Augmenting tomato functional genomics with a genome-wide induced genetic variation resource

Area of Science:

• Plant genetics
• Genomics
• Crop science

Background:

• Induced mutations are crucial for crop improvement, offering new alleles for disease resistance and yield.
• Identifying mutations with subtle or no visible phenotype is challenging but essential for understanding gene function.
• Whole-genome sequencing (WGS) provides a comprehensive view of all mutations in mutagenized populations.

Purpose of the Study:

• To comprehensively identify and characterize induced mutations in ethyl methanesulfonate (EMS)-mutagenized tomato lines using WGS.
• To create a valuable resource for functional genomics and targeted breeding in tomatoes.
• To analyze mutation patterns, including biases and effects on genes and metabolic pathways.

Main Methods:

• Sequencing of 132 doubly EMS-mutagenized tomato lines.
• Bioinformatic analysis to detect novel mutations and short insertions/deletions (InDels).
• Prediction of deleterious mutations using Sorting Intolerant From Tolerant (SIFT) and mapping to metabolic pathways.

Main Results:

• Identification of approximately 41 million novel mutations and 5.5 million short InDels compared to the parental cultivar.
• Mutations were found across 97% of the genome, including genes, promoters, UTRs, and introns.
• Over one-third of genes harbored deleterious mutations, with nearly a fourth impacting multiple metabolic pathways. Novel AT>GC transitions were also observed alongside the typical GC>AT bias.

Conclusions:

• The study generated a large-scale mutation database for tomatoes, significantly enhancing resources for functional genomics and breeding.
• The findings highlight the utility of WGS in uncovering a wide spectrum of mutations, including those with non-apparent phenotypes.
• Validated mutations demonstrate the accuracy of the discovery pipeline and provide insights into gene function and metabolic regulation in tomatoes.