A Zika virus protein expression screen in Drosophila to investigate targeted host pathways during development.

In the past decade, Zika virus (ZIKV) emerged as a global public health concern. Although adult infections are typically mild, maternal infection can lead to adverse fetal outcomes. Understanding how ZIKV proteins disrupt development can provide insights into the molecular mechanisms of disease caused by this virus, which includes microcephaly. In this study, we generated a toolkit to ectopically express ZIKV proteins in vivo in Drosophila melanogaster in a tissue-specific manner using the GAL4/UAS system. We used this toolkit to identify phenotypes and potential host pathways targeted by the virus. Our work identified that expression of most ZIKV proteins caused scorable phenotypes, such as overall lethality, gross morphological defects, reduced brain size and neuronal function defects. We further used this system to identify strain-dependent phenotypes that may have contributed to the increased pathogenesis associated with the outbreak of ZIKV in the Americas in 2015. Our work demonstrates the use of Drosophila as an efficient in vivo model to rapidly decipher how pathogens cause disease and lays the groundwork for further molecular study of ZIKV pathogenesis in flies.

A Zika virus protein expression screen in Drosophila to investigate targeted host pathways during development.

In the past decade, Zika virus (ZIKV) emerged as a global public health concern. While adult infections are typically mild, maternal infection can lead to adverse fetal outcomes. Understanding how ZIKV proteins disrupt development can provide insights into the molecular mechanisms of symptoms caused by this virus including microcephaly. In this study, we generated a toolkit to ectopically express Zika viral proteins in vivo in Drosophila melanogaster in a tissue-specific manner using the GAL4/UAS system. We use this toolkit to identify phenotypes and host pathways targeted by the virus. Our work identified that expression of most ZIKV proteins cause scorable phenotypes, such as overall lethality, gross morphological defects, reduced brain size, and neuronal function defects. We further use this system to identify strain-dependent phenotypes that may contribute to the increased pathogenesis associated with the more recent outbreak of ZIKV in the Americas. Our work demonstrates Drosophila's use as an efficient in vivo model to rapidly decipher how pathogens cause disease and lays the groundwork for further molecular study of ZIKV pathogenesis in flies.

MaizeGDB 2018: the maize multi-genome genetics and genomics database.

Since its 2015 update, MaizeGDB, the Maize Genetics and Genomics database, has expanded to support the sequenced genomes of many maize inbred lines in addition to the B73 reference genome assembly. Curation and development efforts have targeted high quality datasets and tools to support maize trait analysis, germplasm analysis, genetic studies, and breeding. MaizeGDB hosts a wide range of data including recent support of new data types including genome metadata, RNA-seq, proteomics, synteny, and large-scale diversity. To improve access and visualization of data types several new tools have been implemented to: access large-scale maize diversity data (SNPversity), download and compare gene expression data (qTeller), visualize pedigree data (Pedigree Viewer), link genes with phenotype images (MaizeDIG), and enable flexible user-specified queries to the MaizeGDB database (MaizeMine). MaizeGDB also continues to be the community hub for maize research, coordinating activities and providing technical support to the maize research community. Here we report the changes MaizeGDB has made within the last three years to keep pace with recent software and research advances, as well as the pan-genomic landscape that cheaper and better sequencing technologies have made possible. MaizeGDB is accessible online at https://www.maizegdb.org.