The neurotranscriptome of the Aedes aegypti mosquito
© Matthews et al. 2016
Received: 3 September 2015
Accepted: 24 November 2015
Published: 6 January 2016
A complete genome sequence and the advent of genome editing open up non-traditional model organisms to mechanistic genetic studies. The mosquito Aedes aegypti is an important vector of infectious diseases such as dengue, chikungunya, and yellow fever and has a large and complex genome, which has slowed annotation efforts. We used comprehensive transcriptomic analysis of adult gene expression to improve the genome annotation and to provide a detailed tissue-specific catalogue of neural gene expression at different adult behavioral states.
We carried out deep RNA sequencing across all major peripheral male and female sensory tissues, the brain and (female) ovary. Furthermore, we examined gene expression across three important phases of the female reproductive cycle, a remarkable example of behavioral switching in which a female mosquito alternates between obtaining blood-meals from humans and laying eggs. Using genome-guided alignments and de novo transcriptome assembly, our re-annotation includes 572 new putative protein-coding genes and updates to 13.5 and 50.3 % of existing transcripts within coding sequences and untranslated regions, respectively. Using this updated annotation, we detail gene expression in each tissue, identifying large numbers of transcripts regulated by blood-feeding and sexually dimorphic transcripts that may provide clues to the biology of male- and female-specific behaviors, such as mating and blood-feeding, which are areas of intensive study for those interested in vector control.
This neurotranscriptome forms a strong foundation for the study of genes in the mosquito nervous system and investigation of sensory-driven behaviors and their regulation. Furthermore, understanding the molecular genetic basis of mosquito chemosensory behavior has important implications for vector control.
KeywordsMosquito Aedes aegypti mRNA-sequencing De novo genome assembly Host-seeking behavior Neural genes Chemosensory receptors Ion channels G protein-coupled receptors Gonotrophic cycle Neurogenetics
Studies in classic genetic model organisms including the mouse, zebrafish, fly, worm and yeast have led to major advances in biology. All of these systems have in common a sequenced genome and the ability to carry out forward and reverse genetic manipulations. Non-model organisms, such as the mosquitoes we study, have not been accessible to mechanistic genetic studies until recently. The availability of genomes, next-generation sequencing and genome editing technologies now make it possible to apply modern genetics to study animals with important and interesting biology previously inaccessible to molecular genetics.
Aedes aegypti is the primary vector for dengue, chikungunya and yellow fever – debilitating diseases that together are responsible for hundreds of millions of infections and thousands of deaths annually worldwide . Female mosquitoes exhibit remarkable behavioral shifts throughout their adult life. Ae. aegypti are generally anautogenous, meaning that they do not produce eggs without a blood-meal . Female Ae. aegypti use a variety of chemical and physical cues to locate hosts in their environment and to discriminate humans from non-human animals [3–8]. Although male Ae. aegypti do not feed on blood, they also respond to host chemosensory cues, perhaps to locate females congregating near humans . At short range, the male locates a potential mate using the specific frequencies generated by a female’s wing-beat .
After successfully obtaining a blood-meal, female mosquitoes repress host-seeking behavior [11, 12], and utilize the nutrients in the blood-meal to develop a batch of eggs. A female who has reached this physiological state is known as “gravid”. It is known that egg maturation and the beginning of egg-laying behavior occur between 48 and 96 h after a blood-meal . Once the eggs have matured, a gravid female uses cues such as humidity and the presence and quality of liquid water to identify a suitable place to lay her eggs, a behavior also known as oviposition . Following oviposition, a female mosquito recovers her attraction to hosts and seeks out new blood-meals to produce successive batches of eggs. This process, including host-seeking, egg maturation and oviposition, is known as the gonotrophic cycle . Disease transmission by mosquitoes is driven by this cyclical nature of female biting behavior, as a mosquito must first bite an infected host before becoming competent to spread infection to subsequent hosts.
Genetic resources, such as those that have long existed for conventional model organisms, would greatly facilitate investigation into the mechanistic basis of behavior in mosquitoes. While there has been impressive progress in mosquito transgenesis and mutagenesis in the past 20 years [3, 8, 12, 14–22], the large size of the Ae. aegypti genome (~1.3 Gb) and large transposable element load (~47 %) present formidable challenges to genome assembly, physical mapping and annotation [23–26]. Despite the limitations imposed by incomplete annotation of new mosquito genomes, several studies have profiled gene expression in individual sensory organs in the mosquitoes Ae. aegypti [27–29], Culex quinquefasciatus , Anopheles gambiae [31–34], and Toxorhynchites amboinensis .
Our work builds on these efforts by incorporating biological replicates sequenced at greater depth and from many isolated tissues in parallel in both females at several behavioral states, and in males. This large dataset makes it possible to detect genes expressed at low levels or expressed in only a few neurons, and to identify differential gene expression with statistical confidence. Since the anatomical substrate of host-seeking, egg-laying and other mosquito behaviors is likely to be distributed across several tissues, parallel transcriptional profiling of multiple tissues in a single study increases the likelihood of capturing the full repertoire of genes involved in these complex behaviors.
To generate a transcriptome of peripheral and central neural tissues (or “neurotranscriptome”) in Ae. aegypti, we performed Illumina mRNA-sequencing (RNA-seq) on RNA isolated from male and female tissues. Tissues sampled included the brain, antenna, maxillary palp, proboscis, abdominal tip, legs and female ovary. To understand the influence of blood-feeding state on gene expression, we performed RNA-seq on a subset of tissues in female mosquitoes at three time-points: prior to a blood-meal (non-blood-fed), at 48 h following a blood-meal (blood-fed), and at 96 h following a blood-meal (gravid).
This project, as part of the NIAID VectorBase Driving Biological Projects Initiative , set out to accomplish three major goals: 1) to improve the existing annotation of protein-coding genes in the Ae. aegypti genome and identify genes not found in the current genome assembly; 2) to catalogue gene expression at the resolution of single tissues in host-seeking female and male mosquitoes; and 3) to identify changes in gene expression that are correlated with blood-feeding state and its associated behavioral changes. This neurotranscriptome significantly enhances the Ae. aegypti genome annotation, and identifies a large number of genes whose expression is sexually dimorphic and/or variable across the female gonotrophic cycle. We anticipate that these data will drive studies of the genetic and neural circuit basis of host-seeking and egg-laying behavior in Ae. aegypti.
To determine whether the diminished responses to human hosts following blood feeding can be solely attributed to a reduction in sensitivity to CO2, we utilized a multi-insect three-dimensional flight-tracking system  to assess the response of a group of 20 female mosquitoes to a 40 s pulse of CO2 (Fig. 1d and e). As previously described, non-blood-fed female mosquitoes displayed a robust increase in flight activity in response to CO2 , while blood-fed females showed no increase in activity following administration of CO2. Gravid females displayed elevated pre-CO2 baseline flight activity. Male Ae. aegypti mosquitoes also showed a strong response to CO2 (Fig. 1d and e).
Correctly quantitating transcript expression from RNA-seq experiments depends on accurate gene models. Before analyzing gene expression across tissues, the two sexes and the female gonotrophic cycle, we utilized our sequencing data to update the annotation of protein-coding genes in the Ae. aegypti genome (Fig. 2d). The depth, replication and diversity of our sequencing allowed us to re-evaluate the existing annotation of protein-coding genes in the Ae. aegypti genome using two complementary approaches: de novo transcriptome assembly using Trinity  and alignment of sequencing reads directly to the reference genome. By aligning contigs from the de novo assembly back to the genome, we were able to combine data generated from these two approaches and use PASA2 software  to update existing gene annotations (AaegL2.1; obtained from VectorBase ). Reads were also aligned to the genome using STAR , and those aligning to genes were counted using featureCounts , allowing us to estimate transcript abundance and calculate differential expression at the gene level using DESeq2 .
We first carried out a principal component analysis of male and non-blood-fed female libraries to examine the clustering of data by tissue and sex. Large batch effects from library construction methods or problems with tissue contamination during dissection  may be revealed by this process. Virtually all of the biological replicates of the same tissue clustered tightly in principal component space, and for brain and legs across the two sexes (Fig. 2e).
Using our updated geneset annotation, we next classified genes into families related to neuronal function by both incorporating previously published classifications as well as considering their relationship to genes in the well-annotated and -studied vinegar fly Drosophila melanogaster. For pre-existing genes, we identified their closest orthologue in D. melanogaster using pre-calculated orthology calls of OrthoDB . To account for genes added in our geneset re-annotation, and thus not considered by the OrthoDB databases, we additionally performed blastx of the predicted coding sequence of all transcripts against the D. melanogaster proteome (Flybase release 6.06) and report the top BLAST hits with e-values below 0.01 (Additional file 3). Of note, 163 of our 572 proposed novel genes (28.5 %) have blastx hits that meet this criterion, as compared to 85.5 % of all other annotated genes. Finally, we point out that due to the incomplete assembly of the Ae. aegypti genome [23, 43], ours and other approaches that rely on genomic coordinates to describe gene features will run the risk of duplication or error.
A single example of a novel protein-coding gene, RU318, is depicted in Fig. 3d. It has high sequence conservation to the D. melanogaster TRP channel water witch (wtrw) . Notably, the current Ae. aegypti geneset annotation lacks a predicted orthologue to water witch, while two other mosquito genomes (An. gambiae and Cu. quinquefasciatus) contain orthologues. Based on this sequence similarity, we have included RU318 in our revised annotation of TRP channels in Ae. aegypti. Finally, to aid in transgenesis and other genome engineering approaches, we used all predicted coding sequences to generate a consensus Kozak sequence for Ae. aegypti (Fig. 3e).
To describe transcript abundance across tissues, we mapped reads from our tissue-specific RNA-seq libraries to the AaegL3 genome and report transcript abundances in units of transcripts per million (TPM) . Mapping statistics for each library can be found in Additional file 4, and TPM values for each replicate library can be found in Additional file 5 and Additional file 6. We first described the expression of genes related to neuronal function in specific tissues of non-blood-fed female and male Ae. aegypti using expression values calculated against the AaegL.RU annotation.
Insects use three major neurotransmitters: acetylcholine is the primary excitatory neurotransmitter in the central nervous system, glutamate is used for neuromuscular transmission from motor neurons to muscles, and GABA is generally considered to be the primary inhibitory neurotransmitter in insect central synapses. Additionally, a number of biogenic amines including serotonin, dopamine, tyramine, octopamine and histamine function as neurotransmitters or neuromodulators.
Our annotation and a previous analysis  identified three genes likely to be involved in ammonia transport in Ae. aegypti: two predicted orthologues of the D. melanogaster gene ammonium transporter (Amt), AAEL007373 and AAEL007377, as well as a single orthologue of Rh50, AAEL008046. D. melanogaster Amt is required for the response of antennal coeloconic sensilla to ammonia . Ammonia is known to be a host cue for Ae. aegypti  and An. gambiae [50, 51]. AAEL007377 was expressed at very low or undetectable levels (TPM < 1 in all tissues) whereas AAEL007373 was expressed at high levels in female antenna and proboscis as well as male antenna (see Additional file 5). AAEL008046 was expressed at very high levels in male and female brain, as well as antenna (see Additional file 5). We propose that AAEL007373 and AAEL008046 may be involved in ammonia detection in host-seeking Ae. aegypti.
Biogenic amines represent an important class of neurotransmitters and neuromodulators in insects that have been implicated in processes as diverse as reward, aggression, oviposition choice and the control of context-specific social behavior [52–55]. Ae. albopictus mosquitoes fed constitutively with L-DOPA exhibit lower levels of host-seeking behavior . Serotonin neurons innervate the antennal lobe of Ae. aegypti and An. gambiae , as well as the gut of Ae. aegypti  and serotonin has been shown to modulate feeding behavior in larval D. melanogaster . Most serotonin receptors were expressed at appreciable levels in brain and in various peripheral tissues (Fig. 4e). Dopamine receptors had generally variable expression across tissues, including brain, legs and antennae (Fig. 4f). Octopamine/tyramine receptors had generally lower expression values than other receptors, but were detected in brain as well as peripheral tissues (Fig. 4g). The TyrR orthologue AAEL004396 was highly and selectively expressed in ovary. We generally observed little obvious sexual dimorphism in neurotransmitter receptor expression. This suggests that there is a gross conservation of neuronal cell types and signaling pathways, at the transcriptional level, across male and female tissues.
Genes corresponding to Ae. aegypti neuropeptides and neuropeptide receptors were defined by orthology to canonical insect neuropeptides and receptors [12, 60–64]. Many neuropeptides were expressed primarily in brain of male and female mosquitoes, while a number had broader expression patterns that included but were not limited to brain (Fig. 5b; Additional file 7). This is consistent with reports of the direct detection of neuropeptides in specific regions of the brain, including the antennal lobe . Other peptides, including several predicted orthologues of eclosion hormone (EH), ecdysis-triggering hormone (ETH) and bursicon, were not detected at appreciable levels. We speculate that these genes are expressed selectively in earlier developmental stages that were not sampled in the present study of adult tissues. Neuropeptide receptors had generally broad expression patterns (Fig. 5c; Additional file 7), indicating that neuropeptides may be centrally produced while exerting anatomically far-reaching humoral effects.
ORs are an insect-specific family of divergent seven transmembrane domain chemoreceptors that sense volatile odors, including pheromones . The majority of ORs are expressed in the antenna, with restricted subsets expressed in either proboscis or maxillary palp (Fig. 6a; Additional file 7), consistent with previous reports of OR-expressing sensory neurons in these tissues in An. gambiae  and Ae. aegypti . In contrast to the ORs, OBPs are expressed widely in the tissues profiled here, and vary greatly in their transcript abundance (Fig. 6b; note expanded TPM scale relative to Fig. 6a; Additional file 7). Similar results were found in an analysis of OBP expression in An. gambiae mosquitoes  and ants .
Expression (TPM) values for ORs were broadly elevated in female as compared to male antenna. Antennae of male Ae. aegypti are specialized for audition and contain an exaggerated pedicel at their base when compared to female antenna . We speculate that extra cell numbers associated with this enlarged pedicel would effectively dilute mRNA coming from other cells in male antenna, thus reducing the tissue-wide abundance of odorant receptors and other genes expressed in olfactory sensory neurons. To account for these putative differences, we plotted the expression of ORs in male and female antenna (Fig. 6c) normalized to the olfactory co-receptor orco to reflect the approximate number of olfactory sensory neurons. This normalization depends on the assumption that orco expression is not sexually dimorphic, and therefore a reasonable proxy for olfactory sensory neuron number across sexes. Even after accounting for this normalization, we identified 12 OR genes with apparent enrichment in female antenna, with 10- to 35-fold increase in raw expression values as compared to male antennae (Fig. 6c and d). Because a number of untested assumptions were the basis of these conclusions, we note that these results would need to be validated independently, perhaps by RNA in situ hybridization, to gain cellular resolution of gene expression. Increases in mRNA expression could arise either by selective upregulation of gene expression in females, or through developmental changes that would lead to an increase in the number of neurons expressing these receptors in females. Because female mosquitoes show sex-specific chemosensory behavioral responses to odors associated with hosts and oviposition sites, it is not unreasonable to expect sex-specific differences in ORs tuned to these specific odors.
IRs are ligand-gated ion channels derived from variant ionotropic glutamate receptors that tend to be gated by ligands such as acids, aldehydes and amines . The IR family of Ae. aegypti has been previously described , and we identified predicted gene models for 2 additional IRs (RU164 and RU199) using blastx against the D. melanogaster proteome (Additional file 2 and Additional file 3). We found three patterns of IR gene expression: those generally restricted to antenna; others selectively expressed in proboscis, rostrum and maxillary palp; and a small number of IRs expressed across many different tissues examined (Fig. 7a; Additional file 7). Similar results were previously reported in D. melanogaster, Apis mellifera, An. gambiae and Culex quinquefasciatus [30, 31, 72].
GRs are a family of transmembrane receptors distantly related to ORs  that mediate detection of pheromones, tastants, CO2 , and in the case of D. melanogaster Gr28b (Ae. aegypti Gr19), light and heat [74, 75]. The annotation of the GR family of Ae. aegypti was previously described . GRs are predominantly expressed in the rostrum, maxillary palp and proboscis (Fig. 7b; Additional file 7), consistent with their primary and conserved role in taste perception . Notable exceptions include AaegGr1, AaegGr2 and AaegGr3 (Fig. 7b, bottom 3 genes), which encode CO2 receptor genes that function in the maxillary palp .
Pickpocket (PPK) channels are a family of amiloride-sensitive degenerin/epithelial sodium channels (DEG/ENaC) that are involved in the transduction of a number of sensory modalities, including mechanosensation, hygrosensation and pheromone sensing . We first identified Ae. aegypti PPK channels by searching for orthologues to previously described PPKs in D. melanogaster and An. gambiae . Gene expression profiles of the PPK channels reveal broad expression of most genes across several peripheral tissues (Fig. 7c; Additional file 7), including proboscis and legs, consistent with a role in various forms of contact chemosensation.
Transient receptor potential (TRP) channels have been implicated in diverse sensory modalities, including heat, light and chemosensation . Ae. aegypti TRP channels were identified by conducting orthologue searches against the 13 identified D. melanogaster TRP channels . We identified orthologues to all 13, and two additional genes predicted to be orthologues of D. melanogaster painless. Expression of TRP channels was generally broad (Fig. 7d), with several interesting tissue-specific expression patterns, most notably in brain and antenna.
Here we present the “neurotranscriptome” of brain and peripheral nervous system tissues in female and male Ae. aegypti mosquitoes. We used both genome-guided mapping of RNA-seq reads as well as de novo transcriptome reconstruction to improve the annotation of existing protein-coding gene models as well as identify 572 putative novel protein-coding genes. By mapping tissue-specific RNA-seq libraries to transcripts generated by these updated gene models, we examined gene expression in 10 female and 6 male tissues from non-blood-fed animals, as well as a subset of tissues from blood-fed and gravid female mosquitoes, representing two important and distinct behavioral states following a human blood-meal.
Given the fragmented state of the Ae. aegypti genome and gene annotations, it was important to include a de novo assembly approach in our analysis. This allowed us to examine the expression pattern of genes derived from unassembled regions of the genome. For example, a myosin heavy chain gene, RU529, is identical in sequence to Ae. aegypti myo-sex , a gene linked to the sex-determining M-locus of Ae. aegypti in a region absent from the current genome assembly. A targeted search for genes in our dataset with similar expression patterns revealed additional genes with male-specific expression. Interestingly, we saw several novel unmapped genes from our de novo assembly in these searches and suggest that these may also derive from unassembled genomic loci similar to the M-locus. A recent study confirmed the presence of such a factor, nix (identified in our study as RU426), and demonstrated its critical role in sex-determination in Ae. aegypti .
The present study is a valuable dataset, presenting a comprehensive view of protein-coding gene expression in adult tissues, and yet it remains incomplete. We only sequenced polyadenylated RNA derived from 10 adult tissues. We have not explored the repertoire of small RNAs including microRNAs, non-coding RNAs or the regulation of alternative splicing. Our re-annotation approach relied on alignments of short reads and de novo transcripts back to the current draft of the genome, meaning that gene models residing on misassembled genomic contigs might be incorrectly represented. Indeed, a recent effort to generate a physical map for the Ae. aegypti genome found a misassembly rate of approximately 14 %, including 6 of the 10 largest supercontigs , making it likely that many gene models that rely on the present assembly remain incorrect. Ultimately, a comprehensive annotation of protein-coding genes and non-coding loci within the Ae. aegypti genome will require the incorporation of additional genomic sequencing and transcriptomic data derived from distinct developmental stages and tissues .
Whole tissue RNA-seq can identify genes differentially expressed across male and female tissues. However, further work will be required to resolve gene expression profiles in individual cells and cell-types. For the purposes of this study, sexually dimorphic transcripts were conservatively defined as those for which the fold-change observed was greater than 8, though we note that there are many more transcripts with less extreme sex-biased expression. Anatomical differences will make it difficult to determine whether observed differences in transcript abundance represent differential regulation within shared cell-types or variation in the cell-type composition of male and female tissues. Interestingly, we describe relatively few examples of sexually dimorphic expression within the chemosensory gene families examined, suggesting that the striking behavioral differences seen between male and female Ae. aegypti may be encoded in the neural circuits responsible for the processing of sensory stimuli as opposed to gene expression differences at the sensory periphery.
We do note the statistically significant up- and down-regulation of a handful of olfactory receptors in antenna from gravid females. This is similar to an observed shift in OR expression in the antenna of An. gambiae following a blood-meal [32, 81], and suggests that a behavioral shift from host-seeking to oviposition site selection may involve the increased expression of particular ORs tuned to ligands associated with oviposition sites and a concomitant decrease in expression of ORs tuned to host odor. With few exceptions [8, 85], the ligand tuning of specific chemoreceptors has not been determined in Ae. aegypti. A systematic effort to de-orphanize Ae. aegypti chemoreceptors will be required to address the functional relevance of these observed gene expression changes.
A major goal of this work was to identify gene expression changes correlated with blood-feeding state to gain insight into possible mechanisms by which a blood-meal might influence behavior. We describe many genes that change expression in tissues from blood-fed and gravid mosquitoes, including chemoreceptors, neuropeptides, neuropeptide receptors and neurotransmitter receptors and processing enzymes, all of which might play important roles in the regulation of behavior and physiology. However, genes from these classes comprise a small minority of all regulated genes, and thus, are unlikely to alone explain the marked shifts in behavior as female mosquitoes transition from host-seeking to oviposition.
We envision this dataset as a resource to guide the selection of candidate genes involved in mosquito behavior as well as providing insight into the principles of gene expression regulation by blood-feeding. Transgenesis of mosquitoes  and precisely targeted mutagenesis with tools such as zinc-finger nucleases [3, 8, 12], TALENs [18, 19], homing endonucleases , and RNA-guided nucleases [20–22] now allow for the generation of stable mutant lines and other genetic reagents to test the function of candidate genes in mosquito behavior.
We present a broad view of gene expression in non-blood-fed male and female tissues, focusing particularly on gene families related to neuronal function and chemosensation. We demonstrate that the effects of blood-feeding on gene expression are broad. This study represents the most comprehensive, tissue-specific survey of gene expression in adult Ae. aegypti to date and will be foundational in our understanding of the molecular genetic basis of behavior in this important disease vector.
Mosquitoes used in this study were from the genome reference Liverpool strain (LVPIB12) obtained from BEI Resources/CDC/MR-4 (stock number MRA-735). Eggs were hatched in autoclaved water containing ground Tetramin tropical fish food (Tetra) and fed Tetramin food as necessary during larval and pupal development. For routine rearing, adult females were blood-fed on mice under a protocol approved by the Rockefeller University Institutional Animal Care and Use Committee (IACUC Protocol 14756). Male and female adult mosquitoes were reared together under a 14 h light:10 h dark cycle under conditions of 25–28 °C and 70–80 % relative humidity. For female blood-fed libraries, mosquitoes were offered a human arm and allowed to feed to completion. Blood-feeding was verified by separating female mosquitoes with engorged abdomens 24–48 h following blood-feeding. At least 16 h prior to dissections, mosquitoes were separated under cold-anesthesia into groups of the appropriate size for a given library.
Uniport experiments were carried out as described , with the exception of the stimulus, which was a 11 cm2 circle of exposed skin created by cutting a hole in an elbow-length latex glove. CO2 concentration in the airstream was measured at 5 % with a Carbocap Hand-Held CO2 m (model GM70, Vaisala Inc.). SciTrackS experiments were carried out as described . Groups of 20 mosquitoes were placed into the flight arena, allowed to acclimate for 15 min, and then presented with a 40 s pulse of CO2.
Ethics, consent, and permissions
All blood-feeding procedures and behavioral testing with human subjects were approved and monitored by The Rockefeller University Institutional Review Board (IRB; protocol LVO-0652). Subjects gave their written informed consent to participate in these experiments.
Tissue dissection and RNA extraction
Mosquitoes were cold-anesthetized and kept on ice until dissections were complete. Individual tissues were removed by forceps or scissors and immediately flash-frozen by placing into nuclease-free tubes in a dry-ice/ethanol bath (−76 °C). The following number of mosquitoes was used for each female library: antenna, 100–220; maxillary palp, 126–816; proboscis, 275–797; rostrum, 110–142; brain, 9–18; foreleg, 125; midleg, 100–125; hindleg, 100–138; ovary, 9–25; abdominal tip, 50. For male libraries, the following number of mosquitoes was dissected for each tissue library: antenna, 75; rostrum, 40–50; brain, 25; foreleg, 100–125; midleg, 100–125; hindleg, 100–125; abdominal tip, 50. Dissected tissue was stored at −80 °C until RNA extraction.
RNA extraction was performed using the Qiagen RNeasy Mini Kit (Qiagen). Tissue was disrupted with an electric tissue grinder loaded with a disposable RNAse free plastic pestle. For legs, abdominal tip and other cuticle-rich tissue, samples were further disrupted by passing tissue through a QIAshredder Mini spin column (Qiagen). RNA quantity and quality were evaluated using an Agilent BioAnalyzer 2100 and the RNA 6000 Nano Kit (Agilent Technologies).
RNA-seq library preparation
Unstranded libraries from polyA-selected RNA were prepared with TruSeq RNA Sample Preparation Kits (Illumina) or the mRNA sample-prep kit (Illumina), following the manufacturer’s protocol. Between 200 ng and 1 μg of total RNA was used as input for each replicate library. For paired-end libraries, size-selection was performed prior to PCR by gel extraction or by a Pippin Prep instrument (Sage Biosciences) using 2 % agarose cassettes containing ethidium bromide. Size selection resulted in libraries with mean insert sizes (excluding sequencing adapters) of 250–450 base pairs (bp). Library quantity and quality were evaluated using an Agilent BioAnalyzer 2100 and the High Sensitivity DNA Kit.
All sequencing was performed at The Rockefeller University Genomics Resource Center on HiSeq 2000 or Genome Analyzer IIx sequencers (Illumina). All paired end reads were 2 × 101 bp and all single-end reads were 1 × 101 bp with the exception of four 72 bp libraries. Data were de-multiplexed and delivered as fastq files for each library. These sequencing reads are available at the NCBI Sequence Read Archive (SRA) and are associated with BioProject PRJNA236239.
Transcriptome generation: reference-based mapping
All reads from all libraries were aligned to the AaegL2 reference genome obtained from VectorBase  using Cufflinks2, Tophat2 and Bowtie2 software packages . Reads were aligned without respect to existing annotations with the following settings: minimum intron length of 40 bp, maximum intron length of 500 Mb. Cufflinks was run on reads from individual conditions and tissues to identify all putative splice junctions, and then combined using cuffcompare to identify a consensus set of putative splice junctions identified in our sequencing reads.
Transcriptome generation: de novo assembly
We performed de novo assembly as a second approach to reconstruct transcripts from our data. All reads from all libraries were assembled into a genome-free de novo assembly using the Trinity software package (version 2013-02-25) [36, 87]. To account for the depth of sequencing, we first performed read normalization to down-sample the number of reads used in the assembly using the included normalization tool in the Trinity software package with a max_coverage setting of 25. Male paired-end, female paired-end and single-end reads were normalized separately and then combined, resulting in a 49-fold reduction in overall input data. Trinity was run using default settings, with a minimum k-mer coverage of 1, resulting in an assembly with 420,978 contigs.
Geneset annotation: PASA
The spliced alignments of individual sequencing reads and the alignment of contigs from the de novo assembly were used as input to PASA2  as a means of updating the reference gene annotation using the software’s alignment assembly and annotation comparison workflow. Briefly, de novo contigs were aligned to the genome (AaegL2; VectorBase ) using the short read aligners BLAT and GMAP. These alignments were combined with the combined cufflinks output from genome-guided mapping to create assemblies of spliced alignments. These assemblies were compared to reference annotations (AaegL2.1; VectorBase ) and used to extend, update or merge reference annotations. Additionally, this analysis identified 403 putative protein-coding genes not covered by the current annotation (see “Geneset annotation: naming of genes and geneset comparisons below). Default PASA2 parameters were used with the exception of the number of allowed exons in 5’ or 3’ UTRs (−−MAX_UTR_EXONS = 3). Due to a technical oversight, 5 genes were added manually after the PASA2 run, using previously published coordinates: AaegGr27, AaegOr54, AaegIr41d.2, AaegIr75k.4 and AaegIr7h.2.
Identifying novel unmapped genes
To identify novel transcripts that do not map to the current genome assembly, we filtered our de novo assembly as follows. First, we excluded all contigs that mapped to the genome or to cDNA from an existing transcript using GMAP. Next, we required that each contig encoded a complete open reading frame (ORF) of at least 30 amino acids in length, as predicted by transdecoder (http://transdecoder.github.io). We then screened for likely bacterial and fungal contamination by performing blastx with default settings of the remaining contigs against the nr database (NCBI), and excluded anything for which the top hit was fungal, bacterial or mammalian. Finally, we performed blastx of each remaining contig against a database of insect transcriptomes (Anopheles gambiae [AgamP3], Apis mellifera [Amel_4.0], Culex pipiens (now Culex quinquefasciatus) [CpipJ1], Drosophila pseudoobscura [r3.1], Heliconius melpomene [v1.1], Ixodes scapularis [IscaW1.2], Nasonia vitripennis [Nvit_1.0], Rhodnius proxlixus [RproC1], Bombyx mori [SilkDB v1.0], Drosophila melanogaster [r5.50] and Triboleum castaneum [v2.0; without mitochondria], requiring that there was a match with an e-value of less than 0.01. 232 contigs that passed these conservative filters were considered to be high-confidence novel genes derived from portions of the genome that have not been sequenced or had assembly problems. These 232 contigs were collapsed using CD-HIT [88, 89] resulting in 169 novel transcripts that were included in downstream analysis.
Geneset annotation: naming of genes and geneset comparisons
To name each gene in our updated geneset, we first compared them to existing annotations in AaegL3.3 using cuffcompare  and carried over accession numbers for those loci that were highly similar to existing annotations. Genes that did not match existing loci in these cuffcompare analyses are numbered sequentially as RU1–RU572 (Additional file 2). For chemosensory gene families with previously published manual annotation, names were assigned to be consistent with these previous annotations (Additional file 3). For genes with a VectorBase accession number, orthology to Drosophila melanogaster was retrieved from OrthoDB (ODB8, dipteran dataset) . We further used NCBI blastx to compare CDS for all transcripts against the D. melanogaster proteome; hits with an e-value of less than 0.01 (truncated to include the top 10) are listed in Additional file 3. To determine the proportion of transcripts that were updated as compared to the VectorBase annotations (Fig. 3c; AaegL2.1 and AaegL3.3), we used the parseval tool in the AEGeAn package to compare gff3 annotation files .
We note that due to the evolving nature of annotations in Ae. aegypti and the fact that our orthology relies only on a single species (D. melanogaster), the gene families here should not be considered complete or exhaustive.
A file detailing library alignment and quantitation statistics is available as Additional file 4 While all sequencing reads were used for genome reannotation, aberrant clustering of transcriptome-wide expression patterns from two non-blood-fed female brain libraries resulted in their exclusion pool and the DESeq2 model was re-run. Additionally, signs of contamination of male rostrum libraries resulted in their removal from expression analysis (note that these are retained in the PCA plot in Fig. 2e).
Expression data and differential expression analysis
All reads from individual libraries were mapped to the AaegL3 genome using STAR version 2.4.1c , and reads mapping to each gene in the AaegL.RU or AaegL3.3 geneset annotation were counted at the gene level using featureCounts v1.4.6-p3  (Additional file 3). For abundance visualization, raw counts were converted to TPM  in R. Raw counts were used for differential expression analysis in R using DESeq2 v1.8.2 , and the PCA analysis in Fig. 2e was performed with DESeq2 using counts subjected to Variance Stabilizing Transformation (VST).
Sexually dimorphic genes were identified with a DESeq2 model incorporating all non-blood-fed female and male libraries from a single tissue and visualized as MA plots generated with significance indicated at an FDR of α < 0.01 (Fig. 8a–f, Additional file 8). Venn diagrams were generated using the R library VennDiagram (Fig. 8g and h). Transcript abundance of genes identified as dimorphic in at least three tissue groups were visualized as heat maps sorted by the sum of the TPM in the dominant sex (Fig. 8i and j).
Genes regulated by blood-feeding state were identified in DESeq2 with single-tissue models incorporating single-end libraries from female tissues (with the exception of ovary, where all libraries were paired-end). In tissues with three time-points (brain, antenna and hindleg), Z-scores of expression for genes with an FDR of α < 0.01 (in either comparison) were generated using the ‘scale’ function of R, and clustered using the hclust (method = ‘complete’) and dist (‘method = euclidean’) functions in R. (Fig. 9).
Availability of data and materials
All raw reads are deposited in the NCBI SRA under BioProject number PRJNA236239. Gene set annotations, expression data and sequences of new genes generated are available as Additional Files with this manuscript.
- CO2 :
coefficient of variation
degenerin/epithelial sodium channels
expressed sequence tag
Institutional Animal Care and Use Committee
Institutional Review Board
- MA plot:
plot using an M (log ratios) and A (mean average) scale
odorant binding protein
open reading frame
principal component analysis
polymerase chain reaction
Tyramine β hydroxylase
transcripts per million
transient receptor potential
variance stabilizing transformation
We thank Nicolas Robine, and members of the Vosshall Lab for discussions and comments on the manuscript; Felix Baier and Chloe Goldman for expert technical assistance; Katie Kistler for assisting with the behavioral experiments in Fig. 1b and c; Deborah Beck and Gloria Gordon for mosquito rearing; Daniel Lawson for discussion and sharing annotations in progress at VectorBase; Connie Zhao and James Hughes for facilitation of DNA sequencing at the Rockefeller University Genomics Resource Center, and Scott Dewell for bioinformatic support. This work was funded in part by a grant to R. Axel and L.B.V. from the Foundation for the National Institutes of Health through the Grand Challenges in Global Health Initiative and the following National Institutes of Health grants: K99 award from NIDCD to CSM (DC012069), an NIAID VectorBase DBP subcontract to LBV (HHSN272200900039C), and a CTSA award from NCATS (5UL1TR000043). BJM was supported by Henry and Marie-Josée Kravis and Jane Coffin Childs Postdoctoral Fellowships. LBV is an investigator of the Howard Hughes Medical Institute.
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