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      Evolution of Brain-Expressed Biogenic Amine Receptors into Olfactory Trace Amine-Associated Receptors

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          Abstract

          The family of trace amine-associated receptors (TAARs) is distantly related to G protein-coupled biogenic aminergic receptors. TAARs are found in the brain as well as in the olfactory epithelium where they detect biogenic amines. However, the functional relationship of receptors from distinct TAAR subfamilies and in different species is still uncertain. Here, we perform a thorough phylogenetic analysis of 702 TAAR-like (TARL) and TAAR sequences from 48 species. We show that a clade of Tarl genes has greatly expanded in lampreys, whereas the other Tarl clade consists of only one or two orthologs in jawed vertebrates and is lost in amniotes. We also identify two small clades of Taar genes in sharks related to the remaining Taar genes in bony vertebrates, which are divided into four major clades. We further identify ligands for 61 orphan TARLs and TAARs from sea lamprey, shark, ray-finned fishes, and mammals, as well as novel ligands for two 5-hydroxytryptamine receptor 4 orthologs, a serotonin receptor subtype closely related to TAARs. Our results reveal a pattern of functional convergence and segregation: TARLs from sea lamprey and bony vertebrate olfactory TAARs underwent independent expansions to function as chemosensory receptors, whereas TARLs from jawed vertebrates retain ancestral response profiles and may have similar functions to TAAR1 in the brain. Overall, our data provide a comprehensive understanding of the evolution and ligand recognition profiles of TAARs and TARLs.

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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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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              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
                March 2022
                11 January 2022
                11 January 2022
                : 39
                : 3
                : msac006
                Affiliations
                [1 ] Center for Brain Science, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University , Shanghai, China
                [2 ] Department of Anatomy and Physiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine , Shanghai, China
                [3 ] State Key Laboratory of Bioelectronics, Department of Otolaryngology Head and Neck Surgery, Zhongda Hospital, School of Life Sciences and Technology, Jiangsu Province High-Tech Key Laboratory for Bio-Medical Research, Southeast University , Nanjing, China
                [4 ] Co-Innovation Center of Neuroregeneration, Nantong University , Nantong, China
                [5 ] Department of Otolaryngology Head and Neck Surgery, Affiliated Drum Tower Hospital of Nanjing University Medical School, Jiangsu Provincial Key Medical Discipline (Laboratory) , Nanjing, China
                [6 ] Research Institute of Otolaryngology , Nanjing, China
                [7 ] Max Planck Institute for Ornithology, Evolution of Sensory Systems Research Group , Seewiesen, Germany
                [8 ] Macaulay Library, Cornell Lab of Ornithology , Ithaca, NY, USA
                [9 ] Shanghai Research Center for Brain Science and Brain-Inspired Intelligence , Shanghai, China
                Author notes

                Lingna Guo, Wenxuan Dai and Zhengrong Xu contributed equally to this work.

                Corresponding authors: E-mails: renjiec@ 123456seu.edu.cn ; liqian@ 123456shsmu.edu.cn .
                Author information
                https://orcid.org/0000-0002-7601-8894
                https://orcid.org/0000-0003-1300-3377
                Article
                msac006
                10.1093/molbev/msac006
                8890504
                35021231
                68f23a4f-07f3-4264-be22-a2aadcb1b6ff
                © The Author(s) 2022. 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: 16
                Categories
                Discoveries
                AcademicSubjects/SCI01130
                AcademicSubjects/SCI01180

                Molecular biology
                trace amine-associated receptor,olfactory receptor,gpcr,receptor evolution,receptor deorphanization,site-directed mutagenesis,homology modeling

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