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
WHO. World Malaria Report 2023 (WHO, 2023).
de Pina-Costa, A. et al. Malaria in Brazil: What happens outside the Amazonian endemic region. Mem. Inst. Oswaldo Cruz 109, 618–633 (2014).
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).
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).
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).
Deane, L. M. Malaria vectors in Brazil. Mem. Inst. Oswaldo Cruz. 81(Suppl II), 5–14 (1986).
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).
Consoli, R. A. G. B. & Lourenço de Oliveira, R. Principais Mosquitos de Importância Médica no Brasil. (Editora Fiocruz,1994).
Rachou, R. Anofelinos do Brasil: Comportamento das espécies vetoras de malária. Rev. Bras. Malariol. Doenças Trop. 10, 145–181 (1958).
Gadelha, P. From ‘forest malaria’ to ‘bromeliad malaria’: a case-study of scientific controversy and malaria control. Parassitologia 36, 175–95 (1994).
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).
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).
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).
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).
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).
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).
de Oliveira, T. C. et al. Plasmodium simium: population genomics reveals the origin of a reverse zoonosis. J. Infect. Dis. 224, 1950–1961 (2021).
Buery, J. C. et al. Atlantic forest malaria: a review of more than 20 years of epidemiological investigation. Microorganisms 9, 1–14 (2021).
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).
Ramirez, C. C. L. & Dessen, E. M. B. Chromosomal evidence for sibling species of the malaria vector Anopheles cruzii. Genome 43, 143–151 (2000).
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).
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).
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).
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).
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).
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).
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).
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).
Della Torre, A. et al. Speciation within Anopheles gambiae—the glass is half full. Science 298, 115–117 (2002).
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).
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).
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).
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).
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).
Kajitani, R. et al. Efficient de novo assembly of highly heterozygous genomes from whole-genome shotgun short reads. Genome Res. 24, 1384–1395 (2014).
Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).
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).
Holt, R. A. et al. The genome sequence of the malaria mosquito Anopheles gambiae. Science 298, 129–149 (2002).
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).
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).
Aragão, M. B. Distribuição geográfica e abundância de espécies de Anopheles (Kerteszia) (Diptera, Culicidae). Rev. Bras. Malariol. Doenças Trop. 16, 73 (1964).
Hey, J. & Pinho, C. Population genetics and objectivity in species diagnosis. Evolution 66, 1413–1429 (2012).
Neafsey, D. E. et al. Highly evolvable malaria vectors: the genomes of 16 Anopheles mosquitoes. Science 347, 1258522 (2015).
Charlesworth, B., Coyne, J. A. & Barton, N. H. The relative rates of evolution of sex chromosomes and autosomes. Am. Nat. 130, 113–146 (1987).
Thornton, K. & Long, M. Rapid divergence of gene duplicates on the Drosophila melanogaster X chromosome. Mol. Biol. Evol. 19, 918–925 (2002).
Meisel, R. P. & Connallon, T. The faster-X effect: integrating theory and data. Trends Genet. 29, 537–544 (2013).
Bechsgaard, J. et al. Evidence for faster X chromosome evolution in spiders. Mol. Biol. Evol. 36, 1281–1293 (2019).
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).
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).
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).
Miles, A. et al. Genetic diversity of the African malaria vector anopheles gambiae. Nature 552, 96–100 (2017).
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).
Li, H. Seqtk: a fast and lightweight tool for processing FASTA or FASTQ sequences. (2013).
Cabanettes, F. & Klopp, C. D-GENIES: dot plot large genomes in an interactive, efficient and simple way. PeerJ 6, e4958 (2018).
Tamura, K. et al. Estimating divergence times in large molecular phylogenies. Proc. Natl. Acad. Sci. 109, 19333–19338 (2012).
Tamura, K., Stecher, G. & Kumar, S. MEGA11: molecular evolutionary genetics analysis version 11. Mol. Biol. Evol. 38, 3022–3027 (2021).
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).
Queiroz, K. Species concepts and species delimitation. Syst. Biol. 56, 879–886 (2007).
Ridley, M. Evolution. (Blackwell Pub, 2004).
Coyne, J. A., Coyne, H. A. & Orr, H. A. Speciation (Oxford University Press, Incorporated, 2004).
Wright, S. The roles of mutation, inbreeding, crossbreeding and selection in evolution. Proc. XI Int. Congr. Genet. 8, 209–222 (1932).
Mayr, E. Populations, Species, and Evolution: an Abridgment of Animal Species and Evolution (Belknap Press of Harvard University Press, 1970).
Ayala, F. J., Tracey, M. L., Hedgecock, D. & Richmond, R. C. Genetic differentiation during the speciation process in Drosophila. Evolution 28, 576–592 (1974).
Thorpe, J. P. The molecular clock hypothesis: biochemical evolution, genetic differentiation and systematics. Annu. Rev. Ecol. Syst. 13, 139–168 (1982).
Sukumaran, J. & Knowles, L. L. Multispecies coalescent delimits structure, not species. Proc. Natl. Acad. Sci. USA 114, 1607–1611 (2017).
Kirchgatter, K. et al. Phylogeny of Anopheles (Kerteszia) (Diptera: Culicidae) using mitochondrial genes. Insects 11, 324 (2020).
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).
Mayr, E. The Growth of Biological Thought: Diversity, Evoluton and Inheritance (Harvard, 1982).
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).
Loaiza, J. R. et al. Review of genetic diversity in malaria vectors (Culicidae: Anophelinae). Infect., Genet. Evol. 12, 1–12 (2012).
Forattini, O. P. Entomologia Médica (Faculdade de Higiene e Saúde Pública, 1962).
Foster, P. G. et al. Phylogeny of anophelinae using mitochondrial protein coding genes. R. Soc. Open Sci. 4, 170758 (2017).
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).
Coetzee, M., Craig, M. & le Sueur, D. Distribution of African Malaria Mosquitoes Belonging to the Anopheles gambiae Complex. Parasitol. Today 16, 74–77 (2000).
Tene Fossog, B. et al. Habitat segregation and ecological character displacement in cryptic African malaria mosquitoes. Evol. Appl. 8, 326–345 (2015).
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).
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).
Forattini, O. P. Culicidologia Médica (Ed. Universidade de São Paulo, 2002).
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).
Kim, B. Y. et al. Single-fly genome assemblies fill major phylogenomic gaps across the Drosophilidae Tree of Life. PLoS Biol. 22, e3002697 (2024).
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).
Laetsch, D. R. & Blaxter, M. L. BlobTools: Interrogation of genome assemblies. F1000Res 6, 1287 (2017).
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).
Gurevich, A., Saveliev, V., Vyahhi, N. & Tesler, G. QUAST: Quality assessment tool for genome assemblies. Bioinformatics 29, 1072–1075 (2013).
Marçais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764–770 (2011).
Vurture, G. W. et al. GenomeScope: Fast reference-free genome profiling from short reads. Bioinformatics 33, 2202–2204 (2017).
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).
Kolmogorov, M., Yuan, J., Lin, Y. & Pevzner, P. A. Assembly of long, error-prone reads using repeat graphs. Nat. Biotechnol. 37, 540–546 (2019).
Walker, B. J. et al. Pilon: An integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9, e112963 (2014).
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).
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).
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).
Astashyn, A. et al. Rapid and sensitive detection of genome contamination at scale with FCS-GX. Genome Biol. 25, 60 (2024).
Waterhouse, R. M. et al. BUSCO applications from quality assessments to gene prediction and phylogenomics. Mol. Biol. Evol. 35, 543–548 (2018).
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).
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).
Wiens, J. J. & Morrill, M. C. Missing data in phylogenetic analysis: Reconciling results from simulations and empirical data. Syst. Biol. 60, 719–731 (2011).
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).
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).
Wong, T. K. et al. IQ-TREE 3: Phylogenomic Inference Software Using Complex Evolutionary Models. http://www.iqtree.org (2025).
Mai, U. & Mirarab, S. TreeShrink: fast and accurate detection of outlier long branches in collections of phylogenetic trees. BMC Genom. 19, 272 (2018).
Mirarab, S. et al. ASTRAL: genome-scale coalescent-based species tree estimation. Bioinformatics 30, 541–548 (2014).
Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. (2013).
Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Broad Institute. Picard Toolkit. (2019).
Garrison, E. & Marth, G. Haplotype-based variant detection from short-read sequencing. (2012).
Danecek, P. et al. Twelve years of SAMtools and BCFtools. Gigascience 10, giab008 (2021).
Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).
Lindenbaum, P. JVarkit: java-based utilities for Bioinformatics. figshare (2015).
Patterson, N., Price, A. L. & Reich, D. Population structure and eigenanalysis. PLoS Genet. 2, e190 (2006).
Miles, A. et al. scikit-allel: a Python package for exploring and analysing genetic variation data (2023).
Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).
Obbard, D. J. et al. Estimating divergence dates and substitution rates in the Drosophila phylogeny. Mol. Biol. Evol. 29, 3459–3473 (2012).
Rashid, I. et al. Spontaneous mutation rate estimates for the principal malaria vectors Anopheles coluzzii and Anopheles stephensi. Sci. Rep. 12, 226 (2022).
Russo, C. A. M., Takezaki, N. & Nei, M. Molecular phylogeny and divergence times of drosophilid species. Mol. Biol. Evol. 12, 391–404 (1995).
Voges, K. Code for data analysis and figure generation. https://doi.org/10.5281/zenodo.18389048 (2026).
South, A. Rworldmap: a New R Package for Mapping Global Data. http://www.un.org/millenniumgoals/bkgd. (2011).
Pebesma, E. Simple features for R: standardized support for spatial vector. Data. R. J. 10, 439 (2018).
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).
Pebesma, E. & Bivand, R. Spatial Data Science. https://doi.org/10.1201/9780429459016(Chapman and Hall/CRC, 2023).
R Development Core Team. R: a language and environment for statistical computing. (R Foundation for Statistical Computing, Vienna, 2014).
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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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.
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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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DOI: https://doi.org/10.1038/s42003-026-09700-0