PubMed Health⌕ Search

PubMed · 12446985

Map error reduction: using genetic and sequence-based physical maps to order closely linked markers.

Abstract

The Marshfield comprehensive genetic maps are frequently used for linkage and association studies, however, for some regions of these maps the marker order has low level of likelihood ratio support. In order to investigate the level of statistical support and the accuracy of the genetic maps compared to sequence-based physical maps, two approximately 30 cM autosomal regions were selected. The first region was selected from chromosome 3 and consisted predominately of draft sequence. The second region was selected from chromosome 21 and consisted of finished sequence data. The physical order of these markers was based upon their position on Celera (CEL) and Human Genome Project-Santa Cruz (HGP-sc) sequence-based physical maps. The chromosome 3 and 21 regions contained 100 and 61 markers, respectively, on the Marshfield genetic map. The genetic and physical map order was consistent for 88.9 and 89.2% of the markers in the region on chromosome 3 and 21, respectively. Using a novel scoring criterion to assess inconsistent marker order between genetic and physical maps, it was determined that the physical order was likely the correct order for 3.3 and 7.1% of the markers in the chromosome 3 and 21 regions, respectively. To increase the accuracy of the order of markers selected for fine mapping a method is presented which combines information from genetic and sequence-based physical maps.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Andrew T DeWan, Antonio R Parrado, Tara C Matise, Suzanne M Leal. 2002. Map error reduction: using genetic and sequence-based physical maps to order closely linked markers.. https://doi.org/10.1159/000066697

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Statistical test to compare the linkage model and the admixture model based on central limit results.

In the Admixture Model, the probability that an individual carries a certain allele at a specific marker depends on the allele frequencies in K ancestral populations and the proportion of the individual's genome originating from these populations. The markers are assumed to be independent. The Linkage Model is a Hidden Markov Model that extends the Admixture Model by incorporating linkage between neighboring loci. We prove consistency and asymptotic normality of maximum likelihood estimators for the ancestry of individuals in the Linkage Model, complementing earlier results by (Pfaff et al., 2004; Pfaffelhuber and Rohde, 2022; Heinzel, 2025) for the Admixture Model. These results are used to prove that a statistical test that allows for model selection between the Admixture Model and the Linkage Model is an asymptotic level-α-test. Finally, we demonstrate the practical relevance of our results by applying the test to real-world data from The 1000 Genomes Project Consortium (2015).

Genetic Linkage↗

The molecular genetics of schizophrenia: new findings promise new insights.

The high heritability of schizophrenia has stimulated much work aimed at identifying susceptibility genes using positional genetics. However, difficulties in obtaining clear replicated linkages have led to the scepticism that such approaches would ever be successful. Fortunately, there are now signs of real progress. Several strong and well-established linkages have emerged. Three of the best-supported regions are 6p24-22, 1q21-22 and 13q32-34. In these cases, single studies achieved genome-wide significance at P<0.05 and suggestive positive findings have also been reported in other samples. The other promising regions include 8p21-22, 6q21-25, 22q11-12, 5q21-q33, 10p15-p11 and 1q42. The study of chromosomal abnormalities in schizophrenia has also added to the evidence for susceptibility loci at 22q11 and 1q42. Recently, evidence implicating individual genes within some of the linked regions has been reported and more importantly replicated. The weight of evidence now favours NRG1 and DTNBP1 as susceptibility loci, though work remains before we understand precisely how genetic variation at each locus confers susceptibility and protection. The evidence for catechol-O-methyl transferase, RGS4 and G72 is promising but not yet persuasive. While further replications remain the top priority, the respective contributions of each gene, relationships with aspects of the phenotype, the possibility of epistatic interactions between genes and functional interactions between the gene products will all need investigation. The ability of positional genetics to implicate novel genes and pathways will open up new vistas for neurobiological research, and all the signs are that it is now poised to deliver crucial insights into the nature of schizophrenia.

Genetic Linkage↗