An expressed sequence tag (EST) library for Drosophila serrata, a model system for sexual selection and climatic adaptation studies
© Frentiu et al; licensee BioMed Central Ltd. 2009
Received: 01 August 2008
Accepted: 21 January 2009
Published: 21 January 2009
The native Australian fly Drosophila serrata belongs to the highly speciose montium subgroup of the melanogaster species group. It has recently emerged as an excellent model system with which to address a number of important questions, including the evolution of traits under sexual selection and traits involved in climatic adaptation along latitudinal gradients. Understanding the molecular genetic basis of such traits has been limited by a lack of genomic resources for this species. Here, we present the first expressed sequence tag (EST) collection for D. serrata that will enable the identification of genes underlying sexually-selected phenotypes and physiological responses to environmental change and may help resolve controversial phylogenetic relationships within the montium subgroup.
A normalized cDNA library was constructed from whole fly bodies at several developmental stages, including larvae and adults. Assembly of 11,616 clones sequenced from the 3' end allowed us to identify 6,607 unique contigs, of which at least 90% encoded peptides. Partial transcripts were discovered from a variety of genes of evolutionary interest by BLASTing contigs against the 12 Drosophila genomes currently sequenced. By incorporating into the cDNA library multiple individuals from populations spanning a large portion of the geographical range of D. serrata, we were able to identify 11,057 putative single nucleotide polymorphisms (SNPs), with 278 different contigs having at least one "double hit" SNP that is highly likely to be a real polymorphism. At least 394 EST-associated microsatellite markers, representing 355 different contigs, were also found, providing an additional set of genetic markers. The assembled EST library is available online at http://www.chenowethlab.org/serrata/index.cgi.
We have provided the first gene collection and largest set of polymorphic genetic markers, to date, for the fly D. serrata. The EST collection will provide much needed genomic resources for this model species and facilitate comparative evolutionary studies within the montium subgroup of the D. melanogaster lineage.
The genus Drosophila has proved to be one of the most useful groups of organisms with which to investigate fundamental questions in biology. The melanogaster group, in particular, has provided many of the model species currently studied by evolutionary biologists, including the native Australian fly Drosophila serrata . D. serrata belongs to montium, the most speciose yet taxonomically least understood subgroup in the melanogaster group [2, 3]. The utility of D. serrata in addressing evolutionary questions has been long recognized, for example in studies of speciation [4, 5]. More recently, it has gained prominence as a model species for investigating the evolution of traits involved in sexual selection and mate recognition [6–8] and climatic adaptation [9–11]. The identification of functional genetic variants underlying phenotypes of interest, however, has been limited by the absence of a species-specific gene collection.
In recent years Drosophila serrata has become an important system with which to investigate sexual selection. The fly uses a blend of cuticular hydrocarbons (CHCs) as contact pheromones for mate and species recognition . Studies utilizing D. serrata have, for example, investigated the evolution of sexual dimorphism in CHCs [12, 13], divergence of mating preference in novel environments  and post-copulatory sexual selection . Population differences in sexual selection regimes and the underlying genetic architecture of CHCs have also been identified [16, 17], raising the possibility that different loci and/or alleles may be implicated in generating these phenotypes in each population. Although the quantitative genetic basis of CHCs under sexual selection is well understood in this species [18–20], the molecular genetic basis of these phenotypes remains unknown.
The utility of Drosophila serrata to comparative studies (e.g. sexual character evolution) requires an accurate reconstruction of evolutionary relationships. The resolution of systematic relationships in the melanogaster group, however, has proved notoriously problematic [27–30]. Within the montium subgoup, in particular, the high degree of morphological convergence and similarity in male genitalia coupled with limited fossil representation has meant that taxonomic relationships are particularly unclear , necessitating a gene-based approach. Attempts to resolve phylogenetic relationships within the montium subgroup have so far been both sparse and based on very few genes , although relationships among the Australian species have recently received more attention [22, 32, 33]. Resolution of phylogenetic relationships in the highly speciose montium subgroup requires the development of additional genetic markers.
A cost-effective way of identifying a large number of genetic loci is to build an EST library , especially for species possessing a large genome and without a genome sequencing project. ESTs are single read sequences produced from sequencing an mRNA pool that samples the transcribed genes within a given set of tissues, individuals or populations. An EST library represents a resource that can be used for many downstream applications to address questions in evolution and ecology. For example, an EST collection can aid identification of genes underlying phenotypes of interest through the development of expression arrays  and provide a wealth of markers that may offer resolution of previously problematic phylogenetic relationships . Additionally, single nucleotide polymorphisms (SNPs) and simple sequence repeat (SSR) markers (e.g. microsatellites) occurring within EST regions provide a source of potential markers for QTL mapping applications  and population genomic studies [38, 39].
Here, we describe an EST collection from a normalized whole body library for Drosophila serrata as a genomic resource for this model species. The study was designed to simultaneously identify sets of genes potentially involved in the expression of traits of interest to evolutionary biologists and to provide an array of molecular markers for population genomic studies by incorporating multiple individuals from several natural populations of the species. We present the sequences of 6,607 putative genes and outline the discovery of numerous microsatellite and SNP markers present in the dataset. Using this EST collection, we have identified several genes which we hypothesize may be involved in the expression of traits that are implicated in sexual selection and climatic adaptation in D. serrata. Additionally, we have identified genetic loci that may eventually resolve the phylogeny of the montium subgroup. Individual EST reads are available from Genbank and dbEST (accessions FK858115 – FK867478 and 59290665 – 59300028 respectively) and from http://www.chenowethlab.org/serrata/index.cgi.
Contigs (≥ 2 ESTs)
Contigs – peptides
Contigs – other#
EST annotation and identification of genes of interest
EST contigs annotated to genes of interest
Sexual selection and CHCs
Protein, ejaculatory bulb (CG2668-PA)
Yolk protein 2 (CG2979-PA)
Yolk protein 3
Alcohol dehydrogenase (Adh)
Glycerol 3 phosphate dehydrogenase (GPDH)
Cytochrome oxidase subunit II (COII)
The chromosomal distribution of ESTs surveyed in this library was largely similar to that present in Drosophila melanogaster. Chromosomes 2, 3, X and 4 accounted for approximately 37%, 44%, 16% and 0.01% respectively of the total percentage of ESTs discovered in D. serrata. This distribution is close to that observed for D. melanogaster, with chromosomes 2, 3, X and 4 accounting for 37%, 44%, 18% and ~0.01% respectively of the total genome . X-linked sequences are slightly underrepresented in D. serrata compared to D. melanogaster, a result that may be due to the small number of transcripts surveyed in our study or may reflect real biological differences between the species. The number of putative genes identified in our library that were protein coding was 6,009, resulting in a gene density of ~5 genes per Kb if we assume the D. melanogaster euchromatin amount . Given our limited sequencing effort necessitated by cost constraints, these numbers compare well given the estimate of ~14,000 genes in D. melanogster [59, 60] and suggest we have captured slightly less than half of the genes present in the genome. However, a large number were loci that are identified as CG-id only on Flybase, of which on average over half are estimated to be computational predictions with uncharacterized functions and may not represent real genes .
Genetic markers for mapping and population studies
EST-derived microsatellite statistics
Imperfect repeats (< 2 mismatches)
(± S. E.)
(± S. E.)
18.87 (± 6.43)
23.31 (± 9.22)
20.58 (± 3.40)
22.43 (± 11.61)
29.00 (± 4.97)
19.81 (± 8.42)
17.99 (± 4.08)
44.00 (± 0)
23.98 (± 8.31)
Drosophila serrata EST web database
The D. serrata EST collection presented here is available on the web at http://www.chenowethlab.org/serrata/index.cgi. The site comprises several pages from which EST contigs are available for download in several formats (e.g. FASTA). The 'Search' page allows the user to find particular transcripts either by contig identity, annotation or chromosome location (based on Drosophila melanogaster chromosome designation) and for particular microsatellites by sequence type and repeat number. It should be noted that the chromosome arm labeled as 3R of D. serrata by [25, 64] is equivalent to the 2L and not the 3R of D. melanogaster due to an earlier labeling error . Workers wishing to map genes to the D. serrata chromosome labeled as 3R by [25, 64] using sequence homology with D. melanogaster should choose genes found on the 2L arm of the latter species. Contigs can also be viewed either by gene name or by GO terminology. A TAB formatted file provides additional information for each contig, including contig length and results of BLAST searches against other databases (see above). Detailed BLAST results are also available as XML files linked to each contig. The D. serrata EST web database can also be queried using the BLAST tool hosted on the site. Contig identification codes fall into three categories: 1) contigs comprising at least two transcripts, denoted by CL followed by a number from 1 to 1,210; 2) singleton contigs of good sequence quality, denoted by CL0; and 3) singleton contigs of poorer sequence quality, denoted by CLx. A total of 9,364 individual EST reads, excluding rRNAs, RNAs of mitochondrial origin and sequences shorter than 50 bp, have been deposited with Genbank (accessions FK858115 – FK867478) and dbEST (accessions 59290665 – 59300028).
Here we have described an EST collection for the native Australian fly Drosophila serrata that has become a prominent model for studies of sexual selection and climatic adaptation. Using a normalized library from whole fly bodies and 3' end Sanger sequencing of clones, we generated a functionally diverse collection of 6,607 EST contigs, the majority of which encoded peptides in addition to 3' UTRs. Using BLAST analyses we were able to successfully assign putative functions to EST contigs according to sequence homology with the 12 Drosophila genomes available in FlyBase http://flybase.bio.indiana.edu. This unique collection of ESTs will greatly facilitate the development of genomic applications in D. serrata, such as gene expression arrays.
Our approach of incorporating multiple individuals from collections spanning the geographic distribution of the species allowed us to generate genetic markers for population level studies. We identified at least 394 EST-associated microsatellites and, by aligning in a single contig sequences representing different naturally occurring alleles, we discovered at least 1,254 high quality SNP markers. We have already designed and tested primers for 150 EST-derived microsatellites currently being used in QTL mapping studies of traits under sexual selection in D. serrata. Although the total number of SNPs found in the EST collection was 11,210, over half of these were found in contigs of sequence depth ≤ 3 sequences. An additional proportion was found in contigs of depth of at least four sequences but represented by only one allele. An unknown fraction of these SNPs is probably due to reverse transcription and amplification errors during library synthesis, poor quality sequence and assembly and alignment errors rather than genuine polymorphisms. Despite this, we were still able to identify a large number of potentially polymorphic SNPs by considering only those found in contigs of at least four sequences and where the minor allele is found in two transcripts or more. Our results and those of previous workers  suggest that SNP identification can be highly successful from normalized EST libraries if multiple individuals are included in the original mRNA pool, although polymorphic marker identification may be biased towards those found in highly transcribed genes.
Gene annotation against the 12 Drosophila genomes available in FlyBase also allowed identification of genes that may underlie traits of evolutionary and ecological interest. We found at least nine genes that may be involved in the expression of traits under sexual selection (Table 2) such as cuticular hydrocarbons. For example, we have identified partial transcripts from two desaturases (desat1 and desat2) and an elongase involved in CHC biosythesis  (Table 2). Functional polymorphism in desaturase and elongase genes has been shown to produce different CHC profiles in Drosophila simulans and D. melanogaster [44, 46, 65]. The partial transcripts of the desaturase and elongase genes have already been used to design primers for rapid amplification of cDNA ends (RACE) studies, with the goal of obtaining full-length sequences. We have also identified an accessory protein (Acp70A-1; Table 2) transcript in D. serrata that may be involved in male sperm and seminal fluid traits, as has been found in D. melanogaster [47, 66]. Previous work has shown that D. serrata exhibits particularly high female remating rates and levels of multiple paternity in both lab and field populations . Insemination rates and multiple paternity levels may be highly dependent on sperm characteristics and may reflect genetic polymorphism among males at particular genes [47, 67].
Our EST collection and array of microsatellite and SNP makers may also facilitate further exploration of the molecular genetic basis of climatic adaptation along a latitudinal cline in Australian Drosophila serrata. First, we found a number of heat shock protein (Hsp) and other genes (Table 2) that are thought to modulate physiological tolerance to temperature in D. melanogaster [68, 69]. One of these genes, Hsp83 (also known as Hsp90) has been implicated in cold resistance in the closely related species D. birchii . Second, genes involved in CHC biosynthesis may also be involved in desiccation resistance along the cline since cuticular hydrocarbons also serve to waterproof the insect . The genes desat1, desat2 and elongase are of particular interest since they have been shown to mediate CHC polymorphism in D. melanogaster [44–46] a trait that displays clinal variation in Australia in both Drosophila species . For example, desat2 is involved in the biosynthesis of 5,9 dienes in D. melanogaster , compounds which are also found in D. serrata . The gene elongase is also involved in the synthesis of longer chained dienes in D. melanogaster  that are also expressed in D. serrata. Third, the SNPs and microsatellites found in the EST collection could be used to identify genomic regions that may be involved in climatic adaptation. Pronounced genetic divergence at genes underlying phenotypes under selection compared to neutrally evolving markers and specific patterns of sequence polymorphism may indicate areas of the genome involved in adaptation along a cline . Fourth, microarray probes can now be designed to detect changes in gene regulation in response to selection on particular phenotypic traits known to vary clinally. Fifth, our EST collection facilitates physical mapping of particular genes to chromosomal inversions in D. serrata and may help resolve the degree of chromosomal synteny between montium and other subgroups of the D. melanogaster group.
Finally, we were able to identify genes that should be of phylogenetic utility in resolving relationships within the montium subgroup of the Drosophila melanogaster group, which to date remain unclear . EST collections provide a means of obtaining partial sequence for many genes at once, providing potential resolution of previously problematic taxonomic relationships . Partial transcripts from several genes of phylogenetic interest (e.g. aconitase, PGI) were found in our EST collection and potentially more might be identified by BLAST searches using other phylogenetically relevant genes as queries against our database. At the time of development and analysis of our D. serrata EST database, D. kikkawai, D. jambulina and D. birchii were the only other montium species with any significant molecular data in Genbank, out of a subgroup of over 100 species. Phylogenetic markers may be developed using data from these four species for use in other montium taxa, by designing degenerate primers for example. Further work will help resolve phylogenetic relationships in this important subgroup and will allow accurate tracing of the evolutionary history of interesting traits, among other questions.
Drosophila serrata is a native Australian fly that has recently become a prominent model system with which to investigate the evolution of traits under sexual selection and traits involved in climatic adaptation. Understanding the molecular genetic basis of traits of interest to evolutionary biologists has been hampered by a lack of genomic resources for this species. Here, we have reported the development of an EST library for D. serrata from whole fly bodies at several stages of development. We sequenced 11,616 EST clones from the 3' end that were assembled into 6,607 contigs. The majority of contigs was found to contain peptide-coding sequence in addition to 3' UTR and represented a substantially diverse set of gene functions. At least 394 potentially polymorphic microsatellites were found associated with the EST contigs. By incorporating multiple individuals from five populations throughout the distribution of D. serrata, we were able to identify a large number of SNPs, including at least 1,254 'double hit', high quality sequence variants. The EST library contained partial transcripts from genes of interest to studies investigating the molecular genetic basis of sexual sexually selected traits, for example desaturases involved in CHC biosynthesis. A number of genes were also discovered that may code for phenotypes implicated in climatic adaptation along a latitudinal gradient in D. serrata, for example heat shock proteins. The EST library has also revealed a number of genes of potential phylogenetic utility and that may help resolve evolutionary relationships within the highly speciose montium subgroup. We anticipate the genomic resources provided by the EST library will facilitate numerous downstream applications that will answer fundamental questions in evolutionary biology using D. serrata as a model organism.
Fly populations and RNA isolation
Our EST project was designed to simultaneously generate a library of putative genes for sexually selected traits and polymorphic markers for population level studies. The D. serrata sample comprised larvae at the last instar (N = 30) and five adult stages: day 0 (emergence) (30 females, 30 males), day 1 (25 females, 30 males), day 2 (22 females, 28 males), day 3 (30 females, 28 males) and day 4 (23 females, 24 males). Several life stages were used in order to maximize gene discovery for further microarray and gene expression studies. Within the sample used, five populations were represented, spanning the geographical distribution of D. serrata on the east coast of Australia: Cooktown, Cardwell, Sarina, Brisbane and Forster (Figure 1). Flies were obtained from mass bred cultures established from wild-caught inseminated females (N = 20) from each of the five geographical locations and maintained at large population sizes in the laboratory for approximately two years.
Individuals were removed from rearing bottles and immediately frozen in liquid nitrogen. Total RNA was extracted from whole fly bodies using Trizol (Invitrogen, Australia) and mRNA purified using the GenElute mRNA miniprep kit (Sigma-Aldrich, Australia). Equimolar amounts of mRNA from each sex and each life stage were pooled to construct a single cDNA library. Library construction and normalization were performed by Agencourt Biosciences (MA, USA) according to proprietary protocols.
EST sequencing and assembly
Sequencing was performed from the 3' end of transcripts. There are several advantages to this strategy. First, identification of unique contigs (and therefore putatively unique genes) is more reliable than in 5' sequencing projects since alternative splicing is much more frequent in 5' as opposed to 3' UTR , meaning that it is more likely for transcripts of the same gene to share a common polyA tail. This reliability combined with the depth of alignments containing transcripts from multiple individuals facilitates discovery of polymorphic molecular markers, like SNPs and microsatellites . Second, they represent much better features for expression arrays since cross-hybridization amongst gene families is reduced due to 3' UTRs being generally less conserved than coding regions.
Sanger sequencing of the 3' ends of clones was performed by Agencourt Biosciences (MA, USA), using a proprietary sequencing primer. ESTs were clustered using the TGICL tool http://compbio.dfci.harvard.edu/tgi/software under the default parameters, with vector sequences and polyA tails masked. ESTs which were not assembled into any contig were identified and the quality of their sequence was determined using the program LUCY2  with the following parameters: error 0.025 – 0.02, bracket 20 – 0.02 and window (20 0.01 10 0.03). The shortest accepted length of good quality sequence was 18 bp. Single ESTs that passed quality trimming were then grouped into an artificial cluster denoted CL0 and ESTs that did not pass were grouped into another artificial cluster denoted CLx. Therefore, sequences in the cluster CL0 were quality trimmed whereas sequences in the cluster CLx were not. Assembled contigs and individual ESTs from clusters CL0 and CLx were then annotated in the same way.
Annotation of genes via sequence homology with other Drosophila
The 6,607 sequences (contigs and unassembled ESTs) were first queried using nucleotide versus protein blastx against the NCBI nr (non-redundant) protein database, limited to Drosophila entries. Blastx parameters were set to: amino acid substitution matrix BLOSUM-62 , a statistical significance threshold of 10 for database matches  and costs to open an alignment gap and extend a gap of 11 and 1 respectively. Query sequences were filtered for low compositional complexity using the program SEG . Sequences that did not match any proteins were annotated using the following Drosophila melanogaster release R5.1 sequences from FlyBase http://flybase.bio.indiana.edu/: microRNAs, miscellaneous RNAs, noncoding RNAs, all pseudogenes, all transposons and all transfer RNAs. Searches against FlyBase were performed using nucleotide vs. nucleotide blastn. Output from the blastx search was functionally annotated with Gene Ontology (GO) terminology using the blast2go tool with the default parameters http://www.blast2go.de. Genomic localization of the ESTs was done using the tool Exonerate  and the D. melanogaster genome as reference.
Microsatellite and SNP marker identification
The database of 6,607 contigs was mined for microsatellite and SNP markers to be used in future population genetic studies. For the identification of microsatellite markers, we used the program SciRoKo version 3.1  that can easily identify di- to hexanucleotide repeats. Searches were conducted to identify both uninterrupted and interrupted (≤ 2 bp mismatch) motifs, with a minimum number of repeat units of six.
Putative SNP markers were identified from all contigs with at least two ESTs by using a custom Perl script. Polymorphic sites were denoted using an IUB code (e.g. Y). Each SNP was assigned a quality score that was an average of individual PHRED scores for each sequence at that base position. ESTs often contain error mutations introduced during the reverse transcription process and spurious polymorphism may arise in contigs from incorrect assembly. Consequently, using the rationale of , we also identified SNPs that are represented by at least two sequences in contigs with at least four ESTs.
We would like to thank Anthony Cavallaro for technical assistance with RNA extractions. Four anonymous reviewers provided comments that greatly improved the manuscript. Funding for this work was provided by grants from the Australian Research Council (ARC) to SFC, MWB and EAM and a grant from the UQ Foundation awarded to SFC.
- Malloch JR: Notes on Australian Diptera No. X. Proceedings of the Linnean Society of New South Wales. 1927, 52: 1-16.Google Scholar
- Bächli G: TaxoDros. 2005, [http://taxodros.unizh.ch/]Google Scholar
- Lemeunier FD, Tsacas JR, Ashburner M: The melanogaster species group. The genetics and biology of Drosophila. Edited by: Ashburner M, Carson HL, Thompson JN Jr. 1986, London: Academic Press, 3e: 147-256.Google Scholar
- Ayala FJ: Sibling species of the Drosophila serrata group. Evolution. 1965, 19: 538-545. 10.2307/2406250.View ArticleGoogle Scholar
- Dobzhansky T, Mather WB: The evolutionary status of Drosophila serrata. Evolution. 1961, 15: 461-467. 10.2307/2406314.View ArticleGoogle Scholar
- Blows MW, Allan RA: Levels of mate recognition within and between two Drosophila species and their hybrids. American Naturalist. 1998, 152: 826-837. 10.1086/286211.View ArticlePubMedGoogle Scholar
- Chenoweth SF, Blows MW: Dissecting the complex genetic basis of mate choice. Nature Reviews Genetics. 2006, 7 (9): 681-692. 10.1038/nrg1924.View ArticlePubMedGoogle Scholar
- Higgie M, Chenoweth SF, Blows MW: Natural selection and the reinforcement of mate recognition. Science. 2000, 290 (5491): 519-521. 10.1126/science.290.5491.519.View ArticlePubMedGoogle Scholar
- Hallas R, Schiffer M, Hoffmann AA: Clinal variation in Drosophila serrata for stress resistance and body size. Genetical Research. 2002, 79 (2): 141-148. 10.1017/S0016672301005523.View ArticlePubMedGoogle Scholar
- Magiafoglou A, Carew ME, Hoffmann AA: Shifting clinal patterns and microsatellite variation in Drosophila serrata populations: a comparison of populations near the southern border of the species range. Journal of Evolutionary Biology. 2002, 15 (2002): 763-774. 10.1046/j.1420-9101.2002.00439.x.View ArticleGoogle Scholar
- Sgrò CM, Blows MW: Evolution of additive and nonadditive genetic variance in development time along a cline in Drosophila serrata. Evolution. 2003, 57 (8): 1846-1851.View ArticlePubMedGoogle Scholar
- Chenoweth SF, Blows MW: Signal trait sexual dimorphism and mutual sexual selection in Drosophila serrata. Evolution. 2003, 57 (10): 2326-2334.View ArticlePubMedGoogle Scholar
- Chenoweth SF, Blows MW: Contrasting mutual sexual selection on homologous signal traits in Drosophila serrata. American Naturalist. 2005, 165 (2): 281-289. 10.1086/427271.View ArticlePubMedGoogle Scholar
- Rundle HD, Chenoweth SF, Blows MW: The roles of natural and sexual selection during adaptation to a novel environment. Evolution. 2006, 60 (11): 2218-2225.View ArticlePubMedGoogle Scholar
- Frentiu FD, Chenoweth SF: Polyandry and paternity skew in natural and experimental populations of Drosophila serrata. Molecular Ecology. 2008, 17 (6): 1589-1596. 10.1111/j.1365-294X.2008.03693.x.View ArticlePubMedGoogle Scholar
- Chenoweth SF, Blows MW: QST meets the G matrix: the dimensionality of adaptive divergence in multiple correlated quantitative traits. Evolution. 2008, 62 (6): 1437-1449. 10.1111/j.1558-5646.2008.00374.x.View ArticlePubMedGoogle Scholar
- Rundle HD, Chenoweth SF, Blows MW: Comparing complex fitness surfaces: Among-population variation in mutual sexual selection in Drosophila serrata. American Naturalist. 2008, 171 (4): 443-454. 10.1086/528963.View ArticlePubMedGoogle Scholar
- Hine E, Blows MW: Determining the effective dimensionality of the genetic variance-covariance matrix. Genetics. 2006, 173 (2): 1135-1144. 10.1534/genetics.105.054627.PubMed CentralView ArticlePubMedGoogle Scholar
- Hine E, Chenoweth SF, Blows MW: Multivariate quantitative genetics and the lek paradox: Genetic variance in male sexually selected traits of Drosophila serrata under field conditions. Evolution. 2004, 58 (12): 2754-2762.View ArticlePubMedGoogle Scholar
- Petfield D, Chenoweth SF, Rundle HD, Blows MW: Genetic variance in female condition predicts indirect genetic variance in male sexual display traits. Proc Natl Acad Sci U S A. 2005, 102 (17): 6045-6050. 10.1073/pnas.0409378102.PubMed CentralView ArticlePubMedGoogle Scholar
- Frentiu FD, Chenoweth SF: Parallel clines in cuticular hydrocarbons in native and recently colonized Drosophila. In prep
- Schiffer M, Carew ME, Hoffmann AA: Molecular, morphological and behavioural data reveal the presence of a cryptic species in the widely studied Drosophila serrata species complex. Journal of Evolutionary Biology. 2004, 17 (2004): 430-442. 10.1046/j.1420-9101.2003.00657.x.View ArticlePubMedGoogle Scholar
- Jenkins NL, Hoffmann AA: Limits to the southern border of Drosophila serrata : Cold resistance, heritable variation and trade-offs. Evolution. 1999, 53: 1823-1834. 10.2307/2640443.View ArticleGoogle Scholar
- Hoffmann AA, Shirriffs J: Geographic variation for wing shape in Drosophila serrata. Evolution. 2002, 56 (5): 1068-1073.View ArticlePubMedGoogle Scholar
- Stocker AJ, Foley B, Hoffmann AA: Inversion frequencies of Drosophila serrata along an eastern Australian transect. Genome. 2004, 47 (6): 1144-1153. 10.1139/g04-078.View ArticlePubMedGoogle Scholar
- Hoffmann AA, Sgro CM, Weeks AR: Chromosomal inversion polymorphisms and adaptation. Trends in Ecology and Evolution. 2004, 19 (9): 482-488. 10.1016/j.tree.2004.06.013.View ArticlePubMedGoogle Scholar
- Kopp A: Basal relationships in the Drosophila melanogaster species group. Molecular Phylogenetics and Evolution. 2006, 39: 787-798. 10.1016/j.ympev.2006.01.029.View ArticlePubMedGoogle Scholar
- Lewis RL, Beckenbach AT, Mooers AØ: The phylogeny of subgroups within the melanogaster species group: Likelihood tests on COI and COII sequences and a Bayesian estimate of phylogeny. Molecular Phylogenetics and Evolution. 2005, 37: 15-24. 10.1016/j.ympev.2005.02.018.View ArticlePubMedGoogle Scholar
- Schawaroch V: Phylogeny of a paradigm lineage: the Drosophila melanogaster species group. Biological Journal of the Linnean Society. 2002, 76 (1): 21-37. 10.1111/j.1095-8312.2002.tb01711.x.View ArticleGoogle Scholar
- Wong A, Jensen JD, Pool JE, Aquadro CF: Phylogenetic incongruence in the Drosophila melanogaster species group. Molecular Phylogenetics and Evolution. 2007, 43: 1138-1150. 10.1016/j.ympev.2006.09.002.PubMed CentralView ArticlePubMedGoogle Scholar
- Da Lage J-L, Kergoat GJ, Maczowiak F, Silvain J-F, Cariou M-L, Lachaise D: A phylogeny of the Drosophilidae using the Amyrel gene: questioning the Drosophila melanogaster species group boundaries. Journal of Zoological Systematics and Evolutionary Research. 2007, 45 (1): 47-63. 10.1111/j.1439-0469.2006.00389.x.View ArticleGoogle Scholar
- Kelemen L, Moritz C: Comparative phylogeography of a sibling pair of rainforest Drosophila species (Drosophila serrata and D. birchii). Evolution. 1999, 53: 1306-1311. 10.2307/2640835.View ArticleGoogle Scholar
- Schiffer M, McEvey SF: Drosophila bunnanda – a new species from northern Australia with notes on the other Australian members of the montium subgroup (Diptera: Drosophilidae). Zootaxa. 2006, 1333: 1-23.Google Scholar
- Bouck A, Vision T: The molecular ecologist's guide to expressed sequence tags. Molecular Ecology. 2007, 16: 907-924. 10.1111/j.1365-294X.2006.03195.x.View ArticlePubMedGoogle Scholar
- Oleksiak MF, Churchill GA, Crawford DL: Variation in gene expression within and among natural populations. Nature Genetics. 2002, 32 (2): 261-266. 10.1038/ng983.View ArticlePubMedGoogle Scholar
- Dunn CW, Hejnol A, Matus DQ, Pang K, Browne WE, Smith SA, Seaver E, Rouse GW, Obst M, Edgecombe GD: Broad phylogenomic sampling improves resolution of the Animal Tree of Life. Nature. 2008, 452: 745-749. 10.1038/nature06614.View ArticlePubMedGoogle Scholar
- Smith JJ, Kump DK, Walker JA, Parichy DM, Voss SR: A comprehensive expressed sequence tag linkage map for tiger salamander and Mexican axolotl: enabling gene mapping and comparative genomics in Ambystoma. Genetics. 2005, 171 (3): 1161-1171. 10.1534/genetics.105.046433.PubMed CentralView ArticlePubMedGoogle Scholar
- Ellis JR, Burke JM: EST-SSRs as a resource for population genetic analyses. Heredity. 2007, 99 (2): 125-132. 10.1038/sj.hdy.6801001.View ArticlePubMedGoogle Scholar
- Papanicolaou A, Joron M, McMillan WO, Blaxter ML, Jiggins CD: Genomic tools and cDNA derived markers for butterflies. Molecular Ecology. 2005, 14 (19): 2883-2897. 10.1111/j.1365-294X.2005.02609.x.View ArticlePubMedGoogle Scholar
- Staden R: A new computer method for the storage and manipulation of DNA gel reading data. Nucleic Acids Research. 1980, 8 (16): 3673-3694. 10.1093/nar/8.16.3673.PubMed CentralView ArticlePubMedGoogle Scholar
- Altschul SF, Madden TL, Schaffer AA, Zhang JH, Zhang Z, Miller W, Lipman DJ: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research. 1997, 25 (17): 3389-3402. 10.1093/nar/25.17.3389.PubMed CentralView ArticlePubMedGoogle Scholar
- Howard RW, Blomquist GJ: Ecological, behavioral and biochemical aspects of insect hydrocarbons. Annu Rev Entomol. 2005, 50: 371-393. 10.1146/annurev.ento.50.071803.130359.View ArticlePubMedGoogle Scholar
- Bownes M: The regulation of the yolk protein genes, a family of sex differentiation genes in Drosophila melanogaster. BioEssays. 1994, 16 (10): 745-752. 10.1002/bies.950161009.View ArticlePubMedGoogle Scholar
- Chertemps T, Duportets L, Labeur C, Ueda R, Takahashi K, Saigo K, Wicker-Thomas C: A female-biased exrpessed elongase involved in long-chain hydrocarbon biosynthesis and courtship behavior in Drosophila melanogaster. Proceedings of the National Academies of Science (USA). 2007, 104: 4273-4278. 10.1073/pnas.0608142104.View ArticleGoogle Scholar
- Chertemps T, Duportets L, Labeur C, Ueyama M, Wicker-Thomas C: A female-specific desaturase gene responsible for diene hydrocarbon biosynthesis and courtship behaviour in Drosophila melanogaster. Insect Molecular Biology. 2006, 15 (4): 465-473. 10.1111/j.1365-2583.2006.00658.x.View ArticlePubMedGoogle Scholar
- Dallerac R, Labeur C, Jallon JM, Knipple DC, Roelofs WL, Wicker-Thomas C: A delta 9 desaturase gene with a different substrate specificity is responsible for the cuticular diene hydrocarbon polymorphism in Drosophila melanogaster. Proc Natl Acad Sci U S A. 2000, 97 (17): 9449-9454. 10.1073/pnas.150243997.PubMed CentralView ArticlePubMedGoogle Scholar
- Fiumera AC, Dumont BL, Clark AG: Association between sperm competition and natural variation in male reproductive genes on the third chromosome of Drosophila melanogaster. Genetics. 2007, 176 (2): 1245-1260. 10.1534/genetics.106.064915.PubMed CentralView ArticlePubMedGoogle Scholar
- Lung O, Wolfner MF: Identification and characterization of the major Drosophila melanogaster mating plug protein. Insect Biochem Mol Biol. 2001, 31 (6-7): 543-551. 10.1016/S0965-1748(00)00154-5.View ArticlePubMedGoogle Scholar
- Chen B, Walser JC, Rodgers TH, Sobota RS, Burke MR, Rose MR, Feder ME: Abundant, diverse and consequential P elements segregate in promoters of small heat-shock genes in Drosophila populations. Journal of Evolutionary Biology. 2007, 20 (5): 2056-2066. 10.1111/j.1420-9101.2007.01348.x.View ArticlePubMedGoogle Scholar
- Ekengren S, Hultmark D: A family of Turandot-related genes in the humoral stress response of Drosophila. Biochemic Biophys Res Commun. 2001, 284 (4): 998-1003. 10.1006/bbrc.2001.5067.View ArticleGoogle Scholar
- Leemans R, Egger B, Loop T, Kammermeier L, He HQ, Hartmann B, Certa U, Hirth F, H. R: Quantitative transcript imaging in normal and heat-shocked Drosophila embryos by using high-density oligonucleotide arrays. Proceedings of the National Academies of Science (USA). 2000, 97 (22): 12138-12143. 10.1073/pnas.210066997.View ArticleGoogle Scholar
- Morgan TJ, Mackay TFC: Quantitative trait loci for thermotolerance phenotypes in Drosophila melanogaster. Heredity. 2006, 96: 232-242. 10.1038/sj.hdy.6800786.View ArticlePubMedGoogle Scholar
- Sezgin E, Duvernell DD, Matzkin L, Duan YH, Zhu CT, Verrelli BC, Eanes WF: Single-locus latitudinal clines and their relationship to temperate adaptation in metabolic genes and derived alleles in Drosophila melanogaster. Genetics. 2004, 168 (2): 923-931. 10.1534/genetics.104.027649.PubMed CentralView ArticlePubMedGoogle Scholar
- Sørensen JG, Nielsen MM, Kruhøffer M, Justesen J, Loeschcke V: Full genome gene expression analysis of the heat stress response in Drosophila melanogaster. Cell Stress Chaperones. 2005, 10 (4): 312-328. 10.1379/CSC-128R1.1.PubMed CentralView ArticlePubMedGoogle Scholar
- Umina PA, Weeks AR, Kearney MR, McKechnie SW, Hoffmann AA: A rapid shift in a classic clinal pattern in Drosophila reflecting climate change. Science. 2005, 308: 691-693. 10.1126/science.1109523.View ArticlePubMedGoogle Scholar
- Drosopoulou E, Scouras ZG: The organization of the alpha-tubulin gene family in the Drosophila montium subgroup of the melanogaster species group. Genome. 1998, 41 (4): 504-509. 10.1139/gen-41-4-504.View ArticlePubMedGoogle Scholar
- Spaethe J, Briscoe AD: Early duplication and functional diversification of the opsin gene family in insects. Molecular Biology and Evolution. 2004, 21 (8): 1583-1594. 10.1093/molbev/msh162.View ArticlePubMedGoogle Scholar
- The Gene Ontology Consortium: Gene Ontology: Tool for the unification of biology. Nature Genetics. 2000, 25: 25-29. 10.1038/75556.PubMed CentralView ArticleGoogle Scholar
- Adams MD, Celniker S, Holt RA, Evans CA, Gocayne JD: The genome sequence of Drosophila melanogaster. Science. 2000, 287 (24 March): 2185-2195. 10.1126/science.287.5461.2185.View ArticlePubMedGoogle Scholar
- Lin MF, Carlson JW, Crosby MA, Matthews BB, Yu C, Park S, Wan KH, Schroeder AJ, Gramates LS, St Pierre S: Revisiting the protein-coding gene catalog of Drosophila melanogaster using 12 fly genomes. Genome Research. 2007, 17: 1823-1836. 10.1101/gr.6679507.PubMed CentralView ArticlePubMedGoogle Scholar
- Kofler R, Schlötterer C, Lelley T: SciRoKo: a new tool for whole genome microsatellite search and investigation. Bioinformatics. 2007, 23 (13): 1683-1685. 10.1093/bioinformatics/btm157.View ArticlePubMedGoogle Scholar
- Long AD, Beldade P, Macdonald SJ: Estimation of population heterozygosity and library construction-induced mutation rate from expressed sequence tag collections. Genetics. 2007, 176: 711-714. 10.1534/genetics.106.063610.PubMed CentralView ArticlePubMedGoogle Scholar
- Beldade P, Rudd S, Gruber JD, Long AD: A wing expressed sequence tag resource for Bicyclus anynana butterflies, an evo-devo model. BMC Genomics. 2006, 7: 130-10.1186/1471-2164-7-130.PubMed CentralView ArticlePubMedGoogle Scholar
- Mavragani-Tsipidou P, Kyripides N, Scouras ZG: Evolutionary implications of duplications and Balbiani rings in Drosophila: a study of Drosophila serrata. Genome. 1990, 33: 478-485.View ArticlePubMedGoogle Scholar
- Legendre A, Miao X-X, Da Lage J-L, Wicker-Thomas C: Evolution of a desaturase involved in female pheromonal cuticular hydrocarbon biosynthesis and courtship behavior in Drosophila. Insect Biochemistry and Molecular Biology. 2008, 38: 244-255. 10.1016/j.ibmb.2007.11.005.View ArticlePubMedGoogle Scholar
- Fiumera AC, Dumont BL, Clark AG: Natural variation in male-induced 'cost-of-mating' and allele-specific association with male reproductive genes in Drosophila melanogaster. Philosophical Transactions of the Royal Society B. 2006, 361: 355-361. 10.1098/rstb.2005.1791.View ArticleGoogle Scholar
- Mueller JL, Linklater JR, Ram KR, Chapman T, Wolfner MF: Targeted gene deletion and phenotypic analysis of the Drosophila melanogaster seminal fluid protease inhibitor Acp62F. Genetics. 2008, 178 (3): 1605-1614. 10.1534/genetics.107.083766.PubMed CentralView ArticlePubMedGoogle Scholar
- Hoffmann AA, Willi Y: Detecting genetic responses to environmental change. Nature Reviews Genetics. 2008, 9 (6): 421-432. 10.1038/nrg2339.View ArticlePubMedGoogle Scholar
- Rako L, Blacket MJ, McKechnie SW, Hoffmann AA: Candidate genes and thermal phenotypes: identifying ecologically important genetic variation for thermotolerance in the Australian Drosophila melanogaster cline. Molecular Ecology. 2007, 16 (14): 2948-2957. 10.1111/j.1365-294X.2007.03332.x.View ArticlePubMedGoogle Scholar
- Kellermann VM, Hoffmann AA, Sgrò CM: Hsp90 inhibition and the expression of phenotypic variability in the rainforest species Drosophila birchii. Biological Journal of the Linnean Society. 2008, 92: 457-465. 10.1111/j.1095-8312.2007.00875.x.View ArticleGoogle Scholar
- Howard RW, Jackson LL, Banse H, Blows MW: Cuticular hydrocarbons of Drosophila birchii and D. serrata : Identification and role in mate choice in D. serrata. Journal of Chemical Ecology. 2003, 29 (4): 961-976. 10.1023/A:1022992002239.View ArticlePubMedGoogle Scholar
- Turner TL, Levine MT, Eckert ML, Begun DJ: Genomic analysis of adaptive differentiation in Drosophila melanogaster. Genetics. 2008, 179 (1): 455-473. 10.1534/genetics.107.083659.PubMed CentralView ArticlePubMedGoogle Scholar
- Modrek B, Resch A, Grasso C, Lee C: Genome-wide detection of alternative splicing in expressed sequences of human genes. Nucleic Acids Research. 2001, 29 (13): 2850-2859. 10.1093/nar/29.13.2850.PubMed CentralView ArticlePubMedGoogle Scholar
- Li S, Chou HH: Lucy 2: an interactive DNA sequence quality trimming and vector removal tool. Bioinformatics. 2004, 20 (16): 2865-2866. 10.1093/bioinformatics/bth302.View ArticlePubMedGoogle Scholar
- Henikoff S, Henikoff JG: Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci U S A. 1992, 89 (22): 10915-10919. 10.1073/pnas.89.22.10915.PubMed CentralView ArticlePubMedGoogle Scholar
- Karlin S, Altschul SF: Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes. Proc Natl Acad Scie U S A. 1990, 87 (6): 2264-2268. 10.1073/pnas.87.6.2264.View ArticleGoogle Scholar
- Wootton JC, Federhen S: Statistics of local complexity in amino acid sequences and sequence databases. Computers & Chemistry. 1993, 17 (2): 149-163. 10.1016/0097-8485(93)85006-X.View ArticleGoogle Scholar
- Conesa A, Gotz S, Garcia-Gomez JM, Terol J, Robles M: Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005, 21 (18): 3674-3676. 10.1093/bioinformatics/bti610.View ArticlePubMedGoogle Scholar
- Slater GS, Birney E: Automated generation of heuristics for biological sequence comparison. BMC Bioinformatics. 2005, 6: 31-10.1186/1471-2105-6-31.PubMed CentralView ArticlePubMedGoogle Scholar
- Fitzpatrick MJ: Pleiotropy and the genomic location of sexually selected genes. American Naturalist. 2004, 163 (6): 800-808. 10.1086/386297.View ArticlePubMedGoogle Scholar
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