scholarly journals A large-scale zebrafish gene knockout resource for the genome-wide study of gene function

2013 ◽  
Vol 23 (4) ◽  
pp. 727-735 ◽  
Author(s):  
G. K. Varshney ◽  
J. Lu ◽  
D. E. Gildea ◽  
H. Huang ◽  
W. Pei ◽  
...  
BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Nicole Gruenheit ◽  
Amy Baldwin ◽  
Balint Stewart ◽  
Sarah Jaques ◽  
Thomas Keller ◽  
...  

Abstract Background 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. Results 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. Conclusions We present methods and resources, generated using REMI-seq, for high throughput gene function analysis in a key model system.


Nature ◽  
2011 ◽  
Vol 474 (7351) ◽  
pp. 337-342 ◽  
Author(s):  
William C. Skarnes ◽  
Barry Rosen ◽  
Anthony P. West ◽  
Manousos Koutsourakis ◽  
Wendy Bushell ◽  
...  

2018 ◽  
Author(s):  
Kendall R Sanson ◽  
Ruth E Hanna ◽  
Mudra Hegde ◽  
Katherine F Donovan ◽  
Christine Strand ◽  
...  

ABSTRACTAdvances in CRISPR-Cas9 technology have enabled the flexible modulation of gene expression at large scale. In particular, the creation of genome-wide libraries for CRISPR knockout (CRISPRko), CRISPR interference (CRISPRi), and CRISPR activation (CRISPRa) has allowed gene function to be systematically interrogated. Here, we evaluate numerous CRISPRko libraries and show that our recently-described CRISPRko library (Brunello) is more effective than previously published libraries at distinguishing essential and non-essential genes, providing approximately the same perturbation-level performance improvement over GeCKO libraries as GeCKO provided over RNAi. Additionally, we developed genome-wide libraries for CRISPRi (Dolcetto) and CRISPRa (Calabrese). Negative selection screens showed that Dolcetto substantially outperforms existing CRISPRi libraries with fewer sgRNAs per gene and achieves comparable performance to CRISPRko in the detection of gold-standard essential genes. We also conducted positive selection CRISPRa screens and show that Calabrese outperforms the SAM library approach at detecting vemurafenib resistance genes. We further compare CRISPRa to genome-scale libraries of open reading frames (ORFs). Together, these libraries represent a suite of genome-wide tools to efficiently interrogate gene function with multiple modalities.tracr


2018 ◽  
Vol 102 (3) ◽  
pp. 375-400 ◽  
Author(s):  
Yun J. Sung ◽  
Thomas W. Winkler ◽  
Lisa de las Fuentes ◽  
Amy R. Bentley ◽  
Michael R. Brown ◽  
...  

2020 ◽  
Vol 48 (17) ◽  
pp. 9462-9477
Author(s):  
Brendan Veeneman ◽  
Ying Gao ◽  
Joy Grant ◽  
David Fruhling ◽  
James Ahn ◽  
...  

Abstract CRISPR/Cas9 functional genomic screens have emerged as essential tools in drug target discovery. However, the sensitivity of available genome-wide CRISPR libraries is impaired by guides which inefficiently abrogate gene function. While Cas9 cleavage efficiency optimization and essential domain targeting have been developed as independent guide design rationales, no library has yet combined these into a single cohesive strategy to knock out gene function. Here, in a massive reanalysis of CRISPR tiling data using the most comprehensive feature database assembled, we determine which features of guides and their targets best predict activity and how to best combine them into a single guide design algorithm. We present the ProteIN ConsERvation (PINCER) genome-wide CRISPR library, which for the first time combines enzymatic efficiency optimization with conserved length protein region targeting, and also incorporates domains, coding sequence position, U6 termination (TTT), restriction sites, polymorphisms and specificity. Finally, we demonstrate superior performance of the PINCER library compared to alternative genome-wide CRISPR libraries in head-to-head validation. PINCER is available for individual gene knockout and genome-wide screening for both the human and mouse genomes.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yanting Chen ◽  
Zhaoxia Liu ◽  
Jacques Régnière ◽  
Liette Vasseur ◽  
Jian Lin ◽  
...  

AbstractUnderstanding the genetic basis of climatic adaptation is essential for predicting species’ responses to climate change. However, intraspecific variation of these responses arising from local adaptation remains ambiguous for most species. Here, we analyze genomic data from diamondback moth (Plutella xylostella) collected from 75 sites spanning six continents to reveal that climate-associated adaptive variation exhibits a roughly latitudinal pattern. By developing an eco-genetic index that combines genetic variation and physiological responses, we predict that most P. xylostella populations have high tolerance to projected future climates. Using genome editing, a key gene, PxCad, emerged from our analysis as functionally temperature responsive. Our results demonstrate that P. xylostella is largely capable of tolerating future climates in most of the world and will remain a global pest beyond 2050. This work improves our understanding of adaptive variation along environmental gradients, and advances pest forecasting by highlighting the genetic basis for local climate adaptation.


2021 ◽  
Author(s):  
Adrian Jinich ◽  
Anisha Zaveri ◽  
Michael A. DeJesus ◽  
Emanuel Flores-Bautista ◽  
Clare M. Smith ◽  
...  

AbstractCharacterization of gene essentiality across different conditions is a useful approach for predicting gene function. Transposon sequencing (TnSeq) is a powerful means of generating genome-wide profiles of essentiality and has been used extensively in Mycobacterium tuberculosis (Mtb) genetic research. Over the past two decades, dozens of TnSeq screens have been published, yielding valuable insights into the biology of Mtb in vitro, inside macrophages, and in model host organisms. However, these Mtb TnSeq profiles are distributed across dozens of research papers within supplementary materials, which makes querying them cumbersome and assembling a complete and consistent synthesis of existing data challenging. Here, we address this problem by building a central repository of publicly available TnSeq screens performed in M. tuberculosis, which we call the Mtb transposon sequencing database (MtbTnDB). The MtbTnDB encompasses 64 published and unpublished TnSeq screens, and is standardized, open-access, and allows users easy access to data, visualizations, and functional predictions through an interactive web-app (www.mtbtndb.app). We also present evidence that (i) genes in the same genomic neighborhood tend to have similar TnSeq profiles, and (ii) clusters of genes with similar TnSeq profiles tend to be enriched for genes belonging to the same functional categories. Finally, we test and evaluate machine learning models trained on TnSeq profiles to guide functional annotation of orphan genes in Mtb. In addition to facilitating the exploration of conditional genetic essentiality in this important human pathogen via a centralized TnSeq data repository, the MtbTnDB will enable hypothesis generation and the extraction of meaningful patterns by facilitating the comparison of datasets across conditions. This will provide a basis for insights into the functional organization of Mtb genes as well as gene function prediction.


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