Neofunctionalization driven by positive selection led to the retention of the loqs2 gene encoding an Aedes specific dsRNA binding protein.
Aedes mosquitoes
Double-stranded RNA (dsRNA)
RNA interference (RNAi)
dsRNA binding protein (dsRBP)
loqs2
Journal
BMC biology
ISSN: 1741-7007
Titre abrégé: BMC Biol
Pays: England
ID NLM: 101190720
Informations de publication
Date de publication:
25 Jan 2024
25 Jan 2024
Historique:
received:
07
02
2022
accepted:
10
01
2024
medline:
26
1
2024
pubmed:
26
1
2024
entrez:
25
1
2024
Statut:
epublish
Résumé
Mosquito borne viruses, such as dengue, Zika, yellow fever and Chikungunya, cause millions of infections every year. These viruses are mostly transmitted by two urban-adapted mosquito species, Aedes aegypti and Aedes albopictus. Although mechanistic understanding remains largely unknown, Aedes mosquitoes may have unique adaptations that lower the impact of viral infection. Recently, we reported the identification of an Aedes specific double-stranded RNA binding protein (dsRBP), named Loqs2, that is involved in the control of infection by dengue and Zika viruses in mosquitoes. Preliminary analyses suggested that the loqs2 gene is a paralog of loquacious (loqs) and r2d2, two co-factors of the RNA interference (RNAi) pathway, a major antiviral mechanism in insects. Here we analyzed the origin and evolution of loqs2. Our data suggest that loqs2 originated from two independent duplications of the first double-stranded RNA binding domain of loqs that occurred before the origin of the Aedes Stegomyia subgenus, around 31 million years ago. We show that the loqs2 gene is evolving under relaxed purifying selection at a faster pace than loqs, with evidence of neofunctionalization driven by positive selection. Accordingly, we observed that Loqs2 is localized mainly in the nucleus, different from R2D2 and both isoforms of Loqs that are cytoplasmic. In contrast to r2d2 and loqs, loqs2 expression is stage- and tissue-specific, restricted mostly to reproductive tissues in adult Ae. aegypti and Ae. albopictus. Transgenic mosquitoes engineered to express loqs2 ubiquitously undergo developmental arrest at larval stages that correlates with massive dysregulation of gene expression without major effects on microRNAs or other endogenous small RNAs, classically associated with RNA interference. Our results uncover the peculiar origin and neofunctionalization of loqs2 driven by positive selection. This study shows an example of unique adaptations in Aedes mosquitoes that could ultimately help explain their effectiveness as virus vectors.
Sections du résumé
BACKGROUND
BACKGROUND
Mosquito borne viruses, such as dengue, Zika, yellow fever and Chikungunya, cause millions of infections every year. These viruses are mostly transmitted by two urban-adapted mosquito species, Aedes aegypti and Aedes albopictus. Although mechanistic understanding remains largely unknown, Aedes mosquitoes may have unique adaptations that lower the impact of viral infection. Recently, we reported the identification of an Aedes specific double-stranded RNA binding protein (dsRBP), named Loqs2, that is involved in the control of infection by dengue and Zika viruses in mosquitoes. Preliminary analyses suggested that the loqs2 gene is a paralog of loquacious (loqs) and r2d2, two co-factors of the RNA interference (RNAi) pathway, a major antiviral mechanism in insects.
RESULTS
RESULTS
Here we analyzed the origin and evolution of loqs2. Our data suggest that loqs2 originated from two independent duplications of the first double-stranded RNA binding domain of loqs that occurred before the origin of the Aedes Stegomyia subgenus, around 31 million years ago. We show that the loqs2 gene is evolving under relaxed purifying selection at a faster pace than loqs, with evidence of neofunctionalization driven by positive selection. Accordingly, we observed that Loqs2 is localized mainly in the nucleus, different from R2D2 and both isoforms of Loqs that are cytoplasmic. In contrast to r2d2 and loqs, loqs2 expression is stage- and tissue-specific, restricted mostly to reproductive tissues in adult Ae. aegypti and Ae. albopictus. Transgenic mosquitoes engineered to express loqs2 ubiquitously undergo developmental arrest at larval stages that correlates with massive dysregulation of gene expression without major effects on microRNAs or other endogenous small RNAs, classically associated with RNA interference.
CONCLUSIONS
CONCLUSIONS
Our results uncover the peculiar origin and neofunctionalization of loqs2 driven by positive selection. This study shows an example of unique adaptations in Aedes mosquitoes that could ultimately help explain their effectiveness as virus vectors.
Identifiants
pubmed: 38273313
doi: 10.1186/s12915-024-01821-4
pii: 10.1186/s12915-024-01821-4
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
14Subventions
Organisme : Agence nationale pour la recherche (ANR)
ID : ANR-10-IDEX-0002
Organisme : Agence nationale pour la recherche (ANR)
ID : ANR-20-SFRI-0012
Organisme : Agence nationale pour la recherche (ANR)
ID : ANR-17-EURE-0023
Organisme : Agence nationale pour la recherche (ANR)
ID : ANR-10-LABX-0036
Organisme : Agence nationale pour la recherche (ANR)
ID : ANR-21-CE12-0024
Organisme : Conselho Nacional de Desenvolvimento Científico e Tecnológico
ID : 309468/2021-3
Organisme : Fundação de Amparo à Pesquisa do Estado de São Paulo
ID : 2021/06874-9
Informations de copyright
© 2024. The Author(s).
Références
Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, et al. The global distribution and burden of dengue. Nature. 2013;496:504–7.
pubmed: 23563266
pmcid: 3651993
doi: 10.1038/nature12060
Iwamura T, Guzman-Holst A, Murray KA. Accelerating invasion potential of disease vector Aedes aegypti under climate change. Nat Commun. 2020;11:2130.
pubmed: 32358588
pmcid: 7195482
doi: 10.1038/s41467-020-16010-4
Weaver SC, Charlier C, Vasilakis N, Lecuit M. Zika, Chikungunya, and other emerging vector-borne viral diseases. Annu Rev Med. 2018;69:395–408.
pubmed: 28846489
doi: 10.1146/annurev-med-050715-105122
Azar SR, Weaver SC. Vector competence: what has Zika virus taught us? Viruses. 2019;11:867.
pubmed: 31533267
pmcid: 6784050
doi: 10.3390/v11090867
Ferreira-de-Lima VH, Lima-Camara TN. Natural vertical transmission of dengue virus in Aedes aegypti and Aedes albopictus: a systematic review. Parasit Vectors. 2018;11:77.
pubmed: 29391071
pmcid: 5793400
doi: 10.1186/s13071-018-2643-9
Kauffman E, Payne A, Franke MA, Schmid MA, Harris E, Kramer LD. Rearing of Culex spp. and Aedes spp. Mosquitoes. Bio-Protoc. 2017;7:e2542.
pubmed: 29075656
pmcid: 5654580
de Almeida JP, Aguiar ER, Armache JN, Olmo RP, Marques JT. The virome of vector mosquitoes. Curr Opin Virol. 2021;49:7–12.
pubmed: 33991759
doi: 10.1016/j.coviro.2021.04.002
Chamberlain RW, Sudia WD. Mechanism of transmission of viruses by mosquitoes. Annu Rev Entomol. 1961;6:371–90.
pubmed: 13692218
doi: 10.1146/annurev.en.06.010161.002103
Aguiar ERGR, Olmo RP, Marques JT. Virus-derived small RNAs: molecular footprints of host–pathogen interactions. Wiley Interdiscip Rev RNA. 2016;7:824–37.
pubmed: 27170499
pmcid: 7169819
doi: 10.1002/wrna.1361
Olmo RP, Martins NE, Aguiar ERGR, Marques JT, Imler J-L. The insect reservoir of biodiversity for viruses and for antiviral mechanisms. An Acad Bras Ciênc. 2019;91(suppl 3):e20190122.
pubmed: 31166476
doi: 10.1590/0001-3765201920190122
Rosendo Machado S, van der Most T, Miesen P. Genetic determinants of antiviral immunity in dipteran insects – compiling the experimental evidence. Dev Comp Immunol. 2021;119:104010.
pubmed: 33476667
doi: 10.1016/j.dci.2021.104010
de Faria da S IJS, Olmo RP, Silva EG, Marques JT. dsRNA Sensing During Viral Infection: Lessons from Plants, Worms, Insects, and Mammals. J Interferon Cytokine Res. 2013;33:239–53.
doi: 10.1089/jir.2013.0026
Marques JT, Kim K, Wu P-H, Alleyne TM, Jafari N, Carthew RW. Loqs and R2D2 act sequentially in the siRNA pathway in drosophila. Nat Struct Mol Biol. 2010;17:24–30.
pubmed: 20037596
doi: 10.1038/nsmb.1735
Haac ME, Anderson MAE, Eggleston H, Myles KM, Adelman ZN. The hub protein loquacious connects the microRNA and short interfering RNA pathways in mosquitoes. Nucleic Acids Res. 2015;43:3688–700.
pubmed: 25765650
pmcid: 4402513
doi: 10.1093/nar/gkv152
Obbard DJ, Gordon KHJ, Buck AH, Jiggins FM. The evolution of RNAi as a defence against viruses and transposable elements. Philos Trans R Soc B Biol Sci. 2009;364:99–115.
doi: 10.1098/rstb.2008.0168
Palmer WH, Hadfield JD, Obbard DJ. RNA-interference pathways display high rates of adaptive protein evolution in multiple invertebrates. Genetics. 2018;208:1585–99.
pubmed: 29437826
pmcid: 5887150
doi: 10.1534/genetics.117.300567
Bernhardt SA, Simmons MP, Olson KE, Beaty BJ, Blair CD, Black WC. Rapid intraspecific evolution of miRNA and siRNA genes in the mosquito Aedes aegypti. PLoS ONE. 2012;7:e44198.
pubmed: 23028502
pmcid: 3448618
doi: 10.1371/journal.pone.0044198
Dowling D, Pauli T, Donath A, Meusemann K, Podsiadlowski L, Petersen M, et al. Phylogenetic origin and diversification of RNAi pathway genes in insects. Genome Biol Evol. 2016;8:3784–93.
pubmed: 28062756
pmcid: 5521735
Olmo RP, Ferreira AGA, Izidoro-Toledo TC, Aguiar ERGR, de Faria IJS, de Souza KPR, et al. Control of dengue virus in the midgut of Aedes aegypti by ectopic expression of the dsRNA-binding protein Loqs2. Nat Microbiol. 2018;3:1385–93.
pubmed: 30374169
doi: 10.1038/s41564-018-0268-6
Amos B, Aurrecoechea C, Barba M, Barreto A, Basenko EY, Bażant W, et al. VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center. Nucleic Acids Res. 2022;50:D898-911.
pubmed: 34718728
doi: 10.1093/nar/gkab929
Soghigian J, Sither C, Justi SA, Morinaga G, Cassel BK, Vitek CJ, et al. Phylogenomics reveals the history of host use in mosquitoes. Nat Commun. 2023;14:6252.
pubmed: 37803007
pmcid: 10558525
doi: 10.1038/s41467-023-41764-y
Waterhouse RM, Wyder S, Zdobnov EM. The Aedes aegypti genome: a comparative perspective. Insect Mol Biol. 2008;17:1–8.
pubmed: 18237279
doi: 10.1111/j.1365-2583.2008.00772.x
Crawford JE, Alves JM, Palmer WJ, Day JP, Sylla M, Ramasamy R, et al. Population genomics reveals that an anthropophilic population of Aedes aegypti mosquitoes in West Africa recently gave rise to American and Asian populations of this major disease vector. BMC Biol. 2017;15:16.
pubmed: 28241828
pmcid: 5329927
doi: 10.1186/s12915-017-0351-0
Chung JM, Park JE, Hwang HJ, Sang MK, Min HR, Cho HC, et al. Transcriptome studies of the floodwater mosquito, Aedes vexans (Diptera: culicidae) with potential as secondary vectors using Illumina HiSeq 4,000 sequencing. Entomol Res. 2020;50:563–74.
doi: 10.1111/1748-5967.12440
Shi M, Neville P, Nicholson J, Eden J-S, Imrie A, Holmes EC. High-resolution metatranscriptomics reveals the ecological dynamics of mosquito-associated RNA viruses in Western Australia. J Virol. 2017;91:e00680-e717.
pubmed: 28637756
pmcid: 5553174
doi: 10.1128/JVI.00680-17
Caragata EP, Pais FS, Baton LA, Silva JBL, Sorgine MHF, Moreira LA. The transcriptome of the mosquito Aedes fluviatilis (Diptera: Culicidae), and transcriptional changes associated with its native Wolbachia infection. BMC Genomics. 2017;18:6.
pubmed: 28049478
pmcid: 5210266
doi: 10.1186/s12864-016-3441-4
Redmond SN, Sharma A, Sharakhov I, Tu Z, Sharakhova M, Neafsey DE. Linked-read sequencing identifies abundant microinversions and introgression in the arboviral vector Aedes aegypti. BMC Biol. 2020;18:26.
pubmed: 32164699
pmcid: 7068900
doi: 10.1186/s12915-020-0757-y
Chagas AC, Calvo E, Rios-Velásquez CM, Pessoa FA, Medeiros JF, Ribeiro JM. A deep insight into the sialotranscriptome of the mosquito, Psorophora albipes. BMC Genomics. 2013;14:875.
pubmed: 24330624
pmcid: 3878727
doi: 10.1186/1471-2164-14-875
Arraes FBM, Martins-de-Sa D, Noriega Vasquez DD, Melo BP, Faheem M, de Macedo LLP, et al. Dissecting protein domain variability in the core RNA interference machinery of five insect orders. RNA Biol. 2020;0:1–29.
Jouravleva K, Golovenko D, Demo G, Dutcher RC, Hall TMT, Zamore PD, et al. Structural basis of microRNA biogenesis by Dicer-1 and its partner protein Loqs-PB. Mol Cell. 2022;82:4049-4063.e6.
pubmed: 36182693
pmcid: 9637774
doi: 10.1016/j.molcel.2022.09.002
Dias R, Manny A, Kolaczkowski O, Kolaczkowski B. Convergence of domain architecture, structure, and ligand affinity in animal and plant RNA-binding proteins. Mol Biol Evol. 2017;34:1429–44.
pubmed: 28333205
pmcid: 5435087
doi: 10.1093/molbev/msx090
Tants J-N, Fesser S, Kern T, Stehle R, Geerlof A, Wunderlich C, et al. Molecular basis for asymmetry sensing of siRNAs by the Drosophila Loqs-PD/Dcr-2 complex in RNA interference. Nucleic Acids Res. 2017;45:12536–50.
pubmed: 29040648
pmcid: 5716069
doi: 10.1093/nar/gkx886
Holm L. Using Dali for Protein Structure Comparison. In: Gáspári Z, editor. Structural Bioinformatics: Methods and Protocols. New York: Springer, US; 2020. p. 29–42.
doi: 10.1007/978-1-0716-0270-6_3
Ohno S. Evolution by Gene Duplication. Berlin, Heidelberg: Springer Berlin Heidelberg; 1970.
Lynch M, Conery JS. The evolutionary fate and consequences of duplicate genes. Science. 2000;290:1151–5.
pubmed: 11073452
doi: 10.1126/science.290.5494.1151
Prince VE, Pickett FB. Splitting pairs: the diverging fates of duplicated genes. Nat Rev Genet. 2002;3:827–37.
pubmed: 12415313
doi: 10.1038/nrg928
Wertheim JO, Murrell B, Smith MD, Kosakovsky Pond SL, Scheffler K. RELAX: detecting relaxed selection in a phylogenetic framework. Mol Biol Evol. 2015;32:820–32.
pubmed: 25540451
doi: 10.1093/molbev/msu400
Masliah G, Barraud P, Allain FH-T. RNA recognition by double-stranded RNA binding domains: a matter of shape and sequence. Cell Mol Life Sci CMLS. 2013;70:1875–95.
pubmed: 22918483
Wang X, Vukovic L, Koh HR, Schulten K, Myong S. Dynamic profiling of double-stranded RNA binding proteins. Nucleic Acids Res. 2015;43:7566–76.
pubmed: 26184879
pmcid: 4551942
doi: 10.1093/nar/gkv726
Smith MD, Wertheim JO, Weaver S, Murrell B, Scheffler K, Kosakovsky Pond SL. Less is more: an adaptive branch-site random effects model for efficient detection of episodic diversifying selection. Mol Biol Evol. 2015;32:1342–53.
pubmed: 25697341
pmcid: 4408413
doi: 10.1093/molbev/msv022
McDonald JH, Kreitman M. Adaptive protein evolution at the Adh locus in Drosophila. Nature. 1991;351:652–4.
pubmed: 1904993
doi: 10.1038/351652a0
Murga-Moreno J, Coronado-Zamora M, Hervas S, Casillas S, Barbadilla A. iMKT: the integrative McDonald and Kreitman test. Nucleic Acids Res. 2019;47:W283–8.
pubmed: 31081014
pmcid: 6602517
doi: 10.1093/nar/gkz372
Zhai W, Nielsen R, Slatkin M. An investigation of the statistical power of neutrality tests based on comparative and population genetic data. Mol Biol Evol. 2009;26:273–83.
pubmed: 18922762
doi: 10.1093/molbev/msn231
Parsch J, Zhang Z, Baines JF. The influence of demography and weak selection on the McDonald-Kreitman test: an empirical study in Drosophila. Mol Biol Evol. 2009;26:691–8.
pubmed: 19126864
doi: 10.1093/molbev/msn297
Obbard DJ, Jiggins FM, Halligan DL, Little TJ. Natural selection drives extremely rapid evolution in antiviral RNAi genes. Curr Biol. 2006;16:580–5.
pubmed: 16546082
doi: 10.1016/j.cub.2006.01.065
Fredericks AC, Russell TA, Wallace LE, Davidson AD, Fernandez-Sesma A, Maringer K. Aedes aegypti (Aag2)-derived clonal mosquito cell lines reveal the effects of pre-existing persistent infection with the insect-specific bunyavirus Phasi Charoen-like virus on arbovirus replication. PLoS Negl Trop Dis. 2019;13:e0007346.
pubmed: 31693659
pmcid: 6860454
doi: 10.1371/journal.pntd.0007346
Sharma A, Reyes J, Borgmeyer D, Ayala-Chavez C, Snow K, Arshad F, et al. The sugar substitute stevia shortens the lifespan of Aedes aegypti potentially by N-linked protein glycosylation. Sci Rep. 2020;10:6195.
pubmed: 32277123
pmcid: 7148303
doi: 10.1038/s41598-020-63050-3
Akbari OS, Antoshechkin I, Amrhein H, Williams B, Diloreto R, Sandler J, et al. The developmental transcriptome of the mosquito Aedes aegypti, an invasive species and major arbovirus vector. G3 Genes Genomes Genet. 2013;3:1493–509.
doi: 10.1534/g3.113.006742
Biedler JK, Hu W, Tae H, Tu Z. Identification of early zygotic genes in the yellow fever mosquito Aedes aegypti and discovery of a motif involved in early zygotic genome activation. PLoS ONE. 2012;7:e33933.
pubmed: 22457801
pmcid: 3311545
doi: 10.1371/journal.pone.0033933
Shi Z-K, Wen D, Chang M-M, Sun X-M, Wang Y-H, Cheng C-H, et al. Juvenile hormone-sensitive ribosomal activity enhances viral replication in Aedes aegypti. mSystems. 2021;6:e01190-20.
pubmed: 34061577
pmcid: 8269256
doi: 10.1128/mSystems.01190-20
Dong S, Behura SK, Franz AWE. The midgut transcriptome of Aedes aegypti fed with saline or protein meals containing chikungunya virus reveals genes potentially involved in viral midgut escape. BMC Genomics. 2017;18:382.
pubmed: 28506207
pmcid: 5433025
doi: 10.1186/s12864-017-3775-6
Matthews BJ, McBride CS, DeGennaro M, Despo O, Vosshall LB. The neurotranscriptome of the Aedes aegypti mosquito. BMC Genomics. 2016;17:32.
pubmed: 26738925
pmcid: 4704297
doi: 10.1186/s12864-015-2239-0
Tu Z. Transcriptome sequencing of life stages and tissues of the yellow fever mosquito Ae. aegypti. 2012.
Matthews BJ, Dudchenko O, Kingan SB, Koren S, Antoshechkin I, Crawford JE, et al. Improved reference genome of Aedes aegypti informs arbovirus vector control. Nature. 2018;563:501–7.
pubmed: 30429615
pmcid: 6421076
doi: 10.1038/s41586-018-0692-z
Li M, Yang T, Bui M, Gamez S, Wise T, Kandul NP, et al. Suppressing mosquito populations with precision guided sterile males. Nat Commun. 2021;12:5374.
pubmed: 34508072
pmcid: 8433431
doi: 10.1038/s41467-021-25421-w
Ribeiro JMC, Martin-Martin I, Arcà B, Calvo E. A deep insight into the Sialome of male and female Aedes aegypti mosquitoes. PLoS ONE. 2016;11:e0151400.
pubmed: 26999592
pmcid: 4801386
doi: 10.1371/journal.pone.0151400
Tsujimoto H, Hanley KA, Sundararajan A, Devitt NP, Schilkey FD, Hansen IA. Dengue virus serotype 2 infection alters midgut and carcass gene expression in the Asian tiger mosquito, Aedes albopictus. PLOS ONE. 2017;12:e0171345.
pubmed: 28152011
pmcid: 5289563
doi: 10.1371/journal.pone.0171345
Gamez S, Antoshechkin I, Mendez-Sanchez SC, Akbari OS. The developmental transcriptome of Aedes albopictus, a major worldwide human disease vector. G3 GenesGenomesGenetics. 2020;10:1051–62.
doi: 10.1534/g3.119.401006
Gomulski LM, Manni M, Carraretto D, Nolan T, Lawson D, Ribeiro JM, et al. Transcriptional variation of sensory-related genes in natural populations of Aedes albopictus. BMC Genomics. 2020;21:547.
pubmed: 32767966
pmcid: 7430840
doi: 10.1186/s12864-020-06956-6
Vedururu RK, Neave MJ, Sundaramoorthy V, Green D, Harper JA, Gorry PR, et al. Whole transcriptome analysis of Aedes albopictus mosquito head and thorax post-chikungunya virus infection. Pathogens. 2019;8:132.
pubmed: 31461898
pmcid: 6789441
doi: 10.3390/pathogens8030132
Basrur NS, De Obaldia ME, Morita T, Herre M, Von Heynitz RK, Tsitohay YN, et al. Fruitless mutant male mosquitoes gain attraction to human odor. eLife. 2020;9:e63982.
pubmed: 33284111
pmcid: 7806257
doi: 10.7554/eLife.63982
Raddi G, Barletta ABF, Efremova M, Ramirez JL, Cantera R, Teichmann SA, et al. Mosquito cellular immunity at single-cell resolution. Science. 2020;369:1128–32.
pubmed: 32855340
pmcid: 8405044
doi: 10.1126/science.abc0322
Yoon Y, Klomp J, Martin-Martin I, Criscione F, Calvo E, Ribeiro J, et al. Embryo polarity in moth flies and mosquitoes relies on distinct old genes with localized transcript isoforms. eLife. 2019;8:e46711.
pubmed: 31591963
pmcid: 6783274
doi: 10.7554/eLife.46711
Manģera CM, Khamis FM, Awuoche EO, Hassanali A, Ombura FLO, Mireji PO. Transcriptomic response of Anopheles gambiae sensu stricto mosquito larvae to Curry tree (Murraya koenigii) phytochemicals. Parasit Vectors. 2021;14:1.
pubmed: 33388087
doi: 10.1186/s13071-020-04505-4
Hall AB, Papathanos P-A, Sharma A, Cheng C, Akbari OS, Assour L, et al. Radical remodeling of the Y chromosome in a recent radiation of malaria mosquitoes. Proc Natl Acad Sci. 2016;113:E2114–23.
Pinheiro-Silva R, Borges L, Coelho LP, Cabezas-Cruz A, Valdés JJ, Do Rosário V, et al. Gene expression changes in the salivary glands of anopheles coluzzii elicited by plasmodium berghei infection. Parasit Vectors. 2015;8:485.
pubmed: 26395987
pmcid: 4580310
doi: 10.1186/s13071-015-1079-8
Ruiz JL, Yerbanga RS, Lefèvre T, Ouedraogo JB, Corces VG, Gómez-Díaz E. Chromatin changes in Anopheles gambiae induced by plasmodium falciparum infection. Epigenetics Chromatin. 2019;12:5.
pubmed: 30616642
pmcid: 6322293
doi: 10.1186/s13072-018-0250-9
Rose G, Krzywinski J. Developmental transcriptome of sexed Anopheles gambiae embryos. 2015.
Rose G, Krzywinski J. Developmental transcriptome of sexed Anopheles gambiae pupae. 2015.
Rose G, Krzywinski J. Developmental transcriptome of sexed Anopheles gambiae larvae and adult mosquitoes. 2015.
Assis R, Bachtrog D. Neofunctionalization of young duplicate genes in drosophila. Proc Natl Acad Sci U S A. 2013;110:17409–14.
pubmed: 24101476
pmcid: 3808614
doi: 10.1073/pnas.1313759110
Kaessmann H. Origins, evolution, and phenotypic impact of new genes. Genome Res. 2010;20:1313–26.
pubmed: 20651121
pmcid: 2945180
doi: 10.1101/gr.101386.109
Salazar MI, Richardson JH, Sánchez-Vargas I, Olson KE, Beaty BJ. Dengue virus type 2: replication and tropisms in orally infected Aedes aegypti mosquitoes. BMC Microbiol. 2007;7:9.
pubmed: 17263893
pmcid: 1797809
doi: 10.1186/1471-2180-7-9
Lutrat C, Burckbuchler M, Olmo RP, Beugnon R, Fontaine A, Akbari OS, et al. Combining two genetic sexing strains allows sorting of non-transgenic males for Aedes genetic control. Commun Biol. 2023;6:646.
pubmed: 37328568
pmcid: 10275924
doi: 10.1038/s42003-023-05030-7
Li M, Yang T, Kandul NP, Bui M, Gamez S, Raban R, et al. Development of a confinable gene drive system in the human disease vector Aedes aegypti. Life. 2020;9:e51701.
Rozen-Gagnon K, Gu M, Luna JM, Luo J-D, Yi S, Novack S, et al. Argonaute-CLIP delineates versatile, functional RNAi networks in Aedes aegypti, a major vector of human viruses. Cell Host Microbe. 2021;29:834-848.e13.
pubmed: 33794184
pmcid: 8699793
doi: 10.1016/j.chom.2021.03.004
Brennecke J, Aravin AA, Stark A, Dus M, Kellis M, Sachidanandam R, et al. Discrete small RNA-generating loci as master regulators of transposon activity in drosophila. Cell. 2007;128:1089–103.
pubmed: 17346786
doi: 10.1016/j.cell.2007.01.043
Dong Y, Dong S, Dizaji NB, Rutkowski N, Pohlenz T, Myles K, et al. The Aedes aegypti siRNA pathway mediates broad-spectrum defense against human pathogenic viruses and modulates antibacterial and antifungal defenses. PLoS Biol. 2022;20:e3001668.
pubmed: 35679279
pmcid: 9182253
doi: 10.1371/journal.pbio.3001668
Schmidt EE. Transcriptional promiscuity in testes. Curr Biol. 1996;6:768–9.
pubmed: 8805310
doi: 10.1016/S0960-9822(02)00589-4
White-Cooper H, Davidson I. Unique aspects of transcription regulation in male germ cells. Cold Spring Harb Perspect Biol. 2011;3:a002626.
pubmed: 21555408
pmcid: 3119912
doi: 10.1101/cshperspect.a002626
Vastenhouw NL, Cao WX, Lipshitz HD. The maternal-to-zygotic transition revisited. Dev Camb Engl. 2019;146:dev161471.
Heyam A, Coupland CE, Dégut C, Haley RA, Baxter NJ, Jakob L, et al. Conserved asymmetry underpins homodimerization of Dicer-associated double-stranded RNA-binding proteins. Nucleic Acids Res. 2017;45:12577–84.
pubmed: 29045748
pmcid: 5716075
doi: 10.1093/nar/gkx928
Hartig JV, Förstemann K. Loqs-PD and R2D2 define independent pathways for RISC generation in Drosophila. Nucleic Acids Res. 2011;39:3836–51.
pubmed: 21245036
pmcid: 3089465
doi: 10.1093/nar/gkq1324
Trettin KD, Sinha NK, Eckert DM, Apple SE, Bass BL. Loquacious-PD facilitates Drosophila Dicer-2 cleavage through interactions with the helicase domain and dsRNA. Proc Natl Acad Sci. 2017;114:E7939–48.
pubmed: 28874570
pmcid: 5617286
doi: 10.1073/pnas.1707063114
Harshil Patel, Ewels P, Peltzer A, Hammarén R, Botvinnik O, Sturm G, et al. nf-core/rnaseq: nf-core/rnaseq v3.0 - Silver Shark. 2020.
Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal. 2011;17:10.
doi: 10.14806/ej.17.1.200
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15–21.
pubmed: 23104886
doi: 10.1093/bioinformatics/bts635
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for illumina sequence data. Bioinformatics. 2014;30:2114–20.
pubmed: 24695404
pmcid: 4103590
doi: 10.1093/bioinformatics/btu170
Magoc T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27:2957–63.
pubmed: 21903629
pmcid: 3198573
doi: 10.1093/bioinformatics/btr507
Vasimuddin Md, Misra S, Li H, Aluru S. Efficient architecture-aware acceleration of BWA-MEM for multicore systems. In: 2019 IEEE International parallel and distributed processing symposium (IPDPS). 2019. p. 314–24.
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25:2078–9.
pubmed: 19505943
pmcid: 2723002
doi: 10.1093/bioinformatics/btp352
Broad Institute. Picard Toolkit. 2019.
Diesh C, Stevens GJ, Xie P, De Jesus MT, Hershberg EA, Leung A, et al. JBrowse 2: a modular genome browser with views of synteny and structural variation. Genome Biol. 2023;24:74.
pubmed: 37069644
pmcid: 10108523
doi: 10.1186/s13059-023-02914-z
Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017;14:417–9.
pubmed: 28263959
pmcid: 5600148
doi: 10.1038/nmeth.4197
R Core Team. R: A Language and Environment for Statistical Computing. 2021.
Robinson MD, Oshlack A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 2010;11:R25.
pubmed: 20196867
pmcid: 2864565
doi: 10.1186/gb-2010-11-3-r25
Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40.
pubmed: 19910308
doi: 10.1093/bioinformatics/btp616
Soneson C, Love MI, Robinson MD. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Research. 2015;4:1521.
pubmed: 26925227
doi: 10.12688/f1000research.7563.1
Löytynoja A, Goldman N. Uniting alignments and trees. Science. 2009;324:1528–9.
pubmed: 19541988
doi: 10.1126/science.1175949
Ranwez V, Harispe S, Delsuc F, Douzery EJP. MACSE: multiple alignment of coding SEquences accounting for frameshifts and stop codons. PLoS ONE. 2011;6:e22594.
pubmed: 21949676
pmcid: 3174933
doi: 10.1371/journal.pone.0022594
Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, von Haeseler A, et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol. 2020;37:1530–4.
pubmed: 32011700
pmcid: 7182206
doi: 10.1093/molbev/msaa015
Andrew Rambaut. FigTree. 2018.
Minh BQ, Dang CC, Vinh LS, Lanfear R. QMaker: fast and accurate method to estimate empirical models of protein evolution. Syst Biol. 2021;70:1046–60.
pubmed: 33616668
pmcid: 8357343
doi: 10.1093/sysbio/syab010
Webb B, Sali A. Comparative Protein Structure Modeling Using MODELLER. Curr Protoc Bioinforma. 2016;54:5.6.1-5.6.37.
Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Crystallogr. 1993;26:283–91.
doi: 10.1107/S0021889892009944
Schrödinger. The PyMOL Molecular Graphics System. 2021.
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10.
pubmed: 2231712
doi: 10.1016/S0022-2836(05)80360-2
Paradis E, Schliep K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics. 2019;35:526–8.
pubmed: 30016406
doi: 10.1093/bioinformatics/bty633
Weaver S, Shank SD, Spielman SJ, Li M, Muse SV, Kosakovsky Pond SL. Datamonkey 2.0: a modern web application for characterizing selective and other evolutionary processes. Mol Biol Evol. 2018;35:773–7.
pubmed: 29301006
pmcid: 5850112
doi: 10.1093/molbev/msx335
Kosakovsky Pond SL, Frost SDW. Not so different after all: a comparison of methods for detecting amino acid sites under selection. Mol Biol Evol. 2005;22:1208–22.
pubmed: 15703242
doi: 10.1093/molbev/msi105
McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20:1297–303.
pubmed: 20644199
pmcid: 2928508
doi: 10.1101/gr.107524.110
Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics. 2011;27:2156–8.
pubmed: 21653522
pmcid: 3137218
doi: 10.1093/bioinformatics/btr330
Engler C, Marillonnet S. Combinatorial DNA assembly using Golden Gate cloning. Methods Mol Biol Clifton NJ. 2013;1073:141–56.
doi: 10.1007/978-1-62703-625-2_12
Volohonsky G, Terenzi O, Soichot J, Naujoks DA, Nolan T, Windbichler N, et al. Tools for Anopheles gambiae Transgenesis. G3 Bethesda Md. 2015;5:1151–63.
pubmed: 25869647
doi: 10.1534/g3.115.016808
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci. 2005;102:15545–50.
pubmed: 16199517
pmcid: 1239896
doi: 10.1073/pnas.0506580102
Korotkevich G, Sukhov V, Budin N, Shpak B, Artyomov MN, Sergushichev A. Fast gene set enrichment analysis. bioRxiv. 2021. https://doi.org/10.1101/060012 .
Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10:R25.
pubmed: 19261174
pmcid: 2690996
doi: 10.1186/gb-2009-10-3-r25
Stajich JE, Block D, Boulez K, Brenner SE, Chervitz SA, Dagdigian C, et al. The bioperl toolkit: perl modules for the life sciences. Genome Res. 2002;12:1611–8.
pubmed: 12368254
pmcid: 187536
doi: 10.1101/gr.361602
Team TPD. pandas-dev/pandas: Pandas. 2023.
Wickham H. Reshaping data with the reshape package. J Stat Softw. 2007;21.
Wickham H. ggplot2: Elegant Graphics for Data Analysis. 2nd ed. Cham: Springer International Publishing Imprint: Springer; 2016.
doi: 10.1007/978-3-319-24277-4
Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847–9.
pubmed: 27207943
doi: 10.1093/bioinformatics/btw313
Gu Z, Gu L, Eils R, Schlesner M, Brors B. circlize implements and enhances circular visualization in R. Bioinformatics. 2014;30:2811–2.
pubmed: 24930139
doi: 10.1093/bioinformatics/btu393