Linked Life Data

10087191

Source:http://linkedlifedata.com/resource/pubmed/id/10087191

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
1999-5-24
pubmed:abstractText
Genetic association analysis of candidate regions where evidence of linkage has accumulated is becoming a key issue in the study of complex diseases. A high density of markers, at least one per centimorgan, is required to improve the chances of observing linkage disequilibrium with disease alleles. A recently available single nucleotide polymorphism (SNP) map designed to cover the whole genome provides an average density of one marker per 2 cM. In the present study we show that the number of markers can be approximately doubled in a selected region, thus reaching a density suitable for association studies, by applying a completely automated technique for polymorphism detection, denaturing high-performance liquid chromatography (DHPLC). A systematic search for SNPs was performed in the region 5ptel-q13, where weak but convergent evidence for linkage with multiple sclerosis has accumulated. Screening for polymorphisms was performed on 124 sequence tagged sites (STSs) in the 3'UTR ends of expressed sequence tags totaling about 30,000 bp. Thirty SNPs in 28 STSs were found with less than 10% overlap with the markers already detected in the same region. The data confirm the validity of the approach using DHPLC on expressed gene sequences tagged by a set of standard commercially available primers.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
0888-7543
pubmed:author
pubmed:copyrightInfo
Copyright 1999 Academic Press.
pubmed:issnType
Print
pubmed:day
15
pubmed:volume
56
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
247-53
pubmed:dateRevised
2009-11-19
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Identification by denaturing high-performance liquid chromatography of numerous polymorphisms in a candidate region for multiple sclerosis susceptibility.
pubmed:affiliation
Dipartimento di Scienze Mediche, Università di Torino, Novara, Italy. giordano@med.no.unipmn.it
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't