. 2018 Nov;563(7732):501-507.

doi: 10.1038/s41586-018-0692-z. Epub 2018 Nov 14.

Improved reference genome of Aedes aegypti informs arbovirus vector control

Benjamin J Matthews^{1

2

3}, Olga Dudchenko^{4

5

6

7}, Sarah B Kingan⁸, Sergey Koren⁹, Igor Antoshechkin¹⁰, Jacob E Crawford¹¹, William J Glassford¹², Margaret Herre^{13

14}, Seth N Redmond^{15

16}, Noah H Rose^{17

18}, Gareth D Weedall^{19

20}, Yang Wu^{21

22

23}, Sanjit S Batra^{4

5

6}, Carlos A Brito-Sierra^{24

25}, Steven D Buckingham²⁶, Corey L Campbell²⁷, Saki Chan²⁸, Eric Cox²⁹, Benjamin R Evans³⁰, Thanyalak Fansiri³¹, Igor Filipović³², Albin Fontaine^{33

34

35

36}, Andrea Gloria-Soria^{30

37}, Richard Hall⁸, Vinita S Joardar²⁹, Andrew K Jones³⁸, Raissa G G Kay³⁹, Vamsi K Kodali²⁹, Joyce Lee²⁸, Gareth J Lycett¹⁹, Sara N Mitchell¹¹, Jill Muehling⁸, Michael R Murphy²⁹, Arina D Omer^{4

5

6}, Frederick A Partridge²⁶, Paul Peluso⁸, Aviva Presser Aiden^{4

5

40

41}, Vidya Ramasamy³⁸, Gordana Rašić³², Sourav Roy⁴², Karla Saavedra-Rodriguez²⁷, Shruti Sharan^{24

25}, Atashi Sharma^{23

43}, Melissa Laird Smith⁸, Joe Turner⁴⁴, Allison M Weakley¹¹, Zhilei Zhao^{17

18}, Omar S Akbari^{45

46}, William C Black 4th²⁷, Han Cao²⁸, Alistair C Darby⁴⁴, Catherine A Hill^{24

25}, J Spencer Johnston⁴⁷, Terence D Murphy²⁹, Alexander S Raikhel⁴², David B Sattelle²⁶, Igor V Sharakhov^{23

43

48}, Bradley J White¹¹, Li Zhao⁴⁹, Erez Lieberman Aiden^{4

5

6

7

15}, Richard S Mann¹², Louis Lambrechts^{33

35}, Jeffrey R Powell³⁰, Maria V Sharakhova^{23

43

48}, Zhijian Tu^{22

23}, Hugh M Robertson⁵⁰, Carolyn S McBride^{17

18}, Alex R Hastie²⁸, Jonas Korlach⁸, Daniel E Neafsey^{15

16}, Adam M Phillippy⁹, Leslie B Vosshall^{13

51

14}

Affiliations

¹ Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, NY, USA. bnmtthws@gmail.com.
² Howard Hughes Medical Institute, New York, NY, USA. bnmtthws@gmail.com.
³ Kavli Neural Systems Institute, New York, NY, USA. bnmtthws@gmail.com.
⁴ The Center for Genome Architecture, Baylor College of Medicine, Houston, TX, USA.
⁵ Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
⁶ Department of Computer Science, Rice University, Houston, TX, USA.
⁷ Center for Theoretical and Biological Physics, Rice University, Houston, TX, USA.
⁸ Pacific Biosciences, Menlo Park, CA, USA.
⁹ National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
¹⁰ Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
¹¹ Verily Life Sciences, South San Francisco, CA, USA.
¹² Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA.
¹³ Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, NY, USA.
¹⁴ Kavli Neural Systems Institute, New York, NY, USA.
¹⁵ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹⁶ Department of Immunology and Infectious Disease, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
¹⁷ Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
¹⁸ Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
¹⁹ Vector Biology Department, Liverpool School of Tropical Medicine, Liverpool, UK.
²⁰ Liverpool John Moores University, Liverpool, UK.
²¹ Department of Pathogen Biology, School of Public Health, Southern Medical University, Guangzhou, China.
²² Department of Biochemistry, Virginia Tech, Blacksburg, VA, USA.
²³ Fralin Life Science Institute, Virginia Tech, Blacksburg, VA, USA.
²⁴ Department of Entomology, Purdue University, West Lafayette, IN, USA.
²⁵ Purdue Institute for Inflammation, Immunology and Infectious Disease, Purdue University, West Lafayette, IN, USA.
²⁶ Centre for Respiratory Biology, UCL Respiratory, University College London, London, UK.
²⁷ Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA.
²⁸ Bionano Genomics, San Diego, CA, USA.
²⁹ National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
³⁰ Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA.
³¹ Vector Biology and Control Section, Department of Entomology, Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok, Thailand.
³² Mosquito Control Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
³³ Insect-Virus Interactions Group, Department of Genomes and Genetics, Institut Pasteur, Paris, France.
³⁴ Unité de Parasitologie et Entomologie, Département des Maladies Infectieuses, Institut de Recherche Biomédicale des Armées, Marseille, France.
³⁵ Centre National de la Recherche Scientifique, Unité Mixte de Recherche 2000, Paris, France.
³⁶ Aix Marseille Université, IRD, AP-HM, SSA, UMR Vecteurs - Infections Tropicales et Méditerranéennes (VITROME), IHU - Méditerranée Infection, Marseille, France.
³⁷ The Connecticut Agricultural Experiment Station, New Haven, CT, USA.
³⁸ Department of Biological and Medical Sciences, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, UK.
³⁹ Department of Entomology, University of California Riverside, Riverside, CA, USA.
⁴⁰ Department of Bioengineering, Rice University, Houston, TX, USA.
⁴¹ Department of Pediatrics, Texas Children's Hospital, Houston, TX, USA.
⁴² Department of Entomology, Center for Disease Vector Research and Institute for Integrative Genome Biology, University of California, Riverside, CA, USA.
⁴³ Department of Entomology, Virginia Tech, Blacksburg, VA, USA.
⁴⁴ Institute of Integrative Biology, University of Liverpool, Liverpool, UK.
⁴⁵ Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA.
⁴⁶ Tata Institute for Genetics and Society, University of California, San Diego, La Jolla, CA, USA.
⁴⁷ Department of Entomology, Texas A&M University, College Station, TX, USA.
⁴⁸ Laboratory of Ecology, Genetics and Environmental Protection, Tomsk State University, Tomsk, Russia.
⁴⁹ Laboratory of Evolutionary Genetics and Genomics, The Rockefeller University, New York, NY, USA.
⁵⁰ Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
⁵¹ Howard Hughes Medical Institute, New York, NY, USA.

PMID: 30429615
PMCID: PMC6421076
DOI: 10.1038/s41586-018-0692-z

Improved reference genome of Aedes aegypti informs arbovirus vector control

Benjamin J Matthews et al. Nature. 2018 Nov.

. 2018 Nov;563(7732):501-507.

doi: 10.1038/s41586-018-0692-z. Epub 2018 Nov 14.

Authors

Affiliations

¹ Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, NY, USA. bnmtthws@gmail.com.
² Howard Hughes Medical Institute, New York, NY, USA. bnmtthws@gmail.com.
³ Kavli Neural Systems Institute, New York, NY, USA. bnmtthws@gmail.com.
⁴ The Center for Genome Architecture, Baylor College of Medicine, Houston, TX, USA.
⁵ Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
⁶ Department of Computer Science, Rice University, Houston, TX, USA.
⁷ Center for Theoretical and Biological Physics, Rice University, Houston, TX, USA.
⁸ Pacific Biosciences, Menlo Park, CA, USA.
⁹ National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
¹⁰ Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
¹¹ Verily Life Sciences, South San Francisco, CA, USA.
¹² Mortimer B. Zuckerman Mind Brain Behavior Institute, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, USA.
¹³ Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, NY, USA.
¹⁴ Kavli Neural Systems Institute, New York, NY, USA.
¹⁵ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹⁶ Department of Immunology and Infectious Disease, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
¹⁷ Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
¹⁸ Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
¹⁹ Vector Biology Department, Liverpool School of Tropical Medicine, Liverpool, UK.
²⁰ Liverpool John Moores University, Liverpool, UK.
²¹ Department of Pathogen Biology, School of Public Health, Southern Medical University, Guangzhou, China.
²² Department of Biochemistry, Virginia Tech, Blacksburg, VA, USA.
²³ Fralin Life Science Institute, Virginia Tech, Blacksburg, VA, USA.
²⁴ Department of Entomology, Purdue University, West Lafayette, IN, USA.
²⁵ Purdue Institute for Inflammation, Immunology and Infectious Disease, Purdue University, West Lafayette, IN, USA.
²⁶ Centre for Respiratory Biology, UCL Respiratory, University College London, London, UK.
²⁷ Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA.
²⁸ Bionano Genomics, San Diego, CA, USA.
²⁹ National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
³⁰ Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA.
³¹ Vector Biology and Control Section, Department of Entomology, Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok, Thailand.
³² Mosquito Control Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
³³ Insect-Virus Interactions Group, Department of Genomes and Genetics, Institut Pasteur, Paris, France.
³⁴ Unité de Parasitologie et Entomologie, Département des Maladies Infectieuses, Institut de Recherche Biomédicale des Armées, Marseille, France.
³⁵ Centre National de la Recherche Scientifique, Unité Mixte de Recherche 2000, Paris, France.
³⁶ Aix Marseille Université, IRD, AP-HM, SSA, UMR Vecteurs - Infections Tropicales et Méditerranéennes (VITROME), IHU - Méditerranée Infection, Marseille, France.
³⁷ The Connecticut Agricultural Experiment Station, New Haven, CT, USA.
³⁸ Department of Biological and Medical Sciences, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, UK.
³⁹ Department of Entomology, University of California Riverside, Riverside, CA, USA.
⁴⁰ Department of Bioengineering, Rice University, Houston, TX, USA.
⁴¹ Department of Pediatrics, Texas Children's Hospital, Houston, TX, USA.
⁴² Department of Entomology, Center for Disease Vector Research and Institute for Integrative Genome Biology, University of California, Riverside, CA, USA.
⁴³ Department of Entomology, Virginia Tech, Blacksburg, VA, USA.
⁴⁴ Institute of Integrative Biology, University of Liverpool, Liverpool, UK.
⁴⁵ Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA.
⁴⁶ Tata Institute for Genetics and Society, University of California, San Diego, La Jolla, CA, USA.
⁴⁷ Department of Entomology, Texas A&M University, College Station, TX, USA.
⁴⁸ Laboratory of Ecology, Genetics and Environmental Protection, Tomsk State University, Tomsk, Russia.
⁴⁹ Laboratory of Evolutionary Genetics and Genomics, The Rockefeller University, New York, NY, USA.
⁵⁰ Department of Entomology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
⁵¹ Howard Hughes Medical Institute, New York, NY, USA.

PMID: 30429615
PMCID: PMC6421076
DOI: 10.1038/s41586-018-0692-z

Abstract

Female Aedes aegypti mosquitoes infect more than 400 million people each year with dangerous viral pathogens including dengue, yellow fever, Zika and chikungunya. Progress in understanding the biology of mosquitoes and developing the tools to fight them has been slowed by the lack of a high-quality genome assembly. Here we combine diverse technologies to produce the markedly improved, fully re-annotated AaegL5 genome assembly, and demonstrate how it accelerates mosquito science. We anchored physical and cytogenetic maps, doubled the number of known chemosensory ionotropic receptors that guide mosquitoes to human hosts and egg-laying sites, provided further insight into the size and composition of the sex-determining M locus, and revealed copy-number variation among glutathione S-transferase genes that are important for insecticide resistance. Using high-resolution quantitative trait locus and population genomic analyses, we mapped new candidates for dengue vector competence and insecticide resistance. AaegL5 will catalyse new biological insights and intervention strategies to fight this deadly disease vector.

PubMed Disclaimer

Conflict of interest statement

P.P., M.L.S., J.M., S.B.K., R.H. and J.K. are employees of Pacific Biosciences, a company developing single-molecule sequencing technologies. J.L., S.C., H.C. and A.R.H. are employees of Bionano Genomics and own company stock options. O.D., S.S.B., A.D.O., A.P.A. and E.L.A. are inventors on a US provisional patent application 62/347,605, filed 8 June 2016, by the Baylor College of Medicine and the Broad Institute.

Figures

**Fig. 1. AaegL5 assembly statistics and annotation.**
a, b, Treemap of AaegL3 (a) and AaegL4 (b) contigs scaled by length. c, Principal component analysis of allelic variation of the indicated strains at 11,229 SNP loci. n = 7 per genotype d, Flow cytometry analysis of LVP_AGWG genome size. n = 5 per sex. Box plot: median is indicated by the blue line; boxes show first to third quartiles, whiskers are the 1.5× interquartile interval (Extended Data Fig. 1b). e, Treemap of AaegL5 contigs scaled by length. f, Genome composition (Supplementary Data 2, 3). g, Gene set alignment BLASTp coverage is compared between AaegL3.4 and AaegL5.0, with *D. melanogaster* protein queries. h, Alignment of 253 RNA-seq libraries to AaegL3.4 and AaegL5.0 gene set annotations (Supplementary Data 4–9). LTR, long terminal repeat retrotransposon; MITES, miniature inverted-repeat transposable elements; SINES, short interspersed nuclear elements.

**Fig. 2. Chromosomal arrangement and increased number of chemosensory receptor genes.**
a, Location of predicted chemoreceptors (odorant receptors (ORs), gustatory receptors (GRs) and ionotropic receptors (IRs)) by chromosome in AaegL5. The blunt end of the arrowheads marks gene position and the arrow indicates orientation. Filled and open arrowheads represent intact genes and pseudogenes, respectively (Supplementary Data 17–20 and Extended Data Fig. 3). b, Chemosensory receptor annotations are compared between AaegL5 and AaegL3.

**Fig. 3. Application of AaegL5 to resolve the sex-determining locus.**
a, M locus structure indicating high alignment identity (grey-dashed boxes) and boundaries of *myo-sex* and *Nix* gene models (magenta and white boxes, arrowheads represent orientation). b, FISH of BAC clones containing *myo-sex* and *Nix*. Scale bar, 2 μm. Representative image of 10 samples. c, De novo optical map spanning the M locus and bridging the estimated 163-kb gap in the AaegL5 assembly. DNA molecules are cropped at the edges for clarity. d, Chromosome quotient (CQ) analysis of genomic DNA from male and female libraries aligned to AaegL5 chromosome 1. Each dot represents the CQ value of a repeat-masked 1-kb window with >20 reads aligned from male libraries.

**Fig. 4. Copy-number variation in the glutathione S-transferase epsilon gene cluster.**
a, Glutathione S-transferase epsilon (*GSTe*) gene cluster structure in AaegL5 compared to AaegL3 (Supplementary Data 23). Arrowheads indicate gene orientation. b, Dot-plot alignment of AaegL5 *GSTe* region to itself. c, Optical mapping of DNA labelled with indicated enzymes. DNA molecules are cropped at the edges for clarity. d, Genomic sequencing coverage of AaegL3 *GSTe* genes (DNA read pairs mapped to each gene, normalized by gene length in kb) from one LVP_AGWG male and pooled mosquitoes from four other laboratory strains.

**Fig. 5. Using the AaegL5 genome for applied population genetics.**
a, Heat map of linkage based on pairwise recombination fractions for 255 RAD markers ordered by AaegL5 physical coordinates. b, Significant QTLs on chromosome 2 underly systemic DENV dissemination in midgut-infected mosquitoes (Extended Data Fig. 10a). Curves represent log of the odds ratio (LOD) scores obtained by interval mapping. Dotted vertical lines indicate genome-wide statistical significance thresholds (α = 0.05). Confidence intervals of significant QTLs: bright colour, 1.5-LOD interval; light colour, 2-LOD interval with generalist effects (black, across DENV serotypes and isolates) and DENV isolate-specific effects (red, indicative of genotype-by-genotype interactions). c, d, Synteny between linkage map (in cM) and physical map (in Mb) for chromosome 2 (c) and chromosomes 1 and 3 (d). The orange color of chromosome 1 denotes uncertainty in the cM estimates because of deviations in Mendelian ratios surrounding the M locus. e, Chromosome 3 SNPs significantly correlated with deltamethrin survival. f, g, Magnified and inverted view of box in e, centred on the new gene model of voltage-gated sodium channel (*VGSC*, transcript variant X3; the chromosomal position is indicated in red). f, Non-coding genes are omitted for clarity, and other genes indicated with grey boxes. *VGSC* exons are represented by tall boxes and untranslated regions by short boxes. Arrowheads indicate gene orientation. Non-synonymous *VGSC* SNPs are marked with larger black and yellow circles: V1016I = 315,983,763; F1534C = 315,939,224; V410L = 316,080,722. g, Difference in expected heterozygosity (H_exp alive − H_exp dead) for all SNPs.

**Extended Data Fig. 1. Project flowchart, measured genome size and assembly process.**
a, Flowchart of LVP_AGWG strain inbreeding, data collection and experimental design of the AaegL5 assembly process. b, Estimated average 1C genome size for each strain for five *Ae. aegypti* strains and *Ae. mascarensis*, the sister taxon of *Ae. aegypti*, for which the genome size has not previously been measured. There were no significant differences between the sexes within and between the species and strains analysed (P > 0.2). Significant differences between strains were determined using Proc GLM in SAS with both a Tukey and a Scheffé option with the same outcome. Data labelled with different letters are significantly different (P < 0.01). c, Combining Hi-C maps with 2D annotations enabled efficient review of sequences identified as alternative haplotypes by sequence alignment. The figure depicts a roughly 24 Mb × 24 Mb fragment of a contact map generated by aligning a Hi-C dataset to an intermediate genome assembly generated during the process of creating AaegL5. This intermediate assembly was a sequence comprising error-corrected, ordered and oriented FALCON-Unzip contigs. The intensity of each pixel in the contact map correlates with how often pairs of loci co-locate in the nucleus. Maximum intensity is indicated in the lower left of each panel. These maps include reads that do not align uniquely (reads with zero mapping quality); such alignments are randomly assigned to one of the possible genomic locations. Three panels show three types of annotations that are overlaid on top of the contact map. Left, FALCON-Unzip contig boundaries are highlighted as black squares along the diagonal. Notably, large linear features appear above and below the diagonal. These are the result of sequence overlap among contigs, which can indicate the presence of undercollapsed heterozygosity in the contig set. Because reads that do not map uniquely are randomly assigned during the alignment step, Hi-C reads derived from a contig will sometimes be aligned to an overlapping contig. When this happens, the Hi-C read pair may contribute to the formation of a linear feature above and below the diagonal. Therefore, the linear stretches of enriched contact frequency parallel to the diagonal are brought about by the random assignment procedure, and can facilitate the detection of pairs of overlapping contigs. Note that, when the overlap between contigs is owing to undercollapsed heterozygosity, both contigs will exhibit similar long-range contact patterns. This aspect of Hi-C data also provides evidence for the presence of undercollapsed heterozygosity. Centre, LASTZ-alignment-based annotations for fully redundant contigs. The squares shown in blue are obtained by taking diagonal contig boundary annotations (in black) and shifting them up (respectively, left) when drawing above (respectively, below) the diagonal so that the overlapping sequences are horizontally (respectively, vertically) aligned. Note that, as expected, the squares typically span linear, off-diagonal features in the Hi-C data. When one contig is entirely contained in another contig, the redundant contig does not contribute sequence to the merged chromosome-length scaffolds. Right, LASTZ-alignment-based annotations for partially redundant contigs. Again, the squares shown in blue are obtained by taking diagonal contig boundary annotations (in black) and shifting them up and left. The overlaps shown in this panel correspond to contigs that only partially overlap in sequence with other contigs. Consequently, some of their sequence is incorporated in the final fasta. d, Comparison of chromosome lengths between AaegL4 and AaegL5. Numbers are given before post-Hi-C polishing and gap closing. e, Step-wise assembly statistics for Hi-C scaffolding, alternative haplotype removal and annotation. *Removed length, 779,073,495 bp. **The definition of scaffold groups can be found in a previously published study. ***Gaps between contigs were set to 500 bp for calculating scaffold statistics. N/A, not applicable.

Extended Data Fig. 2. Remaining assembly gaps, summary of geneset annotation improvement, chromatin accessibility analysis, physical genome map and gene strucures of biogenic amine-binding receptors and opsins in AaegL5.
a, Representation of structural variants identified at assembly gaps by alignment of Bionano optical maps. The estimated size of an insertion (blue) or deletion (red) relative to the reference is represented by the size of the circle. When the size or type of structural variants could not be determined or did not agree between the two optical maps, the location of the assembly gap is plotted in grey. Approximate locations of the centromeres (red triangles) and telomere-associated repeat sequences (blue triangles) are indicated. Raw data are available as Supplementary Data 1. b, Comparison of protein-coding genes and transcripts in AaegL5.0 (NCBI RefSeq Release 101) and gene set annotations from *An. gambiae* (Agam), *Culex pipiens* (Cpip) and *D. melanogaster* (Dmel). c, *Sex peptide receptor* structure in AaegL3.4 and AaegL5.0, and female brain RNA-seq and ATAC-seq reads aligned to AaegL5. Blue lines on the RNA-seq track indicate splice junctions, with the number of reads spanning a junction represented by line thickness. Exons are represented by tall filled boxes and introns by lines. Arrowheads indicate gene orientation. d, Average read profiles across promoter regions, defined as the transcription start site (TSS) ±2.5 kb. Solid lines represent Tn5-treated native chromatin using the ATAC-seq protocol (n = 4), dotted lines represent Tn5-treated naked genomic DNA (n = 1). Shaded regions represent s.d. e, A physical genome map was developed by localizing 500 BAC clones to chromosomes using FISH. For the development of a final chromosome map for the AaegL5 assembly, we assigned the coordinates of each outmost BAC clone within a band (Supplementary Data 12) to the boundaries between bands. The final resolution of this map varies on average between 5 and 10 Mb because of the differences in BAC mapping density in different regions of chromosomes. f, Schematic of predicted gene structures of the *Ae. aegypti* biogenic amine-binding receptors and opsins. Exons, cylindrical bars; introns, black lines; dopamine receptors, yellow bars; serotonin receptors, magenta bars; muscarinic acetylcholine receptors, green bars; octopamine receptors, blue bars; opsins, dark purple bars; predicted 3′ and 5′ non-coding sequence (dark shading). The ‘unclassified receptor’ *GPRnna19* is not shown. Details on gene models compared to previous annotations and the predicted amino acid sequences of each gene are available in Supplementary Data 14–16.

**Extended Data Fig. 3. Chromosomal arrangement of chemosensory receptor genes.**
The location of predicted chemoreceptors (odorant receptors (ORs), gustatory receptors (GRs) and ionotropic receptors (IRs)) across all three chromosomes in AaegL5. The blunt end of each arrowhead plotted above each chromosome marks gene position and arrowhead indicates orientation. Filled and open arrowheads represent intact genes and pseudogenes, respectively (Supplementary Data 17–20). This figure is identical to Fig. 2a, but here includes gene names.

**Extended Data Fig. 4. Phylogenetic tree of odorant receptor gene families from *Ae. aegypti*, *An. gambiae* and *D. melanogaster*.**
Maximum likelihood odorant receptor tree was rooted with Orco proteins, which are both highly conserved and basal within the odorant receptor family. Support levels for nodes are indicated by the size of black circles—reflecting approximate likelihood ratio tests (aLRT values ranging from 0 to 1 from PhyML v.3.0 run with default parameters). Suffixes after protein names are C, minor assembly correction; F, major assembly modification; N, new model; P, pseudogene. Scale bar, amino acid substitutions per site.

**Extended Data Fig. 5. Phylogenetic tree of the gustatory receptor gene families from *Ae. aegypti*, *An. gambiae* and *D. melanogaster*.**
Maximum likelihood gustatory receptor tree was rooted with the highly conserved and distantly related carbon dioxide and sugar receptor subfamilies, which together form a basal clade within the arthropod gustatory receptor family. Subfamilies and lineages closely related to *D. melanogaster* gustatory receptors of known function are highlighted. Support levels for nodes are indicated by the size of black circles—reflecting approximate likelihood ratio tests (aLRT values ranging from 0 to 1 from PhyML v.3.0 run with default parameters). Suffixes after protein names are C, minor assembly correction; F, major assembly modification; N, new model; P, pseudogene. Scale bar, amino acid substitutions per site.

**Extended Data Fig. 6. Phylogenetic tree of the ionotropic receptor gene families from *Ae. aegypti*, *An. gambiae* and *D. melanogaster*.**
Maximum likelihood phylogenetic tree of ionotropic receptor protein sequences from the indicated species rooted with highly conserved Ir8a and Ir25a proteins. Conserved proteins with orthologues in all species are named outside the circle, and previously unannotated ionotropic receptors are highlighted with red lines. Support levels for nodes are indicated by the size of black circles—reflecting approximate likelihood ratio tests (aLRT values ranging from - to 1 from PhyML v.3.0 run with default parameters). Suffixes after protein names are C, minor assembly correction; F, major assembly modification; N, new model; P, pseudogene. Scale bar, amino acid substitutions per site.

**Extended Data Fig. 7. Chemosensory receptor expression in adult *Ae. aegypti* tissues.**
Previously published RNA-seq data were reanalysed using the new chemoreceptor annotations and genome assembly. Chemoreceptors have been clustered according to Euclidian distance of their expression vectors using the R function hclust. Expression is given for females at three stages of the gonotrophic cycle (0, 48 or 96 h after taking a blood-meal, for which 0 h indicates not blood-fed, 48 h indicates 48 h after the blood-meal, and 96 h indicates gravid). New genes are indicated by black bars on the right.

**Extended Data Fig. 8. Structural variation, the *Hox* gene cluster and *Hox* cofactor motifs.**
a, Linked-read sequencing of two individuals from the LVP_AGWG strain identified putative structural variants in the AaegL5 assembly. b, Comparative genomic arrangement of the Hox cluster (*HOXC*) in five species (Supplementary Data 22). Note the split of *labial* (*lab*) and *proboscipedia* (pb) between two chromosomes in *Ae. aegypti* and *Cx. quinquefasciatus*. Owing to chromosome arm exchange, chromosome 3p in *Cx. quinquefasciatus* is the homologue of chromosome 2p in *Ae. aegypti*. c, Repeats in putative telomere-associated sequences downstream of pb in both species. d, Motifs known to mediate protein–protein interactions with the Hox cofactor Extradenticle (*Exd*) from the five indicated species are aligned using Clustal-Omega. Perfectly aligned residues are coloured according to *Hox* gene identity, non-conserved residues are grey.

**Extended Data Fig. 9. Population genomic structure and linkage disequilibrium analysis of *Ae. aegypti* strains.**
a, Chromosomal patterns of nucleotide diversity (π) in four strains of *Ae. aegypti* measured in 100-kb non-overlapping windows and presented as a LOESS-smoothed curve. b, Mean nucleotide diversity in the strains in a, with s.d. indicated in parentheses. Nucleotide diversity (π) was measured in non-overlapping 100-kb windows. The Liverpool and Costa Rica colonies maintain extensive diversity despite being colonized in the laboratory more than a decade ago, but show reduced genome-wide diversity (on the order of 30–40%) relative to the more recently laboratory colonized Innisfail and Clovis. c, Pairwise linkage disequilibrium between SNPs located within the same chromosome estimated from 28 wild-caught individuals from the indicated populations. Each point represents the mean linkage disequilibrium for that set of binned SNP pairs. Solid lines are LOESS-smoothed curves, and dashed lines correspond to r²_max/2. Inclusion of additional individuals available from the Amacuzac population (up to 137) had a minimal effect on the linkage disequilibrium estimations (∆R² < 0.017; data not shown). d, Linkage disequilibrium (r²) values along the *Ae. aegypti* AaegL5 genome assembly based on pairwise SNP comparisons. Data were obtained from the average r² of SNPs in 1-kb bins.

**Extended Data Fig. 10. QTL analysis of DENV competence in *Ae. aegypti* and Cys-loop LGICs.**
a, Schematic representation of the experimental workflow for testing DENV competence in *Ae. aegypti*, related to Fig. 5b–d. b, Comparison of QTL map density constructed against AaegL3 or AaegL5 assemblies. c, Concentration–response curves showing the effect on *Ae. aegypti* larval motility of insecticides currently used in veterinary and agricultural applications (mean ± s.e.m., n = 7). d, Phylogenetic tree of Cys-loop LGIC subunits for *Ae. aegypti* and *D. melanogaster*. The accession numbers of the *D. melanogaster* sequences used in constructing the tree are: Dα1 (CAA30172), Dα2 (CAA36517), Dα3 (CAA75688), Dα4(CAB77445), Dα5 (AAM13390), Dα6 (AAM13392), Dα7(AAK67257), Dβ1 (CAA27641), Dβ2 (CAA39211), Dβ3 (CAC48166), GluCl (AAG40735), GRD (Q24352), HisCl1 (AAL74413), HisCl2 (AAL74414), LCCH3 (AAB27090), Ntr (NP_651958), pHCl (NP_001034025), RDL (AAA28556). For *Ae. aegypti* sequences, see Supplementary Data 24. ELIC (Erwinia ligand-gated ion channel), which is an ancestral Cys-loop LGIC found in bacteria (accession number P0C7B7), was used as an outgroup. Scale bar, amino acid substitutions per site.

See this image and copyright information in PMC

Comment in

Improved mosquito genome points to population-control strategies.
Celniker SE. Celniker SE. Nature. 2018 Nov;563(7732):482-483. doi: 10.1038/d41586-018-07266-4. Nature. 2018. PMID: 30459371 No abstract available.

Cited by

Global, asynchronous partial sweeps at multiple insecticide resistance genes in Aedes mosquitoes.
Schmidt TL, Endersby-Harshman NM, van Rooyen ARJ, Katusele M, Vinit R, Robinson LJ, Laman M, Karl S, Hoffmann AA. Schmidt TL, et al. Nat Commun. 2024 Jul 24;15(1):6251. doi: 10.1038/s41467-024-49792-y. Nat Commun. 2024. PMID: 39048545
Hybridization between Aedes aegypti and Aedes mascarensis mosquitoes leads to disruption of male sex determination.
Liang J, Kang L, Michalak P, Sharakhov IV. Liang J, et al. Commun Biol. 2024 Jul 22;7(1):886. doi: 10.1038/s42003-024-06560-4. Commun Biol. 2024. PMID: 39039226 Free PMC article.
Challenges of Robust RNAi-Mediated Gene Silencing in Aedes Mosquitoes.
Figueiredo Prates LH, Fiebig J, Schlosser H, Liapi E, Rehling T, Lutrat C, Bouyer J, Sun Q, Wen H, Xi Z, Schetelig MF, Häcker I. Figueiredo Prates LH, et al. Int J Mol Sci. 2024 May 10;25(10):5218. doi: 10.3390/ijms25105218. Int J Mol Sci. 2024. PMID: 38791257 Free PMC article.
Antibodies to Aedes aegypti D7L salivary proteins as a new serological tool to estimate human exposure to Aedes mosquitoes.
Chea S, Willen L, Nhek S, Ly P, Tang K, Oristian J, Salas-Carrillo R, Ponce A, Leon PCV, Kong D, Ly S, Sath R, Lon C, Leang R, Huy R, Yek C, Valenzuela JG, Calvo E, Manning JE, Oliveira F. Chea S, et al. Front Immunol. 2024 May 1;15:1368066. doi: 10.3389/fimmu.2024.1368066. eCollection 2024. Front Immunol. 2024. PMID: 38751433 Free PMC article.
Odorant receptors for floral- and plant-derived volatiles in the yellow fever mosquito, Aedes aegypti (Diptera: Culicidae).
Pullmann-Lindsley H, Huff RM, Boyi J, Pitts RJ. Pullmann-Lindsley H, et al. PLoS One. 2024 May 6;19(5):e0302496. doi: 10.1371/journal.pone.0302496. eCollection 2024. PLoS One. 2024. PMID: 38709760 Free PMC article.

See all "Cited by" articles

References

1. Bhatt S, et al. The global distribution and burden of dengue. Nature. 2013;496:504–507. doi: 10.1038/nature12060. - DOI - PMC - PubMed
1. Nene V, et al. Genome sequence of Aedes aegypti, a major arbovirus vector. Science. 2007;316:1718–1723. doi: 10.1126/science.1138878. - DOI - PMC - PubMed
1. Timoshevskiy VA, et al. An integrated linkage, chromosome, and genome map for the yellow fever mosquito Aedes aegypti. PLoS Negl. Trop. Dis. 2013;7:e2052. doi: 10.1371/journal.pntd.0002052. - DOI - PMC - PubMed
1. Waterhouse RM, et al. BUSCO applications from quality assessments to gene prediction and phylogenomics. Mol. Biol. Evol. 2017;35:543–548. doi: 10.1093/molbev/msx319. - DOI - PMC - PubMed
1. Chin CS, et al. Phased diploid genome assembly with single-molecule real-time sequencing. Nat. Methods. 2016;13:1050–1054. doi: 10.1038/nmeth.4035. - DOI - PMC - PubMed

Publication types

Actions
Actions
Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Improved reference genome of Aedes aegypti informs arbovirus vector control

Affiliations

Improved reference genome of Aedes aegypti informs arbovirus vector control

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Comment in

Similar articles

Cited by

References

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Abstract

Conflict of interest statement

Figures

Comment in

Similar articles

Cited by

References

Publication types

MeSH terms

Substances

Related information

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources