Mutant resources for functional genomics in Dictyostelium discoideum using REMI-seq technology
Genomes can be sequenced with relative ease, but ascribing gene function remains a major challenge. Genetically tractable model systems are crucial to meet this challenge. One powerful model is the social amoeba Dictyostelium discoideum, a eukaryotic microbe widely used to study diverse questions in...
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Published in: | BMC biology Vol. 19; no. 1; p. 172 |
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Main Authors: | , , , , , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
England
BioMed Central Ltd
24-08-2021
BioMed Central BMC |
Subjects: | |
Online Access: | Get full text |
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Summary: | Genomes can be sequenced with relative ease, but ascribing gene function remains a major challenge. Genetically tractable model systems are crucial to meet this challenge. One powerful model is the social amoeba Dictyostelium discoideum, a eukaryotic microbe widely used to study diverse questions in the cell, developmental and evolutionary biology.
We describe REMI-seq, an adaptation of Tn-seq, which allows high throughput, en masse, and quantitative identification of the genomic site of insertion of a drug resistance marker after restriction enzyme-mediated integration. We use REMI-seq to develop tools which greatly enhance the efficiency with which the sequence, transcriptome or proteome variation can be linked to phenotype in D. discoideum. These comprise (1) a near genome-wide resource of individual mutants and (2) a defined pool of 'barcoded' mutants to allow large-scale parallel phenotypic analyses. These resources are freely available and easily accessible through the REMI-seq website that also provides comprehensive guidance and pipelines for data analysis. We demonstrate that integrating these resources allows novel regulators of cell migration, phagocytosis and macropinocytosis to be rapidly identified.
We present methods and resources, generated using REMI-seq, for high throughput gene function analysis in a key model system. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1741-7007 1741-7007 |
DOI: | 10.1186/s12915-021-01108-y |