FlyAtlas 2 in 2022: enhancements to the Drosophila melanogaster expression atlas.

FlyAtlas 2 (flyatlas2.org) is a database and web application for studying the expression of the genes of Drosophila melanogaster in different tissues of adults and larvae. It is based on RNA-Seq data, and incorporates both genes encoding proteins and microRNAs. We have now completed the population of the database with 13 tissues from both male and female adults, five sex-specific tissues, and eight larval tissues. Larval garland cell nephrocytes have also been included. Major enhancements have been made to the application. First, a facility has been added for a 'Profile' search for genes with a similar pattern of tissue expression as a query gene. This may help establish the function of genes for which this is currently unknown. Second, a facility has been added dedicated to the larval midgut, where the difference in gene expression in the five regions of different pH can be explored. A variety of further improvements to the interface are described.

FlyAtlas 2: a new version of the Drosophila melanogaster expression atlas with RNA-Seq, miRNA-Seq and sex-specific data.

FlyAtlas 2 (www.flyatlas2.org) is part successor, part complement to the FlyAtlas database and web application for studying the expression of the genes of Drosophila melanogaster in different tissues of adults and larvae. Although generated in the same lab with the same fly line raised on the same diet as FlyAtlas, the FlyAtlas2 resource employs a completely new set of expression data based on RNA-Seq, rather than microarray analysis, and so it allows the user to obtain information for the expression of different transcripts of a gene. Furthermore, the data for somatic tissues are now available for both male and female adult flies, allowing studies of sexual dimorphism. Gene coverage has been extended by the inclusion of microRNAs and many of the RNA genes included in Release 6 of the Drosophila reference genome. The web interface has been modified to accommodate the extra data, but at the same time has been adapted for viewing on small mobile devices. Users also have access to the RNA-Seq reads displayed alongside the annotated Drosophila genome in the (external) UCSC browser, and are able to link out to the previous FlyAtlas resource to compare the data obtained by RNA-Seq with that obtained using microarrays.

Synthetic genetic interactions allele dependence, uses, and conservation.

Genetic interactions occur between a pair of genes when the phenotype of the double mutant leads to an unexpected phenotype, one that is not predicted from the phenotypes of the single mutants alone. Here, we focus on genetic enhancements, otherwise known as synthetic genetic interactions, where the double mutant phenotype is more severe than expected. Such interactions are rife in natural populations and underlie complex traits, variable penetrance, variable expressivity, and genetic predisposition. Such interactions can also contribute valuable information for functional genomics analysis. Pairwise synthetic genetic interactions are now being systematically uncovered for some simple model genomes. These data are affording us an unparalleled opportunity to examine, understand and exploit genetic enhancements. Here we focus on some key lessons, insights, and confusions arising from these large-scale datasets. We consider if genome-wide datasets support traditional assumptions about the functional relationships between gene products that underlie genetic enhancements. We argue that the genetic enhancement network of an organism is not uniform in nature and is highly dependent on the nature of the interacting alleles. We consider how such genetic networks can be exploited to inform gene product function. Finally, we consider the extent to which genetic enhancement networks are conserved between species.

The functional relationships underlying a synthetic genetic network.

Here, we focus on synthetic lethal genetic interactions, examples of genetic enhancements, where mutations in two different genes result in lethality but only when present together. We recently identified the synthetic lethal network around the PKC1 gene encoding the essential protein kinase C of yeast. We found that this network is heavily enriched for interactions with genes whose products are closely linked to Pkc1 signaling in vivo. Here, we show that: the PKC1 gene elicits a distinct spectrum of genetic interactions to SLT2, encoding a non-essential component of the very same signaling pathway. We also show that the terminal phenotype underlying the synthetic lethal network around PKC1 is not uniform. Synthetic lethal genetic networks thus appear to be very heterogeneous in nature with important implications for what functional relationships can be discovered from them.

The synthetic genetic network around PKC1 identifies novel modulators and components of protein kinase C signaling in Saccharomyces cerevisiae.

Budding yeast Saccharomyces cerevisiae contains one protein kinase C (PKC) isozyme encoded by the essential gene PKC1. Pkc1 is activated by the small GTPase Rho1 and plays a central role in the cell wall integrity (CWI) signaling pathway. This pathway acts primarily to remodel the cell surface throughout the normal life cycle and upon various environmental stresses. The pathway is heavily branched, with multiple nonessential branches feeding into and out of the central essential Rho1-Pkc1 module. In an attempt to identify novel components and modifiers of CWI signaling, we determined the synthetic lethal genetic network around PKC1 by using dominant-negative synthetic genetic array analysis. The resulting mutants are hypersensitive to lowered Pkc1 activity. The corresponding 21 nonessential genes are closely related to CWI function: 14 behave in a chemical-genetic epistasis test as acting in the pathway, and 6 of these genes encode known components. Twelve of the 21 null mutants display elevated CWI reporter activity, consistent with the idea that the pathway is activated by and compensates for loss of the gene products. Four of the 21 mutants display low CWI reporter activity, consistent with the idea that the pathway is compromised in these mutants. One of the latter group of mutants lacks Ack1(Ydl203c), an uncharacterized SEL-1 domain-containing protein that we find modulates pathway activity. Epistasis analysis places Ack1 upstream of Pkc1 in the CWI pathway and dependent on the upstream Rho1 GTP exchange factors Rom2 and Tus1. Overall, the synthetic genetic network around PKC1 directly and efficiently identifies known and novel components of PKC signaling in yeast.

Invadolysin: a novel, conserved metalloprotease links mitotic structural rearrangements with cell migration.

The cell cycle is widely known to be regulated by networks of phosphorylation and ubiquitin-directed proteolysis. Here, we describe IX-14/invadolysin, a novel metalloprotease present only in metazoa, whose activity appears to be essential for mitotic progression. Mitotic neuroblasts of Drosophila melanogaster IX-14 mutant larvae exhibit increased levels of nuclear envelope proteins, monopolar and asymmetric spindles, and chromosomes that appear hypercondensed in length with a surrounding halo of loosely condensed chromatin. Zymography reveals that a protease activity, present in wild-type larval brains, is missing from homozygous tissue, and we show that IX-14/invadolysin cleaves lamin in vitro. The IX-14/invadolysin protein is predominantly found in cytoplasmic structures resembling invadopodia in fly and human cells, but is dramatically relocalized to the leading edge of migrating cells. Strikingly, we find that the directed migration of germ cells is affected in Drosophila IX-14 mutant embryos. Thus, invadolysin identifies a new family of conserved metalloproteases whose activity appears to be essential for the coordination of mitotic progression, but which also plays an unexpected role in cell migration.