Strengthening Public Breeding Pipelines by Emphasizing Quantitative Genetics Principles and Open Source Data Management

Covarrubias‐Pazaran, Giovanny; Martini, Johannes W. R.; Quinn, Michael J.; Atlin, G. N.

doi:10.3389/fpls.2021.681624

Cited by 15 publications

(9 citation statements)

References 15 publications

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“…To ensure successful implementation of GS, breeders must ensure that the necessary facilities and equipment are available on site (e.g., freezers, sterile laboratories), that field technicians are appropriately trained, that genotyping and sample transport costs are identified, and that they collaborate with biometricians to optimize field testing and phenotype collection and to develop GS pipelines using appropriate statistical models (Covarrubias‐Pazaran et al., 2021). In our study, simple pedigree‐based and GS models were used for demonstration, but models that efficiently account for multiple harvests, as is the case in tea breeding, could be considered to obtain the most accurate predictions of genotype performance over time and across a range of environments (De Faveri et al., 2022).…”

Section: Discussionmentioning

confidence: 99%

Genomic selection strategies to increase genetic gain in tea breeding programs

et al. 2022

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Tea [Camellia sinensis (L.) O. Kuntze] is mainly grown in low-to middle-income countries (LMIC) and is a global commodity. Breeding programs in these countries face the challenge of increasing genetic gain because the accuracy of selecting superior genotypes is low and resources are limited. Phenotypic selection (PS) is traditionally the primary method of developing improved tea varieties and can take over 16 yr. Genomic selection (GS) can be used to improve the efficiency of tea breeding by increasing selection accuracy and shortening the generation interval and breeding cycle. Our main objective was to investigate the potential of implementing GS in tea-breeding programs to speed up genetic progress despite the low cost of PS in LMIC. We used stochastic simulations to compare three GS-breeding programs with a Pedigree and PS program. The PS program mimicked a practical commercial teabreeding program over a 40-yr breeding period. All the GS programs achieved at least 1.65 times higher genetic gains than the PS program and 1.4 times compared with Seed-Ped program. Seed-GSc was the most cost-effective strategy of implementing GS in tea-breeding programs. It introduces GS at the seedlings stage to increase selection accuracy early in the program and reduced the generation interval to 2 yr. The Seed-Ped program outperformed PS by 1.2 times and could be implemented where it is not possible to use GS. Our results indicate that GS could be used to improve genetic gain per unit time and cost even in cost-constrained tea-breeding programs.

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Section: Discussionmentioning

confidence: 99%

Genomic selection strategies to increase genetic gain in tea breeding programs

et al. 2022

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“…The average number of consecutive years of trials used for genetic trend estimation was nine (Table S8 ). Following the recommendations of Excellence-in-Breeding Platform 20 , 50 , 51 , data from each breeding pipeline and trait were analysed separately. Due to unbalanced nature of the data and because this is part of an overall exercise across CGIAR crop breeding programs, a common methodology has been used that is considered best ft across a diverse array of situations in which these breeding programs operate, including perennial and annual crops, with and without molecular information, different phenotyping strategies, experimental designs, and use of checks.…”

Section: Methodsmentioning

confidence: 99%

Genetic trends in CIMMYT’s tropical maize breeding pipelines

Prasanna

Burgueño

Beyene

et al. 2022

Sci Rep

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Fostering a culture of continuous improvement through regular monitoring of genetic trends in breeding pipelines is essential to improve efficiency and increase accountability. This is the first global study to estimate genetic trends across the International Maize and Wheat Improvement Center (CIMMYT) tropical maize breeding pipelines in eastern and southern Africa (ESA), South Asia, and Latin America over the past decade. Data from a total of 4152 advanced breeding trials and 34,813 entries, conducted at 1331 locations in 28 countries globally, were used for this study. Genetic trends for grain yield reached up to 138 kg ha−1 yr−1 in ESA, 118 kg ha−1 yr−1 South Asia and 143 kg ha−1 yr−1 in Latin America. Genetic trend was, in part, related to the extent of deployment of new breeding tools in each pipeline, strength of an extensive phenotyping network, and funding stability. Over the past decade, CIMMYT’s breeding pipelines have significantly evolved, incorporating new tools/technologies to increase selection accuracy and intensity, while reducing cycle time. The first pipeline, Eastern Africa Product Profile 1a (EA-PP1a), to implement marker-assisted forward-breeding for resistance to key diseases, coupled with rapid-cycle genomic selection for drought, recorded a genetic trend of 2.46% per year highlighting the potential for deploying new tools/technologies to increase genetic gain.

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“…For IRBP, changing environmental, economic, and market conditions require breeding for new cultivars with higher yield, quality, and disease resistance in shorter breeding cycles and more efficiently. A preferred strategy to achieve this is the implementation of modern breeding strategies such as genomic selection coupled with shorter breeding cycles, what in turn requires and benefits from a centralized breeding database (Covarrubias‐Pazaran et al., 2021). In this paper, we described the consolidation and curation process of all the information available to date from IRBP's breeding records into a unified database, as well as its structure and major features.…”

Section: Resultsmentioning

confidence: 99%

Consolidating 23 years of historical data from an irrigated subtropical rice breeding program in Uruguay

et al. 2023

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Breeding programs generate vast amount of data which are often scattered in separate files. This hinders the application of modern breeding tools such as multienvironment analyses and genomic selection. This research work describes the process of consolidating 23 years of phenotypic, pedigree, and genomic records from the Uruguayan national rice (Oryza sativa L.) breeding program, and the features and structure of the resulting database. Using a custom-made R code, we gathered all the available data from 1997 to 2020 corresponding to field trials, blast disease evaluation nurseries, laboratory analyses of milling and cooking quality, pedigree information, and genomic information for selected advanced breeding lines, and organized it into a relational database. Records of 996 trials in 12 locations over a span of 23 years, 91,636 field plots with information on 14 phenotypic variables, pedigree for 19,447 genotypes, and genomic information regarding 61,260 single nucleotide polymorphism (SNP) markers for 965 genotypes were recovered. The dataset is structured in trials, phenotypes, lines, genomic information, and SNP tables in an easy-to-access relational database, which will be a valuable resource for rice breeding.

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Strengthening Public Breeding Pipelines by Emphasizing Quantitative Genetics Principles and Open Source Data Management

Cited by 15 publications

References 15 publications

Genomic selection strategies to increase genetic gain in tea breeding programs

Genomic selection strategies to increase genetic gain in tea breeding programs

Genetic trends in CIMMYT’s tropical maize breeding pipelines

Consolidating 23 years of historical data from an irrigated subtropical rice breeding program in Uruguay

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