Theoretical and Applied Genetics

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ISSN / EISSN : 0040-5752 / 1432-2242
Current Publisher: Springer Science and Business Media LLC (10.1007)
Former Publisher: , Springer Science and Business Media LLC (10.1007) , Springer Science and Business Media LLC (10.1007) , Springer Science and Business Media LLC (10.1007) , Springer Science and Business Media LLC (10.1007) Springer Science and Business Media LLC (10.1007)
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Latest articles in this journal

Mehwish Kanwal, Naeela Qureshi, Mesfin Gessese, Kerrie Forrest, Prashanth Babu, ,
Theoretical and Applied Genetics pp 1-8; doi:10.1007/s00122-021-03818-x

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, , G. J. Ma, X. H. Li
Theoretical and Applied Genetics pp 1-11; doi:10.1007/s00122-021-03826-x

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Bhavit Chhabra, Vijay Tiwari, Bikram S. Gill, Yanhong Dong,
Theoretical and Applied Genetics pp 1-17; doi:10.1007/s00122-021-03825-y

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Alexander Mahlandt, Nidhi Rawat, Jeff Leonard, Prakash Venglat, Raju Datla, Nathan Meier, Bikram S. Gill, Oscar Riera-Lizarazu, Gary Coleman, Angus S. Murphy, et al.
Theoretical and Applied Genetics pp 1-12; doi:10.1007/s00122-021-03827-w

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Theoretical and Applied Genetics pp 1-18; doi:10.1007/s00122-021-03786-2

Abstract:
Key message We propose the utilisation of environmental covariates in random coefficient models to predict the genotype performances in new locations. Abstract Multi-environment trials (MET) are conducted to assess the performance of a set of genotypes in a target population of environments. From a grower’s perspective, MET results must provide high accuracy and precision for predictions of genotype performance in new locations, i.e. the grower’s locations, which hardly ever coincide with the locations at which the trials were conducted. Linear mixed modelling can provide predictions for new locations. Moreover, the precision of the predictions is of primary concern and should be assessed. Besides, the precision can be improved when auxiliary information is available to characterize the targeted locations. Thus, in this study, we demonstrate the benefit of using environmental information (covariates) for predicting genotype performance in some new locations for Swedish winter wheat official trials. Swedish MET locations can be stratified into zones, allowing borrowing information between zones when best linear unbiased prediction (BLUP) is used. To account for correlations between zones, as well as for intercepts and slopes for the regression on covariates, we fitted random coefficient (RC) models. The results showed that the RC model with appropriate covariate scaling and model for covariate terms improved the precision of predictions of genotypic performance for new locations. The prediction accuracy of the RC model was competitive compared to the model without covariates. The RC model reduced the standard errors of predictions for individual genotypes and standard errors of predictions of genotype differences in new locations by 30–38% and 12–40%, respectively.
Bonny Michael Oloka, Guilherme Da Silva Pereira, Victor A. Amankwaah, Marcelo Mollinari, Kenneth V. Pecota, Benard Yada, Bode A. Olukolu, Zhao-Bang Zeng,
Theoretical and Applied Genetics pp 1-11; doi:10.1007/s00122-021-03797-z

Abstract:
Key message Utilizing a high-density integrated genetic linkage map of hexaploid sweetpotato, we discovered a major dominant QTL for root-knot nematode (RKN) resistance and modeled its effects. This discovery is useful for development of a modern sweetpotato breeding program that utilizes marker-assisted selection and genomic selection approaches for faster genetic gain of RKN resistance. Abstract The root-knot nematode [Meloidogyne incognita (Kofoid & White) Chitwood] (RKN) causes significant storage root quality reduction and yields losses in cultivated sweetpotato [Ipomoea batatas (L.) Lam.]. In this study, resistance to RKN was examined in a mapping population consisting of 244 progenies derived from a cross (TB) between ‘Tanzania,’ a predominant African landrace cultivar with resistance to RKN, and ‘Beauregard,’ an RKN susceptible major cultivar in the USA. We performed quantitative trait loci (QTL) analysis using a random-effect QTL mapping model on the TB genetic map. An RKN bioassay incorporating potted cuttings of each genotype was conducted in the greenhouse and replicated five times over a period of 10 weeks. For each replication, each genotype was inoculated with ca. 20,000 RKN eggs, and root-knot galls were counted ~62 days after inoculation. Resistance to RKN in the progeny was highly skewed toward the resistant parent, exhibiting medium to high levels of resistance. We identified one major QTL on linkage group 7, dominant in nature, which explained 58.3% of the phenotypic variation in RKN counts. This work represents a significant step forward in our understanding of the genetic architecture of RKN resistance and sets the stage for future utilization of genomics-assisted breeding in sweetpotato breeding programs.
, Mami Takahashi, Tetsuya Yamada, Yuhi Kono, Naohiro Yamada, Koji Takahashi, Jouji Moriwaki, Hajime Akamatsu
Theoretical and Applied Genetics pp 1-15; doi:10.1007/s00122-021-03813-2

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Correction
Congcong Li, Genping Wang, Haiquan Li, Guoliang Wang, Jian Ma, Xin Zhao, Linhe Huo, Liquan Zhang, Yanmiao Jiang, Jiewei Zhang, et al.
Theoretical and Applied Genetics pp 1-1; doi:10.1007/s00122-021-03817-y

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