Resources for functional studies in Drosophila

果蝇功能研究资源

• 批准号: 10332199
• 负责人: NORBERT PERRIMON
• 金额: $ 54.5万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10332199
• 关键词: Address; Adult; Algorithms; Anatomy; Antibodies; Atlases; Brain; Cells; Collection; Communities; DNA Binding Domain; Data; Data Analyses; Data Set; Detection; Development; Drosophila genus; Engineering; Enhancers; Funding Opportunities; Gene Combinations; Gene Expression; Gene Expression Profile; Gene Proteins; Generations; Genes; Genomics; In Situ Hybridization; Institutes; Knowledge; Larva; Letters; Maps; Methods; Molecular Profiling; Monoclonal Antibody R24; Nucleic Acid Regulatory Sequences; Organ; Output; Pattern; Phenotype; Proteins; Proxy; Reagent; Reporter; Research Personnel; Research Project Grants; Resources; Sampling; Specificity; System; Technology; Testing; Time; Tissues; Transcription Coactivator; Transgenes; United States National Institutes of Health; Validation; animal model development; base; body map; cell type; cooking; differential expression; experimental study; fly; human disease; human model; prevent; response; single-cell RNA sequencing; tool

PROJECT SUMMARY / ABSTRACT Recent knowledge gained from studies based on scRNAseq provides new opportunities for the characterization of cell types and description of phenotypes. In addition, information gained from scRNAseq can help develop new reagents useful for functional studies. One of the main challenges in scRNAseq studies to address is the mapping of scRNAseq clusters to anatomy. While this can be relatively easily done if a cluster is defined by the unique expression of a single differentially expressed gene (DEG), the task is more complicated if a group of cells can only be defined using a combination of DEGs. To identify combinations of genes whose expression define cell clusters, we propose in Aim 1 to develop an algorithm that determines the smallest unique set of marker genes that define a cluster. A number of approaches and resources can be used to associate the expression of marker genes to the anatomy; however, in most cases co-expression of multiple genes is required to properly map clusters to the anatomy, and existing reagents are limited. As the split-Gal4 method, whereby the DNA-binding domain of Gal4 and a transcriptional activator domain are expressed independently under the control of two different enhancers, is scalable for the detection of multiple genes, in Aim 2, we propose to build on our established TRiP/DRSC platform and generate a collection of 1012 split-Gal4 lines that will be used to map the estimated 450 cell clusters present in the fly. Importantly, the split-Gal4 lines generated from these studies will allow us to address a long-standing issue in the Drosophila field, namely the specificity of existing Gal4 lines, as we and others have observed that the large majority of so-called “tissue-specific” Gal4 driver lines are also expressed in additional, unwanted cell types or tissues. Finally, as the current split-Gal4 system is not compatible with temporal control, preventing the use of split-Gal4 lines for experiments requiring stage specific activation of the UAS driven transgene, in Aim 3, we will develop a robust split-Gal4 method that allows temporal control and generate a collection of 200 inducible split-Gal4 lines that will allow the generation of 100 controllable tissue specific Gal4 patterns, covering most larval and adult tissues. Together, these resources will provide the community with much needed reagents that will be made available and distributed as soon as they are produced by the Bloomington Drosophila Stock Center.

项目摘要/摘要