Identification and Fine-Mapping of Quantitative Trait Loci Controlling Plant Height in Central European Winter Triticale (×Triticosecale Wittmack)

Trini, Johannes; Maurer, Hans Peter; Neuweiler, Jan E.; Würschum, Tobias

doi:10.3390/plants10081592

Cited by 8 publications

(7 citation statements)

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“…Previous studies (Neuweiler et al 2020 , 2021 ; Trini et al 2021 ) have reported grain yield, thousand-kernel weight and plant height based on the same field experiment. For the other traits, the Bonferroni–Holm test was used for outlier detection (Bernal-Vasquez et al 2016 ).…”

Section: Methodsmentioning

confidence: 96%

The performance of phenomic selection depends on the genetic architecture of the target trait

et al. 2021

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Key message The phenomic predictive ability depends on the genetic architecture of the target trait, being high for complex traits and low for traits with major QTL. Abstract Genomic selection is a powerful tool to assist breeding of complex traits, but a limitation is the costs required for genotyping. Recently, phenomic selection has been suggested, which uses spectral data instead of molecular markers as predictors. It was shown to be competitive with genomic prediction, as it achieved predictive abilities as high or even higher than its genomic counterpart. The objective of this study was to evaluate the performance of phenomic prediction for triticale and the dependency of the predictive ability on the genetic architecture of the target trait. We found that for traits with a complex genetic architecture, like grain yield, phenomic prediction with NIRS data as predictors achieved high predictive abilities and performed better than genomic prediction. By contrast, for mono- or oligogenic traits, for example, yellow rust, marker-based approaches achieved high predictive abilities, while those of phenomic prediction were very low. Compared with molecular markers, the predictive ability obtained using NIRS data was more robust to varying degrees of genetic relatedness between the training and prediction set. Moreover, for grain yield, smaller training sets were required to achieve a similar predictive ability for phenomic prediction than for genomic prediction. In addition, our results illustrate the potential of using field-based spectral data for phenomic prediction. Overall, our result confirmed phenomic prediction as an efficient approach to improve the selection gain for complex traits in plant breeding.

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Section: Methodsmentioning

confidence: 96%

The performance of phenomic selection depends on the genetic architecture of the target trait

et al. 2021

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“…Up to now, many research studies have described the QTL regions associated with triticale resistance to both biotic and abiotic stresses such as resistance to Fusarium head blight (FHB) [ 17 , 24 , 25 , 26 ], powdery mildew [ 16 , 22 , 27 , 28 ], yellow rust [ 11 , 17 , 29 ], pink snow mold [ 30 , 31 , 32 ], drought [ 33 , 34 , 35 ], and freezing [ 23 , 32 ]. Many studies showed the analysis of QTL regions associated with the important agronomic factors and morphological features of triticale [ 36 , 37 , 38 , 39 , 40 ]. Additionally, from the breeding perspective, QTL regions linked with androgenic responsiveness [ 41 ], albino plant formation [ 42 ], and ABA accumulation in the anthers in response to stress factors [ 43 , 44 ] were also identified, which can be very useful in modifying an in vitro approach, especially in the androgenesis process.…”

Section: Qtl and Candidate Gene Analysismentioning

confidence: 99%

The Genome Regions Associated with Abiotic and Biotic Stress Tolerance, as Well as Other Important Breeding Traits in Triticale

Gołębiowska

Dyda

2023

Plants

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This review article presents the greatest challenges in modern triticale breeding. Genetic maps that were developed and described thus far, together with the quantitative trait loci and candidate genes linked to important traits are also described. The most important part of this review is dedicated to a winter triticale mapping population based on doubled haploid lines obtained from a cross of the cultivars ‘Hewo’ and ‘Magnat’. Many research studies on this population have focused on the analysis of quantitative trait loci regions associated with abiotic (drought and freezing) and biotic (pink snow mold and powdery mildew) stress tolerance as well as related to other important breeding traits such as stem length, plant height, spike length, number of the productive spikelets per spike, number of grains per spike, and thousand kernel weight. In addition, candidate genes located among these regions are described in detail. A comparison analysis of all of these results revealed the location of common quantitative trait loci regions on the rye chromosomes 4R, 5R, and 6R, with a particular emphasis on chromosome 5R. Described here are the candidate genes identified in the above genome regions that may potentially play an important role in the analysis of trait expression. Nevertheless, these results should guide further research using molecular methods of gene identification and it is worth extending the research to other mapping populations. The article is also a review of research led by other authors on the triticale tolerance to the most current stress factors appearing in the breeding.

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“…The development of semi-dwarf varieties is a reliable way to solve the lodging problem. Dwarfing genes reduce the height of the straw, increasing the yield via higher grain number per ear yield without the risk of losing it as a result of lodging [14,15]. However, in experiments with isogenic recombinant lines, the dwarfing genes, as a rule, reduce the thousand grain weight, impair the assimilation of soil nitrate nitrogen, and reduce drought resistance, and they can extend the periods of flowering and heading [16,17].…”

Section: Introductionmentioning

confidence: 99%

“…Among the dwarfing genes of rye, the dominant allele Ddw1 has the greatest agricultural value. The Gibberellin 2-Oxidase gene is considered a candidate for Ddw1, while its ortholog in wheat is considered to be the Rht12 gene [14,[26][27][28][29][30]. It is able to reduce the height of plants by 25-30%, but at the same time, it reduces the thousand grain weight and the weight of grains per ear [31][32][33][34][35][36][37].…”

Section: Introductionmentioning

confidence: 99%

“…It is able to reduce the height of plants by 25-30%, but at the same time, it reduces the thousand grain weight and the weight of grains per ear [31][32][33][34][35][36][37]. Ddw1 is successfully used in triticale breeding in Poland, Romania, and other European countries [14,38,39]. In our work, we carried out a two-year study on the interaction of the TaGRF3-2A (hereafter designated in the test as Grf3) and Ddw1 genes in spring triticale in the field conditions of the Central Non-Chernozem (Non-Black Earth) Region of the Russian Federation.…”

Section: Introductionmentioning

confidence: 99%

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TaGRF3-2A Improves Some Agronomically Valuable Traits in Semi-Dwarf Spring Triticale

Divashuk

Chernook

Kroupina

et al. 2021

Plants

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The breeding improvement of triticale is tightly associated with the introgression of dwarfing genes, in particular, gibberellin (GA)-insensitive Ddw1 from rye. Despite the increase in harvest index and resistance to lodging, this gene adversely affects grain weight and size. Growth regulation factor (GRF) genes are plant-specific transcription factors that play an important role in plant growth, including GA-induced stem elongation. This study presents the results of a two-year field experiment to assess the effect of alleles of the TaGRF3-2A gene in interaction with DDW1 on economically valuable traits of spring triticale plants grown in the Non-Chernozem zone. Our results show that, depending on the allelic state, the TaGRF3-2A gene in semi-dwarf spring triticale plants influences the thousand grain weight and the grain weight of the main spike in spring triticale, which makes it possible to use it to compensate for the negative effects of the dwarfing allele Ddw1. The identified allelic variants of the TaGRF3-2A gene can be included in marker-assisted breeding for triticale to improve traits.

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Identification and Fine-Mapping of Quantitative Trait Loci Controlling Plant Height in Central European Winter Triticale (×Triticosecale Wittmack)

Cited by 8 publications

References 50 publications

The performance of phenomic selection depends on the genetic architecture of the target trait

The performance of phenomic selection depends on the genetic architecture of the target trait

The Genome Regions Associated with Abiotic and Biotic Stress Tolerance, as Well as Other Important Breeding Traits in Triticale

TaGRF3-2A Improves Some Agronomically Valuable Traits in Semi-Dwarf Spring Triticale

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