Systematic prediction of EMS-induced mutations in a sorghum mutant population

The precise detection of causal DNA mutations (deoxyribonucleic acid) is very crucial for forward genetic studies. Several sources of errors contribute to false-positive detections by current variant-calling algorithms, which impact associating phenotypes with genotypes. To improve the accuracy of mutation detection, we implemented a binning method for the accurate detection of likely ethyl methanesulfonate (EMS)-induced mutations in a sequenced mutant population. We also implemented a clustering algorithm for detecting likely false negatives with high accuracy. Sorghum bicolor is a very valuable crop species with tremendous potential for uncovering novel gene functions associated with highly desirable agronomical traits. We demonstrate the precision of the described approach in the detection of likely EMS-induced mutations from the publicly available low-cost sequencing of the M₃ generation from 600 sorghum BTx623 mutants. The approach detected 3,274,606 single nucleotide polymorphisms (SNPs), of which 96% (3,141,908) were G/C to A/T DNA substitutions, as expected by EMS-mutagenesis mode of action. We demonstrated the general applicability of the described method and showed a high concordance, 94% (3,074,759) SNPs overlap between SAMtools-based and GATK-based variant-calling algorithms. Our clustering algorithm uncovered evidence for an additional 223,048 likely false-negative shared EMS-induced mutations. The final 3,497,654 SNPs represent an 87% increase in SNPs detected from the previous analysis of the mutant population, with an average of one SNP per 125 kb in the sorghum genome. Annotation of the final SNPs revealed 10,263 high-impact and 136,639 moderate-impact SNPs, including 7217 stop-gained mutations, which averages 12 stop-gained mutations per mutant, and four high- or medium-impact SNPs per sorghum gene. We have implemented a public search database for this new genetic resource of 30,285 distinct sorghum genes containing medium- or high-impact EMS-induced mutations. Seedstock for a select 486 of the 600 described mutants are publicly available in the Germplasm Resources Information Network (GRIN) database.