EMAIL - a highly sensitive tool for specific mutation detection in plant improvement programs

TILLING (Targeting Induced Local Lesions IN Genomes) is a useful tool for discovery of specific point mutations in genes of interest to plant breeders. It employs mismatch cleavage detection using endonucleases, particularly CELI and CELII. During PCR annealing, dsDNA heteroduplexes arise in pooled genomic DNA samples containing one or more Single Nucleotide Polymorphisms (SNP) resulting from, for instance, induced mutation. The cleaved fragments can be distinguished from the larger perfectly-matched homoduplex DNA of the unmutated wild types in the sample of pooled individuals. The ability to efficiently detect individuals with specific mutations within pooled samples provides plant breeders with a powerful screening tool to greatly reduce the numbers of plants requiring phenotypic assessment. Further, it enables geneticists to analyse gene function and associate genotype with phenotype. Such protocols suffer from limited ability to detect mismatch cleavage signal due to non-specific removal, by the nuclease, of 5’ end-labelled termini used in the conventional approach. Mutation detection is further limited by high background characteristic of PCR-based end-labelling mismatch scanning techniques. We showed that as nuclease activity increased, internal signal was maintained while 5’ signal decayed. Furthermore, internal labelling improved background. The loss of end-signal constitutes a fundamental problem with the conventional approach to mismatch scanning with CEL nucleases. A new mismatch scanning assay called ‘Endonucleolytic Mutation Analysis by Internal Labelling’ (EMAIL), was developed using capillary electrophoresis, involving internal amplicon labelling by PCR incorporation of fluorescently-labelled deoxynucleotides. Multiple mutations amongst allelic pools have been detected when EMAIL was applied with the mismatch nucleases CELI and CELII. This technique offers greatly increased sensitivity in specific-gene mutant detection in pooled samples, enabling enlarged pool sizes and improving throughput and efficiency. We are investigating the limits of pool sizes to deliver a highly efficient mutation detection and analysis strategy for plant breeders and geneticists.