GWAS, QTL, Linkage study 셋의 차이점

Linkage mapping/recombination mapping/positional cloning - rely on known markers (typically SNPs) that are close to the gene responsible for a disease or trait to segregate with that marker within a family. Works great for high-penetrance, single gene traits and diseases.

QTL mapping/interval mapping - for quantitative traits like height that are polygenic. Same as linkage mapping except the phenotype is continuous and the markers are put into a scoring scheme to measure their contribution - i.e. "marker effects" or "allelic contribution". Big in agriculture.

GWAS/linkage disequilibrium mapping - score thousands of SNPs at once from a population of unrelated individuals. Measure association with a disease or trait with the presumption that some markers are in LD with, or actually are, causative SNPs.

So linkage mapping and QTL mapping are similar in that they rely on Mendelian inheritance to isolate loci. QTL mapping and GWAS are similar in that they typically measure association in terms of log-odds along a genetic or physical map and do not assume one gene or locus is responsible. And finally, linkage mapping and GWAS are both concerned with categorical traits and diseases.

Linkage Study : 가족데이터 - 멘델 유전 이용, 알려진 마커로 high-penetrance, single gene disease 멘델리안 질병에 대해서 연구

QTL : 가족데이터 - 멘델 유전 이용, polygenic & quantitative trait (ex. height)

GWAS : 인구집단 데이터 - LD를 이용, polygenic, categorical trait 둘다