A comprehensive gene expression atlas of sex- and tissue-specificity in the malaria vector, Anopheles gambiae
© Baker et al; licensee BioMed Central Ltd. 2011
Received: 31 January 2011
Accepted: 7 June 2011
Published: 7 June 2011
The mosquito, Anopheles gambiae, is the primary vector of human malaria, a disease responsible for millions of deaths each year. To improve strategies for controlling transmission of the causative parasite, Plasmodium falciparum, we require a thorough understanding of the developmental mechanisms, physiological processes and evolutionary pressures affecting life-history traits in the mosquito. Identifying genes expressed in particular tissues or involved in specific biological processes is an essential part of this process.
In this study, we present transcription profiles for ~82% of annotated Anopheles genes in dissected adult male and female tissues. The sensitivity afforded by examining dissected tissues found gene activity in an additional 20% of the genome that is undetected when using whole-animal samples. The somatic and reproductive tissues we examined each displayed patterns of sexually dimorphic and tissue-specific expression. By comparing expression profiles with Drosophila melanogaster we also assessed which genes are well conserved within the Diptera versus those that are more recently evolved.
Our expression atlas and associated publicly available database, the MozAtlas (http://www.tissue-atlas.org), provides information on the relative strength and specificity of gene expression in several somatic and reproductive tissues, isolated from a single strain grown under uniform conditions. The data will serve as a reference for other mosquito researchers by providing a simple method for identifying where genes are expressed in the adult, however, in addition our resource will also provide insights into the evolutionary diversity associated with gene expression levels among species.
For organisms in which large-scale mutagenic studies are problematic, gene expression catalogues are an important tool for annotating processes on a gene-by-gene basis. In the malarial vector Anopheles gambiae, studies have focused on differential expression in males and females [1, 2], on samples collected before and after the bloodmeal [2, 3] and in dissected tissues such as the midgut , salivary glands [4, 5], ovaries [2, 6], head and carcass [7, 8]. However, since these studies often involve different mosquito strains, different experimental platforms and analysis by different statistical methods, comparison among treatments is challenging. Here, we provide a comprehensive expression atlas and associated publicly available database, the MozAtlas (http://www.tissue-atlas.org), cataloguing the relative strength and specificity of gene expression in tissues of male and female mosquitoes using a single genome-wide platform, protocol and analysis.
We employed transcriptional profiling to analyse RNA levels in whole body mosquito samples, eight separate somatic tissues (head, salivary gland, midgut, Malpighian tubules, thoracic and abdominal carcass) and the reproductive tissues (testis, accessory gland, ovary) of males and females separately. In common with the majority of sexually reproducing organisms, Anopheles has specialized reproductive traits. Of particular interest is the female-specific activity of blood-feeding, which provides protein for egg development and is a key determinant in Plasmodium transmission. In contrast, male mosquitoes feed entirely on sugar, are not adapted for digesting blood and do not transmit malaria. Consequently, those tissues involved in acquiring, ingesting and digesting blood are expected to display substantial sexual dimorphism at the level of gene expression.
In this paper we summarize the functions and sequence level divergence of genes with sexually dimorphic or tissue enriched expression patterns to determine which genes, if any, are rapidly evolving. In addition, by comparing Anopheles expression profiles with matched tissues in Drosophila melanogaster, we assess evolutionary conservation of expression profiles within the Diptera and identify genes recently evolved in Anopheles with tissue specific patterns of expression. Such traits provide ideal candidates for use in population control, where vital or fertility-related genes may be targeted by genetic knockout . With the ongoing development of insect genetics it has become increasingly likely that some pest populations, including mosquitoes, may be controlled with genetic modification [10–15].
Gene expression coverage
Sexually dimorphic gene expression
Sexual dimorphism at the gene expression level is associated with different and distinct functional categories (Additional File 4). For example, genes with 'digestion', 'protein metabolism' and 'proteolytic' functions, especially 'serine-type endopeptidase' are over-expressed in the midgut of females. Genes enriched for 'cellular homeostasis', 'ligase activity' and 'transporter activity' are enriched in the female salivary gland, while the malpighian tubules display an over-representation of genes associated with 'ion transportation'. In comparison, male-elevated genes are largely associated with 'carbohydrate metabolic activity', 'ion transporter activity' and 'iron ion binding' within the midgut, salivary gland and Malpighian tubules, as well as the carcass. Ultimately, many of the genes elevated in either sex are of unknown function.
Tissue specific gene expression
Previous studies indicate that genes with restricted expression have elevated rates of sequence divergence amongst related species . We conducted a large-scale survey of SNP A/S ratios using data from dbSNP to determine if such genes were evolving rapidly in Anopheles. First, 11,224 genes with at least one coding SNP were collected. In total, ~100,000 coding-region SNPs and 316,043 intronic SNPs were identified, corresponding to SNP densities of 5.6 and 7.19 SNPs, respectively, per 1,000 nucleotides. For our entire dataset, the number of non-synonymous coding SNPs per non-synonymous site (A) was 0.0033, the number of synonymous coding SNPs per synonymous site (S) was 0.0068, and the A/S ratio was 0.49.
SNP A/S estimates of < 1 suggest that most nucleotide substitutions have been eliminated by selection, i.e. purifying selection, whereas SNP A/S > 1 indicate that non-synonymous nucleotide substitutions have been maintained, i.e. positive selection. As expected, many tissue-specific genes display a higher ratio of A/S SNP ratio than those ubiquitously expressed throughout the organism, i.e. fewer non-synonymous mutations have been eliminated by selection and are evolving more rapidly (Figure 3B). For example, genes expressed in reproductive tissues including the testis, ovary and the male accessory gland have the highest rates of sequence divergence within Anopheles. Non-reproductive tissues including the head and Malpighian tubules show less deviation, while genes specifically expressed in the salivary gland and midgut have only marginally higher A/S SNP ratios than ubiquitously expressed genes.
Chromosomal distribution of tissue expression
Comparative evolution with Drosophila melanogaster
To identify conserved expression signatures underling the above patterns, we used hierarchical clustering with pair-wise correlation coefficients to identify co-expressed genes for each species. We chose clusters with an average similarity of greater than 0.8 and more than 50 genes for further analysis. Overall, 11 clusters meet these criteria in Anopheles and Drosophila, representing 2884 and 2913 genes respectively (Figure 5C-D; Additional File 6). Adjusting these thresholds, changes the number of groups identified, but were selected to provide a dataset with reasonably sized gene clusters of highly similar expression profiles.
Orthology cluster overlap, tissue expression and enriched gene ontology annotations
signal peptide processing
carbohydrate metabolic process
nucleic acid metabolic process
oogenesis, cell cycle
Single-copy and multi-copy gene families
Online MozAtlas Database
For researchers interested in comparing their own experiments to the MozAtlas, we have constructed an online database and web-browser for querying tissue expression in Anopheles (http://www.tissue-atlas.org). The single gene query displays tables of normalized expression for each probe and tissue available. In addition, this search displays available orthology relations, a) one-to-one Drosophila melanogaster orthologues and corresponding relative gene expression estimates, and b) a gene tree of all mosquito, fly and outgroups within the gene family. We also provide a BLAST and batch searching facilities to output expression values for larger lists of genes that may then be used for further down-stream analysis.
To help improve the functional annotation of the Anopheles gambiae genome we have generated the MozAtlas, a unified catalogue of tissue-specific gene expression from a single mosquito strain. In Drosophila melanogaster, cataloguing tissue expression patterns has been useful, especially for inferring biological functions, since the majority of genes encoded in the genome are not ubiquitously expressed . As with the fruit fly, Anopheles gene expression also exhibits substantial tissue specificity, with only a third of detectably expressed genes found in all tissues. Thus, the MozAtlas is a useful resource for better understanding the mosquito genome, providing direct evidence of genes with tissue restricted expression. Below we highlight the utility of MozAtlas for identifying classes of gene with tissue or sex-biased expression that may be exploited for vector control. Analysis of the MozAtlas also identifies gene expression features that are of interest from an evolutionary perspective, revealing both highly conserved and species-specific aspects of insect biology. Of particular interest, given that malaria parasites are only transmitted through female mosquitoes, we separately catalogued gene expression for each tissue in males and females, thus providing both tissue and sex-specific views of gene expression in the adult.
A major finding from our analysis is the substantial degree of sexually dimorphic gene expression we find at the tissue level: more than half of the genes for which we detect expression exhibit sexual dimorphism in terms of expression level. The head, in particular, has a significantly higher number of female-biased genes and of these, odorant receptors are significantly over-represented (Additional File 4). When searching for a blood-meal, female mosquitoes are attracted to odours emitted by humans, a behaviour mediated by receptors in the antennal sensilla . This activity is not exhibited by males, who feed entirely on nectar, and we presume that the female elevated expression of odorant binding molecules reflect this biology. The identification of molecules associated with female-specific aspects of odorant detection may provide targets for controlling malaria transmission .
We identified other sexually dimorphic expression signatures that appear to be associated with female characteristics, in particular, adaptation to hematophagy. For example in the female salivary gland we found an over-representation of genes with protein and lipid catabolic activity, ion transport and cellular homostasis functions. We suggest that these reflect the fact that, in females, the salivary gland produces compounds to disarm host hemostatic and immune responses, thus allowing mosquitoes to take a blood-meal. Similarly, many proteins found in the midgut are only synthesized by blood-feeding females [3, 21]: numerous digestive and proteolytic molecules implicated in blood digestion were identified as female elevated in our analysis.
In contrast, elevated male gene activity is largely associated with carbohydrate metabolism and ion transport activity. Since male mosquitoes feed entirely on sugar, these results were not surprising. However, somewhat more novel is that iron binding molecules are up-regulated in males. While in female mosquitoes iron is especially important for egg development and is strongly influenced by blood-feeding , iron metabolism has diverse physiological and developmental roles . Although females obtain iron from the blood meal, the sugar diet of males may necessitate more efficient iron uptake and up-regulation of genes that encode iron binding functions.
In both somatic and reproductive tissues, we identified genes with considerable specificity. Tightly controlled, tissue-specific expression is of interest for understanding the basic biology of a species, and is likely to be key in the development of next generation insect control agents. For example, genes uniquely expressed in particular tissues could be targets for inducing sterility or providing regulatory elements to drive localised expression of transgenes. In this respect, the highest proportion of Anopheles tissue-specific expression is in the testis, with approximately 10% of transcription uniquely detected in this tissue. Testis specific expression of genes with important roles in spermatogenesis, sperm competition or sperm-egg interactions present a set of targets with potential for inducing male sterility.
After mating, Anopheles females undergo distinct behavioural and physiological changes due to the transfer of both sperm and proteins produced in the male accessory glands : proteins secreted by males and passed to females in seminal fluid could provide a route for altering female fertility. Via specific expression profiling of accessory glands we have identified a new set of potential Anopheles Acp genes that will enable further investigation of sexual conflict within the mosquito. Sexual antagonism between males and females may be expected to cause rapid Acp sequence evolution . We find that among tissue-specific genes, those expressed in the accessory gland have a higher A/S ratio than in many tissues, including the testis. Slower evolutionary rates in the Anopheles testis might be explained, in part, by their mating behaviour: in polyandrous insects genes involved in spermatogenesis are often under strong positive selection as a result of post-copulatory male-male competition , whereas these pressures in the testis are expected to be absent from the largely monandrous Anopheles mosquitoes .
Genes with ovary specific expression provide potential targets for inducing female sterility in mosquitoes given that they are closely associated with egg formation. Chorion components of the fruit fly eggshell, for example, provide the embryo with protection from the physical environment, and disrupting their function causes female sterility . Recently, proteomic techniques have identified Anopheles eggshell constituents, several of which we find to be specifically expressed in the ovary, making them favourable candidates for use in population control .
In terms of genome structure, we show that genes with male-biased expression are non-randomly distributed around the Anopheles genome. Two mechanisms have been proposed to explain the disparity in chromosomal distribution of male expressed genes. First, during spermatogenesis the X chromosome of males becomes inactivated: since few testis genes are expressed post-meiotically, evidence suggests that chromosomal inactivation has promoted autosomal duplication events from X-linked genes [18, 29, 30]. There is compelling evidence that X-linked inactivation also occurs in nematodes  and mammals , however, an under-representation of male-biased somatically-expressed genes on the X chromosome indicates that other forces are also at work. Second, since males only have one X chromosome, polymorphisms beneficial to one sex may arise that are detrimental to the other sex. Such antagonistic sexual selection may eventually lead to sequence changes and demasculinization of the X chromosome , and consistent with this expectation, genes on the Anopheles X chromosome have less sequence polymorphism than on the autosomes.
Identifying expression divergence within and between closely-related species provides important insights into the selective pressures underlying gene regulation [34, 35]. The opportunity to compare divergence between Drosophila and Anopheles, separated by some 250 million years of evolution, allows us to explore gene and tissue evolution over a considerable time scale. We find that expression similarity in one-to-one orthologues of the midgut, head, carcass and ovary expressed genes is well conserved in the Diptera and, as expected, genes in conserved co-expression clusters perform integral physiological functions.
In contrast, tissues such as the testis, often show considerable transcriptional variation between closely related species [36, 37]. It's been proposed that testis gene regulation plays a critical role in the initial formation of reproductive isolation . In addition to the Anopheles testis, expression in other tissues is also highly divergent: for example, expression in the Malpighian tubules is largely not conserved between Anopheles and Drosophila. As an organ with a key role in detoxification and osmoregulation, this divergence may reflect fundamental differences in the diet of each insect . In addition, salivary gland and male accessory gland expression cluster within rather than between species, evidence for a bout of simultaneous evolution since the last common ancestor was shared. Indeed, no significant co-expression was detected between species, indicating that secretory organ functions have diverged during the Dipteran split.
Recent Anopheles gene duplications are often expressed in the testis and, in Drosophila, extreme expansions also have spermatogenesis-related functions . As well as the testis, other tissues display narrow expression profiles of recent origin in Anopheles. Certainly, the blood meal imposes a range of challenges on the digestive system of mosquitoes and, in part, explains a predominance of gene duplications with salivary gland, Malpighian tubule or midgut expression. Even between members of the same mosquito subgenera, salivary proteins can diverge rapidly over time : our data suggests that this evolutionary pattern may also be common in Malpighian tubule proteins and, to a lesser extent, proteins within the midgut. However, specifically expressed genes in large families do not necessarily highlight unique functions, since homologues may perform the same or similar functions in a larger set of tissues. Gene families with single members are of interest for identifying unique processes, given that closely related homologues are not found within the genome. Narrowly expressed single-copy families were detected dating back to Metazoan and Hymenopteran clades, perhaps accompanying the emergence of differentiated organs. It will be of considerable interest for insect control programs to determine whether such proteins perform integral functions in their specific tissues, given that as single copies they should perform unique roles within the organism.
We have generated a tissue and sex-specific gene expression atlas for Anopheles gambiae and used it to explore mosquito biology related to reproduction, feeding and gene evolution. Given that Anopheles is the major vector of one of the world's most debilitating diseases, our dataset provides an important reference for other mosquito researchers wishing to explore potential roles for genes of interest. Of particular importance is the identification of uniquely expressed genes that may serve as tissue-specific drivers in transgenic constructs or potential knockout targets in the next generation of insect control agents.
RNA collections and microarray platform
Male and female mosquito siblings were separated at pupation and allowed to emerge into separate cages to prevent mating. 3-day old, non-mated females were blood-fed and female tissues were dissected at 24 hour intervals for a three day period following the blood-meal. Equivalent male tissues were dissected from age-matched siblings in parallel. Dissections were carried out in phosphate-buffered saline using dissecting needles and a 28 gauge needle to cleanly separate connected tissues from each other. 'Midgut' samples were dissected clear of the foregut, hindgut and malphigian tubules to include the anterior midgut and stomach. 'Head' samples were produced by severing at the neck and include brain, eyes, cuticle and some fat body. 'Ovary' samples include both ovaries and the common oviduct. 'Salivary gland' samples include the salivary duct, lateral lobes and median lobe. Salivary glands were rinsed extensively in PBS to remove the majority of fat body associated with the glands. 'Carcass' includes the thoracic and abdominal carcass and all tissues therein excluding those tissues individually described in the MozAtlas. Dissected tissues were placed immediately in Trizol to minimize the impact of dissection on the transcriptome. For each of four biological replicates, tissues were pooled from a minimum of 10 mosquitoes dissected at each time point. For each tissue and sex, an equal quantity of total RNA was pooled from three time points sampled after the blood-meal to obtain gene expression estimates throughout oogenesis (24, 48, 72 hrs). Each RNA sample (50 ng) was subsequently amplified in two cycle cDNA target labelling to generate biotinylated cRNA probes for hybridization on to Affymetrix microarrays .
Estimates of gene expression
Oligonucleotide probes and genes were mapped to AgamP3 genome assembly. Unless otherwise stated, datasets were analyzed with the R statistical programming language using programs maintained as part of the Bioconductor suite . In addition to microarray datasets for Anopheles, matching tissues obtained from the Drosophila FlyAtlas were re-analyzed with the same normalization procedure (GEO: GSE1690; GSE7763). Intensity values between arrays were first standardized within tissues for each species separately using the robust multi-array analysis package [44, 45]. The expression presence and absence calls were assessed with the signal to noise ratio of the perfect match and mismatch probes provided on Affymetrix arrays. Probes were used in further analysis only if they were deemed to be present in at least three tissue replicates. All estimates of differential expression were adjusted for multiple testing using the false discovery rate method . Array data has been submitted to the Gene Expression Omnibus under GSE21689.
Sexual dimorphism and tissue specificity
Sexual dimorphism was determined with a linear model of gene expression fit to male and female samples for each tissue as implemented in the LIMMA library . On the basis of differential expression, we subsequently identified probes as either male-biased or female-biased where there was a significant 2-fold change of intensity in one sex, in addition to statistical significance at the Q< 0.05 level (Additional File 3). Two measures of tissue specificity were also calculated: probe detection and tissue expression breadth. Probes were deemed tissue-specific if at least 3 out of 4 mismatch calls were found, but only in a single tissue and sex. In comparison, tissue breadth was measured by normalizing against maximal expression to generate the tau-statistic . The resulting tau-statistic falls within the range of 0 to 1, in which higher values indicate greater tissue-biased expression. Anopheles and Drosophila Gene Ontology annotations (Biological Process, Molecular Function, Cellular Component) and the enrichment of functions were determined using FlyMine with a 1% false discovery rate for multiple testing correction .
When sequences are available for multiple individual in a species, the ratio of observed non-synonymous mutation rate (A) to the synonymous mutation rate (S) can be utilized as an estimate of the selective pressure. To estimate sequence polymorphism within Anopheles we conducted a large-scale survey of dbSNP . While it is not possible to measure selective constraint on individual proteins directly using this approach, it has been demonstrated that when a group of genes are measured together, estimates of variation are robust and in good agreement with A/S for divergence .
Since microarray platforms were designed separately for Drosophila and Anopheles, probes have different affinities to their target RNAs, making the normalization of orthology expression between chips difficult. In order to compare tissue expression profiles between species, each gene was represented as a vector of relative expression abundance (RA) across the sampled tissues to avoid over-estimating divergence based on absolute expression intensity. Where genes are represented by multiple probes, the maximum intensity value recorded in each tissue was used for subsequent analysis. Since the FlyAtlas does not have separate samples for males and females, we combined male and female samples in the MozAtlas to make comparisons between species. Hierarchical clustering of orthologues was performed with measures of RA within and between species. For gene-wise clustering, we used Pearson correlation coefficient as the distance measure and defined similarity between clusters using average-linkage clustering. Co-regulated genes were defined as any group with an average similarity of greater than 0.8 that also contained more than 50 genes. Among species clusters, orthologue overlap was subsequently investigated with a hypergeometric probability distribution to determine enrichment.
DNA and protein sequences were obtained for D. melanogaster and A. gambiae (Ensembl v50) , Tribolium casteneum (Version 3; BeetleBase) , Apis melifera (Version 2; BeeBase)  and Caenorhabditis elegans (ws160; Ensembl v50) . One-to-one orthology relationships were determined using Inparanoid with default parameters, we selected the longest available translation for each annotated protein . Best reciprocal hits between species were grouped together into broader gene-families, and the sequences aligned with MUSCLE . Tree topologies were subsequently reconstructed with both dS (synonymous substitution rate), dN (nonsynonymous substitution rate), nucleotide and protein distance measures using TreeBest [56, 57]. From back-translation of protein alignments, TreeBest creates a consensus tree by merging the results of neighbour joining and maximum likelihood (ML) trees. By default, ML trees based on protein alignment are built under the WAG model, while ML tree based on DNA are built under the HKY model, which models non-uniform base composition and transition/transversion rate bias . Orthology relationships are described as one-to-one, one-to-many and many-to-many gene relationships.
This study was funded by a Grant from the Foundation for the National Institutes of Health through the Grand Challenges in Global Health initiative.
- Hahn MW, Lanzaro GC: Female-biased gene expression in the malaria mosquito Anopheles gambiae. Curr Biol. 2005, 15: R192-193. 10.1016/j.cub.2005.03.005.View ArticlePubMedGoogle Scholar
- Marinotti O, et al: Genome-wide analysis of gene expression in adult Anopheles gambiae. Insect Mol Biol. 2006, 15: 1-12. 10.1111/j.1365-2583.2006.00610.x.View ArticlePubMedGoogle Scholar
- Dana AN, Hong YS, Kern MK, Hillenmeyer ME, Harker BW, Lobo NF, Hogan JR, Romans P, Collins FH: Gene expression patterns associated with blood-feeding in the malaria mosquito Anopheles gambiae. BMC Genomics. 2005, 6: 5-10.1186/1471-2164-6-5.View ArticlePubMedPubMed CentralGoogle Scholar
- Arcà B, Lombardo F, Valenzuela JG, Francischetti IM, Marinotti O, Coluzzi M, Ribeiro JM: An updated catalogue of salivary gland transcripts in the adult female mosquito, Anopheles gambiae. J Exp Biol. 2005, 208: 3971-86. 10.1242/jeb.01849.View ArticlePubMedGoogle Scholar
- Calvo E, Pham VM, Lombardo F, Arcà B, Ribeiro JM: The sialotranscriptome of adult male Anopheles gambiae mosquitoes. Insect Biochem Mol Biol. 2006, 36: 570-5. 10.1016/j.ibmb.2006.04.005.View ArticlePubMedGoogle Scholar
- Koutsos AC, Blass C, Meister S, Schmidt S, MacCallum RM, Soares MB, Collins FH, Benes V, Zdobnov E, Kafatos FC, Christophides GK: Life cycle transcriptome of the malaria mosquito Anopheles gambiae and comparison with the fruitfly Drosophila melanogaster. Proc Natl Acad Sci USA. 2007, 104: 11304-9. 10.1073/pnas.0703988104.View ArticlePubMedPubMed CentralGoogle Scholar
- Biessmann H, Nguyen QK, Le D, Walter MF: Microarray-based survey of a subset of putative olfactory genes in the mosquito Anopheles gambiae. Insect Mol Biol. 2005, 14: 575-89. 10.1111/j.1365-2583.2005.00590.x.View ArticlePubMedGoogle Scholar
- Iatrou K, Biessmann H: Sex-biased expression of odorant receptors in antennae and palps of the African malaria vector Anopheles gambiae. Insect Biochem Mol Biol. 2008, 38: 268-74. 10.1016/j.ibmb.2007.11.008.View ArticlePubMedGoogle Scholar
- Burt A: Site-specific selfish genes as tools for the control and genetic engineering of natural populations. Proc Biol Sci. 2003, 270: 921-928. 10.1098/rspb.2002.2319.View ArticlePubMedPubMed CentralGoogle Scholar
- Heinrich J, Scott M: A repressible female-specific lethal genetic system for making transgenic insect strains suitable for a sterile-release program. Proc Natl Acad Sci USA. 2000, 97: 8229-8232. 10.1073/pnas.140142697.View ArticlePubMedPubMed CentralGoogle Scholar
- Thomas DD, Donnelly CA, Wood RJ, Alphey LS: Insect population control using a dominant, repressible, lethal genetic system. Science. 2000, 287: 2474-2476. 10.1126/science.287.5462.2474.View ArticlePubMedGoogle Scholar
- Franz AW, Sanchez-Vargas I, Adelman ZN, Blair CD, Beaty BJ, James AA, Olson KE: Engineering RNA interference-based resistance to dengue virus type 2 in genetically modified Aedes aegypti. Proc Natl Acad Sci USA. 2006, 103: 4198-4203. 10.1073/pnas.0600479103.View ArticlePubMedPubMed CentralGoogle Scholar
- Phuc HK, Andreasen MH, Burton RS, Vass C, Epton MJ, Pape G, Fu G, Condon KC, Scaife S, Donnelly CA, et al: Late-acting dominant lethal genetic systems and mosquito control. BMC Biol. 2007, 5: 11-10.1186/1741-7007-5-11.View ArticlePubMedPubMed CentralGoogle Scholar
- Windbichler N, Papathanos PA, Catteruccia F, Ranson H, Burt A, Crisanti A: Homing endonuclease mediated gene targeting in Anopheles gambiae cells and embryos. Nucleic Acids Res. 2007, 35: 5922-5933. 10.1093/nar/gkm632.View ArticlePubMedPubMed CentralGoogle Scholar
- Fu G, Lees RS, Nimmo D, Aw D, Jin L, Gray P, Berendonk TU, White-Cooper H, Scaife S, Kim Phuc H, et al: Female-specific flightless phenotype for mosquito control. Proc Natl Acad Sci USA. 2010, 107: 4550-4. 10.1073/pnas.1000251107.View ArticlePubMedPubMed CentralGoogle Scholar
- Larracuente AM, Sackton TB, Greenberg AJ, Wong A, Singh ND, Sturgill D, Zhang Y, Oliver B, Clark AG: Evolution of protein-coding genes in Drosophila. Trends Genet. 2008, 24: 114-123. 10.1016/j.tig.2007.12.001.View ArticlePubMedGoogle Scholar
- Sherry ST, et al: dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001, 29: 308-311. 10.1093/nar/29.1.308.View ArticlePubMedPubMed CentralGoogle Scholar
- Sturgill D, Zhang Y, Parisi M, Oliver B: Demasculinization of x chromosomes in the Drosophila genus. Nature. 2007, 450: 238-241. 10.1038/nature06330.View ArticlePubMedPubMed CentralGoogle Scholar
- Chintapalli VR, Wang J, Dow JA: Using FlyAtlas to identify better Drosophila melanogaster models of human disease. Nat Genet. 2007, 39: 715-720. 10.1038/ng2049.View ArticlePubMedGoogle Scholar
- Carey AF, Wang G, Su C, Zwiebel LJ, Carlson JR: Odorant reception in the malaria mosquito Anopheles gambiae. Nature. 2010, 464: 66-71. 10.1038/nature08834.View ArticlePubMedPubMed CentralGoogle Scholar
- Warr E, Aguilar R, Dong Y, Mahairaki V, Dimopoulos G: Spatial and sex-specific dissection of the Anopheles gambiae midgut transcriptome. BMC Genomics. 2007, 8: 37-10.1186/1471-2164-8-37.View ArticlePubMedPubMed CentralGoogle Scholar
- Dunkov B, Georgieva T: Insect iron binding proteins: insights from the genomes. Insect Biochem Mol Biol. 2006, 36: 300-309. 10.1016/j.ibmb.2006.01.007.View ArticlePubMedGoogle Scholar
- Nichol H, Law JH, Winzerling JJ: Iron metabolism in insects. Annu Rev Entomol. 2002, 47: 535-559. 10.1146/annurev.ento.47.091201.145237.View ArticlePubMedGoogle Scholar
- Rogers DW, Whitten MM, Thailayil J, Soichot J, Levashina EA, Catteruccia F: Molecular and cellular components of the mating machinery in Anopheles gambiae females. Proc Natl Acad Sci USA. 2008, 105: 19390-19395. 10.1073/pnas.0809723105.View ArticlePubMedPubMed CentralGoogle Scholar
- Haerty W, Jagadeeshan S, Kulathinal RJ, Wong A, Ravi Ram K, Sirot LK, Levesque L, Artieri CG, Wolfner MF, Civetta A, et al: Evolution in the fast lane: rapidly evolving sex-related genes in Drosophila. Genetics. 2007, 177: 1321-1335. 10.1534/genetics.107.078865.View ArticlePubMedPubMed CentralGoogle Scholar
- Tripet F, Touré YT, Dolo G, Lanzaro GC: Frequency of multiple inseminations in field-collected Anopheles gambiae females revealed by DNA analysis of transferred sperm. Am J Trop Med Hyg. 2003, 68: 1-5.PubMedGoogle Scholar
- Galanopoulos VK, Orr W, Szabad J, Kafatos FC: Genetic analysis of chorion formation in Drosophila melanogaster: I. The effects of one somatic-specific and seven germ-line-specific mutations. Dev Genet. 1989, 10: 87-97. 10.1002/dvg.1020100204.View ArticlePubMedGoogle Scholar
- Amenya DA, Chou W, Li J, Yan G, Gershon PD, James AA, Marinotti O: Proteomics reveals novel components of the Anopheles gambiae eggshell. J Insect Physiol. 2010, 56: 1414-1419. 10.1016/j.jinsphys.2010.04.013.View ArticlePubMedPubMed CentralGoogle Scholar
- Vibranovski MD, Zhang Y, Long M: General gene movement off the × chromosome in the Drosophila genus. Genome Res. 2009, 19: 897-903. 10.1101/gr.088609.108.View ArticlePubMedPubMed CentralGoogle Scholar
- Kemkemer C, Hense W, Parsch J: Fine-scale analysis of × chromosome inactivation in the male germline of Drosophila melanogaster. Mol Biol Evol. 2010,Google Scholar
- Bean CJ, Schaner CE, Kelly WG: Meiotic pairing and imprinted × chromatin assembly in Caenorhabditis elegans. Nat Genet. 2004, 36: 100-105. 10.1038/ng1283.View ArticlePubMedGoogle Scholar
- Khil PP, Smirnova NA, Romanienko PJ, Camerini-Otero RD: The mouse × chromosome is enriched for sex-biased genes not subject to selection by meiotic sex chromosome inactivation. Nat Genet. 2004, 36: 642-646. 10.1038/ng1368.View ArticlePubMedGoogle Scholar
- Wu CI, Xu EY: Sexual antagonism and × inactivation--the SAXI hypothesis. Trends Genet. 2003, 19: 243-247. 10.1016/S0168-9525(03)00058-1.View ArticlePubMedGoogle Scholar
- Khaitovich P, Hellmann I, Enard W, Nowick K, Leinweber M, Franz H, Weiss G, Lachmann M, P ääbo S: Parallel patterns of evolution in the genomes and transcriptomes of humans and chimpanzees. Science. 2005, 309: 1850-1854. 10.1126/science.1108296.View ArticlePubMedGoogle Scholar
- Zhang Y, Sturgill D, Parisi M, Kumar S, Oliver B: Constraint and turnover in sex-biased gene expression in the genus Drosophila. Nature. 2007, 450: 233-237. 10.1038/nature06323.View ArticlePubMedPubMed CentralGoogle Scholar
- Ranz JM, Castillo-Davis CI, Meiklejohn CD, Hartl DL, et al: 2003, Sex-dependent gene expression and evolution of the Drosophila transcriptome. Science. 2003, 300: 1742-1755. 10.1126/science.1085881.View ArticlePubMedGoogle Scholar
- Meiklejohn CD, Parsch J, Ranz JM, Hartl DL: Rapid evolution of male-biased gene expression in Drosophila. Proc Natl Acad Sci USA. 2003, 100: 9894-9899. 10.1073/pnas.1630690100.View ArticlePubMedPubMed CentralGoogle Scholar
- Voolstra C, Tautz D, Farbrother P, Eichinger L, Harr B: Contrasting evolution of expression differences in the testis between species and subspecies of the house mouse. Genome Res. 2007, 17: 42-49.View ArticlePubMedPubMed CentralGoogle Scholar
- Wang J, Kean L, Yang J, Allan AK, Davies SA, Herzyk P, Dow JA: Function-informed transcriptome analysis of Drosophila renal tubule. Genome Biol. 2004, 5: R69-10.1186/gb-2004-5-9-r69.View ArticlePubMedPubMed CentralGoogle Scholar
- Hahn MW, Han MV, Han SG: Gene family evolution across 12 Drosophila genomes. PLoS Genet. 2007, 3: e197-10.1371/journal.pgen.0030197.View ArticlePubMedPubMed CentralGoogle Scholar
- Arcà B, Lombardo F, Francischetti IM, Pham VM, Mestres-Simon M, Andersen JF, Ribeiro JM: An insight into the sialome of the adult female mosquito Aedes albopictus. Insect Biochem Mol Biol. 2007, 37: 107-27. 10.1016/j.ibmb.2006.10.007.View ArticlePubMedGoogle Scholar
- Affymetrix GeneChip Expression Analysis: Technical Manual. 701021 Rev. 5. 2004, Santa Clara, CA, AffymetrixGoogle Scholar
- Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, et al: Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004, 5: R80-10.1186/gb-2004-5-10-r80.View ArticlePubMedPubMed CentralGoogle Scholar
- Irizarry RA, et al: Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 2003, 4: 249-264. 10.1093/biostatistics/4.2.249.View ArticlePubMedGoogle Scholar
- Wu Z, Irizarry RA, Gentleman R, Martinez-Murillo F, Spencer F: A Model-Based Background Adjustment for Oligonucleotide Expression Arrays. J Am Stat Assoc. 2004, 99: 909-10.1198/016214504000000683.View ArticleGoogle Scholar
- Hochberg Y: Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Royal Stat Soc B. 1995, 57: 289-300.Google Scholar
- Smyth GK: Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 2004, 3: Article 3-Google Scholar
- Yanai I, Benjamin H, Shmoish M, Chalifa-Caspi V, Shklar M, Ophir R, Bar-Even A, Horn-Saban S, Safran M, Domany E, et al: Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification. Bioinformatics. 2005, 21: 650-659. 10.1093/bioinformatics/bti042.View ArticlePubMedGoogle Scholar
- Lyne R, Smith R, Rutherford K, Wakeling M, Varley A, Guillier F, Janssens H, Ji W, Mclaren P, North P, et al: FlyMine: an integrated database for Drosophila and Anopheles genomics. Genome Biol. 2007, 8: R129-10.1186/gb-2007-8-7-r129.View ArticlePubMedPubMed CentralGoogle Scholar
- Liu J, Zhang Y, Lei X, Zhang Z: Natural selection of protein structural and functional properties: a single nucleotide polymorphism perspective. Genome Biol. 2008, 9: R69-10.1186/gb-2008-9-4-r69.View ArticlePubMedPubMed CentralGoogle Scholar
- Flicek P, Aken BL, Ballester B, Beal K, Bragin E, Brent S, Chen Y, Clapham P, Coates G, Fairley S, et al: Ensembl's 10th year. Nucleic Acids Res. 2010, 38: D557-562. 10.1093/nar/gkp972.View ArticlePubMedGoogle Scholar
- Wang L, Wang S, Li Y, Paradesi MS, Brown SJ: BeetleBase: the model organism database for Tribolium castaneum. Nucleic Acids Res. 2007, 35: D476-479. 10.1093/nar/gkl776.View ArticlePubMedGoogle Scholar
- Elsik CG, Worley KC, Zhang L, Milshina NV, Jiang H, Reese JT, Childs KL, Venkatraman A, Dickens CM, Weinstock GM, et al: Community annotation: procedures, protocols, and supporting tools. Genome Res. 2006, 16: 1329-1333. 10.1101/gr.5580606.View ArticlePubMedGoogle Scholar
- O'Brien KP, Remm M, Sonnhammer EL, Inparanoid : A Comprehensive Database of Eukaryotic Orthologs. NAR. 2005, 33: D476-D480.View ArticlePubMedGoogle Scholar
- Edgar RC: MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics. 2004, 5: 113-10.1186/1471-2105-5-113.View ArticlePubMedPubMed CentralGoogle Scholar
- TreeSoft: Softwares for Phylogenetic Trees. [http://treesoft.sourceforge.net/treebest.shtml]
- Ruan J, et al: TreeFam: Update. Nucleic Acids Res. 2008, 36: D735-D740.View ArticlePubMedGoogle Scholar
- Guindon S, Lethiec F, Duroux P, Gascuel O: PHYML Online-a web server for fast maximum likelihood-based phylogenetic inference. Nucleic Acids Res. 2005, 33: W557-W559. 10.1093/nar/gki352.View ArticlePubMedPubMed CentralGoogle Scholar