Programmable RNA-targeting tools
Programmable RNA-targeting tools
批准号:
9379750
负责人:
Feng Zhang
金额:
$109.57万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-08-17 至 2021-06-30
关键词:
AddressAffectAreaBindingBiochemicalBiologicalBrainCell physiologyCellsChromatinClustered Regularly Interspaced Short Palindromic RepeatsCodeComplementComplexDNADNA sequencingDataDevelopmentDiseaseDissectionElongation FactorEngineeringEnzymesEpigenetic ProcessEssential GenesEukaryotic CellEventFoundationsGene ExpressionGene SilencingGene TargetingGenesGeneticGenetic ScreeningGenetic TranscriptionGenetic studyGenomic SegmentGenotypeGoalsGuide RNAKnock-outLibrariesMammalian CellMessenger RNAMethodsMolecularOrganismOrthologous GenePhenotypePopulationProtein IsoformsRNARNA BindingRNA InterferenceRNA SequencesRNA interference screenRNA-Binding ProteinsRegulatory ElementReporterResearch PersonnelRibonucleasesScienceSolidStimulusStructureSystemTechnologyTimeTranscriptTranslationsUntranslated RNAUp-RegulationVariantVisualWorkbasecost effectivedesignexperimental studyflexibilityfluorophoreforward geneticsgenetic approachgenome editinggenome-widegenome-wide analysishuman diseaseimprovedinsightknock-downmicrobialnovelprogramsreconstitutionresponsescaffoldscreeningsensorsmall hairpin RNAtooltool developmenttranscriptome
中文摘要
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英文摘要
Project Summary
Functional understanding of the genetic circuits underlying complex phenotypes, including disease, will require
robust, scalable tools for modulating and tracking transcriptional events. Currently, RNAi using shRNAs is the
only high-throughput approach available, and this is largely limited to transcript knockdown. This project aims
to develop a suite of broadly applicable tools for the interrogation of RNA based on CRISPR-Cas
enzymes that target RNA in a programmable manner. Tools for transcript knockdown, translation
upregulation, and transcript sensing will be developed, which, together, will enable dissection of genetic circuits
in a dynamic, high-throughput manner, accelerating nearly all areas of biomedical science.
The proposal is focused on four key goals:
1. Functionally and biochemically characterize RNA-targeting Cas enzymes, and then harness these
enzymes for transcript editing in eukaryotic cells. Novel RNA-targeting CRISPR-Cas enzymes will be
developed as platforms for transcript knockdown and translational upregulation. The availability of
programmable tools for transcriptome editing in mammalian cells will provide new avenues for analyzing
the effect of gene expression events and will greatly advance our ability to study specific mRNA isoforms,
which is particularly important for understanding the brain.
2. Improve RNA knockdown screens. The current state-of-the-art for forward genetic screens in
mammalian systems uses shRNAs, but these have significant off-target effects. RNAi screens based on
programmable RNA-targeting enzymes will afford more robust, reliable data, boosting forward genetic
approaches.
3. Create programmable reporter systems for transcript sensing. Catalytically inactive RNA-targeting
Cas enzymes will be engineered to serve as programmable RNA-binding scaffolds that can be fused to
various functional moieties (e.g., fluorophores) to develop transcript sensors. These sensors will enable
dynamic, efficient tracking of transcriptional changes over extended periods of time and provide a means
for isolating transcriptionally defined cell populations for further study.
4. Develop genome-wide screens to dissect genetic regulatory circuits. Genome-wide Cas9 knockout
and activation screening will be combined with RNA-targeting sensors to develop high-throughput systems
to identify genomic regions (coding and non-coding) that influence the expression of a target gene.
These tools, which will be openly shared, will be broadly applicable across species and systems and will serve
as a general framework for the expansion of the RNA-targeting toolbox. They will radically transform existing
approaches for studying gene expression dynamics and exploring the significance of isoforms and non-coding
transcripts.
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