Autosomal and maternal effects on pupation behavior inDrosophila melanogaster

Bauer, Sharon J.; Sokolowski, Marla B.

doi:10.1007/bf01067077

Cited by 26 publications

(24 citation statements)

References 23 publications

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“…As expected, Windsor, the more northern site, showed a higher percentage of flies in diapause than Wahisten, 1979;de Belle & Sokolowski, 1987;Bauer & Sokolowski, 1988). The latter two can be thought of as non-chromosomally inherited Wahlsten (1979) and Sokolowski (1992).…”

Section: Resultsmentioning

confidence: 68%

“…components. Transient maternal factors such as the action of the mother's genes on the zygote, affect only the F1 progeny whereas permanent cytoplasmic factors such as effects of mitochondrial genes can be passed on through the maternal parent from generation to generation (Wahlsten, 1979;Bauer & Sokolowski, 1988). V-chromosome effects could not be tested because the diapause response is a sex specific (female) response.…”

Section: Resultsmentioning

confidence: 99%

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Diapause in Drosophila melanogaster females: a genetic analysis

Williams

Sokolowski

1993

Heredity

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Female Drosophila melanogaster exhibit ovarian diapause at low temperatures and short day lengths. We found that D. melanogaster isofemale lines from Windsor (Ontario, Canada) had a significantly higher percentage of females in diapause than did those from Cartersville (Georgia, U.S.A.). To investigate the heredity of this trait, we performed a 16-reciprocal cross analysis using two extreme isofemale lines called W and C. We found that diapause in D. melanogaster is inherited as a simple autosomal recessive trait with the C response (less flies in diapause) completely dominant to the W one. Maternal and cytoplasmic factors did not affect differences in diapause in these lines. The result of our genetic analysis of diapause in D. melanogaster opens many avenues for the genetic dissection of this ecologically relevant trait.

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Section: Resultsmentioning

confidence: 68%

Section: Resultsmentioning

confidence: 99%

Diapause in Drosophila melanogaster females: a genetic analysis

Williams

Sokolowski

1993

Heredity

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“…The for gene does not have pleiotropic effects on these traits, although phenotypic correlations between larval path length and pupation behavior have been found in natural populations (51). Pupation height and larval feeding rate are polygenic characters influenced by many genes with additive effects on the major autosomes in D. melanogaster (23,(52)(53)(54)(55). From the perspective of larval fitness, feeding and moving are two of the most important behaviors performed in the larval period.…”

Section: Discussionmentioning

confidence: 99%

Evolution of foraging behavior inDrosophilaby density-dependent selection

Sokolowski

Pereira²,

Hughes³

1997

Proc. Natl. Acad. Sci. U.S.A.

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212

166

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One of the rare examples of a single major gene underlying a naturally occurring behavioral polymorphism is the foraging locus of Drosophila melanogaster. Larvae with the rover allele, for R , have significantly longer foraging path lengths on a yeast paste than do those homozygous for the sitter allele, for s . These variants do not differ in general activity in the absence of food. The evolutionary significance of this polymorphism is not as yet understood. Here we examine the effect of high and low animal rearing densities on the larval foraging path-length phenotype and show that density-dependent natural selection produces changes in this trait. In three unrelated base populations the long path (rover) phenotype was selected for under high-density rearing conditions, whereas the short path (sitter) phenotype was selected for under low-density conditions. Genetic crosses suggested that these changes resulted from alterations in the frequency of the for s allele in the low-density-selected lines. Further experiments showed that density-dependent selection during the larval stage rather than the adult stage of development was sufficient to explain these results. Densitydependent mechanisms may be sufficient to maintain variation in rover and sitter behavior in laboratory populations.Studies of population dynamics have for the most part mistakenly considered the behavior of organisms within a population to be homogeneous (1). However, individual differences in behavior are common and have consequences for the ecology and evolution of populations. A special case of individual differences is behavioral polymorphism, where individuals within a population can be categorized into morphs (phenotypes or strategists) according to their behavior(s). When the polymorphism has a heritable component, the relative selective advantages of the morphs under different environmental conditions can be measured (2). One condition, population density, varies over time and space and plays a significant role in the evolution of characteristics within populations (3). Population density affects a number of processes, for example, predator-prey (4) and parasite-host interactions (5), the spread of disease (6), competition (7), population regulation (8), and territoriality (9). There have been many theoretical studies of density-dependent selection, including those that model its effect on competitive ability (10-13). However, empirical studies that address whether behavioral polymorphisms affect fitness in a density-dependent manner are rare. The fruit fly Drosophila melanogaster is one of the few systems in which we are beginning to have a detailed empirical understanding of density-dependent selection (14-22). It is an ideal model system to study how a genetically characterized polymorphism in behavior responds to density-dependent selection.The rover͞sitter polymorphism in D. melanogaster is a model system that has been used to address both the mechanistic and evolutionary significance of behavioral phenotypes. The locomotio...

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“…For example, reciprocal crossbreeding of animals can be used to demonstrate maternal environment effects on rate of development (Wainwright, 1980 ), behavior (Bauer & Sokolowski, 1988) or brain size (Wahlsten,1983), and they may also reveal the importance of the cell cytoplasm for individual differences in brain structure (Wimer & Wimer, 1989). One logical method of analyzing such data is a series of orthogonal contrasts.…”

Section: Finding the Sample Size For A Linear Contrastmentioning

confidence: 99%

Sample size to detect a planned contrast and a one degree-of-freedom interaction effect.

Wahłsten¹

1991

Psychological Bulletin

116

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size to detect a planned contrast and a one degree-of-freedom interaction effect. Psychological Bulletin, 1991, 110, 587-595. Made available courtesy of the American Psychological Association: http://www.apa.org/ *** Note: This article may not exactly replicate the final version published in the APA journal. It is not the copy of record Abstract:A simple method is described for estimating the sample size per group required for specified power to detect a linear contrast among J group means. This allows comparison of sample sizes to detect main effects with those needed to detect several realistic kinds of interaction in 2 × 2 and 2 × 2 × 2 designs with a fixed-effects model. For example, when 2 factors are multiplicative, the sample size required to detect the presence of nonadditivity is 7 to 9 times as large as that needed to detect main effects with the same degree of power. In certain other situations, effect sizes for the main effects and interaction may be identical, in which case power and necessary sample sizes to detect the effects will be the same. The method can also be used to find sample size for a complex contrast in a nonfactorial design. Article:The power of the analysis of variance ( ANOVA) to detect statistical interaction in a factorial experiment is substantially less than the power to detect main effects in many situations (Neyman, 1935;Rodger, 1974;Traxler, 1976;Wahlsten, 1990). For example, with a 2 × 2 design, power to detect the multiplicative type of interaction is 16% when power to detect a main effect is 87% (Wahlsten, 1990); hence the ANOVA will frequently point to additivity of effects when in fact they are multiplicative. This is not a universal property of the ANOVA method, however. As shown in this article, the degree of the discrepancy in power depends strongly on the specific kind of interaction that is present in the data. The power function depends on the size of an effect and the degrees of freedom. If two effects have the same size and degrees of freedom, power must necessarily be the same.If the presence or absence of interaction is important for a theory it is imperative that the test of interaction have a power of 80% or, preferably, 90%. This sometimes requires larger samples than are customarily used to detect main effects with ANOVA. But how much larger must they be? Relative sample sizes may give a better impression of the insensitivity of ANOVA to interaction than do relative power values. The power to detect a particular kind of interaction may be half the power to detect a main effect in that circumstance, yet the sample size needed to detect the interaction may be far more than double the sample size needed to detect the main effect with the same degree of power. This larger sample size provides a direct indicator of the additional research subjects, technician time, and grant funds required for the desired sensitivity of the statistical test.This article presents a convenient way to determine appropriate sample sizes for factorial designs in which there are t...

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Autosomal and maternal effects on pupation behavior inDrosophila melanogaster

Cited by 26 publications

References 23 publications

Diapause in Drosophila melanogaster females: a genetic analysis

Diapause in Drosophila melanogaster females: a genetic analysis

Evolution of foraging behavior inDrosophilaby density-dependent selection

Sample size to detect a planned contrast and a one degree-of-freedom interaction effect.

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