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      Extensive characterization of 28 complete chloroplast genomes of Hydrangea species: A perspective view of their organization and phylogenetic and evolutionary relationships

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          Abstract

          The tribe Hydrangeeae displays a unique, distinctive disjunct distribution encompassing East Asia, North America and Hawaii. Despite its complex trait variations and polyphyletic nature, comprehensive phylogenomic and biogeographical studies on this tribe have been lacking. To address this gap, we sequenced and characterized 28 plastomes of Hydrangeeae. Our study highlights the highly conserved nature of Hydrangeaceae chloroplast (cp) genomes in terms of gene content and arrangement. Notably, synapomorphic characteristics of tandem repeats in the conserved domain of accD were observed in the Macrophyllae, Chinenses, and Dichroa sections within the Hydrangeeae tribe. Additionally, we found lower expression of accD in these sections using structure prediction and quantitative real-time PCR analysis. Phylogenomic analyses revealed the subdivision of the Hydrangeeae tribe into two clades with robust support values. Consistent with polyphyletic relationships, sect. Broussaisia was identified as the basal group in the tribe Hydrangeeae. Our study also provides insights into the phylogenetic relationships of Hydrangea petiolaris in the Jeju and Ulleung Island populations, suggesting the need for further studies with more samples and molecular data. Divergence time estimation and biogeographical analyses suggested that the common ancestors of the tribe Hydrangeeae likely originated from North America and East Asia during the Paleocene period via the Bering Land Bridge, potentially facilitating migration within the tribe between these regions. In conclusion, this study enhances our understanding of the evolutionary history and biogeography of the tribe Hydrangeeae, shedding light on the dispersal patterns and origins of this intriguing plant group with its unique disjunct distribution.

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          Highlights

          • The architecture and gene functions of 28 newly sequenced Hydrangeaceae chloroplast genomes were revealed.

          • Hydrangea clade II possessed synapomorphic characteristics of 18-bp tandem repeats in the conserved domain of accD.

          • Phylogenomic analyses revealed the subdivision of the tribe Hydrangeeae into two clades with robust support values.

          • Explored phylogenetic links of Hydrangea petiolaris in Jeju and Ulleung Island populations for evolutionary insights.

          • Divergent analysis showed Hydrangeeae tribe likely originated in East Asia, North America, during Paleocene via Bering Land Bridge.

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            Highly accurate protein structure prediction with AlphaFold

            Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort 1 – 4 , the structures of around 100,000 unique proteins have been determined 5 , but this represents a small fraction of the billions of known protein sequences 6 , 7 . Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’ 8 —has been an important open research problem for more than 50 years 9 . Despite recent progress 10 – 14 , existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14) 15 , demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.
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              MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

              Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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                Author and article information

                Contributors
                Journal
                Comput Struct Biotechnol J
                Comput Struct Biotechnol J
                Computational and Structural Biotechnology Journal
                Research Network of Computational and Structural Biotechnology
                2001-0370
                10 October 2023
                2023
                10 October 2023
                : 21
                : 5073-5091
                Affiliations
                [a ]Department of Life Sciences, Yeungnam University, Gyeongsan, Gyeongsan-buk, Republic of Korea
                [b ]Plant Research Team, Animal and Plant Research Department, Nakdonggang National Institute of Biological Resources, Sangju, Republic of Korea
                [c ]School of Life Sciences, University of Hawai]i at Mānoa, Honolulu, HI, USA
                [d ]Department of Agriculture, Forestry and Bioresources, Plant Genomics and Breeding Institute, Research Institute of Agriculture and Life Science, College of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea
                Author notes
                Article
                S2001-0370(23)00367-7
                10.1016/j.csbj.2023.10.010
                10589384
                37867966
                b08ad555-a6ce-4c1b-a5ab-659dc460e64f
                © 2023 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 5 September 2023
                : 4 October 2023
                : 6 October 2023
                Categories
                Research Article

                hydrangea,biogeography,disjunct distribution,phylogenomics,plastid genome

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