Uncovering hidden variation in polyploid wheat

Abstract

Comprehensive reverse genetic resources, which have been key to understanding gene function in diploid model organisms, are missing in many polyploid crops. Young polyploid species such as wheat, which was domesticated less than 10,000 y ago, have high levels of sequence identity among subgenomes that mask the effects of recessive alleles. Such redundancy reduces the probability of selection of favorable mutations during natural or human selection, but also allows wheat to tolerate high densities of induced mutations. Here we exploited this property to sequence and catalog more than 10 million mutations in the protein-coding regions of 2,735 mutant lines of tetraploid and hexaploid wheat. We detected, on average, 2,705 and 5,351 mutations per tetraploid and hexaploid line, respectively, which resulted in 35-40 mutations per kb in each population. With these mutation densities, we identified an average of 23-24 missense and truncation alleles per gene, with at least one truncation or deleterious missense mutation in more than 90% of the captured wheat genes per population. This public collection of mutant seed stocks and sequence data enables rapid identification of mutations in the different copies of the wheat genes, which can be combined to uncover previously hidden variation. Polyploidy is a central phenomenon in plant evolution, and many crop species have undergone recent genome duplication events. Therefore, the general strategy and methods developed herein can benefit other polyploid crops.

Keywords: exome capture; mutations; polyploidy; reverse genetics; wheat.

Fig. 1.

Overview of the development of the sequenced mutant populations. M₀ seeds were mutagenized with EMS (resulting in M₁ plants), and a single M₂ plant was grown from each M₁ plant. Genomic DNAs were extracted from the M₂ plants, and M₃ seeds were obtained from the same plant. M₃ seeds were planted in the field to produce M₄ seed for distribution. Barcoded sequencing libraries were constructed, used for exome capture, and sequenced by using Illumina. Mutations were identified by using the MAPS pipeline and were deposited in public databases that can be searched online.

Fig. 2.

Characterization of mutations in tetraploid Kronos and hexaploid Cadenza. (A) Genome-wide positions of identified mutations and their effects. The tracks from outside to inside represent gene density along wheat chromosomes (yellow-brown), number of gene models with at least one mutation (i.e., GM₁; red), percentage of GM₁ genes with at least one deleterious allele (truncation and/or missense mutation with SIFT score <0.05; purple), and total mutation densities for Cadenza (red) and Kronos (light blue). Each bin corresponds to a 10-Mb window. (B) Average number of SNPs in mutants and WT controls. (C) Distribution of mutations types in fifteen representative Kronos and Cadenza mutants (“K,” nonmutagenized Kronos; “C,” nonmutagenized Cadenza). Gray/teal indicates EMS-type mutations (C>T/G>A); violet indicates non–EMS-type mutations. (D) Estimated EMS-type error at different HetMC cutoffs (C, coverage; MC, minimum coverage).

Fig. 3.

EMS mutations present in multiple individuals. EMS sequence preference and RH: (A, C, and E) Tetraploid Kronos and (B, D, and F) hexaploid Cadenza. (A and B) Mutations shared by multiple individuals in RH regions. (C and D) Observed (red) and closest Poisson distribution (light blue) of mutations present in non-RH regions of multiple individuals. (A–D) The x-axis indicates the number of individuals sharing the same mutation. (E and F) Sequence preference in regions flanking EMS-type mutations (SI Appendix, Fig. S7). The x-axis indicates the number of nucleotides upstream (negative) and downstream (positive) from the mutated site.

Fig. 4.

Predicted effect of mutant alleles on wheat starch biosynthesis and flowering pathways genes. (A) Wheat starch biosynthesis and (B) flowering pathways. Squares represent individual genes and are colored according to genomes (“A,” green; “B,” blue; “D,” violet). Filled squares represent genes with at least one truncation mutation from the mutant database, squares with crossed diagonals indicate deleterious missense mutations, and single diagonals denote tolerated missense mutations as predicted by SIFT (17). Dashed lines indicate homeologs absent or nonfunctional in the reference. Details for each gene are presented in SI Appendix, Tables S22 and S23. (C–F) Effect of loss-of-function mutations for (C) STARCH BRANCHING ENZYME IIa/b (18), (D) PHYTOCHROME C (25), (E) PHYTOCHROME B (27), and (F) VERNALIZATION 2 (26). Asterisk indicates published characterization of mutant phenotype. Double dagger indicates published characterization of mutant phenotype based on natural mutations.