Whole Genome Characterization of a Few EMS-Induced Mutants of Upland Rice Variety Nagina 22 Reveals a Staggeringly High Frequency of SNPs Which Show High Phenotypic Plasticity Towards the Wild-Type

Abstract

The Indian initiative, in creating mutant resources for the functional genomics in rice, has been instrumental in the development of 87,000 ethylmethanesulfonate (EMS)-induced mutants, of which 7,000 are in advanced generations. The mutants have been created in the background of Nagina 22, a popular drought- and heat-tolerant upland cultivar. As it is a pregreen revolution cultivar, as many as 573 dwarf mutants identified from this resource could be useful as an alternate source of dwarfing. A total of 541 mutants, including the macromutants and the trait-specific ones, obtained after appropriate screening, are being maintained in the mutant garden. Here, we report on the detailed characterizations of the 541 mutants based on the distinctness, uniformity, and stability (DUS) descriptors at two different locations. About 90% of the mutants were found to be similar to the wild type (WT) with high similarity index (>0.6) at both the locations. All 541 mutants were characterized for chlorophyll and epicuticular wax contents, while a subset of 84 mutants were characterized for their ionomes, namely, phosphorous, silicon, and chloride contents. Genotyping of these mutants with 54 genomewide simple sequence repeat (SSR) markers revealed 93% of the mutants to be either completely identical to WT or nearly identical with just one polymorphic locus. Whole genome resequencing (WGS) of four mutants, which have minimal differences in the SSR fingerprint pattern and DUS characters from the WT, revealed a staggeringly high number of single nucleotide polymorphisms (SNPs) on an average (16,453 per mutant) in the genic sequences. Of these, nearly 50% of the SNPs led to non-synonymous codons, while 30% resulted in synonymous codons. The number of insertions and deletions (InDels) varied from 898 to 2,595, with more than 80% of them being 1-2 bp long. Such a high number of SNPs could pose a serious challenge in identifying gene(s) governing the mutant phenotype by next generation sequencing-based mapping approaches such as Mutmap. From the WGS data of the WT and the mutants, we developed a genic resource of the WT with a novel analysis pipeline. The entire information about this resource along with the panicle architecture of the 493 mutants is made available in a mutant database EMSgardeN22 (http://14.139.229.201/EMSgardeN22).

Keywords: EMS mutants; Nagina 22; ionomics; mutant resource; mutation frequency; rice.

FIGURE 1

Frequency distribution of 541 rice EMS mutants of Nagina 22 for major morphological traits. (A) Plant height; (B) panicle length; (C) number of productive tillers; (D) flag leaf length; (E) days to 50% flowering; (F) grain length; (G) grain width; (H) hundred seed weight. Unit of the traits measured are indicated in the parenthesis in the figure.

FIGURE 2

Performance of the rice EMS mutants of Nagina 22 for DUS across two locations, (A) Distribution of similarity index of mutants in two locations, New Delhi (NN) and Cuttack (NC); (B) Traitwise similarity index at NC; (C) Traitwise similarity index at NN; (D) Comparison of traitwise similarity index at NC and NN. Similarity scores were assigned by comparing the mutant trait value with the WT trait value. If they are same, a score “1” was assigned; if not “0” score was assigned. The scores were averaged across all the traits to arrive at mutant similarity index. The scores were also averaged over all the mutants for each trait to arrive at trait similarity index.

FIGURE 3

Morphological trait correlations across two years indicating the stability of the mutants (A) Plant Height (PH); (B) Panicle length (PL); (C) Number of productive tillers (NPT); and (D) FLL. All correlations were according to Pearson’s linear correlations and were found to be positive and significant at P < 0.05.

FIGURE 4

Assessment of genomic similarity of the mutants with Nagina 22 using SSR markers (A) Similarity index of SSR markers used for genotyping the mutants; (B) Polymorphism in the mutants for SSRs. Similarity scores were assigned by comparing the PCR amplicon size of the mutant with that of WT. If they are same a score “1” was assigned; if not “0” score was assigned. The scores were averaged across all the markers to arrive at mutant similarity index. The scores were also averaged over all the mutants for each marker to arrive at trait marker performance index.

FIGURE 5

Descriptive statistics and distribution of organic (chlorophyll and wax content) and inorganic constituents (P, Si, and Cl) in the rice EMS mutant garden of Nagina 22. (A) Total chlorophyll; (B) Epicuticular wax; (C) Phosphorous; (D) Silicon; (E) Chlorine. Units of the traits measured are indicated in the parenthesis. The number of mutants (N) used for each trait assessment is indicated.

FIGURE 6

SNP distribution across different genic regions in the mutants.

FIGURE 7

Distribution of the mutants beyond ±1 standard deviation for the morphological traits and organic and inorganic constituents. This is to show that the mutants with extreme trait value are available for each trait.

FIGURE 8

Snapshot of the mutant garden database indicating the available search options.