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Microbiome diversity and host immune functions influence survivorship of sponge holobionts under future ocean conditions

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  • 1.

    Le Quéré C, Moriarty R, Andrew RM, Canadell JG, Sitch S, Korsbakken JI, et al. Global carbon budget 2015. Earth Syst Sci Data. 2015;7:349–96.

    Article 

    Google Scholar 

  • 2.

    Hoegh-Guldberg O, Mumby PJ, Hooten AJ, Steneck RS, Greenfield P, Gomez E, et al. Coral reefs under rapid climate change and ocean acidification. Science. 2007;318:1737–42.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 3.

    Bell JJ, Bennett HM, Rovellini A, Webster NS. Sponges to be winners under near-future climate scenarios. Bioscience. 2018;68:955–68.

    Article 

    Google Scholar 

  • 4.

    Bell JJ. The functional roles of marine sponges. Estuar Coast Shelf Sci. 2008;79:341–53.

    Article 

    Google Scholar 

  • 5.

    Pita L, Rix L, Slaby BM, Franke A, Hentschel U. The sponge holobiont in a changing ocean: from microbes to ecosystems. Microbiome. 2018;6:46.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 6.

    Smith AM, Berman J, Key MM Jr, Winter DJ. Not all sponges will thrive in a high-CO2 ocean: Review of the mineralogy of calcifying sponges. Palaeogeogr Palaeoclimatol Palaeoecol. 2013;392:463–72.

    Article 

    Google Scholar 

  • 7.

    Webster NS, Thomas T. The sponge hologenome. MBio. 2016;7:e00135–16.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 8.

    Hentschel U, Piel J, Degnan SM, Taylor MW. Genomic insights into the marine sponge microbiome. Nat Rev Microbiol. 2012;10:641–54.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 9.

    Thompson JR, Rivera HE, Closek CJ, Medina M. Microbes in the coral holobiont: partners through evolution, development, and ecological interactions. Front Cell Infect Microbiol. 2014;4:176.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 10.

    Fan L, Liu M, Simister R, Webster NS, Thomas T. Marine microbial symbiosis heats up: the phylogenetic and functional response of a sponge holobiont to thermal stress. ISME J. 2013;7:991–1002.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 11.

    Egan S, Gardiner M. Microbial dysbiosis: rethinking disease in marine ecosystems. Front Microbiol. 2016;7:991.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 12.

    Voolstra CR, Ziegler M. Adapting with microbial help: microbiome flexibility facilitates rapid responses to environmental change. Bioessays. 2020;42:e2000004.

    PubMed 
    Article 

    Google Scholar 

  • 13.

    Botte ES, Nielsen S, Abdul Wahab MA, Webster J, Robbins S, Thomas T, et al. Changes in the metabolic potential of the sponge microbiome under ocean acidification. Nat Commun. 2019;10:4134.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 14.

    Morrow KM, Bourne DG, Humphrey C, Botté ES, Laffy P, Zaneveld J, et al. Natural volcanic CO2 seeps reveal future trajectories for host–microbial associations in corals and sponges. ISME J. 2015;9:894–908.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 15.

    Pollock FJ, Lamb JB, van de Water J, Smith HA, Schaffelke B, Willis BL, et al. Reduced diversity and stability of coral-associated bacterial communities and suppressed immune function precedes disease onset in corals. R Soc Open Sci. 2019;6:190355.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 16.

    Pinzon JH, Kamel B, Burge CA, Harvell CD, Medina M, Weil E, et al. Whole transcriptome analysis reveals changes in expression of immune-related genes during and after bleaching in a reef-building coral. R Soc Open Sci. 2015;2:140214.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 17.

    Pita L, Hoeppner MP, Ribes M, Hentschel U. Differential expression of immune receptors in two marine sponges upon exposure to microbial-associated molecular patterns. Sci Rep. 2018;8:16081.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 18.

    Guzman C, Conaco C. Gene expression dynamics accompanying the sponge thermal stress response. PLoS ONE. 2016;11:e0165368.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 19.

    Riesgo A, Farrar N, Windsor PJ, Giribet G, Leys SP. The analysis of eight transcriptomes from all poriferan classes reveals surprising genetic complexity in sponges. Mol Biol Evol. 2014;31:1102–20.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 20.

    Germer J, Cerveau N, Jackson DJ. The holo-transcriptome of a calcified early branching metazoan. Front Mar Sci. 2017;4:81.

  • 21.

    Ryu T, Seridi L, Moitinho-Silva L, Oates M, Liew YJ, Mavromatis C, et al. Hologenome analysis of two marine sponges with different microbiomes. BMC Genomics. 2016;17:158.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 22.

    Hooper JNA, Van Soest RWM. Systema Porifera. A guide to the classification of sponges. In: Hooper JNA, Van Soest RWM, editors. Systema Porifera. New York, NY: Springer; 2002. p. 1–7.

  • 23.

    Pachauri RK, Allen MR, Barros VR, Broome J, Cramer W, Christ R, et al. Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. Geneva: IPCC; 2014.

  • 24.

    Pierrot DE, Lewis E, Wallace DWR. MS Excel program developed for CO2 system calculations. Oak Ridge, TN: Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, ORNL/CDIAC-IOS; 2006.

  • 25.

    Herlemann DP, Labrenz M, Jurgens K, Bertilsson S, Waniek JJ, Andersson AF. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 2011;5:1571–9.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 26.

    Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852–7.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 27.

    Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 28.

    Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–6.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 29.

    McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE. 2013;8:e61217.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 30.

    Dixon P. VEGAN, a package of R functions for community ecology. J Veg Sci. 2003;14:927–30.

    Article 

    Google Scholar 

  • 31.

    McMurdie PJ, Holmes S. Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput Biol. 2014;10:e1003531.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 32.

    Douglas GM, Maffei VJ, Zaneveld JR, Yurgel SN, Brown JR, Taylor CM, et al. PICRUSt2 for prediction of metagenome functions. Nat Biotechnol. 2020;38:685–8.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 33.

    Asshauer KP, Wemheuer B, Daniel R, Meinicke P. Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data. Bioinformatics. 2015;31:2882–4.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 34.

    Kanehisa M, Sato Y. KEGG Mapper for inferring cellular functions from protein sequences. Protein Sci. 2020;29:28–35.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 35.

    Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 36.

    Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc. 2013;8:1494.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 37.

    Conesa A, Gotz S. Blast2GO: A comprehensive suite for functional analysis in plant genomics. Int J Plant Genomics. 2008;2008:619832.

    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 

  • 38.

    Finn RD, Bateman A, Clements J, Coggill P, Eberhardt RY, Eddy SR, et al. Pfam: the protein families database. Nucleic Acids Res. 2014;42:D222–D30.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 39.

    Eddy SR. Profile hidden Markov models. Bioinformatics. 1998;14:755–63.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 40.

    Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;12:323.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 41.

    Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10:R25.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 42.

    Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 43.

    Alexa A, Rahnenführer J. Gene set enrichment analysis with topGO. Bioconductor Improv. 2009;27:1–26.

  • 44.

    Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47:D607–D13.

    CAS 
    Article 

    Google Scholar 

  • 45.

    Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–504.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 46.

    Moitinho-Silva L, Nielsen S, Amir A, Gonzalez A, Ackermann GL, Cerrano C, et al. The sponge microbiome project. Gigascience. 2017;6:1–7.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 47.

    Lurgi M, Thomas T, Wemheuer B, Webster NS, Montoya JM. Modularity and predicted functions of the global sponge-microbiome network. Nat Commun. 2019;10:992.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 48.

    Srivastava M, Simakov O, Chapman J, Fahey B, Gauthier ME, Mitros T, et al. The Amphimedon queenslandica genome and the evolution of animal complexity. Nature. 2010;466:720–6.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 49.

    Guzman C, Conaco C. Comparative transcriptome analysis reveals insights into the streamlined genomes of haplosclerid demosponges. Sci Rep. 2016;6:18774.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 50.

    Fortunato SA, Adamski M, Ramos OM, Leininger S, Liu J, Ferrier DE, et al. Calcisponges have a ParaHox gene and dynamic expression of dispersed NK homeobox genes. Nature. 2014;514:620–3.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 51.

    Voigt O, Fradusco B, Gut C, Kevrekidis C, Vargas S, Wörheide G. Carbonic anhydrases: an ancient tool in calcareous sponge biomineralization. Front Genet. 2021;12:624533.

  • 52.

    Yuen B, Bayes JM, Degnan SM. The characterization of sponge NLRs provides insight into the origin and evolution of this innate immune gene family in animals. Mol Biol Evol. 2014;31:106–20.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 53.

    Madeira F, Park YM, Lee J, Buso N, Gur T, Madhusoodanan N, et al. The EMBL-EBI search and sequence analysis tools APIs in 2019. Nucleic Acids Res. 2019;47:W636–41.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 54.

    Darriba D, Taboada GL, Doallo R, Posada D. ProtTest 3: fast selection of best-fit models of protein evolution. Bioinformatics. 2011;27:1164–5.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 55.

    Ronquist F, Huelsenbeck JP. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics. 2003;19:1572–4.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 56.

    Wickham H. ggplot2: elegant graphics for data analysis. New York: Springer; 2016.

  • 57.

    McDevitt-Irwin JM, Baum JK, Garren M, Vega Thurber RL. Responses of coral-associated bacterial communities to local and global stressors. Front Mar Sci. 2017;4:262.

  • 58.

    Hori K, Matsumoto S. Bacterial adhesion: from mechanism to control. Biochem Eng J. 2010;48:424–34.

    CAS 
    Article 

    Google Scholar 

  • 59.

    Yao J, Allen C. Chemotaxis is required for virulence and competitive fitness of the bacterial wilt pathogen Ralstonia solanacearum. J Bacteriol. 2006;188:3697–708.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 60.

    Chu H, Mazmanian SK. Innate immune recognition of the microbiota promotes host-microbial symbiosis. Nat Immunol. 2013;14:668–75.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 61.

    Bazzoni F, Beutler B. The tumor necrosis factor ligand and receptor families. N Engl J Med. 1996;334:1717–25.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 62.

    Hayden MS, Ghosh S. Regulation of NF-kappaB by TNF family cytokines. Semin Immunol. 2014;26:253–66.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 63.

    Parrish AB, Freel CD, Kornbluth S. Cellular mechanisms controlling caspase activation and function. Cold Spring Harb Perspect Biol. 2013;5:a008672.

  • 64.

    Wiens M, Korzhev M, Krasko A, Thakur NL, Perovic-Ottstadt S, Breter HJ, et al. Innate immune defense of the sponge Suberites domuncula against bacteria involves a MyD88-dependent signaling pathway. Induction of a perforin-like molecule. J Biol Chem. 2005;280:27949–59.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 65.

    Muller WE, Muller IM. Origin of the metazoan immune system: identification of the molecules and their functions in sponges. Integr Comp Biol. 2003;43:281–92.

    PubMed 
    Article 

    Google Scholar 

  • 66.

    Yuen B Deciphering the genomic toolkit underlying animal-bacteria interactions – insights through the demosponge Amphimedon queenslandica. Saint Lucia, QLD: School of Biological Sciences, The University of Queensland; 2016.

  • 67.

    Gauthier ME, Du Pasquier L, Degnan BM. The genome of the sponge Amphimedon queenslandica provides new perspectives into the origin of Toll-like and interleukin 1 receptor pathways. Evol Dev. 2010;12:519–33.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 68.

    Roue M, Quevrain E, Domart-Coulon I, Bourguet-Kondracki ML. Assessing calcareous sponges and their associated bacteria for the discovery of new bioactive natural products. Nat Prod Rep. 2012;29:739–51.

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 69.

    Steinert G, Busch K, Bayer K, Kodami S, Arbizu PM, Kelly M, et al. Compositional and quantitative insights into bacterial and archaeal communities of South Pacific deep-sea sponges (Demospongiae and Hexactinellida). Front Microbiol. 2020;11:716.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 70.

    Thomas T, Moitinho-Silva L, Lurgi M, Bjork JR, Easson C, Astudillo-Garcia C, et al. Diversity, structure and convergent evolution of the global sponge microbiome. Nat Commun. 2016;7:11870.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 71.

    Yap NV, Whelan FJ, Bowdish DM, Golding GB. The evolution of the scavenger receptor cysteine-rich domain of the class a scavenger receptors. Front Immunol. 2015;6:342.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 72.

    Brown GD, Willment JA, Whitehead L. C-type lectins in immunity and homeostasis. Nat Rev Immunol. 2018;18:374–89.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 73.

    von Moltke J, Ayres JS, Kofoed EM, Chavarria-Smith J, Vance RE. Recognition of bacteria by inflammasomes. Annu Rev Immunol. 2013;31:73–106.

    Article 
    CAS 

    Google Scholar 

  • 74.

    Robertson SJ, Rubino SJ, Geddes K, Philpott DJ. Examining host-microbial interactions through the lens of NOD: from plants to mammals. Semin Immunol. 2012;24:9–16.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 75.

    Ting JP, Lovering RC, Alnemri ES, Bertin J, Boss JM, Davis BK, et al. The NLR gene family: a standard nomenclature. Immunity. 2008;28:285–7.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 76.

    Messier-Solek C, Buckley KM, Rast JP. Highly diversified innate receptor systems and new forms of animal immunity. Semin Immunol. 2010;22:39–47.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 77.

    Bennett HM, Altenrath C, Woods L, Davy SK, Webster NS, Bell JJ. Interactive effects of temperature and pCO2 on sponges: from the cradle to the grave. Glob Chang Biol. 2017;23:2031–46.

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 78.

    Luter HM, Andersen M, Versteegen E, Laffy P, Uthicke S, Bell JJ, et al. Cross-generational effects of climate change on the microbiome of a photosynthetic sponge. Environ Microbiol. 2020;22:4732–44.

  • 79.

    Girvan MS, Campbell CD, Killham K, Prosser JI, Glover LA. Bacterial diversity promotes community stability and functional resilience after perturbation. Environ Microbiol. 2005;7:301–13.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 80.

    Ziegler M, Grupstra CGB, Barreto MM, Eaton M, BaOmar J, Zubier K, et al. Coral bacterial community structure responds to environmental change in a host-specific manner. Nat Commun. 2019;10:3092.

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 81.

    Ribes M, Calvo E, Movilla J, Logares R, Coma R, Pelejero C. Restructuring of the sponge microbiome favors tolerance to ocean acidification. Environ Microbiol Rep. 2016;8:536–44.

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 82.

    Vega Thurber R, Willner-Hall D, Rodriguez-Mueller B, Desnues C, Edwards RA, Angly F, et al. Metagenomic analysis of stressed coral holobionts. Environ Microbiol. 2009;11:2148–63.

    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 

  • 83.

    van de Water J, Chaib De Mares M, Dixon GB, Raina JB, Willis BL, Bourne DG, et al. Antimicrobial and stress responses to increased temperature and bacterial pathogen challenge in the holobiont of a reef-building coral. Mol Ecol. 2018;27:1065–80.

    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 

  • 84.

    Weisz JB, Lindquist N, Martens CS. Do associated microbial abundances impact marine demosponge pumping rates and tissue densities? Oecologia. 2008;155:367–76.

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 85.

    Ludeman DA, Reidenbach MA, Leys SP. The energetic cost of filtration by demosponges and their behavioural response to ambient currents. J Exp Biol. 2017;220:995–1007.

    PubMed 
    Article 

    Google Scholar 

  • 86.

    Perea-Blazquez A, Davy SK, Bell JJ. Estimates of particulate organic carbon flowing from the pelagic environment to the benthos through sponge assemblages. PLoS ONE. 2012;7:e29569.

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 87.

    Morganti TM, Ribes M, Yahel G, Coma R. Size is the major determinant of pumping rates in marine sponges. Front Physiol. 2019;10:1474.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 88.

    Peck LS, Clark MS, Power D, Reis J, Batista FM, Harper EM. Acidification effects on biofouling communities: winners and losers. Glob Chang Biol. 2015;21:1907–13.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 89.

    Ribeiro B, Padua A, Barno A, Villela H, Duarte G, Rossi A, et al. Assessing skeleton and microbiome responses of a calcareous sponge under thermal and pH stresses. ICES J Mar Sci. 2020:fsaa231.

  • 90.

    Lanna E, Klautau M. Life history and reproductive dynamics of the cryptogenic calcareous sponge Sycettusa hastifera (Porifera, Calcarea) living in tropical rocky shores. J Mar Biol Assoc UK. 2018;98:505–14.

    Article 

    Google Scholar 

  • 91.

    Pörtner HO, Langenbuch M, Michaelidis B. Synergistic effects of temperature extremes, hypoxia, and increases in CO2 on marine animals: from Earth history to global change. J Geophys Res. 2005;110:C09S10.

  • 92.

    Emms DM, Kelly S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 2019;20:238.

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 


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