Summary Learning and memory formation in Drosophila rely on a network of neurons in the mushroom bodies (MB). While numerous studies have delineated roles for individual cell types within this network in aspects of learning or memory, whether or not these cells can also be distinguished by the genes they express remains unresolved. In addition, the changes in gene expression that accompany long-term memory formation within the MBs have not yet been studied by neuron type. Here we address both issues by performing RNA sequencing on single cell types (harvested via patch pipets) within the MB. We discover that the expression of genes that encode cell surface receptors is sufficient to identify cell types, and that a subset of these genes, required for sensory transduction in peripheral sensory neurons, are not only expressed within individual neurons of the MB in the central brain, but are also critical for memory formation.

Summary Brains are optimized for processing ethologically relevant sensory signals. However, few studies have characterized the neural coding mechanisms that underlie the transformation from natural sensory information to behavior. Here, we focus on acoustic communication in Drosophila melanogaster, and use computational modeling to link natural courtship song, neuronal codes, and female behavioral responses to song. We show that melanogaster females are sensitive to long timescale song structure (on the order of tens of seconds). From intracellular recordings, we generate models that recapitulate neural responses to acoustic stimuli. We link these neural codes with female behavior by generating model neural responses to natural courtship song. Using a simple decoder, we predict female behavioral responses to the same song stimuli with high accuracy. Our modeling approach reveals how long timescale song features are represented by the Drosophila brain, and how neural representations can be decoded to generate behavioral selectivity for acoustic communication signals.

We demonstrate a time-lapse video approach that allows rapid examination of the spatio-temporal dynamics of Dictyostelium cell populations. Quantitative information was gathered by sampling life histories of more than 2,000 mutant clones from a large mutagenesis collection. Approximately 4% of the clonal lines showed a mutant phenotype at one stage. Many of these could be ordered by clustering into functional groups. The dataset allows one to search and retrieve movies on a geneby-gene and phenotype-by-phenotype basis.

To increase our understanding of imprinting and epigenetic gene regulation, we undertook a search for new imprinted genes. We identified Gatm, a gene that encodes L-arginine:glycine amidinotransferase, which catalyzes the rate-limiting step in the synthesis of creatine. In mouse, Gatm is expressed during development and is imprinted in the placenta and yolk sac, but not in embryonic tissues. The Gatm gene maps to mouse chromosome 2 in a region not previously shown to contain imprinted genes. To determine whether Gatm is located in a cluster of imprinted genes, we investigated the expression pattern of genes located near Gatm: Duox1-2, Slc28a2, Slc30a4 and a transcript corresponding to LOC214616. We found no evidence that any of these genes is imprinted in placenta. We show that a CpG island associated with Gatm is unmethylated, as is a large CpG island associated with a neighboring gene. This genomic screen for novel imprinted genes has elucidated a new connection between imprinting and creatine metabolism during embryonic development in mammals.