Computational Tools For Complex Trait Gene Mapping

Pacific Symposium on Biocomputing 2004

FM De La Vega ; KK Kidd ; A Collins

PID  :  13962

来源: CEUR

【 摘 要 】

The mappingof thegenes underlying complex traitsposesspecialchallenges. Theresultsofseveral years ofeffort bymanygroupsintheextensionofthe linkage mapping methods, used with great effect for localizing majorgenes,hasbeendisappointingonthewholeforcomplextraits.Nowthatwehavean effectivelycompletegenomesequenceandexcitingnewtechnologiesfor genotypingvastnumbersofsinglenucleotide polymorphisms(SNPs) theway isopenfortheadvanceofanewstrategy.Therehavealreadybeenseveral successful outcomesfor complex trait mapping through theanalysisof linkage disequilibrium (LD) and haplotypes. However, these are early daysandsomeofthe difficulties are only slowly becoming apparent. Recent evidence[1]suggests that the human genome may contain up to 15 million SNPs. For thisreason the probabilityofactuallyincludingadiseasecausalSNPinasampleofSNPstyped at a spacing of several kilobases is low. Furthermore, thisimpliesthatup to 100other SNPsmaybe inlinkagedisequilibriumwitha causal SNP.This posesmajordifficultiesforidentifyingacausalsitebuttheinitialtargetis simplytodeterminecandidateregionswithconfidence.TheInternational HapMap project [2] has the aimofdelimitinghaplotypeblocks inanumber of populationstogenerate agenome-wide SNPmapforassociationstudies.Oneoutcomeof thisproject willbe a largebodyofempiricaldataonpatternsof linkagedisequilibriumacrossthehumangenome.Othergroupsand organizations are involved intheirowndata collection andevaluationstudies. Aspectsoftheeffectivecollection,representationanduseofthesevastand developingdataresourcesarethetopicsofthesixpapersincludedinthis volume.[First Paragraph]