Linked Life Data

10613838

Source:http://linkedlifedata.com/resource/pubmed/id/10613838

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2000-1-27
pubmed:abstractText
One approach to sequencing a large genome is (1) to sequence a collection of nonoverlapping "seeds" chosen from a genomic library of large-insert clones [such as bacterial artificial chromosomes (BACs)] and then (2) to take successive "walking" steps by selecting and sequencing minimally overlapping clones, using information such as clone-end sequences to identify the overlaps. In this paper we analyze the strategic issues involved in using this approach. We derive formulas showing how two key factors, the initial density of seed clones and the depth of the genomic library used for walking, affect the cost and time of a sequencing project-that is, the amount of redundant sequencing and the number of steps to cover the vast majority of the genome. We also discuss a variant strategy in which a second genomic library with clones having a somewhat smaller insert size is used to close gaps. This approach can dramatically decrease the amount of redundant sequencing, without affecting the rate at which the genome is covered.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1088-9051
pubmed:author
pubmed:issnType
Print
pubmed:volume
9
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1163-74
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Sequencing a genome by walking with clone-end sequences: a mathematical analysis.
pubmed:affiliation
Laboratory for Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't