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      Endosperm Evolution by Duplicated and Neofunctionalized Type I MADS-Box Transcription Factors

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          Abstract

          MADS-box transcription factors (TFs) are present in nearly all major eukaryotic groups. They are divided into Type I and Type II that differ in domain structure, functional roles, and rates of evolution. In flowering plants, major evolutionary innovations like flowers, ovules, and fruits have been closely connected to Type II MADS-box TFs. The role of Type I MADS-box TFs in angiosperm evolution remains to be identified. Here, we show that the formation of angiosperm-specific Type I MADS-box clades of Mγ and Mγ-interacting Mα genes (Mα*) can be tracked back to the ancestor of all angiosperms. Angiosperm-specific Mγ and Mα* genes were preferentially expressed in the endosperm, consistent with their proposed function as heterodimers in the angiosperm-specific embryo nourishing endosperm tissue. We propose that duplication and diversification of Type I MADS genes underpin the evolution of the endosperm, a developmental innovation closely connected to the origin and success of angiosperms.

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          IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

          Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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              ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

              Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                Mol Biol Evol
                Mol Biol Evol
                molbev
                Molecular Biology and Evolution
                Oxford University Press
                0737-4038
                1537-1719
                January 2022
                13 December 2021
                13 December 2021
                : 39
                : 1
                : msab355
                Affiliations
                [1 ] Department of Plant Biology, Uppsala BioCenter, Swedish University of Agricultural Sciences and Linnean Centre for Plant Biology , Uppsala, Sweden
                [2 ] Max Planck Institute of Molecular Plant Physiology , Potsdam-Golm, Germany
                Author notes
                Corresponding author: E-mail: koehler@ 123456mpimp-golm.mpg.de .
                Article
                msab355
                10.1093/molbev/msab355
                8788222
                34897514
                9031cf86-e96a-4e3b-9421-3b8dfc2b7d82
                © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Pages: 9
                Categories
                Discoveries
                AcademicSubjects/SCI01130
                AcademicSubjects/SCI01180

                Molecular biology
                plant reproduction,endosperm evolution,mads-box transcription factors,gene duplication

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