scholarly journals Genetic interaction analysis of point mutations enables interrogation of gene function at a residue-level resolution

BioEssays ◽  
2014 ◽  
Vol 36 (7) ◽  
pp. 706-713 ◽  
Author(s):  
Hannes Braberg ◽  
Erica A. Moehle ◽  
Michael Shales ◽  
Christine Guthrie ◽  
Nevan J. Krogan
Keyword(s):  
Gene Function ◽  
Genetic Interaction ◽  
Interaction Analysis ◽  
Point Mutations ◽  
Residue Level ◽  
Genetic Interaction Analysis

scholarly journals Integration of two RAB5 groups during endosomal transport in plants

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Emi Ito ◽  
Kazuo Ebine ◽  
Seung-won Choi ◽  
Sakura Ichinose ◽  
Tomohiro Uemura ◽  
...  
Keyword(s):  
Genetic Interaction ◽  
Interaction Analysis ◽  
Plant Cells ◽  
Eukaryotic Cells ◽  
Endosomal Trafficking ◽  
Effector Molecule ◽  
Endosomal Transport ◽  
Vacuolar Transport ◽  
Rab Effector ◽  
Genetic Interaction Analysis

RAB5 is a key regulator of endosomal functions in eukaryotic cells. Plants possess two different RAB5 groups, canonical and plant-unique types, which act via unknown counteracting mechanisms. Here, we identified an effector molecule of the plant-unique RAB5 in Arabidopsis thaliana, ARA6, which we designated PLANT-UNIQUE RAB5 EFFECTOR 2 (PUF2). Preferential colocalization with canonical RAB5 on endosomes and genetic interaction analysis indicated that PUF2 coordinates vacuolar transport with canonical RAB5, although PUF2 was identified as an effector of ARA6. Competitive binding of PUF2 with GTP-bound ARA6 and GDP-bound canonical RAB5, together interacting with the shared activating factor VPS9a, showed that ARA6 negatively regulates canonical RAB5-mediated vacuolar transport by titrating PUF2 and VPS9a. These results suggest a unique and unprecedented function for a RAB effector involving the integration of two RAB groups to orchestrate endosomal trafficking in plant cells.

scholarly journals Robust genetic interaction analysis

2018 ◽  
Vol 20 (2) ◽  
pp. 624-637 ◽  
Author(s):  
Mengyun Wu ◽  
Shuangge Ma
Keyword(s):  
Genetic Interaction ◽  
Interaction Analysis ◽  
Genetic Interaction Analysis

scholarly journals A genetic interaction analysis identifies cancer drivers that modify EGFR dependency

2017 ◽  
Vol 31 (2) ◽  
pp. 184-196 ◽  
Author(s):  
Sida Liao ◽  
Teresa Davoli ◽  
Yumei Leng ◽  
Mamie Z. Li ◽  
Qikai Xu ◽  
...  
Keyword(s):  
Genetic Interaction ◽  
Interaction Analysis ◽  
Cancer Drivers ◽  
Genetic Interaction Analysis

scholarly journals Conducting genetic interaction analysis with CRISPR-Cas9-based strategies in Candida albicans

2021 ◽  
Vol 3 (12) ◽  
Author(s):  
Viola Halder ◽  
Brianna McDonnell ◽  
Rebecca Shapiro
Keyword(s):  
Candida Albicans ◽  
Stress Response ◽  
Genetic Interaction ◽  
Interaction Analysis ◽  
Relative Fitness ◽  
Vaginal Mucosa ◽  
Response Gene ◽  
Fungal Genes ◽  
Genetic Interaction Analysis ◽  
Stress Response Gene

Candida albicans is an opportunistic fungal pathogen found in the oral mucosa, the gut, the vaginal mucosa, and humans' skin. While C. albicans can cause superficial infections, severe invasive infections can occur in immunocompromised individuals. Understanding the survival mechanisms and pathogenesis of C. albicans is critical for novel antifungal drug discovery. Determining the relationships between different genes can create a genetic interaction map, which can identify complementary gene sets, central to C. albicans survival, as potential drug targets in combination therapy. A genetic approach using the CRISPR-Cas9-based genome editing platform will focus on genetic interaction analysis of C. albicans stress response genes. The ultimate goal is to create a stress response gene deletion library to study its pathogen survival role. This library of single and double stress response gene mutants will be screened under diverse growth conditions to assess their relative fitness. Genetic interaction analysis will help map out epistatic interactions between fungal genes involved in growth, survival, and pathogenesis and uncover putative targets for combination antifungal therapy based on negative or synthetic lethal genetic interactions.

scholarly journals Genetic landscape of T cells identifies synthetic lethality for T-ALL

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Connor P. O’Meara ◽  
Lucia Guerri ◽  
Divine-Fondzenyuy Lawir ◽  
Fernando Mateos ◽  
Mary Iconomou ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Genetic Variants ◽  
Genetic Interaction ◽  
Synthetic Lethality ◽  
Interaction Analysis ◽  
T Cell Development ◽  
Cell Development ◽  
Cell Type ◽  
Genetic Interaction Analysis

AbstractTo capture the global gene network regulating the differentiation of immature T cells in an unbiased manner, large-scale forward genetic screens in zebrafish were conducted and combined with genetic interaction analysis. After ENU mutagenesis, genetic lesions associated with failure of T cell development were identified by meiotic recombination mapping, positional cloning, and whole genome sequencing. Recessive genetic variants in 33 genes were identified and confirmed as causative by additional experiments. The mutations affected T cell development but did not perturb the development of an unrelated cell type, growth hormone-expressing somatotrophs, providing an important measure of cell-type specificity of the genetic variants. The structure of the genetic network encompassing the identified components was established by a subsequent genetic interaction analysis, which identified many instances of positive (alleviating) and negative (synthetic) genetic interactions. Several examples of synthetic lethality were subsequently phenocopied using combinations of small molecule inhibitors. These drugs not only interfered with normal T cell development, but also elicited remission in a model of T cell acute lymphoblastic leukaemia. Our findings illustrate how genetic interaction data obtained in the context of entire organisms can be exploited for targeted interference with specific cell types and their malignant derivatives.

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