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Anopheles (Kerteszia) cruzii, the main malaria vector in the Brazilian Atlantic Forest, is a complex of at least five cryptic species
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  • Published: 25 February 2026

Anopheles (Kerteszia) cruzii, the main malaria vector in the Brazilian Atlantic Forest, is a complex of at least five cryptic species

  • Kamila Voges  ORCID: orcid.org/0000-0003-1375-99161,
  • Guilherme de Rezende Dias2,
  • Eduardo Guimarães Dupim  ORCID: orcid.org/0000-0003-2540-71843,
  • André Nóbrega Pitaluga4,5,
  • Thyago Vanderlinde2,
  • Carlos José de Carvalho Pinto5,6,
  • Helder Ricas Rezende7,
  • Fabiana Uno2,
  • Sarah Jayne Forrester  ORCID: orcid.org/0000-0001-8332-71968,
  • James Chong  ORCID: orcid.org/0000-0001-9447-74218,
  • A. Bernardo Carvalho  ORCID: orcid.org/0000-0001-8959-64692,5 na1 &
  • …
  • Luísa D. P. Rona  ORCID: orcid.org/0000-0002-3400-39501,5 na1 

Communications Biology , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Evolutionary genetics
  • Genome
  • Population genetics

Abstract

Malaria, a tropical disease caused by Plasmodium and transmitted by Anopheles, remains a public health concern in Brazil. While most cases occur in the Amazon, transmission persists in the Atlantic Forest, where Anopheles mosquitoes of the Kerteszia subgenus are the primary vectors of human and simian malaria. Previous studies using cytogenetics, isoenzymes, and molecular markers have suggested cryptic species within Anopheles (Kerteszia) cruzii and Anopheles (Kerteszia) bellator. We sequenced 55 genomes: 35 An. cruzii s.l. (four with Nanopore and 31 with Illumina), 12 An. bellator s.l., and eight An. homunculus, the latter two with Illumina. Phylogenomic analysis revealed at least five cryptic species within An. cruzii s.l., labelled A-E, with evidence of sympatry in some locations. Anopheles bellator s.l. also forms a species complex, comprising at least three distinct lineages. These cryptic species showed high genetic differentiation (FST range: 0.4-0.7), typical of interspecific comparisons. In contrast, An. homunculus populations showed low differentiation (FST ~ 0.2), suggesting a single widespread species. Our analysis confirms cryptic speciation in An. cruzii and An. bellator, but not in An. homunculus. These findings are important for understanding malaria transmission in the Atlantic Forest, given that vector competence may differ among cryptic species.

Data availability

Accession numbers for the samples are available in the NCBI SRA under BioProject PRJNA1269491. Illumina-sequenced samples correspond to accessions SAMN48789258-SAMN48789358, and Nanopore-sequenced samples correspond to accessions SAMN48793262-SAMN48793265. The genes used to generate Fig. 1 and Supplementary Fig. 5 correspond to those annotated by BUSCO v4.1.4 using the Diptera reference set (odb10), downloaded from the BUSCO database (https://busco.ezlab.org/). Details of the phylogenomic analyses are provided in the script “phylogenomic_inferences” available at https://doi.org/10.5281/zenodo.18389048. The data used to generate Figs. 2, 3, and 7, as well as Supplementary Fig. 6, are provided in Supplementary Data 2.

Code availability

The code used for data analysis can be accessed at the following GitHub repository: https://github.com/kamilavoges/Phylogenomics_Kerteszia116.

References

  1. WHO. World Malaria Report 2023 (WHO, 2023).

  2. de Pina-Costa, A. et al. Malaria in Brazil: What happens outside the Amazonian endemic region. Mem. Inst. Oswaldo Cruz 109, 618–633 (2014).

    Google Scholar 

  3. Carlos, B. C., Rona, L. D. P., Christophides, G. K. & Souza-Neto, J. A. A comprehensive analysis of malaria transmission in Brazil. Pathog. Glob. Health 113, 1–13 (2019).

    Google Scholar 

  4. Marrelli, M. T., Malafronte, R. S., Sallum, M. A. M. & Natal, D. Kerteszia subgenus of Anopheles associated with the Brazilian Atlantic rainforest: current knowledge and future challenges. Malar. J. 6, 1–8 (2007).

    Google Scholar 

  5. Benchimol, J. L. & Sá, M. R. Adolpho Lutz, Obra Completa: Febre amarela, malária & protozoologia/Yellow Fever, Malaria & Protozoology. Rio de Janeiro Editora FIOCRUZ 956 (2005).

  6. Deane, L. M. Malaria vectors in Brazil. Mem. Inst. Oswaldo Cruz. 81(Suppl II), 5–14 (1986).

  7. Brasil, P. et al. Outbreak of human malaria caused by Plasmodium simium in the Atlantic Forest in Rio de Janeiro: a molecular epidemiological investigation. Lancet Glob. Health 5, e1038–e1046 (2017).

    Google Scholar 

  8. Consoli, R. A. G. B. & Lourenço de Oliveira, R. Principais Mosquitos de Importância Médica no Brasil. (Editora Fiocruz,1994).

  9. Rachou, R. Anofelinos do Brasil: Comportamento das espécies vetoras de malária. Rev. Bras. Malariol. Doenças Trop. 10, 145–181 (1958).

    Google Scholar 

  10. Gadelha, P. From ‘forest malaria’ to ‘bromeliad malaria’: a case-study of scientific controversy and malaria control. Parassitologia 36, 175–95 (1994).

    Google Scholar 

  11. Ueno, H. M., Forattini, O. P. & Kakitani, I. Vertical and seasonal distribution of Anopheles (Kerteszia) in Ilha Comprida, Southeastern Brazil. Rev. Saude Publica 41, 269–275 (2007).

    Google Scholar 

  12. Medeiros-Sousa, A. R. et al. Effects of anthropogenic landscape changes on the abundance and acrodendrophily of Anopheles (Kerteszia) cruzii, the main vector of malaria parasites in the Atlantic Forest in Brazil. Malar. J. 18, 110 (2019).

    Google Scholar 

  13. Branquinho, M. S. et al. Infection of Anopheles (Kerteszia) cruzii by Plasmodium vivax </i> and Plasmodium vivax variant VK247 in the municipalities of São Vicente and Juquitiba, São Paulo. Rev. Panam. Salud Publica 2, 189–93 (1997).

    Google Scholar 

  14. Duarte, A. M. R. C. et al. Natural infection in anopheline species and its implications for autochthonous malaria in the Atlantic forest in Brazil. Parasit. Vectors 6, 1–6 (2013).

    Google Scholar 

  15. Buery, J. C. et al. Ecological characterisation and infection of Anophelines (Diptera: Culicidae) of the Atlantic Forest in the southeast of Brazil over a 10 year period: has the behaviour of the autochthonous malaria vector changed? Mem. Inst. Oswaldo Cruz 113, 111–118 (2018).

    Google Scholar 

  16. de Oliveira, T. C., Rodrigues, P. T., Duarte, A. M. R. C., Rona, L. D. P. & Ferreira, M. U. Ongoing host-shift speciation in Plasmodium simium. Trends Parasitol. 37, 940–942 (2021).

    Google Scholar 

  17. de Oliveira, T. C. et al. Plasmodium simium: population genomics reveals the origin of a reverse zoonosis. J. Infect. Dis. 224, 1950–1961 (2021).

    Google Scholar 

  18. Buery, J. C. et al. Atlantic forest malaria: a review of more than 20 years of epidemiological investigation. Microorganisms 9, 1–14 (2021).

    Google Scholar 

  19. Yamasaki, T. et al. Detection of etiological agents of malaria in howler monkeys from Atlantic Forests, rescued in regions of São Paulo city, Brazil. J. Med Primatol. 40, 392–400 (2011).

    Google Scholar 

  20. Ramirez, C. C. L. & Dessen, E. M. B. Chromosomal evidence for sibling species of the malaria vector Anopheles cruzii. Genome 43, 143–151 (2000).

    Google Scholar 

  21. Ramirez, C. C. L. & Dessen, E. M. B. Chromosome differentiated populations of Anopheles cruzii: evidence for a third sibling species. Genetica 1, 73–80 (2000).

    Google Scholar 

  22. Carvalho-Pinto, C. J. de & Lourenço-de-Oliveira, R. Isoenzimatic analysis of four Anopheles (Kerteszia) cruzii (Diptera: Culicidae) populations of Brazil. Mem. Inst. Oswaldo Cruz 99, 471–475 (2004).

    Google Scholar 

  23. Rona, L. D., Carvalho-Pinto, C. J., Gentile, C., Grisard, E. C. & Peixoto, A. A. Assessing the molecular divergence between Anopheles (Kerteszia) cruzii populations from Brazil using the timeless gene: Further evidence of a species complex. Malar. J. 8, 1–10 (2009).

    Google Scholar 

  24. Rona, L. D., Carvalho-Pinto, C. J. & Peixoto, A. A. Molecular evidence for the occurrence of a new sibling species within the Anopheles (Kerteszia) cruzii complex in south-east Brazil. Malar. J. 9, 1–9 (2010).

    Google Scholar 

  25. Rona, L. D., Carvalho-Pinto, C. J., Mazzoni, C. J. & Peixoto, A. A. Estimation of divergence time between two sibling species of the Anopheles (Kerteszia) cruzii complex using a multilocus approach. BMC Evol. Biol. 10, 91 (2010).

    Google Scholar 

  26. Rona, L. D., Carvalho-Pinto, C. J. & Peixoto, A. A. Evidence for the occurrence of two sympatric sibling species within the Anopheles (Kerteszia) cruzii complex in southeast Brazil and the detection of asymmetric introgression between them using a multilocus analysis. BMC Evol. Biol. 13, 207 (2013).

    Google Scholar 

  27. De Rezende Dias, G. et al. Cryptic diversity in an Atlantic Forest malaria vector from the mountains of South-East Brazil. Parasit. Vectors 11, 1–11 (2018).

    Google Scholar 

  28. Coluzzi, M., Sabatini, A., Petrarca, V. & Di Deco’, M. A. Chromosomal differentiation and adaptation to human environments in the Anopheles gambiae complex. R. Soc. Trop. Med. Hyg. 73, 483–497 (1979).

  29. Della Torre, A. et al. Speciation within Anopheles gambiae—the glass is half full. Science 298, 115–117 (2002).

    Google Scholar 

  30. Miguel, R. B. et al. Malaria in the state of Rio de Janeiro, Brazil, an Atlantic Forest area: an assessment using the health surveillance service. Mem. Inst. Oswaldo Cruz 109, 634–640 (2014).

    Google Scholar 

  31. Lorenz, C., Patané, J. S. L. & Suesdek, L. Morphogenetic characterisation, date of divergence, and evolutionary relationships of malaria vectors Anopheles cruzii and Anopheles homunculus. Infect. Genet. Evol. 35, 144–152 (2015).

    Google Scholar 

  32. de Carvalho-Pinto, C. J. & Lourenço-de-Oliveira, R. Isoenzymatic analysis of four Anopheles (Kerteszia) bellator Dyar & Knab (Diptera: Culicidae) populations. Mem. Inst. Oswaldo Cruz 98, 1045–1048 (2003).

    Google Scholar 

  33. Voges, K. et al. Novel molecular evidence of population structure in Anopheles (Kerteszia) bellator from Brazilian Atlantic Forest. Mem. Inst. Oswaldo Cruz 114, 1–5 (2019).

    Google Scholar 

  34. Cardoso, J. D. C. et al. New records of Anopheles homunculus in central and Serra do Mar biodiversity corridors of the Atlantic Forest, Brazil. J. Am. Mosq. Control Assoc. 28, 1–5 (2012).

    Google Scholar 

  35. Kajitani, R. et al. Efficient de novo assembly of highly heterozygous genomes from whole-genome shotgun short reads. Genome Res. 24, 1384–1395 (2014).

    Google Scholar 

  36. Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).

    Google Scholar 

  37. Gendrin, M. et al. Two chromosomal reference genome sequences for the malaria mosquito, Anopheles (Nyssorhynchus) darlingi, Root, 1926 from French Guiana and Peru. Wellcome Open Res 10, 187 (2025).

    Google Scholar 

  38. Holt, R. A. et al. The genome sequence of the malaria mosquito Anopheles gambiae. Science 298, 129–149 (2002).

    Google Scholar 

  39. Segerman, B., Ástvaldsson, Á., Mustafa, L., Skarin, J. & Skarin, H. The efficiency of Nextera XT tagmentation depends on G and C bases in the binding motif leading to uneven coverage in bacterial species with low and neutral GC-content. Front. Microbiol. 13, 944770 (2022).

  40. Santos, F. A. B., Lemes, R. B. & Otto, P. A. HW_TEST, a program for comprehensive HARDY-WEINBERG equilibrium testing. Genet. Mol. Biol. 43, e20190380 (2020).

  41. Aragão, M. B. Distribuição geográfica e abundância de espécies de Anopheles (Kerteszia) (Diptera, Culicidae). Rev. Bras. Malariol. Doenças Trop. 16, 73 (1964).

  42. Hey, J. & Pinho, C. Population genetics and objectivity in species diagnosis. Evolution 66, 1413–1429 (2012).

    Google Scholar 

  43. Neafsey, D. E. et al. Highly evolvable malaria vectors: the genomes of 16 Anopheles mosquitoes. Science 347, 1258522 (2015).

  44. Charlesworth, B., Coyne, J. A. & Barton, N. H. The relative rates of evolution of sex chromosomes and autosomes. Am. Nat. 130, 113–146 (1987).

    Google Scholar 

  45. Thornton, K. & Long, M. Rapid divergence of gene duplicates on the Drosophila melanogaster X chromosome. Mol. Biol. Evol. 19, 918–925 (2002).

    Google Scholar 

  46. Meisel, R. P. & Connallon, T. The faster-X effect: integrating theory and data. Trends Genet. 29, 537–544 (2013).

    Google Scholar 

  47. Bechsgaard, J. et al. Evidence for faster X chromosome evolution in spiders. Mol. Biol. Evol. 36, 1281–1293 (2019).

    Google Scholar 

  48. Darolti, I., Fong, L. J. M., Sandkam, B. A., Metzger, D. C. H. & Mank, J. E. Sex chromosome heteromorphism and the Fast-X effect in poeciliids. Mol. Ecol. 32, 4599–4609 (2023).

    Google Scholar 

  49. Lawson, D. J., van Dorp, L. & Falush, D. A tutorial on how not to over-interpret STRUCTURE and ADMIXTURE bar plots. Nat. Commun. 9, 3258 (2018).

    Google Scholar 

  50. Caputo, B. et al. Population genomic evidence of a putative ‘far-west’ African cryptic taxon in the Anopheles gambiae complex. Commun. Biol. 7, 1115 (2024).

  51. Miles, A. et al. Genetic diversity of the African malaria vector anopheles gambiae. Nature 552, 96–100 (2017).

    Google Scholar 

  52. Sallum, M. A. M., Obando, R. G., Carrejo, N. & Wilkerson, R. C. Identification key to the Anopheles mosquitoes of South America (Diptera: Culicidae). III. Male genitalia. Parasit. Vectors 13, 1–23 (2020).

    Google Scholar 

  53. Li, H. Seqtk: a fast and lightweight tool for processing FASTA or FASTQ sequences. (2013).

  54. Cabanettes, F. & Klopp, C. D-GENIES: dot plot large genomes in an interactive, efficient and simple way. PeerJ 6, e4958 (2018).

    Google Scholar 

  55. Tamura, K. et al. Estimating divergence times in large molecular phylogenies. Proc. Natl. Acad. Sci. 109, 19333–19338 (2012).

    Google Scholar 

  56. Tamura, K., Stecher, G. & Kumar, S. MEGA11: molecular evolutionary genetics analysis version 11. Mol. Biol. Evol. 38, 3022–3027 (2021).

    Google Scholar 

  57. Mayden, R. L. A hierarchy of species concepts: the denouement in the saga of the species problem. In Species: the Units of Diversity (Chapman & Hall, 1997).

  58. Queiroz, K. Species concepts and species delimitation. Syst. Biol. 56, 879–886 (2007).

    Google Scholar 

  59. Ridley, M. Evolution. (Blackwell Pub, 2004).

  60. Coyne, J. A., Coyne, H. A. & Orr, H. A. Speciation (Oxford University Press, Incorporated, 2004).

  61. Wright, S. The roles of mutation, inbreeding, crossbreeding and selection in evolution. Proc. XI Int. Congr. Genet. 8, 209–222 (1932).

    Google Scholar 

  62. Mayr, E. Populations, Species, and Evolution: an Abridgment of Animal Species and Evolution (Belknap Press of Harvard University Press, 1970).

  63. Ayala, F. J., Tracey, M. L., Hedgecock, D. & Richmond, R. C. Genetic differentiation during the speciation process in Drosophila. Evolution 28, 576–592 (1974).

    Google Scholar 

  64. Thorpe, J. P. The molecular clock hypothesis: biochemical evolution, genetic differentiation and systematics. Annu. Rev. Ecol. Syst. 13, 139–168 (1982).

    Google Scholar 

  65. Sukumaran, J. & Knowles, L. L. Multispecies coalescent delimits structure, not species. Proc. Natl. Acad. Sci. USA 114, 1607–1611 (2017).

    Google Scholar 

  66. Kirchgatter, K. et al. Phylogeny of Anopheles (Kerteszia) (Diptera: Culicidae) using mitochondrial genes. Insects 11, 324 (2020).

    Google Scholar 

  67. Wondji, C., Simard, F. & Fontenille, D. Evidence for genetic differentiation between the molecular forms M and S within the Forest chromosomal form of Anopheles gambiae in an area of sympatry. Insect Mol. Biol. 11, 11–19 (2002).

    Google Scholar 

  68. Mayr, E. The Growth of Biological Thought: Diversity, Evoluton and Inheritance (Harvard, 1982).

  69. Carnaval, A. C., Hickerson, M. J., Haddad, C. F. B., Rodrigues, M. T. & Moritz, C. Stability predicts genetic diversity in the Brazilian Atlantic forest hotspot. Science 323, 785–789 (2009).

    Google Scholar 

  70. Loaiza, J. R. et al. Review of genetic diversity in malaria vectors (Culicidae: Anophelinae). Infect., Genet. Evol. 12, 1–12 (2012).

    Google Scholar 

  71. Forattini, O. P. Entomologia Médica (Faculdade de Higiene e Saúde Pública, 1962).

  72. Foster, P. G. et al. Phylogeny of anophelinae using mitochondrial protein coding genes. R. Soc. Open Sci. 4, 170758 (2017).

  73. Corrêa, R. R. & Cerqueira, F. M. C. Descrição de Anopheles (Kerteszia) laneanus, nova espécie de anofelino de Campos do Jordão (Diptera, Culicidae). Arq. Hig. Saude Publica 9, 111–117 (1944).

    Google Scholar 

  74. Coetzee, M., Craig, M. & le Sueur, D. Distribution of African Malaria Mosquitoes Belonging to the Anopheles gambiae Complex. Parasitol. Today 16, 74–77 (2000).

    Google Scholar 

  75. Tene Fossog, B. et al. Habitat segregation and ecological character displacement in cryptic African malaria mosquitoes. Evol. Appl. 8, 326–345 (2015).

    Google Scholar 

  76. Pombi, M. et al. Dissecting functional components of reproductive isolation among closely related sympatric species of the Anopheles gambiae complex. Evol. Appl. 10, 1102–1120 (2017).

    Google Scholar 

  77. Campos, M., Rona, L. D. P., Willis, K., Christophides, G. K. & MacCallum, R. M. Unravelling population structure heterogeneity within the genome of the malaria vector Anopheles gambiae. BMC Genom. 22, 422 (2021).

    Google Scholar 

  78. Forattini, O. P. Culicidologia Médica (Ed. Universidade de São Paulo, 2002).

  79. Dos Santos, M. M. M. et al. Morphological identification of species of the Nuneztovari Complex of Anopheles (Diptera: Culicidae) from an area affected by a Brazilian hydroelectric plant. Zootaxa 4565, 235–244 (2019).

    Google Scholar 

  80. Kim, B. Y. et al. Single-fly genome assemblies fill major phylogenomic gaps across the Drosophilidae Tree of Life. PLoS Biol. 22, e3002697 (2024).

  81. Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015).

    Google Scholar 

  82. Laetsch, D. R. & Blaxter, M. L. BlobTools: Interrogation of genome assemblies. F1000Res 6, 1287 (2017).

    Google Scholar 

  83. Manni, M., Berkeley, M. R., Seppey, M., Simão, F. A. & Zdobnov, E. M. BUSCO update: novel and streamlined workflows along with broader and deeper phylogenetic coverage for scoring of eukaryotic, prokaryotic, and viral genomes. Mol. Biol. Evol. 38, 4647–4654 (2021).

    Google Scholar 

  84. Gurevich, A., Saveliev, V., Vyahhi, N. & Tesler, G. QUAST: Quality assessment tool for genome assemblies. Bioinformatics 29, 1072–1075 (2013).

    Google Scholar 

  85. Marçais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764–770 (2011).

    Google Scholar 

  86. Vurture, G. W. et al. GenomeScope: Fast reference-free genome profiling from short reads. Bioinformatics 33, 2202–2204 (2017).

    Google Scholar 

  87. Koren, S. et al. Canu: Scalable and accurate long-read assembly via adaptive κ-mer weighting and repeat separation. Genome Res. 27, 722–736 (2017).

    Google Scholar 

  88. Kolmogorov, M., Yuan, J., Lin, Y. & Pevzner, P. A. Assembly of long, error-prone reads using repeat graphs. Nat. Biotechnol. 37, 540–546 (2019).

    Google Scholar 

  89. Walker, B. J. et al. Pilon: An integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9, e112963 (2014).

    Google Scholar 

  90. Bonenfant, Q., Noe, L. & Touzet, H. Porechop ABI: discovering unknown adapters in Oxford Nanopore Technology sequencing reads for downstream trimming. Bioinform. Adv. 3, vbac085 (2023).

  91. Cheng, H., Concepcion, G. T., Feng, X., Zhang, H. & Li, H. Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nat. Methods 18, 170–175 (2021).

    Google Scholar 

  92. Stanojević, D., Lin, D. & Florez De Sessions, P. Telomere-to-telomere phased genome assembly using error-corrected Simplex nanopore reads. biorxiv. https://doi.org/10.1101/2024.05.18.594796 (2024).

  93. Astashyn, A. et al. Rapid and sensitive detection of genome contamination at scale with FCS-GX. Genome Biol. 25, 60 (2024).

  94. Waterhouse, R. M. et al. BUSCO applications from quality assessments to gene prediction and phylogenomics. Mol. Biol. Evol. 35, 543–548 (2018).

    Google Scholar 

  95. Dias, G. R., Dupim, E. G., Vanderlinde, T., Mello, B. & Carvalho, A. B. A phylogenomic study of Steganinae fruit flies (Diptera: Drosophilidae): strong gene tree heterogeneity and evidence for monophyly. BMC Evol. Biol. 20, 1–12 (2020).

    Google Scholar 

  96. Abascal, F., Zardoya, R. & Telford, M. J. TranslatorX: Multiple alignment of nucleotide sequences guided by amino acid translations. Nucleic Acids Res 38, 7–13 (2010).

    Google Scholar 

  97. Wiens, J. J. & Morrill, M. C. Missing data in phylogenetic analysis: Reconciling results from simulations and empirical data. Syst. Biol. 60, 719–731 (2011).

  98. Nute, M., Chou, J., Molloy, E. K. & Warnow, T. The performance of coalescent-based species tree estimation methods under models of missing data. BMC Genom. 19, 286 (2018).

  99. Smith, B. T., Mauck, W. M., Benz, B. W. & Andersen, M. J. Uneven missing data skew phylogenomic relationships within the lories and lorikeets. Genome Biol. Evol. 12, 1131–1147 (2020).

    Google Scholar 

  100. Wong, T. K. et al. IQ-TREE 3: Phylogenomic Inference Software Using Complex Evolutionary Models. http://www.iqtree.org (2025).

  101. Mai, U. & Mirarab, S. TreeShrink: fast and accurate detection of outlier long branches in collections of phylogenetic trees. BMC Genom. 19, 272 (2018).

  102. Mirarab, S. et al. ASTRAL: genome-scale coalescent-based species tree estimation. Bioinformatics 30, 541–548 (2014).

    Google Scholar 

  103. Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. (2013).

  104. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Google Scholar 

  105. Broad Institute. Picard Toolkit. (2019).

  106. Garrison, E. & Marth, G. Haplotype-based variant detection from short-read sequencing. (2012).

  107. Danecek, P. et al. Twelve years of SAMtools and BCFtools. Gigascience 10, giab008 (2021).

  108. Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).

    Google Scholar 

  109. Lindenbaum, P. JVarkit: java-based utilities for Bioinformatics. figshare (2015).

  110. Patterson, N., Price, A. L. & Reich, D. Population structure and eigenanalysis. PLoS Genet. 2, e190 (2006).

    Google Scholar 

  111. Miles, A. et al. scikit-allel: a Python package for exploring and analysing genetic variation data (2023).

  112. Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).

    Google Scholar 

  113. Obbard, D. J. et al. Estimating divergence dates and substitution rates in the Drosophila phylogeny. Mol. Biol. Evol. 29, 3459–3473 (2012).

    Google Scholar 

  114. Rashid, I. et al. Spontaneous mutation rate estimates for the principal malaria vectors Anopheles coluzzii and Anopheles stephensi. Sci. Rep. 12, 226 (2022).

    Google Scholar 

  115. Russo, C. A. M., Takezaki, N. & Nei, M. Molecular phylogeny and divergence times of drosophilid species. Mol. Biol. Evol. 12, 391–404 (1995).

    Google Scholar 

  116. Voges, K. Code for data analysis and figure generation. https://doi.org/10.5281/zenodo.18389048 (2026).

  117. South, A. Rworldmap: a New R Package for Mapping Global Data. http://www.un.org/millenniumgoals/bkgd. (2011).

  118. Pebesma, E. Simple features for R: standardized support for spatial vector. Data. R. J. 10, 439 (2018).

    Google Scholar 

  119. Becker, R., Wilks, A., Minka, T. & Deckmyn, A. maps: Draw Geographical Maps. CRAN: Contributed Packages. Available from: https://cran.r-project.org/package=maps (2023).

  120. Pebesma, E. & Bivand, R. Spatial Data Science. https://doi.org/10.1201/9780429459016(Chapman and Hall/CRC, 2023).

  121. R Development Core Team. R: a language and environment for statistical computing. (R Foundation for Statistical Computing, Vienna, 2014).

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Acknowledgements

The authors thank Natália Valério de Souza, Iara Carolini Pinheiro, André Akira Gonzaga Yoshikawa, Sabrina Fernandes Cardoso, João Victor Costa Guesser, Anna Luiza Buainain, Julia Levinstein, Felipe Rocha, and Paulo Paiva for their assistance during fieldwork; Paulo Paiva for critically reading the manuscript; LAMEB—Federal University of Santa Catarina for access to microscopy facilities and technical support; and Dr. Bernard Kim for assistance with Nanopore sequencing. This paper forms part of the Ph.D. thesis of Kamila Voges, undertaken within the Postgraduate Programme in Cell and Developmental Biology (PPGBCD) at the Center for Biological Sciences (CCB), Federal University of Santa Catarina (UFSC), Brazil. This work was supported by CAPES, CNPq-INCT-EM, the Royal Society (grant numbers: AL\191009; AL\201013; AL\211028; AL\221016; AL\24100017) to LR, and the Welcome Trust grant number 207486/Z/17/Z to ABC. FU is supported by CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Finance Code 001.

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Author notes
  1. These authors contributed equally: A. Bernardo Carvalho, Luísa D. P. Rona.

Authors and Affiliations

  1. Departamento de Biologia Celular, Embriologia e Genética, Universidade Federal de Santa Catarina, Florianópolis, Brasil

    Kamila Voges & Luísa D. P. Rona

  2. Departamento de Genética, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil

    Guilherme de Rezende Dias, Thyago Vanderlinde, Fabiana Uno & A. Bernardo Carvalho

  3. Departamento de Genética e Biologia Evolutiva, Universidade de São Paulo, São Paulo, Brasil

    Eduardo Guimarães Dupim

  4. Laboratório de Biologia Molecular de Parasitas e Vetores, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brasil

    André Nóbrega Pitaluga

  5. Instituto Nacional de Ciência e Tecnologia em Entomologia Molecular, Rio de Janeiro, Brasil

    André Nóbrega Pitaluga, Carlos José de Carvalho Pinto, A. Bernardo Carvalho & Luísa D. P. Rona

  6. Departamento de Microbiologia, Imunologia e Parasitologia, Universidade Federal de Santa Catarina, Florianópolis, Brasil

    Carlos José de Carvalho Pinto

  7. Secretaria de Estado da Saúde do Espírito Santo, Vitória, Espírito Santo, Brasil

    Helder Ricas Rezende

  8. Department of Biology, University of York, York, UK

    Sarah Jayne Forrester & James Chong

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Contributions

K.V., L.D.P.R., A.B.C., C.J.C.P., A.N.P., G.R.D. and H.R.R. collected the mosquitoes. K.V. and C.J.C.P. conducted the morphological identification. K.V., L.D.P.R., A.B.C., J.C., G.R.D., E.G.D., F.U., S.J.F. and T.V. were responsible for data generation, genome assembly, and analysis. K.V. drafted the manuscript, with critical revisions provided by L.D.P.R., A.B.C. and G.R.D. L.D.P.R. and A.B.C. contributed to the design and coordination of the study. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Kamila Voges or Luísa D. P. Rona.

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Communications Biology thanks Jan Conn, Panagiotis Ioannidis and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Wannes Dermauw and Tobias Goris. A peer review file is available.

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Voges, K., Dias, G.d.R., Dupim, E.G. et al. Anopheles (Kerteszia) cruzii, the main malaria vector in the Brazilian Atlantic Forest, is a complex of at least five cryptic species. Commun Biol (2026). https://doi.org/10.1038/s42003-026-09700-0

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  • Received: 05 June 2025

  • Accepted: 03 February 2026

  • Published: 25 February 2026

  • DOI: https://doi.org/10.1038/s42003-026-09700-0

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