Genomic selection ≈ Genomic selection
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Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection Open
Significance The introduction of genomic selection in dairy cattle improvement programs in 2008 was expected to increase rates of genetic gain, particularly for traits with low heritabilities, such as fertility and longevity. Our analysis …
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<b>Genes Software – extended and integrated with the R, Matlab and Selegen Open
O programa GENES é um software destinado à análise e processamento de dados fenotípicos e moleculares por meio de diferentes modelos biométricos. Na versão atual estão disponibilizadas rotinas de integração com o software livre R e com os …
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Status and prospects of genome‐wide association studies in plants Open
Genome‐wide association studies (GWAS) have developed into a powerful and ubiquitous tool for the investigation of complex traits. In large part, this was fueled by advances in genomic technology, enabling us to examine genome‐wide genetic…
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Genomic Selection in the Era of Next Generation Sequencing for Complex Traits in Plant Breeding Open
Genomic selection (GS) is a promising approach exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. In plant breeding, it provides opportunities to increase …
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The Value of Expanding the Training Population to Improve Genomic Selection Models in Tetraploid Potato Open
Genomic selection (GS) is becoming increasingly applicable to crops as the genotyping costs continue to decrease, which makes it an attractive alternative to traditional selective breeding based on observed phenotypes. With genome-wide mol…
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Enhancing genetic gain in the era of molecular breeding Open
As one of the important concepts in conventional quantitative genetics and breeding, genetic gain can be defined as the amount of increase in performance that is achieved annually through artificial selection. To develop pro ducts that mee…
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On the Road to Breeding 4.0: Unraveling the Good, the Bad, and the Boring of Crop Quantitative Genomics Open
Understanding the quantitative genetics of crops has been and will continue to be central to maintaining and improving global food security. We outline four stages that plant breeding either has already achieved or will probably soon achie…
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Genomic selection methods for crop improvement: Current status and prospects Open
With marker and phenotype information from observed populations, genomic selection (GS) can be used to establish associations between markers and phenotypes. It aims to use genome-wide markers to estimate the effects of all loci and thereb…
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A review of deep learning applications for genomic selection Open
Background Several conventional genomic Bayesian (or no Bayesian) prediction methods have been proposed including the standard additive genetic effect model for which the variance components are estimated with mixed model equations. In rec…
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GALLO: An R package for genomic annotation and integration of multiple data sources in livestock for positional candidate loci Open
Background The development of high-throughput sequencing and genotyping methodologies has enabled the identification of thousands of genomic regions associated with several complex traits. The integration of multiple sources of biological …
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Combining High‐Throughput Phenotyping and Genomic Information to Increase Prediction and Selection Accuracy in Wheat Breeding Open
Genomics and phenomics have promised to revolutionize the field of plant breeding. The integration of these two fields has just begun and is being driven through big data by advances in next‐generation sequencing and developments of field‐…
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The Modern Plant Breeding Triangle: Optimizing the Use of Genomics, Phenomics, and Enviromics Data Open
OPINION article Front. Plant Sci., 16 April 2021Sec. Plant Breeding https://doi.org/10.3389/fpls.2021.651480
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A Two‐Part Strategy for Using Genomic Selection to Develop Inbred Lines Open
We propose a strategy for implementing genomic selection in plant breeding programs for developing inbred lines that reorganizes traditional breeding programs into two distinct components. These components are: (i) a population improvement…
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Non-additive Effects in Genomic Selection Open
In the last decade, genomic selection has become a standard in the genetic evaluation of livestock populations. However, most procedures for the implementation of genomic selection only consider the additive effects associated with SNP (Si…
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Toward the sequence-based breeding in legumes in the post-genome sequencing era Open
Efficiency of breeding programs of legume crops such as chickpea, pigeonpea and groundnut has been considerably improved over the past decade through deployment of modern genomic tools and technologies. For instance, next-generation sequen…
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Back to the future: revisiting MAS as a tool for modern plant breeding Open
New models for integration of major gene MAS with modern breeding approaches stand to greatly enhance the reliability and efficiency of breeding, facilitating the leveraging of traditional genetic diversity. Genetic diversity is well recog…
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Use of Crop Growth Models with Whole‐Genome Prediction: Application to a Maize Multienvironment Trial Open
High throughput genotyping, phenotyping, and envirotyping applied within plant breeding multienvironment trials (METs) provide the data foundations for selection and tackling genotype × environment interactions (GEIs) through whole‐genome …
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Genomic Selection for Processing and End‐Use Quality Traits in the CIMMYT Spring Bread Wheat Breeding Program Open
Wheat ( Triticum aestivum L.) cultivars must possess suitable end‐use quality for release and consumer acceptability. However, breeding for quality traits is often considered a secondary target relative to yield largely because of amount o…
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AlphaSim: Software for Breeding Program Simulation Open
This paper describes AlphaSim, a software package for simulating plant and animal breeding programs. AlphaSim enables the simulation of multiple aspects of breeding programs with a high degree of flexibility. AlphaSim simulates breeding pr…
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Effect of Trait Heritability, Training Population Size and Marker Density on Genomic Prediction Accuracy Estimation in 22 bi-parental Tropical Maize Populations Open
Genomic selection is being used increasingly in plant breeding to accelerate genetic gain per unit time. One of the most important applications of genomic selection in maize breeding is to predict and select the best un-phenotyped lines in…
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Genomic selection in plant breeding: Key factors shaping two decades of progress Open
Genomic selection, the application of genomic prediction (GP) models to select candidate individuals, has significantly advanced in the past two decades, effectively accelerating genetic gains in plant breeding. This article provides a hol…
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Optimising Genomic Selection in Wheat: Effect of Marker Density, Population Size and Population Structure on Prediction Accuracy Open
Genomic selection applied to plant breeding enables earlier estimates of a line’s performance and significant reductions in generation interval. Several factors affecting prediction accuracy should be well understood if breeders are to har…
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Multitrait, Random Regression, or Simple Repeatability Model in High‐Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield Open
High‐throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( Triticum aestivum L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and geno…
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Beyond Genomic Prediction: Combining Different Types of <i>omics</i> Data Can Improve Prediction of Hybrid Performance in Maize Open
The ability to predict the agronomic performance of single-crosses with high precision is essential for selecting superior candidates for hybrid breeding. With recent technological advances, thousands of new parent lines, and, consequently…
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Multi-environment Genomic Prediction of Plant Traits Using Deep Learners With Dense Architecture Open
Genomic selection is revolutionizing plant breeding and therefore methods that improve prediction accuracy are useful. For this reason, active research is being conducted to build and test methods from other areas and adapt them to the con…
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Hybrid breeding of rice via genomic selection Open
Summary Hybrid breeding is the main strategy for improving productivity in many crops, especially in rice and maize. Genomic hybrid breeding is a technology that uses whole‐genome markers to predict future hybrids. Predicted superior hybri…
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Applications of Machine Learning Methods to Genomic Selection in Breeding Wheat for Rust Resistance Open
New methods and algorithms are being developed for predicting untested phenotypes in schemes commonly used in genomic selection (GS). The prediction of disease resistance in GS has its own peculiarities: a) there is consensus about the add…
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Factors Affecting the Accuracy of Genomic Selection for Agricultural Economic Traits in Maize, Cattle, and Pig Populations Open
Genomic Selection (GS) has been proved to be a powerful tool for estimating genetic values in plant and livestock breeding. Newly developed sequencing technologies have dramatically reduced the cost of genotyping and significantly increase…
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Increasing Genomic‐Enabled Prediction Accuracy by Modeling Genotype × Environment Interactions in Kansas Wheat Open
Wheat ( Triticum aestivum L.) breeding programs test experimental lines in multiple locations over multiple years to get an accurate assessment of grain yield and yield stability. Selections in early generations of the breeding pipeline ar…
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Initiating maize pre-breeding programs using genomic selection to harness polygenic variation from landrace populations Open
Results of this study provide guidelines for SeeD and similar initiatives on how to initiate pre-breeding programs that aim to harness polygenic variation from landraces.