Enhanced Linkage Maps




Enhanced Linkage Maps From Family-Based Genetics Studies


Background

Accurate genetic maps are required for successful and efficient linkage mapping of disease genes. However, most available genome-wide genetic maps were built using only small collections of pedigrees, and therefore have large sampling errors. A large set of genetic studies genotyped by the NHLBI Mammalian Genotyping Service (MGS) provide appropriate data for generating more accurate maps.

Results

We collected a large sample of genotype data generated by the MGS using the Weber screening sets 9 and 10. This collection includes genotypes for over 4,400 pedigrees containing over 17,000 genotyped individuals from different populations. We identified and cleaned numerous relationship and genotyping errors, as well as verified the marker orders. We used this dataset to: a) test for population-specific distribution of recombination; and b) re-estimate the genetic map distances (with standard errors). The map-interval sizes from the European (or European descent), Chinese, and Hispanic samples are in quite good agreement with each other. We found one map interval on chromosome 8p with a statistically significant difference in size between the European and Chinese samples, and several map intervals with significant size differences between the maps of the African-American and Chinese samples. When comparing Palauan with European samples, a statistically significant difference was detected at the telomeric region of chromosome 11p. Several significant differences were also identified between populations in chromosomal and genome lengths.

Conclusions

Our analyses result in population-specific screening set maps with improved accuracy, which can in turn be used to improve the accuracy of disease-mapping studies. As a result of the large sample size, the 95% CI for a 10 cM map interval in our map is only 2.4 cM, considerably smaller than in previously published maps.

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Principal Investigators


© 2014 Matise Laboratory of Computational Genetics
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