Strategies for identification of mutations induced by carbon-ion beam irradiation in Arabidopsis thaliana by whole genome re-sequencing.

Heavy-ion beam irradiation is a powerful physical mutagen that has been used to create numerous mutant materials in plants. These materials are an essential resource for functional genomics research in the post-genome era. The advent of Next-Generation Sequencing (NGS) technology has promoted the study of functional genomics and molecular breeding. A wealth of information can be gathered from whole genome re-sequencing; however, understanding the molecular mutation profile at genome wide, as well as identifying causal genes for a given phenotype are big challenging issues for researchers. The huge outputs created by NGS make it difficult to capture key information. It is worthy to explore an effective and efficient data-sieving strategy for mutation scanning at whole genome scale. Re-sequencing data from one laboratory wild type (Columbia) and eleven M3 Arabidopsis thaliana lines derived from carbon-ion beam irradiation were used in present study. Both the number and different combinations of samples used for analysis affected the sieving results. The result indicated that using six samples was sufficient to filter out the shared mutation (background interference) sites as well as to identify the true mutation sites in the whole genome. The final number of candidate mutation sites could be further narrowed down by combining traditional rough map-based cloning. Our results demonstrated the feasibility of a parallel sequencing analysis as an efficient tool for the identification of mutations induced by carbon-ion beam irradiation. For the first time, we presented different analysis strategies for handling massive parallel sequencing data sets to detect the mutations induced by carbon-ion beam irradiation in Arabidopsis thaliana with low false-positive rate, as well as to identify the causative nucleotide changes responsible for a mutant phenotype.