Genetic Analysis of Pre-Harvest Sprouting Resistance in a Wheat × Spelt Cross

Zanetti, S.; Winzeler, M.; Keller, Martin; Keller, Beat; Messmer, Monika

doi:10.2135/cropsci2000.4051406x

Cited by 100 publications

(69 citation statements)

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“…The minor effect QPhs.spa-1A1 QTL at cfa2135 coincides with a QTL reported by Knox et al (2012) and Jaiswal et al (2012), and is near to QTL reported in many other studies (Glein et al 2006;Munkvold et al 2009;Mohan et al 2009;Singh et al 2010;Rehman et al 2012;Singh et al 2014). Singh et al (2010) and Zanetti et al (2000) detected a QTL on chromosome 1A that was possibly involved with alpha-amylase activity, an important predictor of preharvest sprouting. QPhs.spa-1B in interval wmc44-gwm328 that explained 18 % of the phenotypic variation for GI10d and GI14d is in a different position from QTL reported by Munkvold et al (2009), Jaiswal et al (2012 and Singh et al (2014).…”

Section: Discussionsupporting

confidence: 86%

Maximizing the identification of QTL for pre-harvest sprouting resistance using seed dormancy measures in a white-grained hexaploid wheat population

et al. 2015

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Pre-harvest sprouting in spring wheat causes significant financial loss to growers throughout the world and sprouting damage can be reduced by growing resistant genotypes. Several genetic factors, especially those related to seed dormancy, are involved in the control of pre-harvest sprouting resistance. The objective of this study was to identify quantitative trait loci (QTL) influencing pre-harvest sprouting resistance from multiple measures of dormancy at multiple germination intervals on seed harvested across multiple environments. A doubled haploid mapping population of 91 individuals derived from a cross of two Canadian white-seeded spring wheat genotypes, SC8021-V2 (pre-harvest sprouting resistant) and AC Karma (moderately susceptible to pre-harvest sprouting) was used for QTL mapping. Daily germination counts were analysed using germination index, germination resistance and percent germination at intervals of 3, 5, 7, 10, 14 and 21 days from spike samples collected from six field and one greenhouse environments in Saskatchewan, Canada. Continuous frequency distributions at certain measure-durations indicated genetic complexity of dormancy segregation in the SC8021-V2/AC Karma cross. Composite interval mapping detected significant (p B 0.05) QTL associated with resistance to pre-harvest sprouting on all 21 wheat chromosomes. Of the 26 total QTL, six were novel and the rest were detected either at the same marker or overlapping a marker interval reported in other studies. QTL expressed consistently for germination index, germination resistance and percent germination at different germination durations on chromosomes 2B, 4A, 5D and 6D. QTL identified on homoeologous chromosomes 4A, 4B and 4D with chromosome specific molecular variants of SSR marker wmc617 suggest a conserved region for controlling dormancy on group four. The majority of QTL mapped in regions known to contain factors affecting different components of pre-harvest sprouting resistance like seed dormancy, seed coat colour, ABA responsiveness and alpha-amylase activity. This study demonstrated that using multiple measures of seed dormancy Electronic supplementary material The online version of this article (doi:10.1007/s10681-015-1460-x) contains supplementary material, which is available to authorized users. Euphytica (2015) 205:287-309 DOI 10.1007/s10681-015-1460 at multiple intervals of germination enhanced identification of QTL affecting dormancy in white-seeded hexaploid wheat.

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Section: Discussionsupporting

confidence: 86%

Maximizing the identification of QTL for pre-harvest sprouting resistance using seed dormancy measures in a white-grained hexaploid wheat population

et al. 2015

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“…There is no report we are aware of where seed dormancy QTL have been reported on chromosome 6D, although the only PHS-related QTL on chromosome 6D was reported by Zanetti et al (2000) for FN and aamylase activity. The high level of susceptibility to PHS in Janz and at the same time the proven expression of PHS resistance associated with some of its genomic regions in SBLs is in agreement with the expressionsuppression phenomenon sometimes observed in wheat, especially in relation to the D-genome, in which gene(s) express in synthetic hexaploids only when the corresponding repressor is absent (Eastwood 1995;Kema et al 1995;Imtiaz et al 2003).…”

Section: Qtl Controlling Seed Dormancy and Phs In Wheatmentioning

confidence: 99%

“…These SSRs were supplemented with 30 SSRs randomly selected from A and B genomes of wheat. An additional 33 SSR markers targeting all QTL reportedly linked to PHS on A and B genomes were used in screening for parental polymorphism (Zanetti et al 2000;Flintham et al 2002;Tan et al 2006). The linkage map constructed with the BC 1 F 7 population was composed of 82 loci of which 60 were grouped into five linkage groups (Figure 2), while others either remained unlinked or distantly linked.…”

Section: Phenotypic Variation For Seed Dormancy and Phsmentioning

confidence: 99%

“…The correlation between SI and VI (Table 2) ranged from 0.45 to 0.71, which indicated that SI may not be a good estimator of PHS, especially gauging the level of variability in a range of resistant materials. Zanetti et al (2000), Shorter et al (2005), and others also used a-amylase activity and FN to evaluate and map QTL for PHS response. Although both parameters have a high correlation with PHS, this may not represent a casual relationship with PHS, because they measure the damage done to endosperm due to sprouting rather than PHS per se.…”

Section: Qtl Controlling Seed Dormancy and Phs In Wheatmentioning

confidence: 99%

“…Therefore both seed dormancy and PHS are complex traits controlled by many genes or quantitative trait loci (QTL) (Paterson and Sorrells 1990;Mares 1996;Flintham et al 2002). In wheat, QTL associated with PHS resistance have been identified spanning all 21 chromosomes of the three hexaploid wheat genomes (Anderson et al 1993;Roy et al 1999;Zanetti et al 2000;Kato et al 2001;Mares and Mrva 2001;Flintham et al 2002;Groos et al 2002;Mares et al 2005;Imtiaz et al 2006;Kottearachchi et al 2006;Ogbonnaya et al 2006), underlying the complexity of PHSR. Four parameters, namely grain dormancy, wetting spikes, falling number (FN), and a-amylase have been used to evaluate and map gene(s)/QTL for PHSR (Zanetti et al 2000;Kuwal et al 2005;Mares et al 2005).…”

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confidence: 99%

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Characterization of Quantitative Trait Loci Controlling Genetic Variation for Preharvest Sprouting in Synthetic Backcross-Derived Wheat Lines

Ogbonnaya²,

et al. 2008

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Aegilops tauschii, the wild relative of wheat, has stronger seed dormancy, a major component of preharvest sprouting resistance (PHSR), than bread wheat. A diploid Ae. tauschii accession (AUS18836) and a tetraploid (Triticum turgidum L. ssp. durum var. Altar84) wheat were used to construct a synthetic wheat (Syn37). The genetic architecture of PHS was investigated in 271 BC 1 F 7 synthetic backcross lines (SBLs) derived from Syn37/2*Janz (resistant/susceptible). The SBLs were evaluated in three environments over 2 years and PHS was assessed by way of three measures: the germination index (GI), which measures grain dormancy, the whole spike assay (SI), which takes into account all spike morphology, and counted visually sprouted seeds out of 200 (VI). Grain color was measured using both Chroma Meter-and NaOH-based approaches. QTL for PHSR and grain color were mapped and their additive and epistatic effects as well as their interactions with environment were estimated by a mixed linear-model approach. Single-locus analysis following composite interval mapping revealed four QTL for GI, two QTL for SI, and four QTL for VI on chromosomes 3DL and 4AL. The locus QPhs.dpiv-3D.1 on chromosome 3DL was tightly linked to the red grain color (RGC) at a distance of 5 cM. The other locus on chromosome 3D, ''QPhs.dpiv-3D.2'' was independent of RGC locus. Two-locus analysis detected nine QTL with main effects and 18 additive 3 additive interactions for GI, SI, and VI. Two of the nine main effects QTL and two epistatic QTL showed significant interactions with environments. Both additive and epistatic effects contributed to phenotypic variance in PHSR and the identified markers are potential candidates for marker-assisted selection of favorable alleles at multiple loci. SBLs derived from Ae. tauschii proved to be a promising tool to dissect, introgress, and pyramid different PHSR genes into adapted wheat genetic backgrounds. The enhanced expression of PHS resistance in SBLs enabled us to develop white PHS-resistant wheat germplasm from the red-grained Ae. tauschii accession.

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Genome‐wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat

et al. 2022

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Association mapping using crop cultivars allows identification of genetic loci of direct relevance to breeding. Here, 150 U.K. wheat (Triticum aestivum L.) cultivars genotyped with 23,288 single nucleotide polymorphisms (SNPs) were used for genome‐wide association studies (GWAS) using historical phenotypic data for grain protein content, Hagberg falling number (HFN), test weight, and grain yield. Power calculations indicated experimental design would enable detection of quantitative trait loci (QTL) explaining ≥20% of the variation (PVE) at a relatively high power of >80%, falling to 40% for detection of a SNP with an R2≥ .5 with the same QTL. Genome‐wide association studies identified marker‐trait associations for all four traits. For HFN (h2 = .89), six QTL were identified, including a major locus on chromosome 7B explaining 49% PVE and reducing HFN by 44 s. For protein content (h2 = 0.86), 10 QTL were found on chromosomes 1A, 2A, 2B, 3A, 3B, and 6B, together explaining 48.9% PVE. For test weight, five QTL were identified (one on 1B and four on 3B; 26.3% PVE). Finally, 14 loci were identified for grain yield (h2 = 0.95) on eight chromosomes (1A, 2A, 2B, 2D, 3A, 5B, 6A, 6B; 68.1% PVE), of which five were located within 16 Mbp of genetic regions previously identified as under breeder selection in European wheat. Our study demonstrates the utility of exploiting historical crop datasets, identifying genomic targets for independent validation, and ultimately for wheat genetic improvement.

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Genetic Analysis of Pre-Harvest Sprouting Resistance in a Wheat × Spelt Cross

Cited by 100 publications

References 2 publications

Maximizing the identification of QTL for pre-harvest sprouting resistance using seed dormancy measures in a white-grained hexaploid wheat population

Maximizing the identification of QTL for pre-harvest sprouting resistance using seed dormancy measures in a white-grained hexaploid wheat population

Characterization of Quantitative Trait Loci Controlling Genetic Variation for Preharvest Sprouting in Synthetic Backcross-Derived Wheat Lines

Genome‐wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat

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