Assessment of the genetic diversity, population structure and allele distribution of major plant development genes in bread wheat cultivars using DArT and gene-specific markers

Kiss, Tibor; Balla, Krisztina; Cseh, András; Berki, Zita; Horváth, Attila; Vida, Gy.; Veisz, O.; Karsaï, I.

doi:10.1007/s42976-021-00136-2

Cited by 4 publications

(8 citation statements)

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“…( Ibrahim, 2019 , Mahpara et al, 2018a ) found that wheat yield was dependent on plant height, number of tillers per plant and dry weight. Similarly, increase in number of tillers per plant and other yield related traits improved wheat yield in different studies observed hereditary variation in seven wheat parents during an experiment on RAPD markers for estimation of genetic diversity ( Awaad, 2021 , Kiss et al, 2021 , Mahpara et al, 2017b ). ( Tariq et al, 2020 ) worked on sixty-three wheat genotypes and found maximum genetic divergence for anti-oxidant enzymes and phenolic compounds .…”

Section: Introductionmentioning

confidence: 99%

Grain yield and correlated traits of bread wheat lines: Implications for yield improvement

Ullah

Mahpara

Bibi

et al. 2021

Saudi Journal of Biological Sciences

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Global wheat yields are suffering due to differences in regional climatic conditions and soil fertility. Plant breeders are continuously working to improve the yield per unit area of wheat crop through selecting superior lines as parents. The screening and field evaluation of available lines allow the selection of superior ones and subsequently improved varieties. Therefore, heritable distinctions among 33 bread wheat lines for yield and related attributes were assessed under field conditions. The experiment included thirty lines and three check varieties. Data relating to different plant characteristics was collected at maturity. Significant differences were recorded for yield and related traits of tested wheat lines and check varieties. Wheat lines V 6 , V 12 and V 20 proved better with reduced number of days to reach anthesis and other desirable traits compared to check varieties. Days to start heading had strong correlation with spike length and number of spikelets spike -1 . Flag leaf area had positive relationship with peduncle length and yield related traits. The 1000-garin weight and grain yield were also correlated with each other. It is concluded that V 6 , V 10 and V 20 proved better for all studied traits than the rest of the lines. Therefore, these lines could be used in wheat breeding program as parents to improve yield.

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Section: Introductionmentioning

confidence: 99%

Grain yield and correlated traits of bread wheat lines: Implications for yield improvement

Ullah

Mahpara

Bibi

et al. 2021

Saudi Journal of Biological Sciences

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“…In the first case, 249 perfect DArT markers, covering the genome evenly, were used to determine the population structure with the help of the STRUCTURE 2.3.4 program ( Pritchard et al., 2000 ). The results of these analyses had been published earlier by Kiss et al. (2021) .…”

Section: Methodsmentioning

confidence: 91%

“…In the cases of VRN-A1 and PPD-B1 , the CNV was also determined via the multiplex TaqMan ® assay (IDna Genetics Ltd., Norwich, UK). Diversity Arrays Technology (DArT) analysis was performed by Diversity Arrays Technology Pty Ltd. (CSIRO, Yarralumla, ACT, Australia; Kiss et al., 2021 ), 15K Infinium analysis was performed by the TraitGenetics GmbH (Gatersleben, Germany), and the SNPs represent a subset of markers from the Illumina wheat 90K SNP array ( Wang et al., 2014 ).…”

Section: Methodsmentioning

confidence: 99%

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Effects of genetic components of plant development on yield-related traits in wheat (Triticum aestivum L.) under stress-free conditions

Horváth

Kiss²,

Berki³

et al. 2023

Front. Plant Sci.

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The dynamics of plant development not only has an impact on ecological adaptation but also contributes to the realization of genetically determined yield potentials in various environments. Dissecting the genetic determinants of plant development becomes urgent due to the global climate change, which can seriously affect and even disrupt the locally adapted developmental patterns. In order to determine the role plant developmental loci played in local adaptation and yield formation, a panel of 188 winter and facultative wheat cultivars from diverse geographic locations were characterized with the 15K Illumina Single Nucleotide Polymorphism (SNP) chip and functional markers of several plant developmental genes and included into a multiseason field experiment. Genome-wide association analyses were conducted on five consecutive developmental phases spanning from the first node appearance to full heading together with various grain yield–related parameters. The panel was balanced for the PPD-D1 photoperiod response gene, which facilitated the analyses in the two subsets of photoperiod-insensitive and -sensitive genotypes in addition to the complete panel. PPD-D1 was the single highest source, explaining 12.1%–19.0% of the phenotypic variation in the successive developmental phases. In addition, 21 minor developmental loci were identified, each one explaining only small portions of the variance, but, together, their effects amounted to 16.6%–50.6% of phenotypic variance. Eight loci (2A_27, 2A_727, 4A_570, 5B_315, 5B_520, 6A_26, 7A_1-(VRN-A3), and 7B_732) were independent of PPD-D1. Seven loci were only detectable in the PPD-D1-insensitive genetic background (1A_539, 1B_487, 2D_649, 4A_9, 5A_584-(VRN-A1), 5B_571-(VRN-B1), and 7B_3-(VRN-B3)), and six loci were only detectable in the sensitive background, specifically 2A_740, 2D_25, 3A_579, 3B_414, 7A_218, 7A_689, and 7B_538. The combination of PPD-D1 insensitivity and sensitivity with the extremities of early or late alleles in the corresponding minor developmental loci resulted in significantly altered and distinct plant developmental patterns with detectable outcomes on some yield-related traits. This study examines the possible significance of the above results in ecological adaptation.

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“…Recent advances in genotyping and sequencing technologies have progressively expedited the introduction of genomic-based techniques in modern plant breeding. DArT, SSR, and SNP molecular marker systems have been validated for population genetic studies in wheat [ 25 , 26 , 27 , 28 ]. Particularly, Mora et al [ 25 ] and, more recently, Ballesta et al [ 28 ] reported that the population genetic structure of the Santa Rosa and Cauquenes sites is separated into two significantly differentiated clusters with relatively high differentiation values (Fst) according to the Bayesian clustering method (implemented in the software STRUCTURE) and a principal component analysis (PCA), which is in agreement with previous studies that have examined the genetic structure of different collections of bread wheat germplasm in the world [ 29 , 30 ].…”

Section: Discussionmentioning

confidence: 99%

Spectral-Based Classification of Genetically Differentiated Groups in Spring Wheat Grown under Contrasting Environments

Ballesta

Maldonado

Mora‐Poblete

et al. 2023

Plants

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The global concern about the gap between food production and consumption has intensified the research on the genetics, ecophysiology, and breeding of cereal crops. In this sense, several genetic studies have been conducted to assess the effectiveness and sustainability of collections of germplasm accessions of major crops. In this study, a spectral-based classification approach for the assignment of wheat cultivars to genetically differentiated subpopulations (genetic structure) was carried out using a panel of 316 spring bread cultivars grown in two environments with different water regimes (rainfed and fully irrigated). For that, different machine-learning models were trained with foliar spectral and genetic information to assign the wheat cultivars to subpopulations. The results revealed that, in general, the hyperparameters ReLU (as the activation function), adam (as the optimizer), and a size batch of 10 give neural network models better accuracy. Genetically differentiated groups showed smaller differences in mean wavelengths under rainfed than under full irrigation, which coincided with a reduction in clustering accuracy in neural network models. The comparison of models indicated that the Convolutional Neural Network (CNN) was significantly more accurate in classifying individuals into their respective subpopulations, with 92 and 93% of correct individual assignments in water-limited and fully irrigated environments, respectively, whereas 92% (full irrigation) and 78% (rainfed) of cultivars were correctly assigned to their respective classes by the multilayer perceptron method and partial least squares discriminant analysis, respectively. Notably, CNN did not show significant differences between both environments, which indicates stability in the prediction independent of the different water regimes. It is concluded that foliar spectral variation can be used to accurately infer the belonging of a cultivar to its respective genetically differentiated group, even considering radically different environments, which is highly desirable in the context of crop genetic resources management.

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Assessment of the genetic diversity, population structure and allele distribution of major plant development genes in bread wheat cultivars using DArT and gene-specific markers

Cited by 4 publications

References 70 publications

Grain yield and correlated traits of bread wheat lines: Implications for yield improvement

Grain yield and correlated traits of bread wheat lines: Implications for yield improvement

Effects of genetic components of plant development on yield-related traits in wheat (Triticum aestivum L.) under stress-free conditions

Spectral-Based Classification of Genetically Differentiated Groups in Spring Wheat Grown under Contrasting Environments

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