Selection, Gene Interaction, and Flexible Gene Networks

Downloaded from symposium.cshlp.org on November 11, 2009 - Published by Cold Spring Harbor Laboratory Press Selection, Gene Interaction, and Flexible Gene Networks R.J. GREENSPAN The Neurosciences Institute, San Diego, California 92121 and The Kavli Institute for Brain and Mind, University of California at San Diego, La Jolla, California 92093-0526 Correspondence: [email protected] Recent results from a variety of different kinds of experiments, mainly using behavior as an assay, and ranging from laboratory selection experiments to gene interaction studies, show that a much wider range of genes can affect phenotype than those identified as “core genes” in classical mutant screens. Moreover, very pleiotropic genes can produce specific phenotypes when mild variants are combined. These studies also show that gene networks readily change configuration and the relation- ships between interacting genes in response to the introduction of additional genetic variants, suggesting that the networks range widely and have a high degree of flexibility and malleability. Such flexibility, in turn, offers a plausible mechanism for the molding of phenotypes through microevolution, as a prerequisite to making a suitable environment for the acceptance of newly arising large-effect mutations in the transition from microevolution to macroevolution. The concept of single-gene mutant analysis to study the can (and do) affect phenotype than those normally consid- mechanisms of behavior is now so deeply embedded as an ered to be core genes. Such findings have some interesting analytical approach that its history of being challenged implications for the molding of phenotypes through seems unimaginable. This is the legacy of Seymour Ben - microevolution, as well as for ways of thinking about the zer’s foray into the behavior of the fruit fly 40 years ago. But transition from microevolution to macroevolution. They challenged it was, and from very divergent sources, includ- may also require us to modify our picture of how molecular ing traditional neurobiologists (see, e.g., Hoyle 1974; pathways affect phenotypes. Purves and Lichtman 1985) and a former molecular biolo- gist (Stent 1982). A third challenge came from quantitative DISCREPANT GENES behavior genetics and pitted the two founders of Drosophila behavior genetics, Jerry Hirsch and Seymour Benzer, Following in Hirsch’s footsteps, selection has been against each other over the issue of natural versus induced conducted on a variety of Drosophila behaviors since his variants. In the late 1960s, when Benzer began his program inaugural work in the late 1950s (for review, see Green - of inducing mutants affecting behavior, Hirsch had already span 2004a). With the advent of microarray technology, been performing selection experiments to produce heritable several recent selection experiments have been subjected behavioral differences in fruit flies for nearly 10 years to gene expression profiling as a way of characterizing (Greenspan 2008). Hirsch’s objection was that the induced molecular differences between selected and unselected mutants coming out of Benzer’s screens were unnatural, (or divergently selected) phenotypes. would never survive in the wild, and therefore gave a mis- The genes so identified are mixed with respect to their leading picture. From Benzer’s point of view, the inability direct relationship to the selected phenotype. Some of the to identify, let alone analyze, the genes underlying Hirsch’s expression differences may actually be in the relevant selected phenotypes rendered that whole program useless. polymorphisms, others surely are not. Expression level In one sense, the conflict was moot because each side had differences have been previously shown to underlie many a different goal. Hirsch’s goal was to understand genetic mutant effects on behavior (Greenspan 1997) including architecture and the sources of natural phenotypic variation, natural variants (Osborne et al. 1997). In cases where the and Benzer’s was to understand mechanism in what has expression differences are not in the actual polymorphic become the dominant molecular paradigm of explaining genes, some may nonetheless be the consequences of biological processes in terms of core genetic mech anisms such differences, e.g., downstream targets of transcription that function in pathway-like fashion (Greenspan 2001). factors, and may thus take us one step closer to the actual But the issue of reconciling natural variation affecting a basis for the phenotypic effect. A gene’s role can some- phenotype with induced mutants has surfaced again as the times be confirmed if it is capable of exerting an isolated advancing molecular armamentarium has made possible the effect on the phenotype, as shown in tests of independ- identification and analysis of both kinds of variants. Recent ently isolated mutants (see below). Of course, there will studies on the molecular basis of selected phenotypes raise be cases where the expression differences are phenotypi- some puzzling questions about the relationship between cally irrelevant and simply reflect hitchhiking variants natural and induced variants. A separate set of studies on that are linked to the selected loci. And finally, there will gene interaction shows that a much wider range of genes certainly be relevant allelic differences that are missed by Cold Spring Harbor Symposia on Quantitative Biology, Volume LXXIV. © 2009 Cold Spring Harbor Laboratory Press 978-087969870-6 1 Downloaded from symposium.cshlp.org on November 11, 2009 - Published by Cold Spring Harbor Laboratory Press 2 GREENSPAN this technology due to the fact that they are not caused by Expression profiles were done on wing disc tissue dis- expression level differences or that they are so spatially sected from these strains. The magnitude of the differ- restricted that their magnitude would not stand out against ences was somewhat higher than in the shorter-term the background of activity elsewhere. Despite all of these selection experiments, with many more of them exceed- caveats, expression profiles provide a rough sketch of the ing twofold (Weber et al. 2008). Much more striking, differences underlying selection effects. however, is the continued lack of overlap between these Most laboratory selection experiments with Drosophila differentially expressed genes and any of the more than are short term and performed on small populations, on the 200 genes identified over the years as affecting wing order of 20–30 generations selecting the top ~10% of a pop- development (Brody 1999). Any concern from the earlier ulation of ~200 (Greenspan 2004a). Expression profiles analyses that the phenotypes may have been undersam- have been done on RNA extracted from fly heads (mostly pled in the mutagenesis studies is adequately allayed here. brain) of D. melanogaster strains differentially selected for The final example of a selection experiment subjected mating speed (Mackay et al. 2005), aggression (Fig. 1) (see to expression analysis is perhaps the record holder for Dierick and Greenspan 2006; Edwards et al. 2006), and long-term laboratory selection in a metazoan. The indoor locomotor activity (Jordan et al. 2007). All have yielded a record for selection in any organism is 10,000 generations bewilderingly wide range of genes, as is common with for Escherichia coli (Lenski and Travisano 1994), but in microarray results. Two notable attributes are shared by all 1958, Jerry Hirsch began selecting Drosophila for diver- of these studies. First, the expression differences found for gence in geotaxis behavior and continued doing so for those genes significantly differing between strains are rela- more than 600 generations until the lines stabilized spon- tively small, almost all less than twofold in magnitude. One taneously in 1983 (Fig. 3, left) (see Hirsch 1959; Ricker might attribute this feature to the likelihood that most natu- and Hirsch 1985). When tested again in 2000, they still ral variants are relatively mild. The second feature is the lack displayed the appropriate phenotypic difference (Fig. 3, of any overlap between these genes and any that had previ- right) (see Toma et al. 2002). ously been identified through classical, Benzerian mutant Gene expression profiles were obtained for RNA from analysis (Hall 1982, 1994a; Kyriacou and Hall 1994; heads of the divergent strains, and, as usual, many genes Wilson et al. 2008). This is all the more surprising given the differed. The magnitude of expression difference in these number and range of genes that differ in these experiments. flies was considerably greater than that in any of the pre- The question of how well expression analysis identifies the vious examples, with many showing fourfold to eightfold pertinent genes is addressed below. differences and a few even higher (Toma et al. 2002). And Few selection experiments, behavioral or otherwise, go as in the earlier examples, the differing genes showed no on for more than 30 generations, and very few of these overlap with any of the genes identified previously as have been analyzed molecularly. One of the rarities is a geotaxis mutants (Armstrong et al. 2006). medium-term selection experiment for divergence in wing Two trends stand out from this admittedly small set of morphology that was conducted during a time frame more examples. First, none of the genes match those found in than twice as long as usual. An initial 20 generations of standard mutant searches, and second, the magnitude of the selection produced divergence

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