Abstract
BackgroundThe apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. >35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known MLH1 germ line mutation.MethodsQuality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.ResultsOn chromosome 3, in the MLH1-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the MLH1 region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the MLH1 region perfectly matched the mutation status of the family members.ConclusionWe developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.
Highlights
The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC
The Alohomora program [32] was used first to combine the genotype data generated with the single nucleotide polymorphism (SNP) arrays, and the pedigree and SNP information and secondly, to convert these data into the appropriate format for further analysis
We show that we can perform linkage analysis with high-density 10K SNP arrays in large families for which not all members could be genotyped
Summary
The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. We setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known MLH1 germ line mutation. The first HNPCC loci were mapped to chromosomes 2 and 3 using microsatellite markers [5,6] This eventually led to the identification of germ line mutations in MSH2 [7] and MLH1 [8], respectively. It is shown that first degree relatives of patients with colorectal cancer have a relative risk of 2.3 to develop the disease [15] This indicates that still some genes with strong or moderate effect on CRC development remain to be identified. Different linkage analysis studies revealed potentially interesting regions on chromosomes 3q, 9q, 11q, 14q, 15q and 22q [16,17,18,19,20]
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