Background: Targeting Induced Local Lesions in Genomes (TILLING) is a powerful reverse genetics approach for functional genomics studies. We used high-throughput sequencing, combined with a two-dimensional pooling strategy, with either minimum read percentage with non-reference nucleotide or minimum variance multiplier as mutation prediction parameters, to detect genes related to abiotic and biotic stress resistances. In peanut, lipoxygenase genes were reported to be highly induced in mature seeds infected with Aspergillus spp., indicating their importance in plant-fungus interactions. Recent studies showed that phospholipase D (PLD) expression was elevated more quickly in drought sensitive lines than in drought tolerant lines of peanut. A newly discovered lipoxygenase (LOX) gene in peanut, along with two peanut PLD genes from previous publications were selected for TILLING. Additionally, two major allergen genes Ara h 1 and Ara h 2, and fatty acid desaturase AhFAD2, a gene which controls the ratio of oleic to linoleic acid in the seed, were also used in our study. The objectives of this research were to develop a suitable TILLING by sequencing method for this allotetraploid, and use this method to identify mutations induced in stress related genes.
Results: We screened a peanut root cDNA library and identified three candidate LOX genes. The gene AhLOX7 was selected for TILLING due to its high expression in seeds and roots. By screening 768 M2 lines from the TILLING population, four missense mutations were identified for AhLOX7, three missense mutations were identified for AhPLD, one missense and two silent mutations were identified for Ara h 1.01, three silent and five missense mutations were identified for Ara h 1.02, one missense mutation was identified for AhFAD2B, and one silent mutation was identified for Ara h 2.02. The overall mutation frequency was 1 SNP/1,066 kb. The SNP detection frequency for single copy genes was 1 SNP/344 kb and 1 SNP/3,028 kb for multiple copy genes.
Conclusions: Our TILLING by sequencing approach is efficient to identify mutations in single and multi-copy genes. The mutations identified in our study can be used to further study gene function and have potential usefulness in breeding programs.