Candidate Gene Analysis for Macronutrient Selection QTL

描述(申请人提供)：这项申请是我们先前资助的直接延续，目的是在C67BL/6J和CAST/EI小鼠近交系中控制常量营养素选择的QTL的遗传图谱，这两个品系的自选常量营养素摄入量明显不同。全基因组扫描显示，代表自选脂肪和碳水化合物摄入量的性状与第6、8、17、18和X染色体上的显著连锁。当体重作为协变量时，17和18染色体上的基因座也与总能量摄入有关。这是第一个在小鼠身上定位的食物偏好或总能量摄入量的QTL。目前这项建议的总体目标是确定影响膳食脂肪摄入量的数量性状基因(QTL)Mnif1和位于染色体17的影响碳水化合物和千卡摄入量的MNic1的候选基因。在目标1中，我们将通过培育B6.CAST同源和亚同源品系，分离并缩小Mnif1和MNic1区间，使其大小适合于位置候选方法。在目标2中，基因表达微阵列将用于识别候选基因。微阵列的探针将由受体株(B6)和我们实验室开发的间隔特异性亚基因株(B6)的组织中的cDNA组成，mRNA将从在摄食表型调节中起重要作用的组织，即下丘脑、孤束核/最后区、肝脏、胃、小肠、胰腺、脂肪细胞、肌肉中获得。首先，将使用小鼠寡核苷酸阵列(来自Unigene的16,463个基因)进行全基因组基因表达筛选，该阵列现已准备就绪，可从PBRC基因组学核心获得。因此，我们将描述QTL中基因影响的上游或下游发生的转录差异。这些数据将提供一个切入点，用于对控制这些摄食行为的过程进行建模，并识别最有希望的组织以用于QTL特定阵列。接下来，将设计定制的阵列，用于全面分析控制Chr 8(Mnif1)上脂肪摄取和Chr 17上碳水化合物摄取(MNic1)的QTL亚基因区间内存在的所有小鼠和人类基因的转录活性。对饲养性状的生物学知识和对QTL内外差异表达基因的分析将有助于我们将候选基因的数量减少到极少数，并选择那些值得进一步研究的基因，以便在决定表型方面发挥作用。候选基因的识别将加深我们对食物摄取调节的理解。在小鼠身上找到调节大量营养素摄入的基因，将有助于我们了解影响人类食物偏好的遗传和环境因素的贡献。这应该会导致对肥胖和糖尿病的有价值的见解，以及修改可能有助于控制体重增加或促进减肥的大量营养素选择的新方法。

DESCRIPTION (provided by applicant): This application is a direct continuation of our previous grant directed at the genetic mapping of QTL controlling macronutrient selection in the C67BL/6J and CAST/Ei mouse inbred strains which differ markedly in their self-selected intake of macronutrient diets. A genome-wide scan revealed significant linkage for traits representing self-selected fat and carbohydrate intake on chromosome 6, 8, 17, 18 and X. Loci on chromosome 17 and 18 were linked also to total energy intake when body weight was used as a covariate. These are the first QTL for food preference or total energy intake that have been mapped in the mouse. The overall goal of the current proposal is to identify candidate genes underlying Mnif1, a quantitative trait locus (QTL) for dietary fat intake located on chromosome 8, and Mnic1 on chromosome 17 for carbohydrate and kilocalorie intake. In Aim 1, we will isolate and narrow the Mnif1 and Mnic1 intervals to a size suitable for the positional candidate approach, by developing B6.CAST congenic and subcongenic lines. In Aim 2, gene expression microarrays will be used to identify candidate genes. The probes for the microarrays will consist of cDNA from tissues of the recipient strain (B6) and the interval-specific subcongenic strains (B6.CAST) developed in our laboratory, mRNA will be harvested from tissues important in the regulation of food intake phenotypes, i.e, hypothalamus, solitary tract nucleus/area postrema, liver, stomach, small intestine, pancreas, adipocyte, muscle. First, a genome-wide gene expression screen will be performed using a mouse oligonucleotide array (16,463 genes from UniGene) now ready and available from the PBRC Genomics Core. Thus we will characterize transcriptional differences that occur upstream or downstream from effects of genes within the QTL. These data will provide an entry point for modelling the process by which these feeding behaviors are controlled, and for identifying the most promising tissues to profile with the QTL-specific arrays. Next, custom arrays will be designed for the purpose of performing comprehensive analyses of the transcriptional activity of all mouse and human genes present in the subcongenic intervals for the QTL controlling fat intake on Chr 8 (Mnif1) and carbohydrate intake on Chr 17 (Mnic1). Knowledge of the biology of the feeding traits and analysis of differentially expressed genes within and outside of the QTL will help us reduce the number of candidates to a very few and select those that deserve further investigation for a functional role in determining the phenotype. Candidate gene identification will enhance our understanding of the regulation of food intake. Finding genes regulating macronutrient intake in mice will help us to understand the contribution of genetic versus environmental factors affecting food preferences in humans. This should lead to valuable insights into obesity and diabetes, and new approaches for modifying macronutrient selection that could be useful in controlling weight gain or promoting weight loss.