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. 2015 Jan 2;347(6217):1258522.
doi: 10.1126/science.1258522. Epub 2014 Nov 27.

Mosquito genomics. Highly evolvable malaria vectors: the genomes of 16 Anopheles mosquitoes

Daniel E Neafsey 1 , Robert M Waterhouse 2 , Mohammad R Abai 3 , Sergey S Aganezov 4 , Max A Alekseyev 4 , James E Allen 5 , James Amon 6 , Bruno Arcà 7 , Peter Arensburger 8 , Gleb Artemov 9 , Lauren A Assour 10 , Hamidreza Basseri 3 , Aaron Berlin 11 , Bruce W Birren 11 , Stephanie A Blandin 12 , Andrew I Brockman 13 , Thomas R Burkot 14 , Austin Burt 15 , Clara S Chan 16 , Cedric Chauve 17 , Joanna C Chiu 18 , Mikkel Christensen 5 , Carlo Costantini 19 , Victoria L M Davidson 20 , Elena Deligianni 21 , Tania Dottorini 13 , Vicky Dritsou 22 , Stacey B Gabriel 23 , Wamdaogo M Guelbeogo 24 , Andrew B Hall 25 , Mira V Han 26 , Thaung Hlaing 27 , Daniel S T Hughes 28 , Adam M Jenkins 29 , Xiaofang Jiang 30 , Irwin Jungreis 16 , Evdoxia G Kakani 31 , Maryam Kamali 32 , Petri Kemppainen 33 , Ryan C Kennedy 34 , Ioannis K Kirmitzoglou 35 , Lizette L Koekemoer 36 , Njoroge Laban 37 , Nicholas Langridge 5 , Mara K N Lawniczak 13 , Manolis Lirakis 38 , Neil F Lobo 39 , Ernesto Lowy 5 , Robert M MacCallum 13 , Chunhong Mao 40 , Gareth Maslen 5 , Charles Mbogo 41 , Jenny McCarthy 8 , Kristin Michel 20 , Sara N Mitchell 42 , Wendy Moore 43 , Katherine A Murphy 18 , Anastasia N Naumenko 32 , Tony Nolan 13 , Eva M Novoa 16 , Samantha O'Loughlin 15 , Chioma Oringanje 43 , Mohammad A Oshaghi 3 , Nazzy Pakpour 44 , Philippos A Papathanos 45 , Ashley N Peery 32 , Michael Povelones 46 , Anil Prakash 47 , David P Price 48 , Ashok Rajaraman 17 , Lisa J Reimer 49 , David C Rinker 50 , Antonis Rokas 51 , Tanya L Russell 14 , N'Fale Sagnon 24 , Maria V Sharakhova 32 , Terrance Shea 11 , Felipe A Simão 52 , Frederic Simard 19 , Michel A Slotman 53 , Pradya Somboon 54 , Vladimir Stegniy 9 , Claudio J Struchiner 55 , Gregg W C Thomas 56 , Marta Tojo 57 , Pantelis Topalis 21 , José M C Tubio 58 , Maria F Unger 39 , John Vontas 38 , Catherine Walton 33 , Craig S Wilding 59 , Judith H Willis 60 , Yi-Chieh Wu 61 , Guiyun Yan 62 , Evgeny M Zdobnov 52 , Xiaofan Zhou 63 , Flaminia Catteruccia 31 , George K Christophides 13 , Frank H Collins 39 , Robert S Cornman 60 , Andrea Crisanti 45 , Martin J Donnelly 64 , Scott J Emrich 10 , Michael C Fontaine 65 , William Gelbart 66 , Matthew W Hahn 67 , Immo A Hansen 48 , Paul I Howell 68 , Fotis C Kafatos 13 , Manolis Kellis 16 , Daniel Lawson 5 , Christos Louis 69 , Shirley Luckhart 44 , Marc A T Muskavitch 70 , José M Ribeiro 71 , Michael A Riehle 43 , Igor V Sharakhov 72 , Zhijian Tu 73 , Laurence J Zwiebel 74 , Nora J Besansky 75
Affiliations

Mosquito genomics. Highly evolvable malaria vectors: the genomes of 16 Anopheles mosquitoes

Daniel E Neafsey et al. Science. .

Abstract

Variation in vectorial capacity for human malaria among Anopheles mosquito species is determined by many factors, including behavior, immunity, and life history. To investigate the genomic basis of vectorial capacity and explore new avenues for vector control, we sequenced the genomes of 16 anopheline mosquito species from diverse locations spanning ~100 million years of evolution. Comparative analyses show faster rates of gene gain and loss, elevated gene shuffling on the X chromosome, and more intron losses, relative to Drosophila. Some determinants of vectorial capacity, such as chemosensory genes, do not show elevated turnover but instead diversify through protein-sequence changes. This dynamism of anopheline genes and genomes may contribute to their flexible capacity to take advantage of new ecological niches, including adapting to humans as primary hosts.

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Figures

Figure 1
Figure 1. Geography, vector status, molecular phylogeny, gene orthology, and genome alignability of the 16 newly sequenced anopheline mosquitoes and selected other dipterans
(A) Global geographic distributions of the 16 sampled anophelines and the previously sequenced An. gambiae and An. darlingi. Ranges are colored for each species or group of species as shown in panel B, e.g. light blue for An. farauti. (B) The maximum likelihood molecular phylogeny of all sequenced anophelines and selected dipteran outgroups. Shapes between branch termini and species names indicate vector status (rectangles, major vectors; ellipses, minor vectors, triangles, non-vectors) and are colored according to geographic ranges shown in panel A. (C) Barplots show total gene counts for each species partitioned according to their orthology profiles; from ancient genes found across insects to lineage-restricted and species-specific genes. (D) Heat map illustrating the density (in 2 kb sliding windows) of whole genome alignments along the lengths of An. gambiae chromosomal arms: from white where An. gambiae aligns to no other species, to red where An. gambiae aligns to all the other anophelines.
Figure 2
Figure 2. Patterns of anopheline chromosomal evolution
(A) Anopheline genomes have conserved gene membership on chromosome arms (‘elements’; colored and labeled 1–5). Unlike Drosophila, chromosome elements reshuffle between chromosomes via translocations as intact elements, and do not show fissions or fusions. The tree depicts the supported molecular topology for the species studied. (B) Conserved synteny blocks decay rapidly within chromosomal arms as the phylogenetic distance increases between species. Moving left to right, the dotplot panels show gene-level synteny between chromosome 2R of An. gambiae (x axis) and inferred ancestral sequences (y axes; inferred using PATHGROUPS) at increasing evolutionary timescales (MYA = million years ago) estimated via an ultrametric phylogeny. Gray horizontal lines represent scaffold breaks. Discontinuity of the red lines/dots indicates rearrangement. (C) Anopheline X chromosomes exhibit higher rates of rearrangement (P < ×ばつ10−5), measured as breaks per megabase (Mb) per million years (MY), compared with autosomes, despite a paucity of polymorphic inversions on the X. (D) The anopheline X chromosome also displays a higher rate of gene movement to other chromosomal arms than any of the autosomes. Chromosomal elements are labeled around the perimeter; internal bands are colored according to the chromosomal element source and match element colors in panels A and C. Bands are sized to indicate the relative ratio of genes imported versus exported for each chromosomal element, and the relative allocation of exported genes to other elements.
Figure 3
Figure 3. Contrasting evolutionary properties of selected gene functional categories
Examined evolutionary properties of orthologous groups of genes include: a measure of amino acid conservation/divergence (evolutionary rate), a measure of selective pressure (dN/dS), a measure of gene duplication in terms of mean gene copy-number per species (number of genes), and a measure of ortholog universality in terms of number of species with orthologs (number of species). Notched boxplots show medians, extend to the first and third quartiles, and their widths are proportional to the number of orthologous groups in each functional category. Functional categories derive from curated lists associated with various functions/processes as well as annotated Gene Ontology or InterPro categories (denoted by asterisks).
Figure 4
Figure 4. Phylogeny-based insights into anopheline biology
(A) Maximum-likelihood amino acid based phylogenetic tree of three transglutaminase enzymes (TG1 (green), TG2 (yellow) and TG3 (red)) in 14 anopheline species with Culex quinquefasciatus (Cxqu), Ae. aegypti (Aeae) and D. melanogaster (Dmel) serving as outgroups. TG3 is the enzyme responsible for the formation of the male mating plug in An. gambiae, acting upon the substrate Plugin, the most abundant mating plug protein. Higher rates of evolution for plug-forming TG3 are supported by elevated levels of dN. Mating plug phenotypes are noted where known within the TG3 clade. (B) Concerted evolution in CPFL cuticular proteins. Species symbols used are the same as in panel a. In contrast to the TG1/TG2/TG3 phylogeny, CPFL paralogs cluster by sub-generic clades rather than individually recapitulating the species phylogeny. Gene family size variation among species may reflect both gene gain/loss and variation in gene set completeness. (C) Odorant receptor (OR) observed gene counts and inferred ancestral gene counts on an ultrametric phylogeny. At least 10 OR genes were gained on the branch leading to the common ancestor of the An. gambiae species complex, though the overall number of OR genes does not vary dramatically across the genus.
Figure 5
Figure 5. Genesis of novel anopheline genes
(A) Retrotransposition of the E2D/effete gene generated a ubiquitin-conjugating enzyme at the base of the genus, which exhibits much higher sequence divergence than the original multi-exon gene. WebLogo plots contrast the amino acid conservation of the original effete gene with the diversification of the retrotransposed copy (residues 38–75; species represented are An. minimus, An. dirus, An. funestus, An. farauti, An. atroparvus, An. sinensis, An. darlingi, and An. albimanus). (B) The SG7 salivary protein-encoding gene was generated from the C-terminal half of the 30 KDa gene. SG7 then underwent tandem duplication and intron loss to generate another salivary protein, SG7-2. Numerals indicate length of segments in base pairs. (C) The origin of STAT1, a signal transducer and activator of transcription gene involved in immunity, occurred through a retrotransposition event in the Cellia ancestor after divergence from An. dirus and An. farauti. The intronless STAT1 is much more divergent than its multi-exon progenitor, STAT2, and has been maintained in all descendent species. An independent retrotransposition event created a retrogene copy in An. atroparvus, which is also more divergent than its progenitor.

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