Simulating the Collaborative Cross: Power of Quantitative Trait Loci Detection and Mapping Resolution in Large Sets of Recombinant Inbred Strains of Mice

Valdar, William; Flint, Jonathan; Mott, Richard

doi:10.1534/genetics.104.039313

Cited by 171 publications

(204 citation statements)

References 15 publications

(16 reference statements)

Supporting

Mentioning

197

Contrasting

Unclassified

Order By: Relevance

“…22,47,48 RI strains are an ideal resource for systems biology research as they provide a reproducible, highly varied and diversified yet controlled set of genetic backgrounds for functional genomics, QTL mapping and identification of interactive gene networks modulating disease phenotype. 49 Being inbred, RI strains are perpetually renewable and have many advantages over F2 or backcross populations. Experiments performed with RI mice can be repeated in different laboratories and at different times with expected reproducibility.…”

Section: Discussionmentioning

confidence: 99%

Susceptibility to severe streptococcal sepsis: use of a large set of isogenic mouse lines to study genetic and environmental factors

et al. 2007

View full text Add to dashboard Cite

Variation in responses to pathogens is influenced by exposure history, environment and the host's genetic status. We recently demonstrated that human leukocyte antigen class II allelic differences are a major determinant of the severity of invasive group A streptococcal (GAS) sepsis in humans. While in-depth controlled molecular studies on populations of genetically wellcharacterized humans are not feasible, it is now possible to exploit genetically diverse panels of recombinant inbred BXD mice to define genetic and environmental risk factors. Our goal in this study was to standardize the model and identify genetic and nongenetic covariates influencing invasive infection outcomes. Despite having common ancestors, the various BXD strains (n strains ¼ 33, n individuals ¼ 445) showed marked differences in survival. Mice from all strains developed bacteremia but exhibited considerable differences in disease severity, bacterial dissemination and mortality rates. Bacteremia and survival showed the expected negative correlation. Among nongenetic factors, age -but not sex or weight -was a significant predictor of survival (P ¼ 0.0005). To minimize nongenetic variability, we limited further analyses to mice aged 40-120 days and calculated a corrected relative survival index that reflects the number of days an animal survived post-infection normalized to all significant covariates. Genetic background (strain) was the most significant factor determining susceptibility (Pp0.0001), thus underscoring the strong effect of host genetic variation in determining susceptibility to severe GAS sepsis. This model offers powerful unbiased forward genetics to map specific quantitative trait loci and networks of pathways modulating the severity of GAS sepsis.

show abstract

Section: Discussionmentioning

confidence: 99%

Susceptibility to severe streptococcal sepsis: use of a large set of isogenic mouse lines to study genetic and environmental factors

et al. 2007

View full text Add to dashboard Cite

show abstract

“…The genotypic value of an individual was the sum of all of its QTL effects. From the genotypic values of the set of PIs, the genotypic variance s g 2 was calculated (Valdar et al, 2006), which was the same for all mating designs. The phenotypic values of the RILs of each subpopulation were generated by adding a realization from a normal distribution N(0,(1Àh 2 )s g 2 /h 2 ) to the genotypic values of the RILs, where h 2 denotes the heritability.…”

Section: Genotypic and Phenotypic Valuesmentioning

confidence: 99%

QTL detection power of multi-parental RIL populations in Arabidopsis thaliana

2012

View full text Add to dashboard Cite

A major goal of today's biology is to understand the genetic basis of quantitative traits. This can be achieved by statistical methods that evaluate the association between molecular marker variation and phenotypic variation in different types of mapping populations. The objective of this work was to evaluate the statistical power of quantitative trait loci (QTL) detection of various multi-parental mating designs, as well as to assess the reasons for the observed differences. Our study was based on an empirical data of 20 Arabidopsis thaliana accessions, which have been selected to capture the maximum genetic diversity. The examined mating designs differed strongly with respect to the statistical power to detect QTL. We observed the highest power to detect QTL for the diallel cross with random mating design. The results of our study suggested that performing sibling mating within subpopulations of joint-linkage mapping populations has the potential to considerably increase the power for QTL detection. Our results, however, revealed that using designs in which more than two parental alleles segregate in each subpopulation increases the power even more.

show abstract

“…32 The first CC genetic loci have also now been mapped. 31 -33 As predicted from the computer simulations, 34 QTL mapped in the pre-CC are an order of magnitude narrower than QTL mapped using an intercross mapping population. 31,32 For example, a QTL for periosteal circumference mapped to chromosome 19 had a confidence interval width of only 0.96 Mb containing five candidate genes.…”

Section: Genetic Loci Mapping In Micementioning

confidence: 91%

The need for mouse models in osteoporosis genetics research

Ackert‐Bicknell¹,

Hibbs²

2012

BoneKEy Reports

View full text Add to dashboard Cite

Osteoporosis, the progressive loss of bone mass resulting in fragility fractures, affects ~ 75 million people in the United States, Europe and Japan. Bone mineral density (BMD) correlates with fracture risk and is widely used in clinical settings to predict fracture. Numerous studies have demonstrated that peak bone mass is highly heritable and consequently a number of genome-wide association studies (GWASs) have been conducted to identify the genes that regulate BMD. Traditional intercross mapping in the mouse has met with limited successes in the field of skeletal biology. With the advent of human GWAS, questions have arisen about the continued need for mouse models in genetics research. However, significant advances have been made in the field of mouse genetics, including new genetics resource populations and loci mapping techniques, which enable gene-level mapping resolution. In this review, we discuss the need for mouse models to help understand the skeletal biology underlying novel human GWAS findings, how loci discovered in the mouse can be used to complement GWAS analysis and highlight the recent advances made in the field of skeletal biology from the use of these new and developing resources. We conclude this paper with a discussion of the need for systems-level approaches in the skeletal biology field, with an emphasis on the need for pathway and network analyses.

show abstract

Simulating the Collaborative Cross: Power of Quantitative Trait Loci Detection and Mapping Resolution in Large Sets of Recombinant Inbred Strains of Mice

Cited by 171 publications

References 15 publications

Susceptibility to severe streptococcal sepsis: use of a large set of isogenic mouse lines to study genetic and environmental factors

Susceptibility to severe streptococcal sepsis: use of a large set of isogenic mouse lines to study genetic and environmental factors

QTL detection power of multi-parental RIL populations in Arabidopsis thaliana

The need for mouse models in osteoporosis genetics research

Contact Info

Product

Resources

About