ABSTRACT. The SBP-box gene family is specific to plants and encodes a class of zinc finger-containing transcription factors with a broad range of functions. Although SBP-box genes have been identified in numerous plants, including green algae, moss, silver birch, snapdragon, Arabidopsis, rice, and maize, there is little information concerning SBP-box genes, or the corresponding miR156/157, function in melon. Using the highly conserved sequence of the Arabidopsis thaliana SBPbox domain protein as a probe of information sequence, the genomewide protein database of melon was explored to obtain 13 SBP-box protein sequences, which were further divided into 4 groups, based on phylogenetic analysis. A further analysis centered on the melon SBPbox genetic family's phylogenetic evolution, sequence similarities, gene structure, and miR156 target sequence was also conducted. Analysis of all the expression patterns of melon SBP-box family genes showed that the SBP-box genes were detected in 7 kinds of tissue, and fruit had the highest expression level. CmSBP11 tends to present its specific expression in melon fruit and root. CmSBP09 expression was the highest in flower. Overall, the molecular evolution and expression 8795©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 13 (4): 8794-8806 (2014) Identification and analysis of SBP-Box gene pattern of the melon SBP-box gene family, revealed by these results, suggest its function differentiation that followed gene duplication.
Since the outbreak of COVID-19 in 2019, the 2019-nCov coronavirus has appeared diverse mutational characteristics due to its own flexible conformation. One multiple-mutant strain (Omicron) with surprisingly infective activity outburst, and affected the biological activities of current drugs and vaccines, making the epidemic significantly difficult to prevent and control, and seriously threaten health around the world. Importunately exploration of mutant characteristics for novel coronavirus Omicron can supply strong theoretical guidance for learning binding mechanism of mutant viruses. What’s more, full acknowledgement of key mutated-residues on Omicron strain can provide new methodology of the novel pathogenic mechanism to human ACE2 receptor, as well as the subsequent vaccine development. In this research, 3D structures of 32 single-point mutations of 2019-nCov were firstly constructed, and 32-sites multiple-mutant Omicron were finally obtained based one the wild-type virus by homology modeling method. One total number of 33 2019-nCov/ACE2 complex systems were acquired by protein-protein docking, and optimized by using preliminary molecular dynamics simulations. Binding free energies between each 2019-nCov mutation system and human ACE2 receptor were calculated, and corresponding binding patterns especially the regions adjacent to mutation site were analyzed. The results indicated that one total number of 6 mutated sites on the Omicron strain played crucial role in improving binding capacities from 2019-nCov to ACE2 protein. Subsequently, we performed long-term molecular dynamic simulations and protein-protein binding energy analysis for the selected 6 mutations. 3 infected individuals, the mutants T478K, Q493R and G496S with lower binding energies − 66.36, -67.98 and − 67.09 kcal/mol also presents the high infectivity. These findings indicated that the 3 mutations T478K, Q493R and G496S play the crucial roles in enhancing binding affinity of Omicron to human ACE2 protein. All these results illuminate important theoretical guidance for future virus detection of the Omicron epidemic, drug research and vaccine development.
Background With the rapid development of accurate sequencing and assembly technologies, an increasing number of high-quality chromosome-level and haplotype-resolved assemblies of genomic sequences have been derived, from which there will be great opportunities for computational pangenomics. Although genome graphs are among the most useful models for pangenome representation, their structural complexity makes it difficult to present genome information intuitively, such as the linear reference genome. Thus, efficiently and accurately analyzing the genome graph spatial structure and coordinating the information remains a substantial challenge. Results We developed a new method, a colored superbubble (cSupB), that can overcome the complexity of graphs and organize a set of species- or population-specific haplotype sequences of interest. Based on this model, we propose a tri-tuple coordinate system that combines an offset value, topological structure and sample information. Additionally, cSupB provides a novel method that utilizes complete topological information and efficiently detects small indels (< 50 bp) for highly similar samples, which can be validated by simulated datasets. Moreover, we demonstrated that cSupB can adapt to the complex cycle structure. Conclusions Although the solution is made suitable for increasingly complex genome graphs by relaxing the constraint, the directed acyclic graph, the motif cSupB and the cSupB method can be extended to any colored directed acyclic graph. We anticipate that our method will facilitate the analysis of individual haplotype variants and population genomic diversity. We have developed a C + + program for implementing our method that is available at https://github.com/eggleader/cSupB.
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