Department of Plant Sciences, University of California, Davis, CA 95516, USA.
BMC Genomics. 2010 Dec 6;11:692. doi: 10.1186/1471-2164-11-692.
A five-dimensional (5-D) clone pooling strategy for screening of bacterial artificial chromosome (BAC) clones with molecular markers utilizing highly-parallel Illumina GoldenGate assays and PCR facilitates high-throughput BAC clone and BAC contig anchoring on a genetic map. However, this strategy occasionally needs manual PCR to deconvolute pools and identify truly positive clones.
A new implementation is reported here for our previously reported clone pooling strategy. Row and column pools of BAC clones are divided into sub-pools with 1~ 2 x genome coverage. All BAC pools are screened with Illumina's GoldenGate assay and the BAC pools are deconvoluted to identify individual positive clones. Putative positive BAC clones are then further analyzed to find positive clones on the basis of them being neighbours in a contig. An exhaustive search or brute force algorithm was designed for this deconvolution and integrated into a newly developed software tool, FPCBrowser, for analyzing clone pooling data. This algorithm was used with empirical data for 55 Illumina GoldenGate SNP assays detecting SNP markers mapped on Aegilops tauschii chromosome 2D and Ae. tauschii contig maps. Clones in single contigs were successfully assigned to 48 (87%) specific SNP markers on the map with 91% precision.
A new implementation of 5-D BAC clone pooling strategy employing both GoldenGate assay screening and assembled BAC contigs is shown here to be a high-throughput, low cost, rapid, and feasible approach to screening BAC libraries and anchoring BAC clones and contigs on genetic maps. The software FPCBrowser with the integrated clone deconvolution algorithm has been developed and is downloadable at http://avena.pw.usda.gov/wheatD/fpcbrowser.shtml.
利用高通量 Illumina GoldenGate 分析和 PCR，针对带有分子标记的细菌人工染色体（BAC）克隆进行 5 维（5-D）克隆池筛选，这是一种克隆池筛选策略，可促进 BAC 克隆和 BAC 重叠群在遗传图谱上的高通量锚定。然而，这种策略偶尔需要进行手动 PCR 以解析池并鉴定真正的阳性克隆。
本文报道了我们之前报道的克隆池筛选策略的一种新实现。将 BAC 克隆的行和列池划分为具有 1~2 倍基因组覆盖度的亚池。所有 BAC 池均用 Illumina 的 GoldenGate 分析进行筛选，然后对 BAC 池进行解析，以鉴定单个阳性克隆。然后，对推定的阳性 BAC 克隆进行进一步分析，根据它们在重叠群中的邻接关系找到阳性克隆。设计了一种穷举搜索或暴力算法用于这种解析，并将其集成到一个新开发的软件工具 FPCBrowser 中，用于分析克隆池数据。该算法与用于检测映射到 Ae. tauschii 染色体 2D 和 Ae. tauschii 重叠群图谱上的 SNP 标记的 55 个 Illumina GoldenGate SNP 分析的经验数据一起使用。在图谱上，成功地将单个重叠群中的克隆分配给了 48 个（87%）特定 SNP 标记，精度为 91%。
本文展示了一种新的 5-D BAC 克隆池筛选策略的实现，该策略结合了 GoldenGate 分析筛选和组装的 BAC 重叠群，是一种高通量、低成本、快速且可行的筛选 BAC 文库和将 BAC 克隆和重叠群锚定在遗传图谱上的方法。带有集成克隆解析算法的软件 FPCBrowser 已开发完成并可在 http://avena.pw.usda.gov/wheatD/fpcbrowser.shtml 下载。
