Linked Life Data

3870876

Source:http://linkedlifedata.com/resource/pubmed/id/3870876

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
1988-6-20
pubmed:abstractText
Simple but exact statistical tests for detecting a cluster of associated nucleotide changes in DNA are presented. The tests are based on the linear distribution of a set of s sites among a total of n sites, where the s sites may be the variable sites, sites of insertion/deletion, or categorized in some other way. These tests are especially useful for detecting gene conversion and intragenic recombination in a sample of DNA sequences. In this case, the sites of interest are those that correspond to particular ways of splitting the sequences into two groups (e.g., sequences A and D vs. sequences B, C, and E-J). Each such split is termed a phylogenetic partition. Application of these methods to a well-documented case of gene conversion in human gamma-globin genes shows that sites corresponding to two of the three observed partitions are significantly clustered, whereas application to hominoid mitochondrial DNA sequences--among which no recombination is expected to occur--shows no evidence of such clustering. This indicates that clustering of partition-specific sites is largely due to intragenic recombination or gene conversion. Alternative hypotheses explaining the observed clustering of sites, such as biased selection or mutation, are discussed.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0737-4038
pubmed:author
pubmed:issnType
Print
pubmed:volume
2
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
539-56
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
1985
pubmed:articleTitle
Statistical methods of DNA sequence analysis: detection of intragenic recombination or gene conversion.
pubmed:affiliation
Center for Demographic and Population Genetics, University of Texas, Houston 77225.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S.