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

Citation

Addo-Quaye, Charles (2022), Systematic prediction of EMS-induced mutations in a sorghum mutant population, Dryad, Dataset, https://doi.org/10.5061/dryad.hmgqnk9hj

Abstract

Sorghum is a next-generation crop species with tremendous potential for discovering highly desirable agronomical traits. We described an improved method for the systematic detection of EMS-induced mutations in the previous sequencing of the M3 generation of 600 sorghum BTx623 mutants. We used both SAMtools and GATK-based variant-calling algorithms to demonstrate the general utility of the method. The approach also includes a clustering algorithm for detecting likely false-negative EMS-induced mutations. We detected 3,497,654 EMS-induced single nucleotide polymorphisms (SNPs) in 30,285 distinct sorghum genes, and cataloged 10,263 high impact and 136,639 moderate impact SNPs. We also implemented a light-weight web portal for searching the mutation database for the 600 sorghum mutants.

Methods

NGS Sequencing data:

Illumina Sequencing of mutant individuals at 6X coverage. Sequencing data is available at the NCB SRA (SRA Accession Number SRP065118).

SNP Calling: SAMtools and GATK

SNP Annotations: snpEff and SIFT4G

Gene Annotation: Phytozome gene annotation for sorghum BTx623

Funding

HHS | NIH | National Institute of General Medical Sciences (NIGMS), Award: P20GM103408