The figure below shows the pedigree of a family for a completely penetrant, auto
ID: 36556 • Letter: T
Question
The figure below shows the pedigree of a family for a completely penetrant, autosomal dominant disease, together with the corresponding genotype of each individual for four microsatellite loci. The four microsatellite loci are not linked.
What hypothesis or hypotheses can you propose about the linkage relationships between the microsatellite loci and the putative disease gene? Describe how you could go about testing your hypothesis. I do not want any calculations in your answer for this question
The figure below shows the pedigree of a family for a completely penetrant, autosomal dominant disease, together with the corresponding genotype of each individual for four microsatellite loci. The four microsatellite loci are not linked. What hypothesis or hypotheses can you propose about the linkage relationships between the microsatellite loci and the putative disease gene? Describe how you could go about testing your hypothesis. I do not want any calculations in your answer for this questionExplanation / Answer
After genetic linkage has been identified for a complex disease, the next step is often fine-mapping by association analysis, using single-nucleotide polymorphisms (SNPs) within a linkage region. If a SNP shows evidence of association, it is useful to know whether the linkage result can be explained in part or in full by the candidate SNP. The genotype identity-by-descent sharing test (GIST) and linkage and association modeling in pedigrees (LAMP) are two methods that were specifically proposed to address this question. GIST determines whether there is significant correlation between family-specific weights, defined by the presence of a tentatively associated allele in affected siblings, and family-specific nonparametric linkage scores. LAMP constructs a pedigree likelihood function of the marker data conditional on the trait data, and implements three likelihood ratio tests to characterize the relationship between the candidate SNP and the disease locus.
The classic family-based transmission/disequilibrium test was proposed to test for association in the presence of linkage in family trios containing two parents and one affected offspring . This approach has been extended to other family structures . If a single-nucleotide polymorphism (SNP) shows evidence of association, a hypothesis of interest is whether the linkage result can be explained in part or in full by the candidate SNP.
For example, Bipolar disorder is a common, heritable mental illness characterized by recurrent episodes of mania and depression. Despite considerable effort to elucidate the genetic underpinnings of bipolar disorder, causative genetic risk factors remain elusive. A comprehensive genomic analysis of bipolar disorder in a large Old Order Amish pedigree was conducted. Microsatellite genotypes and high-density SNP-array genotypes of 388 family members were combined with whole genome sequence data for 50 of these subjects, comprising 18 parent-child trios. This study design permitted evaluation of candidate variants within the context of haplotype structure by resolving the phase in sequenced parent-child trios and by imputation of variants into multiple unsequenced siblings. Non-parametric and parametric linkage analysis of the entire pedigree as well as on smaller clusters of families identified several nominally significant linkage peaks, each of which included dozens of predicted deleterious variants. Close inspection of exonic and regulatory variants in genes under the linkage peaks using family-based association tests revealed additional credible candidate genes for functional studies and further replication in population-based cohorts. However, despite the in-depth genomic characterization of this unique, large and multigenerational pedigree from a genetic isolate, there was no convergence of evidence implicating a particular set of risk loci or common pathways. The striking haplotype and locus heterogeneity observed has profound implications for the design of studies of bipolar and other related disorders