Department of Anthropology, University of Illinois Urbana-Champaign, Urbana, Illinois, United States of America.
PLoS One. 2007 May 9;2(5):e438. doi: 10.1371/journal.pone.0000438.
We developed a novel method for identifying SNPs widely distributed throughout the coding and non-coding regions of a genome. The method uses large-scale parallel pyrosequencing technology in combination with bioinformatics tools. We used this method to generate approximately 23,000 candidate SNPs throughout the Macaca mulatta genome. We estimate that over 60% of the SNPs will be of high frequency and useful for mapping QTLs, genetic management, and studies of individual relatedness, whereas other less frequent SNPs may be useful as population specific markers for ancestry identification. We have created a web resource called MamuSNP to view the SNPs and associated information online. This resource will also be useful for researchers using a wide variety of Macaca species in their research.
我们开发了一种新的方法,用于鉴定广泛分布于基因组编码区和非编码区的 SNPs。该方法结合了大规模平行焦磷酸测序技术和生物信息学工具。我们使用这种方法在恒河猴基因组中生成了大约 23000 个候选 SNPs。我们估计,超过 60%的 SNPs 将是高频的,可用于定位 QTL、遗传管理和个体亲缘关系的研究,而其他低频的 SNPs 可能作为特定于群体的祖先识别标记有用。我们创建了一个名为 MamuSNP 的网络资源,可在线查看 SNPs 和相关信息。这个资源对于在研究中使用多种恒河猴物种的研究人员也将是有用的。