Enhanced Linkage Maps From Family-Based Genetics Studies
Abstract
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.
Manuscript is currently in preparation.
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Principal Investigators:
Tara C. Matise, Ph.D. Rutgers University
Daniel Weeks, Ph.D. University of Pittsburgh
Chunsheng He Rockefeller University