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Berv JS, Singhal S, Field DJ, Walker-Hale N, McHugh SW, Shipley JR, Miller ET, Kimball RT, Braun EL, Dornburg A, Parins-Fukuchi CT, Prum RO, Winger BM, Friedman M, Smith SA. Genome and life-history evolution link bird diversification to the end-Cretaceous mass extinction. SCIENCE ADVANCES 2024; 10:eadp0114. [PMID: 39083615 PMCID: PMC11290531 DOI: 10.1126/sciadv.adp0114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Accepted: 06/28/2024] [Indexed: 08/02/2024]
Abstract
Complex patterns of genome evolution associated with the end-Cretaceous [Cretaceous-Paleogene (K-Pg)] mass extinction limit our understanding of the early evolutionary history of modern birds. Here, we analyzed patterns of avian molecular evolution and identified distinct macroevolutionary regimes across exons, introns, untranslated regions, and mitochondrial genomes. Bird clades originating near the K-Pg boundary exhibited numerous shifts in the mode of molecular evolution, suggesting a burst of genomic heterogeneity at this point in Earth's history. These inferred shifts in substitution patterns were closely related to evolutionary shifts in developmental mode, adult body mass, and patterns of metabolic scaling. Our results suggest that the end-Cretaceous mass extinction triggered integrated patterns of evolution across avian genomes, physiology, and life history near the dawn of the modern bird radiation.
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Affiliation(s)
- Jacob S. Berv
- Department of Ecology and Evolutionary Biology, University of Michigan, 1105 North University Avenue, Biological Sciences Building, University of Michigan, Ann Arbor, MI 48109, USA
- Museum of Paleontology, University of Michigan, 1105 North University Avenue, Biological Sciences Building, University of Michigan, Ann Arbor, MI 48109, USA
- Museum of Zoology, University of Michigan, 1105 North University Avenue, Biological Sciences Building, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sonal Singhal
- Department of Biology, California State University, Dominguez Hills, Carson, CA 90747, USA
| | - Daniel J. Field
- Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK
- Museum of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
| | - Nathanael Walker-Hale
- Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EA, UK
| | - Sean W. McHugh
- Department of Evolution, Ecology, and Population Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - J. Ryan Shipley
- Department of Forest Dynamics, Swiss Federal Institute for Forest, Snow, and Landscape Research WSL, Zürcherstrasse 111 8903, Birmensdorf, Switzerland
| | - Eliot T. Miller
- Center for Avian Population Studies, Cornell Lab of Ornithology, Cornell University, Ithaca, NY 14850, USA
| | - Rebecca T. Kimball
- Department of Biology, University of Florida, Gainesville, FL 32611, USA
| | - Edward L. Braun
- Department of Biology, University of Florida, Gainesville, FL 32611, USA
| | - Alex Dornburg
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC 28223, USA
| | - C. Tomomi Parins-Fukuchi
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario M5S 3B2, Canada
| | - Richard O. Prum
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA
- Peabody Museum of Natural History, Yale University, New Haven, CT 06520, USA
| | - Benjamin M. Winger
- Department of Ecology and Evolutionary Biology, University of Michigan, 1105 North University Avenue, Biological Sciences Building, University of Michigan, Ann Arbor, MI 48109, USA
- Museum of Zoology, University of Michigan, 1105 North University Avenue, Biological Sciences Building, University of Michigan, Ann Arbor, MI 48109, USA
| | - Matt Friedman
- Museum of Paleontology, University of Michigan, 1105 North University Avenue, Biological Sciences Building, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Earth and Environmental Sciences, University of Michigan, 1100 North University Avenue, University of Michigan, Ann Arbor, MI 48109, USA
| | - Stephen A. Smith
- Department of Ecology and Evolutionary Biology, University of Michigan, 1105 North University Avenue, Biological Sciences Building, University of Michigan, Ann Arbor, MI 48109, USA
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2
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Stiller J, Feng S, Chowdhury AA, Rivas-González I, Duchêne DA, Fang Q, Deng Y, Kozlov A, Stamatakis A, Claramunt S, Nguyen JMT, Ho SYW, Faircloth BC, Haag J, Houde P, Cracraft J, Balaban M, Mai U, Chen G, Gao R, Zhou C, Xie Y, Huang Z, Cao Z, Yan Z, Ogilvie HA, Nakhleh L, Lindow B, Morel B, Fjeldså J, Hosner PA, da Fonseca RR, Petersen B, Tobias JA, Székely T, Kennedy JD, Reeve AH, Liker A, Stervander M, Antunes A, Tietze DT, Bertelsen MF, Lei F, Rahbek C, Graves GR, Schierup MH, Warnow T, Braun EL, Gilbert MTP, Jarvis ED, Mirarab S, Zhang G. Complexity of avian evolution revealed by family-level genomes. Nature 2024; 629:851-860. [PMID: 38560995 PMCID: PMC11111414 DOI: 10.1038/s41586-024-07323-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 03/15/2024] [Indexed: 04/04/2024]
Abstract
Despite tremendous efforts in the past decades, relationships among main avian lineages remain heavily debated without a clear resolution. Discrepancies have been attributed to diversity of species sampled, phylogenetic method and the choice of genomic regions1-3. Here we address these issues by analysing the genomes of 363 bird species4 (218 taxonomic families, 92% of total). Using intergenic regions and coalescent methods, we present a well-supported tree but also a marked degree of discordance. The tree confirms that Neoaves experienced rapid radiation at or near the Cretaceous-Palaeogene boundary. Sufficient loci rather than extensive taxon sampling were more effective in resolving difficult nodes. Remaining recalcitrant nodes involve species that are a challenge to model due to either extreme DNA composition, variable substitution rates, incomplete lineage sorting or complex evolutionary events such as ancient hybridization. Assessment of the effects of different genomic partitions showed high heterogeneity across the genome. We discovered sharp increases in effective population size, substitution rates and relative brain size following the Cretaceous-Palaeogene extinction event, supporting the hypothesis that emerging ecological opportunities catalysed the diversification of modern birds. The resulting phylogenetic estimate offers fresh insights into the rapid radiation of modern birds and provides a taxon-rich backbone tree for future comparative studies.
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Affiliation(s)
- Josefin Stiller
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
| | - Shaohong Feng
- Center for Evolutionary & Organismal Biology, Liangzhu Laboratory & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiashan, China
| | - Al-Aabid Chowdhury
- School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia
| | | | - David A Duchêne
- Center for Evolutionary Hologenomics, The Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Qi Fang
- BGI Research, Shenzhen, China
| | - Yuan Deng
- BGI Research, Shenzhen, China
- BGI Research, Wuhan, China
| | - Alexey Kozlov
- Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
| | - Alexandros Stamatakis
- Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
- Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece
- Institute for Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Santiago Claramunt
- Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
- Department of Natural History, Royal Ontario Museum, Toronto, Ontario, Canada
| | - Jacqueline M T Nguyen
- College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia
- Australian Museum Research Institute, Sydney, New South Wales, Australia
| | - Simon Y W Ho
- School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia
| | - Brant C Faircloth
- Department of Biological Sciences and Museum of Natural Science, Louisiana State University, Baton Rouge, LA, USA
| | - Julia Haag
- Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
| | - Peter Houde
- Department of Biology, New Mexico State University, Las Cruces, NM, USA
| | - Joel Cracraft
- Department of Ornithology, American Museum of Natural History, New York, NY, USA
| | - Metin Balaban
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Uyen Mai
- Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Guangji Chen
- BGI Research, Wuhan, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Rongsheng Gao
- BGI Research, Wuhan, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | | | - Yulong Xie
- Center for Evolutionary & Organismal Biology, Liangzhu Laboratory & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zijian Huang
- Center for Evolutionary & Organismal Biology, Liangzhu Laboratory & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhen Cao
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Zhi Yan
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Huw A Ogilvie
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Luay Nakhleh
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Bent Lindow
- Natural History Museum Denmark, University of Copenhagen, Copenhagen, Denmark
| | - Benoit Morel
- Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies, Heidelberg, Germany
- Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece
| | - Jon Fjeldså
- Natural History Museum Denmark, University of Copenhagen, Copenhagen, Denmark
| | - Peter A Hosner
- Natural History Museum Denmark, University of Copenhagen, Copenhagen, Denmark
- Center for Global Mountain Biodiversity, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Rute R da Fonseca
- Center for Global Mountain Biodiversity, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Bent Petersen
- Center for Evolutionary Hologenomics, The Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Centre of Excellence for Omics-Driven Computational Biodiscovery, Faculty of Applied Sciences, AIMST University, Bedong, Malaysia
| | - Joseph A Tobias
- Department of Life Sciences, Imperial College London, Silwood Park, Ascot, UK
| | - Tamás Székely
- Milner Centre for Evolution, University of Bath, Bath, UK
- ELKH-DE Reproductive Strategies Research Group, University of Debrecen, Debrecen, Hungary
| | - Jonathan David Kennedy
- Center for Macroecology, Evolution, and Climate, The Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Andrew Hart Reeve
- Natural History Museum Denmark, University of Copenhagen, Copenhagen, Denmark
| | - Andras Liker
- HUN-REN-PE Evolutionary Ecology Research Group, University of Pannonia, Veszprém, Hungary
- Behavioural Ecology Research Group, Center for Natural Sciences, University of Pannonia, Veszprém, Hungary
| | | | - Agostinho Antunes
- CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Porto, Portugal
- Department of Biology, Faculty of Sciences, University of Porto, Porto, Portugal
| | | | - Mads F Bertelsen
- Centre for Zoo and Wild Animal Health, Copenhagen Zoo, Frederiksberg, Denmark
| | - Fumin Lei
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Carsten Rahbek
- Center for Global Mountain Biodiversity, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Center for Macroecology, Evolution, and Climate, The Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Institute of Ecology, Peking University, Beijing, China
- Danish Institute for Advanced Study, University of Southern Denmark, Odense, Denmark
| | - Gary R Graves
- Center for Macroecology, Evolution, and Climate, The Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Vertebrate Zoology, National Museum of Natural History, Smithsonian Institution, Washington, DC, USA
| | | | - Tandy Warnow
- University of Illinois Urbana-Champaign, Champaign, IL, USA
| | - Edward L Braun
- Department of Biology, University of Florida, Gainesville, FL, USA
| | - M Thomas P Gilbert
- Center for Evolutionary Hologenomics, The Globe Institute, University of Copenhagen, Copenhagen, Denmark
- University Museum, NTNU, Trondheim, Norway
| | - Erich D Jarvis
- Vertebrate Genome Lab, The Rockefeller University, New York, NY, USA
- Howard Hughes Medical Institute, Durham, NC, USA
| | | | - Guojie Zhang
- Center for Evolutionary & Organismal Biology, Liangzhu Laboratory & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiashan, China.
- BGI Research, Wuhan, China.
- Villum Center for Biodiversity Genomics, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
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Mirarab S, Rivas-González I, Feng S, Stiller J, Fang Q, Mai U, Hickey G, Chen G, Brajuka N, Fedrigo O, Formenti G, Wolf JBW, Howe K, Antunes A, Schierup MH, Paten B, Jarvis ED, Zhang G, Braun EL. A region of suppressed recombination misleads neoavian phylogenomics. Proc Natl Acad Sci U S A 2024; 121:e2319506121. [PMID: 38557186 PMCID: PMC11009670 DOI: 10.1073/pnas.2319506121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 02/07/2024] [Indexed: 04/04/2024] Open
Abstract
Genomes are typically mosaics of regions with different evolutionary histories. When speciation events are closely spaced in time, recombination makes the regions sharing the same history small, and the evolutionary history changes rapidly as we move along the genome. When examining rapid radiations such as the early diversification of Neoaves 66 Mya, typically no consistent history is observed across segments exceeding kilobases of the genome. Here, we report an exception. We found that a 21-Mb region in avian genomes, mapped to chicken chromosome 4, shows an extremely strong and discordance-free signal for a history different from that of the inferred species tree. Such a strong discordance-free signal, indicative of suppressed recombination across many millions of base pairs, is not observed elsewhere in the genome for any deep avian relationships. Although long regions with suppressed recombination have been documented in recently diverged species, our results pertain to relationships dating circa 65 Mya. We provide evidence that this strong signal may be due to an ancient rearrangement that blocked recombination and remained polymorphic for several million years prior to fixation. We show that the presence of this region has misled previous phylogenomic efforts with lower taxon sampling, showing the interplay between taxon and locus sampling. We predict that similar ancient rearrangements may confound phylogenetic analyses in other clades, pointing to a need for new analytical models that incorporate the possibility of such events.
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Affiliation(s)
- Siavash Mirarab
- Electrical and Computer Engineering Department, University of California, San Diego, CA95032
| | | | - Shaohong Feng
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou310058, China
- Liangzhu Laboratory, Zhejiang University, Hangzhou311121, China
| | - Josefin Stiller
- Section for Ecology & Evolution, Department of Biology, University of Copenhagen, København2100, Denmark
| | - Qi Fang
- BGI-Research, Shenzhen518083, China
| | - Uyen Mai
- Electrical and Computer Engineering Department, University of California, San Diego, CA95032
| | - Glenn Hickey
- Genomics Institute, University of California, Santa Cruz, CA96064
| | - Guangji Chen
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou310058, China
- Liangzhu Laboratory, Zhejiang University, Hangzhou311121, China
| | - Nadolina Brajuka
- Vertebrate Genome Lab, Rockefeller University, New York, NY10065
| | - Olivier Fedrigo
- Vertebrate Genome Lab, Rockefeller University, New York, NY10065
| | - Giulio Formenti
- Vertebrate Genome Lab, Rockefeller University, New York, NY10065
| | - Jochen B. W. Wolf
- Division of Evolutionary Biology, Faculty of Biology, Ludwig-Maximillians-Universität, Munich82152, Germany
| | - Kerstin Howe
- Tree of Life Division, Wellcome Sanger Institute, CambridgeCB10 1RQ, United Kingdom
| | - Agostinho Antunes
- Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Porto4099-002, Portugal
- Department of Biology, Faculty of Sciences, University of Porto, Porto4099-002, Portugal
| | | | - Benedict Paten
- Genomics Institute, University of California, Santa Cruz, CA96064
| | - Erich D. Jarvis
- Vertebrate Genome Lab, Rockefeller University, New York, NY10065
| | - Guojie Zhang
- Center for Evolutionary & Organismal Biology, Zhejiang University School of Medicine, Hangzhou310058, China
| | - Edward L. Braun
- Department of Biology, University of Florida, Gainesville, FL32611
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4
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Wang N, Braun EL, Liang B, Cracraft J, Smith SA. Categorical edge-based analyses of phylogenomic data reveal conflicting signals for difficult relationships in the avian tree. Mol Phylogenet Evol 2022; 174:107550. [PMID: 35691570 DOI: 10.1016/j.ympev.2022.107550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 05/13/2022] [Accepted: 06/02/2022] [Indexed: 11/28/2022]
Abstract
Phylogenetic analyses fail to yield a satisfactory resolution of some relationships in the tree of life even with genome-scale datasets, so the failure is unlikely to reflect limitations in the amount of data. Gene tree conflicts are particularly notable in studies focused on these contentious nodes, and taxon sampling, different analytical methods, and/or data type effects can further confound analyses. Although many efforts have been made to incorporate biological conflicts, few studies have curated individual genes for their efficiency in phylogenomic studies. Here, we conduct an edge-based analysis of Neoavian evolution, examining the phylogenetic efficacy of two recent phylogenomic bird datasets and three datatypes (ultraconserved elements [UCEs], introns, and coding regions). We assess the potential causes for biases in signal-resolution for three difficult nodes: the earliest divergence of Neoaves, the position of the enigmatic Hoatzin (Opisthocomus hoazin), and the position of owls (Strigiformes). We observed extensive conflict among genes for all data types and datasets even after meticulous curation. Edge-based analyses (EBA) increased congruence and provided information about the impact of data type, GC content variation (GCCV), and outlier genes on each of nodes we examined. First, outlier gene signals appeared to drive different patterns of support for the relationships among the earliest diverging Neoaves. Second, the placement of Hoatzin was highly variable, although our EBA did reveal a previously unappreciated data type effect with an impact on its position. It also revealed that the resolution with the most support here was Hoatzin + shorebirds. Finally, GCCV, rather than data type (i.e., coding vs non-coding) per se, was correlated with a signal that supports monophyly of owls + Accipitriformes (hawks, eagles, and vultures). Eliminating high GCCV loci increased the signal for owls + mousebirds. Categorical EBA was able to reveal the nature of each edge and provide a way to highlight especially problematic branches that warrant a further examination. The current study increases our understanding about the contentious parts of the avian tree, which show even greater conflicts than appreciated previously.
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Affiliation(s)
- Ning Wang
- College of Life Sciences, Inner Mongolia University, Hohhot 010070, China; Department of Ecology & Evolutionary Biology, University of Michigan, 1105 N University Ave, Ann Arbor, MI 48109-1048, USA; Department of Ornithology, American Museum of Natural History, New York, NY 10024, USA.
| | - Edward L Braun
- Department of Biology, University of Florida, Gainesville, FL 32607, USA
| | - Bin Liang
- College of Life Sciences, Inner Mongolia University, Hohhot 010070, China; Department of Ecology & Evolutionary Biology, University of Michigan, 1105 N University Ave, Ann Arbor, MI 48109-1048, USA
| | - Joel Cracraft
- Department of Ornithology, American Museum of Natural History, New York, NY 10024, USA
| | - Stephen A Smith
- Department of Ecology & Evolutionary Biology, University of Michigan, 1105 N University Ave, Ann Arbor, MI 48109-1048, USA
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Protein Structure, Models of Sequence Evolution, and Data Type Effects in Phylogenetic Analyses of Mitochondrial Data: A Case Study in Birds. DIVERSITY 2021. [DOI: 10.3390/d13110555] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein-coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acid exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution matrix for transmembrane helices estimated using a variety of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa.
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Forthman M, Braun EL, Kimball RT. Gene tree quality affects empirical coalescent branch length estimation. ZOOL SCR 2021. [DOI: 10.1111/zsc.12512] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Affiliation(s)
- Michael Forthman
- Department of Entomology & Nematology University of Florida Gainesville FL USA
- California State Collection of Arthropods Plant Pest Diagnostics Branch California Department of Food & Agriculture Sacramento CA USA
| | - Edward L. Braun
- Department of Biology University of Florida Gainesville FL USA
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Kuhl H, Frankl-Vilches C, Bakker A, Mayr G, Nikolaus G, Boerno ST, Klages S, Timmermann B, Gahr M. An Unbiased Molecular Approach Using 3'-UTRs Resolves the Avian Family-Level Tree of Life. Mol Biol Evol 2021; 38:108-127. [PMID: 32781465 PMCID: PMC7783168 DOI: 10.1093/molbev/msaa191] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Presumably, due to a rapid early diversification, major parts of the higher-level phylogeny of birds are still resolved controversially in different analyses or are considered unresolvable. To address this problem, we produced an avian tree of life, which includes molecular sequences of one or several species of ∼90% of the currently recognized family-level taxa (429 species, 379 genera) including all 106 family-level taxa of the nonpasserines and 115 of the passerines (Passeriformes). The unconstrained analyses of noncoding 3-prime untranslated region (3′-UTR) sequences and those of coding sequences yielded different trees. In contrast to the coding sequences, the 3′-UTR sequences resulted in a well-resolved and stable tree topology. The 3′-UTR contained, unexpectedly, transcription factor binding motifs that were specific for different higher-level taxa. In this tree, grebes and flamingos are the sister clade of all other Neoaves, which are subdivided into five major clades. All nonpasserine taxa were placed with robust statistical support including the long-time enigmatic hoatzin (Opisthocomiformes), which was found being the sister taxon of the Caprimulgiformes. The comparatively late radiation of family-level clades of the songbirds (oscine Passeriformes) contrasts with the attenuated diversification of nonpasseriform taxa since the early Miocene. This correlates with the evolution of vocal production learning, an important speciation factor, which is ancestral for songbirds and evolved convergent only in hummingbirds and parrots. As 3′-UTR-based phylotranscriptomics resolved the avian family-level tree of life, we suggest that this procedure will also resolve the all-species avian tree of life
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Affiliation(s)
- Heiner Kuhl
- Department of Behavioural Neurobiology, Max Planck Institute for Ornithology, Seewiesen, Germany.,Max Planck Institute for Molecular Genetics, Sequencing Core Facility, Berlin, Germany.,Department of Ecophysiology and Aquaculture, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany
| | - Carolina Frankl-Vilches
- Department of Behavioural Neurobiology, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - Antje Bakker
- Department of Behavioural Neurobiology, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - Gerald Mayr
- Ornithological Section, Senckenberg Research Institute, Frankfurt am Main, Germany
| | - Gerhard Nikolaus
- Department of Behavioural Neurobiology, Max Planck Institute for Ornithology, Seewiesen, Germany
| | - Stefan T Boerno
- Max Planck Institute for Molecular Genetics, Sequencing Core Facility, Berlin, Germany
| | - Sven Klages
- Max Planck Institute for Molecular Genetics, Sequencing Core Facility, Berlin, Germany
| | - Bernd Timmermann
- Max Planck Institute for Molecular Genetics, Sequencing Core Facility, Berlin, Germany
| | - Manfred Gahr
- Department of Behavioural Neurobiology, Max Planck Institute for Ornithology, Seewiesen, Germany
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8
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Abstract
The phylogeny of Neoaves, the largest clade of extant birds, has remained unclear despite intense study. The difficulty associated with resolving the early branches in Neoaves is likely driven by the rapid radiation of this group. However, conflicts among studies may be exacerbated by the data type analyzed. For example, analyses of coding exons typically yield trees that place Strisores (nightjars and allies) sister to the remaining Neoaves, while analyses of non-coding data typically yield trees where Mirandornites (flamingos and grebes) is the sister of the remaining Neoaves. Our understanding of data type effects is hampered by the fact that previous analyses have used different taxa, loci, and types of non-coding data. Herein, we provide strong corroboration of the data type effects hypothesis for Neoaves by comparing trees based on coding and non-coding data derived from the same taxa and gene regions. A simple analytical method known to minimize biases due to base composition (coding nucleotides as purines and pyrimidines) resulted in coding exon data with increased congruence to the non-coding topology using concatenated analyses. These results improve our understanding of the resolution of neoavian phylogeny and point to a challenge—data type effects—that is likely to be an important factor in phylogenetic analyses of birds (and many other taxonomic groups). Using our results, we provide a summary phylogeny that identifies well-corroborated relationships and highlights specific nodes where future efforts should focus.
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