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. 2012 Dec 5;110(4):312–320. doi: 10.1038/hdy.2012.88

Genetic correlation between the pre-adult developmental period and locomotor activity rhythm in Drosophila melanogaster

K H Takahashi 1, K Teramura 2, S Muraoka 2, Y Okada 2, T Miyatake 2,*
PMCID: PMC3607109  PMID: 23211793

Abstract

Biological clocks regulate various behavioural and physiological traits; slower circadian clocks are expected to slow down the development, suggesting a potential genetic correlation between the developmental period and circadian rhythm. However, a correlation between natural genetic variations in the developmental period and circadian rhythm has only been found in Bactrocera cucurbitae. The number of genetic factors that contribute to this genetic correlation is largely unclear. In this study, to examine whether natural genetic variations in the developmental period and circadian rhythm are correlated in Drosophila melanogaster, we performed an artificial disruptive selection on the developmental periods using wild-type strains and evaluated the circadian rhythms of the selected lines. To investigate whether multiple genetic factors mediate the genetic correlation, we reanalyzed previously published genome-wide deficiency screening data based on DrosDel isogenic deficiency strains and evaluated the effect of 438 genomic deficiencies on the developmental periods. We then randomly selected 32 genomic deficiencies with significant effects on the developmental periods and tested their effects on circadian rhythms. As a result, we found a significant response to selection for longer developmental periods and their correlated effects on circadian rhythms of the selected lines. We also found that 18 genomic regions had significant effects on the developmental periods and circadian rhythms, indicating their potential for mediating the genetic correlation between the developmental period and circadian rhythm. The novel findings of our study might lead to a better understanding of how this correlation is regulated genetically in broader taxonomic groups.

Keywords: circadian rhythm, deficiency screening, disruptive selection, free-running period

Introduction

Biological clocks regulate various behavioural and physiological traits and allow organisms to accommodate to daily and seasonal environmental cycles (Panda et al., 2002; Paranjpe et al., 2004; Mazzoni et al., 2005). The core molecular mechanisms of these clocks are highly conserved across taxa, and the generation of molecular oscillation has been well studied in flies and mammals (Panda et al., 2002; Grima et al., 2004; Chiu et al., 2011; Goda et al., 2011). In general, faster circadian clocks are expected to speed up development and shorten the pre-adult developmental period, whereas slower clocks prolong this period (Paranjpe et al., 2005), suggesting a potential genetic correlation between the developmental period and circadian rhythm.

A genetic correlation between the developmental period and circadian rhythm has been demonstrated in two fly species, Drosophila melanogaster and Bactrocera cucurbitae. In D. melanogaster, period (per) mutants have a wide range of circadian rhythm variations represented by largely different free-running periods (τ) (wild type: τ=24 h, perS: τ=19 h, perL: τ=28 h) that are positively correlated with the developmental periods (perS develops faster than perL regardless of the light conditions; Kyriacou et al., 1990). The positive genetic correlation between the free-running and developmental periods might be mediated by the pleiotropic effects of per mutations. Another example in D. melanogaster is the genetic correlation between the timing of adult emergence and circadian clocks found by Kumar et al., 2007. Flies selected to emerge in the morning showed shorter circadian rhythm than the ones selected to emerge at evening, indicating the regulation of pre-adult period by a circadian clock (Kumar et al., 2007). In B. cucurbitae, Miyatake (1995) performed a disruptive selection on the developmental period and established selected lines with shorter and longer developmental periods. Under constant darkness, Shimizu et al. (1997) then observed that the selected lines with shorter developmental periods had shorter free-running periods, whereas the lines with longer developmental periods had longer free-running periods, indicating a positive genetic correlation between the developmental period and circadian rhythm in this species. In addition, the developmental and free-running periods of B. cucurbitae were also genetically correlated with the timing of mating (Miyatake et al., 2002). This genetic correlation between life-history and behavioural traits might have an important role in ecological diversifications (Miyatake, 2002). However, in a broader range of organisms it is still unknown whether natural genetic variations in the developmental period and circadian rhythm are correlated with each other. In addition, the number of quantitative trait loci other than per that contribute to genetic correlation are largely unclear.

To examine whether the correlation between natural genetic variations in the developmental period and circadian rhythm in B. cucurbitae also exists in D. melanogaster, we performed an artificial disruptive selection on the developmental periods of strains that originated from wild populations. We then evaluated the circadian rhythms represented as the free-running periods of these lines. To map the genomic regions that had effects on the developmental periods, we reanalyzed the genome-wide deficiency mapping data of Takahashi et al. (2011a) and evaluated the effect of 438 isogenic deficient strains covering about 65% of the D. melanogaster genome. We then randomly selected 32 genomic deficiencies with significant effects on the developmental periods, and tested their effects on the free-running periods. As a result, we found a significant response to the selection for longer developmental periods, and their correlated effects to prolong free-running periods in the selected lines. We also found that 253 genomic deficiencies had significant effects on the developmental periods. Of the 32 deficiencies randomly selected from the deficiencies that had effects on the developmental periods, we found 18 deficiencies that had significant effects on the free-running periods. These results clearly show that there was an ample natural genetic variation in developmental period in D. melanogaster, and it had significant correlation with the natural genetic variation in circadian rhythm. The deficiency mapping identified a number of genomic regions that affected the developmental periods and circadian rhythms, suggesting that genetic correlation between them might be mediated by multiple genetic factors.

Materials and methods

Selection experiments

Flies

We obtained 20 wild strains of D. melanogaster that had been collected from across the Japanese islands and maintained in EHIME-Fly, the laboratory for Drosophila resources at Ehime University. We used the same strains that were described in Tsujino and Takahashi (2012), and complete details of the strains can be found in that publication. We mixed four individuals (two females and two males) from each strain to produce a base population of 80 individuals. In this manner, we produced three independent base populations originated from the same set of flies that were reared for three generations at 23 °C under constant light in incubators (MIR-254 or MIR-154; SANYO, Osaka, Japan) in 250-ml plastic bottles containing 50 ml of fly medium containing dried yeast, soy flour, cornmeal, agar, malt extract and dextrose.

Artificial selection on the developmental periods

The developmental period in our study was characterized by days from oviposition of the eggs to their eclosion. We established three ‘short' lines that were selected for shorter developmental periods and three ‘long' lines that were selected for a longer developmental periods by mixing 30 females and 30 males from each base population. During each selection round, we collected all the emerged flies and calculated their developmental periods. Collections were made every 12 h to ensure the virginity of females. We ranked all the emerged females and males on the basis of their developmental periods, and established the next generation using the top 30 females and 30 males for each short line, and the bottom 30 females and 30 males for each long line. The average number of emerged adults was 283.44 throughout the selection, indicating that our current selection procedure selected on an average 21% of individuals from the top or the bottom of the trait score distribution in each generation. We mixed the selected females and males, and maintained them together for a few days to allow them to mate freely. We then transferred the flies to experimental 250-ml plastic bottles and allowed the flies to oviposit for 12 h to maintain the larval density in the plastic bottles at a sufficiently low level to avoid intense intra-specific competition. We incubated the bottles until the flies of the next generation emerged. We reared the flies in the incubators at 23 °C under constant light conditions. Three control lines were also established from the three base populations and were maintained in the same way as the selection lines except for the selection process. We measured the developmental periods of the control lines every five generations.

Locomotor activity rhythm assay of the artificially selected lines

To examine whether artificial selection on the developmental periods had an effect on the circadian rhythms, we measured the locomotor activity of the short, long and control strains at the 25th generation by evaluating the free-running periods. Flies aged 3–7 days after eclosion were entrained for 4 days in cycles of 12-h light and 12-h darkness at 25 °C in incubators. The locomotor activity of these flies was monitored using a DAM2 system (TriKinetics, Waltham, MA, USA) for 10 days in constant darkness. To characterize the rhythmicity of the locomotor activity of these flies, we performed a χ2 periodogram analysis using Clocklab software (Actimetrics, Wilmette, IL, USA) that identified rhythmic flies and determined their free-running periods (τ).

Statistical analysis

To evaluate the divergence in the developmental periods of the short and long lines, we performed a one-way analysis of variance (ANOVA) repeatedly for every generation using the developmental periods as a dependent variable, and the selection treatments (short or long) as an independent variable. We used the mean developmental period of each line in this analysis and regarded three lines of each treatment as biological replicates.

We also tested the effect of artificial selection on the free-running periods at the 25th generation using a one-way ANOVA. In this analysis, we compared the control lines with the long and short lines in a pairwise manner. We used τ scores as the dependent variables and the treatments (control/long or control/short) as independent variables.

To confirm the normality and equality of variance of the data sets used for the above analyses, we performed the Kolmogorov–Smirnov test and F test. When the data sets did not fulfil the requirements of ANOVA, we did not apply ANOVA.

Reanalysis of deficiency screening data to identify genomic regions with effects on the developmental periods

To map genomic regions with effects on the developmental periods, we reanalyzed the deficiency screening data of Takahashi et al. (2011a) in which they solely focused on temporal variation in the developmental periods and not on the mean developmental period. Takahashi et al. (2011a) used DrosDel isogenic deficiency strains and evaluated the developmental period defined as days from oviposition of the eggs to their eclosion. The breakpoints of the deletions were determined at a single base-pair resolution, allowing high-resolution mapping of the candidate genomic regions. The control strain (DSK001: w1118iso; 2iso; 3iso) was isogenized for the X, second and third chromosomes, and all the deficiency strains shared the same genetic background as the control strain (Ryder et al., 2004, 2007). In our study, we reanalyzed the developmental period data of 438 DrosDel deficiency strains that covered about 65% of the whole genome region (Appendix 1). Additional details of the deletion strains are available on the DrosDel web page (http://www.drosdel.org.uk/).

Deficiency effects on the locomotor activity rhythms

We randomly chose 32 deficiencies whose effects on the developmental periods were detected by deficiency screening and evaluated their effect on the locomotor activity rhythms. Because of the homozygous lethality of most deficiencies, we tested deficiency-control heterozygotes (Df/+) for the locomotor activity rhythms, as in Takahashi et al., 2011a. We introduced 100 eggs from each of the crosses between the control strain and the deletion strains into a glass vial along with a standard cornmeal agar medium (details are described in Takahashi et al., 2011b). We crossed females of the control strain with males of each deficiency strain to control the maternal effect. The eggs were reared at 23 °C under constant light in incubators. We genotyped emerging adults (target genotype, Df/+ nontarget genotype, balancer/+) and collected flies for locomotor activity measurements. To obtain control individuals (+/+), we collected 100 eggs from strain DSK001 and reared them as described above. We then monitored the locomotor activity of these control flies in the same way as we did for the selection experiment to determine their free-running periods (τ).

Statistical analysis

To evaluate the effects of deletions on the mean developmental periods and free-running periods, we performed pairwise comparisons between +/+ and each Df/+ using one-way ANOVA. We used average vial-level scores for the developmental periods and individual-level scores for the free-running periods. We checked the normality of the distribution of the scores for each genotype separately using the Kolmogorov–Smirnov test, and equality of variance of the data sets using F test. To correct for multiple tests with different genotypes, we applied the Benjamini and Hochberg (1995) procedure to control the false discovery rate. Deviation from the normal distribution was considered significant if the adjusted false discovery rate P-value was <0.05. As a result, no significant deviations from the normal distribution were detected in any of the cases in our study. For the ANOVA, we used the average vial-level developmental period or individual-level free-running period as the dependent variable, whereas the genotype (+/+ or Df/+) as the independent variable. Correction for multiple tests was performed using the Benjamini–Hochberg procedure, as in the normality test described above. In addition, we calculated the effect size (Cohen's d) of each deficiency to draw a robust conclusion, regardless of the sample size variation and the existence of outliers, and to make the results of different tests comparable. For the developmental periods, we performed separate analyses of sexes and tested correlation of the effect sizes of the developmental periods between males and females to determine any sex-specific effect of the deletions. We also tested the correlation between the effect sizes of deletions on the developmental and free-running periods to determine any genetic correlation. All statistical analyses were performed using the statistical software R 2.8.1 (R Development Core Team 2005).

Results

Effects of artificial selection on the developmental periods

As a result of artificial selection, the developmental periods of long and short lines diverged significantly in both females and males where there were a few cases that violated the requirements for ANOVA and were not analysed (Figure 1). The mean developmental periods of the short lines remained at the same level as the control lines throughout selection, whereas the mean developmental periods of the long lines increased continuously until the 20th generation (Figure 1).

Figure 1.

Figure 1

Selection responses of the female flies (a) and the male flies (b). Short lines (○) were selected for a shorter developmental period, long lines (Inline graphic) were selected for a longer developmental period, whereas control lines (Inline graphic) were not subjected to any selection. Error bars represent s.e's. Asterisks represent statistically significant differences between short and long lines: *P<0.05, **P<0.001, ***P<0.0001. NA indicates cases where the data sets violated the requirements of ANOVA and the test was not applied.

Locomotor activity rhythms of the selected lines

The free-running periods of the long lines (average score±s.e.: 24.25±0.09) were significantly increased (P=0.016) compared with the control lines (23.82±0.06), whereas those of the short lines (23.96±0.08) were not significantly different from the control lines.

Effects of deficiencies on the developmental periods

As a result of screening, we found 81 genomic regions with significant effects on the development periods in females only, 27 genomic regions with significant effects in males only and 145 genomic regions with significant effects in both females and males (Figure 2, Appendix 1).

Figure 2.

Figure 2

Distribution of deficiencies on the second, third and X chromosomes. Genomic regions covered by deficiencies are filled with black, while bars below each chromosome represent the location of each deficiency. Bars representing deficiencies with significant effects on the developmental periods are filled with different colours based on sex specificity, that is, a significant effect only in female flies is shown in red; a significant effect only in male flies is shown in blue; and a significant effect in both female and male flies is shown in purple. A full color version of this figure is available at the Heredity journal online.

Compared with the developmental period of +/+ (13.51 days in female and 13.45 days in male on average), developmental period of Df/+ deviated positively in both females and males (0.39 on average ranging from −1.35 to 4.89 days in females and 0.53 on average ranging from −1.45 to 4.71 days in males). The frequency distribution of the effect size of deficiencies on the developmental periods was assessed using Cohen's d for the term ‘genotype' in the ANOVA model as shown in Figure 3. The effect sizes were centred around zero, indicating that most deficiencies had little effect on the developmental periods. Longer tails of the effect size distributions on the positive side indicated that deficiencies tended to prolong the developmental periods in females and males (Figure 3). We found a positive correlation between the effect sizes in females and males (correlation coefficient: 0.863, P<0.0001; Figure 4), suggesting that a large number of deficiencies had consistent effects on the developmental periods in females and males.

Figure 3.

Figure 3

Frequency distribution of the effect size (Cohen's d) of deletions on the developmental periods in female and male flies.

Figure 4.

Figure 4

Correlation between the effects of deficiencies on the developmental periods in female and male flies.

Effects of deficiencies on the locomotor activity rhythms

Of the 32 deficiencies with effects on developmental periods, 18 deficiencies had a significant effect on the free-running periods (Figure 5). The overall correlation between the effects of deficiencies on the developmental and free-running periods was not significant (correlation coefficient: 0.093, P>0.05; Figure 6).

Figure 5.

Figure 5

Free-running periods of the control homozygotes (+/+) and deficiency heterozygotes (Df/+). Error bars represent s.e's. Asterisks represent statistically significant differences between the +/+ and each Df/+ genotype: *P<0.05, **P<0.01, ***P<0.001.

Figure 6.

Figure 6

The overall correlation between the effects of deficiencies on the developmental and free-running periods.

Discussion

In our study, we observed a significant response to artificial selection for longer developmental periods, and this selection resulted in increased free-running periods in the selected lines, indicating a genetic correlation between the developmental period and circadian rhythm in D. melanogaster. We also found that 18 genomic deficiencies affected the developmental periods and circadian rhythms, suggesting that multiple genetic factors contribute to the genetic correlation between them.

A significant response to artificial selection for longer developmental periods and lack of response to selection for shorter developmental periods were observed in our study. This pattern of response to disruptive selection on the developmental period was similar to that observed by Zwaan et al. (1995) in D. melanogaster and by Miyatake (1995) in B. cucurbitae. The asymmetric response to disruptive selection might be attributable to a scarcity of natural genetic variations that shorten the developmental period. In Drosophila species, at least, natural selection seems to favour a shorter developmental period because most endoparasitic wasps attack the larval stage or feed externally on the pupae (Wertheim et al., 2005), and a shorter developmental period might reduce the risk of such parasitism. In addition, most Drosophila species utilize patchy and ephemeral resources such as mushrooms or fallen fruits (Takahashi et al., 2005; Mitsui et al., 2006), so rapidly completing their pre-adult development before the degradation of resource patches might be advantageous. Furthermore, for a species such as D. melanogaster whose small overwintering population increases in the absence of population pressure every spring, reduction in developmental period leads to the higher intrinsic rate of increase of the population (Lewontin, 1965). This demographic fitness effects is stronger in developmental period than in other life-history traits such as fecundity and longevity (Lewontin, 1965). If these selective advantages lead to a higher selection pressure that favours a shorter developmental period, natural genetic variations for a shorter developmental period will be more deficient than those for a longer developmental period. Selective advantage of shorter developmental period is not necessarily true for other organisms such as a comma butterfly Polygonia c-album, whose seasonal variation in developmental period is well known (Nylin, 1988, 1992). Under a variable environment, plasticity in a life-history trait such as developmental period can be adaptive (Nylin and Gotthard, 1998).

The pattern of genetic correlation between the developmental periods and circadian rhythms found in our selection experiments (a longer developmental period corresponded to a longer free-running period) was consistent with the pattern found in previous studies on D. melanogaster and B. cucurbitae (Kyriacou et al., 1990; Shimizu et al., 1997). Other than these fly species, a genetic correlation between the developmental period and circadian rhythm has only been examined in a seed beetle Callosobruchus chinensis; however, no significant genetic correlation was observed (Harano and Miyatake, 2011). Although the genetic architecture underlying this genetic correlation remains unclear, and it might be different among species, the pattern of genetic correlation might be broadly conserved across Dipteran insects. Further studies are needed to evaluate whether this genetic correlation is a widespread phenomenon in broader taxonomic groups.

In the deficiency screening for genomic regions with effects on the developmental periods, we found a large number of genomic deficiencies that had effects on the developmental periods in females and males. As the genomic deficiencies examined in our study were experimentally generated, the significant effect of these genomic regions does not necessarily mean that they contribute to natural genetic variations in the developmental periods in D. melanogaster. However, it does suggest that a large number of quantitative trait loci in the D. melanogaster genome are potentially involved in the developmental period. The effect size distributions of the deficiencies deviated positively from zero in females and males, indicating that a larger number of deficiencies prolonged the developmental period. The positively biased effect of deficiencies might support the hypothesis that flies have evolved to develop faster, which partially explains the asymmetric response to disruptive selection in the current and previous studies (Miyatake, 1995; Zwaan et al., 1995).

Although the speed of circadian clocks is known to correlate with developmental period (Paranjpe et al., 2005), how the deficiencies affected developmental period in this study is unclear. In fact, the deleterious effect of the deficiencies on pre-adult survival was shown in Takahashi et al. (2011b), and it might also impair normal developmental processes and slow down the pre-adult development. Such deleterious effect of deficiencies may obscure the general correlation of the deficiencies' effects on developmental period and circadian rhythm because the indirect fitness effect of the deficiencies on pre-adult period is not necessarily expected to affect circadian rhythm at adult stage. In our study, the correlation between deficiency effects on the developmental and free-running periods was not significant, indicating no general genetic correlation between them. However, we found 18 genomic deficiencies with significant effects on both the developmental and free-running periods that might mediate the genetic correlation between them. The general lack of correlation between developmental and free-running periods indicates that there are many genomic regions with little pleiotropic effects. On the contrary, only a limited number of the genomic regions showed such pleiotropic effects. This suggests that these genomic regions have the potential to mediate the genetic correlation between the developmental period and circadian rhythm that was found in the selection experiment in our study. As these deficiencies encompass 33.9 genes on an average, it remains unclear whether a single gene within these deficiencies had a pleiotropic effect that affected the developmental and free-running periods. MacDonald and Rosbash (2001) performed a microarray analysis to study global circadian gene expression in D. melanogaster and found 134 cycling genes under constant dark conditions. Ueda et al. (2002) also performed a microarray analysis using different strains of D. melanogaster from the ones used by MacDonald and Rosbash (2001) to profile gene expression patterns and found 455 periodically expressed genes under constant dark conditions. Among the 18 deficiencies that had effects on both the developmental and free-running periods, three of the deficiencies encompassed eight genes that were found to be expressed periodically by McDonald and Rosbash (2001), whereas 12 deficiencies encompassed 27 genes that were found to be expressed periodically by Ueda et al., 2002 (Table 1). In our study, whether a change in the expression level of these genes affected the free-running periods of the Df/+ flies was not clear, but they are primary candidate genes with potential effects on the free-running period. Six of the 18 deficiencies encompassed no periodically expressed genes that were found in the two expression profiling studies (Table 1). As these deficiencies encompassed a relatively small number of genes (4.3 on average), a further detailed examination of individual candidate genes might lead to the discovery of novel clock genes. In addition, future examination of the individual candidate genes using RNAi or mutation approaches might elucidate how the genetic correlation between the developmental period and circadian rhythm was mediated in these deficiencies.

Table 1. Deficiencies with significant effects on both developmental period and circadian rhythm, and cycling genes found in expression profling studies (McDonald and Rosbash, 2001; Ueda et al., 2002) encompassed in each deficiency.

Chromosome Deficiency No. of genes deleted McDonald and Rosbash, 2001 Ueda et al., 2002
2L Df(2L)ED779 16   CG9934, CG16978
  Df(2L)ED1186 61   CG10283, CG10383
  Df(2L)ED4559 66   CG3523, CG3605
2R Df(2R)ED4071 103   Eps-15, Tina-1, CG3511, CG3608
3L Df(3L)ED4483 39 CG10616, CG10657 sowah, CG10418, CG10638
3R Df(3R)ED5177 7    
  Df(3R)ED5339 22   CG8861
  Df(3R)ED5511 47 Ugt35b, Ugt86Da Tctp, Ugt35b
  Df(3R)ED5634 40 CG9631, CG9649, CG31326, CG33109 Cyp6d5, CG9649
  Df(3R)ED5664 53   Art3, smp-30, Spn88Eb, CG12241
  Df(3R)ED6315 2    
  Df(3R)ED6332 4    
  Df(3R)ED6362 6    
  Df(3R)ED10549 2    
  Df(3R)ED10564 29   Art3, Spn88Eb, CG12241
  Df(3R)ED10566 29   Art3, Spn88Eb, CG12241
  Df(3R)ED10894 80   Lsd-1, mbc, Rpn9, CG10208, CG10214
  Df(3R)ED10961 5    

In our study, we performed disruptive selection on the developmental periods of D. melanogaster and found a genetic correlation between the developmental periods and circadian rhythms. We also identified 18 genomic deficiencies with effects on the developmental periods and circadian rhythms, and postulated that these genomic regions might potentially mediate the genetic correlation between them. The novel findings reported in our study might lead to a better understanding of how this correlation is regulated genetically in broader taxonomic groups.

Data archiving

There were no data to deposit.

Acknowledgments

This work was financially supported by Special Coordination Funds for Promoting Sciences and Technology of The Ministry of Education, Sport, Culture, Science and Technology of Japan, and a Grant-in-Aid for Scientific Research (KAKENHI 23770087) to KHT, and a Grant-in-Aid for Scientific Research (KAKENHI 23570027) to TM.

Appendix 1

Table A1. Deficiencies used for the screening, and their location, size, and mean developmental period and FDR from ANOVA.

Chromosome Deletion ID Region Deletion size (bp) Developmental period
        Female Male
2L Df(2L)ED3 35B2–35D1 843185 13.797 (0.104) 13.537 (0.760)
  Df(2L)ED21 21B3–21B7 125158 14.736 (0.002) 14.683 (0.001)
  Df(2L)ED40 21D1–21D2 9980 13.037 (0.015) 13.139 (0.092)
  Df(2L)ED49 1A1–100E1 19888 13.712 (0.054) 13.564 (0.607)
  Df(2L)ED87 21E2–21E2 284732 14.006 (0.034) 13.894 (0.278)
  Df(2L)ED94 21E2–21E3 468874 14.482 (0.000) 14.264 (0.002)
  Df(2L)ED105 21E2–22A1 567674 13.495 (0.977) 14.396 (0.019)
  Df(2L)ED108 21F1–22A1 301394 12.945 (0.021) 14.000 (0.467)
  Df(2L)ED122 22B1–22D4 494297 13.444 (0.631) 13.812 (0.130)
  Df(2L)ED123 22B8–22D4 236161 13.396 (0.711) 13.529 (0.832)
  Df(2L)ED124 22D3–22D4 23445 13.266 (0.086) 13.814 (0.106)
  Df(2L)ED125 22B2–22D4 484626 13.582 (0.620) 13.201 (0.221)
  Df(2L)ED132 23A3–23A3 106 12.804 (0.000) 13.015 (0.035)
  Df(2L)ED136 22F4–23A3 260190 13.227 (0.034) 13.299 (0.422)
  Df(2L)ED206 23B8–23C5 181763 12.283 (0.000) 12.338 (0.000)
  Df(2L)ED216 23B8–23C5 181892 13.389 (0.674) 13.329 (0.656)
  Df(2L)ED234 23C4–24A2 632936 15.142 (0.299) 15.290 (0.111)
  Df(2L)ED243 24A2–24A4 24683 13.607 (0.209) 13.777 (0.321)
  Df(2L)ED247 24A2–24C3 138959 13.791 (0.127) 13.920 (0.027)
  Df(2L)ED250 24F4–25A7 344209 13.874 (0.226) 13.505 (0.874)
  Df(2L)ED256 25B1–25B10 108097 13.853 (0.312) 13.484 (0.943)
  Df(2L)ED270 25F2–25F5 141567 13.001 (0.012) 13.029 (0.022)
  Df(2L)ED279 25F2–26A1 248827 13.165 (0.049) 13.436 (0.955)
  Df(2L)ED280 25F5–26A1 105526 13.172 (0.031) 13.385 (0.758)
  Df(2L)ED284 25F2–26A3 285333 13.050 (0.004) 13.273 (0.398)
  Df(2L)ED285 25F5–26A3 142032 12.890 (0.001) 12.979 (0.020)
  Df(2L)ED292 25F5–26B2 179079 13.801 (0.015) 14.300 (0.008)
  Df(2L)ED299 26B1–26B2 2194 12.556 (0.060) 12.893 (0.213)
  Df(2L)ED330 26A3–26B2 55750 14.834 (0.005) 14.680 (0.007)
  Df(2L)ED331 26B2–26B2 18588 13.012 (0.141)
  Df(2L)ED334 25F2–26B2 341038 14.246 (0.032) 14.813 (0.095)
  Df(2L)ED343 26B2–26B5 82250 13.396 (0.256) 13.095 (0.046)
  Df(2L)ED347 25F5–26B5 280456 13.465 (0.923) 13.613 (0.604)
  Df(2L)ED353 26B2–26B5 83109 13.258 (0.291) 13.115 (0.234)
  Df(2L)ED354 26B1–26B5 102961 13.889 (0.571) 13.875 (0.151)
  Df(2L)ED369 26C3–26D1 72246 12.853 (0.000) 13.018 (0.055)
  Df(2L)ED371 26C3–26D1 73530 13.798 (0.005) 13.416 (0.873)
  Df(2L)ED373 26B2–26D1 430254 12.900 (0.078) 13.575 (0.691)
  Df(2L)ED374 26B10–26D1 232319 12.469 (0.000)
  Df(2L)ED384 26B2–26D7 465648 12.860 (0.043) 13.214 (0.285)
  Df(2L)ED385 26B1–26D7 485500 14.746 (0.000) 15.261 (0.000)
  Df(2L)ED438 27D1–27D4 52278 13.676 (0.572) 13.973 (0.095)
  Df(2L)ED440 27D3–27E1 74563 13.582 (0.772) 13.416 (0.893)
  Df(2L)ED463 27F4–27F7 661 13.681 (0.224) 13.483 (0.905)
  Df(2L)ED478 27F7–28B1 139196 13.246 (0.072) 13.306 (0.422)
  Df(2L)ED494 27F4–28B1 153371 14.267 (0.010) 14.330 (0.006)
  Df(2L)ED496 28C4–28C4 9590 13.003 (0.001) 13.154 (0.184)
  Df(2L)ED501 27F7–28C4 376256 13.658 (0.225) 13.644 (0.347)
  Df(2L)ED502 28C1–28C4 122088 12.914 (0.013) 12.623 (0.003)
  Df(2L)ED508 28B1–28C4 223552 13.159 (0.198) 13.783 (0.377)
  Df(2L)ED517 27F7–28D2 447744 13.502 (0.993) 13.845 (0.127)
  Df(2L)ED548 28E1–28E9 91467 13.766 (0.174) 14.090 (0.007)
  Df(2L)ED573 28F1–29A2 95377 13.082 (0.089) 13.437 (0.943)
  Df(2L)ED578 28F1–29A3 103066 13.735 (0.474) 14.180 (0.142)
  Df(2L)ED611 29B4–29C3 36967 13.694 (0.529) 13.916 (0.080)
  Df(2L)ED623 29C1–29E4 296560 13.052 (0.007) 13.083 (0.091)
  Df(2L)ED629 29B4–29E4 317273 13.913 (0.097) 13.602 (0.351)
  Df(2L)ED630 29C3–29E4 278827 13.028 (0.003) 12.923 (0.009)
  Df(2L)ED632 29E1–29E4 156152 12.776 (0.000) 13.167 (0.095)
  Df(2L)ED647 29E1–29F5 414176 13.752 (0.043) 13.574 (0.632)
  Df(2L)ED659 29E1–30A3 646785 14.150 (0.007) 14.392 (0.012)
  Df(2L)ED673 30A4–30B3 226380 13.171 (0.069) 12.912 (0.006)
  Df(2L)ED677 30B3–30B12 144271 13.416 (0.486) 13.600 (0.617)
  Df(2L)ED678 29F5–30B12 623585 13.563 (0.753) 13.552 (0.581)
  Df(2L)ED679 30B12–30B12 10552 13.644 (0.624) 13.684 (0.604)
  Df(2L)ED680 30A4–30B12 376664 13.441 (0.606) 13.622 (0.370)
  Df(2L)ED684 30B12–30C1 42145 13.926 (0.107) 13.789 (0.110)
  Df(2L)ED690 30B3–30E4 480705 13.176 (0.312) 13.080 (0.334)
  Df(2L)ED692 30B12–30E4 346986 14.350 (0.001) 14.558 (0.001)
  Df(2L)ED695 30C5–30E4 218967 13.259 (0.078) 13.295 (0.490)
  Df(2L)ED697 30C1–30E4 301348 13.554 (0.711) 13.415 (0.836)
  Df(2L)ED700 30E1–30E4 20668 12.849 (0.158) 12.904 (0.239)
  Df(2L)ED701 30C5–30F1 249119 14.252 (0.001) 14.436 (0.001)
  Df(2L)ED729 31B1–31D7 100900 14.059 (0.005) 14.485 (0.034)
  Df(2L)ED746 31F4–32A5 225931 13.774 (0.022) 13.769 (0.170)
  Df(2L)ED748 31B1–32A5 485690 14.408 (0.000) 14.345 (0.001)
  Df(2L)ED758 33C1–33E4 367471 13.591 (0.567) 13.649 (0.406)
  Df(2L)ED760 33B8–33E5 426429 13.925 (0.007) 13.922 (0.052)
  Df(2L)ED761 33A2–33E5 627604 13.596 (0.288) 13.983 (0.190)
  Df(2L)ED769 33E9–34A1 277041 13.675 (0.155) 14.165 (0.001)
  Df(2L)ED771 33E4–34A1 388303 14.323 (0.009) 14.703 (0.012)
  Df(2L)ED773 33E9–34A3 429228 13.596 (0.689) 13.751 (0.110)
  Df(2L)ED774 34A3–34A3 683 13.538 (0.869) 13.257 (0.293)
  Df(2L)ED775 33B8–34A3 965018 13.862 (0.036) 14.651 (0.002)
  Df(2L)ED776 33E4–34A3 540490 13.758 (0.260) 14.181 (0.009)
  Df(2L)ED777 33E7–34A3 490576 13.444 (0.727) 14.050 (0.016)
  Df(2L)ED778 33E9–34A7 619745 13.758 (0.079) 14.243 (0.012)
  Df(2L)ED779 34A3–34A7 191200 15.034 (0.000) 15.014 (0.001)
  Df(2L)ED780 33E4–34A7 731007 13.846 (0.029) 14.300 (0.003)
  Df(2L)ED784 34A4–34B6 327612 14.388 (0.011) 14.078 (0.325)
  Df(2L)ED791 34E1–35B4 811156 14.445 (0.024) 14.367 (0.003)
  Df(2L)ED793 34E4–35B4 754489 14.832 (0.001) 14.712 (0.027)
  Df(2L)ED796 35C1–35C4 152111 14.046 (0.070) 13.890 (0.143)
  Df(2L)ED929 21B3–21B3 18484 13.965 (0.130) 13.762 (0.300)
  Df(2L)ED1000 35B8–35D1 336213 13.490 (0.962) 13.871 (0.180)
  Df(2L)ED1004 35B10–35D1 272692 14.107 (0.089) 14.260 (0.070)
  Df(2L)ED1050 35B8–35D4 765231 13.524 (0.890) 13.581 (0.679)
  Df(2L)ED1054 35B10–35D4 701710 14.509 (0.002) 14.367 (0.007)
  Df(2L)ED1056 35D2–35D4 284125 13.834 (0.154) 14.099 (0.009)
  Df(2L)ED1092 35F12–36A10 329835 13.632 (0.287) 13.907 (0.022)
  Df(2L)ED1102 35F12–36A10 334647 13.739 (0.097) 14.476 (0.009)
  Df(2L)ED1109 36A3–36A10 164790 13.649 (0.312) 13.842 (0.124)
  Df(2L)ED1143 36A10–36B1 106247 13.369 (0.604) 13.633 (0.440)
  Df(2L)ED1153 35F12–36B2 502171 14.371 (0.011) 14.243 (0.012)
  Df(2L)ED1158 36B1–36C9 658852 14.270 (0.005) 14.228 (0.040)
  Df(2L)ED1161 36A10–36C9 788014 13.920 (0.043) 13.770 (0.180)
  Df(2L)ED1164 36A10–36C9 787566 14.424 (0.005) 14.547 (0.001)
  Df(2L)ED1165 36C1–36C9 360447 14.071 (0.134) 14.244 (0.010)
  Df(2L)ED1175 36C1–36C10 383436 13.023 (0.005) 13.222 (0.227)
  Df(2L)ED1183 36E6–36F7 465553 14.700 (0.000) 14.796 (0.000)
  Df(2L)ED1186 36E6–37A2 581220 15.539 (0.000) 15.559 (0.001)
  Df(2L)ED1187 36F7–37A2 115693 12.594 (0.000)
  Df(2L)ED1196 36E6–37B1 671892 15.616 (0.000) 16.005 (0.000)
  Df(2L)ED1198 36F7–37B1 206365 14.008 (0.150) 14.359 (0.017)
  Df(2L)ED1200 44D8–45B4 155049 13.739 (0.504) 13.700 (0.376)
  Df(2L)ED1202 37B1–37C5 334948 13.600 (0.638) 13.449 (0.981)
  Df(2L)ED1226 37B9–37E3 460658 12.967 (0.008) 13.407 (0.835)
  Df(2L)ED1231 37C5–37E3 305616 13.897 (0.267) 14.071 (0.135)
  Df(2L)ED1236 37B9–37E4 483659 14.190 (0.001) 14.054 (0.058)
  Df(2L)ED1238 37C1–37E4 357571 13.600 (0.765) 13.671 (0.456)
  Df(2L)ED1242 37E5–37F1 15994 13.709 (0.460) 13.820 (0.225)
  Df(2L)ED1243 37B9–37F1 524349 13.676 (0.281) 13.787 (0.294)
  Df(2L)ED1245 37C1–37F1 398261 14.035 (0.055) 14.701 (0.007)
  Df(2L)ED1250 37E5–37F1 24869 13.665 (0.264) 14.193 (0.024)
  Df(2L)ED1251 37B9–37F1 533224 14.610 (0.000) 14.334 (0.045)
  Df(2L)ED1272 37C5–38A2 594884 13.577 (0.611) 14.381 (0.003)
  Df(2L)ED1303 37E5–38C6 864775 12.979 (0.314) 12.853 (0.285)
  Df(2L)ED1305 38B4–38C6 296988 13.974 (0.009) 13.832 (0.084)
  Df(2L)ED1315 38B4–38F5 832122 13.384 (0.690) 13.298 (0.604)
  Df(2L)ED1317 38D1–38F5 278939 12.811 (0.001) 13.185 (0.315)
  Df(2L)ED1375 38F5–39D2 457289 13.355 (0.650) 13.295 (0.495)
  Df(2L)ED1378 38F1–39D2 574133 14.519 (0.002) 14.539 (0.002)
  Df(2L)ED1382 39B4–39D2 159357 14.625 (0.000) 14.723 (0.002)
  Df(2L)ED1384 38F5–39D2 474447 14.049 (0.072) 13.999 (0.066)
  Df(2L)ED1451 38F5–39E2 666875 13.094 (0.059) 12.919 (0.035)
  Df(2L)ED1454 39E3–39E6 28361 13.345 (0.267) 13.498 (0.867)
  Df(2L)ED1455 39A1–39E6 605551 13.742 (0.146) 13.468 (0.956)
  Df(2L)ED1462 39B4–39E6 406785 12.744 (0.299) 12.889 (0.370)
  Df(2L)ED1466 39E3–40A5 199232 13.027 (0.104) 13.609 (0.578)
  Df(2L)ED1473 39B4–40A5 577656 14.392 (0.000) 14.710 (0.000)
  Df(2L)ED2809 21B1–21B1 5306 13.059 (0.018) 12.925 (0.016)
  Df(2L)ED4330 23C4–23C5 56592 14.350 (0.012) 14.173 (0.055)
  Df(2L)ED4559 23C4–23F6 479077 15.643 (0.000) 15.024 (0.001)
  Df(2L)ED4651 23B8–23F6 604377 15.272 (0.000) 14.978 (0.000)
  Df(2L)ED5878 21B1–21B3 93755 14.447 (0.001) 14.133 (0.046)
  Df(2L)ED6569 27A1–27C4 212193 13.582 (0.526) 13.574 (0.460)
  Df(2L)ED7007 27A1–27C7 254709 13.915 (0.167) 13.509 (0.762)
  Df(2L)ED7666 22F4–22F4 1188 13.295 (0.460) 13.150 (0.343)
  Df(2L)ED7733 21E2–21F1 266285 13.307 (0.545) 13.516 (0.875)
  Df(2L)ED7762 22A6–22D3 539713 13.730 (0.460) 14.008 (0.028)
  Df(2L)ED7853 25A3–25B10 299273 13.981 (0.049) 13.507 (0.794)
  Df(2L)ED8142 31E1–32A4 271218 13.185 (0.010) 13.564 (0.608)
  Df(2L)ED8185 34E1–35A4 456009 14.205 (0.003) 14.336 (0.001)
  Df(2L)ED8186 34E4–35A4 399342 13.715 (0.244) 13.802 (0.247)
  Df(2L)ED8368 36B1–36B2 33618 13.052 (0.008) 12.876 (0.015)
  Df(2L)ED8386 36C1–36C9 337487 14.427 (0.000) 14.894 (0.000)
  Df(2L)ED12487 25C3–25F2 604135 14.180 (0.001) 14.141 (0.058)
  Df(2L)ED12527 28C4–28D3 203671 13.660 (0.506) 13.507 (0.812)
  Df(2L)ED13216 36A12–36B1 70720 13.694 (0.503) 13.443 (0.958)
2R Df(2R)ED1 53E9–53F8 70595 13.464 (0.766) 13.625 (0.507)
  Df(2R)ED1482 42A8–42A11 96487 12.641 (0.000) 12.945 (0.010)
  Df(2R)ED1484 42A2–42A14 351791 13.136 (0.092) 13.103 (0.129)
  Df(2R)ED1552 42A11–42C7 608682 12.923 (0.143) 12.713 (0.130)
  Df(2R)ED1612 42A13–42E6 829140 13.294 (0.335) 13.305 (0.495)
  Df(2R)ED1618 42C3–43A1 518138 13.074 (0.001) 13.230 (0.258)
  Df(2R)ED1673 42E4–43D3 547751 13.013 (0.014) 13.092 (0.337)
  Df(2R)ED1715 43A4–43F1 589972 13.633 (0.616) 13.799 (0.276)
  Df(2R)ED1725 43E4–44B5 542121 13.943 (0.005) 14.367 (0.002)
  Df(2R)ED1735 43F8–44D4 638302 13.364 (0.460) 13.573 (0.655)
  Df(2R)ED1742 44B8–44E3 549961 14.059 (0.029) 14.051 (0.005)
  Df(2R)ED1770 14A8–14C6 551912 13.569 (0.808) 13.345 (0.832)
  Df(2R)ED1791 44F7–45F1 630522 13.504 (0.980) 13.679 (0.258)
  Df(2R)ED2076 47A10–47C1 343202 13.206 (0.467) 13.416 (0.939)
  Df(2R)ED2098 47A7–47C6 482345 13.727 (0.482) 14.060 (0.167)
  Df(2R)ED2155 47C6–47F8 503346 13.121 (0.074) 13.120 (0.073)
  Df(2R)ED2219 47D6–48B6 467979 13.925 (0.338) 13.667 (0.579)
  Df(2R)ED2222 47F13–48B6 212411 13.921 (0.021) 14.149 (0.004)
  Df(2R)ED2308 49D3–49E7 216614 13.517 (0.959) 13.199 (0.110)
  Df(2R)ED2311 49E4–49F10 277450 13.861 (0.256) 14.217 (0.065)
  Df(2R)ED2354 50E6–51B1 315512 13.361 (0.448) 13.469 (0.949)
  Df(2R)ED2423 51C5–51F11 520185 13.747 (0.075) 13.602 (0.484)
  Df(2R)ED2426 51E2–52B1 482016 13.436 (0.571) 13.870 (0.151)
  Df(2R)ED2436 51F11–52D11 627239 13.832 (0.027) 14.057 (0.008)
  Df(2R)ED2457 52D11–52E7 129848 14.078 (0.001) 14.268 (0.001)
  Df(2R)ED2487 52E6–53C4 261478 13.026 (0.011) 13.258 (0.428)
  Df(2R)ED2748 53D11–53F8 268682 13.251 (0.192) 13.458 (0.988)
  Df(2R)ED2751 53D14–53F8 240132 13.229 (0.145) 13.510 (0.874)
  Df(2R)ED3181 57F10–57F10 524868 13.682 (0.376) 13.731 (0.169)
  Df(2R)ED3610 54F1–55C8 561128 14.107 (0.011) 13.733 (0.490)
  Df(2R)ED3683 55C2–56C4 940122 13.139 (0.250) 13.285 (0.391)
  Df(2R)ED3728 56D10–56E2 264297 13.827 (0.460) 13.785 (0.266)
  Df(2R)ED3791 57B1–57D4 552570 13.507 (0.964) 13.608 (0.347)
  Df(2R)ED3921 57F9–57F10 11246 13.063 (0.004) 13.030 (0.024)
  Df(2R)ED3923 57F6–57F10 67570 13.897 (0.007) 13.935 (0.018)
  Df(2R)ED3943 37B9–37C5 688723 14.051 (0.139) 14.440 (0.034)
  Df(2R)ED3952 58B10–58E5 386674 13.111 (0.181) 13.196 (0.151)
  Df(2R)ED4061 60C8–60D13 270614 13.308 (0.282) 13.517 (0.794)
  Df(2R)ED4071 60C8–60E8 540173 15.150 (0.000) 15.192 (0.000)
  Df(2R)ED9039 48C5–48E4 283867 13.695 (0.256) 13.936 (0.016)
  Df(2R)ED9045 48F5–49A7 212898 12.561 (0.009) 12.625 (0.051)
3L Df(3L)ED201 91A5–91F1 224017 13.677 (0.338) 13.463 (0.973)
  Df(3L)ED202 61C9–61F7 597642 13.666 (0.314) 13.989 (0.133)
  Df(3L)ED207 61C9–62A6 829369 14.917 (0.000) 14.586 (0.001)
  Df(3L)ED208 63C1–63F5 644000 13.142 (0.059) 13.155 (0.200)
  Df(3L)ED210 64B9–64C13 804208 13.650 (0.621) 14.010 (0.135)
  Df(3L)ED211 65A9–65B4 334624 13.078 (0.179) 12.973 (0.124)
  Df(3L)ED215 69B5–69C4 86745 14.816 (0.000) 15.106 (0.001)
  Df(3L)ED217 70F4–71E1 831026 13.044 (0.397) 13.512 (0.901)
  Df(3L)ED218 71B1–71E1 575028 13.824 (0.066) 14.073 (0.201)
  Df(3L)ED220 72D4–72F1 324193 15.556 (0.000) 16.338 (0.000)
  Df(3L)ED223 73A1–73D5 439052 14.400 (0.006) 14.075 (0.181)
  Df(3L)ED224 75B1–75C6 429316 13.678 (0.398) 13.670 (0.495)
  Df(3L)ED225 75C1–75D4 435192 12.806 (0.008) 13.076 (0.185)
  Df(3L)ED228 76A1–76D2 701102 13.070 (0.251) 13.189 (0.637)
  Df(3L)ED230 79C2–80A4 699720 14.182 (0.009) 14.657 (0.000)
  Df(3L)ED231 80B1–80C1 73704 13.299 (0.448) 13.176 (0.239)
  Df(3L)ED4079 61A5–61B1 91461 13.048 (0.005) 13.082 (0.082)
  Df(3L)ED4177 61C1–61E2 715336 13.693 (0.603) 13.784 (0.221)
  Df(3L)ED4191 61C3–62A2 934664 14.067 (0.134) 14.225 (0.151)
  Df(3L)ED4196 61C7–62A2 839354 13.322 (0.630) 13.183 (0.656)
  Df(3L)ED4238 61C9–62A4 808192 13.773 (0.231) 14.281 (0.109)
  Df(3L)ED4256 62A3–62A6 40559 13.158 (0.104) 13.148 (0.391)
  Df(3L)ED4284 62B4–62B12 168110 13.856 (0.276) 13.657 (0.523)
  Df(3L)ED4287 62B4–62E5 756319 13.585 (0.600) 13.356 (0.652)
  Df(3L)ED4288 63A6–63B7 78264 13.748 (0.411) 13.577 (0.643)
  Df(3L)ED4293 63C1–63C1 24226 13.607 (0.624) 13.391 (0.866)
  Df(3L)ED4341 63F6–64B9 637145 15.781 (0.000) 15.684 (0.001)
  Df(3L)ED4342 64A12–64B12 347385 14.029 (0.001) 14.242 (0.003)
  Df(3L)ED4408 66A22–66C5 320467 14.596 (0.001) 15.186 (0.000)
  Df(3L)ED4414 66D12–66E6 233661 13.299 (0.146) 13.386 (0.758)
  Df(3L)ED4415 66D12–66E6 213016 13.571 (0.690) 14.124 (0.169)
  Df(3L)ED4416 66E1–67B1 522145 12.963 (0.049) 12.969 (0.079)
  Df(3L)ED4421 66D12–67B3 638749 13.420 (0.869) 13.409 (0.919)
  Df(3L)ED4457 67E2–68A7 761858 12.730 (0.025) 12.902 (0.088)
  Df(3L)ED4470 68A6–68E1 736241 14.399 (0.000) 14.616 (0.004)
  Df(3L)ED4483 69A5–69D3 415994 15.832 (0.000) 15.876 (0.000)
  Df(3L)ED4486 69C4–69F6 518066 14.190 (0.061) 14.047 (0.091)
  Df(3L)ED4502 70A3–70C10 765786 13.485 (0.959) 13.674 (0.264)
  Df(3L)ED4515 70C6–70C15 97860 13.398 (0.394) 13.329 (0.604)
  Df(3L)ED4528 70C15–70D2 39982 13.417 (0.711) 13.229 (0.378)
  Df(3L)ED4534 70C15–70D3 156653 13.228 (0.294) 13.052 (0.245)
  Df(3L)ED4536 70C11–70D3 202563 13.211 (0.181) 13.213 (0.318)
  Df(3L)ED4543 70C6–70F4 822815 15.457 (0.000) 15.225 (0.000)
  Df(3L)ED4606 72D4–73C4 692639 14.750 (0.012) 15.115 (0.012)
  Df(3L)ED4674 73B5–73E5 388134 13.679 (0.373) 13.651 (0.337)
  Df(3L)ED4685 73D5–74E2 721094 13.645 (0.368) 13.394 (0.790)
  Df(3L)ED4710 74D1–75B11 651836 14.658 (0.004) 15.145 (0.000)
  Df(3L)ED4743 75D4–75D8 133616 13.261 (0.210) 13.317 (0.423)
  Df(3L)ED4744 75D8–75E1 14368 13.572 (0.437) 13.713 (0.351)
  Df(3L)ED4782 75F2–76A1 174808 13.128 (0.129) 13.524 (0.812)
  Df(3L)ED4786 75F7–76A5 194711 13.210 (0.281) 13.605 (0.490)
  Df(3L)ED4789 76A1–76A5 124956 13.455 (0.706) 13.231 (0.180)
  Df(3L)ED4799 76A1–76B3 311466 13.130 (0.129) 13.145 (0.105)
  Df(3L)ED4858 76D3–77C1 506447 13.685 (0.670) 13.273 (0.624)
  Df(3L)ED4957 78C3–78F1 530381 14.150 (0.114) 14.042 (0.151)
  Df(3L)ED4978 78D5–79A2 346878 13.709 (0.229) 14.120 (0.143)
  Df(3L)ED5013 80A1–80B1 150650 13.438 (0.620) 13.795 (0.142)
  Df(3L)ED5017 80A4–80C2 162804 15.020 (0.004) 15.512 (0.000)
3R Df(3R)ED2 21E2–21E2 697540 14.896 (0.000) 15.026 (0.002)
  Df(3R)ED5020 82A3–82B1 108705 13.058 (0.015) 13.056 (0.127)
  Df(3R)ED5021 82A1–82B1 193118 13.114 (0.311) 12.879 (0.055)
  Df(3R)ED5046 82A1–82D3 541858 13.517 (0.949) 13.402 (0.809)
  Df(3R)ED5066 82D1–82E4 302797 13.947 (0.002) 13.682 (0.280)
  Df(3R)ED5071 82A1–82E4 755409 14.519 (0.027) 14.737 (0.005)
  Df(3R)ED5092 82A3–82E8 805399 16.192 (0.000) 15.897 (0.001)
  Df(3R)ED5095 82D1–82E8 437200 13.993 (0.004) 13.657 (0.312)
  Df(3R)ED5100 82A1–82E8 889812 15.927 (0.000) 15.953 (0.000)
  Df(3R)ED5138 82D5–82F8 483811 13.700 (0.250) 13.592 (0.607)
  Df(3R)ED5142 82B3–82F8 811587 14.413 (0.006) 13.938 (0.035)
  Df(3R)ED5147 82E8–83A1 280684 14.583 (0.000) 14.745 (0.001)
  Df(3R)ED5156 82F8–83A4 193919 13.179 (0.011) 13.413 (0.791)
  Df(3R)ED5177 83B4–83B6 23466 14.994 (0.000) 15.166 (0.001)
  Df(3R)ED5187 83B7–83B8 6020 13.840 (0.411) 13.315 (0.604)
  Df(3R)ED5196 83B9–83D2 323565 14.812 (0.001) 14.922 (0.000)
  Df(3R)ED5197 83B7–83D2 359362 13.095 (0.019) 13.191 (0.127)
  Df(3R)ED5220 84E6–84E11 116309 13.035 (0.015) 13.316 (0.424)
  Df(3R)ED5221 84C4–84E11 965801 12.803 (0.000) 13.098 (0.130)
  Df(3R)ED5223 84D9–84E11 602379 12.537 (0.003) 12.743 (0.118)
  Df(3R)ED5230 84E6–85A5 675360 12.900 (0.018) 12.903 (0.068)
  Df(3R)ED5296 84F6–85C3 806270 13.612 (0.612) 13.797 (0.169)
  Df(3R)ED5301 85C3–85C3 22497 13.007 (0.000) 13.247 (0.370)
  Df(3R)ED5327 85D1–85D1 2719 13.251 (0.159) 13.404 (0.821)
  Df(3R)ED5330 85A5–85D1 560209 13.350 (0.534) 13.967 (0.310)
  Df(3R)ED5331 85C3–85D1 195601 13.296 (0.363) 13.265 (0.523)
  Df(3R)ED5339 85D1–85D11 125299 14.819 (0.001) 15.291 (0.000)
  Df(3R)ED5416 85D16–85E6 335297 13.279 (0.114) 13.363 (0.744)
  Df(3R)ED5428 85E1–85F8 417820 14.345 (0.001) 13.946 (0.051)
  Df(3R)ED5438 85E5–85F8 321934 13.401 (0.727) 13.517 (0.779)
  Df(3R)ED5472 85F16–86B1 180223 12.976 (0.113) 13.156 (0.221)
  Df(3R)ED5474 85F11–86B1 241312 12.819 (0.068) 12.757 (0.055)
  Df(3R)ED5495 85F16–86C7 716259 13.103 (0.078) 13.911 (0.296)
  Df(3R)ED5506 86C7–86D5 287750 13.012 (0.001) 13.179 (0.151)
  Df(3R)ED5511 86C7–86D9 359178 12.267 (0.000) 12.376 (0.000)
  Df(3R)ED5514 86C7–86E11 684255 14.812 (0.014) 15.350 (0.000)
  Df(3R)ED5516 86D8–86E13 385730 13.222 (0.355) 13.422 (0.938)
  Df(3R)ED5518 86C7–86E13 734902 16.708 (0.000) 16.480 (0.000)
  Df(3R)ED5519 86E11–86E13 53930 13.442 (0.590) 13.415 (0.815)
  Df(3R)ED5554 87B5–87B11 162903 13.172 (0.005) 13.239 (0.420)
  Df(3R)ED5558 86F9–87B11 615275 13.967 (0.021) 13.584 (0.495)
  Df(3R)ED5559 86E11–87B11 874834 16.437 (0.000) 16.316 (0.000)
  Df(3R)ED5573 87B5–87B13 196465 12.413 (0.007) 12.480 (0.016)
  Df(3R)ED5573 87B5–87B13 196465 12.413 (0.007) 12.480 (0.016)
  Df(3R)ED5577 86F9–87B13 648837 15.059 (0.000) 15.191 (0.000)
  Df(3R)ED5591 87B7–87C7 369479 14.148 (0.003) 14.157 (0.012)
  Df(3R)ED5608 87C7–87D7 275690 14.633 (0.005) 15.577 (0.003)
  Df(3R)ED5610 87B11–87D7 551659 15.055 (0.000) 14.990 (0.000)
  Df(3R)ED5612 87C7–87F6 925149 14.381 (0.003) 14.908 (0.001)
  Df(3R)ED5613 87E3–87F6 385385 14.031 (0.003) 14.607 (0.001)
  Df(3R)ED5622 87F10–88A4 300090 14.410 (0.281) 14.339 (0.030)
  Df(3R)ED5623 87E3–88A4 724163 15.169 (0.005) 15.043 (0.020)
  Df(3R)ED5634 88A4–88B1 260040 15.023 (0.001) 14.968 (0.001)
  Df(3R)ED5642 87F10–88C2 797952 14.295 (0.000) 14.238 (0.001)
  Df(3R)ED5644 88A4–88C9 607806 13.849 (0.057) 13.920 (0.024)
  Df(3R)ED5657 88D1–88D7 221350 15.628 (0.000) 15.788 (0.000)
  Df(3R)ED5660 88D1–88E1 396848 15.593 (0.000) 16.485 (0.000)
  Df(3R)ED5662 88D1–88E2 434545 16.315 (0.000) 16.406 (0.000)
  Df(3R)ED5664 88D1–88E3 531540 16.487 (0.000) 16.892 (0.000)
  Df(3R)ED5688 88E12–88F1 37068 12.838 (0.006) 12.759 (0.018)
  Df(3R)ED5705 88E12–89A5 502138 14.695 (0.006) 14.733 (0.035)
  Df(3R)ED5780 89E11–90C1 625324 13.339 (0.181) 13.331 (0.437)
  Df(3R)ED5781 89E13–90C1 562695 12.786 (0.094) 13.074 (0.377)
  Df(3R)ED5785 90C2–90D1 225960 13.234 (0.068) 13.199 (0.377)
  Df(3R)ED5807 90C2–91A5 681121 13.654 (0.405) 13.500 (0.875)
  Df(3R)ED5815 90F4–91B8 491112 16.000 (0.030)
  Df(3R)ED5911 91C5–91F8 422856 14.796 (0.000) 15.143 (0.001)
  Df(3R)ED5938 91D4–92A11 735402 15.433 (0.004) 15.173 (0.001)
  Df(3R)ED6025 92A11–92E2 666791 16.041 (0.000) 16.167 (0.000)
  Df(3R)ED6027 92B3–92E2 472646 13.051 (0.015) 13.011 (0.027)
  Df(3R)ED6052 93D4–93D8 68869 12.421 (0.002) 12.520 (0.014)
  Df(3R)ED6058 93D4–93F6 423105 13.936 (0.072) 14.315 (0.005)
  Df(3R)ED6076 93E10–94A1 409323 15.137 (0.000) 14.307 (0.002)
  Df(3R)ED6079 94A1–94A2 91507 12.831 (0.000) 12.724 (0.003)
  Df(3R)ED6085 93F14–94B5 706744 12.909 (0.220) 13.009 (0.262)
  Df(3R)ED6090 94A1–94C1 656195 15.311 (0.002) 14.784 (0.003)
  Df(3R)ED6091 94B5–94C4 138626 12.950 (0.024) 12.879 (0.057)
  Df(3R)ED6093 94A2–94C4 592519 15.693 (0.000) 15.445 (0.000)
  Df(3R)ED6096 94B5–94E7 634288 15.238 (0.000) 15.042 (0.002)
  Df(3R)ED6103 94D3–94E9 359862 14.967 (0.000) 14.465 (0.006)
  Df(3R)ED6105 94E9–94E11 37549 15.042 (0.000) 14.990 (0.000)
  Df(3R)ED6116 95B4–95C1 46434 12.850 (0.004) 13.036 (0.152)
  Df(3R)ED6119 95C8–95C12 35707 15.143 (0.003) 15.516 (0.002)
  Df(3R)ED6144 95C8–95D1 55833 12.513 (0.003) 12.644 (0.024)
  Df(3R)ED6150 95D1–95D11 114310 12.696 (0.005) 12.839 (0.054)
  Df(3R)ED6155 95B4–95D11 283236 14.231 (0.010) 14.395 (0.002)
  Df(3R)ED6168 95D1–95F8 328141 12.396 (0.000) 12.499 (0.012)
  Df(3R)ED6187 95D10–96A7 492295 15.640 (0.004) 15.140 (0.001)
  Df(3R)ED6220 96A7–96C3 639975 14.415 (0.000) 14.521 (0.001)
  Df(3R)ED6232 96F10–97D2 762106 16.057 (0.000) 16.125 (0.000)
  Df(3R)ED6235 97B9–97D12 445273 13.148 (0.092) 13.285 (0.299)
  Df(3R)ED6242 97E4–97E11 123525 14.735 (0.000) 14.669 (0.001)
  Df(3R)ED6255 97D2–97F1 482865 15.119 (0.001) 14.706 (0.000)
  Df(3R)ED6265 97E2–98A7 467511 12.530 (0.000) 12.568 (0.014)
  Df(3R)ED6277 98B6–98B6 10924 12.711 (0.006) 12.918 (0.179)
  Df(3R)ED6290 98C3–98E5 485726 14.406 (0.000) 14.603 (0.001)
  Df(3R)ED6310 98F12–99B2 373258 14.381 (0.000) 14.540 (0.001)
  Df(3R)ED6315 99B10–99C1 17077 15.210 (0.000) 14.863 (0.003)
  Df(3R)ED6316 99A5–99C1 527344 15.444 (0.000) 15.342 (0.000)
  Df(3R)ED6332 99E4–99F2 111366 15.221 (0.000) 14.913 (0.000)
  Df(3R)ED6346 100A5–100B1 265322 18.383 (0.000) 18.167 (0.000)
  Df(3R)ED6361 100C7–100E3 469313 15.383 (0.000) 14.575 (0.001)
  Df(3R)ED6362 100E1–100E3 141893 14.821 (0.000) 14.861 (0.001)
  Df(3R)ED7665 84B4–84E11 1003556 14.300 (0.161) 14.200 (0.337)
  Df(3R)ED10257 83A7–83B4 81922 15.026 (0.000) 15.102 (0.002)
  Df(3R)ED10549 88D6–88D7 17163 15.191 (0.000) 15.051 (0.000)
  Df(3R)ED10555 88C9–88D8 361038 14.177 (0.000) 14.170 (0.030)
  Df(3R)ED10556 88D6–88E1 192661 15.288 (0.000) 15.723 (0.001)
  Df(3R)ED10557 88D6–88E2 230358 15.780 (0.001) 15.707 (0.000)
  Df(3R)ED10561 88E2–88E2 25799 14.868 (0.000) 14.829 (0.000)
  Df(3R)ED10564 88D6–88E3 327353 14.923 (0.001) 15.267 (0.000)
  Df(3R)ED10566 88E2–88E5 118112 14.942 (0.000) 15.751 (0.000)
  Df(3R)ED10639 89B7–89D2 268307 15.219 (0.000) 14.799 (0.007)
  Df(3R)ED10642 89C7–89D5 171514 15.051 (0.000) 14.778 (0.002)
  Df(3R)ED10811 93A4–93B8 111808 15.364 (0.001) 14.993 (0.000)
  Df(3R)ED10820 93A4–93B12 162720 14.892 (0.001) 14.455 (0.043)
  Df(3R)ED10838 93C1–93D4 162185 15.819 (0.000) 15.639 (0.006)
  Df(3R)ED10893 95C8–95E1 217754 14.634 (0.000) 14.210 (0.049)
  Df(3R)ED10894 95A7–95E1 435407 15.191 (0.000) 15.194 (0.000)
  Df(3R)ED10946 96B20–96D1 221386 15.604 (0.000) 15.305 (0.000)
  Df(3R)ED10953 96C6–96D1 70912 16.225 (0.000) 16.207 (0.000)
  Df(3R)ED10961 97E11–97F1 19770 14.822 (0.000) 15.015 (0.001)
  Df(3R)ED10966 97E11–97F1 28417 14.737 (0.000) 14.581 (0.002)
  Df(3R)ED10970 97E11–98B5 652492 14.692 (0.008) 14.530 (0.001)
  Df(3R)ED10993 99B10–99C2 41267 15.588 (0.000) 15.175 (0.000)
  Df(3R)ED13102 99B1–99B10 279997 15.610 (0.000) 15.324 (0.000)
X Df(1)ED404 1D2–1E3 200503 13.672 (0.321)
  Df(1)ED409 2C7–2F5 275404 13.634 (0.869)
  Df(1)ED411 3A3–3A8 172827 13.592 (0.894)
  Df(1)ED418 5C7–5E4 377712 13.837 (0.044)
  Df(1)ED429 9D3–9D3 38567 14.373 (0.001) 14.302 (0.005)
  Df(1)ED447 17C1–17F1 356796 14.914 (0.000)
  Df(1)ED6396 1B5–1B8 30101 14.692 (0.000)
  Df(1)ED6443 1B14–1E1 370684 14.746 (0.000)
  Df(1)ED6574 2E1–3A2 203136 13.271 (0.597)
  Df(1)ED6579 3A6–3A8 53476 15.794 (0.000)
  Df(1)ED6584 3A8–3B1 49222 12.961 (0.008)
  Df(1)ED6630 3B1–3C5 351370 14.868 (0.000)
  Df(1)ED6712 3D3–3F1 357080 14.100 (0.078)
  Df(1)ED6727 4B6–4D5 585887 14.266 (0.011)
  Df(1)ED6802 5A12–5D1 285900 13.346 (0.265)
  Df(1)ED6829 5C7–5F3 451119 13.048 (0.117)
  Df(1)ED6849 5F3–6D3 452200 13.862 (0.080)
  Df(1)ED6878 6C12–6D8 103655 13.514 (0.964)
  Df(1)ED6906 7A3–7B2 210722 13.191 (0.181)
  Df(1)ED6940 36A10–36B1 297221 12.454 (0.001)
  Df(1)ED6957 8B6–8C13 243242 13.179 (0.021)
  Df(1)ED6989 8F9–9B1 383820 13.428 (0.694)
  Df(1)ED6991 8F9–9B4 524871 12.155 (0.002)
  Df(1)ED7005 9B1–9D3 513509 15.667 (0.007)
  Df(1)ED7010 9D3–9D4 82437 14.383 (0.007)
  Df(1)ED7067 10B8–10C10 210959 13.265 (0.048)
  Df(1)ED7147 10D7–11A1 290417 13.373 (0.610)
  Df(1)ED7153 11A1–11B1 560373 13.976 (0.025)
  Df(1)ED7161 11A1–11B14 743779 14.781 (0.010)
  Df(1)ED7165 11B15–11E1 386346 14.032 (0.014)
  Df(1)ED7170 11B15–11E8 524724 13.839 (0.101)
  Df(1)ED7173 11B15–11F1 621133 14.467 (0.002)
  Df(1)ED7217 12A9–12C6 180238 13.205 (0.077)
  Df(1)ED7229 12E5–12F2 431710 12.961 (0.000)
  Df(1)ED7261 12F2–12F5 185603 13.074 (0.376)
  Df(1)ED7265 12F4–13A5 181838 13.986 (0.144)
  Df(1)ED7289 13A5–13A12 100973 13.941 (0.044)
  Df(1)ED7294 13B1–13C3 274883 13.860 (0.296)
  Df(1)ED7331 13C3–13F1 363268 12.469 (0.044)
  Df(1)ED7344 13E1–13F17 241694 14.022 (0.022)
  Df(1)ED7355 14A8–14B7 186930 13.662 (0.583) 13.600 (0.679)
  Df(1)ED7374 15A1–15E3 412445 12.860 (0.071)
  Df(1)ED7413 17D1–17F1 206484 13.793 (0.269)
  Df(1)ED7441 18A3–18C2 168474 13.211 (0.119)
  Df(1)ED7635 19A2–19C1 278714 13.568 (0.656) 14.125 (0.045)
  Df(1)ED7664 19F1–19F6 250376 13.396 (0.576)
  Df(1)ED11354 61B1–61C1 191859 12.944 (0.094)
  Df(1)ED11437 2F6–3A4 518880 13.137 (0.198)
  Df(1)ED12405 19C4–19E5 594760 13.802 (0.224)
  Df(1)ED12425 19E7–19F3 216238 13.645 (0.473)
  Df(1)ED12432 20C1–20C1 97858 13.842 (0.287) 13.716 (0.366)
  Df(1)ED13157 18F4–19C1 288549 13.747 (0.114) 14.750 (0.005)
  Df(1)ED13478 16F6–16F7 16605 13.712 (0.219)
  Df(1)ED14021 20C1–20E1 320915 13.465 (0.803)

The authors declare no conflict of interest.

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