Quantitative Trait Loci mapping analysis

Identifying loci that contribute to phenotype variations once a genetic cross is made is an important step in mouse-based research. Now you can advance the identification of Quantitative Trait Loci (QTL) using our well-established Gene Mapping and the Statistical Analysis Services. The service includes genotyping DNA samples from a cross performed by you or by JAX® Breeding Services, combined with the use of specialized statistical methods developed at The Jackson Laboratory for QTL discovery. Here at The Jackson Laboratory we have analyzed many QTL crosses for our own scientists and are now pleased to offer this service to the broader scientific community.

Recent references which have utilized our QTL methods

Service details

First, each mouse from the cross is genotyped using selected single nucleotide polymorphisms (SNPs) from our panel of over 2,000 SNP markers. This genotype information is then combined with phenotype information and statistically analyzed using state-of-the-art QTL data analysis software1,2,3,4. For more details about the service or methods used, please visit our FAQ page. Our process is as follows:

  • You complete a questionnaire describing your project. 
  • We contact you for a brief phone consultation, to ensure the experimental design meets your objectives
  • We provide you a project quote for your review and acceptance
  • A Project Specialist is assigned to track the progress of your study and communicate with you at all stages of the process, from receipt of samples through completion of data analysis
  • DNA is extracted, quantitated and quality assessed
  • The DNA is processed for SNP genotyping assay
  • A subset of informative SNPs are selected from our panel of over 2,000 SNP markers
  • All DNA samples are genotyped
  • Genotype and phenotype data are analyzed at The Jackson Laboratory by the Computational Sciences-Statistics and Analysis group. First, quality control and diagnostic plots of the genotyping and phenotyping data are generated. Then, you can choose the depth of analysis you would like to have performed.
    • Level 1 Analysis: Preliminary analysis using a one-dimensional genome scan for major QTL detection.
      • For each phenotype, a genome-wide one-dimensional scan is run to detect major QTL using a statistical model that addresses covariates such as sex and/or body weight.
    • Level 2 Analysis: Thorough QTL analysis suitable for publication.
      • For each phenotype, genome-wide two-dimensional scans are run to test for major QTL and detect QTL*QTL interactions and fit multiple regression models for candidate QTL and covariates. Several plots are generated from the analysis including one and two-dimensional scan plots. For each major QTL detected, confidence interval and effect plots are generated.
  • A report is then generated including a description of methods, QC results and statistics for QTL found from the analysis. View a Level 1 Analysis sample report (.pdf) or Level 2 Analysis sample report (.pdf). The data featured in the example reports were published in Peters et al. Mamm Genome (2005) 16(10):749-63.
  • A final phone call up to one hour in length is conducted after you have reviewed the report to answer any questions you may have.

A Project Specialist will be assigned to track the progress of your study and will communicate with you at all stages of the process, from receipt of samples through completion of data analysis.

Pricing

Pricing for QTL projects is provided by quotation, and depends on the number of phenotyes, the number of animals, and the level of analysis requested. Please call for details.

References

  1. Broman KW, Wu H, Sen S, Churchill GA (2003) R/qtl: QTL mapping in experimental crosses. Bioinformatics 19:889-890.
  2. Doerge, RW and Churchill, GA (1996) Permutation tests for multiple loci affecting a quantitative character. Genetics 142, 285-294.
  3. Lander E and Kruglyak L (1995) Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nature Genetics  11: 241-247.
  4. Sen S and Churchill GA (2001) A statistical framework for quantitative trait mapping. Genetics 159, 371-387.

Still have questions?