Forward genetics by sequencing EMS variation induced inbred lines

Abstract

In order to leverage novel sequencing techniques for cloning genes in eukaryotic organisms with complex genomes, the false positive rate of variant discovery must be controlled for by experimental design and informatics. We sequenced five lines from three pedigrees of EMS mutagenized Sorghum bicolor, including a pedigree segregating a recessive dwarf mutant. Comparing the sequences of the lines, we were able to identify and eliminate error prone positions. One genomic region contained EMS mutant alleles in dwarfs that were homozygous reference sequence in wild-type siblings and heterozygous in segregating families. This region contained a single non-synonymous change that cosegregated with dwarfism in a validation population and caused a premature stop codon in the sorghum ortholog encoding the giberellic acid biosynthetic enzyme entkaurene oxidase. Application of exogenous giberillic acid rescued the mutant phenotype.Our method for mapping did not require outcrossing and introduced no segregation variance. This enables work when line crossing is complicated by life history, permitting gene discovery outside of genetic models.This inverts the historical approach of first using recombination to define a locus and then sequencing genes. Our formally identical approach first sequences all the genes and then seeks co-segregation with the trait.Mutagenized lines lacking obvious phenotypic alterations are available for an extention of this approach: mapping with a known marker set in a line that is phenotypically identical to starting material for EMS mutant generation.

Development and characterization of an EMS-mutagenized wheat population and identification of salt-tolerant wheat lines

“…The highest and lowest number of mutations was observed in the B and D sub-genomes respectively, for both the mutant lines. It has been reported that the number of polymorphisms in a mutagenized genome may scale with overall genome size [35]. Among the three sub-genomes of wheat, the order of genome size is B (5.180 Gb) > A (4.935 Gb) > D (3.951 Gb) [36].…”

Discovery of mutations in Chenopodium quinoa Willd through EMS mutagenesis and mutation screening using pre-selection phenotypic data and next-generation sequencing

“…Given the ploidy level of C. quinoa, 2n = 4x = 36, and the genome size of 1.39 Gb (Jarvis et al, 2017), the rate of mutation, 1/203 kb, obtained in the current study would probably achieve approximately 6847 mutations throughout the whole genome of quinoa. Despite the high capacity to generate mutations in the genome, it is thought that the polyploidy of quinoa allows it to remain viable despite a high level of mutation (Martín et al, 2009) and the genome's coding capacity determines the phenotypically effective mutational target (Addo-Quaye et al, 2017). These criteria should be considered when new quinoa mutagenesis protocols are developed.…”

“…TILLING is an efficient reverse genetics approach for detecting induced mutations in pools of individuals. Combined with the NGS technologies, and the resolving power of overlapping pool design, TILLING provides an efficient and economical platform for functional genomics across thousands of organisms (Addo-Quaye et al, 2017), independently of the genome size, ploidy and reproductive system of plants (Rashid et al, 2011). Although TILLING is most powerful when applied to crops for which whole-genome sequences are available, it can be applied to target genes in any crop, provided that the sequence of the target gene itself is known in the target genome (Kumar et al, 2017).…”

Combining next‐generation sequencing and progeny testing for rapid identification of induced recessive and dominant mutations in maize M2 individuals

“…However, each of these approaches involved preceding backcrossing programs or analysis of large numbers of F 2 individuals for the assembly of bulks. Addo-Quaye et al (2017) omitted backcrossing and sequenced pools of Sorghum bicolor EMS mutant and wild-type individuals to filter for homozygous SNPs causing non-synonymous amino acid exchanges in the mutant population and could identify a recessive mutation. Although they were able to find a homozygous SNP in a protein-coding region their approach potentially missed mutations not caused by SNPs like insertions or deletions and would furthermore not have enough discriminative power to detect mutations in a heterozygous state, which is relevant for homozygous lethal alleles.…”