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      Firefly genomes illuminate parallel origins of bioluminescence in beetles

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          Abstract

          Fireflies and their luminous courtships have inspired centuries of scientific study. Today firefly luciferase is widely used in biotechnology, but the evolutionary origin of bioluminescence within beetles remains unclear. To shed light on this long-standing question, we sequenced the genomes of two firefly species that diverged over 100 million-years-ago: the North American Photinus pyralis and Japanese Aquatica lateralis. To compare bioluminescent origins, we also sequenced the genome of a related click beetle, the Caribbean Ignelater luminosus, with bioluminescent biochemistry near-identical to fireflies, but anatomically unique light organs, suggesting the intriguing hypothesis of parallel gains of bioluminescence. Our analyses support independent gains of bioluminescence in fireflies and click beetles, and provide new insights into the genes, chemical defenses, and symbionts that evolved alongside their luminous lifestyle.

          eLife digest

          Glowing fireflies dancing in the dark are one of the most enchanting sights of a warm summer night. Their light signals are ‘love messages’ that help the insects find a mate – yet, they also warn a potential predator that these beetles have powerful chemical defenses. The light comes from a specialized organ of the firefly where a small molecule, luciferin, is broken down by the enzyme luciferase.

          Fireflies are an ancient group, with the common ancestor of the two main lineages originating over 100 million years ago. But fireflies are not the only insects that produce light: certain click beetles are also bioluminescent.

          Fireflies and click beetles are closely related, and they both use identical luciferin and similar luciferases to create light. This would suggest that bioluminescence was already present in the common ancestor of the two families. However, the specialized organs in which the chemical reactions take place are entirely different, which would indicate that the ability to produce light arose independently in each group.

          Here, Fallon, Lower et al. try to resolve this discrepancy and to find out how many times bioluminescence evolved in beetles. This required using cutting-edge DNA sequencing to carefully piece together the genomes of two species of fireflies ( Photinus pyralis and Aquatica lateralis) and one species of click beetle ( Ignelater luminosus). The genetic analysis revealed that, in all species, the genes for luciferases were very similar to the genetic sequences around them, which code for proteins that break down fat. This indicates that the ancestral luciferase arose from one of these metabolic genes getting duplicated, and then one of the copies evolving a new role.

          However, the genes for luciferase were very different between the fireflies and the click beetles. Further analyses suggested that bioluminescence evolved at least twice: once in an ancestor of fireflies, and once in the ancestor of the bioluminescent click beetles.

          More results came from the reconstituted genomes. For example, Fallon, Lower et al. identified the genes ‘turned on’ in the bioluminescent organ of the fireflies. This made it possible to list genes that may be involved in creating luciferin, and enable flies to grow brightly for long periods. In addition, the genetic information yielded sequences from bacteria that likely live inside firefly cells, and which may participate in the light-making process or the production of potent chemical defenses.

          Better genetic knowledge of beetle bioluminescence could bring new advances for both insects and humans. It may help researchers find and design better light-emitting molecules useful to track and quantify proteins of interest in a cell. Ultimately, it would allow a detailed understanding of firefly populations around the world, which could contribute to firefly ecotourism and help to protect these glowing insects from increasing environmental threats.

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          Most cited references 189

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          The genome of the model beetle and pest Tribolium castaneum.

          Tribolium castaneum is a member of the most species-rich eukaryotic order, a powerful model organism for the study of generalized insect development, and an important pest of stored agricultural products. We describe its genome sequence here. This omnivorous beetle has evolved the ability to interact with a diverse chemical environment, as shown by large expansions in odorant and gustatory receptors, as well as P450 and other detoxification enzymes. Development in Tribolium is more representative of other insects than is Drosophila, a fact reflected in gene content and function. For example, Tribolium has retained more ancestral genes involved in cell-cell communication than Drosophila, some being expressed in the growth zone crucial for axial elongation in short-germ development. Systemic RNA interference in T. castaneum functions differently from that in Caenorhabditis elegans, but nevertheless offers similar power for the elucidation of gene function and identification of targets for selective insect control.
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            Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources

            Background In order to improve gene prediction, extrinsic evidence on the gene structure can be collected from various sources of information such as genome-genome comparisons and EST and protein alignments. However, such evidence is often incomplete and usually uncertain. The extrinsic evidence is usually not sufficient to recover the complete gene structure of all genes completely and the available evidence is often unreliable. Therefore extrinsic evidence is most valuable when it is balanced with sequence-intrinsic evidence. Results We present a fairly general method for integration of external information. Our method is based on the evaluation of hints to potentially protein-coding regions by means of a Generalized Hidden Markov Model (GHMM) that takes both intrinsic and extrinsic information into account. We used this method to extend the ab initio gene prediction program AUGUSTUS to a versatile tool that we call AUGUSTUS+. In this study, we focus on hints derived from matches to an EST or protein database, but our approach can be used to include arbitrary user-defined hints. Our method is only moderately effected by the length of a database match. Further, it exploits the information that can be derived from the absence of such matches. As a special case, AUGUSTUS+ can predict genes under user-defined constraints, e.g. if the positions of certain exons are known. With hints from EST and protein databases, our new approach was able to predict 89% of the exons in human chromosome 22 correctly. Conclusion Sensitive probabilistic modeling of extrinsic evidence such as sequence database matches can increase gene prediction accuracy. When a match of a sequence interval to an EST or protein sequence is used it should be treated as compound information rather than as information about individual positions.
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              Database resources of the National Center for Biotechnology.

               D Wheeler (2003)
              In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, PubMed, PubMed Central (PMC), LocusLink, the NCBITaxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR (e-PCR), Open Reading Frame (ORF) Finder, References Sequence (RefSeq), UniGene, HomoloGene, ProtEST, Database of Single Nucleotide Polymorphisms (dbSNP), Human/Mouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes and related tools, the Map Viewer, Model Maker (MM), Evidence Viewer (EV), Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                16 October 2018
                2018
                : 7
                Affiliations
                [1 ]Whitehead Institute for Biomedical Research CambridgeUnited States
                [2 ]deptDepartment of Biology Massachusetts Institute of Technology CambridgeUnited States
                [3 ]deptDepartment of Molecular Biology and Genetics Cornell University IthacaUnited States
                [4 ]deptDepartment of Biology Bucknell University LewisburgUnited States
                [5 ]deptDepartment of Biology University of Rochester RochesterUnited States
                [6 ]deptDepartment of Environmental Biology Chubu University KasugaiJapan
                [7 ]deptGraduate School of Bioagricultural Sciences Nagoya University NagoyaJapan
                [8 ]Monterey Bay Aquarium Research Institute Moss LandingUnited States
                [9 ]deptDepartment of Biology Brigham Young University ProvoUnited States
                [10 ]deptDepartment of Genetics University of Georgia AthensUnited States
                [11 ]deptBiodesign Center for Mechanisms of Evolution Arizona State University TempeUnited States
                [12 ]Center of Agronomic Research, National Institute of Agricultural Technology CórdobaArgentina
                [13 ]Centre for Ecology and Hydrology (CEH) WallingfordUnited Kingdom
                [14 ]deptDepartment of Plant Sciences University of California Davis DavisUnited States
                [15 ]deptDepartment of Plant Biology University of Georgia AthensUnited States
                [16 ]deptDepartment of Microbiology Immunology and Biochemistry University of Tennessee HSC MemphisUnited States
                [17 ]deptDepartment of Biology Tufts University MedfordUnited States
                [18 ]deptNIBB Core Research Facilities National Institute for Basic Biology OkazakiJapan
                Université Lausanne Switzerland
                Max-Planck Institute for Evolutionary Biology Germany
                Université Lausanne Switzerland
                Max-Planck Institute for Evolutionary Biology Germany
                Author notes
                [†]

                These authors contributed equally to this work.

                Article
                36495
                10.7554/eLife.36495
                6191289
                30324905
                © 2018, Fallon et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                Product
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000997, Arnold and Mabel Beckman Foundation;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100005665, Kinship Foundation;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: Graduate Student Fellowship
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000875, Pew Charitable Trusts;
                Award ID: Pew Scholar Program in the Biomedical Sciences
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100006324, National Institute for Basic Biology;
                Award ID: Cooperative Research Program, 12-202
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: 5R35-GM119515-03
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100008065, Georgia Research Alliance;
                Award ID: Lars G. Ljungdahl Distinguished Investigator
                Award Recipient :
                Funded by: Experiment.com;
                Award ID: https://experiment.com/projects/illuminating-the-firefly-genome
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: MCB-1818132
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Genetics and Genomics
                Custom metadata
                The first genomic view of beetle luciferase evolution indicates evolutionary independence of luciferase between fireflies and click-beetles, and provide valuable datasets which will accelerate the discovery of new biotechnological tools.

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