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Mammalian Genome

, Volume 25, Issue 3–4, pp 109–119 | Cite as

Heritability and coefficient of genetic variation analyses of phenotypic traits provide strong basis for high-resolution QTL mapping in the Collaborative Cross mouse genetic reference population

  • Fuad A. IraqiEmail author
  • Hanifa Athamni
  • Alexandra Dorman
  • Yasser Salymah
  • Ian Tomlinson
  • Aysar Nashif
  • Ariel Shusterman
  • Ervin Weiss
  • Yael Houri-Haddad
  • Richard Mott
  • Morris Soller
Article

Abstract

Most biological traits of human importance are complex in nature; their manifestation controlled by the cumulative effect of many genetic factors interacting with one another and with the individual’s life history. Because of this, mouse genetic reference populations (GRPs) consisting of collections of inbred lines or recombinant inbred lines (RIL) derived from crosses between inbred lines are of particular value in analysis of complex traits, since massive amounts of data can be accumulated on the individual lines. However, existing mouse GRPs are derived from inbred lines that share a common history, resulting in limited genetic diversity, and reduced mapping precision due to long-range gametic disequilibrium. To overcome these limitations, the Collaborative Cross (CC) a genetically highly diverse collection of mouse RIL was established. The CC, now in advanced stages of development, will eventually consist of about 500 RIL derived from reciprocal crosses of eight divergent founder strains of mice, including three wild subspecies. Previous studies have shown that the CC indeed contains enormous diversity at the DNA level, that founder haplotypes are inherited in expected frequency, and that long-range gametic disequilibrium is not present. We here present data, primarily from our own laboratory, documenting extensive genetic variation among CC lines as expressed in broad-sense heritability (H2) and by the well-known “coefficient of genetic variation,” demonstrating the ability of the CC resource to provide unprecedented mapping precision leading to identification of strong candidate genes.

Keywords

Quantitative Trait Locus Recombinant Inbred Line Quantitative Trait Locus Mapping Quantitative Trait Locus Location Quantitative Trait Locus Allele 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was supported by the Wellcome Trust grants 085906/Z/08/Z, 083573/Z/07/Z, and 075491/Z/04, Israeli Science Foundation grant (ISF)/429/09, Hendrech and Eiran Gotwert Fund for studying diabetes, and Merian and George Saiah Fund for studying infectious diseases. We thank Tel-Aviv University for their core funding and technical support and the Israeli Counsel for Higher Education for financial supporting Prof. Iraqiıs lab.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Fuad A. Iraqi
    • 1
    Email author
  • Hanifa Athamni
    • 1
  • Alexandra Dorman
    • 1
  • Yasser Salymah
    • 1
  • Ian Tomlinson
    • 2
  • Aysar Nashif
    • 3
  • Ariel Shusterman
    • 3
  • Ervin Weiss
    • 3
  • Yael Houri-Haddad
    • 3
  • Richard Mott
    • 2
  • Morris Soller
    • 4
  1. 1.Department of Clinical Microbiology and Immunology, Sackler Faculty of MedicineTel Aviv UniversityTel AvivIsrael
  2. 2.Welcome Trust human Genome centerUniversity of OxfordOxfordUK
  3. 3.Department of Prosthodontics, Dental School at HadassahHebrew UniversityJerusalemIsrael
  4. 4.Department of Genetics, Silberman Institute of Life SciencesHebrew UniversityJerusalemIsrael

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