Gene mapping projects | ||||
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The Miller laboratory is engaged in a range of
mouse gene mapping projects, in a collaboration with David Burke of the
Human Genetics Department. Our key statistical collaborator is Andrzej
Galecki of the Geriatrics Center and Institute of Gerontology. 1. Overall mapping strategy: UM-HET3 mice Several of the mapping efforts make use of a population of mice called "UM-HET3," generated through a cross between (BALB/c x C57BL/6)F1 females and (C3H/He x DBA/2)F1 males. The UM-HET3 offspring are, from a genetic perspective, all brothers and sisters; each shares half its genes, but a different half, with every other member of the population. Each mouse in our test group is evaluated by the Burke laboratory to determine which genetic alleles it has inherited from the maternal and paternal side. Our laboratory, with a set of collaborators, then evaluates phenotypes of interest, so that statistical methods can be used to discover which sections of the genome contain loci that influence the traits in question. The traits fall into three general classes: (a) those, such as life span and cause of death, that require that the mouse live out its natural life span; (b) those that can be assessed without harm to the mice and can thus be measured in mice included within a longevity study; and (c) those that require that the mouse be sacrificed to provide access to internal tissues. The loci in question are called quantitative trait loci (QTL); their identification is a first step towards cloning the genes of interest, and can also provide insights into the physiological basis for the genetic effects seen in these mice. The National Institute on Aging's Intervention Testing Program uses HET3 mice for its studies of putative anti-aging interventions; more information about this program can be found on the NIA's website [link]. [Top of page] In a study of ~250 UM-HET3 mice we found found evidence for genes on five mouse chromosomes that influence life expectancy. Surprisingly, four of the five loci were sex-specific in their effect: two with an effect in males only, and two others that in combination had an effect only in females. The fifth QTL had an equivalent effect in both male and female mice. The genes were typically epistatic: the QTL on chromosome 9, for example, had an effect only in mice that inherited one of the two possible alleles at the QTL on chromosome 10 [PubMed]. Necropsy data (provided by the late Dr. Clarence Chrisp) was available for more than 90% of these mice, and showed that the effects of the QTL on longevity did not depend on the specific cause of death. For each of the genetic alleles found to have a significant effect on life span, we found quantitatively similar effects on the subset of mice dying of cancer and in the group of mice dying of non-neoplastic illnesses [PubMed]. This suggests the important conclusion that some underlying timing process - presumably the aging process itself - contributes to the timing of multiple late life illnesses. [Top of page] 3. Genes that influence age-sensitive traits: bone, T cells, hormones Completed studies using the UM-HET3 system have produced evidence for mouse loci that have influences on the size and shape of the femur [PubMed], femoral resistance to breakage [PubMed], age-related changes in vertebral properties [PubMed], changes in levels of multiple hormones [PubMed], age-sensitive T cell subsets [PubMed], cause of death [PubMed], and age-sensitive changes in protein folding and cross-linking [PubMed]. These studies have led to some general conclusions of interest, in addition to the information about genetic control of the specific traits evaluated. (a) The studies of hormone levels and T cell subsets have shown clearly that age-sensitive traits can be influenced by alleles that act early in life, and by (different) sets of loci whose effects become apparent only in middle age. (b) Advanced mathematical methods that evaluate multiple loci in parallel can show non-additive three-locus and four-locus interaction effects that often account for a high proportion of apparent outliers in a population distribution [PubMed]. Three gene mapping studies are currently underway in the laboratory. :
Collaborators include: David Burke, Andrzej Galecki, Shu Chen, Phil Hanlon, Steve Goldstein, Jim Harper, Steve Austad, Ari Gafni, Clarence Chrisp, Ruth Lipman. Support: National Institute of Aging. [Last update: December, 2007] |
Mouse femur for CT scanning. The Goldstein lab measures multiple parameters for each femur, which have overlapping but not identical genetic controls.
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