Genes on Chromosome 17 Regulating % Body Fat in the Mouse

描述（由申请人提供）：本项目的长期目标是鉴定和表征位于小鼠近端17号染色体（Chr 17）上的数量性状基因（QTG），这些基因赋予肥胖症的易感性和风险。我们已经使用C57 BL/6 N和129 P2小鼠品系之间的小鼠杂交确定了Chr 17上%体脂含量的显著连锁。在这个位点上，C57 BL等位基因与体脂增加相关。在使用不同C57小鼠亚系的许多其他小鼠遗传杂交中，已经鉴定了近端Chr 17上该区域的连锁，并且C57等位基因总是赋予肥胖风险增加的等位基因。基于单倍型的关联分析和生物信息学的物理位置的基因基础这Chr 17 QTL已显着缩小。将使用各种分子技术，包括平铺阵列，测序和表达分析来确定近端Chr 17上该性状的最佳候选者。最后，将使用在null/null小鼠中测量的表型和重组定量互补（rQC）试验验证特定候选物的作用。然后通过表征候选QTG的分子功能以及细胞和系统生物学，在野生型、null/null和rQC试验中产生的小鼠中检测经验证QTG的功能作用。 公共卫生相关性：确定疾病风险的遗传基础将导致开发更好的肥胖症和肥胖症相关疾病的治疗方法，并将导致根据患者的遗传背景为患者量身定制治疗方法。

DESCRIPTION (provided by applicant): The long-term objective of this project is to identify and characterize the quantitative trait genes (QTGs) located on proximal mouse chromosome 17 (Chr17) that confer susceptibility and risk for the development of obesity. We have identified significant linkage for % body fat content on Chr17 using a mouse cross between C57BL/6N and 129P2 mouse strains. At this locus it is the C57BL allele that is associated with increased body fat. Linkage in this region on proximal Chr17 has been identified in numerous other mouse genetic crosses using different substrains of C57 mice, and the C57 allele is always the allele conferring increased risk for obesity. The physical location of the genes underlying this Chr17 QTL has been significantly narrowed by haplotype-based association analysis and bioinformatics. The best candidates for this trait on proximal Chr17 will be identified using a variety of molecular techniques including tiling arrays, sequencing, and expression analyses. Finally the role of specific candidates will be validated using phenotypes measured in null/null mice and the recombinant Quantitative Complementation (rQC) test. The functional role of validated QTGs will then be tested in wildtype, null/null and the mice produced in the rQC test by characterizing the molecular function, as well as the cellular and systems biology of the candidate QTG. PUBLIC HEALTH RELEVANCE: Identification of the genetic basis of disease risk will lead to the development of better treatments for obesity and obesity-related diseases and will lead to methods for tailoring treatment to individual patients based upon their genetic background.