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Evidence that natural selection maintains genetic variation for sleep in Drosophila melanogaster.

Svetec N, Zhao L, Saelao P, Chiu JC, Begun DJ - BMC Evol. Biol. (2015)

Bottom Line: We also found evidence for geographic variation for sunrise anticipation.Furthermore, the present study suggests that natural selection plays a major role in generating transcriptomic variation associated with circadian behaviors.Finally, we identified genomic variants plausibly causally associated with the observed behavioral and transcriptomic variation.

View Article: PubMed Central - PubMed

Affiliation: Department of Evolution and Ecology, University of California, 3352 Storer Hall, One Shields Ave., Davis, CA, 95618, USA. nhsvetec@ucdavis.edu.

ABSTRACT

Background: Drosophila melanogaster often shows correlations between latitude and phenotypic or genetic variation on different continents, which suggests local adaptation with respect to a heterogeneous environment. Previous phenotypic analyses of latitudinal clines have investigated mainly physiological, morphological, or life-history traits. Here, we studied latitudinal variation in sleep in D. melanogaster populations from North and Central America. In parallel, we used RNA-seq to identify interpopulation gene expression differences.

Results: We found that in D. melanogaster the average nighttime sleep bout duration exhibits a latitudinal cline such that sleep bouts of equatorial populations are roughly twice as long as those of temperate populations. Interestingly, this pattern of latitudinal variation is not observed for any daytime measure of activity or sleep. We also found evidence for geographic variation for sunrise anticipation. Our RNA-seq experiment carried out on heads from a low and high latitude population identified a large number of gene expression differences, most of which were time dependent. Differentially expressed genes were enriched in circadian regulated genes and enriched in genes potentially under spatially varying selection.

Conclusion: Our results are consistent with a mechanistic and selective decoupling of nighttime and daytime activity. Furthermore, the present study suggests that natural selection plays a major role in generating transcriptomic variation associated with circadian behaviors. Finally, we identified genomic variants plausibly causally associated with the observed behavioral and transcriptomic variation.

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A large fraction of the geographic variation in gene expression is circadian time specific. A) Venn Diagram showing the distribution across timepoints of the genes differentially expressed between PC and RI. B) Venn Diagram showing the distribution across timepoints of the genes differentially expressed and located into the 5% outlier FST windows. Actual number of genes is indicated in parenthesis.
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Fig5: A large fraction of the geographic variation in gene expression is circadian time specific. A) Venn Diagram showing the distribution across timepoints of the genes differentially expressed between PC and RI. B) Venn Diagram showing the distribution across timepoints of the genes differentially expressed and located into the 5% outlier FST windows. Actual number of genes is indicated in parenthesis.

Mentions: The timepoint at which the greatest number of genes were differentially expressed was ZT01 (FigureĀ 5A), at which 76% (N = 1612) of the genes showed geographic variation in expression, as compared to ZT13, ZT18 and ZT22, where respectively 23% (N = 491), 23% (N = 492), and 29% (N = 616) of the expressed genes showed geographic differences. In addition, 66% of the genes differentially expressed at ZT01 were not differentially expressed at other timepoints. The ZT01 timepoint is unique in several respects: (1) it is our only daytime timepoint, (2) it is a peak activity time, and (3) it corresponds to a transition time between night and day. Moreover, the fact our experimental lights turned on suddenly in the morning rather than ramping smoothly could have contributed to the strong expression differences observed at ZT01.Figure 5


Evidence that natural selection maintains genetic variation for sleep in Drosophila melanogaster.

Svetec N, Zhao L, Saelao P, Chiu JC, Begun DJ - BMC Evol. Biol. (2015)

A large fraction of the geographic variation in gene expression is circadian time specific. A) Venn Diagram showing the distribution across timepoints of the genes differentially expressed between PC and RI. B) Venn Diagram showing the distribution across timepoints of the genes differentially expressed and located into the 5% outlier FST windows. Actual number of genes is indicated in parenthesis.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4374177&req=5

Fig5: A large fraction of the geographic variation in gene expression is circadian time specific. A) Venn Diagram showing the distribution across timepoints of the genes differentially expressed between PC and RI. B) Venn Diagram showing the distribution across timepoints of the genes differentially expressed and located into the 5% outlier FST windows. Actual number of genes is indicated in parenthesis.
Mentions: The timepoint at which the greatest number of genes were differentially expressed was ZT01 (FigureĀ 5A), at which 76% (N = 1612) of the genes showed geographic variation in expression, as compared to ZT13, ZT18 and ZT22, where respectively 23% (N = 491), 23% (N = 492), and 29% (N = 616) of the expressed genes showed geographic differences. In addition, 66% of the genes differentially expressed at ZT01 were not differentially expressed at other timepoints. The ZT01 timepoint is unique in several respects: (1) it is our only daytime timepoint, (2) it is a peak activity time, and (3) it corresponds to a transition time between night and day. Moreover, the fact our experimental lights turned on suddenly in the morning rather than ramping smoothly could have contributed to the strong expression differences observed at ZT01.Figure 5

Bottom Line: We also found evidence for geographic variation for sunrise anticipation.Furthermore, the present study suggests that natural selection plays a major role in generating transcriptomic variation associated with circadian behaviors.Finally, we identified genomic variants plausibly causally associated with the observed behavioral and transcriptomic variation.

View Article: PubMed Central - PubMed

Affiliation: Department of Evolution and Ecology, University of California, 3352 Storer Hall, One Shields Ave., Davis, CA, 95618, USA. nhsvetec@ucdavis.edu.

ABSTRACT

Background: Drosophila melanogaster often shows correlations between latitude and phenotypic or genetic variation on different continents, which suggests local adaptation with respect to a heterogeneous environment. Previous phenotypic analyses of latitudinal clines have investigated mainly physiological, morphological, or life-history traits. Here, we studied latitudinal variation in sleep in D. melanogaster populations from North and Central America. In parallel, we used RNA-seq to identify interpopulation gene expression differences.

Results: We found that in D. melanogaster the average nighttime sleep bout duration exhibits a latitudinal cline such that sleep bouts of equatorial populations are roughly twice as long as those of temperate populations. Interestingly, this pattern of latitudinal variation is not observed for any daytime measure of activity or sleep. We also found evidence for geographic variation for sunrise anticipation. Our RNA-seq experiment carried out on heads from a low and high latitude population identified a large number of gene expression differences, most of which were time dependent. Differentially expressed genes were enriched in circadian regulated genes and enriched in genes potentially under spatially varying selection.

Conclusion: Our results are consistent with a mechanistic and selective decoupling of nighttime and daytime activity. Furthermore, the present study suggests that natural selection plays a major role in generating transcriptomic variation associated with circadian behaviors. Finally, we identified genomic variants plausibly causally associated with the observed behavioral and transcriptomic variation.

Show MeSH