Genomic selection in plant breeding: Key factors shaping two decades of progress

Alemu, Admas; Åstrand, Johanna; Montesinos-López, Osval A.; Isidro y Sánchez, Julio; Fernández-Gónzalez, Javier; Tadesse, Wuletaw; Vetukuri, Ramesh R.; Carlsson, Anders S.; Ceplitis, Alf; Crossa, José; Ortiz, Rodomiro; Chawade, Aakash

doi:10.1016/j.molp.2024.03.007

Cited by 11 publications

(1 citation statement)

References 301 publications

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“…Though GS breeding designs have immense potential for expediting the breeding process, the efficacy of genomic selection and prediction in plant breeding can be hindered by the complexity of target genes and polygenic trait stacks of interest [ 67 ]. Full efficiency as a breeding tool requires accommodation for all potential setbacks, including heritability and complex general architecture.…”

Section: Genomic Selectionmentioning

confidence: 99%

Tools and Techniques to Accelerate Crop Breeding

Williams,

Subramani,

Lofton

et al. 2024

Plants

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As climate changes and a growing global population continue to escalate the need for greater production capabilities of food crops, technological advances in agricultural and crop research will remain a necessity. While great advances in crop improvement over the past century have contributed to massive increases in yield, classic breeding schemes lack the rate of genetic gain needed to meet future demands. In the past decade, new breeding techniques and tools have been developed to aid in crop improvement. One such advancement is the use of speed breeding. Speed breeding is known as the application of methods that significantly reduce the time between crop generations, thereby streamlining breeding and research efforts. These rapid-generation advancement tactics help to accelerate the pace of crop improvement efforts to sustain food security and meet the food, feed, and fiber demands of the world’s growing population. Speed breeding may be achieved through a variety of techniques, including environmental optimization, genomic selection, CRISPR-Cas9 technology, and epigenomic tools. This review aims to discuss these prominent advances in crop breeding technologies and techniques that have the potential to greatly improve plant breeders’ ability to rapidly produce vital cultivars.

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Section: Genomic Selectionmentioning

confidence: 99%

Tools and Techniques to Accelerate Crop Breeding

Williams,

Subramani,

Lofton

et al. 2024

Plants

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A Modified Bayesian Optimization Approach for Determining a Training Set to Identify the Best Genotypes from a Candidate Population in Genomic Selection

Tu,

Liao

2024

JABES

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Training set optimization is a crucial factor affecting the probability of success for plant breeding programs using genomic selection. Conventionally, the training set optimization is developed to maximize Pearson’s correlation between true breeding values and genomic estimated breeding values for a testing population, because it is an essential component of genetic gain in plant breeding. However, many practical breeding programs aim to identify the best genotypes for target traits in a breeding population. A modified Bayesian optimization approach is therefore developed in this study to construct training sets for tackling such an interesting problem. The proposed approach is based on Monte Carlo simulation and data cross-validation, which is shown to be competitive with the existing methods developed to achieve the maximal Pearson’s correlation. Four real genome datasets, including two rice, one wheat, and one soybean, are analyzed in this study. An R package is generated to facilitate the application of the proposed approach. Supplementary materials accompanying this paper appear online.

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Has genomic selection fulfilled its promise?

Banks

2024

CABI Reviews

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Genomic selection has been increasingly implemented since its initial description in 2001. The initial focus of activity was in the dairy industry in the developed world but it has now been adopted in all major livestock species, and adoption is underway in most agronomically important plants. The promise of genomic selection includes increased accuracy of estimation of genetic merit, earlier estimation of genetic merit, the capacity to make improvements in traits previously less tractable to genetic change, and the capacity to estimate genetic merit in animals without phenotypic records. Each of these benefits has been realised in practice, with the significance of the opportunity varying with species. At the same time, ease of adoption and realisation of benefits has varied, based on three broad parameters: the availability of suitable (and sufficiently cheap) genotyping tools, the prior extent of systematic recording of phenotypes, and the use of estimates of genetic merit in selection. The effectiveness of genomic selection depends on the existence and composition of a genomic reference population, and this is the most significant challenge for any industry, breed or breeding program seeking to achieve the available benefits. The challenge is two-fold: first, to ensure that sufficient of the right phenotypes are recorded on the right animals, and second, flowing directly from the first, is to fund the phenotyping effort – and challenges aspects are ongoing. “Right” in the context of both phenotypes and animals means most informative, or relevant to the breeding objective or goal. No standard approach has been outlined for addressing these challenges, but the review presents some simple conceptual thinking that can assist. Genomic selection also heightens the importance of ensuring maintenance of genetic diversity, and of monitoring changes in both selected and non-selected traits. Genomic selection has fulfilled its promise where applied effectively and is increasing scope for genetic improvement both in rate of progress and trait coverage. At the same time, its dependencies must be addressed in order to the potential benefits to be realised, and this will likely require new organisational and funding arrangements in many situations.

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Genomic selection in plant breeding: Key factors shaping two decades of progress

Cited by 11 publications

References 301 publications

Tools and Techniques to Accelerate Crop Breeding

Tools and Techniques to Accelerate Crop Breeding

A Modified Bayesian Optimization Approach for Determining a Training Set to Identify the Best Genotypes from a Candidate Population in Genomic Selection

Has genomic selection fulfilled its promise?

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