13 research outputs found

    Reproductive Capacity Evolves in Response to Ecology through Common Changes in Cell Number in Hawaiian Drosophila

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    © 2019 Elsevier Ltd Lifetime reproductive capacity is a critical fitness component. In insects, female reproductive capacity is largely determined by the number of ovarioles, the egg-producing subunits of the ovary [e.g., 1]. Recent work has provided insights into ovariole number regulation in Drosophila melanogaster. However, whether mechanisms discovered under laboratory conditions explain evolutionary variation in natural populations is an outstanding question. We investigated potential effects of ecology on the developmental processes underlying ovariole number evolution among Hawaiian Drosophila, a large adaptive radiation wherein the highest and lowest ovariole numbers of the family have evolved within 25 million years. Previous studies proposed that ovariole number correlated with oviposition substrate [2–4] but sampled largely one clade of these flies and were limited by a provisional phylogeny and the available comparative methods. We test this hypothesis by applying phylogenetic modeling to an expanded sampling of ovariole numbers and substrate types and show support for these predictions across all major groups of Hawaiian Drosophila, wherein ovariole number variation is best explained by adaptation to specific substrates. Furthermore, we show that oviposition substrate evolution is linked to changes in the allometric relationship between body size and ovariole number. Finally, we provide evidence that the major changes in ovarian cell number that regulate D. melanogaster ovariole number also regulate ovariole number in Hawaiian drosophilids. Thus, we provide evidence that this remarkable adaptive radiation is linked to evolutionary changes in a key reproductive trait regulated at least partly by variation in the same developmental parameters that operate in the model species D. melanogaster. Organisms leaving more offspring likely have higher fitness. Sarikaya et al. use the adaptive radiation of Hawaiian Drosophila to investigate the evolution of fecundity. They find that habitat shifts played a strong role and identify a developmental process that underlies evolutionary change in ovarian development and impacts egg-laying capacity

    Altering Hippo pathway activity in somatic cells changes IC and GC number.

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    <p>Changes in (A) IC or (B) GC number in ovaries expressing <i>hpo</i>, <i>wts</i> or <i>yki</i> RNAi, or overexpressing <i>hpo</i> or <i>yki</i> under the <i>bab</i>:<i>GAL4</i> or <i>tj</i>:<i>GAL4</i> drivers. Bar graphs are as explained in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.g002" target="_blank">Fig. 2</a> legend. ** <i>p</i><0.01, * <i>p</i><0.05, + <i>p</i> = 0.05 against the UAS parental line and <i>p</i><0.05 against the GAL4 parental line. n = 10 for each genotype. Numerical values can be found in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.s011" target="_blank">S3 Table</a>. (C) Pie charts of proportions of ICs (green) and GCs (yellow) in ovaries under indicated selected experimental conditions. * <i>p</i><0.05. Numerical values can be found in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.s014" target="_blank">S6 Table</a>; pie charts for all experimental conditions shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.s007" target="_blank">S7 Fig.</a> (D–N) LP stage larval ovaries representative of control and experimental samples used to obtain cell type counts. Scale bar = 10 μm.</p

    The Hippo pathway regulates coordinated growth of the soma and germ line.

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    <p>(A) Summary of changes in TFC, IC and GC numbers when expression of genes from various growth pathways were altered in our study and two other studies [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.ref006" target="_blank">6</a>,<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.ref049" target="_blank">49</a>]. Black triangles indicate significant increase; white triangles indicate significant decrease; = indicate no significant change. (B) Model of how Hippo pathway influences coordinated proliferation of somatic cells and germ cells in the larval ovary. Contributions of the present study are indicated in blue; elements of the model derived from other studies [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.ref006" target="_blank">6</a>,<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.ref049" target="_blank">49</a>] are indicated in black. The Hippo pathway interacts with JAK/STAT to regulate proliferation of TFCs, and interacts with EGFR and JAK/STAT pathways to regulate autonomous proliferation of ICs and non-autonomous proliferation of GCs. In addition, <i>yki</i> acts independently of <i>hpo</i> to influence proliferation of GCs in a non-canonical manner. (C) Summary of representative IC (green)/GC (yellow) proportions observed in our experiments, further elaborated in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.s007" target="_blank">S7 Fig</a>. Proportions of ICs and GCs are similar to controls when we knock down <i>hpo</i> or <i>wts</i> alone in the soma, but disrupting both <i>hpo</i> and EGFR or JAK/STAT pathway members leads to loss of proportional growth. Asterisk denotes <i>p</i><0.05. See <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.s014" target="_blank">S6 Table</a> for numerical values.</p

    The Hippo pathway interacts with the EGFR pathway to regulate IC and GC growth.

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    <p>(A) Expression pattern of EGFR pathway activity marker pMAPK in wild type L3 ovary. Expression is mainly in posterior IC cells. Scale bar = 10 μm and applies also to A’. (B) pMAPK expression in ovary expressing <i>UAS</i>:<i>hpo</i><sup><i>RNAi</i></sup> in the soma, exposed at same laser setting as (A). Scale bar = 10 μm and applies also to B’. (C) Relative intensity of anti-pMAPK fluorescence in wild type compared to <i>hpo</i> knockdown experimental (n = 8). Overall expression level of pMAPK is higher than controls, most prominently in the ICs. (D–E) Percent difference in TF (red), IC (green), and GC (yellow) number in double RNAi (<i>hpo</i> and <i>egfr</i>, or <i>hpo</i> and <i>spi</i>) compared to <i>hpo</i> single RNAi sibling controls (D), and wild type sibling controls (E). * <i>p</i><0.05, ** <i>p</i><0.01. Numerical values can be found in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.s012" target="_blank">S4 Table</a>. (F) Pie charts showing proportions of ICs (green) and GCs (yellow) under indicated selected experimental conditions. * <i>p</i><0.05, see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.s014" target="_blank">S6 Table</a> for numerical values; pie charts for all experimental conditions shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.s007" target="_blank">S7 Fig</a>.</p

    Yorkie activity regulates GC number.

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    <p>Changes in (A) GC number in ovaries expressing <i>hpo</i>, <i>wts</i>, <i>ex</i>, <i>hpo/wts/ex</i> triple, <i>hipk</i>, <i>yki or sd</i> RNAi, or overexpressing <i>hpo</i>, <i>yki or yki</i><sup><i>S168A</i></sup> under the <i>nos</i>:<i>GAL4</i> driver. Bar graphs are as explained in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.g002" target="_blank">Fig. 2</a> legend. * <i>p</i><0.05, ** <i>p</i><0.01 against controls. n = 10 for each genotype. Numerical values can be found in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004962#pgen.1004962.s010" target="_blank">S2 Table</a>. (B–E) LP stage larval ovaries representative of control and experimental samples used to obtain cell type counts. Scale bar = 10 μm. (F) Ratio of size (number of cells per clone) of homozygous mutant versus homozygous wild type twin spot clones for control (<i>w</i><sup><i>un-1</i></sup>), <i>hpo</i><sup><i>BF33</i></sup> and <i>yki</i><sup><i>B5</i></sup> alleles. ** <i>p</i><0.01 against control. (G–I) LP stage larval ovaries representative of control and experimental samples for clonal analysis showing GCs (Vasa, red), homozygous wild type clones (strong GFP expression; yellow arrowhead), and clones homozygous for tested alleles (no GFP; white arrowhead). n = 10 for each genotype.</p

    Phenotypic coupling of sleep and starvation resistance evolves in D. melanogaster

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    Abstract Background One hypothesis for the function of sleep is that it serves as a mechanism to conserve energy. Recent studies have suggested that increased sleep can be an adaptive mechanism to improve survival under food deprivation in Drosophila melanogaster. To test the generality of this hypothesis, we compared sleep and its plastic response to starvation in a temperate and tropical population of Drosophila melanogaster. Results We found that flies from the temperate population were more starvation resistant, and hypothesized that they would engage in behaviors that are considered to conserve energy, including increased sleep and reduced movement. Surprisingly, temperate flies slept less and moved more when they were awake compared to tropical flies, both under fed and starved conditions, therefore sleep did not correlate with population-level differences in starvation resistance. In contrast, total sleep and percent change in sleep when starved were strongly positively correlated with starvation resistance within the tropical population, but not within the temperate population. Thus, we observe unexpectedly complex relationships between starvation and sleep that vary both within and across populations. These observations falsify the simple hypothesis of a straightforward relationship between sleep and energy conservation. We also tested the hypothesis that starvation is correlated with metabolic phenotypes by investigating stored lipid and carbohydrate levels, and found that stored metabolites partially contributed towards variation starvation resistance. Conclusions Our findings demonstrate that the function of sleep under starvation can rapidly evolve on short timescales and raise new questions about the physiological correlates of sleep and the extent to which variation in sleep is shaped by natural selection
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