Abstract
Many phytophagous insect species are ecologic specialists that have adapted to utilize a single host plant. Drosophila sechellia is a specialist that utilizes the ripe fruit of Morinda citrifolia, which is toxic to its sibling species, D. simulans. Here we apply multiplexed shotgun genotyping and QTL analysis to examine the genetic basis of resistance to M. citrifolia fruit toxin in interspecific hybrids. We find that at least four dominant and four recessive loci interact additively to confer resistance to the M. citrifolia fruit toxin. These QTL include a dominant locus of large effect on the third chromosome (QTL-IIIsima) that was not detected in previous analyses. The small-effect loci that we identify overlap with regions that were identified in selection experiments with D. simulans on octanoic acid and in QTL analyses of adult resistance to octanoic acid. Our high-resolution analysis sheds new light upon the complexity of M. citrifolia resistance, and suggests that partial resistance to lower levels of M. citrifolia toxin could be passed through introgression from D. sechellia to D. simulans in nature. The identification of a locus of major effect, QTL-IIIsima, is an important step towards identifying the molecular basis of host plant specialization by D. sechellia.
Introduction
How genetic architecture may contribute to the emergence of ecological specialization remains an open question (Forister et al. 2012). Genetic mapping methods between recently diverged species have made it possible to assess the relative contributions of dominance, epistasis, complexity and effect size upon the emergence of adaptive traits. The fruit fly, Drosophila sechellia provides a clear example of adaptive specialization within the Drosophila simulans clade, which includes D. simulans, D. sechellia and D. mauritiana. The three species emerged on islands in the Indian Ocean. D. simulans probably evolved on Madagascar, but D. sechellia and D. mauritiana are endemic to the Seychelles and Mascarene Islands, respectively (Lachaise et al. 1986). Molecular analysis suggests that D. simulans, D. mauritiana and D. sechellia diverged simultaneously about 242,000 years ago, although subsequent admixture has occurred since speciation (Kliman et al. 2000; Garrigan et al. 2012). While both D. simulans and D. mauritiana exploit a wide variety of fruit, D. sechellia is a specialist, and wild D. sechellia are found, most frequently, on the fruit of Morinda citrifolia (Tsacas and Bachli, 1986; Louis and David, 1986; Matute and Ayroles, 2014), which is toxic to other species of Drosophila when it is ripe (Louis and David 1986; R’Kha et al. 1991; Legal et al. 1994). Adult D. sechellia are attracted to ripe M. citrifolia, and oviposition behavior is stimulated by M. citrifolia fruit volatiles (R’Kha et al. 1991; Legal et al. 1992; Higa and Fuyama. 1993; Legal et al. 1999). Neither unripe nor fermenting M. citrifolia fruit is toxic to D. simulans or D. melanogaster (Legal et al. 1992; Farine et al. 1996; Legal et al. 1994). Gas chromatography-mass spectrometry analysis of ripe M. citrifolia fruit revealed an abundance of the compound, octanoic acid, a linear 8-chain fatty acid that was prevalent in ripe, but not unripe or fermenting fruit (Legal et al. 1994; Farine et al. 1996; Legal et al. 1999). Octanoic acid is toxic to D. simulans, D. mauritiana and D. melanogaster at all stages of development (R’Kha et al. 1991; Legal et al. 1992; Jones 1998; 2001).
The genetic basis for octanoic acid resistance varies with developmental stage. Using 15 genetic markers, Jones (1998) found that resistance in adults is mostly dominant, and is conveyed by a region on 3R, two regions on the X and additional factors on the second chromosome that could not be localized. To identify larval resistance genes, Jones (2001) used eleven genetic markers and found a dominant major effect locus on the right arm of the third chromosome, with smaller effect loci on 2L and 2R, as well as sex-specific epistatic interactions. A scan for recessive loci revealed a single locus of large effect on 3R and a small-effect interaction between 2L and 2R. Although these analyses have established that octanoic acid resistance in D. sechellia is a trait of moderate complexity, the low resolution of these analyses makes it difficult to guess the number or location of loci that are involved. It is therefore not possible to compare the recessive and dominant factors, or adult and juvenile resistance loci with confidence. In addition, mapping at lower resolution increases the likelihood of finding ‘ghost QTLs’; QTL peaks created between two true loci when intervening markers are not available to resolve them (Broman and Speed, 1999). With the emergence of low cost next generation sequencing, it has become possible to assign ancestry at each polymorphic site that exists between two genomes. DNA barcoding methods make high-density genotyping cost effective by multiplexing many individual genomes into a single sequencing library (Baird et al. 2008; Andolfatto et al. 2011). In order to create a high resolution picture of the genetic architecture of M. citrifolia resistance in D. sechellia, we have used multiplexed shotgun genotyping (MSG), to genotype M. citrifolia resistant and sensitive larvae at hundreds of thousands of markers. Here we show that the genetic basis for larval resistance in D. sechellia, from the second larval instar (L2) to puparium formation, is conferred through a single dominant locus of large effect in combination with smaller-effect dominant and recessive loci.
Materials and Methods
Larval Resistance Assays
To generate synchronized larvae, we transferred individual late first instar (L1) larvae from timed egg lays to separate media dishes. After 2 hours, L2 larvae were identified and then moved to M. citrifolia, the octanoic acid test medium, or to regular fly food. The midpoint of the 2-hour interval is taken as the time of L1-L2 molt. Molting larvae were identified by the presence of double mouth hooks, posterior to anterior peristalsis movements or ecdysis.
To generate the octanoic acid test medium, octanoic acid from Sigma, (St. Louis, MO) was diluted in water and mixed with 0.25 g nutritional yeast and 2.0g of Carolina instant Drosophila food, formula 4-24 (Burlington, NC), and used within one hour. For the octanoic acid dose-response tests, larvae were staged at the L1 to L2 molt, and moved to octanoic acid medium three hours after the onset of the second instar to avoid handling during the L2 molt. The number of pupae was recorded after three days. Larvae were tested in groups of 30.
M. citrifolia was grown in Hawaii, and shipped frozen overnight to New York (a generous gift of Scot Nelson, University of Hawaii). We find that each fruit from this source always produces 100% lethality in D. simulans. For the M. citrifolia resistance assays used to phenotype larvae for QTL mapping, L2 larvae were individually selected from 6-12 hour collections and transferred to thawed M. citrifolia fruit that had been frozen at the ‘transluscent gray’ stage while still firm (Chan-Blanco et al. 2006). Frozen fruits were thawed overnight at room temperature and used within 24 hours. The larvae on M. citrifolia were monitored for the next 6 hours. Those larvae that stopped moving, (but were not undergoing peristalsis movements of a molt) were considered M. citrifolia sensitive. Those that survived to form puparia were considered resistant.
Genotyping
We generated recombinant mapping populations by crossing female D. simulansNueva to male D. sechelliaw30, since the reciprocal cross does not produce offspring in our experience. The virgin F1 hybrid females were backcrossed to either parental stock.
For multiplexed shotgun genotyping, DNA was extracted from individual flies using a modified version of the Purgene protocol (supporting information). Custom barcode adapters (supporting information) were ligated onto genomic DNA, and libraries of 384 barcoded individual genomes were processed according to Andolfatto et al. (2011). For our D. simulans backcross, we combined barcoded genomic DNA from 384 individual sensitive larvae into a lane of an Illumina HiSeq (SRS645327), and 384 resistant larvae into another lane of an Illumina HiSeq (SRS645328). For the D. sechelliaw30 backcross, we combined barcoded DNA from 186 resistant larvae with 192 sensitive larvae into a separate lane (SRS645326). The reads of all our libraries were mapped to a recent D. simulans genome assembly (Hu et al. 2012) that was updated with the parental strains, D. simulansNueva(SRS643607) and D. sechelliaw30 (ID: 2867884) with the UpdateParental function of the MSG package (Github:JaneliaSciComp/msg). The reference genome (Hu et al. 2012) uses the D. melanogaster genome release r5.33 as a reference guide, and we use these D. melanogaster coordinates throughout the manuscript. The MSG package was installed on Galaxy Cloudman on the Amazon Elastic Compute Cloud. Configuration files, msg.cfg and update.cfg with selected parameters are available as supporting information.
We used indel locations reported in Erezyilmaz and Stern (2013) to identify species-specific insertions and deletions (supporting information). The primers 3R22.36f: 5’ CAGTACACAATGGTGGGCAT 3’, and 3R22.36r: 5’TTTGGTCCAAAAGGAAGCTGA 3’ straddle a region of a D. simulans - D. sechellia alignment that contains a 20bp deletion in D. simulans. The PCR-amplified products were visualized on a gel made with 2.5% Lonza MetaPhor agarose (Basel, Switzerland).
Post MSG processing
The perl script, pull_thin.pl created by David Stern (Janelia Farm and HHMI; supporting information) was used to prune our genotype files to relevant locations that straddle recombination events. The D. sechelliaw30 backcross data set was thinned from 406,475 markers to 8,206 markers. The D. simulans backcross dataset was thinned from 298,768 markers to 7,483 markers.
Qtl Mapping
We treated M. citrifolia resistance as a binary trait and scored survivorship to puparium formation. We used the detectable and powercalc functions of the R package, R/QTL Design (Sen et al. 2007) to determine the power of our QTL experiments to detect given effect sizes. We used the scanone function in R/qtl (Broman et al. 2003) to scan for QTL, and plotted the results in R. To assess the statistical significance of our LOD scores in the one-dimensional analyses, we performed permutation analysis with 1000 replicates. For two-dimensional scans, we used reduced datasets that contained 190 markers for the D. sechelliaw30 backcross, and 125 markers for the D. simulans backcross. We analyzed the reduced datasets using the scantwo function in R/qtl and in the R/qtl interface, J/qtl (Jackson Labs, Maine). The statistical significance of our two-dimensional scans was assessed using 500 permutation replicates. The fit of models were tested using the fitqtl function of R/qtl (Broman et al. 2003).
Fly Strains
The QTL experiments were performed with a white eyed mutant of the srain, D. simulansNueva (San Diego Stock Center # = 14021-0251.006) and D. sechelliaw30 (14021-0248.30). The mutant strains, D. simulanscutsy,ro,ca (San Diego Stock Center # = 14021-0251.116), and D. simulansjv,st,e,p (San Diego Stock Center # = 14021-0251.174) were used in marker association experiments. We used an inbred line of D. sechellia (San Diego Stock Center # = 14021-0248.13), D. sechelliaD1Alc for the marker association experiments with D. simulanscutsy,ro,ca.
Results
Resistance during the late larval stages and puparium formation
Ripening in M. citrifolia occurs as hard green fruit turns pale yellow, softens, and becomes a translucent gray color as the fruit ripens (Chan-Blanco et al. 2006). After hatching, Drosophila progress through three larval stages (L1-L3). The onset of metamorphosis occurs as the third instar larva becomes immobile and forms a puparium. We used fruits at the ‘translucent gray’ stage, and devised a high-throughput method for selecting juvenile Drosophila for resistance. Staged L2 larvae are transferred from fly food to M. citrifolia fruit, and allowed to feed and form puparia. Under these conditions, 73% of D. sechelliaw30 larvae (N= 180), but no D. simulansNueva larvae (N=240), survived to form puparia (Figure 1).
To compare the efficacy of our M. citrifolia fruit assay to the effects of pure octanoic acid, we examined the dose-response relationship between octanoic acid concentrations in food for the stages from L2 to pupariation. D. sechelliaw30 had a ~ 3-fold greater resistance to octanoic acid than D. simulansNueva (Figure 2; D. sechelliaw30 LD50 = ~0.6% for, D. simulansNueva LD50 = ~0.22% octanoic acid). The level of toxicity at which 73% of D. sechelliaw30 larvae died, roughly corresponds to 0.46% octanoic acid.
Most L2 larvae did not die upon contact with octanoic acid. Lethality, instead, occurred at a range of times after contact. We tested, next, the possibility that toxicity in D. simulans larvae is due to octanoic acid during specific developmental intervals. We exposed D. simulansNueva staged L2 larvae to an intermediate dose 0.2 % of octanoic acid for 6 hour periods, then returned larvae to octanoic acid-free medium and measured survivorship to the pupal stage (Figure 3). We found that the survivorship of D. simulansNueva larvae during the intermolt period (hours 6-24) was comparable to the survivorship of control larvae that were similarly handled, but not exposed to octanoic acid (Figure 3). In contrast, all D. simulansNueva larvae that were exposed to octanoic acid during either the L1 to L2 molt (N = 90), or the L2 to L3 molt (N = 90), did not survive to form puparia (Figure 3). These data show that, at the concentration that we describe here, octanoic acid toxicity during the second larval instar occurs at molts.
QTL Analysis
D. sechellia and D. simulans produce fertile f emale offspring when crossed (Lachaise et al. 1986). Previous work has shown that resistance to M. citrifolia toxin by D. sechellia adults is mostly dominant in F1 hybrid D. simulans/D. sechellia larvae, but that resistance to M. citrifolia toxin and octanoic acid in developing embryos involves both dominant and recessive factors, as well as a maternal contribution (R’Kha et al. 1991; Jones, 2001). We asked whether resistance is dominant or recessive in our assay. The overall survivorship of F1 D. sechelliaw30/ D. simulansNueva hybrids to M. citrifolia toxin is intermediate between the survivorship of the two parents, which suggests that resistance in D. sechellia is comprised of both dominant and recessive factors (Figure 1). To map these loci at high resolution, we screened L2 larvae from backcrosses to either parent in our M. citrifolia assays, and genotyped individual larvae using multiplexed shotgun genotyping (Andolfatto et al. 2011).
We first examined the contribution of recessive loci to M. citrifolia resistance in 359 individuals from an F1 backcross to D. sechelliaw30. We find that the map of recessive loci for M. citrifolia resistance is dominated by QTL on the third chromosome; all regions of the third chromosome are significant at the 99% level (Figure 4). The highest peak is on the left arm of chromosome III at ~15,860,000 (LOD=20.2). Inclusion of a neighboring peak at ~3:18,900,000 did not increase the likelihood of our model significantly (Table 1). We therefore treat this region as one locus, QTL-IIIseca. A second large effect locus appears on the right arm at ~3:40,070,000 with LOD =17.0 (QTL-IIIsecb, Figure 4). In addition, 2 QTL scans indicate that a resistance locus exists on chromosome III at ~45,180,000 (QTL-IIIsecc, LOD = 10.9; Figure 4, S1), and inclusion of this region improves the fit or our model (Table 1). We also found a significant contribution from the X chromosome; the left half is significant at the 95% confidence level, and a peak lies at ~X:10,680,000 (QTL-Xsec, LOD = 6.5). Recessive loci on the second and the fourth chromosomes did not contribute significantly to resistance. The best-fit model contains QTL-IIIseca, QTL-IIIsecb, QTL-IIIsecC and QTL-Xsec interacting additively (Table 1). We did not detect significant epistasis between loci in our two-QTL scans (Figure SI).
Given the genetic and environmental variances of our lines, and the number of backcross individuals tested, our D. sechelliaw30 backcross QTL experiment is designed to detect effect sizes of 0.19 and 0.175 with 90, and 80 per cent power, respectively. The effect sizes of QTL-IIIseca, QTL-IIIsecb, QTL-IIIsecc and QTL-Xsec exceed the threshold for detection with 90% power (Figure S2).
We next examined the effect of dominant loci in D. sechellia’s resistance to M. citrifolia toxin in progeny of F1 backcrosses to D. simulansNueva. QTL analysis showed that resistance to M. citrifolia is dominated by a QTL of large effect on the right arm of chromosome III at ~ 46,954,562 bp (QTL-IIIasim; LOD = 33.8; Figure 5). Larvae with one copy of the D. sechelliaw30 allele at QTL-IIIsima were more than twice as likely to survive to pupariate (Figure 5B; Figure S2). We also detected two significant peaks on the left arm of chromosome 3 at ~ 4,898,627 bp (LOD=4.42) and at 9,012,208 bp (LOD = 4.48), although a model including both markers did not significantly increase the likelihood score over a model that includes just one of the two 3L markers. We therefore treat these terms as a single locus, QTL-IIIsimb. In addition, a broad region of significance on the right arm of chromosome II has a peak at ~43,480,964 bp (QTL-IIsim, LOD = 5.8) and spans several megabases. Finally, we found a broad region on the X chromosome between ~X:10,000,000 and ~X: 18,200,000 that has a peak at ~X: 14,358,268 bp (QTL-Xsim, LOD= 6.1). We did not detect significant epistasis between QTLs in two-dimensional, two QTL scans (Figure S1). Instead, we find that a model that fits our data best consists of QTL-IIIasim, QTL-IIIbsim, QTL-IIsim and QTL-Xsim interacting additively (Table 1). Inclusion of additional QTL did not improve the fit of our model significantly (Table 1).
Based upon the sample size, environmental and genetic variances of our cross, a QTL with effect size of 0.12, where 0 is sensitive and 1 is resistant, would be detectable with 80% power, and a QTL with effect size of 0.134 would be detected with 90% power in our D. simulansNueva backcross. The effect sizes of the four QTL that we report exceed the 90% power threshold (Figure S2).
Tests of QTL-IIIsima and the effect of the X chromosome
The location of our largest-effect QTL in the D. simulans Nueva backcross differs from the large effect locus described by Jones for octanoic acid sensitivity in larvae (2001) and in adults (1998). We therefore performed additional checks of our approach. First, we compared the genotype of a sample of our MSG-genotyped flies at ~3:46,689,564 with an indel marker at 3:46,617,828 using PCR. The PCR-indel genotypes of all 179 genotyped individuals matched the genotypes produced by MSG (data not shown). To confirm the existence of QTL-IIIsima, we next crossed a D. simulans strain, marked by the cutsy mutation and by claret (ca) at ~3:50,000,000, (Kimble and Church, 1983) to D. sechelliaD1A1C, and backcrossed F1 females to the marked D. simulanscutsy,ca parental strain. The genetic map position of cutsy is 3-74 in D. simulans (Coyne, 1997) which is, roughly, ~3:42,000,000 (D. melanogaster genome location). We compared the frequency of each recessive marker in 242 F1 backcross progeny that were viable in M. citrifolia from L2 to adulthood with the frequency of each marker in 872 larvae that were not exposed to M. citrifolia fruit. We found that cutsy+ (∑2 = 20.6, p = 5.8 × 10−6), was most strongly associated with M. citrifolia resistance, followed by ca+ (∑2 =6.2, p = 0.01). We next used the molecular markers at 3:46,617,828 to test for linkage to an additional 89 resistant and 91 sensitive D. simulans backcross progeny. We found strong linkage to this region (p = 4 × 10-5, Fisher’s Exact Test; ∑2 = 27, p = 2.06 × 10−7, Chi-squared test, Table 2).
These data confirm that QTL-IIIsima, is located near ~3:47,000,000, and suggest that QTL-IIIsima may be closer to ~3:42,300,000 than to ~3:50,000,000 (Table 2). Finally, we asked if M. citrifolia resistance in our assay is linked to ebony (e), since Jones et al (2001) found that a QTL linked to e confers resistance to octanoic acid in a larval assay. The genomes of the D. simulans clade share a large inversion on 3R with respect to D. melanogaster that contains e (Ashburner, 1989). In our QTL map, which uses the D. melanogaster genome as a scaffold, the e gene is located at ~3:41,620,000, but in D. simulans, e is located at ~3:28,656,573. Like Jones (2001), we also find that M. citrifolia resistance is linked to e in our assay, although the linkage is weaker than the linkage between resistance and cutsy, ca or 3:46,617,828 ( Table 3; ∑2 = 5.08, p = 0.02).
Our analysis of both the D. simulans backcross and the D. sechelliaw30 backcross revealed resistance loci on the X chromosome, which contradicts previous work (Jones, 2001). If the X chromosome does confer resistance in our assay, larvae with one X chromosome from D. sechelliaw30 should have greater resistance than larvae with only a D. simulans chromosome. As an additional test of our QTL model, we asked if female F1 larvae had greater survivorship than male F1 larvae from the cross, ♀ D. simulansNueva × ♂ D. sechelliaw30, since males would only have a single X chromosome from D. simulansNueva mother. In this case we find that more F1 females than F1 males (p = 9.36 × 10−7, Fisher’s Exact Test, N = 141 larvae in M. citrifolia vs N = 371 control larvae). This result indicates that the X chromosome from D. sechellia has a significant effect upon resistance to M. citrifolia toxin.
Discussion
We have addressed the genetic basis for evolved resistance to M. citrifolia fruit toxin in D. sechellia. We find that resistance to the toxic fruit during the period from the second instar to puparium formation is composed of both dominant and recessive effects. Multiple significant recessive loci were detected on the third chromosome (QTL-IIIseca-c), as well as a region on the X chromosome (QTL-Xsim). A scan for dominant loci identified a large effect locus at ~3: 46,954,562 bp (QTL-IILsima) and three regions of smaller effect that are located on the X (QTL-Xsim), on 2R(QTL-IIsim), and on 3L (QTL-IILsimb). QTL-IILsim a is within an interval that overlaps with QTL-IIIsecC, which may indicate that the two QTL are the same locus that acts additively. We found no evidence for significant epistasis between any QTLs. Additional checks of our locus of largest effect, QTL-IIIsima using visible and molecular markers confirms that the locus that confers resistance to D. sechelliaw30 is between ~3:42,000,000 and ~3:47,000,000, but closer to ~3:47,000,000.
Although the set of loci that we detected overlap with the regions identified by Jones (2001), the two sets are not identical. Both analyses indicate a major effect locus on 3R, (Figure 5, Table 1), but Jones (2001) finds that the major effect locus is near e, and a region near QTL-IIIsima was not significant. Another major difference between our QTL map and that of Jones (2001) is the effect of the X chromosome. We found significant QTL peaks on the X chromosome in both the D. simulans and D. sechelliaw30 backcrosses, while Jones (2001) did not detect any effects on the X chromosome. In addition, Jones found that a region on the left arm of chromosome II accounted for 11-12% of the phenotypic variation in the D. simulans backcross (Jones, 2001), but we did not detect significant QTL on 2L in either backcross (Figure 4, 5). Finally, Jones (2001) detects epistasis between 2L and 2R in the D. sechellia backcross and between 2R and 3R in the D. simulans backcross whereas we did not detect significant epistasis between loci.
Several factors may account for the discrepancies between our QTL map and the previous analysis by Jones (2001). Firstly, we used fresh-frozen M. citrifolia for our assays, while Jones used purified octanoic acid in fly food. Although previous work (Legal et al, 1994) has established that octanoic acid is the toxic component of M. citrifolia fruit, other components of the fruit may contribute to the toxicity or uptake of octanoic acid. Secondly, the two analyses may test different phases of development. Jones (2001) allowed females to oviposit on control or octanoic acid containing medium, then recorded the visible markers of emerging adults. D. simulans embryos are highly sensitive to M. citrifolia (R’Kha, 1991), while D. sechellia embryos are largely resistant. The lethality of octanoic acid decreases over time, presumably as the semi-volatile compound dissipates. In Jones’ assay, therefore, embryonic resistance factors would be under the greatest selection while later stages of development would experience increasingly lower effective octanoic acid concentrations. Jones (2001) also provides strong evidence for a maternally inherited resistance factor, which further complicates genetic mapping. A locus that encodes a maternally-provided factor would not appear in selection experiments if the offspring have resistant mothers. Therefore, any differences between the set of larval resistance factors described here and those described by Jones (2001) could be due to maternally provided factors, selection upon different stages of resistance, or any combination of the two. Finally, we compare the genotypes of resistant larvae with those of sensitive larvae for our QTL analyses, whereas Jones compares the genotypes of resistant larvae with those of larvae that have not been exposed to octanoic acid. Interestingly, linkage to the region containing e was not significant in our QTL map, but it was significant when we used untreated backcross progeny as a control (Figure 5; Table 3).
In contrast to larval resistance, the resistance to volatile octanoic acid in adults is conferred through dominant loci on the 2nd, 3rd and X chromosomes (Jones, 1998). The resistance factor on chromosome 2 had too small of an effect to be mapped, but the loci on the X and III were further resolved with visible markers (Jones, 1998). A region on the right arm of chromosome 3 that is linked to e had the greatest effect, and recent work has fine mapped this locus to the interval bounded by ~3:26,136,000 and ~3:26,315,000 (Hungate et al. 2014). Interestingly, our D. simulans backcross QTL map for larval resistance overlaps with a locus on the X chromosome discovered by Jones (1998) for adult resistance; a region between miniature (~X:11,700,000) and forked (~X:17,130,000). We find a broad significant region from ~X:10,000,000 to ~X:18,200,000 that peaks at ~X:14,358,268.
The response of insect populations to insecticide treatment may provide insight into how resistance to M. citrifolia toxin may have evolved in D. sechellia. Exposures to insecticide concentrations that lie within the distribution of viability tend to produce resistance that is based on multiple loci, each of small effect (McKenzie et al, 1992). Such variation has been found to regulate the expression level or copy number of detoxifying enzymes, such as the cytochrome P450s and by other metabolic enzymes, such as carboxylases and esterases (McKenzie and Batterham, 1994; Ranson et al. 2002; ffrench-Constant et al. 2004). Selection outside of the viability distribution with very high levels of insecticide, on the other hand, tends to produce large-effect loci conferred by amino acid substitutions of single genes that are the targets of pesticides. These targets include ligand-gated ion channels, like the GABA receptor subunit in which an amino acid replacement confers resistance to dieldrin (ffrench-Constant et al. 1991), or a voltage gated sodium channel in which resistance to DDT is conferred by either of two amino acid replacements (Williamson et al. 1996; Miyazaki et al. 1996). The genetic architecture of resistance to M. citrifolia fruit toxin in D. sechellia that we describe here bears hallmarks of both types of selection; one large effect locus on 3R accounts for 24% of the phenotypic difference between D. simulansNueva and D. sechelliaw30, but in the best-fit model, additional smaller effect loci also confer resistance (Table 1).
Data from selection experiments suggest that complete resistance did not arise only through consolidation of existing variation in resistance alleles alone. Colson (2004) selected for increased resistance in a cosmopolitan strain of D. simulans for 20 generations. She found that resistance to octanoic acid rapidly increased by 18% before it plateaued at a fraction of the resistance seen in D. sechellia. These data show that either the variation within the cosmopolitan strain that was used is not representative of the variation within the common D. simulans - D. sechellia ancestor, or that resistance in D. sechellia arose through new mutation(s). Interestingly, two regions discovered in these selection experiments overlap substantially with QTL-IIsim at cytological location 57C and QTL-Xsim, at cytological location 13D (Colson 2004). Colocalization of our small-effect loci with the evolved resistance regions of Colson (2004) supports a scenario where the smaller-effect loci discovered in our experiments are the products of selection within the viability distribution of D. simualns for octanoic acid.
The genetic complexity of resistance to M. citrifolia fruit in D. sechellia appears to be a barrier to full introgression of this trait into D. simulans. Amlou et al (1997) tried to introgress octanoic acid resistance into D. simulans by backcrossing resistant adult hybrids to D. simulans. Despite strong directional selection, resistance decreased with each generation to D. simulans levels. Our own efforts to introgress the resistance phenotype into D. simulansNueva (phenotype-based introgression) did not progress beyond one generation of selection upon ripe M. citrifolia (data not shown). However, the lack of epistasis between the four major QTL suggests that partial resistance could easily be introgressed from D. sechellia to D. simulans. Partial resistance would improve the viability of hybrid flies on fermenting fruit, which has been shown to have lower levels of octanoic acid (Legal et al. 1994; Farine et al. 1996; Legal et al. 1999). Such introgression of partial resistance may occur routinely in the Seychelles, where D. simulans and D. sechellia co-exist. Matute and Ayroles (2014) recently showed that D. simulans and D. sechellia hybrids are prevalent in some of the islands in the Seychelles. They also found that F1 D. simulans/D.sechellia hybrids and morphologically D. simulans flies are found on M. citrifolia fruit, although the stage of fruit maturation was not reported (Matute and Ayroles, 2014).
QTL analyses typically produce confidence intervals that are too large to resolve candidate genes. In the case of QTL-IIIsima, the confidence interval created by a 1.5 LOD score drop from the peak value of QTL-IIIsima spans from ~3:45,769,000 to ~3:47,000,000, about 1.2 Mbp. This interval contains 128 protein-coding genes, only 70 of which are named. There are also numerous non-protein coding genes, which have recently been shown to regulate an evolved difference in morphology in Drosophila (Arif et al, 2013). Additional work with introgression lines or D. melanogaster deficiency strains will be needed to further resolve this interval with fine scale mapping. These experiments are currently underway in our laboratory.
Supporting Information
Figure S1. Two dimensional, two-QTL scans for the D. sechelliaw30 and D. simulansNueva backcrosses. For each graph, the top triangle shows the improvement in fit of the full model over a single QTL model (LODfv1), the bottom right triangle shows the improvement in fit of the additive model (LODav1) over the single QTL model. A) In the D. sechelliaw30 backcross, little difference is found between the LODfv1 and LODav1 models. The significant interaction between the two QTL on chromosome 3 is additive: ~3:45,009,000 × ~3:15,860,000 (LODfv1 = 10.0, LODav1 = 9.6, LODepistasis = 0.38). These locations correspond to QTL-IIIseca and QTL-IIIsecc. B) D. simulansNueva backcross. A locus at ~3:46,040,000 interacts with a locus at ~X:15,001,000 (LODfv1 = 7.1, LODav1 = 4.9, LODepistasis = 2.2). A second interaction occurs between loci at ~2:43,020,000 and ~X:15,001,000 (LODfv1 = 5.7, LODav1 = 4.8, LODepistasis = 0.9). A third interaction occurs between loci on the right arms of the second and third chromosomes, ~3:47,001,000 × ~2:43,024,000 (LODfv1 = 4.4, LODav1 = 4.4, LODepistasis = 0.001). A fourth interaction occurs between two loci on the third chromosome, ~3:9,011,000 and ~3:47,001,000 (LODfv1 = 6.1, LOD av1 = 3.4, LODepistasis = 2.7). The significance of all the LODfv1 and LODav1interactions met or exceeded the p = 0.01 threshold, but no episatic interactions were significant. The locations of the loci reported here are all within the confidence intervals of QTL-IIsim, QTL-IIIsim, QTL-IIIsimb and QTL-Xsim
Figure S2. Whole genome effect plots for (A) the D. sechelliaw30 backcross, (B) the D. simulansNueva backcross. The effect of each location on the autosomes is given in blue, and the standard errors are shaded in light blue. For the X chromosome, effect sizes are given in red, with standard errors shaded in pink. For males, the effect size of each location on the X is given in orange, and the standard errors are shaded in light orange.
Supporting Information File 1. The sequence of 384 barcoded adapters that were used to ligate FC2 linkers for Illumina sequencing (Andolfatto et al, 2011).
Supporting Information File 2. The configuration file with parameters that was used for updating the D. simulansw501 genome with D. simulansNueva and D. sechelliaw30 genome reads.
Supporting Information File 3. msg.cfg: the configuration file with the parameters that were used for msg mapping.
Acknowledgments
We thank Prof Scot Nelson, (University of Hawaii, Manoa) for his generous gifts of M. citrifolia fruit. We also thank Greg Pinero and David Stern for installation of the MSG program onto the Amazon/Galaxy Cloud. This work was supported by Stony Brook University start-up funds.