Genomic Prediction and Genetic Correlation of Agronomic, Blackleg Disease, and Seed Quality Traits in Canola (Brassica napus L.)

Fikere, Mulusew; Barbulescu, Denise M.; Malmberg, M. Michelle; Maharjan, Pankaj; Salisbury, P. A.; Kant, Surya; Panozzo, Joe; Norton, Sally L.; Spangenberg, Germán; Cogan, Noel O. I.; Daetwyler, Hans D.

doi:10.3390/plants9060719

Cited by 19 publications

(20 citation statements)

References 63 publications

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“…Increased phenotypic heritability has been shown to have a greater impact on whole-genome prediction accuracies, more so than training set population size and marker density (Zhang et al, 2017 ). Fikere et al ( 2020 ) reported moderate-to-high genomic prediction accuracies using genomic best linear unbiased prediction (GBLUP) models upon evaluating genetic correlations and genomic prediction accuracies for several agronomic, disease, and seed quality traits in canola. The inclusion of genotype-by-environment interaction in the GBLUP model resulted in further, though slight, improvements in predictions.…”

Section: Genomic Selection In Crop Improvementmentioning

confidence: 99%

Genomics Armed With Diversity Leads the Way in Brassica Improvement in a Changing Global Environment

et al. 2021

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Meeting the needs of a growing world population in the face of imminent climate change is a challenge; breeding of vegetable and oilseed Brassica crops is part of the race in meeting these demands. Available genetic diversity constituting the foundation of breeding is essential in plant improvement. Elite varieties, land races, and crop wild species are important resources of useful variation and are available from existing genepools or genebanks. Conservation of diversity in genepools, genebanks, and even the wild is crucial in preventing the loss of variation for future breeding efforts. In addition, the identification of suitable parental lines and alleles is critical in ensuring the development of resilient Brassica crops. During the past two decades, an increasing number of high-quality nuclear and organellar Brassica genomes have been assembled. Whole-genome re-sequencing and the development of pan-genomes are overcoming the limitations of the single reference genome and provide the basis for further exploration. Genomic and complementary omic tools such as microarrays, transcriptomics, epigenetics, and reverse genetics facilitate the study of crop evolution, breeding histories, and the discovery of loci associated with highly sought-after agronomic traits. Furthermore, in genomic selection, predicted breeding values based on phenotype and genome-wide marker scores allow the preselection of promising genotypes, enhancing genetic gains and substantially quickening the breeding cycle. It is clear that genomics, armed with diversity, is set to lead the way in Brassica improvement; however, a multidisciplinary plant breeding approach that includes phenotype = genotype × environment × management interaction will ultimately ensure the selection of resilient Brassica varieties ready for climate change.

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Section: Genomic Selection In Crop Improvementmentioning

confidence: 99%

Genomics Armed With Diversity Leads the Way in Brassica Improvement in a Changing Global Environment

et al. 2021

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“…The number of breeding programs that have already implemented genomic-assisted breeding has increased considerably in recent years [ 229 , 230 , 231 ]. The use of this approach has been facilitated by the development of high-throughput genotyping techniques (such as genotyping by sequencing and DNA chip arrays) in various important crop species, including maize [ 232 , 233 , 234 ], tomato [ 235 , 236 ], wheat [ 237 , 238 ], and rice [ 239 , 240 ], among others.…”

Section: Gwas Genomic and Phenomic Predictionmentioning

confidence: 99%

OMICs, Epigenetics, and Genome Editing Techniques for Food and Nutritional Security

Gogolev

Ahmar

Akpınar³

et al. 2021

Plants

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The incredible success of crop breeding and agricultural innovation in the last century greatly contributed to the Green Revolution, which significantly increased yields and ensures food security, despite the population explosion. However, new challenges such as rapid climate change, deteriorating soil, and the accumulation of pollutants require much faster responses and more effective solutions that cannot be achieved through traditional breeding. Further prospects for increasing the efficiency of agriculture are undoubtedly associated with the inclusion in the breeding strategy of new knowledge obtained using high-throughput technologies and new tools in the future to ensure the design of new plant genomes and predict the desired phenotype. This article provides an overview of the current state of research in these areas, as well as the study of soil and plant microbiomes, and the prospective use of their potential in a new field of microbiome engineering. In terms of genomic and phenomic predictions, we also propose an integrated approach that combines high-density genotyping and high-throughput phenotyping techniques, which can improve the prediction accuracy of quantitative traits in crop species.

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“…However, it requires the construction of a prediction pattern by integrating marker information with a phenotypic database in a model training step [53] and has led to fundamental changes in plant breeding programs [58]. Genetic progression is improved by genomic selection in crop breeding programs via phenotypic predictions to select ideal phenotypes, based only on their genomic information [59].…”

Section: Benefits and Challenges Of Genomic-enabled Prediction In Plant Breedingmentioning

confidence: 99%

Plant Breeding Integrated with Genomic-Enabled Prediction

Bidabadi¹,

Sharifi²,

Jain³

2021

obm genet

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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 and Genetic Correlation of Agronomic, Blackleg Disease, and Seed Quality Traits in Canola (Brassica napus L.)

Cited by 19 publications

References 63 publications

Genomics Armed With Diversity Leads the Way in Brassica Improvement in a Changing Global Environment

Genomics Armed With Diversity Leads the Way in Brassica Improvement in a Changing Global Environment

OMICs, Epigenetics, and Genome Editing Techniques for Food and Nutritional Security

Plant Breeding Integrated with Genomic-Enabled Prediction

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