Quantitative Trait Locus Analysis Using J/qtl

Smith, R. V.; Sheppard, Keith; DiPetrillo, Keith; Churchill, Gary A.

doi:10.1007/978-1-60761-247-6_10

Cited by 33 publications

(28 citation statements)

References 6 publications

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“…QTL mapping analysis was performed using J/qtl 1.3.3 software (The Jackson Laboratories; churchill.jax.org/software/jqtl.shtml) (23). QTL scans were run using the EM Algorithm (Maximum Likelihood) method using default convergence parameters.…”

Section: Methodsmentioning

confidence: 99%

A genetic basis of variation in eccrine sweat gland and hair follicle density

Kamberov

Karlsson

Kamberova

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Among the unique features of humans, one of the most salient is the ability to effectively cool the body during extreme prolonged activity through the evapotranspiration of water on the skin's surface. The evolution of this novel physiological ability required a dramatic increase in the density and distribution of eccrine sweat glands relative to other mammals and a concomitant reduction of body hair cover. Elucidation of the genetic underpinnings for these adaptive changes is confounded by a lack of knowledge about how eccrine gland fate and density are specified during development. Moreover, although reciprocal changes in hair cover and eccrine gland density are required for efficient thermoregulation, it is unclear if these changes are linked by a common genetic regulation. To identify pathways controlling the relative patterning of eccrine glands and hair follicles, we exploited natural variation in the density of these organs between different strains of mice. Quantitative trait locus mapping identified a large region on mouse Chromosome 1 that controls both hair and eccrine gland densities. Differential and allelic expression analysis of the genes within this interval coupled with subsequent functional studies demonstrated that the level of En1 activity directs the relative numbers of eccrine glands and hair follicles. These findings implicate En1 as a newly identified and reciprocal determinant of hair follicle and eccrine gland density and identify a pathway that could have contributed to the evolution of the unique features of human skin.eccrine sweat gland | hair follicle | ectodermal placode | engrailed 1 | ectodermal appendage

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Section: Methodsmentioning

confidence: 99%

A genetic basis of variation in eccrine sweat gland and hair follicle density

Kamberov

Karlsson

Kamberova

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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“…The java-based QTL mapping program (J/qtl) was used to perform QTL analysis using 648 informative germline SNPs with a single locus model of inheritance, whereby a single QTL analysis was performed for all aggressive disease traits [22]. In addition, a binary model was used for binary traits, and a non-parametric model was used for all other traits [22]. Age of death and primary tumor burden were used as additive covariates in these analyses.…”

Section: Tissue Collection and Quantificationmentioning

confidence: 99%

“…Briefly, metastasis-related traits (e.g., distant metastasis-free survival [DMFS], presence or absence of lymph node metastasis, lymph node metastasis burden) and tumor related-traits (primary tumor burden, seminal vesicle tumor burden) were quantified in a mapping population of 201 transgene-positive (TRAMP 9 PWK/PhJ) F2 intercross males (Supplementary Data, Table S1). The java-based QTL mapping program (J/qtl) was used to perform QTL analysis using 648 informative germline SNPs with a single locus model of inheritance, whereby a single QTL analysis was performed for all aggressive disease traits [22]. In addition, a binary model was used for binary traits, and a non-parametric model was used for all other traits [22].…”

Section: Tissue Collection and Quantificationmentioning

confidence: 99%

GNL3 and SKA3 are novel prostate cancer metastasis susceptibility genes

Lee

Williams

et al. 2015

Clin Exp Metastasis

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Prostate cancer (PC) is very common in developed countries. However, the molecular determinants of PC metastasis are unclear. Previously, we reported that germline variation influences metastasis in the C57BL/6-Tg(TRAMP)8247Ng/J (TRAMP) mouse model of PC. These mice develop prostate tumors similar to a subset of poor outcome, treatment-associated human PC tumors. Here, we used TRAMP mice to nominate candidate genes and validate their role in aggressive human PC in PC datasets and cell lines. Candidate metastasis susceptibility genes were identified through quantitative trait locus (QTL) mapping in 201 (TRAMP × PWK/PhJ) F2 males. Two metastasis-associated QTLs were identified; one on chromosome 12 (LOD = 5.86), and one on chromosome 14 (LOD = 4.41). Correlation analysis using microarray data from (TRAMP × PWK/PhJ) F2 prostate tumors identified 35 metastasis-associated transcripts within the two loci. The role of these genes in susceptibility to aggressive human PC was determined through in silico analysis using multiple datasets. First, analysis of candidate gene expression in two human PC datasets demonstrated that five candidate genes were associated with an increased risk of aggressive disease and lower disease-free survival. Second, four of these genes (GNL3, MAT1A, SKA3, and ZMYM5) harbored SNPs associated with aggressive tumorigenesis in the PLCO/CGEMS GWAS of 1172 PC patients. Finally, over-expression of GNL3 and SKA3 in the PC-3 human PC cell line decreased in vitro cell migration and invasion. This novel approach demonstrates how mouse models can be used to identify metastasis susceptibility genes, and gives new insight into the molecular mechanisms of fatal PC.

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“…The bayesian confidence intervals, which define the most likely limits for the QTL, were calculated in J/qtl. 13 The Scvg2 interval spans from 7384755 to 26195496 base pair on Chr. 3, a region containing 215 genes (Fig.…”

Section: Resultsmentioning

confidence: 99%

Mapping Novel Subcutaneous Angiogenesis Quantitative Trait Loci in [B6×MRL]F2 Mice

Morales

Rowehl

Smith

et al. 2014

Advances in Wound Care

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Objective: MRL/MpJ mice are known for enhanced healing, but mechanistic details or how specific aspects of wounding (e.g., angiogenesis) contribute to healing are unknown. While previous studies investigated the systemic effects of immunity in MRL/MpJ healing, few have focused on tissue-intrinsic effects. Approach: Ex vivo skin biopsies from MRL/MpJ and C57BL/6J mice were cultured in ex vivo conditions that favor endothelial cell growth to compare their angiogenic potential. We localized enhanced angiogenesis quantitative trait loci (QTL) in an F2 intercross. We then performed an expression analysis in cultured skin biopsies from MRL/MpJ and C57BL/6J mice to determine the pathways that are associated with the capacity for differential growth.

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Quantitative Trait Locus Analysis Using J/qtl

Cited by 33 publications

References 6 publications

A genetic basis of variation in eccrine sweat gland and hair follicle density

A genetic basis of variation in eccrine sweat gland and hair follicle density

GNL3 and SKA3 are novel prostate cancer metastasis susceptibility genes

Mapping Novel Subcutaneous Angiogenesis Quantitative Trait Loci in [B6×MRL]F2 Mice

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