韓國首爾大學(xué)基因醫(yī)學(xué)研究所徐廷瑄教授領(lǐng)導(dǎo)的研究小組宣稱,，他們通過對30名中國人、韓國人和日本人的基因組研究,，成功繪制出中日韓人種超高清基因拷貝數(shù)變異圖譜,，并根據(jù)該圖譜發(fā)現(xiàn)，亞洲人獨(dú)有的基因拷貝數(shù)變異共有3500多個(gè),。
所謂基因拷貝數(shù)變異(Copy Number Vriations)是指在人類基因組中廣泛存在的,，從1000bp(堿基對)到數(shù)百萬bp范圍內(nèi)的缺失、插入,、重復(fù)和復(fù)雜多位點(diǎn)的變異,。研究表明，不少人類復(fù)雜性狀疾病都和拷貝數(shù)變異有密切關(guān)系,。
2006年,，第一張人類基因組第一代基因拷貝數(shù)變異圖譜問世。這張遺傳圖譜是通過對歐洲,、非洲和亞洲祖先4個(gè)人群的270個(gè)個(gè)體樣品進(jìn)行分析,，用兩個(gè)互補(bǔ)的技術(shù)——單核苷酸多態(tài)性(SNPs)基因分型和以克隆為基礎(chǔ)的比較基因組雜交進(jìn)行基因拷貝數(shù)變異篩選，獲得了一共1447個(gè)拷貝數(shù)變異,。
之后的一系列研究顯示,，基因拷貝數(shù)變異是個(gè)體之間在基因組序列差異上的一個(gè)重要源泉，是研究基因組進(jìn)化和表型差異的一個(gè)重要因素,。許多關(guān)于基因拷貝數(shù)變異的研究結(jié)果表明，拷貝數(shù)變異可導(dǎo)致不同程度的基因表達(dá)差異,，對正常表型的構(gòu)成及疾病的發(fā)生發(fā)展具有一定作用,。拷貝數(shù)變異研究在法醫(yī)學(xué)方面也具有重要意義,，在探索法醫(yī)學(xué)個(gè)體識別的遺傳變異時(shí)不能忽略拷貝數(shù)變異這一基因組多樣性的新形式,。
首爾大學(xué)醫(yī)學(xué)院此次繪制的基因拷貝數(shù)變異圖譜與西方繪制的現(xiàn)有圖譜不同，是只針對中日韓人種進(jìn)行研究并繪制完成的,，將有效適用于特定人群的疾病診療,，并為今后正式研究基因拷貝數(shù)變異和疾病之間的關(guān)聯(lián)性提供了良好平臺。
當(dāng)?shù)谝粡埲祟惢蚪M草圖問世時(shí),，我們對這一劃時(shí)代的成就充滿期待,，渴望它在醫(yī)學(xué)診斷、預(yù)防和治療方面，能夠迅速兌現(xiàn)基因組研究的初衷,。10年過去了，我們發(fā)現(xiàn)那不過是生命科學(xué)這部天書的扉頁,?；蚪M測序現(xiàn)已不算難事，科學(xué)家面臨的更大挑戰(zhàn),，是從浩繁的基因組序列中找到惠及健康的有用信息,。或許,，研究基因拷貝數(shù)變異,，我們才翻到了這部天書的某一章節(jié)。(生物谷Bioon.com)
生物谷推薦原文出處：
Human Molecular Genetics doi:10.1093/hmg/ddp564
Copy number variations in East-Asian population and their evolutionary and functional implications
Seon-Hee Yim1,3,, Tae-Min Kim1,2,, Hae-Jin Hu1,2, Ji-Hong Kim1,2, Bong-Jo Kim4, Jong-Young Lee4, Bok-Ghee Han4, Seung-Hun Shin1,2, Seung-Hyun Jung1,2 and Yeun-Jun Chung1,2,*
Recent discovery of the copy number variation (CNV) in normal individuals has widened our understanding of genomic variation. However, most of the reported CNVs have been identified in Caucasians, which may not be directly applicable to people of different ethnicities. To profile CNV in East-Asian population, we screened CNVs in 3578 healthy, unrelated Korean individuals, using the Affymetrix Genome-Wide Human SNP array 5.0. We identified 144 207 CNVs using a pooled data set of 100 randomly chosen Korean females as a reference. The average number of CNVs per genome was 40.3, which is higher than that of CNVs previously reported using lower resolution platforms. The median size of CNVs was 18.9 kb (range 0.2–5406 kb). Copy number losses were 4.7 times more frequent than copy number gains. CNV regions (CNVRs) were defined by merging overlapping CNVs identified in two or more samples. In total, 4003 CNVRs were defined encompassing 241.9 Mb accounting for 8% of the human genome. A total of 2077 CNVRs (51.9%) were potentially novel. Known CNVRs were larger and more frequent than novel CNVRs. Sixteen percent of the CNVRs were observed in 1% of study subjects and 24% overlapped with the OMIM genes. A total of 476 (11.9%) CNVRs were associated with segmental duplications. CNVS/CNVRs identified in this study will be valuable resources for studying human genome diversity and its association with disease.
