A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans

2008 ◽  
Vol 40 (2) ◽  
pp. 181-188 ◽  
Author(s):  
Insuk Lee ◽  
Ben Lehner ◽  
Catriona Crombie ◽  
Wendy Wong ◽  
Andrew G Fraser ◽  
...  
2010 ◽  
Vol 344 (2) ◽  
pp. 1100-1109 ◽  
Author(s):  
Kazumasa Hada ◽  
Masako Asahina ◽  
Hiroshi Hasegawa ◽  
Yasunori Kanaho ◽  
Frank J. Slack ◽  
...  

Genome ◽  
1990 ◽  
Vol 33 (1) ◽  
pp. 109-114 ◽  
Author(s):  
Denise V. Clark ◽  
Robert C. Johnsen ◽  
Kim S. McKim ◽  
David L. Baillie

A screen was conducted for lethal mutations in the nematode Caenorhabditis elegans in a strain containing the mutator mut-4(st700)I to examine the nature of mutator-induced lethal mutations within two large chromosomal regions comprising a total of 49 map units (linkage group IV (right) and linkage group V (left)). The genetic analysis of 28 lethal mutations has revealed that the mutator locus mut-4(st700)I causes both putative single-gene mutations and deficiencies. We have identified lethal mutations in three different genes, in addition to seven deficiencies. There is a mutational hot spot on linkage group V (left) around the lin-40 locus. Six mutations appear to be alleles of lin-40. In addition, 5 of 7 deficiencies have breakpoints at or very near lin-40. All seven deficiencies delete the left-most known gene on linkage group V (left) and thus appear to delete the tip of the chromosome. This is in contrast to gamma ray and formaldehyde induced deficiencies, which infrequently delete the closest known gene to the tip of a chromosome.Key words: Caenorhabditis elegans, mutator, deficiencies, lethal mutations.


Genetics ◽  
1987 ◽  
Vol 117 (3) ◽  
pp. 467-476
Author(s):  
Samuel M Politz ◽  
Karl J Chin ◽  
Daniel L Herman

ABSTRACT We have studied developmental stage-specificity and genetic specification of surface antigens in the nematode Caenorhabditis elegans. Rabbit antisera directed against the adult C. elegans cuticle were used in conjunction with antiserum adsorption experiments to obtain antibody reagents with specificity for the adult surface. Adult-specific antibodies were used to identify several varietal strains of C. elegans that display antigen-negative phenotypes as adults. Genetic mapping results using the surface antigen phenotype as a marker indicated that a single gene (designated srf-1) or cluster of genes on linkage group II determines the adult surface antigen phenotype.


2020 ◽  
Vol 10 (7) ◽  
pp. 2353-2364 ◽  
Author(s):  
Kathryn S. Evans ◽  
Erik C. Andersen

Pleiotropy, the concept that a single gene controls multiple distinct traits, is prevalent in most organisms and has broad implications for medicine and agriculture. The identification of the molecular mechanisms underlying pleiotropy has the power to reveal previously unknown biological connections between seemingly unrelated traits. Additionally, the discovery of pleiotropic genes increases our understanding of both genetic and phenotypic complexity by characterizing novel gene functions. Quantitative trait locus (QTL) mapping has been used to identify several pleiotropic regions in many organisms. However, gene knockout studies are needed to eliminate the possibility of tightly linked, non-pleiotropic loci. Here, we use a panel of 296 recombinant inbred advanced intercross lines of Caenorhabditis elegans and a high-throughput fitness assay to identify a single large-effect QTL on the center of chromosome V associated with variation in responses to eight chemotherapeutics. We validate this QTL with near-isogenic lines and pair genome-wide gene expression data with drug response traits to perform mediation analysis, leading to the identification of a pleiotropic candidate gene, scb-1, for some of the eight chemotherapeutics. Using deletion strains created by genome editing, we show that scb-1, which was previously implicated in response to bleomycin, also underlies responses to other double-strand DNA break-inducing chemotherapeutics. This finding provides new evidence for the role of scb-1 in the nematode drug response and highlights the power of mediation analysis to identify causal genes.


2021 ◽  
Author(s):  
Saul Moore

Protocol for screening candidate behaviour-modifying E. coli BW25113 single-gene deletion mutants from the 'Keio Collection', to investigate their effects on Caenorhabditis elegans behaviour when killed by ultraviolet (UV) light


2006 ◽  
Vol 14 (4) ◽  
pp. 662-670 ◽  
Author(s):  
W B Derry ◽  
R Bierings ◽  
M van Iersel ◽  
T Satkunendran ◽  
V Reinke ◽  
...  

2008 ◽  
Vol 24 (18) ◽  
pp. 2044-2050 ◽  
Author(s):  
Markus W. Covert ◽  
Nan Xiao ◽  
Tiffany J. Chen ◽  
Jonathan R. Karr

AbstractMotivation: The effort to build a whole-cell model requires the development of new modeling approaches, and in particular, the integration of models for different types of processes, each of which may be best described using different representation. Flux-balance analysis (FBA) has been useful for large-scale analysis of metabolic networks, and methods have been developed to incorporate transcriptional regulation (regulatory FBA, or rFBA). Of current interest is the integration of these approaches with detailed models based on ordinary differential equations (ODEs).Results: We developed an approach to modeling the dynamic behavior of metabolic, regulatory and signaling networks by combining FBA with regulatory Boolean logic, and ordinary differential equations. We use this approach (called integrated FBA, or iFBA) to create an integrated model of Escherichia coli which combines a flux-balance-based, central carbon metabolic and transcriptional regulatory model with an ODE-based, detailed model of carbohydrate uptake control. We compare the predicted Escherichia coli wild-type and single gene perturbation phenotypes for diauxic growth on glucose/lactose and glucose/glucose-6-phosphate with that of the individual models. We find that iFBA encapsulates the dynamics of three internal metabolites and three transporters inadequately predicted by rFBA. Furthermore, we find that iFBA predicts different and more accurate phenotypes than the ODE model for 85 of 334 single gene perturbation simulations, as well for the wild-type simulations. We conclude that iFBA is a significant improvement over the individual rFBA and ODE modeling paradigms.Availability: All MATLAB files used in this study are available at http://www.simtk.org/home/ifba/.Contact: [email protected] information: Supplementary data are available at Bioinformatics online.


BMC Genomics ◽  
2016 ◽  
Vol 17 (1) ◽  
Author(s):  
Rania Nakad ◽  
L. Basten Snoek ◽  
Wentao Yang ◽  
Sunna Ellendt ◽  
Franziska Schneider ◽  
...  

2018 ◽  
Author(s):  
Mikel Hernaez ◽  
Olivier Gevaert

AbstractGene regulatory networks describe the regulatory relationships among genes, and developing methods for reverse engineering these networks are an ongoing challenge in computational biology. The majority of the initially proposed methods for gene regulatory network discovery create a network of genes and then mine it in order to uncover previously unknown regulatory processes. More recent approaches have focused on inferring modules of co-regulated genes, linking these modules with regulator genes and then mining them to discover new molecular biology.In this work we analyze module-based network approaches to build gene regulatory networks, and compare their performance to the well-established single gene network approaches. In particular, we focus on the problem of linking genes with known regulatory genes. First, modules are created iteratively using a regression approach that links co-expressed genes with few regulatory genes. After the modules are built, we create bipartite graphs to identify a set of target genes for each regulatory gene. We analyze several methods for uncovering these modules and show that a variational Bayes approach achieves significant improvement with respect to previously used methods for module creation on both simulated and real data. We also perform a topological and gene set enrichment analysis and compare several module-based approaches to single gene network approaches where a graph is built from the gene expression profiles without clustering genes in modules. We show that the module-based approach with variational Bayes outperforms all other methods and creates regulatory networks with a significantly higher rate of enriched molecular pathways.The code is written in R and can be downloaded from https://github.com/mikelhernaez/linker.


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