Zhu Mengjin, Zhao Shuhong
Key Laboratory of Agricultural Animal Genetics, Breeding, Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, PR China.
Int J Biol Sci. 2007 Oct 25;3(7):420-7. doi: 10.7150/ijbs.3.420.
Although it has been widely applied in identification of genes responsible for biomedically, economically, or even evolutionarily important complex and quantitative traits, traditional candidate gene approach is largely limited by its reliance on the priori knowledge about the physiological, biochemical or functional aspects of possible candidates. Such limitation results in a fatal information bottleneck, which has apparently become an obstacle for further applications of traditional candidate gene approach on many occasions. While the identification of candidate genes involved in genetic traits of specific interest remains a challenge, significant progress in this subject has been achieved in the last few years. Several strategies have been developed, or being developed, to break the barrier of information bottleneck. Recently, being a new developing method of candidate gene approach, digital candidate gene approach (DigiCGA) has emerged and been primarily applied to identify potential candidate genes in some studies. This review summarizes the progress, application software, online tools, and challenges related to this approach.
尽管传统的候选基因方法已广泛应用于鉴定与生物医学、经济或甚至进化上重要的复杂和数量性状相关的基因,但其很大程度上受到对可能候选基因的生理、生化或功能方面的先验知识的依赖所限制。这种限制导致了致命的信息瓶颈,这显然在许多情况下已成为传统候选基因方法进一步应用的障碍。虽然鉴定涉及特定感兴趣遗传性状的候选基因仍然是一项挑战,但在过去几年中该领域已取得了重大进展。已经或正在开发几种策略来打破信息瓶颈的障碍。最近,作为候选基因方法的一种新的发展方法,数字候选基因方法(DigiCGA)已经出现,并在一些研究中主要用于鉴定潜在的候选基因。本综述总结了与该方法相关的进展、应用软件、在线工具和挑战。