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Cui J, Chen Y, Hines HM, Ma L, Yang W, Wang C, Liu S, Li H, Cai W, Da W, Williams P, Tian L. Does coevolution in refugia drive mimicry in bumble bees? Insights from a South Asian mimicry group. SCIENCE ADVANCES 2024; 10:eadl2286. [PMID: 38865449 PMCID: PMC11168453 DOI: 10.1126/sciadv.adl2286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 05/09/2024] [Indexed: 06/14/2024]
Abstract
Müllerian mimicry was proposed to be an example of a coevolved mutualism promoted by population isolation in glacial refugia. This, however, has not been well supported in butterfly models. Here, we use genomic data to test this theory while examining the population genetics behind mimetic diversification in a pair of co-mimetic bumble bees, Bombus breviceps Smith and Bombus trifasciatus Smith. In both lineages, populations were structured by geography but not as much by color pattern, suggesting sharing of color alleles across regions of restricted gene flow and formation of mimicry complexes in the absence of genetic differentiation. Demographic analyses showed mismatches between historical effective population size changes and glacial cycles, and niche modeling revealed only mild habitat retraction during glaciation. Moreover, mimetic subpopulations of the same color form in the two lineages only in some cases exhibit similar population history and genetic divergence. Therefore, the current study supports a more complex history in this comimicry than a simple refugium-coevolution model.
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Affiliation(s)
- Jixiang Cui
- Department of Entomology, College of Plant Protection, China Agricultural University, Beijing, China
- MOA Key Lab of Pest Monitoring and Green Management, College of Plant Protection, China Agricultural University, Beijing, China
| | - Yuxin Chen
- Department of Entomology, College of Plant Protection, China Agricultural University, Beijing, China
- MOA Key Lab of Pest Monitoring and Green Management, College of Plant Protection, China Agricultural University, Beijing, China
| | - Heather M. Hines
- Department of Biology, The Pennsylvania State University, University Park, PA, USA
| | - Ling Ma
- Department of Entomology, College of Plant Protection, China Agricultural University, Beijing, China
- MOA Key Lab of Pest Monitoring and Green Management, College of Plant Protection, China Agricultural University, Beijing, China
| | - Wanhu Yang
- Department of Entomology, College of Plant Protection, China Agricultural University, Beijing, China
- MOA Key Lab of Pest Monitoring and Green Management, College of Plant Protection, China Agricultural University, Beijing, China
| | - Chao Wang
- Department of Entomology, College of Plant Protection, China Agricultural University, Beijing, China
- MOA Key Lab of Pest Monitoring and Green Management, College of Plant Protection, China Agricultural University, Beijing, China
| | - Shanlin Liu
- Department of Entomology, College of Plant Protection, China Agricultural University, Beijing, China
- MOA Key Lab of Pest Monitoring and Green Management, College of Plant Protection, China Agricultural University, Beijing, China
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Hu Li
- Department of Entomology, College of Plant Protection, China Agricultural University, Beijing, China
- MOA Key Lab of Pest Monitoring and Green Management, College of Plant Protection, China Agricultural University, Beijing, China
| | - Wanzhi Cai
- Department of Entomology, College of Plant Protection, China Agricultural University, Beijing, China
- MOA Key Lab of Pest Monitoring and Green Management, College of Plant Protection, China Agricultural University, Beijing, China
| | - Wa Da
- Tibet Plateau Institute of Biology, Lhasa, Tibet 850001, China
- Medog Biodiversity Observation and Research Station of Xizang Autonomous Region, Tibet, China
| | - Paul Williams
- Department of Life Sciences, Natural History Museum, London SW7 5BD, UK
| | - Li Tian
- Department of Entomology, College of Plant Protection, China Agricultural University, Beijing, China
- MOA Key Lab of Pest Monitoring and Green Management, College of Plant Protection, China Agricultural University, Beijing, China
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Salgado-Roa FC, Pardo-Diaz C, Rueda-M N, Cisneros-Heredia DF, Lasso E, Salazar C. The Andes as a semi-permeable geographical barrier: Genetic connectivity between structured populations in a widespread spider. Mol Ecol 2024; 33:e17361. [PMID: 38634856 DOI: 10.1111/mec.17361] [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: 01/16/2024] [Revised: 04/03/2024] [Accepted: 04/09/2024] [Indexed: 04/19/2024]
Abstract
Geographical barriers like mountain ranges impede genetic exchange among populations, promoting diversification. The effectiveness of these barriers in limiting gene flow varies between lineages due to each species' dispersal modes and capacities. Our understanding of how the Andes orogeny contributes to species diversification comes from well-studied vertebrates and a few arthropods and plants, neglecting organisms unable to fly or walk long distances. Some arachnids, such as Gasteracantha cancriformis, have been hypothesized to disperse long distances via ballooning (i.e. using their silk to interact with the wind). Yet, we do not know how the environment and geography shape its genetic diversity. Therefore, we tested whether the Andes contributed to the diversification of G. cancriformis acting as an absolute or semi-permeable barrier to genetic connectivity between populations of this spider at opposite sides of the mountain range. We sampled thousands of loci across the distribution of the species and implemented population genetics, phylogenetic, and landscape genetic analyses. We identified two genetically distinct groups structured by the Central Andes, and a third less structured group in the Northern Andes that shares ancestry with the previous two. This structure is largely explained by the altitude along the Andes, which decreases in some regions, possibly facilitating cross-Andean dispersal and gene flow. Our findings support that altitude in the Andes plays a major role in structuring populations in South America, but the strength of this barrier can be overcome by organisms with long-distance dispersal modes together with altitudinal depressions.
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Affiliation(s)
- Fabian C Salgado-Roa
- Department of Biology, Faculty of Natural Sciences, Universidad del Rosario, Bogotá, Colombia
- School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Carolina Pardo-Diaz
- Department of Biology, Faculty of Natural Sciences, Universidad del Rosario, Bogotá, Colombia
| | - Nicol Rueda-M
- Department of Biology, Faculty of Natural Sciences, Universidad del Rosario, Bogotá, Colombia
| | - Diego F Cisneros-Heredia
- Colegio de Ciencias Biológicas y Ambientales, Instituto de Biodiversidad Tropical IBIOTROP, Laboratorio de Zoología Terrestre, Museo de Zoología & Extensión USFQ Galápagos GAIAS, Galapagos Science Center, Universidad San Francisco de Quito USFQ, Quito, Ecuador
| | - Eloisa Lasso
- Department of Biological Sciences, Universidad de los Andes, Bogotá, Colombia
- Smithsonian Tropical Research Institute, Panama, Republic of Panama
- Estación Científica Coiba AIP, Panama, Republic of Panama
| | - Camilo Salazar
- Department of Biology, Faculty of Natural Sciences, Universidad del Rosario, Bogotá, Colombia
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Jiao X, Wu L, Zhang D, Wang H, Dong F, Yang L, Wang S, Amano HE, Zhang W, Jia C, Rheindt FE, Lei F, Song G. Landscape Heterogeneity Explains the Genetic Differentiation of a Forest Bird across the Sino-Himalayan Mountains. Mol Biol Evol 2024; 41:msae027. [PMID: 38318973 PMCID: PMC10919924 DOI: 10.1093/molbev/msae027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 01/26/2024] [Accepted: 01/31/2024] [Indexed: 02/07/2024] Open
Abstract
Mountains are the world's most important centers of biodiversity. The Sino-Himalayan Mountains are global biodiversity hotspot due to their extremely high species richness and endemicity. Ample research investigated the impact of the Qinghai-Tibet Plateau uplift and Quaternary glaciations in driving species diversification in plants and animals across the Sino-Himalayan Mountains. However, little is known about the role of landscape heterogeneity and other environmental features in driving diversification in this region. We utilized whole genomes and phenotypic data in combination with landscape genetic approaches to investigate population structure, demography, and genetic diversity in a forest songbird species native to the Sino-Himalayan Mountains, the red-billed leiothrix (Leiothrix lutea). We identified 5 phylogeographic clades, including 1 in the East of China, 1 in Yunnan, and 3 in Tibet, roughly consistent with differences in song and plumage coloration but incongruent with traditional subspecies boundaries. Isolation-by-resistance model best explained population differentiation within L. lutea, with extensive secondary contact after allopatric isolation leading to admixture among clades. Ecological niche modeling indicated relative stability in the extent of suitable distribution areas of the species across Quaternary glacial cycles. Our results underscore the importance of mountains in the diversification of this species, given that most of the distinct genetic clades are concentrated in a relatively small area in the Sino-Himalayan Mountain region, while a single shallow clade populates vast lower-lying areas to the east. This study highlights the crucial role of landscape heterogeneity in promoting differentiation and provides a deep genomic perspective on the mechanisms through which diversity hotspots form.
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Affiliation(s)
- Xiaolu Jiao
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Lei Wu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Dezhi Zhang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Huan Wang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Feng Dong
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Le Yang
- Tibet Plateau Institute of Biology, Lhasa 850000, China
| | - Shangyu Wang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | | | - Weiwei Zhang
- Center for Wildlife Resources Conservation Research, Jiangxi Agricultural University, Nanchang, China
| | - Chenxi Jia
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Frank E Rheindt
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Fumin Lei
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Gang Song
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
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López WR, Altamiranda-Saavedra M, Kehl SD, Ferro I, Bellomo C, Martínez VP, Simoy MI, Gil JF. Modeling potential risk areas of Orthohantavirus transmission in Northwestern Argentina using an ecological niche approach. BMC Public Health 2023; 23:1236. [PMID: 37365559 DOI: 10.1186/s12889-023-16071-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 06/07/2023] [Indexed: 06/28/2023] Open
Abstract
BACKGROUND Hantavirus Pulmonary Syndrome (HPS) is a rodent-borne zoonosis in the Americas, with up to 50% mortality rates. In Argentina, the Northwestern endemic area presents half of the annually notified HPS cases in the country, transmitted by at least three rodent species recognized as reservoirs of Orthohantavirus. The potential distribution of reservoir species based on ecological niche models (ENM) can be a useful tool to establish risk areas for zoonotic diseases. Our main aim was to generate an Orthohantavirus risk transmission map based on ENM of the reservoir species in northwest Argentina (NWA), to compare this map with the distribution of HPS cases; and to explore the possible effect of climatic and environmental variables on the spatial variation of the infection risk. METHODS Using the reservoir geographic occurrence data, climatic/environmental variables, and the maximum entropy method, we created models of potential geographic distribution for each reservoir in NWA. We explored the overlap of the HPS cases with the reservoir-based risk map and a deforestation map. Then, we calculated the human population at risk using a census radius layer and a comparison of the environmental variables' latitudinal variation with the distribution of HPS risk. RESULTS We obtained a single best model for each reservoir. The temperature, rainfall, and vegetation cover contributed the most to the models. In total, 945 HPS cases were recorded, of which 97,85% were in the highest risk areas. We estimated that 18% of the NWA population was at risk and 78% of the cases occurred less than 10 km from deforestation. The highest niche overlap was between Calomys fecundus and Oligoryzomys chacoensis. CONCLUSIONS This study identifies potential risk areas for HPS transmission based on climatic and environmental factors that determine the distribution of the reservoirs and Orthohantavirus transmission in NWA. This can be used by public health authorities as a tool to generate preventive and control measures for HPS in NWA.
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Affiliation(s)
- Walter R López
- Instituto de Investigaciones de Enfermedades Tropicales (IIET), Universidad Nacional de Salta (UNSa), Sede Regional Orán, A4400, Salta, Argentina
| | - Mariano Altamiranda-Saavedra
- Grupo de Investigación Bioforense, Facultad de Derecho Y Ciencias Forenses, Tecnológico de Antioquia Institución Universitaria, Antioquia, Colombia
| | - Sebastián D Kehl
- Instituto Nacional de Enfermedades Infecciosas (INEI), Administración Nacional de Laboratorios E Institutos de Salud (ANLIS) "Dr. C. G. Malbrán", Buenos Aires, Argentina
| | - Ignacio Ferro
- Instituto de Ecorregiones Andinas (INECOA), Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), Universidad Nacional de Jujuy (UNJu), San Salvador de Jujuy, Argentina
| | - Carla Bellomo
- Instituto Nacional de Enfermedades Infecciosas (INEI), Administración Nacional de Laboratorios E Institutos de Salud (ANLIS) "Dr. C. G. Malbrán", Buenos Aires, Argentina
| | - Valeria P Martínez
- Instituto Nacional de Enfermedades Infecciosas (INEI), Administración Nacional de Laboratorios E Institutos de Salud (ANLIS) "Dr. C. G. Malbrán", Buenos Aires, Argentina
| | - Mario I Simoy
- Instituto de Investigaciones en Energía No Convencional (INENCO), Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), Universidad Nacional de Salta (UNSa), A4400, Salta, Argentina
- Instituto Multidisciplinario Sobre Ecosistemas Y Desarrollo Sustentable (UNCPBA - CICPBA), Tandil, Argentina
| | - José F Gil
- Instituto de Investigaciones de Enfermedades Tropicales (IIET), Universidad Nacional de Salta (UNSa), Sede Regional Orán, A4400, Salta, Argentina.
- Instituto de Investigaciones en Energía No Convencional (INENCO), Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), Universidad Nacional de Salta (UNSa), A4400, Salta, Argentina.
- Cátedra de Química Biológica Y Biología Molecular de La Facultad de Ciencias Naturales, Universidad Nacional de Salta, A4400, Salta, Argentina.
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