Stat 246 Lecture 2 Part A An quick overview of human genetic linkage analysis Purpose of human linkage analysis To obtain a crude chromosomal location of the gene or genes associated with a phenotype of interest e g a genetic disease or an important quantitative trait Examples cystic fibrosis found diabetes multiple sclerosis and blood pressure Linkage Strategies Traditional from the 1980s or earlier Linkage analysis on pedigrees Allele sharing methods candidate genes genome screen Association studies candidate genes Animal models identifying candidate genes Newer from the 1990s Focus on special populations Finland Hutterites Haplotype sharing many variants Congenic consomic lines in mice new for complex traits Linkage analysis Allele sharing methods Association Studies Animal Models Linkage Strategies II On the horizon here Single nucleotide polymorphism SNPs Functional analyses finding candidate genes Needed starting to happen New multilocus analysis techniques especially Ways of dealing with large pedigrees Better phenotypes ones closer to gene products Large collaborations Horses for courses Each of these strategies has its domain of applicability Each of them has a different theoretical basis and method of analysis Which is appropriate for mapping genes for a disease of interest depends on a number of matters most importantly the disease and the population from which the sample comes The disease matters Definition phenotype prevalence features such as age of onset Genetics nature of genes resistance susceptibility number of genes nature of their contributions additive interacting size of effect Environment other relevant variables e g sex Genotype by environment interactions The population matters History pattern of growth immigration Composition homogeneous or melting pot or in between Mating patterns family sizes mate choice level of consanguinity Frequencies of disease related alleles and of marker alleles Ages of disease related alleles Complex traits Definition vague but usually thought of as having multiple possibly interacting loci with unknown penetrances and phenocopies The terms polygenic and oligogenic are also used but these do have more specific meanings There is some evidence that using a range of made up models can help map genes for complex traits but no one really knows Affected only methods are widely used with variance component methods becoming popular The jury is still out on which if any will succeed Few success stories so far Important heart disease cancer susceptibility diabetes are all complex traits Design of gene mapping studies How good are your data implying a genetic component to your trait Can you estimate the size of the genetic component Have you got or will you eventually have enough of the right sort of data to have a good chance of getting a definitive result Power studies Simulations Genotyping Choice of markers highly polymorphic preferred Heterozygosity and PIC value are the measures commonly used Reliability of markers important too Good quality data critical errors can play a surprisingly large role Preparing genotype data for analysis Data cleaning is the big issue here Need much ancillary data how good is it Analysis A very large range of methods programs are available Effort to understand their theory will pay off in leading to the right choice of analysis tools Trying everything is not recommended but not uncommon Many opportunities for innovation Interpretation of results of analysis An important issue here is whether you have established linkage The standards seem to be getting increasingly stringent What p value or LOD should you use Dealing with multiple testing especially in the context of genome scans and the use of multiple models and multiple phenotypes is one of the big issues Replication of results This has recently become a big issue with complex diseases especially in psychiatry Nature Genetics suggested in May 1998 that they will require replication before publishing results mapping complex traits Simulations by Suarez et al 1994 show that sample sizes necessary for replication may be substantially greater than that needed for first detection Topics not mentioned Sex linked traits sex specific recombination fractions liability classes mutations genetic heterogeneity exclusion mapping homozygosity mapping interference variance component methods twin studies and much more Some of these topics plus the ones are covered in two books Handbook of Human Genetic Linkage by J D Terwilliger J Ott 1994 Johns Hopkins University Press Analysis of Human Genetic Linkage by J Ott 3rd Edition 1999 Johns Hopkins University Press
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