Sammalisto S, Hiekkalinna T, Suviolahti E, Sood K, Metzidis A, Pajukanta P, Lilja H E, Soro-Paavonen A, Taskinen M-R, Tuomi T, Almgren P, Orho-Melander M, Groop L, Peltonen L, Perola M
Department of Molecular Medicine, National Public Health Institute, Helsinki, Finland.
J Med Genet. 2005 Dec;42(12):932-9. doi: 10.1136/jmg.2005.031278. Epub 2005 Apr 12.
Many genome-wide scans aimed at complex traits have been statistically underpowered due to small sample size. Combining data from several genome-wide screens with comparable quantitative phenotype data should improve statistical power for the localisation of genomic regions contributing to these traits.
To perform a genome-wide screen for loci affecting adult stature by combined analysis of four previously performed genome-wide scans.
We developed a web based computer tool, Cartographer, for combining genetic marker maps which positions genetic markers accurately using the July 2003 release of the human genome sequence and the deCODE genetic map. Using Cartographer, we combined the primary genotype data from four genome-wide scans and performed variance components (VC) linkage analyses for human stature on the pooled dataset of 1417 individuals from 277 families and performed VC analyses for males and females separately.
We found significant linkage to stature on 1p21 (multipoint LOD score 4.25) and suggestive linkages on 9p24 and 18q21 (multipoint LOD scores 2.57 and 2.39, respectively) in males-only analyses. We also found suggestive linkage to 4q35 and 22q13 (multipoint LOD scores 2.18 and 2.85, respectively) when we analysed both females and males and to 13q12 (multipoint LOD score 2.66) in females-only analyses.
We strengthened the evidence for linkage to previously reported quantitative trait loci (QTL) for stature and also found significant evidence of a novel male-specific QTL on 1p21. Further investigation of several interesting candidate genes in this region will help towards characterisation of this first sex-specific locus affecting human stature.
由于样本量小，许多针对复杂性状的全基因组扫描在统计学上的效力不足。将来自几个全基因组筛查的数据与可比的定量表型数据相结合，应该会提高定位影响这些性状的基因组区域的统计效力。
通过对四项先前进行的全基因组扫描进行联合分析，对影响成人身高的基因座进行全基因组筛查。
我们开发了一个基于网络的计算机工具Cartographer，用于合并遗传标记图谱，该工具利用2003年7月发布的人类基因组序列和deCODE遗传图谱准确地定位遗传标记。使用Cartographer，我们合并了四项全基因组扫描的原始基因型数据，并对来自277个家庭的1417名个体的汇总数据集进行了人类身高的方差成分（VC）连锁分析，并分别对男性和女性进行了VC分析。
在仅针对男性的分析中，我们发现1p21与身高有显著连锁（多点LOD得分4.25），在9p24和18q21有提示性连锁（多点LOD得分分别为2.57和2.39）。在对男性和女性进行联合分析时，我们还发现与4q35和22q13有提示性连锁（多点LOD得分分别为2.18和2.85），在仅针对女性的分析中发现与13q12有提示性连锁（多点LOD得分2.66）。
我们加强了与先前报道的身高数量性状基因座（QTL）连锁的证据，并且还发现了1p21上一个新的男性特异性QTL的显著证据。对该区域几个有趣的候选基因进行进一步研究将有助于鉴定这个影响人类身高的首个性别特异性基因座。
