Department of Plant Biology and Genome Center, University of California, Davis, California 95616, USA.
Plant Physiol. 2011 Jul;156(3):1257-68. doi: 10.1104/pp.110.169748. Epub 2011 Apr 29.
Discovery of rare mutations in populations requires methods, such as TILLING (for Targeting Induced Local Lesions in Genomes), for processing and analyzing many individuals in parallel. Previous TILLING protocols employed enzymatic or physical discrimination of heteroduplexed from homoduplexed target DNA. Using mutant populations of rice (Oryza sativa) and wheat (Triticum durum), we developed a method based on Illumina sequencing of target genes amplified from multidimensionally pooled templates representing 768 individuals per experiment. Parallel processing of sequencing libraries was aided by unique tracer sequences and barcodes allowing flexibility in the number and pooling arrangement of targeted genes, species, and pooling scheme. Sequencing reads were processed and aligned to the reference to identify possible single-nucleotide changes, which were then evaluated for frequency, sequencing quality, intersection pattern in pools, and statistical relevance to produce a Bayesian score with an associated confidence threshold. Discovery was robust both in rice and wheat using either bidimensional or tridimensional pooling schemes. The method compared favorably with other molecular and computational approaches, providing high sensitivity and specificity.
在群体中发现罕见突变需要使用 TILLING(靶向诱导基因组局部突变)等方法,以便同时处理和分析许多个体。以前的 TILLING 方案采用酶或物理方法区分异源双链体与同源双链体靶 DNA。利用水稻(Oryza sativa)和小麦(Triticum durum)的突变群体,我们开发了一种基于 Illumina 测序的方法,从多维汇集模板中扩增目标基因,每个实验代表 768 个个体。通过独特的示踪序列和条形码辅助测序文库的并行处理,可灵活调整靶向基因、物种和汇集方案的数量和汇集排列。对测序读取进行处理和比对到参考序列,以识别可能的单核苷酸变化,然后评估其频率、测序质量、在池中的交点模式以及统计相关性,以生成具有相关置信度阈值的贝叶斯分数。使用二维或三维汇集方案,在水稻和小麦中均能稳健地发现突变。该方法与其他分子和计算方法相比具有较高的灵敏度和特异性。