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    Differential carbon utilization enables co-existence of recently speciated Campylobacteraceae in the cow rumen epithelial microbiome

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    Warmth shifts symbionts

    Abigail Meyer from the University of Minnesota, USA, and colleagues from the USA, investigated the physiological and morphological responses to experimental warming and CO2 additions in the widespread forest lichen Evernia mesomorpha. While impacts of CO2 were largely negligible, warming and associated drying was linked to decreases in biomass, carbon assimilation and respiration rates. As well as bleaching of the lichen, indicative of death of the photobiont, the authors found evidence of shifts in internal algal communities, including increased proportions of certain algal clades under warming. While the study reveals the sensitivity of lichen algae to warming, further work is needed to reveal whether photobiont turnover may assist in lichen acclimation and recovery. More

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    Author Correction: Genomic analysis of sewage from 101 countries reveals global landscape of antimicrobial resistance

    Research Group for Genomic Epidemiology, Technical University of Denmark, Kgs, Lyngby, DenmarkPatrick Munk, Christian Brinch, Frederik Duus Møller, Thomas N. Petersen, Rene S. Hendriksen, Anne Mette Seyfarth, Jette S. Kjeldgaard, Christina Aaby Svendsen & Frank M. AarestrupCentre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh, UKBram van Bunnik & Mark WoolhouseCentre for Antibiotic Resistance Research (CARe), University of Gothenburg, Gothenburg, SwedenFanny Berglund & D. G. Joakim LarssonDepartment of Viroscience, Erasmus MC, Rotterdam, The NetherlandsMarion KoopmansInstitute of Public Health, Tirana, AlbaniaArtan BegoUniversidad de Buenos Aires, Buenos Aires, ArgentinaPablo PowerMelbourne Water Corporation, Melbourne, AustraliaCatherine Rees & Kris CoventryCharles Darwin University, Darwin, AustraliaDionisia LambrinidisUniversity of Copenhagen, Frederiksberg C, DenmarkElizabeth Heather Jakobsen Neilson & Yaovi Mahuton Gildas HounmanouCharles Darwin University, Darwin Northern Territory, AustraliaKaren GibbCanberra Hospital, Canberra, AustraliaPeter CollignonALS Water, Scoresby, AustraliaSusan CassarAustrian Agency for Health and Food Safety (AGES), Vienna, AustriaFranz AllerbergerUniversity of Dhaka, Dhaka, BangladeshAnowara Begum & Zenat Zebin HossainEnvironmental Protection Department, Bridgetown, St. Michael, BarbadosCarlon WorrellLaboratoire Hospitalier Universitaire de Bruxelles (LHUB-ULB), Brussels, BelgiumOlivier VandenbergAQUAFIN NV, Aartselaar, BelgiumIlse PietersPolytechnic School of Abomey-Calavi, Abomey-Calavi, BeninDougnon Tamègnon VictorienUniversidad Catσlica Boliviana San Pablo, La Paz, BoliviaAngela Daniela Salazar Gutierrez & Freddy SoriaPublic Health Institute of the Republic of Srpska, Faculty of Medicine University of Banja Luka, Banja Luka, Bosnia and HerzegovinaVesna Rudić GrujićPublic Health Institute of the Republic of Srpska, Banja Luka, Bosnia and HerzegovinaNataša MazalicaBotswana International University of Science and Technology, Palapye, BotswanaTeddie O. RahubeUniversidade Federal de Minas Gerais, Belo Horizonte, BrazilCarlos Alberto Tagliati & Larissa Camila Ribeiro de SouzaOswaldo Cruz Institute, Rio de Janeiro, BrazilDalia RodriguesVale Institute of Technology, Belιm, PA, BrazilGuilherme OliveiraNational Center of Infectious and Parasitic Diseases, Sofia, BulgariaIvan IvanovUniversity of Ouagadougou, Ouagadougou, Burkina FasoBonkoungou Isidore Juste & Traoré OumarInstitut Pasteur du Cambodge, Phnom Penh, CambodiaThet Sopheak & Yith VuthyCentre Pasteur du Cameroun, Yaoundι, CameroonAntoinette Ngandjio, Ariane Nzouankeu & Ziem A. Abah Jacques OlivierUniversity of Regina, Regina, CanadaChristopher K. YostEau Terre Environnement Research Centre (INRS-ETE), Quebec City G1K 9A9, Canada and Indian Institute of Technology, Jammu, IndiaPratik KumarEau Terre Environnement Research Centre (INRS-ETE), Quebec City G1K 9A9, Canada and Lassonde School of Enginerring, York University, Toronto, CanadaSatinder Kaur BrarUniversity of N’Djamena, N’Djamena, ChadDjim-Adjim TaboEscuela de Medicina Veterinaria, Facultad de Ciencias de la Vida, Universidad Andres Bello, Santiago, ChileAiko D. AdellInstitute of Public Health, Santiago, ChileEsteban Paredes-Osses & Maria Cristina MartinezUniversidad Catolica del Maule, Centro de Biotecnología de los Recursos Naturales, Facultad de Ciencias Agrarias y Forestales, Talca, ChileSara Cuadros-OrellanaGuangdong Provincial Center for Disease Control and Prevention, Guangzhou, ChinaChangwen Ke, Huanying Zheng & Li BaishengThe Hong Kong Polytechnic University, Hong Kong, ChinaLok Ting Lau & Teresa ChungShantou University Medical College, Shantou, ChinaXiaoyang JiaoNanjing University of Information Science and Technology, Nanjing, ChinaYongjie YuCenter for Disease Control and Prevention of Henan province, Zhengzhou, ChinaZhao JiaYongColombian Integrated Program for Antimicrobial Resistance Surveillance – Coipars, CI Tibaitatα, Corporaciσn Colombiana de Investigaciσn Agropecuaria (AGROSAVIA), Tibaitatα – Mosquera, Cundinamarca, ColombiaJohan F. Bernal Morales, Maria Fernanda Valencia & Pilar Donado-GodoyInstitut Pasteur de Côte d’Ivoire, Abidjan, Côte d’IvoireKalpy Julien CoulibalyUniversity of Zagreb, Zagreb, CroatiaJasna HrenovicAndrija Stampar Teaching Institute of Public Health, Zagreb, CroatiaMatijana JergovićVeterinary Research Institute, Brno, Czech RepublicRenáta KarpíškováCentre de Recherche en Sciences Naturelles de Lwiro (CRSN-LWIRO), Bukavu, Democratic Republic of CongoZozo Nyarukweba DeogratiasBIOFOS A/S, Copenhagen K, DenmarkBodil ElsborgTechnical University of Denmark, Kgs., Lyngby, DenmarkLisbeth Truelstrup Hansen & Pernille Erland JensenSuez Canal University, Ismailia, EgyptMohamed AbouelnagaUniversity of Sadat City, Sadat City, EgyptMohamed Fathy SalemMinistry of Health, Environmental Microbiology, Tallinn, EstoniaMarliin KoolmeisterAddis Ababa University, Addis Ababa, EthiopiaMengistu Legesse & Tadesse EgualeUniversity of Helsinki, Helsinki, FinlandAnnamari HeikinheimoFrench Institute Search Pour L’exploitation De La Mer (Ifremer), Nantes, FranceSoizick Le Guyader & Julien SchaefferInstituto Nacional de Investigaciσn en Salud Pϊblica-INSPI (CRNRAM), Galαpagos, Quito, EcuadorJose Eduardo VillacisNational Public Health Laboratories, Ministry of Health and Social Welfare, Kotu, GambiaBakary SannehNational Center for Disease Control and Public Health, Tbilisi, GeorgiaLile MalaniaRobert Koch Institute, Berlin, GermanyAndreas Nitsche & Annika BrinkmannTechnische Universitδt Dresden, Institute of Hydrobiology, Dresden, GermanySara Schubert, Sina Hesse & Thomas U. BerendonkUniversity for Development Studies, Tamale, GhanaCourage Kosi Setsoafia SabaUniversity of Ghana, Accra, GhanaJibril MohammedKwame Nkrumah University of Science and Technology, Kumasi, PMB, GhanaPatrick Kwame FegloCouncil for Scientific and Industrial Research Water Research Institute, Accra, GhanaRegina Ama BanuVeterinary Research Institute of Thessaloniki, Hellenic Agricultural Organisation-DEMETER, Thermi, GreeceCharalampos KotzamanidisAthens Water Supply and Sewerage Company (EYDAP S.A.), Athens, GreeceEfthymios LytrasUniversidad de San Carlos de Guatemala, Guatemala City, GuatemalaSergio A. LickesSemmelweis University, Institute of Medical Microbiology, Budapest, HungaryBela KocsisUniversity of Veterinary Medicine, Budapest, HungaryNorbert SolymosiUniversity of Iceland, Reykjavνk, IcelandThorunn R. ThorsteinsdottirCochin University of Science and Technology, Cochin, IndiaAbdulla Mohamed HathaKasturba Medical College, Manipal, IndiaMamatha BallalApollo Diagnostics, Mangalore, IndiaSohan Rodney BangeraShiraz University of Medical Sciences, Shiraz, IranFereshteh FaniShahid Beheshti University of Medical Sciences, Tehran, IranMasoud AlebouyehNational University of Ireland Galway, Galway, IrelandDearbhaile Morris, Louise O’Connor & Martin CormicanBen Gurion University of the Negev and Ministry of Health, Beer-Sheva, IsraelJacob Moran-GiladIstituto Zooprofilattico Sperimentale del Lazio e della Toscana, Rome, ItalyAntonio Battisti, Elena Lavinia Diaconu & Patricia AlbaCNR – Water Research Institute, Verbania, ItalyGianluca Corno & Andrea Di CesareNational Institute of Infectious Diseases, Tokyo, JapanJunzo Hisatsune, Liansheng Yu, Makoto Kuroda, Motoyuki Sugai & Shizuo KayamaNational Center of Expertise, Taldykorgan, KazakhstanZeinegul ShakenovaMount Kenya University, Thika, KenyaCiira KiiyukiaKenya Medical Research Institute, Nairobi, KenyaEric Ng’enoUniversity of Prishtina “Hasan Prishtina” & National Institute of Public Health of Kosovo, Pristina, KosovoLul RakaKuwait Institute for Scientific Research, Kuwait City, KuwaitKazi Jamil, Saja Adel Fakhraldeen & Tareq AlaatiInstitute of Food Safety, Riga, LatviaAivars Bērziņš, Jeļena Avsejenko, Kristina Kokina, Madara Streikisa & Vadims BartkevicsAmerican University of Beirut, Beirut, LebanonGhassan M. MatarCentral Michigan University & Michigan Health Clinics, Saginaw, MI, USAZiad DaoudNational Food and Veterinary Risk Assessment Institute, Vilnius, LithuaniaAsta Pereckienė & Ceslova Butrimaite-AmbrozevicieneLuxembourg Institute of Science and Technology, Belvaux, LuxembourgChristian PennyInstitut Pasteur de Madagascar, Antananarivo, MadagascarAlexandra Bastaraud & Jean-Marc CollardUniversity of Antananarivo, Centre d’Infectiologie Charles Mιrieux, Antananarivo, MadagascarTiavina Rasolofoarison, Luc Hervé Samison & Mala Rakoto AndrianariveloUniversity of Malawi, Blantyre, MalawiDaniel Lawadi BandaMalaysian Genomics Resource Centre Berhad, Kuala Lumpur, MalaysiaArshana AminAIMST University, COMBio, Kedah, MalaysiaHeraa Rajandas & Sivachandran ParimannanWater Services Corporation, Luqa, MaltaDavid SpiteriEnvironmental Health Directorate, St. Venera, MaltaMalcolm Vella HaberUniversity of Mauritius, Reduit, MauritiusSunita J. SantchurnInstitute for Public Health Montenegro, Podgorica, MontenegroAleksandar Vujacic & Dijana DjurovicInstitut Pasteur du Maroc, Casablanca, MoroccoBrahim Bouchrif & Bouchra KarraouanCentro de Investigaηγo em Saϊde de Manhiηa (CISM), Maputo, MozambiqueDelfino Carlos VubilAgriculture and Forestry University, Kathmandu, NepalPushkar PalNational Institute for Public, Health and the Environment (RIVM), Bilthoven, The NetherlandsHeike Schmitt & Mark van PasselUniversity of Otago, Dunedin, New ZealandGert-Jan Jeunen & Neil GemmellUniversity of Otago, Christchurch, New ZealandStephen T. ChambersUniversity of Central America, Managua, NicaraguaFania Perez Mendoza & Jorge Huete-PιrezUniversidad Nacional Autσnoma de Nicaragua-Leσn, Leσn, NicaraguaSamuel VilchezUniversity of Ilorin, Ilorin, NigeriaAkeem Olayiwola Ahmed, Ibrahim Raufu Adisa & Ismail Ayoade OdetokunUniversity of Ibadan, Ibadan, NigeriaKayode FashaeNorwegian Institute of Public Health, Oslo, NorwayAnne-Marie Sørgaard & Astrid Louise WesterVEAS, Slemmestad, NorwayPia Ryrfors & Rune HolmstadUniversity of Agriculture, Faisalabad, PakistanMashkoor MohsinAga Khan University, Karachi, PakistanRumina Hasan & Sadia ShakoorLaboratorio Central de Salud Publica, Asuncion, ParaguayNatalie Weiler Gustafson & Claudia Huber SchillInstituto Nacional de Salud, Lima, PeruMaria Luz Zamudio RojasUniversidad de Piura, Piura, PeruJorge Echevarria Velasquez & Felipe Campos YauceWHO Environmental and Occupational Health, Manila, PhilippinesBonifacio B. 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F. Tay, Rogelio Zuniga-Montanez & Stefan WuertzPublic Health Authority of the Slovak Republic, Bratislava, SlovakiaDagmar Gavačová, Katarína Pastuchová & Peter TruskaNational Laboratory of Health, Environment and Food, Ljubljana, SloveniaMarija TrkovIndependent consultant, Johannesburg, South AfricaKaren KeddyDaspoort Waste Water Treatment Works, Pretoria, South AfricaKerneels EsterhuyseKorea Advanced Institute of Science and Technology, Daejeon, South KoreaMin Joon SongSchool of Veterinary Sciences, Lugo, SpainMarcos Quintela-BalujaLabaqua, Santiago de Compostela, SpainMariano Gomez LopezIRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la Universitat Autonoma de Barcelona, Bellaterra, SpainMarta Cerdà-CuéllarUniversity of Kelaniya, Ragama, Sri LankaR. R. D. P. Perera, N. K. B. K. R. G. W. Bandara & H. I. 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    Strain assessmentWe did not detect any C-strain individual following analysis of 138 fully assembled mitochondrial DNA genomes (mitogenomes) from Australian samples. Our results, particularly that from Northern Territory, are not dissimilar to the finding of Piggott et al.56 who detected only two (i.e., 4.2%) C-strain mtCOI haplotype individuals from a much larger (i.e., n = 48) Northern Territory sample size. Proportions of C-strain to R-strain also varied significantly across the different SEA populations (Table S1) in contrast to the patterns observed in China, India, and African nations (e.g.,22,33,34,39,57). All Australian populations analysed for their corn or rice mitochondrial haplotypes via mitogenome assemblies of whole genome sequencing data therefore contrasted with the invasive populations from SEA where in some countries (e.g., Myanmar, Vietnam) FAW with the C-strain mtCOI haplotypes made up approximately 50% of the populations examined (see Table S1 for C- and R-strains mitogenome proportions, see also Fig. 1 ‘C-strain’ and ‘R-strain’ Maximum Likelihood cladograms).Figure 1Maximum Likelihood cladograms of unique Spodoptera frugiperda C-strain and R-strain partial mitochondrial genomes based on concatenation of the 13 PCGs (11,393 bp) using IQ-Tree with 1000 UFBoot replications. Individuals in clades I, II, III, and IV (C-strain) and in Clades I, II, V (R-strain) that are in the same colour scheme (i.e., green, orange, blue, or pinks) shared 100% nucleotide identity. Mitogenome haplotypes from native individuals for both C- and R-strains are in khaki green colour. Red and dark grey dots at branch nodes represent bootstrap values of 87–100% and 74–86%, respectively. Bootstrap values  Hetexp; see60) could likewise indicate recent mixing of distinct populations from SEA that suggest multiple introductions (e.g.,33,39 cf.46,47,61,62; i.e., due to a recent bottleneck from a recent western Africa founder event).Table 1 Population genetic differentiation via pairwise FST estimates between Spodoptera frugiperda populations from the invasive ranges of Africa (Uganda, Malawi, Benin), South Asia (India), East Asia (China (Cangyuan (CY), Xinping (XP), YuanJiang (YJ)), South Korea), Southeast Asia (Malaysia (Johor, Kedah, Penang States), Laos, Vietnam, Myanmar), and Pacific/Australia (Papua New Guinea (PNG), Australia—Kununurra (Western Australia, WA), Northern Territory (NT), Strathmore, Walkamin, Burdekin, Mackay (Queensland, Qld), Wee Waa (New South Wales, NSW).Full size tableThe observed heterozygosity excess detected in all invasive range populations could be further explained as due to population sub-structure and isolation breaking through periodic migration. Significant numbers of loci (ca. 30%) were also shown to not be in Hardy–Weinberg equilibrium (HWE) especially for the Malaysian (i.e., Kedah), but also Australian (i.e., Wee Waa, NT, Kununurra), Chinese (e.g., XP), South Korean, and Malawian populations. Taken as a whole, genetic diversity results from this study therefore suggested that the invasive Asian (i.e., SA, SEA, EA) FAW populations exhibited signatures of recent mixing of previously separated populations. Simulated patterns of moth migration of various invasive FAW populations such as between Myanmar and China (e.g.,41,42,55) and to Australia54 are incompatible with the population genomic data, which suggests these were likely discrete and non-panmictic FAW populations with the most probable explanation being due to multiple origins of founding populations.Genetic differentiation analysisEstimates of pairwise genetic differentiation (FST) between populations varied significantly (Table 1) and extended to between populations within a country (e.g., Mackay vs. rest of Australia; Kedah vs. rest of Malaysia). Of interest are the pairwise estimates between different Australian FAW populations from Kununurra (Western Australia), Northern Territory, Queensland (Strathmore, Walkamin, Burdekin, Mackay) and New South Wales (Wee Waa) that represented the most recently reported invasive populations in this study, and predominantly showed significant differentiation amongst themselves (with the exception of the two Queensland populations of Mackay and partially for Walkamin) and with other SEA/SA/EA countries. The majority of non-significant population genetic differentiation estimates were in SEA where the presence of FAW was reported earlier, i.e., since 2018 (e.g.,63,64 or as early as 200865,66; see also33), while across Asia (e.g., China) since 2016 but also potentially pre-2014 (16,67; see also33).Interestingly, significant genetic differentiation was observed between populations from Yunnan province in China and populations from Myanmar, Laos, and Vietnam. Penang and Johor (Malaysia) populations were not significantly differentiated from other SE Asian populations, nor with Ugandan and Malawian populations from east Africa. Individuals from Benin and Mackay (Queensland, Australia) showed non-significant genetic differentiation with all populations except with Kedah, and for Mackay also surprisingly with the Wee Waa population from New South Wales. The South Korean population exhibited significant genetic differentiation with SE Asian population except with Mackay, India and the Yuanjiang (YJ) population in Yunnan Province. Finally, the Kedah population, being one of the earliest collected samples from Malaysia and having been maintained as a laboratory population, showed strong differentiation with all populations (and lowest nucleotide diversity, π = 0.237; Table 2) further supporting unique, non-African, introduction events in SEA. Strong genetic differentiation suggested there was limited gene flow to breakdown sub-structure between populations, and the FST estimates from these invasive populations therefore failed to support a west-to-east spread pathway for the FAW. This observation instead suggested the widespread presence of genetically distinct FAW populations, likely due to independent introductions and therefore also highlighting likely biosecurity weaknesses especially in East Asia (e.g., China, South Korea) and SEA (e.g., Malaysia).Table 2 Population statistics for Spodoptera frugiperda populations from Southeast Asia (i.e., Malaysia (MYS; Johor, Kedah, Penang), Laos, Vietnam, Myanmar), East Asia (i.e., South Korea), and Pacific/Australia (i.e., Papua New Guinea (PNG), Australia).Full size tableThe genetic diversity of Australian populations identified surprisingly complex sub-structure patterns given the short time frame of population detections across different northern Australian regions. Significant genetic differentiation between, e.g., Kununurra (WA), Northern Territory (NT), Queensland (e.g., Strathmore, Burdekin), and Wee Waa (NSW) populations suggests these populations likely derived from separate establishment events. The WA Kununurra population was not significantly differentiated from the Johor State (Malaysia), India and the Cangyuan (CY) China populations, suggesting a potential south-eastern route from SA/SEA into north-western Australia. Contrasting this, Walkamin and Mackay populations showed non-significant genetic differentiation with the Madang (PNG) population, suggesting a potential second pathway for SEA individuals to arrive at the north-eastern region of Australia. Significant genetic differentiation between WA, NT, and Qld populations suggested that at least during the early stage of pest establishment in northern Australia, there was limited gene flow to homogenise the unique genetic background carried by these distinct individuals, some of which exhibited also distinct insecticide resistance profiles48,49.PCAWe selected specific populations to compare using Principal Component Analysis (PCA) as examples to support evidence of independent introductions, as seen from Fig. 3a between China (CY, YJ, XP) populations vs. Myanmar, in Fig. 3b (within Malaysian populations between those collected from Penang and Johor States vs. Kedah State), in Fig. 3c for between China and East Africa (e.g., Uganda, Malawi), and where Benin and India individuals that grouped with either China or east Africa; and in Fig. 3d between China, Malaysia (Kedah State), and Australia (NT, NSW)). Genetic variability between Australian populations (e.g., Strathmore (QLD) vs. NT and NSW) was also evident (Fig. 3d).Figure 3Principal component analysis (PCA) showing variability between selected FAW populations from their invasive ranges. (a) China and Myanmar; (b) Kedah and Johor/Penang populations from Malaysia, (c) China and east African (Uganda/Malawi) populations, (d) Australia (Strathmore, Qld/Northern Territory + New South Wales), China, and Malaysia (Kedah) populations, (e) Australia (Strathmore, Qld) and PNG (Madang Province) populations, (f) Lao PDR/Vietnam and South Korea populations, (g) China and SE Asian (Lao PDR/Vietnam/Myanmar/Philippines/Malaysia) and Pacific/Australia (PNG) populations, and (h) Australia, China and Malaysia (Kedah) populations. Note the overall population genomic variability between countries (e.g., a, c–g) and within countries (e.g., Malaysia (b), Australia (d)). Populations with similar genomic variability are also evident, e.g., for Strathmore (e) and South Korea (f); and for Madang (e) and Lao PDR/Vietnam (f), further supporting potential different population origins of various FAW populations across the current invasive regions. The Southeast Asian and Chinese populations are overall different (g), Australia’s FAW populations showed similarity with both Southeast Asia and China (g, h).Full size imagePCA also showed that differences existed between FAW populations from the Madang Province in PNG and with the Strathmore population from Qld (Fig. 3e). The SEA FAW populations from Lao PDR/Vietnam also exhibited diversity from the South Korean population (Fig. 3f), with the South Korean and Strathmore populations largely exhibiting similar diversity patterns, while the Madang population shared similarity with Laos and Vietnam populations. Plotting all SEA populations against China clearly showed that populations from SEA were distinct from the Chinese FAW populations (Fig. 3g), while in Australia, individuals from various populations shared similarity with both Chinese and SEA FAW. Despite the connectedness of the landscape between SEA and China, SEA largely appeared to have their own FAW populations, with FAW in SEA and in China differing in their genome compositions overall as shown via PCA.PCA further enabled visualisation of genetic diversity amongst Australia FAW populations, suggesting that arrival and establishment of FAW likely involved separate introduction events that followed closely after each other and over a short timeframe. While it had been anticipated that the southward spread of FAW from SEA would necessarily lead to Australia FAW and PNG FAW to share similar genetic backgrounds, the Madang Province FAW population appeared to be different from the Strathmore (Qld) population, with the Madang population being more similar to Lao PDR/Vietnam populations, and the Strathmore population more similar to FAW from South Korea.DivMigrate analysisDirectionality of gene flow between African, South Asia (Indian), East Asia (China) and SE Asian populations were predominantly from China to east African and SE Asian populations (e.g., Figs. 4a, b, S-1; see also Table 3), while movements of FAW in Laos and Vietnam (i.e., the Indochina region) were predominantly with other SEA countries (e.g., with Myanmar and East Africa; Figs. 4c, d, S-2; see also Table 3) but with no directional movements to the three Yunnan populations (CY, XP, YJ). Migration directionality with other SE Asian populations (e.g., Johor (JB; Fig. S-3) and Penang (PN, Fig. S-4)) showed that these two populations (but especially the Johor population) were predominantly source populations for Uganda, Malawi, Philippines, Vietnam, and PNG (Fig. S-3). Bidirectional migration between Myanmar and Laos PDR populations were also detected with the Johor population from Malaysia (Fig. S-3). When India was selected as the source population, bidirectional migration events were detected with Myanmar and with the Cangyuan (CY) populations (Fig. S-5) while unidirectional migration events from India to Uganda and Malawi and to Laos were detected, and the China Yuanjian (YJ) population showed unidirectional migration to India. Unidirectional migration events from CY and YJ populations to the PNG Madang population were detected, while bidirectional migration events between PNG and Myanmar, Laos PDR, Philippines, Vietnam, and with Uganda and Malawi were also detected (Fig. S-6). No migration events were detected between the West African Benin population and with the South Korean population.Figure 4Source populations are CY (a) and XP (b). (c, d) DivMigrate analyses with edge weight setting at 0.453 showing unidirectional (yellow arrow lines) and bidirectional (blue arrow lines) migration between countries in Africa and South Asia/East Asia/SE Asia. Migration rates between populations are as provided in Table 3. (c) Vietnam (VNM) as the source population identified an incidence of unidirectional migration from Malaysia (MYS) Johor state (JB) to Vietnam, while bidirectional migration events were detected from Vietnam to other SE Asian (e.g., Philippines (PHL), Lao PDR (Lao), Myanmar (MMR)), to Pacific/Australia (i.e., Papua New Guinea (PNG)), as well as to east Africa (Uganda (UGA), Malawi (MWI)). (d) Lao PDR (LAO) as source population identified bidirectional migration events between various SEA populations and east African populations, while unidirectional migration events were identified from India (IND) and China (CHN) Yunnan populations (CY, YJ) to Laos PDR. No migration events were evident from SE Asian populations to China.(a, b) DivMigrate analyses with edge weight setting at 0.453 showing unidirectional (yellow arrow lines) and bidirectional (blue arrow lines) gene flow between countries in Africa and South Asia/East Asia/SE Asia. Significant migration rates (at alpha = 0.5) are in red and as provided in Table 3. Incidences of unidirectional migration were predominantly detected from China (CHN) Yunnan populations (CY, XP) to SE Asian populations (e.g., Myanmar (MMR), Laos PDR (Lao), Philippines (PHL)) and to east African populations (e.g., Uganda (UGA), Malawi (MWI)) (a, b).Full size imageTable 3 DivMigrate matrix showing effective migration rates calculated using GST from source to target invasive populations.Full size tableAdmixture analysisAdmixture analyses involving all Australian, Southeast Asian and South Korean populations from this study; and native populations from the Americas and Caribbean Islands, and invasive populations from Africa (Benin, Uganda, Malawi), India, and China33, provided an overall complex picture of population structure that reflected the species’ likely introduction histories across its invasive ranges.Admixture analysis that excluded New World, African and Indian populations identified four genetic clusters (i.e., K = 4) to best describe these invasive populations from SEA, and EA (i.e., China, South Korea), and Pacific/Australia (Fig. 5a). At K = 4, Australian populations from NT and NSW, YJ population from China, South Korean, and Malaysia’s Kedah population, each showed unique admixture patterns (i.e., some individuals from NT and NSW populations lacked cluster 3; most of YJ (but also some CY and XP) individuals lacked clusters 1 and 2; South Korean (e.g., MF individuals) lacked cluster 2; Malaysia’s Kedah population lacked evidence of admixture (i.e., reflecting its laboratory culture history) and was made up predominantly by individuals that belonged to cluster 4. Populations from China also differed from most populations from SEA due to the overall absence of genetic cluster 4. Taken as a whole, establishment of the FAW populations in China, Malaysia, vs. other SE Asian populations, and between Australian populations (e.g., NT/NSW cf. WA/Qld), likely involved individuals from diverse genetic background (i.e., multiple introductions). At K = 4, the majority of Australian populations appeared to contain genetic clusters similar to China (i.e., cluster 3) and to SEA (i.e., cluster 2).Figure 5Admixture and corresponding CV plots for FAW populations from: (a) Australia, China, South Korea, Lao PDR, Myanmar, Malaysia, Philippines, PNG, and Vietnam, and (b) Benin, China, India, South Korea, Lao PDR, Myanmar, Malaysia, Philippines, PNG, Tanzania, and Vietnam. Optimal ancestral genetic clusters are K = 4 for both admixture plots. Boxed individuals have unique admixture patterns at K = 4 when compared with other populations. China FAW lacked Cluster 2 (navy blue colour; present in almost all SEA and Australian FAW), while in NSW and NT some individuals lacked cluster 3. South Korea ‘MF’ population generally lacked cluster 2, while Kedah (Malaysia) showed distinct (cluster 4) pattern for all individuals. The overall same observations are evident in the admixture plot in (b), with African FAW generally exhibiting admixture patterns similar to SEA populations than to Chinese FAW. With the exception of Kedah (Malaysia) and some Chinese FAW individuals, all FAW in the invasive range showed evidence of genomic admixture (i.e., hybrid signature). The figures were generated using the POPHELPER program  and further manipulated in Microsoft PowerPoint for Mac v16.54.Full size imageOverall admixture patterns at best K = 4 in China and SEA remained unchanged when analysed together with African and Indian individuals (Fig. 5b; excluded Australia). Benin individuals were either similar to China or to SEA, while eastern African populations (e.g., Uganda, Malawi) were similar to Southeast Asian populations from e.g., Vietnam, Laos, and is in agreement with the phylogenetic inference (Fig. 3) that identified these African individuals as having loci that were derived from Southeast Asian populations.Genome-wide SNP loci demonstrated that invasive FAW populations from SEA and Australia exhibited admixed genomic signatures similar to that observed in other invasive populations33,34. While the current invasive populations in Africa and Asia likely arrived already as hybrids as suggested by Yainna et al.68, the Malaysia Kedah State population was potentially established by offspring of a non-admixed female. Distinct admixture patterns in Malaysian FAW populations between Kedah and Johor/Penang states therefore suggested that establishment of these populations was likely as separate introduction events. As reported also in Tay et al.33, the Chinese YJ population appeared to have admixed signature that differed from XP and CY populations, and suggested that the YJ population could have a different introduction history than the XP and CY populations. Similar multiple genetic signatures based on lesser nuclear markers by Jiang et al.39 also supported likely multiple introductions of China Yunnan populations. More

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