Plant Breeding Integrated with Genomic-Enabled Prediction

Plant breeding programs have used conventional breeding methods, such as hybridization, induced mutations, and other methods to manipulate the plant genome within the species' natural genetic boundaries to improve crop varieties. However, repeatedly using conventional breeding methods might lead to the erosion of the gene reservoir, thereby rendering crops vulnerable to environmental stresses and hampering future progress in crop production, food and nutritional security, and socio-economic benefits. Integrating innovative technologies in breeding programs to accelerate gene flow is critical for sustaining global plant production. Genomic prediction is a promising tool to assist the rapid selection of premiere genotypes and accelerate breeding gains for climate-resilient plant varieties. This review surveys the annals and principles of genomic-enabled prediction. Based on the problem that is investigated through the prediction, as well as several other factors, such as trait heritability, the relationship between the individuals to be predicted and those used to train the models for prediction, the number of markers, sample size, and the interaction between genotype and environment, different levels of accuracy have been reported. Genomic prediction might play a decisive role and facilitate gene flow from gene bank accessions to elite lines in future breeding programs.

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Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery

Nature Genetics ◽

10.1038/ng.3920 ◽

2017 ◽

Vol 49 (9) ◽

pp. 1297-1303 ◽

Cited By ~ 102

Author(s):

John M Hickey ◽

◽

Tinashe Chiurugwi ◽

Ian Mackay ◽

Wayne Powell

Keyword(s):

Plant Breeding ◽

Genomic Prediction ◽

Breeding Programs ◽

Biological Discovery

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Generalizable approaches for genomic prediction of metabolites in plants

10.1101/2021.11.24.469870 ◽

2021 ◽

Author(s):

Lauren J Brzozowski ◽

Malachy T Campbell ◽

Haixiao Hu ◽

Melanie Caffe ◽

Lucia Guterrez ◽

...

Keyword(s):

Plant Breeding ◽

Genomic Prediction ◽

Prediction Accuracy ◽

Group Model ◽

Plant Metabolites ◽

Plant Populations ◽

Breeding Programs ◽

Breeding Lines ◽

Consistent Model ◽

Selection For

Plant metabolites are important for plant breeders to improve nutrition and agronomic performance, yet integrating selection for metabolomic traits is limited by phenotyping expense and limited genetic characterization, especially of uncommon metabolites. As such, developing biologically-based and generalizable genomic selection methods for metabolites that are transferable across plant populations would benefit plant breeding programs. We tested genomic prediction accuracy for more than 600 metabolites measured by GC-MS and LC-MS in oat (Avena sativa L.) seed. Using a discovery germplasm panel, we conducted metabolite GWAS (mGWAS) and selected loci to use in multi-kernel models that encompassed metabolome-wide mGWAS results, or mGWAS from specific metabolite structures or biosynthetic pathways. Metabolite kernels developed from LC-MS metabolites in the discovery panel improved prediction accuracy of LC-MS metabolite traits in the validation panel, consisting of more advanced breeding lines. No approach, however, improved prediction accuracy for GC-MS metabolites. We tested if similar metabolites had consistent model ranks and found that, while different metrics of similarity had different results, using annotation-free methods to group metabolites led to consistent within-group model rankings. Overall, testing biological rationales for developing kernels for genomic prediction across populations, contributes to developing frameworks for plant breeding for metabolite traits.

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Legal protection of plant biotechnological inventions

Agricultural and Food Science ◽

10.23986/afsci.72371 ◽

1989 ◽

Vol 61 (5) ◽

pp. 405-414

Author(s):

P. T. Vanhala ◽

T. Pehu ◽

H. G. Gyllenberg

Keyword(s):

Plant Breeding ◽

Legal Protection ◽

The United States ◽

Plant Production ◽

Breeding Methods ◽

Industrial Countries ◽

Plant Variety ◽

New Varieties ◽

Variety Protection ◽

Biotechnological Inventions

Within biotechnology, plant production is regarded as one of the most promising adaptations. New plant breeding methods are considered to better fulfil the requirements set on patentability than the traditional breeding methods. In Europe, a plant variety can be protected by special legislation. The present patent laws in Europe are not applied to plant biotechnological inventions. The United States has three systems under which new varieties of plants may be protected. These include The 1930 Plant Patent Act, The 1970 Plant Variety Protection Act and The 1952 Patent Statute. Companies that have specialized in plant breeding and organizations representing the industrial countries recommend improvements to the legal protection. On the other hand, farmers and the developing countries are against better protection.

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Integration of transformation technology and traditional breeding of cereals

Acta Agronomica Hungarica ◽

10.1556/aagr.50.2002.3.1 ◽

2002 ◽

Vol 50 (3) ◽

pp. 225-233 ◽

Cited By ~ 1

Author(s):

Z. Bedő

Keyword(s):

Sustainable Development ◽

Transgenic Plant ◽

Plant Breeding ◽

Plant Transformation ◽

Crop Production ◽

Genome Segment ◽

Breeding Methods ◽

The Sustainable Development ◽

The Stability ◽

Traditional Breeding

The integration of conventional plant breeding and plant transformation is necessitated by the fact that, prior to the gene technological phase, traditional breeding methods have to be used to develop agronomically valuable homozygous genotypes which can then be modified for a gene or genome segment by means of gene manipulation techniques. Once the genotype selected by means of conventional breeding has been transformed, traditional methods are again used to examine the agronomic properties of the lines developed from the transgenic plant and the stability of the transgenic variety, following the DUS criteria elaborated by UPOV. The seed production of genetically modified plant varieties must be safe and economical and the cultivation of the variety should contribute to the sustainable development of up-to-date crop production.

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Multi-Species Genomics-Enabled Selection for Improving Agroecosystems Across Space and Time

Frontiers in Plant Science ◽

10.3389/fpls.2021.665349 ◽

2021 ◽

Vol 12 ◽

Author(s):

Marnin D. Wolfe ◽

Jean-Luc Jannink ◽

Michael B. Kantar ◽

Nicholas Santantonio

Keyword(s):

Food Security ◽

Plant Breeding ◽

Crop Yields ◽

Unintended Consequences ◽

Breeding Methods ◽

Agricultural Systems ◽

Breeding Programs ◽

Space And Time ◽

Selection Strategies ◽

Selection For

Plant breeding has been central to global increases in crop yields. Breeding deserves praise for helping to establish better food security, but also shares the responsibility of unintended consequences. Much work has been done describing alternative agricultural systems that seek to alleviate these externalities, however, breeding methods and breeding programs have largely not focused on these systems. Here we explore breeding and selection strategies that better align with these more diverse spatial and temporal agricultural systems.

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New trends in plant breeding - example of soybean

Genetika ◽

10.2298/gensr1501131m ◽

2015 ◽

Vol 47 (1) ◽

pp. 131-142 ◽

Cited By ~ 5

Author(s):

Jegor Miladinovic ◽

Milos Vidic ◽

Vuk Djordjevic ◽

Svetlana Balesevic-Tubic

Keyword(s):

Plant Breeding ◽

Descent Method ◽

Physiological Data ◽

Breeding Methods ◽

Single Seed Descent ◽

Biotic And Abiotic Stresses ◽

Great Opportunity ◽

Conventional Breeding ◽

Remote Sensing Techniques ◽

Single Seed Descent Method

Soybean breeding and selection is a continual process designed to increase yield levels and improve resistance to biotic and abiotic stresses. Soybean breeders have been successful in producing a large number of varieties using conventional breeding methods, the Single Seed Descent method in particular. In recent decades, with the increased use of genetic transformations, backcrossing is more frequent though the only trait that has been commercialized is glyphosate tolerance. Physiological breeding poses a particular challenge, as well as phenotyping and development of useful criteria and techniques suitable for plant breeding. Using modern remote sensing techniques provides great opportunity for collecting a large amount of physiological data in real environment, which is necessary for physiological breeding. Molecular based plant breeding methods and techniques are a conceptual part of any serious breeding program. Among those methods, the most extensively used is marker-assisted selection, as a supplement to conventional breeding methods.

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CRISPR/Cas9 Technology and Applications in Plants

Turkish Journal of Agriculture - Food Science and Technology ◽

10.24925/turjaf.v9i1.1-6.3313 ◽

2021 ◽

Vol 9 (1) ◽

pp. 1-6

Author(s):

Emine Açar ◽

Yıldız Aka Kaçar

Keyword(s):

Plant Breeding ◽

Genome Editing ◽

Agricultural Production ◽

Production Systems ◽

Agricultural Products ◽

Plant Genome ◽

Breeding Programs ◽

Efficient System ◽

Breeding Techniques ◽

Agricultural Production Systems

In order to increase access to nutritious foods around the world, innovative technologies need to be developed and integrated into agricultural production systems. The new plant breeding techniques developed offer many advantages for making modifications in the plant genome. CRSPR/Cas9, one of the genome editing technologies, is an efficient system with high potential that allows the formation of target-oriented mutations in many agricultural products and allows the mutation of new and desired characters to be obtained through breeding programs without the use of foreign genetic elements. In this review, we have summarize the discovery, evalution, functionality, genome editing studies of plants and the strong potentials of CRSPR/Cas9 technology for plant breeding.

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Genomic Selection in Rubber Tree Breeding: A Comparison of Models and Methods for dealing with G × E

10.1101/603662 ◽

2019 ◽

Author(s):

L.M. Souza ◽

F.R. Francisco ◽

P.S. Gonçalves ◽

E.J. Scaloppi Junior ◽

V. Le Guen ◽

...

Keyword(s):

Plant Breeding ◽

Genomic Selection ◽

Genomic Prediction ◽

Prediction Models ◽

Rubber Tree ◽

Tree Breeding ◽

Genotypic Effect ◽

Breeding Programs ◽

Genetic Breeding ◽

Effect Model

AbstractSeveral genomic prediction models incorporating genotype × environment (G×E) interactions have recently been developed and used in genomic selection (GS) in plant breeding programs. G×E interactions decrease selection accuracy and limit genetic gains in plant breeding. Two genomic data sets were used to compare the prediction ability of multi-environment G×E genomic models and two kernel methods (a linear kernel (genomic best linear unbiased predictor, GBLUP) (GB) and a nonlinear kernel (Gaussian kernel, GK)) and prediction accuracy (PA) of five genomic prediction models: (1) one without environmental data (BSG); (2) a single-environment, main genotypic effect model (SM); (3) a multi-environment, main genotypic effect model (MM); (4) a multi-environment, single variance GxE deviation model (MDs); and (5) a multi-environment, environment-specific variance GxE deviation model (MDe). We evaluated the utility of GS with 435 rubber tree individuals in two sites and genotyped the individuals with genotyping-by-sequencing (GBS) of single-nucleotide polymorphisms (SNPs). Prediction models were estimated for diameter (DAP) and height (AP) at different ages, with a heritability ranging from 0.59 to 0.75 for both traits. Applying the model (BSG, SM, MM, MDs, and MDe) and kernel method (GBLUP and GK) combinations to rubber tree data showed that models with the nonlinear GK and linear GBLUP kernel had similar PAs. Multi-environment models were superior to single-environment genomic models regardless the kernel (GBLUP or GK), suggesting that introducing interactions between markers and environmental conditions increases the proportion of variance explained by the model and, more importantly, the PA. In the best scenario (well-watered (WW / GK), an increase of 6.7 and 8.7 fold of genetic gain can be obtained for AP and DAP, respectively, with multi-environment GS (MM, MDe and MDS) than by conventional genetic breeding model (CBM). Furthermore, GS resulted in a more balanced selection response in DAP and AP and if used in conjunction with traditional genetic breeding programs will contribute to a reduction in selection time. With the rapid advances in and declining costs of genotyping methods, balanced against the overall costs of managing large progeny trials and potential increased gains per unit time, we are hopeful that GS can be implemented in rubber tree breeding programs.

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