Genetic Analysis: An Integrated Approach (2nd Edition)
Genetic Analysis: An Integrated Approach (2nd Edition)
2nd Edition
ISBN: 9780321948908
Author: Mark F. Sanders, John L. Bowman
Publisher: PEARSON
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Chapter 21, Problem 19P
Summary Introduction

To analyze:

The aim of GWAS (Genome wide association studies) is to locate chromosome regions containing the genes influencing the risk of disease, when applied to the study of the human genome. Unique articular genes can be identified in these regions; especially mutant alleles that intensify disease risk are to be sequenced. So far, the recognition of these alleles occasionally led to a new therapeutic strategy, but more frequently the identification of disease alleles is the only outcome.

a. From a physician’s perspective, describe the importance of identification of these alleles that increase the risk of a specific disease.

b. Explain the importance of identifying alleles that increase disease risk for a person who is currently free of the disease but what about the persons having pre-disposal of this disease that is running in the family.

c. Describe the personal or ethical issues occured from GWAS, might be of concern to physicians or to those who may carry an allele that increases the risk of disease.

Introduction:

GWAS is designed for the detection and location of the genes that influence the appearance of the trait by multiple genes. These multiple genes responsible for a particular trait are dispersed throughout the genome. Hence, the GWAS helps to locate the particular gene in the genome.

GWAS does not create any gene map of a chromosome rather it finds the association of traits and the groups of alleles to locate these influencing genes on different chromosomes.

In the GWAS, the term association refers to the trait co-occurs with group of alleles more often than expected.

The GWAS connects the presence of DNA marker having sequence variation with quantitative trait loci (QTL) affecting the particular phenotype. GWAS scans the entire genome to locate the QTL by statistical analysis.

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