Mapping of a trans-acting regulatory locus of Bone gamma carboxyglutamate protein-related sequence 1 (Bglap-rs1) mRNA levels in mouse chromosome substitution strains

2010 ◽  
Vol 27 ◽  
pp. S50-S51
Author(s):  
M. Dzur-Gejdosova ◽  
P. Simecek ◽  
I. Chvatalova ◽  
J. Forejt
Keyword(s):  
Mouse Chromosome ◽  
Mrna Levels ◽  
Chromosome Substitution ◽  
Related Sequence ◽  
Regulatory Locus ◽  
Chromosome Substitution Strains

Phenotyping mouse chromosome substitution strains reveal multiple QTLs for febrile seizure susceptibility

2009 ◽  
Vol 8 (2) ◽  
pp. 248-255 ◽  
Author(s):  
E. V. S. Hessel ◽  
K. L. I. Van Gassen ◽  
I. G. Wolterink-Donselaar ◽  
P. J. Stienen ◽  
C. Fernandes ◽  
...  
Keyword(s):  
Mouse Chromosome ◽  
Febrile Seizure ◽  
Seizure Susceptibility ◽  
Chromosome Substitution ◽  
Chromosome Substitution Strains

scholarly journals Chromosomes 6 and 13 Harbor Genes that Regulate Pubertal Timing in Mouse Chromosome Substitution Strains

Endocrinology ◽  
2004 ◽  
Vol 145 (10) ◽  
pp. 4447-4451 ◽  
Author(s):  
Thomas D. Krewson ◽  
Pamela J. Supelak ◽  
Annie E. Hill ◽  
Jonathan B. Singer ◽  
Eric S. Lander ◽  
...  
Keyword(s):  
Mouse Chromosome ◽  
Pubertal Timing ◽  
Chromosome Substitution ◽  
Chromosome Substitution Strains

scholarly journals Genomic survey of prepulse inhibition in mouse chromosome substitution strains

2009 ◽  
Vol 8 (8) ◽  
pp. 806-816 ◽  
Author(s):  
M. P. Leussis ◽  
M. L. Frayne ◽  
M. Saito ◽  
E. M. Berry ◽  
K. A. Aldinger ◽  
...  
Keyword(s):  
Mouse Chromosome ◽  
Prepulse Inhibition ◽  
Chromosome Substitution ◽  
Chromosome Substitution Strains

scholarly journals Widespread Inter-Chromosomal Epistasis Regulates Glucose Homeostasis and Gene Expression

2017 ◽  
Author(s):  
Anlu Chen ◽  
Yang Liu ◽  
Scott M. Williams ◽  
Nathan Morris ◽  
David A. Buchner
Keyword(s):  
Gene Expression ◽  
Mouse Chromosome ◽  
Complex Traits ◽  
Large Scale ◽  
Allelic Variation ◽  
Genetic Regulation ◽  
Chromosome Substitution ◽  
Epistatic Interactions ◽  
Dominant Feature ◽  
Chromosome Substitution Strains

AbstractThe relative contributions of additive versus non-additive interactions in the regulation of complex traits remains controversial. This may be in part because large-scale epistasis has traditionally been difficult to detect in complex, multi-cellular organisms. We hypothesized that it would be easier to detect interactions using mouse chromosome substitution strains that simultaneously incorporate allelic variation in many genes on a controlled genetic background. Analyzing metabolic traits and gene expression levels in the offspring of a series of crosses between mouse chromosome substitution strains demonstrated that inter-chromosomal epistasis was a dominant feature of these complex traits. Epistasis typically accounted for a larger proportion of the heritable effects than those due solely to additive effects. These epistatic interactions typically resulted in trait values returning to the levels of the parental CSS host strain. Due to the large epistatic effects, analyses that did not account for interactions consistently underestimated the true effect sizes due to allelic variation or failed to detect the loci controlling trait variation. These studies demonstrate that epistatic interactions are a common feature of complex traits and thus identifying these interactions is key to understanding their genetic regulation.

scholarly journals A Novel Mapping Strategy Utilizing Mouse Chromosome Substitution Strains Identifies Multiple Epistatic Interactions That Regulate Complex Traits

2020 ◽  
Vol 10 (12) ◽  
pp. 4553-4563
Author(s):  
Anna K. Miller ◽  
Anlu Chen ◽  
Jacquelaine Bartlett ◽  
Li Wang ◽  
Scott M. Williams ◽  
...  
Keyword(s):  
Mouse Chromosome ◽  
Complex Traits ◽  
Allelic Variation ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Chromosome Substitution ◽  
Distribution Width ◽  
Epistatic Qtl ◽  
Hepatic Expression ◽  
Chromosome Substitution Strains

The genetic contribution of additive vs. non-additive (epistatic) effects in the regulation of complex traits is unclear. While genome-wide association studies typically ignore gene-gene interactions, in part because of the lack of statistical power for detecting them, mouse chromosome substitution strains (CSSs) represent an alternate approach for detecting epistasis given their limited allelic variation. Therefore, we utilized CSSs to identify and map both additive and epistatic loci that regulate a range of hematologic- and metabolism-related traits, as well as hepatic gene expression. Quantitative trait loci (QTL) were identified using a CSS-based backcross strategy involving the segregation of variants on the A/J-derived substituted chromosomes 4 and 6 on an otherwise C57BL/6J genetic background. In the liver transcriptomes of offspring from this cross, we identified and mapped additive QTL regulating the hepatic expression of 768 genes, and epistatic QTL pairs for 519 genes. Similarly, we identified additive QTL for fat pad weight, platelets, and the percentage of granulocytes in blood, as well as epistatic QTL pairs controlling the percentage of lymphocytes in blood and red cell distribution width. The variance attributed to the epistatic QTL pairs was approximately equal to that of the additive QTL; however, the SNPs in the epistatic QTL pairs that accounted for the largest variances were undetected in our single locus association analyses. These findings highlight the need to account for epistasis in association studies, and more broadly demonstrate the importance of identifying genetic interactions to understand the complete genetic architecture of complex traits.

scholarly journals Two Quantitative Trait Loci for Prepulse Inhibition of Startle Identified on Mouse Chromosome 16 Using Chromosome Substitution Strains

Genetics ◽  
2005 ◽  
Vol 171 (4) ◽  
pp. 1895-1904 ◽  
Author(s):  
Tracey L. Petryshen ◽  
Andrew Kirby ◽  
Ronald P. Hammer ◽  
Shaun Purcell ◽  
Sinead B. O'Leary ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Mouse Chromosome ◽  
Prepulse Inhibition ◽  
Quantitative Trait ◽  
Chromosome Substitution ◽  
Chromosome 16 ◽  
Trait Loci ◽  
Chromosome Substitution Strains

scholarly journals A novel mapping strategy utilizing mouse chromosome substitution strains identifies multiple epistatic interactions that regulate complex traits

2020 ◽  
Author(s):  
Anna K. Miller ◽  
Anlu Chen ◽  
Jacquelaine Bartlett ◽  
Li Wang ◽  
Scott M. Williams ◽  
...  
Keyword(s):  
Mouse Chromosome ◽  
Complex Traits ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Chromosome Substitution ◽  
Distribution Width ◽  
Epistatic Qtl ◽  
Hepatic Expression ◽  
Chromosome Substitution Strains ◽  
Additive Qtls

AbstractThe genetic contribution of additive versus non-additive (epistatic) effects in the regulation of complex traits is unclear. While genome-wide association studies typically ignore gene-gene interactions, in part because of the lack of statistical power for detecting them, mouse chromosome substitution strains (CSSs) represent an alternate and powerful model for detecting epistasis given their limited allelic variation. Therefore, we utilized CSSs to identify and map both additive and epistatic loci that regulate a range of hematologic- and metabolism-related traits, as well as hepatic gene expression. Quantitative trait loci (QTLs) were identified using a CSS-based backcross strategy involving the segregation of variants on the A/J-derived substituted chromosomes 4 and 6 on an otherwise C57BL/6J genetic background. In the liver transcriptomes of offspring from this cross, we identified and mapped additive QTLs regulating the hepatic expression of 768 genes, and epistatic QTL pairs for 519 genes. Similarly, we identified additive QTLs for fat pad weight, platelets, and the percentage of granulocytes in blood, as well as epistatic QTL pairs controlling the percentage of lymphocytes in blood and red cell distribution width. The variance attributed to the epistatic QTL pairs was approximately equal to that of the additive QTLs; however, the SNPs in the epistatic QTL pairs that accounted for the largest variances were undetected in our single locus association analyses. These findings highlight the need to account for epistasis in association studies, and more broadly demonstrate the importance of identifying genetic interactions to understand the complete genetic architecture of complex traits.

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