Multifamily QTL analysis and comprehensive design of genotypes for high-quality soft wheat

Ishikawa, Goro; Hayashi, Takeshi; Nakamura, Kazuhiro; Tanaka, Tsuyoshi; Kobayashi, Fuminori; Ito, Hiroyuki; Ikenaga, Sachiko; Taniguchi, Yoshinori; Nakamura, Toshiki

doi:10.1371/journal.pone.0230326

Cited by 10 publications

(7 citation statements)

References 53 publications

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“…A slight difference existed between flour ash content and flour yield between the wild-type and “28511,” whereas the flour color of the mutant was discolored. This discoloration was attributed to the increase in grain protein content because a correlation between flour color and protein content was found in a multifamily QTL analysis using “Kitahonami” [ 59 ].…”

Section: Discussionmentioning

confidence: 99%

“…The maturity stage was recorded when the grains had a 40% moisture content. Grain samples harvested from field trials were subjected to the following analyses [ 59 ]: grain weight per 10 ha and 1,000-grain weight were calculated using fully ripened grains, and grain protein content was measured using near-infrared spectroscopy with an Infratec NOVA instrument (FOSS, Hilleroed, Denmark) and adjusted to a moisture content of 13.5%. The grain ash content was determined by combustion at 600 °C for 4 h. The flour yield was calculated as the percentage of total flour weight (A flour + B flour) relative to the sample weight (A flour + B flour + bran).…”

Section: Methodsmentioning

confidence: 99%

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Genome sequencing-based coverage analyses facilitate high-resolution detection of deletions linked to phenotypes of gamma-irradiated wheat mutants

et al. 2022

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Background Gamma-irradiated mutants of Triticum aestivum L., hexaploid wheat, provide novel and agriculturally important traits and are used as breeding materials. However, the identification of causative genomic regions of mutant phenotypes is challenging because of the large and complicated genome of hexaploid wheat. Recently, the combined use of high-quality reference genome sequences of common wheat and cost-effective resequencing technologies has made it possible to evaluate genome-wide polymorphisms, even in complex genomes. Results To investigate whether the genome sequencing approach can effectively detect structural variations, such as deletions, frequently caused by gamma irradiation, we selected a grain-hardness mutant from the gamma-irradiated population of Japanese elite wheat cultivar “Kitahonami.” The Hardness (Ha) locus, including the puroindoline protein-encoding genes Pina-D1 and Pinb-D1 on the short arm of chromosome 5D, primarily regulates the grain hardness variation in common wheat. We performed short-read genome sequencing of wild-type and grain-hardness mutant plants, and subsequently aligned their short reads to the reference genome of the wheat cultivar “Chinese Spring.” Genome-wide comparisons of depth-of-coverage between wild-type and mutant strains detected ~ 130 Mbp deletion on the short arm of chromosome 5D in the mutant genome. Molecular markers for this deletion were applied to the progeny populations generated by a cross between the wild-type and the mutant. A large deletion in the region including the Ha locus was associated with the mutant phenotype, indicating that the genome sequencing is a powerful and efficient approach for detecting a deletion marker of a gamma-irradiated mutant phenotype. In addition, we investigated a pre-harvest sprouting tolerance mutant and identified a 67.8 Mbp deletion on chromosome 3B where Viviparous-B1 and GRAS family transcription factors are located. Co-dominant markers designed to detect the deletion-polymorphism confirmed the association with low germination rate, leading to pre-harvest sprouting tolerance. Conclusions Short read-based genome sequencing of gamma-irradiated mutants facilitates the identification of large deletions linked to mutant phenotypes when combined with segregation analyses in progeny populations. This method allows effective application of mutants with agriculturally important traits in breeding using marker-assisted selection.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Genome sequencing-based coverage analyses facilitate high-resolution detection of deletions linked to phenotypes of gamma-irradiated wheat mutants

et al. 2022

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“…We investigated 188 F 1 derived doubled haploid lines (DHLs) derived from a cross between Shunyou and Kitahonami (Ishikawa et al 2020). Traits were evaluated in 192 accessions including two replicates of the parental varieties.…”

Section: Plant Materialsmentioning

confidence: 99%

Genetic mechanisms determining grain number distribution along the spike and their effect on yield components in wheat

et al. 2021

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The number of wheat grains is one of the major determinant of yield. Many quantitative trait loci (QTLs) and some causal genes such as GNI-A1 and WAPO-A1 that are associated with grain number per spike (GNS) have been identi ed, but the underlying mechanisms remain largely unknown. We analyzed QTLs for grain number and other related traits using 188 doubled haploid lines derived from the Japanese highyield variety, Kitahonami, as a parent to elucidate the genetic mechanism determining grain number. The major QTLs for grain number at the apical, central and basal parts of the spike were identi ed in different chromosomal regions. We considered GNI-A1 and WAPO-A1 as candidate genes controlling grain number at the central and basal parts of the spike, respectively. Kitahonami had the favorable 105Y allele of GNI-A1 and WAPO-A1b allele, and unfavorable alleles of QTLs for grain number at the apical part of spikes. Pyramiding the favorable alleles of these QTLs signi cantly increased GNS without signi cantly reducing thousand-grain weight (TGW). In contrast, the accumulation of favorable alleles of QTLs for TGW signi cantly decreased GNS, whereas days to heading positively correlated with GNS. Late heading increased the spikelet number per spike, resulting in a higher GNS. Pyramiding of the QTLs for TGW and days to heading also altered the GNS. In conclusion, GNS is a complex trait controlled by many QTLs, and it is essential for breeding to design.

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“…We constructed a linkage map using genotype data from Ishikawa et al (2020) and MapDisto v2.1.0.1 (Lorieux 2012). Linkage groups were identi ed using a minimum logarithm of odds (LOD) score of 4 and a maximum recombination fraction of 0.30.…”

Section: Map Construction and Qtl Analysismentioning

confidence: 99%

Genetic Mechanisms Determining Grain Number Distribution Along the Spike and Their Effect on Yield Components in Wheat

Mizuno

Ishikawa

Kojima

et al. 2021

Preprint

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The number of wheat grains is one of the major determinant of yield. Many quantitative trait loci (QTLs) and some causal genes such as GNI-A1 and WAPO-A1 that are associated with grain number per spike (GNS) have been identified, but the underlying mechanisms remain largely unknown. We analyzed QTLs for grain number and other related traits using 188 doubled haploid lines derived from the Japanese high-yield variety, Kitahonami, as a parent to elucidate the genetic mechanism determining grain number. The major QTLs for grain number at the apical, central and basal parts of the spike were identified in different chromosomal regions. We considered GNI-A1 and WAPO-A1 as candidate genes controlling grain number at the central and basal parts of the spike, respectively. Kitahonami had the favorable 105Y allele of GNI-A1 and WAPO-A1b allele, and unfavorable alleles of QTLs for grain number at the apical part of spikes. Pyramiding the favorable alleles of these QTLs significantly increased GNS without significantly reducing thousand-grain weight (TGW). In contrast, the accumulation of favorable alleles of QTLs for TGW significantly decreased GNS, whereas days to heading positively correlated with GNS. Late heading increased the spikelet number per spike, resulting in a higher GNS. Pyramiding of the QTLs for TGW and days to heading also altered the GNS. In conclusion, GNS is a complex trait controlled by many QTLs, and it is essential for breeding to design.

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Multifamily QTL analysis and comprehensive design of genotypes for high-quality soft wheat

Cited by 10 publications

References 53 publications

Genome sequencing-based coverage analyses facilitate high-resolution detection of deletions linked to phenotypes of gamma-irradiated wheat mutants

Genome sequencing-based coverage analyses facilitate high-resolution detection of deletions linked to phenotypes of gamma-irradiated wheat mutants

Genetic mechanisms determining grain number distribution along the spike and their effect on yield components in wheat

Genetic Mechanisms Determining Grain Number Distribution Along the Spike and Their Effect on Yield Components in Wheat

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