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      Genus-Wide Characterization of Bumblebee Genomes Provides Insights into Their Evolution and Variation in Ecological and Behavioral Traits

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      1 , 1 , 2 , 1 , 1 , 3 , 4 , 5 , 6 , 7 , 6 , 7 , 8 , 9 , 10 , 9 , 11 , 12 , 12 , 13 , 14 , 14 , 15 , 15 , 16 , 16 , 2 , 17 , 18 , 19 , 20 , 1 , 1 , 1 , 1 , 5 , 1 , 21 , 22 , 23 , 4 , 2 , 24 , 25 , 26 , 27 , 23 , 28 , 18 , 22
      Molecular Biology and Evolution
      Oxford University Press
      Bombus, insect diversity, genome assembly, genome evolution, gene family evolution

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          Abstract

          Bumblebees are a diverse group of globally important pollinators in natural ecosystems and for agricultural food production. With both eusocial and solitary life-cycle phases, and some social parasite species, they are especially interesting models to understand social evolution, behavior, and ecology. Reports of many species in decline point to pathogen transmission, habitat loss, pesticide usage, and global climate change, as interconnected causes. These threats to bumblebee diversity make our reliance on a handful of well-studied species for agricultural pollination particularly precarious. To broadly sample bumblebee genomic and phenotypic diversity, we de novo sequenced and assembled the genomes of 17 species, representing all 15 subgenera, producing the first genus-wide quantification of genetic and genomic variation potentially underlying key ecological and behavioral traits. The species phylogeny resolves subgenera relationships, whereas incomplete lineage sorting likely drives high levels of gene tree discordance. Five chromosome-level assemblies show a stable 18-chromosome karyotype, with major rearrangements creating 25 chromosomes in social parasites. Differential transposable element activity drives changes in genome sizes, with putative domestications of repetitive sequences influencing gene coding and regulatory potential. Dynamically evolving gene families and signatures of positive selection point to genus-wide variation in processes linked to foraging, diet and metabolism, immunity and detoxification, as well as adaptations for life at high altitudes. Our study reveals how bumblebee genes and genomes have evolved across the Bombus phylogeny and identifies variations potentially linked to key ecological and behavioral traits of these important pollinators.

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          IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

          Abstract IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.
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            PAML 4: phylogenetic analysis by maximum likelihood.

            PAML, currently in version 4, is a package of programs for phylogenetic analyses of DNA and protein sequences using maximum likelihood (ML). The programs may be used to compare and test phylogenetic trees, but their main strengths lie in the rich repertoire of evolutionary models implemented, which can be used to estimate parameters in models of sequence evolution and to test interesting biological hypotheses. Uses of the programs include estimation of synonymous and nonsynonymous rates (d(N) and d(S)) between two protein-coding DNA sequences, inference of positive Darwinian selection through phylogenetic comparison of protein-coding genes, reconstruction of ancestral genes and proteins for molecular restoration studies of extinct life forms, combined analysis of heterogeneous data sets from multiple gene loci, and estimation of species divergence times incorporating uncertainties in fossil calibrations. This note discusses some of the major applications of the package, which includes example data sets to demonstrate their use. The package is written in ANSI C, and runs under Windows, Mac OSX, and UNIX systems. It is available at -- (http://abacus.gene.ucl.ac.uk/software/paml.html).
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              MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity

              MCScan is an algorithm able to scan multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and align these regions using genes as anchors. The MCScanX toolkit implements an adjusted MCScan algorithm for detection of synteny and collinearity that extends the original software by incorporating 14 utility programs for visualization of results and additional downstream analyses. Applications of MCScanX to several sequenced plant genomes and gene families are shown as examples. MCScanX can be used to effectively analyze chromosome structural changes, and reveal the history of gene family expansions that might contribute to the adaptation of lineages and taxa. An integrated view of various modes of gene duplication can supplement the traditional gene tree analysis in specific families. The source code and documentation of MCScanX are freely available at http://chibba.pgml.uga.edu/mcscan2/.
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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
                February 2021
                18 September 2020
                18 September 2020
                : 38
                : 2
                : 486-501
                Affiliations
                [1 ] Institute of Apicultural Research, Chinese Academy of Agricultural Sciences , Beijing, China
                [2 ] School of Life Sciences, Chongqing University , Chongqing, China
                [3 ] Division of Biological Sciences, University of Montana , Missoula, MT
                [4 ] State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University , Wuhan, China
                [5 ] Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University , Fuzhou, China
                [6 ] MIT Computer Science and Artificial Intelligence Laboratory , Cambridge, MA
                [7 ] Broad Institute of MIT and Harvard , Cambridge, MA
                [8 ] Institute of Atmospheric Pollution Research-Italian National Research Council C/O Department of Physics, University of Bari , Bari, Italy
                [9 ] Department of Entomology, Virginia Polytechnic and State University , Blacksburg, VA
                [10 ] Department of Cytology and Genetics, Tomsk State University , Tomsk, Russian Federation
                [11 ] Department of Livestock Population Genomics, Institute of Animal Science, University of Hohenheim , Stuttgart, Germany
                [12 ] UC Santa Cruz Genomics Institute, University of California Santa Cruz , Santa Cruz, CA
                [13 ] Deutsches Krebsforschungszentrum , Heidelberg, Germany
                [14 ] Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences , Shenzhen, China
                [15 ] BGI Genomics, BGI-Shenzhen , Shenzhen, China
                [16 ] China National Center for Bioinformation & Beijing Institute of Genomics, Chinese Academy of Sciences , Beijing, China
                [17 ] College of Pharmacy and Life Science, Jiujiang University , Jiujiang, China
                [18 ] Department of Ecology and Evolution, University of Lausanne, and Swiss Institute of Bioinformatics , Lausanne, Switzerland
                [19 ] Department of Entomology, University of Illinois at Urbana-Champaign , Champaign, IL
                [20 ] Department of Medical Microbiology and Immunology, Genome Center, and MIND Institute, University of California Davis , Davis, CA
                [21 ] Institute of Sericultural and Apiculture, Yunnan Academy of Agricultural Sciences , Mengzi, China
                [22 ] Department of Biology, Colorado State University , Fort Collins, CO
                [23 ] Department of Ecology, Evolution and Behaviour, Institute of Integrative Biology, University of Liverpool , Liverpool, United Kingdom
                [24 ] School of Biological Sciences, Illinois State University , Normal, IL
                [25 ] Department of Biology, Indiana University , Bloomington, IN
                [26 ] Department of Computer Science, Indiana University , Bloomington, IN
                [27 ] Department of Biology, Reed College , Portland, OR
                [28 ] Department of Life Sciences, Natural History Museum , London, United Kingdom
                Author notes

                Cheng Sun, Jiaxing Huang, Yun Wang, Xiaomeng Zhao, Long Su, Gregg W C Thomas and Mengya Zhao authors contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-3197-5367
                Article
                msaa240
                10.1093/molbev/msaa240
                7826183
                32946576
                ab0909e7-6f4b-4f97-b1db-7dd3d444e84c
                © The Author(s) 2020. 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 ( http://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
                Funding
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 31971397
                Funded by: Science and Technology Innovation Project of Chinese Academy of Agricultural Sciences;
                Award ID: CAAS-ASTIP-2019-IAR
                Funded by: Fundamental Research Funds for Central Non-Profit Scientific Institution of China;
                Award ID: Y2019XK13
                Funded by: National Human Genome Research Institute of the National Institutes of Health;
                Award ID: U41HG007234
                Funded by: National Institutes of Health, DOI 10.13039/100000002;
                Award ID: R01 HG004037
                Funded by: Novartis Foundation for Medical-Biological Research, DOI 10.13039/501100004784;
                Award ID: 18B116
                Funded by: Swiss National Science Foundation, DOI 10.13039/501100001711;
                Award ID: PP00P3_170664
                Funded by: National Science Foundation, DOI 10.13039/100000001;
                Award ID: DBI-1564611
                Categories
                Discoveries
                AcademicSubjects/SCI01130
                AcademicSubjects/SCI01180

                Molecular biology
                bombus,insect diversity,genome assembly,genome evolution,gene family evolution
                Molecular biology
                bombus, insect diversity, genome assembly, genome evolution, gene family evolution

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