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Discovery of rare mutations in populations: TILLING by sequencing
Authors:Tsai Helen  Howell Tyson  Nitcher Rebecca  Missirian Victor  Watson Brian  Ngo Kathie J  Lieberman Meric  Fass Joseph  Uauy Cristobal  Tran Robert K  Khan Asif Ali  Filkov Vladimir  Tai Thomas H  Dubcovsky Jorge  Comai Luca
Affiliation:Department of Plant Biology and Genome Center (H.T., T.H., B.W., K.J.N., M.L., R.K.T., A.A.K., L.C.), Department of Plant Sciences (R.N., C.U., T.H.T., J.D.), Department of Computer Sciences (V.M., V.F.), Bioinformatics Core, Genome Center (J.F.), and United States Department of Agriculture Agricultural Research Service, Crops Pathology and Genetics Research Unit (T.H.T.), University of California, Davis, California 95616
Abstract: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.
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