Disequilibrium Mapping of Complex Genetic Diseases

复杂遗传疾病的不平衡图谱

• 批准号: 7651902
• 负责人: Bruce RANNALA
• 金额: $ 30.02万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-01-01 至 2012-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7651902
• 关键词: Affect; Algorithms; Appearance; Base Pairing; Behavior; Chromosomes; Complex; Computational algorithm; Computer software; Crohn' s disease; Cystic Fibrosis; DNA; DNA Sequence; DNA biosynthesis; Data; Development; Disease; Disease susceptibility; Environment; Family; Fathers; Frequencies; Genealogy; Generations; Genes; Genetic; Genetic Materials; Genetic Polymorphism; Genetic Recombination; Genetic Variation; Genome; Genomics; Genotype; Goals; Graph; Hereditary Disease; Human; Human Genome; Individual; Inherited; Location; Maps; Markov Chains; Meiosis; Methods; Modeling; Molecular Analysis; Monozygotic twins; Mothers; Mutation; Non-Insulin-Dependent Diabetes Mellitus; Outcome; Parents; Pattern; Play; Point Mutation; Population; Population Analysis; Population Genetics; Population Sizes; Predisposition; Probability; Research; Role; Sampling; Simulate; Single Nucleotide Polymorphism; Statistical Methods; Structure; Techniques; Technology; Variant; Work; base; computerized tools; disease transmission; egg; genetic variant; genome wide association study; genome-wide; genotyping technology; human data; human population genetics; improved; migration; new technology; novel; offspring; programs; public health relevance; simulation; sperm cell; tool; trait; transmission process

DESCRIPTION (provided by applicant): The proposed research will develop new statistical analysis methods and computer software for interpreting patterns of genetic variation in human populations. The genome of every human (apart from identical twins) is unique and genetic variation explains much of the variation of features observed among individuals including differences in behavior, disease susceptibility, physical appearance, etc. New technologies are providing vast amounts of information concerning subtle DNA variations among individuals in human populations. A common form of variation arises from single base-pair changes in the DNA sequence caused by point mutation; this involves an accidental insertion of a mismatched base during DNA replication. Point mutations occur at a very low rate but accumulate in the genetic material transmitted from parents to offspring over thousands of generations. DNA variants produced by point mutation are termed single-nucleotide polymorphisms (SNPs) and are an important genetic component of individual variation. High-throughput molecular analysis technologies can produce "genotypes" for millions of SNPs spread over the genome of an individual. The genotype refers to the combination of SNPs on chromosomes inherited from the mother and father. Patterns of SNPs on individual chromosomes are determined mainly by recombination -- exchanges of DNA segments between chromosomes during meiosis (transmission to eggs or sperm). The proposed research will develop computational tools to infer rates of chromosomal recombination on a fine scale. Complex genetic diseases (Crohn disease, for example) are relatively common and are thought to result from the combined effects of environment and genetics. Family-based disease transmission studies, which have worked well to locate genes causing simple genetic diseases (e.g., cystic fibrosis), have low power to locate genes influencing complex diseases. Another goal of the proposed research will be to provide statistical tools to locate genetic variants in the human genome that increase individual susceptibility to complex genetic disease, using as data population samples of SNPs from disease-affected cases and unaffected controls. PUBLIC HEALTH RELEVANCE: The proposed research will provide new statistical methods and computer software for interpreting data on human population genetic variation across the genome. Specifically, the proposed research will facilitate the development of a fine-scale map of local recombination rates over the human genome; recombination plays an important role in determining frequencies of occurrence of physical traits (and genetic diseases) in human populations. As well, the proposed research will provide new methods for locating genetic changes (mutations) in the human genome that increase individual susceptibility to complex genetic disease such as type II diabetes.

描述（由申请人提供）：拟议的研究将开发新的统计分析方法和计算机软件，以解释人群中遗传变异的模式。每个人的基因组（除了相同的双胞胎）是独特的，遗传变异解释了个体之间观察到的特征的大部分变化，包括行为差异，疾病敏感性，外观外观等。新技术正在提供大量有关人群中个体细微DNA变异的信息。变异的一种常见形式是由点突变引起的DNA序列的单基对变化。这涉及在DNA复制过程中意外插入不匹配的碱基。点突变的发生率很低，但积累了从父母传播到以上世代的后代的遗传物质中。通过点突变产生的DNA变异称为单核苷酸多态性（SNP），是个体变异的重要遗传成分。高通量分子分析技术可以生成数百万个SNP的“基因型”，分布在个体的基因组上。基因型是指SNP在父母继承的染色体上的结合。单个染色体上SNP的模式主要是通过重组来确定的 - 减数分裂过程中染色体之间的DNA片段交换（传播到卵或精子）。拟议的研究将开发计算工具，以精细的规模推断染色体重组的速率。复杂的遗传疾病（例如，克罗恩病）相对普遍，被认为是由环境和遗传学的综合作用引起的。基于家庭的疾病传播研究在定位引起简单遗传疾病（例如囊性纤维化）的基因方面效果很好，具有低功率来定位影响复杂疾病的基因。拟议的研究的另一个目标是提供统计工具来定位人类基因组中的遗传变异，以增加对复杂遗传疾病的易感性，并使用来自受疾病影响病例和未受影响的对照的SNP的数据总体样本。公共卫生相关性：拟议的研究将提供新的统计方法和计算机软件，以解释整个基因组人口遗传变异的数据。具体而言，拟议的研究将有助于开发人类基因组上局部重组率的细小图。重组在确定人群中物理特征（和遗传疾病）发生的频率中起着重要作用。同样，拟议的研究还将为人类基因组中定位遗传变化（突变）的新方法，以增加对复杂遗传疾病（例如II型糖尿病）的敏感性。