSSI residues that interacted with maltopentaose were Pro537 and Phe538, in addition to the side-chain residues, Glu543, Trp548, His572, and Ser575. By comparing the amino acid sequences, it was possible to observe the isoforms sharing the same family and protein domains in the structures of ObGBSSI and MaGBSSII in the alignment matrix and to observe their common regions (Figure 6). Although these regions underwent diversification between GBSSI and GBSSII during evolution, they still share the same domains found in the protein family. We added taxa from the Poaceae family to verify the conservation of the GBSSI binding domain and the conserved residues reported in other studies. There was a sequence conservation of the KTGGL motif in GBSSI and GBSSII, in addition to two Cys336 residues present in ObGBSSI present in most GBSSI taxa; however, we noted a substitution by Val336 residue at this position. In the GBSSII isoform, Cys336 was mutated by Trp336. The Cys528 residue present in ObGBSSI was conserved in all GBSSI taxa, except in Brachypodium distachyon GBSSI and Triticum aestivum GBSSII, where there was a change to Phe528 at this position (Figure 7). Analysis of mutation and their effects on protein structural stability Mutational analyses of the ObGBSSI and MaGBSSII structures were performed using alanine scanning to assess the influence of mutations on the structural stability of both proteins. Our results revealed that most alanine substitutions in the sequences of ObGBSSI and MaGBSSII were destabilizing. In ObGBSSI, the residues within the KTGGL motif had highly destabilizing values, such as Thr16 (+2.7 kcal mol -1 ), Gly17 (+2.96 kcal mol -1 ), and Leu19 (+2.26 kcal mol -1 ), which play important roles in GBSSI activity. Furthermore, the conserved residues Cys336 (+6.28 kcal mol -1 ) and Cys528 (+5.53 kcal mol -1 ) were destabilizing in both analyzed sequences (Figure 8). Additionally, some residues that may interact with ADP, such as Asn265 (+2.24 kcal mol-1), Leu434 (+2.89 kcal mol-1), Gly435 (+6.09 kcal mol -1 ), and Ile489 (+2.19 kcal mol -1 ) showed destabilizing mutations. In GBSSII isoforms, Cys336 was replaced by Val in Oryza brachyantha , Sorghum bicolor , and Zea mays , while in other taxa, this residue is altered to Trp. In MaGBSSII, the Gly residue (+6.03 kcal mol -1 ) with a high destabilizing value within the same conserved domain found in GBSSI isoforms stood out, along with a residue that may interact with the ligand, such as Trp694 (+3.74 kcal mol -1 ). Other highly destabilizing residues in MaGBSSII included Gly301 (+6.03 kcal mol-1), Gly415 (+6.14 kcal mol -1 ), Phe421 (+5.37 kcal mol -1 ), Gly461 (+12.33 kcal mol -1 ), Gly542 (+7.02 kcal mol -1 ), Gly582 (+9.28 kcal mol -1 ), and Arg626 (+5.84 kcal mol -1 ). The complete list of amino acid residues in the isoforms can be found in the supplementary material S4. Discussion Our results shed new light on the evolutionary history and structural features of the Granule-Bound Starch Synthase enzyme, allowing us to understand molecular diversification and its structural evolution and conservation throughout angiosperms’ history. Phylogenetic analysis showed that GBSS was well-conserved, reflecting the classification of large higher phylogenetic groups, such as eudicots and monocots, as well as other large groups, such as commelinids, Fabids, Superasterids, Superrosids, and Rosids. Gene duplication events were observed for Superrosids and Superasterids. The GBSSII isoform evolved from an ancestral GBSSI lineage (Figure 1). Diversification occurred in the eudicot group, although taxa that preserve this isoform were present within the monocot group. Some monocot taxa were present within the GBSSII clade, which is an indication of evolutionary convergence. Theoretical three-dimensional structures were classified in the same large family of proteins and their protein domains were conserved; however, the catalytic sites showed some differences. Although we demonstrated the diversification of this gene in parallel with the evolution of flowering plants, most of the structural characteristics of the enzyme were shown to be conserved. Phylogenetic analysis of the GBSS coding sequences showed their conservation in large phylogenetic groups, such as commelinids, Superasterids, and Superrosids, in addition to the clustering of two major phylogenetic groups of plants: monocots and eudicots. These data are in agreement with the classifications presented by other phylogenetic studies using other molecular markers, such as the APG III and IV (The Angiosperm Phylogeny Group) systems (Bremer et al. 2009; Chase et al. 2016), thus highlighting the effectiveness of GBSS in deciphering the phylogenetic histories of flowering plants. Phylogenetic analysis showed that the gene encoding the GBSS enzyme forms a GBSSI group in monocots and that the GBSSII group is concentrated in eudicots, as suggested by previous studies (Cheng et al. 2012; Lu et al. 2012; Park et al. 2017). However, the GBSSII isoform is not exclusively nested in eudicots, being also present in monocots. The appearance of GBSSII isoforms in monocots has been cited in previous studies (Cheng et al. 2012; Lu et al. 2012) but it was suggested that the diversification between the groups was quite remote and that they were separated into distinct groups. Nevertheless, during the process of GBSS diversification, some taxa, such as maize ( Zea mays ), rice ( Oryza sativa , sorghum (Sorghum bicolor), wheat ( Triticum aestivum ), and banana ( Musa acuminata ), maintained this isoform, which indicates that it is a key component in the metabolism of these organisms. Miao et al. (2014) showed that the GBSSII isoform of banana has a greater phylogenetic relationship with those in groups of eudicots than the GBSSI isoforms of monocots, including its own GBSSI isoform. The process of GBSS enzyme diversification between monocots and eudicots may be associated with a major whole-genome duplication event that occurred 251 million years ago (Cheng et al. 2012). A previous study that evaluated the diversification of other starch-synthesizing enzymes in plants showed that these enzymes underwent genetic duplication at different levels (Qu et al. 2018). Furthermore, the occurrence of a whole-genome duplication event in an angiosperm ancestor approximately 150 to 270 million years ago is well known (Jiao et al. 2011). Thus, duplication of the ancestral GBSS gene in angiosperms was likely the result of duplications in the genome, in addition to genetic duplications at different levels (Cheng et al. 2012; Qu et al. 2018). Modeled structures of GBSSI and GBSSII The structural overlap between ObGBSSI and the reference OsGBSSI, in addition to being a good overlap, reveals a typical GT-B structure and a peculiar Rossmann fold in OsGBSSI in the N- and C-terminal domain (Momma and Fujimoto, 2012). Another important structural feature of the ObGBSSI is the presence of a KTGGL motif in the N-terminal region. Studies on Escherichia coli glycogen synthase complexed with ADP and maltooligosaccharides have shown closed dynamic movement with two Rossmann fold domains associated with the KTGGL motif (Momma and Fujimoto, 2012). The RMSD-Cα value for both enzymes was 0.340 Å, suggesting that the structure of ObGBSSI is very similar to that of OsGBSSI and probably has a closed active state. We conjecture that the mechanism of ADP binding to the active site may be a factor that contributed to the closed state of the enzyme(Momma and Fujimoto, 2012). All residues that bind to ADP are conserved in the ObGBSSI structure (Figure 3). ADP can likely bind similarly to the structure of ObGBSSI. The Cys336 residue located between the N and C-terminal domain was not conserved in Poacea, which corroborates the findings of Momma and Fujimoto (2012). Comparison of the theoretical structure of GBSSII to that of HvSSI showed a high structural overlap that can be attributed to the HvSSI adopting a characteristic GT-B fold (a double Rossmann fold); the MaGBSSII structure may have the same characteristic (Cuesta-Seijo et al. 2013) The presence of a KTGGL motif in the MaGBSSII structure validated its Rossman-like fold, similar to the GBSSI isoforms, indicating a high degree of structural similarity. In contrast, the large N-terminal region present in MaGBSSII and HvSSI was absent in ObGBSSI. This region is characterized by an extensive loop and may be related to the conformational changes of the structure after cofactor binding (Cuesta-Seijo et al. 2013). MaGBSSII has an active site characteristic of GT5 and HvSSI and the amino acid residues of both domains have a closed conformation (Cuesta-Seijo et al. 2013). The two main maltopentaose-binding residues, Pro686 and Phe687, are conserved in MaGBSSII, as well as the side chains of the residues Glu689, Trp694, His718, and Ser684. At the binding site of HvSSI, the residues Pro537 and Phe538 form a helical structure around the molecule and the maltopentaose interacts with the side chains of residues Glu543, Trp548, His572, and Ser575 (Cuesta-Seijo et al. 2013). Mutation analysis indicated that the substitution of Thr564 by Asn710 in MaGBSSII did not affect ligand stability. Despite experiencing phylogenetic and structural divergence, the gene encoding the GBSS enzyme retained a significant portion of its functional structural domains. Among these was the GT-B fold, characterized by a double Rossman fold, which is shared with other enzymes involved in starch synthesis. This structural feature is specifically confined to the GT5 and GT1 domains and plays a role in regulation and protein-protein interactions (Qu et al. 2018). The differences between the secondary structures of the GBSSI and GBSSII isoforms were also noted by Qu et al. (2018). dN/dS rates and analyses of mutation Throughout evolution, mutations that lead to advantageous changes face a significantly low probability of occurrence. This is primarily due to energetic barriers that can disrupt the conformation of a protein, hindering the emergence of beneficial alterations. These energetic barriers act as obstacles, impeding the spontaneous acquisition of advantageous mutations within protein structures. As a result, the evolutionary trajectory of proteins is often constrained by the intricate interplay between mutation, energetic stability, and functional adaptation (Faber et al. 2019). The reflections on mutations in the stability and function of proteins have been widely investigated in the literature (Shortle 1992; Neves Cruz et al. 2020; Bellamy-Carter et al. 2021; Almeida de Jesus et al. 2022c; Lee and Kuczera 2023). Most alanine substitutions in the structures of the ObGBSSI and MaGBSSII isoforms are destabilizing, especially the residues located in the KTGGL motif present in the N-terminal region, such as Thr16 (+2.7 kcal mol -1 ), Gly17 (+2.96 kcal mol -1 ), and Leu19 (+2.26 kcal mol -1 ), which play important roles in the activity of OsGBSSI. These residues interact with ADP forming a binding pocket (Momma and Fujimoto, 2012; Sheng et al. 2009). These alterations could impact the structures of both GBSS isoforms, as this domain is associated with the characteristic of the Rossmann fold, which is a distinctive feature of the GT-B protein families (Cuesta-Seijo et al. 2013; Momma and Fujimoto, 2012; Sheng et al. 2009). These residues are critical for both structures, along with other residues within the N-terminal and C-terminal domains, which also exhibited highly destabilizing energies. In the GBSSI isoform sequences, there are two key residues present for the stability of the N and C-terminal domains: Cys336 (+6.28 kcal mol-1) and Cys528 (+5.53 kcal mol-1) (Figure 8). Alterations to these residues result in highly destabilizing values. These residues form a disulfide bond in OsGBSSI. (Momma and Fujimoto, 2012). In MaGBSSII, the characteristic active site of GT5, found in HvSSI, exhibits nearby residues that showed destabilizing mutations. However, residues Pro537 and Phe538, which interact with maltopentaose, did not show destabilizing values. Conversely, residues Phe884 (+3.27 kcal mol -1 ) and Trp694 (+3.74 kcal mol -1 ) displayed destabilizing values. The substitution of Thr564 by Asn710 in MaGBSSII may not affect ligand binding since this alteration did not exhibit destabilizing effects. The remaining residues in the side chain maintained neutral values. However, any changes to these amino acids linked to the GT5 and GT1 domains, which are related to protein regulation, could affect interactions not only with their respective ligands but also among proteins (Qu et al. 2018). The analysis of mutations in both structures using the dN/dS rate of the coding region showed a predominance of purifying selection (dN/dS<1) indicating that the selection is maintaining, for the most part, the functional integrity of the gene that encodes the GBSS enzyme in angiosperms. GBSSI and GBSSII are highly conserved (Kharabian-Masouleh et al. 2011). Another study comparing GBSSI and GBSSII isoforms obtained indications of purifying selection in Poaceae and Fabaceae orthologs (Pan et al. 2009). Signs of positive selection were also observed in the two residue sites of the GBSSI isoform in Manihot esculenta (Yang et al. 2013). Final considerations This study reported the evolutionary history of the gene encoding GBSS in the general context of flowering plants. The Waxy gene, encoding the enzyme GBSS, is well-conserved in flowering plants and we corroborate with the existence of two isoforms named GBSSI and GBSSII. Some monocot taxa exist within the eudicot clades, nested within the GBSSII divergence, likely due to convergence processes acting on this gene. The structures of the ObGBSSI and MaGBSSII isoforms elucidated in silico provide evidence as to how the same binding mechanisms are used in the binding of ADP and pentasaccharide molecules with GBSSI and GBSSII. The isoforms share the same motifs and domains, exhibiting N- and C-terminal domains with Rossmann fold characteristics. The ObGBSSI structure contains a KTGGL motif in the N-terminal region, which is also present in the MaGBSSII isoform. In MaGBSSII, there is a change from Thr564 to Asn710 but the change occurs in a part of the side chain that does not interact directly with the ligand due to its positive energy value of mutation (ΔG>0). The two main residues at the binding site that interact with maltopentaose, Pro686 and Phe687, are conserved in the theoretical model of MaGBSSII, as are the residues Glu689, Trp694, His718, and Ser68. We conjecture that the PaGBSSI and MaGBSSII isoforms interact in the same mode with their cofactors because the main residues in the cavities of both isoforms are conserved. An analysis of mutations in the protein sequences of ObGBSSI and MaGBSSII highlighted the importance of the stability and function of proteins in the evolution of GBSS isoforms in angiosperms. The presence of destabilizing mutations in critical regions, such as residues of the KTGGL motif and residues of Cys336 and Cys528, suggests a fundamental role of these regions in maintaining the structural and functional integrity of proteins. While there was evidence of positive selective pressure in some cases (dN/dS>1) and destabilizing mutations (ΔΔG>0), there was a predominance of purifying selection (dN/dS<1) and stabilizing mutations (ΔΔG<0). This indicates a greater proportion of synonymous changes, which do not affect the final product of the gene, thereby maintaining its functional integrity. This contrasts with previous studies that demonstrated high conservation of GBSSI and GBSSII in angiosperms but also indicated purifying selection. In combination, these findings offer novel insights into the evolutionary history, structure, and function of the key enzymes responsible for starch synthesis in plants. However, additional studies are necessary to explore genetic diversity, differential expression in different tissues and environmental conditions, and the interaction between enzymes and other components of starch metabolism. Furthermore, additional research on genetic and epigenetic regulation of the genes involved in food synthesis can offer valuable insights into how plants respond to environmental stimuli and modulate their food production in different physiological contexts, particularly important for a climate change scenario. In the final analysis, these complementary studies will be essential for a complete understanding of the evolution and function of enzymes that synthesize food in plants, contributing to potential applications in genetic improvement and agricultural biotechnology. Declarations Funding This study was financed by the Brazilian funding agency Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, Brazil) - Finance Code 001 References Almeida de Jesus D, Batista DM, Monteiro EF, et al (2022a) Structural changes and adaptative evolutionary constraints in FLOWERING LOCUS T and TERMINAL FLOWER1-like genes of flowering plants. Front Genet 13:954015. https://doi.org/10.3389/FGENE.2022.954015/BIBTEX Almeida de Jesus D, Batista DM, Monteiro EF, et al (2022b) Structural changes and adaptative evolutionary constraints in FLOWERING LOCUS T and TERMINAL FLOWER1-like genes of flowering plants. Front Genet 13:954015. https://doi.org/10.3389/fgene.2022.954015 Almeida de Jesus D, Batista DM, Monteiro EF, et al (2022c) Structural changes and adaptative evolutionary constraints in FLOWERING LOCUS T and TERMINAL FLOWER1-like genes of flowering plants. Front Genet 13:954015. https://doi.org/10.3389/fgene.2022.954015 Altschul SF, Madden TL, Schäffer AA, et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402. https://doi.org/10.1093/NAR/25.17.3389 Anisimova M, Gil M, Dufayard JF, et al (2011) Survey of Branch Support Methods Demonstrates Accuracy, Power, and Robustness of Fast Likelihood-based Approximation Schemes. Syst Biol 60:685–699. https://doi.org/10.1093/SYSBIO/SYR041 Arnold K, Bordoli L, Kopp J, Schwede T (2006) The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics 22:195–201. https://doi.org/10.1093/bioinformatics/bti770 Banerjee S, Deshpande PA (2016) On origin and evolution of carbonic anhydrase isozymes: A phylogenetic analysis from whole-enzyme to active site. Comput Biol Chem 61:121–129. https://doi.org/10.1016/J.COMPBIOLCHEM.2016.01.003 Bellamy-Carter J, O’Grady L, Passmore M, et al (2021) Decoding Protein Gas-Phase Stability with Alanine Scanning and Collision-Induced Unfolding Ion Mobility Mass Spectrometry. Analysis & Sensing 1:63–69. https://doi.org/10.1002/ANSE.202000019 Benkert P, Biasini M, Schwede T (2011) Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics 27:343–350. https://doi.org/10.1093/BIOINFORMATICS/BTQ662 Benkert P, Tosatto SCE, Schomburg D (2008) QMEAN: A comprehensive scoring function for model quality assessment. Proteins 71:261–277. https://doi.org/10.1002/PROT.21715 Benson D, Boguski M, Lipman DJ, Ostell J (1990) The National Center for Biotechnology Information. Genomics 6:389–391. https://doi.org/10.1016/0888-7543(90)90583-G Biasini M, Bienert S, Waterhouse A, et al (2014) SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. - PubMed - NCBI. Nucleic Acids Res 42:W252–W258 Bremer B, Bremer K, Chase MW, et al (2009) An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG III. Botanical Journal of the Linnean Society 161:105–121. https://doi.org/10.1111/j.1095-8339.2009.00996.x Chase MW, Christenhusz MJM, Fay MF, et al (2016) An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Botanical Journal of the Linnean Society 181:1–20. https://doi.org/10.1111/boj.12385 Cheng J, Khan MA, Qiu W-M, et al (2012) Diversification of Genes Encoding Granule-Bound Starch Synthase in Monocots and Dicots Is Marked by Multiple Genome-Wide Duplication Events. PLoS One 7:e30088. https://doi.org/10.1371/journal.pone.0030088 Cuesta-Seijo JA, Nielsen MM, Marri L, et al (2013) Structure of starch synthase I from barley: insight into regulatory mechanisms of starch synthase activity. Acta Crystallogr D Biol Crystallogr 69:1013–1025. https://doi.org/10.1107/S090744491300440X Delgado J, Radusky LG, Cianferoni D, Serrano L (2019) FoldX 5.0: working with RNA, small molecules and a new graphical interface. Bioinformatics 35:4168–4169. https://doi.org/10.1093/BIOINFORMATICS/BTZ184 Delport W, Poon AFY, Frost SDW, Kosakovsky Pond SL (2010) Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology. Bioinformatics 26:2455–2457. https://doi.org/10.1093/BIOINFORMATICS/BTQ429 Dian W, Jiang H, Chen Q, et al (2003) Cloning and characterization of the granule-bound starch synthase II gene in rice: Gene expression is regulated by the nitrogen level, sugar and circadian rhythm. Planta 218:261–268. https://doi.org/10.1007/s00425-003-1101-9 do Carmo CD, Sousa MBE, dos Santos Silva PP, et al (2020) Identification and validation of mutation points associated with waxy phenotype in cassava. BMC Plant Biol 20:1–12. https://doi.org/10.1186/s12870-020-02379-3 Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797. https://doi.org/10.1093/nar/gkh340 Edwards A, Vincken JP, Suurs LCJM, et al (2002) Discrete forms of amylose are synthesized by isoforms of GBSSI in pea. Plant Cell 14:1767–1785. https://doi.org/10.1105/tpc.002907 Faber MS, Wrenbeck EE, Azouz LR, et al (2019) Impact of In Vivo Protein Folding Probability on Local Fitness Landscapes. Mol Biol Evol 36:2764–2777. https://doi.org/10.1093/MOLBEV/MSZ184 Felsenstein J (1981) Evolutionary trees from DNA sequences: A maximum likelihood approach. J Mol Evol 17:368–376. https://doi.org/10.1007/BF01734359 Goujon M, McWilliam H, Li W, et al (2010) A new bioinformatics analysis tools framework at EMBL-EBI. Nucleic Acids Res 38:. https://doi.org/10.1093/nar/gkq313 Guerois R, Nielsen JE, Serrano L (2002) Predicting Changes in the Stability of Proteins and Protein Complexes: A Study of More Than 1000 Mutations. J Mol Biol 320:369–387. https://doi.org/10.1016/S0022-2836(02)00442-4 Guindon S, Dufayard JF, Lefort V, et al (2010) New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0. Syst Biol 59:307–321. https://doi.org/10.1093/SYSBIO/SYQ010 Jiao Y, Wickett NJ, Ayyampalayam S, et al (2011) Ancestral polyploidy in seed plants and angiosperms. Nature 473:97–100. https://doi.org/10.1038/nature09916 Kanehisa M (2002) The KEGG databases at GenomeNet. Nucleic Acids Res 30:42–46. https://doi.org/10.1093/nar/30.1.42 Kato K, Suzuki Y, Hosaka Y, et al (2019) Effect of high temperature on starch biosynthetic enzymes and starch structure in japonica rice cultivar ‘Akitakomachi’ (Oryza sativa L.) endosperm and palatability of cooked rice. J Cereal Sci 87:209–214. https://doi.org/10.1016/j.jcs.2019.04.001 Kharabian‐Masouleh A, Waters DLE, Reinke RF, Henry RJ (2011) Discovery of polymorphisms in starch‐related genes in rice germplasm by amplification of pooled DNA and deeply parallel sequencing † . Plant Biotechnol J 9:1074–1085. https://doi.org/10.1111/j.1467-7652.2011.00629.x Kiefer F, Arnold K, Künzli M, et al (2009) The SWISS-MODEL Repository and associated resources. Nucleic Acids Res 37:. https://doi.org/10.1093/nar/gkn750 Kosakovsky Pond SL, Frost SDW (2005) Datamonkey: rapid detection of selective pressure on individual sites of codon alignments. Bioinformatics 21:2531–2533. https://doi.org/10.1093/BIOINFORMATICS/BTI320 Kosakovsky Pond SL, Murrell B, Fourment M, et al (2011) A Random Effects Branch-Site Model for Detecting Episodic Diversifying Selection. Mol Biol Evol 28:3033–3043. https://doi.org/10.1093/MOLBEV/MSR125 Kosakovsky Pond SL, Poon AFY, Velazquez R, et al (2020) HyPhy 2.5—A Customizable Platform for Evolutionary Hypothesis Testing Using Phylogenies. Mol Biol Evol 37:295–299. https://doi.org/10.1093/MOLBEV/MSZ197 Kumar S, Stecher G, Li M, et al (2018) MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 35:1547–1549. https://doi.org/10.1093/molbev/msy096 Lee KH, Kuczera K (2023) Simulation analysis of selective alanine mutation effect on stability of human prion protein. J Biomol Struct Dyn 41:2619–2629. https://doi.org/10.1080/07391102.2022.2036237 Li Q, Pan Z, Liu J, et al (2019) A mutation in Waxy gene affects amylose content, starch granules and kernel characteristics of barley (Hordeum vulgare). Plant Breeding 138:513–523. https://doi.org/10.1111/pbr.12695 Lovell SC, Davis IW, Arendall WB, et al (2003) Structure validation by Calpha geometry: phi,psi and Cbeta deviation. Proteins 50:437–50. https://doi.org/10.1002/prot.10286 Lu Y, Li L, Zhou Y, et al (2012) Cloning and Characterization of the Wx Gene Encoding a Granule-Bound Starch Synthase in Lotus (Nelumbo nucifera Gaertn). Plant Mol Biol Report 30:1210–1217. https://doi.org/10.1007/s11105-012-0430-x McWilliam H, Li W, Uludag M, et al (2013) Analysis Tool Web Services from the EMBL-EBI. Nucleic Acids Res 41:. https://doi.org/10.1093/nar/gkt376 Miao H, Sun P, Liu W, et al (2014) Identification of genes encoding granule-bound starch synthase involved in amylose metabolism in banana fruit. PLoS One 9:e88077. https://doi.org/10.1371/journal.pone.0088077 MOMMA M, FUJIMOTO Z (2012) Interdomain Disulfide Bridge in the Rice Granule Bound Starch Synthase I Catalytic Domain as Elucidated by X-Ray Structure Analysis. Biosci Biotechnol Biochem 76:1591–1595. https://doi.org/10.1271/bbb.120305 Neves Cruz J, da Costa KS, de Carvalho TAA, de Alencar NAN (2020) Measuring the structural impact of mutations on cytochrome P450 21A2, the major steroid 21-hydroxylase related to congenital adrenal hyperplasia. J Biomol Struct Dyn 38:1425–1434. https://doi.org/10.1080/07391102.2019.1607560 Pan X, Tang Y, Li M, et al (2009) Isoforms of GBSSI and SSII in four legumes and their phylogenetic relationship to their orthologs from other angiosperms. J Mol Evol 69:625–634. https://doi.org/10.1007/S00239-009-9300-Z/TABLES/1 Park YJ, Nishikawa T, Matsushima K, Nemoto K (2017) Characterization of a new granule-bound starch synthase gene found in amaranth grains (Amaranthus cruentus L.). Molecular Breeding 37:. https://doi.org/10.1007/s11032-017-0712-y Pettersen EF, Goddard TD, Huang CC, et al (2004) UCSF Chimera - A visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612. https://doi.org/10.1002/jcc.20084 Qu J, Xu S, Zhang Z, et al (2018) Evolutionary, structural and expression analysis of core genes involved in starch synthesis. Sci Rep 8:12736. https://doi.org/10.1038/s41598-018-30411-y Saha J, Chatterjee C, Sengupta A, et al (2014) Genome-wide analysis and evolutionary study of sucrose non-fermenting 1-related protein kinase 2 (SnRK2) gene family members in Arabidopsis and Oryza. Comput Biol Chem 49:59–70. https://doi.org/10.1016/J.COMPBIOLCHEM.2013.09.005 Schymkowitz J, Borg J, Stricher F, et al (2005) The FoldX web server: an online force field. Nucleic Acids Res 33:W382. https://doi.org/10.1093/NAR/GKI387 Seung D (2020) Amylose in starch: towards an understanding of biosynthesis, structure and function. New Phytologist 228:1490–1504. https://doi.org/10.1111/nph.16858 Seung D, Echevarría-Poza A, Steuernagel B, Smith AM (2020) Natural polymorphisms in Arabidopsis result in wide variation or loss of the amylose component of StARCH. Plant Physiol 182:870–881. https://doi.org/10.1104/pp.19.01062 Shapter FM, Eggler P, Lee LS, Henry RJ (2009) Variation in Granule Bound Starch Synthase I (GBSSI) loci amongst Australian wild cereal relatives (Poaceae). J Cereal Sci 49:4–11. https://doi.org/10.1016/j.jcs.2008.06.013 Sheng F, Jia X, Yep A, et al (2009) The Crystal Structures of the Open and Catalytically Competent Closed Conformation of Escherichia coli Glycogen Synthase. J Biol Chem 284:17796. https://doi.org/10.1074/JBC.M809804200 Shortle D (1992) Mutational studies of protein structures and their stabilities. Q Rev Biophys 25:205–250. https://doi.org/10.1017/S0033583500004674 Sippl MJ (1993) Recognition of errors in three-dimensional structures of proteins. Proteins: Structure, Function, and Bioinformatics 17:355–362. https://doi.org/10.1002/PROT.340170404 Smith MD, Wertheim JO, Weaver S, et al (2015) Less Is More: An Adaptive Branch-Site Random Effects Model for Efficient Detection of Episodic Diversifying Selection. Mol Biol Evol 32:1342–1353. https://doi.org/10.1093/MOLBEV/MSV022 Stanke M, Diekhans M, Baertsch R, Haussler D (2008) Using native and syntenically mapped cDNA alignments to improve de novo gene finding. Bioinformatics 24:637–644. https://doi.org/10.1093/BIOINFORMATICS/BTN013 Stanke M, Steinkamp R, Waack S, Morgenstern B (2004) AUGUSTUS: a web server for gene finding in eukaryotes. Nucleic Acids Res 32:W309–W312. https://doi.org/10.1093/nar/gkh379 Stanke M, Tzvetkova A, Morgenstern B (2006) AUGUSTUS at EGASP: using EST, protein and genomic alignments for improved gene prediction in the human genome. Genome Biology 2006 7:1 7:1–8. https://doi.org/10.1186/GB-2006-7-S1-S11 Stanke M, Waack S (2003) Gene prediction with a hidden Markov model and a new intron submodel. Bioinformatics 19:ii215–ii225. https://doi.org/10.1093/BIOINFORMATICS/BTG1080 Trifinopoulos J, Nguyen LT, von Haeseler A, Minh BQ (2016) W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis. Nucleic Acids Res 44:W232–W235. https://doi.org/10.1093/nar/gkw256 Vrinten PL, Nakamura T (2000) Wheat Granule-Bound Starch Synthase I and II Are Encoded by Separate Genes That Are Expressed in Different Tissues. Plant Physiol 122:255–264. https://doi.org/10.1104/pp.122.1.255 Weaver S, Shank SD, Spielman SJ, et al (2018) Datamonkey 2.0: A Modern Web Application for Characterizing Selective and Other Evolutionary Processes. Mol Biol Evol 35:773–777. https://doi.org/10.1093/MOLBEV/MSX335 Webb B, Sali A (2017) Protein Structure Modeling with MODELLER. In: Methods in Molecular Biology. pp 39–54 Wiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35:W407–W410. https://doi.org/10.1093/NAR/GKM290 Yang Z, Wang Y, Xu S, et al (2013) Molecular evolution and functional divergence of soluble starch synthase genes in cassava (Manihot Esculenta Crantz). Evolutionary Bioinformatics 2013:239–249. https://doi.org/10.4137/EBO.S11991/ASSET/IMAGES/LARGE/10.4137_EBO.S11991-FIG1.JPEG Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterialS1.pdf SupplementaryMaterialS2.pdf SupplementaryMaterialS3.xlsx SupplementaryMaterialS4.xlsx Cite Share Download PDF Status: Published Journal Publication published 19 Feb, 2025 Read the published version in Plant Molecular Biology Reporter → Version 1 posted Editorial decision: Revision requested 29 Nov, 2024 Reviews received at journal 17 Nov, 2024 Reviewers agreed at journal 02 Nov, 2024 Reviews received at journal 01 Nov, 2024 Reviewers agreed at journal 29 Oct, 2024 Reviewers agreed at journal 28 Oct, 2024 Reviewers agreed at journal 27 Oct, 2024 Reviewers invited by journal 27 Oct, 2024 Editor assigned by journal 26 Jul, 2024 Submission checks completed at journal 26 Jul, 2024 First submitted to journal 21 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4778293","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":335445222,"identity":"6ba1a331-91b8-4954-b53e-ebfed0a631a1","order_by":0,"name":"Elvis Santos Leonardo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIie3PsQrCMBCA4YODdDnpekLxGSKCCoq+iiB0ancHEUTQzVnwJZycI8FO4uwuODgpgjipqRXc2roJ5h+SDPnIBcBm+8UcAJWcMN7ZyyaYEAYQnXinXAQSQjI+ZBMXqby6QXNQm28ux12/TuDo9SKNFEckNYHP3jZcNoLIDEa+v0sjUouOBtDMVFhWAmEIUzWVtA0xgz0MoUMluOcgElEpAhUT3IfjHIQ1Kk2yW5yRqGI4ZRJZf3Enw9H51mu5bB65BNdByXV0lEre471Wwa81+/onPH1z22az2f6nJ7FgO/PRdKmwAAAAAElFTkSuQmCC","orcid":"","institution":"Universidade Federal do Oeste do Pará)","correspondingAuthor":true,"prefix":"","firstName":"Elvis","middleName":"Santos","lastName":"Leonardo","suffix":""},{"id":335445224,"identity":"19066a9b-296f-4238-9a6c-64bc5a81aa4e","order_by":1,"name":"Kauê Santana","email":"","orcid":"","institution":"Universidade Federal do Oeste do Pará, Instituto de Biodiversidade)","correspondingAuthor":false,"prefix":"","firstName":"Kauê","middleName":"","lastName":"Santana","suffix":""},{"id":335445225,"identity":"85532f6e-02d1-4673-af77-778e0777cf8a","order_by":2,"name":"Thiago André","email":"","orcid":"","institution":"Universidade de Brasília, Brasília (DF)","correspondingAuthor":false,"prefix":"","firstName":"Thiago","middleName":"","lastName":"André","suffix":""}],"badges":[],"createdAt":"2024-07-21 22:53:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4778293/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4778293/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11105-025-01547-9","type":"published","date":"2025-02-19T15:57:15+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63013317,"identity":"816e1d57-72e8-411c-9775-32e315588836","added_by":"auto","created_at":"2024-08-22 06:11:34","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":74643,"visible":true,"origin":"","legend":"\u003cp\u003eMaximum likelihood phylogenetic analysis of the GBSS enzyme in flowering plants. The tree is derived from the alignment of nucleotide sequences of coding regions. The taxa in blue represent eudicots, those in green represent monocots, and those in violet represent the taxa that share the GBSSII isoform. Two organisms, \u003cem\u003eMusa acuminata\u003c/em\u003e among monocots and \u003cem\u003ePrunus avium\u003c/em\u003e among eudicots, are represented. The region highlighted in violet in the figure shows the GBSSII diversification that occurred within the eudicot group in the most recent common ancestors among Fabids, Superasterids, and Superrosids. Bootstrap values for all branches are provided in Supplementary Material S2\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/45a0fde3e1de100a7760fbe5.jpg"},{"id":63013936,"identity":"e392bdfd-2701-4109-bbf7-cf9a73794757","added_by":"auto","created_at":"2024-08-22 06:19:35","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":96236,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentation of the theoretical model and structural alignment of the GBSS isoforms’ structures. (A) Structure of \u003cem\u003eOryza brachyantha\u003c/em\u003e GBSSI (ObGBSSI); the region in green represents the catalytic domain involved in starch synthesis (InterPro: IPR013534, N-terminal region), and the purple region represents the glycosyltransferase domain, family 1 (InterPro: IPR001296, C-terminal region) of the protein. In red, Cys336 and Cys528 are conserved in the OsGBSSI reference structure, these residues link both the N and C terminal domains by a disulfide bond B) Structure of \u003cem\u003eOryza sativa japonica\u003c/em\u003e GBSSI (OsGBSSI); the region in cyan represents the catalytic domain involved in starch synthesis (InterPro: IPR013534, N-terminal region), and the orange region represents the glycosyltransferase domain, family 1 (InterPro: IPR001296, C-terminal region) of the protein. (C) Structural alignment between ObGBSSI and OsGBSSI; the N- and C-terminal domains of ObGBSSI and OsGBSSI show the structural overlap between the starch synthesis and glycosyltransferase domains, family 1, thus confirming a high structural conservation; RMSD-Cα = 0.340 Å. The red arrow shows the adenosine diphosphate complexed to the OsGBSSI structure\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/ab098bbb39e76b1fd9f7c98f.jpg"},{"id":63013319,"identity":"f22c869a-0d6a-4fe0-890e-060c8b1b4bcf","added_by":"auto","created_at":"2024-08-22 06:11:35","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":72543,"visible":true,"origin":"","legend":"\u003cp\u003e(A) \u003cem\u003eOryza brachyantha\u003c/em\u003e GBSSI (ObGBSSI) structure showing the KTGGL motif at the N-terminal region. The motif is highlighted with a purple-colored region and arrow. (B) Superposition of the \u003cem\u003eOryza sativa japonica\u003c/em\u003e GBSSI (OsGBSSI) structure (residues in green color, PDB 3VUF) with the ADP-complexed structure. The ADP molecule is highlighted with the electron density map. Residues from ObGBSSI are shown in blue. The dashed lines represent the hydrogen bonds\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/91b85055d2c0715f07a2da4b.jpg"},{"id":63013320,"identity":"062f5fd5-1e86-497b-a71a-1701063211a1","added_by":"auto","created_at":"2024-08-22 06:11:35","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":106792,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentation of the modeled structures of GBSSII and structural alignment. (A) Structure of the MaGBSSII. The region in blue represents the catalytic domain of starch synthesis (InterPro: IPR013534, N-terminus), and the region in red represents the glycosyltransferase, family 1 domain (InterPro: IPR001296, C-terminus). (B) Structure of the HvSSI. The region in cyan represents the catalytic domain of starch synthesis (InterPro: IPR013534, N-terminus) and the region in orange represents the glycosyltransferase, family 1 domain (InterPro: IPR001296, C-terminus). (C) Structural alignment between MaGBSSI and HvSSI. The green arrow shows the adenosine diphosphate molecule attached to the HvSSI structure\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/6e61b2877315196cdd6068ad.jpg"},{"id":63013325,"identity":"c250b392-a5a9-4653-8e81-24520338db16","added_by":"auto","created_at":"2024-08-22 06:11:35","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":90794,"visible":true,"origin":"","legend":"\u003cp\u003eMaltopentaose complexed to the SSI protein structure as seen in an electron density map. Residues in blue represent the SSI structure of HvSSI (PDB ID: 4HLN) and residues in green represent the GBSSII structure of MaGBSSII. The dashed lines are likely interactions with hydrogen molecules\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/4bb61797e7d0d600c82eb978.jpg"},{"id":63013324,"identity":"be6c9dc7-a26f-471f-871b-e3ddd39b446d","added_by":"auto","created_at":"2024-08-22 06:11:35","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":177682,"visible":true,"origin":"","legend":"\u003cp\u003eMultiple sequence alignment of the modeled GBSSI and GBSSII, including the sequences used as templates from Oryza sativa (PDB ID: 3VUE, chain A) and Hordeum vulgare (PDB ID: 4HLN, chain A). The classification of the protein family is highlighted in red, and the protein domains are shown in green and blue.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/83d8cee72d357d3593d4fb2d.jpg"},{"id":63013939,"identity":"8e929b00-76fc-40c6-be03-45143306c2cd","added_by":"auto","created_at":"2024-08-22 06:19:35","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":168571,"visible":true,"origin":"","legend":"\u003cp\u003eMultiple sequence alignments of the modeled GBSSI and GBSSII, including sequences from taxons of the Poaceae family. The KTGGL motif and the residues Cys336 and Cys528 present in ObGBSSI are highlighted at the sequence alignment\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/4e9be14fa1c4952e56ba6615.jpg"},{"id":63013318,"identity":"16d34d17-01b3-4df2-bd91-4310ccf6347b","added_by":"auto","created_at":"2024-08-22 06:11:35","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":76665,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Alanine scanning results of the amino acid sequence of ObGBSSI, where Cys225 corresponds to Cys336 and Cys447 corresponds to the position of residue Cys528 in the analysis. (B) Protein sequence of MaGBSSII and the impact of substitutions in its amino acid sequence, with the KTGGL protein motif highlighted\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/f3963976673c331882d6a274.jpg"},{"id":77052720,"identity":"814ee6b8-7a83-48fa-b8bc-d8196610e04b","added_by":"auto","created_at":"2025-02-24 16:23:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1625345,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/c4a287e8-9d8f-4b56-b00d-74ca63ffb8ed.pdf"},{"id":63013937,"identity":"a69fd872-2b48-4c85-84c8-0bf7237827b1","added_by":"auto","created_at":"2024-08-22 06:19:35","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1465451,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialS1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/460901c10b768152e51fdf6a.pdf"},{"id":63013327,"identity":"7209e512-2183-4bf6-885c-d7e06802eefa","added_by":"auto","created_at":"2024-08-22 06:11:35","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":209684,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialS2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/e7a55bfb92b5a6469296ca19.pdf"},{"id":63013323,"identity":"195dbb04-1996-4030-8712-9686c4ab5f55","added_by":"auto","created_at":"2024-08-22 06:11:35","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":86594,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/5d814e0938d6b70703870d23.xlsx"},{"id":63013326,"identity":"993870de-240b-4daf-8eb9-cbe42376fcdc","added_by":"auto","created_at":"2024-08-22 06:11:35","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":85881,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4778293/v1/1d2ea8b0d84d2f940f243a78.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Molecular evolution of the granule-bound starch synthase in flowering plants","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStarch is the main storage carbohydrate produced by plants.\u0026nbsp;It is widely used for human nutrition and is one of the main constituents of cereals, tubers, legumes, and fruits\u0026nbsp;(Miao et al. 2014; do Carmo et al. 2020; Seung et al. 2020).\u0026nbsp;Starch exists in the form of semi-crystalline insoluble granules and is composed of two types of polymers: amylose and amylopectin\u0026nbsp;(Cheng et al. 2012; Miao et al. 2014; do Carmo et al. 2020; Seung et al. 2020); the relative proportions of which vary\u0026nbsp;in different organs.\u0026nbsp;Amylose is a linear polymer formed\u0026nbsp;by glucose residues that are linked by\u0026nbsp;α-1,4 bonds.\u0026nbsp;Amylopectin also contains linear chains with\u0026nbsp;α-1,4 bonds, in addition to\u0026nbsp;branched chains with\u0026nbsp;α-1,6 bonds\u0026nbsp;(Kato et al. 2019; Seung et al. 2020).\u0026nbsp;Amylopectin is the main polymer of starch forming part of the semi-crystalline matrix of the granule, with the adjacent chains forming double helices that pack into semicrystalline lamellae, while the branching points give rise to amorphous lamellae\u0026nbsp;(Seung 2020). However,\u0026nbsp;the role of amylose in plant growth and survival remains unclear\u0026nbsp;(Seung et al. 2020).\u003c/p\u003e\n\u003cp\u003eThe synthesis of amylose is catalyzed by granule-bound starch synthase (GBSS), which transfers glucose residues from ADP-glucose\u0026nbsp;to produce long chains of amylose and amylopectin (Cheng et al. 2012). In most cereals studied to date, GBSS consists of two isoforms:\u0026nbsp;GBSSI and GBSSII.\u0026nbsp;\u003cem\u003eGBSSI\u003c/em\u003e is expressed mostly in storage tissues such as\u0026nbsp;the endosperm and seed embryos,\u0026nbsp;whereas \u003cem\u003eGBSSII\u003c/em\u003e expression is linked mostly to leaves, stems, roots, and pericarps\u0026nbsp;(Vrinten and Nakamura 2000; Dian et al. 2003; Cheng et al. 2012). In addition, there may be a difference\u0026nbsp;in the expression profiles of\u0026nbsp;further isoforms: GBSSIa and GBSSIb. For instance, in cereals, other plants (Vrinten and Nakamura 2000; Dian et al. 2003; Cheng et al. 2012)\u0026nbsp;and peas (\u003cem\u003ePsium sativum\u003c/em\u003e), \u003cem\u003eGBSSIa\u003c/em\u003e is highly expressed in embryos and \u003cem\u003eGBSSIb\u003c/em\u003e is highly expressed in leaves\u0026nbsp;(Edwards et al. 2002).\u003c/p\u003e\n\u003cp\u003eThe isoenzymes involved in starch synthesis have been widely reported in\u0026nbsp;monocots and dicots.\u0026nbsp;During starch synthesis, the \u003cem\u003eWaxy\u003c/em\u003e gene encodes GBSS (Miao et al. 2014; Li et al. 2019). Phylogenetic analysis of the \u003cem\u003eGBSS\u003c/em\u003e gene showed that monocots contain the\u0026nbsp;GBSSI isoform\u0026nbsp;and form\u0026nbsp;a group separate from the dicots, which contain the GBSSII isoform\u0026nbsp;(Lu et al. 2012).\u0026nbsp;This suggests a divergence in the enzymes responsible for starch synthesis in plants.\u0026nbsp;Another study that evaluated the variation in \u003cem\u003eGBSSI\u003c/em\u003e in a group of Poaceae showed the conservation of exons and introns (Shapter et al. 2009). Characterization of a new gene (\u003cem\u003eCrGBSSIb\u003c/em\u003e) in \u003cem\u003eAmaranthus cruentus\u003c/em\u003e and its phylogenetic analyses also revealed that monocots are grouped under GBSSI while dicots are grouped under GBSSII,\u0026nbsp;which is consistent with previous studies (Cheng et al. 2012; Park et al. 2017). Moreover, a study on the evolution of GBSS genes in angiosperms revealed the occurrence of a duplication event 251 million years ago(Lu et al. 2012; Cheng et al. 2012). Other studies involving GBSS and other genes that participate in starch synthesis\u0026nbsp;have indicated that there were one or two gene duplication processes before the grasses diverged (Cheng et al. 2012). Furthermore, there are structural similarities between GBSS and soluble starch synthases, which may be attributed to common ancestry and duplication events (Qu et al. 2018). The molecular evolution of enzymes involved in starch synthesis in plants has been extensively studied to understand the evolutionary relationships that permeate\u0026nbsp;starch evolution and the functional aspects of their molecular mechanisms\u0026nbsp;(Saha et al. 2014; Banerjee and Deshpande. 2016; Almeida de Jesus et al. 2022). Previous studies have reported the presence of genes encoding the GBSS enzyme in \u003cem\u003eP. sativum\u003c/em\u003e (Edwards et al. 2002), rice (\u003cem\u003eOryza sativa\u003c/em\u003e) (Momma and Fujimoto.\u0026nbsp;2012), barley (\u003cem\u003eHordeum vulgare\u003c/em\u003e) (Cuesta-Seijo et al. 2013; Li et al. 2019), and banana (\u003cem\u003eMusa acuminata\u003c/em\u003e) (Miao et al. 2014).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOwing to the low number of copies of the gene encoding GBSS, it has been widely used to study phylogenetic and evolutionary relationships in plants (Cheng et al. 2012). However, most of these studies have focused on small phylogenetic groups (Cheng et al. 2012; Li et al. 2012) and no comprehensive phylogenetic studies involving angiosperms as a whole, to our knowledge, have been reported to date. Further, only a few computational studies on the structural aspects of this enzyme have been reported (Cuesta-seijo et al. 2013; Momma and Fujimoto. 2012), limiting a better understanding of its function. Evolutionary analyses have provided new insights into the evolutionary history of this enzyme, allowing us to better understand its structural and functional diversification (Saha et al. 2014; Banerjee and Deshpande 2016; Almeida de Jesus et al. 2022a). In this study, we used homology modeling to determine the enzyme structural diversity by identifying important protein domains and motifs. For that, we performed a comprehensive phylogenetic analysis of genes encoding the GBSS enzyme.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e\u003cstrong\u003eDNA Sequence Recovery\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe coding sequences of two genes that encode the GBSS enzyme were obtained through the NCBI GenBank database (//www.ncbi.nlm.nih.gov/) (Benson et al. 1990). A thorough search was conducted using the BLASTn tool to identify the maximum number of available taxa in the database (Altschul et al. 1997). Two reference sequences were selected for the GBSSI isoform: NM103023.4 from \u003cem\u003eArabidopsis thaliana\u003c/em\u003e and FJ804468.1 from \u003cem\u003eOryza sativa\u003c/em\u003e. For the GBSSII isoform, the sequences chosen were GQ150862.1 from \u003cem\u003eOryza sativa\u003c/em\u003e and AF109395.1 from \u003cem\u003eTriticum aestivum\u003c/em\u003e. These accession codes were selected due to their complete sequence annotation in the database. Sequences with identities above 80% were included in subsequent analyses. In addition, a sequence search was conducted throughout the GenBank database using the name of the enzyme ‘\u003cem\u003egranule-bound starch synthase\u003c/em\u003e’ to retrieve sequences that may not have been captured through Blastn.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe coding sequences (CDSs) of GBSS were obtained from GenBank and only complete CDSs were selected for analysis. To complement the information obtained from the database, we recovered sequences of taxa with unannotated genomes by performing an optimized BLASTn search using the same reference sequence, NM103023.4 and FJ804468.1 for GBSSI, to isoform GBSSII GQ150862.1 and AF109395.1. In this case, only the genomes of taxa without any representatives recovered in the first search were obtained.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo annotate the coding and non-coding regions, exons, and introns of the recovered genome fragments, we used the AUGUSTUS\u0026nbsp;program\u0026nbsp;(Stanke and Waack 2003), which is used for gene prediction using genomic fragments (https://bioinf.uni-greifswald.de/augustus/) (Stanke et al. 2004). AUGUSTUS performs ab initio and alignment-based gene prediction (Stanke et al. 2006, 2008). All\u0026nbsp;the predicted genes were validated\u0026nbsp;against the GenBank database\u0026nbsp;using the BLASTn algorithm to verify their similarity\u0026nbsp;to other GBSS genes deposited in the database.\u003c/p\u003e\n\u003cp\u003eA total of 732 accessions were obtained, including\u0026nbsp;the CDSs of GBSSI and GBSSII\u0026nbsp;and 101 genes obtained from unannotated genomes. We also applied a filter to eliminate repeat data, very short sequences (\u0026lt; 500 bp), and non-GBSS genes. Finally, we obtained 376 GBSS gene sequences that were used in\u0026nbsp;the subsequent analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhylogenetic analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, multiple sequence alignment was performed using the MUSCLE algorithm (Edgar 2004), implemented in Geneious Prime® version 20221.1 (https://www.geneious.com/prime/) using the default settings. Then, phylogenetic analyses were performed using the W-IQ-TREE web server(Trifinopoulos et al. 2016). The construction of the phylogenetic tree was based on the maximum likelihood method (Felsenstein 1981),\u0026nbsp;in which the substitution model was automated with an ultrafast bootstrap with a value of 3,000 and maximum of 2,000 iterations. The minimum correlation coefficient was set at 0.99. To support the branches, the SH-aLRT test was used with 2,000 replicates (Guindon et al. 2010) along with the approximate Bayes test (Anisimova et al. 2011). The best nucleotide substitution model for the sequence dataset was the GTR+F+I+G4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCalculation of dN/dS rates\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of positive selection which is indicative of adaptive evolutionary changes was carried out through the Datamokey webserver (https://www.datamonkey.org) (Kosakovsky Pond and Frost 2005; Delport et al. 2010; Weaver et al. 2018). The aBSREL test, implemented on a server, is a fundamental approach to infer the presence of positive selection in molecular sequences (Kosakovsky Pond et al. 2011; Smith et al. 2015).\u003c/p\u003e\n\u003cp\u003eThe aBSREL test expands the Branch-Site Random Effects (BSREL) model, allowing for the assessment of the rate of evolution (ꙍ\u0026nbsp;= dN/dS) among different branches of the phylogenetic tree. Using the Likelihood Ratio Test (LRT), a null model (lack of positive selection) is compared to an alternative model on the branches, while the adjusted p-value test is applied to control false positives and determine the statistical significance of the results\u0026nbsp;(Smith et al. 2015).\u003c/p\u003e\n\u003cp\u003eBefore submitting the alignment of the coding GBSS sequences to the web server, the data was prepared by removing all stop codons using the HyPhy 2.5.57 program.\u0026nbsp;(Kosakovsky Pond et al. 2020). Subsequently, the sequences were aligned with the MUSCLE algorithm, implemented in the MEGA program version 11.0.13\u0026nbsp;(Kumar et al. 2018), using the following sets: gap open: -2.90; gap extend: -0.20; hydrophobicity multiplier: 1.20; using 1,000 iterations. The remaining settings were kept as default. The resulting alignment was checked to ensure the correct alignment of reading frames.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIn silico\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003estructural modeling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe structures of the GBSS isoforms were modeled using the Swiss-Model web server (Arnold et al. 2006; Kiefer et al. 2009; Biasini et al. 2014) (https://swissmodel.expasy.org/). The alignment search for template structures was carried out on the web server and two structures were identified, one for each isoform see Supplementary Material S1. The selection of the protein sequences for modeling was determined using aBSREL analysis to detect positive selection, focusing on \u003cem\u003eOryza brachyantha, Sorghum bicolor,\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;Sorghum leiocladum\u003c/em\u003e. Additional taxa were selected to encompass representatives of major groups like Commelinids, Superrosids, and Superasterids, all of which share both isoforms. This approach aimed to identify structural patterns between the two isoforms within each classification group\u0026nbsp;(Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003eTaxa used for the \u003cem\u003ein silico\u003c/em\u003e structural modeling of the granule-bound starch synthase (GBSS) I and II.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.4040404040404%\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.2020202020202%\" style=\"width: 22.2463%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOrder\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.39393939393939%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigher-classification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.816326530612244%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eMusa acuminata GBSSII\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"2\" style=\"width: 22.2463%;\"\u003e\n \u003cp\u003eZingiberales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\" rowspan=\"7\"\u003e\n \u003cp\u003eCoomelinids\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" rowspan=\"7\"\u003e\n \u003cp\u003eMonocots\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eMusa acuminata GBSSI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.66666666666667%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eOryza sativa GBSSI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" rowspan=\"5\" style=\"width: 22.2463%;\"\u003e\n \u003cp\u003ePoales\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eOryza brachyantha GBSSI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eOryza brachyantha GBSSII\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eSorghum leiocladum GBSSI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eSorghum bicolor GBSSII\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.816326530612244%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003ePrunus avium GBSSI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"2\" style=\"width: 22.2463%;\"\u003e\n \u003cp\u003eRosales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.448979591836736%\" rowspan=\"4\"\u003e\n \u003cp\u003eSuperrosids\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.3265306122449%\" rowspan=\"9\"\u003e\n \u003cp\u003eEudicots\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003ePrunus avium GBSSII\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.66666666666667%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eGlycine soja GBSSI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" rowspan=\"2\" style=\"width: 22.2463%;\"\u003e\n \u003cp\u003eFabales\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eGlycine soja GBSSII\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.78048780487805%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eSolanum tuberosum GBSSI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.390243902439025%\" rowspan=\"2\" style=\"width: 22.2463%;\"\u003e\n \u003cp\u003eSolanales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.829268292682926%\" rowspan=\"5\"\u003e\n \u003cp\u003eSuperrasterids\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eSolanum tuberosum GBSSII\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.66666666666667%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eArabdopsis thalianna GBSSI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" style=\"width: 22.2463%;\"\u003e\n \u003cp\u003eBrasicales\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"66.66666666666667%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eCoffea euginoides GBSSI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" rowspan=\"2\" style=\"width: 22.2463%;\"\u003e\n \u003cp\u003eGentianales\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" valign=\"top\" style=\"width: 54.8551%;\"\u003e\n \u003cp\u003e\u003cem\u003eCoffea euginoides GBSSI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eWe used the homolog structure of \u003cem\u003eOryza sativa japonica\u003c/em\u003e (PDB ID:3VUE, chain A, resolution 2.7 Å) and \u003cem\u003eHordeum vulgare\u003c/em\u003e (PDB ID:4HLN, chain A, resolution 2.7 Å). All structures modeled had loop regions refined using a script from the Modeller program (Webb and Sali 2017). In general, the structure of \u003cem\u003eOryza sativa\u003c/em\u003e was used as a template for the GBSSI isoform of the taxa, while the structure of \u003cem\u003eHordeum vulgare\u003c/em\u003e was used as a template for the GBSSII isoform. The taxa \u003cem\u003eOryza brachyantha\u003c/em\u003e, \u003cem\u003eSorghum bicolor\u003c/em\u003e, and \u003cem\u003eSorghum leiocladum\u003c/em\u003e for GBSSI and GBSSII isoforms were modeled using the protein structure of \u003cem\u003eOryza sativa\u003c/em\u003e as a template. For more details verify the Supplementary Material S1.\u003c/p\u003e\n\u003cp\u003eThe theoretical models were validated by stereochemical analysis using the Ramachandran plot (Lovell et al. 2003) on a Swiss-Model server (Arnold et al. 2006; Biasini et al. 2014). The quality of the stereochemistry of the models was determined as a function of their phi and psi angles. Structural validation of the modeled protein structure was performed using the QMEAN plot (Benkert et al. 2008, 2011), which is a composite score that employs average strength statistical potential (Sippl 1993). To verify possible errors in the structures, an analysis was performed on the ProSa-Web server (Wiederstein and Sippl 2007) (https://prosa.services.came.sbg.ac.at/prosa.php), which is a widely used tool for checking errors in three-dimensional protein structures, and allows error recognition for both theoretically and experimentally elucidated structures (Wiederstein and Sippl 2007).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe theoretical structures of the GBSS enzyme were aligned using the USCF Chimera version 1.17 (Pettersen et al. 2004). To perform the structural alignment, we selected the modeled structures of \u003cem\u003ePrunus avium\u003c/em\u003e GBSSI and \u003cem\u003eMusa acuminata\u003c/em\u003e GBSSII. This selection was based on the lowest mean squared deviation of α-carbons (RMSD-Cα) obtained between the two structures. Structural comparisons allowed us to analyze the similarities and differences of conserved and non-conserved structural motifs for both protein isoforms. We also inferred relevant structural aspects of the molecular function, such as the residue composition and conformation of their binding sites.\u003c/p\u003e\n\u003cp\u003eThe InterPro\u0026nbsp;database,\u0026nbsp;available in the EMBL database from the European Institute of Bioinformatics,\u0026nbsp;was used to identify protein families and domains\u0026nbsp;(Goujon et al. 2010; McWilliam et al. 2013). The MOTIF tool available in GenomeNet was used to perform a functional search using the amino acid sequence to identify structural motifs (Kanehisa 2002). We used all sequences applied in the comparative modeling (Table 1) and all sequences were aligned and compared to verify the conserved regions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMutational analysis of protein structures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted mutation analysis of ObGBSSI and MaGBSSII to determine which amino acids significantly affect structural stability. An alanine scan was performed using the FoldX 5.0 program \u0026nbsp;(Delgado et al. 2019). The FoldX toolkit was created to evaluate the effect of mutations on protein structure stability (Guerois et al. 2002; Schymkowitz et al. 2005) The software uses a linear combination of different empirical terms to calculate the free energy (ΔG). The empirical terms included electrostatic interactions, Coulomb terms, van der Waals terms, hydrophobic and solvation forces, hydrogen bonds, and other types of interactions. The result was interpreted using mutational analysis (ΔΔGfold) and expressed as the difference between the free energy of the wild-type structure (ΔGwt) and the mutant structure (ΔGmut) (kcal.mol-1) according to Equation 1:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAXIAAAA3CAYAAAARxsFiAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAf3SURBVHhe7dtJjw1fGMfx0/+9oXkDgo1YSKRZiJXEECuJGGJlIYSIFRbNkpg3IqZY2Jh2NsSQWCAShBASG0TEshHegP/9HvXTR3XV7Uu7dft0/z5JqenU9NQ5z+06Vfp+tAQzM8vWf8XYzMwy5URuZpY5J3Izs8w5kZuZZc6J3Mwsc07kZmaZcyI3M8ucE7mZWeacyM3MMudEbmaWOSdyM7PMOZGbmWXOidzMLHNO5GZmmXMiNzPLnBO5mVnmnMjNzDLnRG5mljkncjOzzDmRm5llzonczCxzTuRmZjUePnwYVq1aVcz9tGPHjtDX11fM/cSyq1evFnPN60kif/nyZQzEaBe+cePGMHfu3GJupJs3b4ZFixbFfTEw3ctgdovjMDaj1bfPnz/HhjhjxoxYjjHz79+/L0rYZHT06NGwefPmcOvWrWJJiPXjzJkzxdyw06dPh4sXL8Z60xM/emD79u0/OPSGDRuKJSO9e/culmF48eJFsXTYlStX4rqzZ8/G+aGhobi/lStXxvmJwnEYu3b1jXgNDAzEgVjjwYMHsTxjm5y493PmzCnmfnfkyJFYP6rQ7miTTWs8kdNw+vv7fwWD+SqDg4OxDGWZTrEN27I+RUOcaAnMcRib0eobMWV9eTnJ34l88iKJ1yVk1aUq+sOraY0fkb8caSS64Lpg0bgoQ9nyL6P+Cq36C7VXSJycU7vhb5JrbnEYb0arb8S03ZOhTT56IqvTLpGj3Y9AtzTeR37s2LGwe/fuMHv27NBKbOH69evFmmH0ZdIvTJlNmzaFViOM/Zzy8ePHOF6wYEEcjwf0o7Xi2XZI+9o6kWMcxpvR6hsxXbhwYTFnFsKjR49CKxkXc39uxYoV4f79+8VcMxpN5LyU46UdjQq8SLh27dqIl0onTpyIiQtLly6NQT137lycr0PS08u+tOy+ffviMhJiHd5MU4aXG2Usq1vXbU3HQddKPMp4c1+37l/RfRht6PQcOq1vZWzDcXjpKfyAann6Y1rG+vJXDqLzt/Htw4cPbT8u6ETTL8obTeQnT56MjUmWL18ex3fv3o1j0Ei/fv0aE5e0Hn0rvzhIGxQJanBwMPT394dt27bFZWzz7NmzMDQ0FNasWROXVeFYbFtl7969YWBgoJirp0TXbqhr4FV6EYd213rp0qViqnu41qonmfKQxqSdTuobnj9/Xkz99Pjx4zg+dOhQHGPt2rXxq4QbN26EKVOmFEtHYn2dduvMxqKxRM4v1JMnT377i3DmzJkxOV24cKFYEsLly5fDnj17irmf1q9fH5Maf2GBR2Tcvn07jmXatGlh8eLFxVwIr169CsuWLYvHafeXKNi2DtuP5l93rfQqDnXX2kkM2uETP37MmtJpfWP+zp078fxE1zp//vw4Zh1dMPyArF69+tdf+FWmTp1aTI3Ubt2/wFNXL54cJ5pZs2aFt2/fFnN/p10d6YpWgmkEL5zKX1dAL+x4GcVQ9QUBeIHAPqSVxGJZfVnANnxCxnLohYUGUKbVcOM826ZfgXBu6fnpawaVrTr3bul2HHg5Shnm2V/6Yobt0n2l8WKsdaL7p+Nxbjq/1l+gcR2x4zhMa+i2TuobFB/KK94qo2vl2nTe2mdaP4iRtmUbxQJprFW+jGWUYZ+a5hwoz0AcwbFZr/NiWsfSOWtosr5ONKoTdXQf6pTbVBO636IKqsR1A18XMFSt08A+hIZD49N+FTwalRDwtEJTXo2OBlZuJCrLftifGicNK91Pt3U7DpRJr5XtdK1pIle8wHrKaV2K+BBPyrC9zo99p0mN7ZuieNQNxFioA0q2DFw3STW9VpaL6gc/BlyzkjDYJr1myulY+mEr03Ltj2ndH/ab3juOpfNieXos5tOy9vfUjspYzv3RUC7DPWR50xrrWvny5QtXVzvQn8tQtU4D+xAef/nfVNovj0I8Rlf1IQuP23yhwLZ86UH3w+vXr4u1w/gaZOvWrb8esTVuSrfj0KpsYcmSJXFaXQ9v3ryJ4xTx2rlzZ5xuF4MtW7bE7h36nnft2hVfytL9Q59yK7EUpZrVSX0TukuePn36ax3xPHjwYG1fPPVDL1GJy7p16+I7iCrEWseq61rRcu0Puj/lLr+m6+JkRd3dv39/MTeM9pXWo3JX5fHjx3tS5xv//LBJ3759i4NMnz49vtiiz1N9qGowaVkaz/nz52M5Del+clOOQ+uv1fiJFUi4zM+bNy/Oc63fv3+P08Tr1KlTcZp4Qevoi1V/LC8RDx8+HD+5IimS2HnRSGIqfxqp2OeEc07H1A8aNNfBsnv37sV3ECA+Kgdiq6+HPn36FMda38k7g/K9A/thH+WXtFDZ3GI83vAjfuDAgT96r6OPGfhooHGtX5UJicdPLo9Bj6I8/vMoyjIevfUYWi6rLgLmGfOozSMV2+emKg48yusRkXHavaSy4HpVjkd8HusZQNn0sZIuGMVTj5eMU4qpuiFykdYFUD+oEyxjYJpl0DLFghhR1xjUZabrJ7bQ/tlG94BlVfdO69lW55DeV47Duhzr6nhEHdZ9b4d7UdUV05Q+/mlVBrM/whcSdD/Y36Hri6cg/2cu+xecyM3MMjeh+8jNzCYDJ3Izs8w5kZuZZc6J3Mwsc07kZmaZcyI3M8ucE7mZWeacyM3MMudEbmaWOSdyM7PMOZGbmWXOidzMLHNO5GZmmXMiNzPLnBO5mVnmnMjNzDLnRG5mlrUQ/gf61BmIsapFmgAAAABJRU5ErkJggg==\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003ewhere ΔG\u003csub\u003efold,wt\u003c/sub\u003e is the change in free energy of the wild-type structure and ΔG\u003csub\u003efold,mut\u003c/sub\u003e is the change in the mutant structure. When ΔΔG \u0026lt; 0, the mutation is considered stabilizing; if ΔΔG \u0026gt; 0, the mutation is considered destabilizing. To better understand the effects of mutations on the structures, we classified the ΔΔG values into five categories: highly stabilizing (ΔΔG \u0026lt; -1.84 kcal mol\u003csup\u003e-1\u003c/sup\u003e), mildly stabilizing (-1.84 kcal mol\u003csup\u003e-1\u003c/sup\u003e ≤ ΔΔG \u0026lt; -0.46 kcal mol\u003csup\u003e-1\u003c/sup\u003e), neutral (-0.46 kcal mol\u003csup\u003e-1\u003c/sup\u003e \u0026lt; ΔΔG ≤ +0.46 kcal mol-1), mildly destabilizing (+0.46 kcal mol\u003csup\u003e-1\u003c/sup\u003e \u0026lt; ΔΔG ≤ +1.84 kcal mol\u003csup\u003e-1\u003c/sup\u003e), and highly destabilizing (ΔΔG \u0026gt; +1.84 kcal mol\u003csup\u003e-1\u003c/sup\u003e) (Almeida de Jesus et al. 2022b).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePhylogenetic analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultiple sequence alignments performed using the MUSCLE algorithm resulted in an alignment matrix of 14,457 bp of coding regions, comprising 13 exons. Phylogenetic analysis, considering the already well-known classification of angiosperms, provided evidence that \u003cem\u003eGBSS\u003c/em\u003e virtually represents the evolution of angiosperms, particularly the monocot (branch support with 100% bootstrap) and eudicot (branch support with 100% bootstrap) lineages, in addition to the major classification groups, such as Commelinids, Fabids, Superasterids, Superrosids, and Rosids (all with bootstrap values above 90%) (Figure 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results showed evidence of \u003cem\u003eGBSSI\u003c/em\u003e duplication in eudicots of the Superasterid and Superrosid groups, which is probably a consequence of a genome duplication event that may have occurred in these lineage histories, as indicated by some studies (Cheng et al. 2012; Qu et al. 2018). In general, \u003cem\u003eGBSSII\u003c/em\u003e is nested within the eudicotyledon (tricolpate) clade; however, monocot taxa were observed within this classification, specifically \u003cem\u003eMusa acuminata\u003c/em\u003e and \u003cem\u003ePhoenix dactylifera\u003c/em\u003e, which present the GBSSII isoform, indicating evolutionary convergence. The structures of the isoforms of \u003cem\u003eMusa acuminata\u003c/em\u003e (among monocots) and \u003cem\u003ePrunus avium\u003c/em\u003e (among eudicots) showed that the structures of GBSSI were more similar to each other than to those of GBSSII, which represents a group that diversified from eudicots. In principle, these results indicated that the GBSS gene possessed an ancestral GBSSI lineage from which the GBSSII lineage evolved and that the genes encoding GBSSII are not exclusive to eudicots. The complete phylogeny with the classification of groups and taxa is shown in Supplementary Material S2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003edN/dS Rates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the aBSREL analysis, out of the 512 branches analyzed, 43 were identified in the ω2 class, suggesting positive selection in these branches due to a high ω rate. On the other hand, 188 branches were classified in the ω1 class, indicating a lower ω rate, which suggests the predominance of purifying selection in these branches. Therefore, there is evidence that a greater number of taxa and sites are under purifying selection rather than positive selection. All results showed high statistical significance, as evidenced by the p-values and significant results of the LRT test. For additional details, please see the Supplementary Table S3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIn silico\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003estructural modeling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe structural isoforms of the enzyme GBSS are closely related due to their low RMSD-Cα value. The theoretical structures of GBSSI generally exhibited 16 β sheets and 18 α helices. The GBSSI from \u003cem\u003eOryza brachyantha\u003c/em\u003e and \u003cem\u003eSolanum tuberosum\u003c/em\u003e showed 17 β sheet structures, \u003cem\u003eSorghum leiocladum\u003c/em\u003e had 15 β sheet structures, while the isoform GBSSII structures showed 18 β sheets and a variation in the number of α helices ranging from 18 to 23 structures among the modeled taxa. The GBSSSII structures of \u003cem\u003eMusa acuminata\u003c/em\u003e and \u003cem\u003eSolanum tuberosum\u003c/em\u003e showed 23 α helices and \u003cem\u003ePrunus avium\u0026nbsp;\u003c/em\u003eshowed 24 α helix structures. Research in the InterPro and GenomeNet databases of the modeled structures revealed that all belonged to the glycogen synthase family of bacteria/plants (InterPro: IPR011835) and contained two domains: the starch synthesis domain (InterPro: IPR013534) and the glycosyltransferase domain, family 1 (InterPro: IPR001296).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe GBSSII isoform differs from GBSSI in its secondary structure and exhibits numerous loop regions. Its ATP binding site is situated externally. In contrast, the GBSSI isoform features a cavity between its N-terminal and C-terminal regions, forming a pit (Figures 2 and 3). Overall, 15 structural models were generated, all showing stereochemistry values exceeding 92%, approximate z-score values consistent with experimental models, and energy plots reflecting satisfactory values (see Supplementary Material S1).\u003c/p\u003e\n\u003cp\u003eThe structural alignment resulted in low RMSD-Cα values for the theoretical GBSSI structures compared with the protein structure of \u003cem\u003eOryza sativa japonica\u0026nbsp;\u003c/em\u003e(PDB ID: 3VUE), showing that the structures are structurally well correlated. Further, there was a low RMSD-Cα between the theoretical GBSSII structures and the starch synthase I (PDB ID:4HLN) in the model of \u003cem\u003eHordeum vulgare\u003c/em\u003e, showing\u0026nbsp;an excellent structural relationship. The RMSD between the\u0026nbsp;structures of the GBSSI and GBSSII isoforms showed higher values (Table 2) due to their structural differences, such as those in the number of\u0026nbsp;β-sheets\u0026nbsp;and\u0026nbsp;α-helices.\u0026nbsp;\u0026nbsp;The modeled structures of \u003cem\u003eOryza brachyantha\u003c/em\u003e, \u003cem\u003eSolanum tuberosum,\u003c/em\u003e and \u003cem\u003eSorghum leiocladum\u003c/em\u003e present a lower RMSD value and their structures are more similar to the structure used as a reference from \u003cem\u003eOryza sativa japonica\u003c/em\u003e (PDB ID: 3VUE).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e RMSD-Cα values resulting from structural alignment between target modeled structures and their respective reference structures applied in the comparative modeling.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTargets + GBSSI (3VUF)\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnzyme\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSD (Å)\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTargets + SSI (4HLN)\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSD (Å)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eArabidopsis thaliana\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eArabidopsis thaliana\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.884\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eCoffea eugenioides\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eCoffea eugenioides\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.883\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eCoffea eugenioides\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eCoffea eugenioides\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.259\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eGlycine soja\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eGlycine soja\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eGlycine soja\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eGlycine soja\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eHordeum vulgare 4HLN\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eSSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eOryza sativa Japonica\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eMusa acuminata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eMusa acuminata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eMusa acuminata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eMusa acuminata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eOryza brachyantha\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eOryza brachyantha\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.804\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eOryza brachyantha\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eOryza brachyantha\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.797\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003ePrunus avium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003ePrunus avium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.838\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003ePrunus avium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003ePrunus avium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eSolanum tuberosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eSolanum tuberosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.867\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eSolanum tuberosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eSolanum tuberosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.466\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eSorghum bicolor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eSorghum bicolor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.791\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u003cem\u003eSorghum leiocladum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003eGBSSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.8659793814433%\"\u003e\n \u003cp\u003e\u003cem\u003eSorghum leiocladum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.402061855670103%\"\u003e\n \u003cp\u003e1.804\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eGBSS1(3VUF) - Structural model used as a model for the GBSS1 isoforms\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eRMSD – Root Mean Square Derivation of Cα atoms in the structural alignment\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eSSI (4HLN) – Structural model used as a model for the GBSS2 isoforms\u003c/p\u003e\n\u003cp\u003eHere, we present the theoretical structure of the \u003cem\u003eOryza brachyantha\u003c/em\u003e GBSSI (ObGBSSI) enzyme. This enzyme consists of 504 amino acids and two structural domains and belongs to the bacteria/plant glycogen synthesizer family (InterPro: IPR011835). The starch synthesis domain (IPR013534) corresponds to residues 94 to 354 in the N-terminal region, while the glycosyltransferase domain family 1 (IPR001296) corresponds to residues 408 to 524 in the C-terminal region, as compared to the structure of \u003cem\u003eOryza sativa japonica\u003c/em\u003e GBSSI (OsGBSSI), in which the domains exhibited a good structural overlap (Figure 2). Both domains showed overlapping β-α-β structures.\u003c/p\u003e\n\u003cp\u003eThe structural alignment showed that ADP-binding residues were conserved in ObGBSSI (Figure 3). This structural overlap shows the conservation of amino acids at the binding site; the position and chemical nature are maintained and most likely the form of complexation of the PaGBSSI structure with the ADP ligand is the same. All residues that bind to ADP in OsGBSSI were observed to be conserved at the same position.\u003c/p\u003e\n\u003cp\u003eThe theoretical structure of the GBSS II enzyme from \u003cem\u003eMusa acuminata\u003c/em\u003e (MaGBSSII) contains 473 amino acid residues and belongs to the bacteria/plant glycogen synthesizer family (InterPro: IPR011835). The enzyme contains the two domains present in the ObGBSSI protein: the starch synthesis domain (IPR013534), found in the N-terminal region and comprising the residues 285–530, and the glycosyl transferase domain, family 1 (IPR001296), found in the C-terminal region and comprising residues 567–697. The structural alignment of the MaGBSSII with the SSI of \u003cem\u003eHordeum vulgare\u003c/em\u003e (HvSSI) showed a good overlap of the two structural domains (RMSD = 0.204 Å) (Figure 4). The structural comparison showed that the HvSSI residues were conserved in the MaGBSSII structure and that the structure is bound to maltopentaose (Figure 5). All amino acid residues were found to be conserved, except for a change from Thr564 in HvSSI to Asn710 in MaGBSSII. Hypothetically, the form of interaction between maltopentaose and GBSSII enzyme from \u003cem\u003eMusa acuminata\u003c/em\u003e should be similar if not identical. The two main HvSSI residues that interacted with maltopentaose were Pro537 and Phe538, in addition to the side-chain residues, Glu543, Trp548, His572, and Ser575.\u003c/p\u003e\n\u003cp\u003eBy comparing the amino acid sequences, it was possible to observe the isoforms sharing the same family and protein domains in the structures of ObGBSSI and MaGBSSII in the alignment matrix and to observe their common regions (Figure 6). Although these regions underwent diversification between GBSSI and GBSSII during evolution, they still share the same domains found in the protein family.\u003c/p\u003e\n\u003cp\u003eWe added taxa from the Poaceae family to verify the conservation of the GBSSI binding domain and the conserved residues reported in other studies. There was a sequence conservation of the KTGGL motif in GBSSI and GBSSII, in addition to two Cys336 residues present in ObGBSSI present in most GBSSI taxa; however, we noted a substitution by Val336 residue at this position. In the GBSSII isoform, Cys336 was mutated by Trp336. The Cys528 residue present in ObGBSSI was conserved in all GBSSI taxa, except in \u003cem\u003eBrachypodium distachyon\u003c/em\u003e GBSSI and \u003cem\u003eTriticum aestivum\u003c/em\u003e GBSSII, where there was a change to Phe528 at this position (Figure 7).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of mutation and their effects on protein structural stability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMutational analyses of the ObGBSSI and MaGBSSII structures were performed using alanine scanning to assess the influence of mutations on the structural stability of both proteins. Our results revealed that most alanine substitutions in the sequences of ObGBSSI and MaGBSSII were destabilizing. In ObGBSSI, the residues within the KTGGL motif had highly destabilizing values, such as Thr16 (+2.7 kcal mol\u003csup\u003e-1\u003c/sup\u003e), Gly17 (+2.96 kcal mol\u003csup\u003e-1\u003c/sup\u003e), and Leu19 (+2.26 kcal mol\u003csup\u003e-1\u003c/sup\u003e), which play important roles in GBSSI activity.\u0026nbsp;Furthermore, the conserved residues Cys336 (+6.28 kcal mol\u003csup\u003e-1\u003c/sup\u003e) and Cys528 (+5.53 kcal mol\u003csup\u003e-1\u003c/sup\u003e) were destabilizing in both analyzed sequences (Figure 8). Additionally, some residues that may interact with ADP, such as Asn265 (+2.24 kcal mol-1), Leu434 (+2.89 kcal mol-1), Gly435 (+6.09 kcal mol\u003csup\u003e-1\u003c/sup\u003e), and Ile489 (+2.19 kcal mol\u003csup\u003e-1\u003c/sup\u003e) showed destabilizing mutations.\u003c/p\u003e\n\u003cp\u003eIn GBSSII isoforms, Cys336 was replaced by Val in \u003cem\u003eOryza brachyantha\u003c/em\u003e, \u003cem\u003eSorghum bicolor\u003c/em\u003e, and\u003cem\u003e\u0026nbsp;Zea mays\u003c/em\u003e, while in other taxa, this residue is altered to Trp. In MaGBSSII, the Gly residue (+6.03 kcal mol\u003csup\u003e-1\u003c/sup\u003e) with a high destabilizing value within the same conserved domain found in GBSSI isoforms stood out, along with a residue that may interact with the ligand, such as Trp694 (+3.74 kcal mol\u003csup\u003e-1\u003c/sup\u003e). Other highly destabilizing residues in MaGBSSII included Gly301 (+6.03 kcal mol-1), Gly415 (+6.14 kcal mol\u003csup\u003e-1\u003c/sup\u003e), Phe421 (+5.37 kcal mol\u003csup\u003e-1\u003c/sup\u003e), Gly461 (+12.33 kcal mol\u003csup\u003e-1\u003c/sup\u003e), Gly542 (+7.02 kcal mol\u003csup\u003e-1\u003c/sup\u003e), Gly582 (+9.28 kcal mol\u003csup\u003e-1\u003c/sup\u003e), and Arg626 (+5.84 kcal mol\u003csup\u003e-1\u003c/sup\u003e). The complete list of amino acid residues in the isoforms can be found in the supplementary material S4.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur results shed new light on the evolutionary history and structural features of the Granule-Bound Starch Synthase enzyme, allowing us to understand molecular diversification and its structural evolution and conservation throughout angiosperms\u0026rsquo; history.\u003c/p\u003e\n\u003cp\u003ePhylogenetic analysis showed that \u003cem\u003eGBSS\u003c/em\u003e was well-conserved, reflecting the classification of large higher phylogenetic groups, such as eudicots and monocots, as well as other large groups, such as commelinids,\u0026nbsp;Fabids, Superasterids, Superrosids, and Rosids. Gene duplication events were observed for Superrosids and Superasterids. The GBSSII isoform evolved from an ancestral GBSSI lineage (Figure 1). Diversification occurred in the eudicot group, although taxa that preserve this isoform were present within the monocot group. Some monocot taxa were present within the GBSSII clade, which is an indication of evolutionary convergence. Theoretical three-dimensional structures were classified in the same large family of proteins\u0026nbsp;and their protein domains\u0026nbsp;were conserved; however, the catalytic sites showed some differences. Although we demonstrated the diversification of this gene in parallel with the evolution of flowering plants, most of the structural characteristics of the enzyme were shown to be conserved.\u003c/p\u003e\n\u003cp\u003ePhylogenetic analysis of the GBSS coding sequences showed their conservation in large phylogenetic groups, such as commelinids, Superasterids, and Superrosids, in addition to the clustering of two major phylogenetic groups of plants: monocots and eudicots. These data are in agreement with the classifications presented by other phylogenetic studies using other molecular markers, such as the APG III and IV (The Angiosperm Phylogeny Group) systems\u0026nbsp;(Bremer et al. 2009; Chase et al. 2016), thus highlighting the effectiveness of \u003cem\u003eGBSS\u003c/em\u003e in deciphering the phylogenetic histories of flowering plants. Phylogenetic analysis showed that the gene encoding the GBSS enzyme forms a GBSSI group in monocots and\u0026nbsp;that the GBSSII group is concentrated in eudicots, as suggested by previous studies (Cheng et al. 2012; Lu et al. 2012; Park et al.\u0026nbsp;2017). However, the GBSSII isoform is not exclusively\u0026nbsp;nested in eudicots,\u0026nbsp;being also present in monocots. The appearance of GBSSII isoforms in monocots has been cited in previous studies (Cheng et al. 2012; Lu et al. 2012) but it was suggested that the diversification between the groups was quite remote\u0026nbsp;and that they were separated into distinct groups.\u0026nbsp;Nevertheless,\u0026nbsp;during the process of\u0026nbsp;GBSS diversification, some taxa, such as maize (\u003cem\u003eZea mays\u003c/em\u003e), rice (\u003cem\u003eOryza sativa\u003c/em\u003e, sorghum (Sorghum bicolor), wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e), and banana (\u003cem\u003eMusa acuminata\u003c/em\u003e), maintained this isoform,\u0026nbsp;which indicates that it is a key component in the metabolism of these organisms. Miao et al. (2014) showed that the GBSSII isoform of banana has a greater phylogenetic relationship with those in groups of eudicots than the GBSSI isoforms of monocots, including its own\u0026nbsp;GBSSI isoform.\u003c/p\u003e\n\u003cp\u003eThe process of GBSS enzyme diversification between monocots and eudicots may be associated with a major whole-genome duplication event that occurred 251 million years ago (Cheng et al. 2012). A previous study that evaluated the diversification of other starch-synthesizing enzymes in plants showed that these enzymes underwent genetic duplication at different levels (Qu et al. 2018). Furthermore, the occurrence of a whole-genome duplication event in an angiosperm ancestor approximately 150 to 270 million years ago is well known (Jiao et al. 2011). Thus, duplication of the ancestral GBSS gene in angiosperms was likely the result of duplications in the genome, in addition to genetic duplications at different levels (Cheng et al. 2012; Qu et al. 2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eModeled structures of GBSSI and GBSSII\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe structural overlap between ObGBSSI and the reference OsGBSSI, in addition to being a good overlap, reveals a typical GT-B structure and a peculiar Rossmann fold in OsGBSSI in the N- and C-terminal domain (Momma and Fujimoto, 2012). Another important structural feature of the ObGBSSI is the presence of a KTGGL motif in the N-terminal region. Studies on \u003cem\u003eEscherichia coli\u003c/em\u003e glycogen synthase complexed with ADP and maltooligosaccharides\u0026nbsp;have shown closed dynamic movement with two Rossmann fold domains associated with the KTGGL motif (Momma and Fujimoto, 2012). The RMSD-C\u0026alpha; value for both enzymes was 0.340 \u0026Aring;, suggesting that the structure\u0026nbsp;of\u0026nbsp;ObGBSSI is very similar to that of OsGBSSI and probably has a closed active state. We conjecture that the mechanism of ADP binding to the active site may be a factor that contributed to the closed state of the enzyme(Momma and Fujimoto, 2012). All residues that bind to ADP are conserved in the\u0026nbsp;ObGBSSI structure\u0026nbsp;(Figure 3). ADP can likely bind similarly to the structure of ObGBSSI. The Cys336 residue located between the N and C-terminal domain was not conserved in Poacea, which corroborates the findings of Momma and Fujimoto (2012).\u003c/p\u003e\n\u003cp\u003eComparison of the theoretical structure of GBSSII to that of HvSSI\u0026nbsp;showed\u0026nbsp;a high structural overlap that can be attributed to\u0026nbsp;the HvSSI adopting a characteristic GT-B fold (a double Rossmann fold);\u0026nbsp;the MaGBSSII structure may have the same characteristic (Cuesta-Seijo et al. 2013)\u0026nbsp;The presence of a KTGGL motif in the MaGBSSII structure validated its Rossman-like fold, similar to the GBSSI isoforms, indicating a high degree of structural similarity.\u0026nbsp;In contrast, the large N-terminal region present in\u0026nbsp;MaGBSSII and HvSSI was absent in ObGBSSI. This region is characterized by an extensive loop and may be related to the conformational changes of the structure after cofactor binding (Cuesta-Seijo et al. 2013).\u0026nbsp;MaGBSSII has an active site characteristic of GT5 and HvSSI\u0026nbsp;and the amino acid residues of both domains have a closed conformation\u0026nbsp;(Cuesta-Seijo et al. 2013). The two main maltopentaose-binding residues, Pro686 and Phe687,\u0026nbsp;are conserved in MaGBSSII, as well as the side chains of the residues Glu689, Trp694, His718, and Ser684. At the binding site of HvSSI, the residues Pro537 and Phe538 form a helical structure around the molecule and the maltopentaose interacts with the side chains\u0026nbsp;of residues Glu543, Trp548, His572, and Ser575 (Cuesta-Seijo et al. 2013). Mutation analysis indicated that the substitution\u0026nbsp;of\u0026nbsp;Thr564 by Asn710 in MaGBSSII did not affect ligand stability.\u003c/p\u003e\n\u003cp\u003eDespite experiencing phylogenetic and structural divergence, the gene encoding the GBSS enzyme retained a significant portion of its functional structural domains. Among these was the GT-B fold, characterized by a double Rossman fold, which is shared with other enzymes involved in starch synthesis. This structural feature is specifically confined to the GT5 and GT1 domains and plays a role in regulation and protein-protein interactions\u0026nbsp;(Qu et al. 2018). The differences\u0026nbsp;between the secondary structures of the GBSSI and GBSSII isoforms were also noted by Qu et al. (2018).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003edN/dS rates and analyses of mutation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThroughout evolution, mutations that lead to advantageous changes face a significantly low probability of occurrence. This is primarily due to energetic barriers that can disrupt the conformation of a protein, hindering the emergence of beneficial alterations. These energetic barriers act as obstacles, impeding the spontaneous acquisition of advantageous mutations within protein structures. As a result, the evolutionary trajectory of proteins is often constrained by the intricate interplay between mutation, energetic stability, and functional adaptation (Faber et al. 2019). The reflections on mutations in the stability and function of proteins have been widely investigated in the literature (Shortle 1992; Neves Cruz et al. 2020; Bellamy-Carter et al. 2021; Almeida de Jesus et al. 2022c; Lee and Kuczera 2023). Most alanine substitutions in the structures of the ObGBSSI and MaGBSSII isoforms are destabilizing, especially the residues located in the KTGGL motif present in the N-terminal region, such as Thr16 (+2.7 kcal mol\u003csup\u003e-1\u003c/sup\u003e), Gly17 (+2.96 kcal mol\u003csup\u003e-1\u003c/sup\u003e), and Leu19 (+2.26 kcal mol\u003csup\u003e-1\u003c/sup\u003e), which play important roles in the activity of OsGBSSI. These residues interact with ADP forming a binding pocket (Momma and Fujimoto, 2012; Sheng et al. 2009). These alterations could impact the structures of both GBSS isoforms, as this domain is associated with the characteristic of the Rossmann fold, which is a distinctive feature of the GT-B protein families (Cuesta-Seijo et al. 2013; Momma and Fujimoto, 2012; Sheng et al. 2009). These residues are critical for both structures, along with other residues within the N-terminal and C-terminal domains, which also exhibited highly destabilizing energies.\u003c/p\u003e\n\u003cp\u003eIn the GBSSI isoform sequences, there are two key residues present for the stability of the N and C-terminal domains: Cys336 (+6.28 kcal mol-1) and Cys528 (+5.53 kcal mol-1) (Figure 8). Alterations to these residues result in highly destabilizing values. These residues form a disulfide bond in OsGBSSI. (Momma and Fujimoto, 2012). In MaGBSSII, the characteristic active site of GT5, found in HvSSI, exhibits nearby residues that showed destabilizing mutations. However, residues Pro537 and Phe538, which interact with maltopentaose, did not show destabilizing values. Conversely, residues Phe884 (+3.27 kcal mol\u003csup\u003e-1\u003c/sup\u003e) and Trp694 (+3.74 kcal mol\u003csup\u003e-1\u003c/sup\u003e) displayed destabilizing values. The substitution of Thr564 by Asn710 in MaGBSSII may not affect ligand binding since this alteration did not exhibit destabilizing effects. The remaining residues in the side chain maintained neutral values. However, any changes to these amino acids linked to the GT5 and GT1 domains, which are related to protein regulation, could affect interactions not only with their respective ligands but also among proteins (Qu et al. 2018).\u003c/p\u003e\n\u003cp\u003eThe analysis of mutations in both structures using the dN/dS rate of the coding region showed a predominance of purifying selection (dN/dS\u0026lt;1) indicating that the selection is maintaining, for the most part, the functional integrity of the gene that encodes the GBSS enzyme in angiosperms. \u003cem\u003eGBSSI\u003c/em\u003e and \u003cem\u003eGBSSII\u003c/em\u003e are highly conserved (Kharabian-Masouleh et al. 2011). Another study comparing GBSSI and GBSSII isoforms obtained indications of purifying selection in Poaceae and Fabaceae orthologs (Pan et al. 2009). Signs of positive selection were also observed in the two residue sites of the GBSSI isoform in \u003cem\u003eManihot esculenta\u003c/em\u003e (Yang et al. 2013).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinal considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study reported the evolutionary history of the gene encoding GBSS in the general context of flowering plants. The Waxy gene, encoding the enzyme GBSS, is well-conserved in flowering plants and we corroborate with the existence of two isoforms named GBSSI and GBSSII. Some monocot taxa exist within the eudicot clades, nested within the GBSSII divergence, likely due to convergence processes acting on this gene. The structures of the ObGBSSI and MaGBSSII isoforms elucidated in silico provide evidence as to how the same binding mechanisms are used in the binding of ADP and pentasaccharide molecules with GBSSI and GBSSII. The isoforms share the same motifs and domains, exhibiting N- and C-terminal domains with Rossmann fold characteristics. The ObGBSSI structure contains a KTGGL motif in the N-terminal region, which is also present in the MaGBSSII isoform. In MaGBSSII, there is a change from Thr564 to Asn710 but the change occurs in a part of the side chain that does not interact directly with the ligand due to its positive energy value of mutation (\u0026Delta;G\u0026gt;0). The two main residues at the binding site that interact with maltopentaose, Pro686 and Phe687, are conserved in the theoretical model of MaGBSSII, as are the residues Glu689, Trp694, His718, and Ser68. We conjecture that the PaGBSSI and MaGBSSII isoforms interact in the same mode with their cofactors because the main residues in the cavities of both isoforms are conserved.\u003c/p\u003e\n\u003cp\u003eAn analysis of mutations in the protein sequences of ObGBSSI and MaGBSSII highlighted the importance of the stability and function of proteins in the evolution of GBSS isoforms in angiosperms. The presence of destabilizing mutations in critical regions, such as residues of the KTGGL motif and residues of Cys336 and Cys528, suggests a fundamental role of these regions in maintaining the structural and functional integrity of proteins.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhile there was evidence of positive selective pressure in some cases (dN/dS\u0026gt;1) and destabilizing mutations (\u0026Delta;\u0026Delta;G\u0026gt;0), there was a predominance of purifying selection (dN/dS\u0026lt;1) and stabilizing mutations (\u0026Delta;\u0026Delta;G\u0026lt;0). This indicates a greater proportion of synonymous changes, which do not affect the final product of the gene, thereby maintaining its functional integrity. This contrasts with previous studies that demonstrated high conservation of \u003cem\u003eGBSSI\u003c/em\u003e and \u003cem\u003eGBSSII\u003c/em\u003e in angiosperms but also indicated purifying selection.\u003c/p\u003e\n\u003cp\u003eIn combination, these findings offer novel insights into the evolutionary history, structure, and function of the key enzymes responsible for starch synthesis in plants. However, additional studies are necessary to explore genetic diversity, differential expression in different tissues and environmental conditions, and the interaction between enzymes and other components of starch metabolism. Furthermore, additional research on genetic and epigenetic regulation of the genes involved in food synthesis can offer valuable insights into how plants respond to environmental stimuli and modulate their food production in different physiological contexts, particularly important for a climate change scenario. In the final analysis, these complementary studies will be essential for a complete understanding of the evolution and function of enzymes that synthesize food in plants, contributing to potential applications in genetic improvement and agricultural biotechnology.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was financed by the Brazilian funding agency Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior (CAPES, Brazil) - Finance Code 001\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlmeida de Jesus D, Batista DM, Monteiro EF, et al (2022a) Structural changes and adaptative evolutionary constraints in FLOWERING LOCUS T and TERMINAL FLOWER1-like genes of flowering plants. Front Genet 13:954015. https://doi.org/10.3389/FGENE.2022.954015/BIBTEX\u003c/li\u003e\n\u003cli\u003eAlmeida de Jesus D, Batista DM, Monteiro EF, et al (2022b) Structural changes and adaptative evolutionary constraints in FLOWERING LOCUS T and TERMINAL FLOWER1-like genes of flowering plants. Front Genet 13:954015. https://doi.org/10.3389/fgene.2022.954015\u003c/li\u003e\n\u003cli\u003eAlmeida de Jesus D, Batista DM, Monteiro EF, et al (2022c) Structural changes and adaptative evolutionary constraints in FLOWERING LOCUS T and TERMINAL FLOWER1-like genes of flowering plants. Front Genet 13:954015. https://doi.org/10.3389/fgene.2022.954015\u003c/li\u003e\n\u003cli\u003eAltschul SF, Madden TL, Sch\u0026auml;ffer AA, et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389\u0026ndash;3402. https://doi.org/10.1093/NAR/25.17.3389\u003c/li\u003e\n\u003cli\u003eAnisimova M, Gil M, Dufayard JF, et al (2011) Survey of Branch Support Methods Demonstrates Accuracy, Power, and Robustness of Fast Likelihood-based Approximation Schemes. Syst Biol 60:685\u0026ndash;699. https://doi.org/10.1093/SYSBIO/SYR041\u003c/li\u003e\n\u003cli\u003eArnold K, Bordoli L, Kopp J, Schwede T (2006) The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics 22:195\u0026ndash;201. https://doi.org/10.1093/bioinformatics/bti770\u003c/li\u003e\n\u003cli\u003eBanerjee S, Deshpande PA (2016) On origin and evolution of carbonic anhydrase isozymes: A phylogenetic analysis from whole-enzyme to active site. Comput Biol Chem 61:121\u0026ndash;129. https://doi.org/10.1016/J.COMPBIOLCHEM.2016.01.003\u003c/li\u003e\n\u003cli\u003eBellamy-Carter J, O\u0026rsquo;Grady L, Passmore M, et al (2021) Decoding Protein Gas-Phase Stability with Alanine Scanning and Collision-Induced Unfolding Ion Mobility Mass Spectrometry. Analysis \u0026amp; Sensing 1:63\u0026ndash;69. https://doi.org/10.1002/ANSE.202000019\u003c/li\u003e\n\u003cli\u003eBenkert P, Biasini M, Schwede T (2011) Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics 27:343\u0026ndash;350. https://doi.org/10.1093/BIOINFORMATICS/BTQ662\u003c/li\u003e\n\u003cli\u003eBenkert P, Tosatto SCE, Schomburg D (2008) QMEAN: A comprehensive scoring function for model quality assessment. Proteins 71:261\u0026ndash;277. https://doi.org/10.1002/PROT.21715\u003c/li\u003e\n\u003cli\u003eBenson D, Boguski M, Lipman DJ, Ostell J (1990) The National Center for Biotechnology Information. Genomics 6:389\u0026ndash;391. https://doi.org/10.1016/0888-7543(90)90583-G\u003c/li\u003e\n\u003cli\u003eBiasini M, Bienert S, Waterhouse A, et al (2014) SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. - PubMed - NCBI. Nucleic Acids Res 42:W252\u0026ndash;W258\u003c/li\u003e\n\u003cli\u003eBremer B, Bremer K, Chase MW, et al (2009) An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG III. Botanical Journal of the Linnean Society 161:105\u0026ndash;121. https://doi.org/10.1111/j.1095-8339.2009.00996.x\u003c/li\u003e\n\u003cli\u003eChase MW, Christenhusz MJM, Fay MF, et al (2016) An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Botanical Journal of the Linnean Society 181:1\u0026ndash;20. https://doi.org/10.1111/boj.12385\u003c/li\u003e\n\u003cli\u003eCheng J, Khan MA, Qiu W-M, et al (2012) Diversification of Genes Encoding Granule-Bound Starch Synthase in Monocots and Dicots Is Marked by Multiple Genome-Wide Duplication Events. PLoS One 7:e30088. https://doi.org/10.1371/journal.pone.0030088\u003c/li\u003e\n\u003cli\u003eCuesta-Seijo JA, Nielsen MM, Marri L, et al (2013) Structure of starch synthase I from barley: insight into regulatory mechanisms of starch synthase activity. Acta Crystallogr D Biol Crystallogr 69:1013\u0026ndash;1025. https://doi.org/10.1107/S090744491300440X\u003c/li\u003e\n\u003cli\u003eDelgado J, Radusky LG, Cianferoni D, Serrano L (2019) FoldX 5.0: working with RNA, small molecules and a new graphical interface. Bioinformatics 35:4168\u0026ndash;4169. https://doi.org/10.1093/BIOINFORMATICS/BTZ184\u003c/li\u003e\n\u003cli\u003eDelport W, Poon AFY, Frost SDW, Kosakovsky Pond SL (2010) Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology. Bioinformatics 26:2455\u0026ndash;2457. https://doi.org/10.1093/BIOINFORMATICS/BTQ429\u003c/li\u003e\n\u003cli\u003eDian W, Jiang H, Chen Q, et al (2003) Cloning and characterization of the granule-bound starch synthase II gene in rice: Gene expression is regulated by the nitrogen level, sugar and circadian rhythm. Planta 218:261\u0026ndash;268. https://doi.org/10.1007/s00425-003-1101-9\u003c/li\u003e\n\u003cli\u003edo Carmo CD, Sousa MBE, dos Santos Silva PP, et al (2020) Identification and validation of mutation points associated with waxy phenotype in cassava. BMC Plant Biol 20:1\u0026ndash;12. https://doi.org/10.1186/s12870-020-02379-3\u003c/li\u003e\n\u003cli\u003eEdgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792\u0026ndash;1797. https://doi.org/10.1093/nar/gkh340\u003c/li\u003e\n\u003cli\u003eEdwards A, Vincken JP, Suurs LCJM, et al (2002) Discrete forms of amylose are synthesized by isoforms of GBSSI in pea. Plant Cell 14:1767\u0026ndash;1785. https://doi.org/10.1105/tpc.002907\u003c/li\u003e\n\u003cli\u003eFaber MS, Wrenbeck EE, Azouz LR, et al (2019) Impact of In Vivo Protein Folding Probability on Local Fitness Landscapes. Mol Biol Evol 36:2764\u0026ndash;2777. https://doi.org/10.1093/MOLBEV/MSZ184\u003c/li\u003e\n\u003cli\u003eFelsenstein J (1981) Evolutionary trees from DNA sequences: A maximum likelihood approach. J Mol Evol 17:368\u0026ndash;376. https://doi.org/10.1007/BF01734359\u003c/li\u003e\n\u003cli\u003eGoujon M, McWilliam H, Li W, et al (2010) A new bioinformatics analysis tools framework at EMBL-EBI. Nucleic Acids Res 38:. https://doi.org/10.1093/nar/gkq313\u003c/li\u003e\n\u003cli\u003eGuerois R, Nielsen JE, Serrano L (2002) Predicting Changes in the Stability of Proteins and Protein Complexes: A Study of More Than 1000 Mutations. J Mol Biol 320:369\u0026ndash;387. https://doi.org/10.1016/S0022-2836(02)00442-4\u003c/li\u003e\n\u003cli\u003eGuindon S, Dufayard JF, Lefort V, et al (2010) New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0. Syst Biol 59:307\u0026ndash;321. https://doi.org/10.1093/SYSBIO/SYQ010\u003c/li\u003e\n\u003cli\u003eJiao Y, Wickett NJ, Ayyampalayam S, et al (2011) Ancestral polyploidy in seed plants and angiosperms. Nature 473:97\u0026ndash;100. https://doi.org/10.1038/nature09916\u003c/li\u003e\n\u003cli\u003eKanehisa M (2002) The KEGG databases at GenomeNet. Nucleic Acids Res 30:42\u0026ndash;46. https://doi.org/10.1093/nar/30.1.42\u003c/li\u003e\n\u003cli\u003eKato K, Suzuki Y, Hosaka Y, et al (2019) Effect of high temperature on starch biosynthetic enzymes and starch structure in japonica rice cultivar \u0026lsquo;Akitakomachi\u0026rsquo; (Oryza sativa L.) endosperm and palatability of cooked rice. J Cereal Sci 87:209\u0026ndash;214. https://doi.org/10.1016/j.jcs.2019.04.001\u003c/li\u003e\n\u003cli\u003eKharabian‐Masouleh A, Waters DLE, Reinke RF, Henry RJ (2011) Discovery of polymorphisms in starch‐related genes in rice germplasm by amplification of pooled DNA and deeply parallel sequencing \u003csup\u003e\u0026dagger;\u003c/sup\u003e. Plant Biotechnol J 9:1074\u0026ndash;1085. https://doi.org/10.1111/j.1467-7652.2011.00629.x\u003c/li\u003e\n\u003cli\u003eKiefer F, Arnold K, K\u0026uuml;nzli M, et al (2009) The SWISS-MODEL Repository and associated resources. Nucleic Acids Res 37:. https://doi.org/10.1093/nar/gkn750\u003c/li\u003e\n\u003cli\u003eKosakovsky Pond SL, Frost SDW (2005) Datamonkey: rapid detection of selective pressure on individual sites of codon alignments. Bioinformatics 21:2531\u0026ndash;2533. https://doi.org/10.1093/BIOINFORMATICS/BTI320\u003c/li\u003e\n\u003cli\u003eKosakovsky Pond SL, Murrell B, Fourment M, et al (2011) A Random Effects Branch-Site Model for Detecting Episodic Diversifying Selection. Mol Biol Evol 28:3033\u0026ndash;3043. https://doi.org/10.1093/MOLBEV/MSR125\u003c/li\u003e\n\u003cli\u003eKosakovsky Pond SL, Poon AFY, Velazquez R, et al (2020) HyPhy 2.5\u0026mdash;A Customizable Platform for Evolutionary Hypothesis Testing Using Phylogenies. Mol Biol Evol 37:295\u0026ndash;299. https://doi.org/10.1093/MOLBEV/MSZ197\u003c/li\u003e\n\u003cli\u003eKumar S, Stecher G, Li M, et al (2018) MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 35:1547\u0026ndash;1549. https://doi.org/10.1093/molbev/msy096\u003c/li\u003e\n\u003cli\u003eLee KH, Kuczera K (2023) Simulation analysis of selective alanine mutation effect on stability of human prion protein. J Biomol Struct Dyn 41:2619\u0026ndash;2629. https://doi.org/10.1080/07391102.2022.2036237\u003c/li\u003e\n\u003cli\u003eLi Q, Pan Z, Liu J, et al (2019) A mutation in Waxy gene affects amylose content, starch granules and kernel characteristics of barley (Hordeum vulgare). Plant Breeding 138:513\u0026ndash;523. https://doi.org/10.1111/pbr.12695\u003c/li\u003e\n\u003cli\u003eLovell SC, Davis IW, Arendall WB, et al (2003) Structure validation by Calpha geometry: phi,psi and Cbeta deviation. Proteins 50:437\u0026ndash;50. https://doi.org/10.1002/prot.10286\u003c/li\u003e\n\u003cli\u003eLu Y, Li L, Zhou Y, et al (2012) Cloning and Characterization of the Wx Gene Encoding a Granule-Bound Starch Synthase in Lotus (Nelumbo nucifera Gaertn). Plant Mol Biol Report 30:1210\u0026ndash;1217. https://doi.org/10.1007/s11105-012-0430-x\u003c/li\u003e\n\u003cli\u003eMcWilliam H, Li W, Uludag M, et al (2013) Analysis Tool Web Services from the EMBL-EBI. Nucleic Acids Res 41:. https://doi.org/10.1093/nar/gkt376\u003c/li\u003e\n\u003cli\u003eMiao H, Sun P, Liu W, et al (2014) Identification of genes encoding granule-bound starch synthase involved in amylose metabolism in banana fruit. PLoS One 9:e88077. https://doi.org/10.1371/journal.pone.0088077\u003c/li\u003e\n\u003cli\u003eMOMMA M, FUJIMOTO Z (2012) Interdomain Disulfide Bridge in the Rice Granule Bound Starch Synthase I Catalytic Domain as Elucidated by X-Ray Structure Analysis. Biosci Biotechnol Biochem 76:1591\u0026ndash;1595. https://doi.org/10.1271/bbb.120305\u003c/li\u003e\n\u003cli\u003eNeves Cruz J, da Costa KS, de Carvalho TAA, de Alencar NAN (2020) Measuring the structural impact of mutations on cytochrome P450 21A2, the major steroid 21-hydroxylase related to congenital adrenal hyperplasia. J Biomol Struct Dyn 38:1425\u0026ndash;1434. https://doi.org/10.1080/07391102.2019.1607560\u003c/li\u003e\n\u003cli\u003ePan X, Tang Y, Li M, et al (2009) Isoforms of GBSSI and SSII in four legumes and their phylogenetic relationship to their orthologs from other angiosperms. J Mol Evol 69:625\u0026ndash;634. https://doi.org/10.1007/S00239-009-9300-Z/TABLES/1\u003c/li\u003e\n\u003cli\u003ePark YJ, Nishikawa T, Matsushima K, Nemoto K (2017) Characterization of a new granule-bound starch synthase gene found in amaranth grains (Amaranthus cruentus L.). Molecular Breeding 37:. https://doi.org/10.1007/s11032-017-0712-y\u003c/li\u003e\n\u003cli\u003ePettersen EF, Goddard TD, Huang CC, et al (2004) UCSF Chimera - A visualization system for exploratory research and analysis. J Comput Chem 25:1605\u0026ndash;1612. https://doi.org/10.1002/jcc.20084\u003c/li\u003e\n\u003cli\u003eQu J, Xu S, Zhang Z, et al (2018) Evolutionary, structural and expression analysis of core genes involved in starch synthesis. Sci Rep 8:12736. https://doi.org/10.1038/s41598-018-30411-y\u003c/li\u003e\n\u003cli\u003eSaha J, Chatterjee C, Sengupta A, et al (2014) Genome-wide analysis and evolutionary study of sucrose non-fermenting 1-related protein kinase 2 (SnRK2) gene family members in Arabidopsis and Oryza. Comput Biol Chem 49:59\u0026ndash;70. https://doi.org/10.1016/J.COMPBIOLCHEM.2013.09.005\u003c/li\u003e\n\u003cli\u003eSchymkowitz J, Borg J, Stricher F, et al (2005) The FoldX web server: an online force field. Nucleic Acids Res 33:W382. https://doi.org/10.1093/NAR/GKI387\u003c/li\u003e\n\u003cli\u003eSeung D (2020) Amylose in starch: towards an understanding of biosynthesis, structure and function. New Phytologist 228:1490\u0026ndash;1504. https://doi.org/10.1111/nph.16858\u003c/li\u003e\n\u003cli\u003eSeung D, Echevarr\u0026iacute;a-Poza A, Steuernagel B, Smith AM (2020) Natural polymorphisms in Arabidopsis result in wide variation or loss of the amylose component of StARCH. Plant Physiol 182:870\u0026ndash;881. https://doi.org/10.1104/pp.19.01062\u003c/li\u003e\n\u003cli\u003eShapter FM, Eggler P, Lee LS, Henry RJ (2009) Variation in Granule Bound Starch Synthase I (GBSSI) loci amongst Australian wild cereal relatives (Poaceae). J Cereal Sci 49:4\u0026ndash;11. https://doi.org/10.1016/j.jcs.2008.06.013\u003c/li\u003e\n\u003cli\u003eSheng F, Jia X, Yep A, et al (2009) The Crystal Structures of the Open and Catalytically Competent Closed Conformation of Escherichia coli Glycogen Synthase. J Biol Chem 284:17796. https://doi.org/10.1074/JBC.M809804200\u003c/li\u003e\n\u003cli\u003eShortle D (1992) Mutational studies of protein structures and their stabilities. Q Rev Biophys 25:205\u0026ndash;250. https://doi.org/10.1017/S0033583500004674\u003c/li\u003e\n\u003cli\u003eSippl MJ (1993) Recognition of errors in three-dimensional structures of proteins. Proteins: Structure, Function, and Bioinformatics 17:355\u0026ndash;362. https://doi.org/10.1002/PROT.340170404\u003c/li\u003e\n\u003cli\u003eSmith MD, Wertheim JO, Weaver S, et al (2015) Less Is More: An Adaptive Branch-Site Random Effects Model for Efficient Detection of Episodic Diversifying Selection. Mol Biol Evol 32:1342\u0026ndash;1353. https://doi.org/10.1093/MOLBEV/MSV022\u003c/li\u003e\n\u003cli\u003eStanke M, Diekhans M, Baertsch R, Haussler D (2008) Using native and syntenically mapped cDNA alignments to improve de novo gene finding. Bioinformatics 24:637\u0026ndash;644. https://doi.org/10.1093/BIOINFORMATICS/BTN013\u003c/li\u003e\n\u003cli\u003eStanke M, Steinkamp R, Waack S, Morgenstern B (2004) AUGUSTUS: a web server for gene finding in eukaryotes. Nucleic Acids Res 32:W309\u0026ndash;W312. https://doi.org/10.1093/nar/gkh379\u003c/li\u003e\n\u003cli\u003eStanke M, Tzvetkova A, Morgenstern B (2006) AUGUSTUS at EGASP: using EST, protein and genomic alignments for improved gene prediction in the human genome. Genome Biology 2006 7:1 7:1\u0026ndash;8. https://doi.org/10.1186/GB-2006-7-S1-S11\u003c/li\u003e\n\u003cli\u003eStanke M, Waack S (2003) Gene prediction with a hidden Markov model and a new intron submodel. Bioinformatics 19:ii215\u0026ndash;ii225. https://doi.org/10.1093/BIOINFORMATICS/BTG1080\u003c/li\u003e\n\u003cli\u003eTrifinopoulos J, Nguyen LT, von Haeseler A, Minh BQ (2016) W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis. Nucleic Acids Res 44:W232\u0026ndash;W235. https://doi.org/10.1093/nar/gkw256\u003c/li\u003e\n\u003cli\u003eVrinten PL, Nakamura T (2000) Wheat Granule-Bound Starch Synthase I and II Are Encoded by Separate Genes That Are Expressed in Different Tissues. Plant Physiol 122:255\u0026ndash;264. https://doi.org/10.1104/pp.122.1.255\u003c/li\u003e\n\u003cli\u003eWeaver S, Shank SD, Spielman SJ, et al (2018) Datamonkey 2.0: A Modern Web Application for Characterizing Selective and Other Evolutionary Processes. Mol Biol Evol 35:773\u0026ndash;777. https://doi.org/10.1093/MOLBEV/MSX335\u003c/li\u003e\n\u003cli\u003eWebb B, Sali A (2017) Protein Structure Modeling with MODELLER. In: Methods in Molecular Biology. pp 39\u0026ndash;54\u003c/li\u003e\n\u003cli\u003eWiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35:W407\u0026ndash;W410. https://doi.org/10.1093/NAR/GKM290\u003c/li\u003e\n\u003cli\u003eYang Z, Wang Y, Xu S, et al (2013) Molecular evolution and functional divergence of soluble starch synthase genes in cassava (Manihot Esculenta Crantz). Evolutionary Bioinformatics 2013:239\u0026ndash;249. https://doi.org/10.4137/EBO.S11991/ASSET/IMAGES/LARGE/10.4137_EBO.S11991-FIG1.JPEG\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-molecular-biology-reporter","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pmbr","sideBox":"Learn more about [Plant Molecular Biology Reporter](http://link.springer.com/journal/11105)","snPcode":"11105","submissionUrl":"https://submission.nature.com/new-submission/11105/3","title":"Plant Molecular Biology Reporter","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"starch synthesis, angiosperms, plant storage organs, evolutionary analyses, carbohydrate storage. ","lastPublishedDoi":"10.21203/rs.3.rs-4778293/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4778293/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Starch is the main storage carbohydrate in plants and, as well as being a natural resource of global importance for human consumption, serves as a raw material for some industries. Granule-bound starch synthase (GBSS) is the key enzyme in starch synthesis. However, the evolution of structural diversity of this enzyme in flowering plants remains poorly understood. This study applied a comprehensive phylogenetic analysis of genes encoding the GBSS enzyme to better understand its evolutionary history and used homology modeling to determine the enzyme's structure by identifying important protein domains and motifs. The gene encoding the GBSS enzyme was highly conserved in angiosperms and phylogenetic analysis confirmed the evolution of two isoforms, GBSSI and GBSSII. This molecular diversification could be linked to duplication events in plant genomes. Although the two isoforms share similarities, they showed structural variances and amino acid substitutions. Furthermore, the occurrence of destabilizing mutations in key residues in binding sites and conserved domains were under greater influence of purifying selection, maintaining the stability of the protein. This study provides a more comprehensive understanding of the evolutionary and structural history of the main enzymes involved in starch synthesis, which could support future studies that aim to increase our understanding of starch biosynthesis and the evolutionary and functional divergence of GBSS in plants. We highlight that attention regarding isoforms is required when using GBSS to reconstruct phylogenetic trees.","manuscriptTitle":"Molecular evolution of the granule-bound starch synthase in flowering plants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-22 06:11:30","doi":"10.21203/rs.3.rs-4778293/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-29T09:30:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-17T19:52:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"22181432678904608283872594543187593866","date":"2024-11-02T10:52:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-01T04:15:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"212481373520862180244469991730263015191","date":"2024-10-29T11:44:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"261486295530706865366065239922793528006","date":"2024-10-28T12:52:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259003153518460236354130696067801457994","date":"2024-10-28T01:45:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-27T18:37:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-26T04:15:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-26T04:14:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant Molecular Biology Reporter","date":"2024-07-21T22:40:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-molecular-biology-reporter","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pmbr","sideBox":"Learn more about [Plant Molecular Biology Reporter](http://link.springer.com/journal/11105)","snPcode":"11105","submissionUrl":"https://submission.nature.com/new-submission/11105/3","title":"Plant Molecular Biology Reporter","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5a0308da-f409-44f6-b2ef-0eb2846aa814","owner":[],"postedDate":"August 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-24T16:05:24+00:00","versionOfRecord":{"articleIdentity":"rs-4778293","link":"https://doi.org/10.1007/s11105-025-01547-9","journal":{"identity":"plant-molecular-biology-reporter","isVorOnly":false,"title":"Plant Molecular Biology Reporter"},"publishedOn":"2025-02-19 15:57:15","publishedOnDateReadable":"February 19th, 2025"},"versionCreatedAt":"2024-08-22 06:11:30","video":"","vorDoi":"10.1007/s11105-025-01547-9","vorDoiUrl":"https://doi.org/10.1007/s11105-025-01547-9","workflowStages":[]},"version":"v1","identity":"rs-4778293","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4778293","identity":"rs-4778293","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}