AlphaSimR: an R package for breeding program simulations

Abstract This paper introduces AlphaSimR, an R package for stochastic simulations of plant and animal breeding programs. AlphaSimR is a highly flexible software package able to simulate a wide range of plant and animal breeding programs for diploid and autopolyploid species. AlphaSimR is ideal for testing the overall strategy and detailed design of breeding programs. AlphaSimR utilizes a scripting approach to building simulations that is particularly well suited for modeling highly complex breeding programs, such as commercial breeding programs. The primary benefit of this scripting approach is that it frees users from preset breeding program designs and allows them to model nearly any breeding program design. This paper lists the main features of AlphaSimR and provides a brief example simulation to show how to use the software.

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AlphaSimR: An R-package for Breeding Program Simulations

10.1101/2020.08.10.245167 ◽

2020 ◽

Cited By ~ 6

Author(s):

R. Chris Gaynor ◽

Gregor Gorjanc ◽

John M. Hickey

Keyword(s):

Software Package ◽

R Package ◽

Animal Breeding ◽

Breeding Program ◽

Stochastic Simulations ◽

Breeding Programs ◽

Detailed Design ◽

Building Simulations ◽

Wide Range ◽

Commercial Breeding

AbstractThis paper introduces AlphaSimR, an R package for stochastic simulations of plant and animal breeding programs. AlphaSimR is a highly flexible software package able to simulate a wide range of plant and animal breeding programs for diploid and autopolyploid species. AlphaSimR is ideal for testing the overall strategy and detailed design of breeding programs. AlphaSimR utilizes a scripting approach to building simulations that is particularly well suited for modeling highly complex breeding programs, such as commercial breeding programs. The primary benefit of this scripting approach is that it frees users from preset breeding program designs and allows them to model nearly any breeding program design. This paper lists the main features of AlphaSimR and provides a brief example simulation to show how to use the software.

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A unifying concept of animal breeding programs

10.1101/2020.07.08.193201 ◽

2020 ◽

Author(s):

H. Simianer ◽

A. Ganesan ◽

L. Buettgen ◽

N.T. Ha ◽

T. Pook

Keyword(s):

R Package ◽

Companion Paper ◽

Animal Breeding ◽

Breeding Program ◽

General Definition ◽

Full Description ◽

Genetic Progress ◽

Breeding Programs ◽

Definition Of ◽

Transgenic Technologies

ABSTRACTModern animal breeding programs are constantly evolving with advances in breeding theory, biotechnology and genetics. Surprisingly, there seems to be no generally accepted succinct definition of what exactly a breeding program is, neither is there a unified language to describe breeding programs in a comprehensive, unambiguous and reproducible way. In this work, we try to fill this gap by suggesting a general definition of breeding programs that also pertains to cases where genetic progress is not achieved through selection, but e.g. through transgenic technologies, or the aim is not to generate genetic progress, but e.g. to maintain genetic diversity. The key idea of the underlying concept is to represent a breeding program in modular form as a directed graph that is composed of nodes and edges, where nodes represent cohorts of breeding units, usually individuals, and edges represent breeding activities, like ‘selection’ or ‘reproduction’. We claim, that by defining a comprehensive set of nodes and edges it is possible to represent any breeding program of arbitrary complexity by such a graph, which thus comprises a full description of the breeding program. This concept is implemented in a web-based tool (MoBPSweb, available at www.mobps.de) which is described in a companion paper, and has a link to the R-package MoBPS (Modular Breeding Program Simulator) to simulate the described breeding programs. The approach is illustrated by showcasing three different breeding programs of increasing complexity. Finally, potential limitations of the concept are indicated and extensions to other fields, like plant breeding, are discussed.

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Why and How to Switch to Genomic Selection: Lessons From Plant and Animal Breeding Experience

Frontiers in Genetics ◽

10.3389/fgene.2021.629737 ◽

2021 ◽

Vol 12 ◽

Author(s):

◽

Aline Fugeray-Scarbel ◽

Catherine Bastien ◽

Mathilde Dupont-Nivet ◽

Stéphane Lemarié

Keyword(s):

Genetic Diversity ◽

Genomic Selection ◽

Plant Species ◽

Animal Species ◽

Animal Breeding ◽

Breeding Cycle ◽

Breeding Programs ◽

The Third ◽

Wide Range ◽

Selection For

The present study is a transversal analysis of the interest in genomic selection for plant and animal species. It focuses on the arguments that may convince breeders to switch to genomic selection. The arguments are classified into three different “bricks.” The first brick considers the addition of genotyping to improve the accuracy of the prediction of breeding values. The second consists of saving costs and/or shortening the breeding cycle by replacing all or a portion of the phenotyping effort with genotyping. The third concerns population management to improve the choice of parents to either optimize crossbreeding or maintain genetic diversity. We analyse the relevance of these different bricks for a wide range of animal and plant species and sought to explain the differences between species according to their biological specificities and the organization of breeding programs.

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“Crispy” Blackberry Genotypes: A Breeding Innovation of the University of Arkansas Blackberry Breeding Program

HortScience ◽

10.21273/hortsci.51.5.468 ◽

2016 ◽

Vol 51 (5) ◽

pp. 468-471 ◽

Cited By ~ 11

Author(s):

Alejandra A. Salgado ◽

John R. Clark

Keyword(s):

Negative Impact ◽

Breeding Program ◽

University Of Arkansas ◽

Fresh Market ◽

Breeding Programs ◽

Color Reversion ◽

Wide Range ◽

Penetration Force ◽

Postharvest Handling ◽

The University

The University of Arkansas (UA) blackberry breeding program began in 1964, with the aim to provide high-quality fruit to the fresh market industry. One of the important traits for successful blackberry (Rubus subgenus Rubus Watson) postharvest handling is flesh firmness, so developing cultivars with high firmness is a top priority for the fresh market blackberry breeding programs across the world. In particular, the Arkansas blackberry program has a wide range of genotypes with exceptional firmness characteristics, including fruit with a unique crispy texture and firmness. During 2013 and 2014, fruit firmness measurements were done on 15 Arkansas genotypes including those with crispy and noncrispy textures. Firmness measurements consisted of fruit compression, skin drupelet penetration, and receptacle penetration. Confocal photos were taken on sections of berries of a subset of crispy and noncrispy genotypes, and color reversion was evaluated among these genotypes after storage. Compression force values differentiated crispy and noncrispy genotypes, with average values of 11.8 Newton (N) and 8.0 N, respectively. Drupelet penetration force was also higher for crispy genotypes averaging 0.23 N and noncrispy 0.15 N; similarly, receptacle penetration force averaged 0.20 N for crispy and 0.18 N for noncrispy genotypes. Visual inspection of fruit tissue revealed that drupelet mesocarp cells and receptacle cells and cell walls of crispy genotypes maintained their structure during ripening and did not break apart, whereas noncrispy genotypes did not maintain their structure and cellular integrity. Color reversion is a postharvest disorder in which drupelets of blackberry fruits turn red after being black at harvest. Therefore, it has a negative impact for growers, shippers, and consumers. After storage at 5 °C for 7 days, crispy genotypes expressed low levels of reversion compared with noncrispy genotypes. For crispy genotypes, 13.2% of drupelets developed color reversion, whereas a 41.0% developed this disorder in noncrispy genotypes, implying a better postharvest potential of this texture.

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Software update: Moving the R package sommer to multivariate mixed models for genome-assisted prediction

10.1101/354639 ◽

2018 ◽

Cited By ~ 4

Author(s):

Giovanny Covarrubias-Pazaran

Keyword(s):

Random Effects ◽

Mixed Models ◽

Mixed Model ◽

R Package ◽

Animal Breeding ◽

Breeding Programs ◽

Incidence Matrices ◽

Software Update ◽

Trial Analysis ◽

User Friendly

AbstractIn the last decade the use of mixed models has become a pivotal part in the implementation of genome-assisted prediction in plant and animal breeding programs. Exploiting the use genetic correlation among traits through multivariate predictions has been proposed in recent years as a way to boost prediction accuracy and understand pleiotropy and other genetic and ecological phenomena better. Multiple mixed model solvers able to use relationship matrices or deal with marker-based incidence matrices have been released in the last years but multivariate versions are scarse. Such solvers have become quite popular in plant and animal breeding thanks to user-friendly platforms such as R. Among such software one of the most recent and popular is the sommer package. In this short communication we discuss the update of the package that is able to run multivariate mixed models with multiple random effects and different covariance structures at the level of random effects and trait-to-trait covariance along with other functionalities for genetic analysis and field trial analysis to enhance the genome-assisted prediction capabilities of researchers.

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Making WAVES in Breedbase: An Integrated Spectral Data Storage and Analysis Pipeline for Plant Breeding Programs

10.1101/2020.09.18.278549 ◽

2020 ◽

Author(s):

Jenna Hershberger ◽

Nicolas Morales ◽

Christiano C. Simoes ◽

Bryan Ellerbrock ◽

Guillaume Bauchet ◽

...

Keyword(s):

Plant Breeding ◽

Open Source ◽

Spectral Data ◽

Data Storage ◽

Cross Validation ◽

R Package ◽

List Type ◽

Breeding Programs ◽

Wide Range ◽

Prediction Functions

ABSTRACTVisible and near-infrared (vis-NIRS) spectroscopy is a promising tool for increasing phenotyping throughput in plant breeding programs, but existing analysis software packages are not optimized for a breeding context. Additionally, commercial software options are often outside of budget constraints for some breeding and research programs. To that end, we developed an open-source R package, waves, for the streamlined analysis of spectral data with several cross-validation schemes to assess prediction accuracy. Waves is compatible with a wide range of spectrometer models and performs visualization, filtering, aggregation, cross-validation set formation, model training, and prediction functions for the association of vis-NIRS spectra with reference measurements. Furthermore, we have integrated this package into the Breedbase family of open-source databases, expanding the analysis capabilities of this growing digital ecosystem to a number of crop species. Taken together, the standalone and Breedbase versions of waves enhance the accessibility of tools for the analysis of spectral data during the plant breeding process.Core ideaswaves is an open-source R package for spectral data analysis in plant breedingBreeding relevant cross-validation schemes to evaluate predictive accuracy of modelsExtension of Breedbase—an open-source database—to support spectral data storageGraphical user interface developed for implementation of waves in Breedbase

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Estimation of realized rates of genetic gain and indicators for breeding program assessment

10.1101/409342 ◽

2018 ◽

Cited By ~ 2

Author(s):

J.E. Rutkoski

Keyword(s):

Oryza Sativa ◽

Genetic Gain ◽

Program Assessment ◽

Careful Consideration ◽

Breeding Program ◽

Stochastic Simulations ◽

Breeding Value ◽

Estimation Methods ◽

Breeding Programs ◽

The Past

AbstractRoutine estimation of the rate of genetic gain (ΔGt) realized by a breeding program has been proposed as a means to monitor its effectiveness. Several methods of realized ΔGt estimation have been utilized in other studies, but none have been objectively evaluated in a plant breeding context. Stochastic simulations of 80 rice (Oryza sativa) breeding programs over 28 years were done to generate data used to evaluate five methods of realized ΔGt estimation in terms of error, precision, efficiency and correlation between true and predicted annual mean breeding values. Two indicators of ΔGt, the expected ΔGt and the average number of equivalent complete generations (EqCg), were described and evaluated. At best, estimates of realized ΔGt were over or underestimated by 15% and 27% when considering all 28 years and the past 15 years of breeding respectively. The best methods were the control population, estimated breeding value, and ERA trial methods. Among these, correlations between true and estimated ΔGt were at best 0.59, indicating that these methods cannot very accurately rank breeding programs in terms of realized ΔGt. The expected ΔGt and the average EqCg were shown to be useful indicators for determining if a non-zero genetic gain is expected. Determining which of the three best realized ΔGt estimation methods evaluated, if any, would be appropriate for any given breeding program should be done with careful consideration of the objectives, resources, seed stocks, and structure of the data available.

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Catalase Polymorphism and Inheritance in Peach

HortScience ◽

10.21273/hortsci.27.1.41 ◽

1992 ◽

Vol 27 (1) ◽

pp. 41-43 ◽

Cited By ~ 3

Author(s):

Dennis J. Werner

Keyword(s):

Prunus Persica ◽

Plant Introduction ◽

The United States ◽

Male Parent ◽

Heterozygous State ◽

Breeding Programs ◽

Wide Range ◽

The World ◽

Commercial Cultivars ◽

Commercial Breeding

Catalase isozymes were examined in a wide range of peach [Prunus persica (L.) Batsch] cultivars representing historical U.S. cultivars, commercial cultivars from numerous North American breeding programs, and the peach plant introduction (PI) collection. All historical peach cultivars from the United States and those released from commercial breeding programs were fixed for the slow (Cat l-2) allele, with the exception of `Belle of Georgia', `Honeyglo' nectarine, and various cultivars from the Univ. of Florida breeding program, which possessed a fast-migrating (Cat 1-l) allele in homozygous or heterozygous state. Polymorphism was revealed in the 51 peach PI clones examined, with allelic frequencies of 0.69 and 0.31 for the Cat l-2 and Cat l-1 alleles, respectively. Most PIs that originated directly from China were homozygous Cat l-l/Cat l-l, while most PI clones introduced from Europe were homozygous Cat l-2/Cat l-2. Examination of the catalase genotype of cultivars previously proposed as the possible male parent of `Belle of Georgia' (`Champion', `Early Crawford', `Late Crawford', `Oldmixion Free', and `Stump-the-World') revealed that none of these cultivars could have been the male parent of `Belle of Georgia'. Segregation data from various peach crosses was consistent with the hypothesis that catalase polymorphism could be explained by the presence of two alleles at a single locus.

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MoBPSweb: A web-based framework to simulate and compare breeding programs

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab023 ◽

2021 ◽

Author(s):

Torsten Pook ◽

Lisa Büttgen ◽

Amudha Ganesan ◽

Ngoc-Thuy Ha ◽

Henner Simianer

Keyword(s):

Relevant Information ◽

R Package ◽

Simulation Software ◽

Breeding Program ◽

Breeding Value ◽

Simulation Framework ◽

Breeding Programs ◽

Web Based ◽

Value Estimation ◽

Downstream Analysis

Abstract In this work, we introduce a new web-based simulation framework (”MoBPSweb”) that combines a unified language to describe breeding programs with the simulation software MoBPS, standing for ’Modular Breeding Program Simulator’. Thereby, MoBPSweb provides a flexible environment to log, simulate, evaluate, and compare breeding programs. Inputs can be provided via modules ranging from a Vis.js-based environment for” drawing” the breeding program to a variety of modules to provide phenotype information, economic parameters, and other relevant information. Similarly, results of the simulation study can be extracted and compared to other scenarios via output modules (e.g. observed phenotypes, the accuracy of breeding value estimation, inbreeding rates), while all simulations and downstream analysis are executed in the highly efficient R-package MoBPS.

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Matoa (Pometia Pinata Foster): Local Fruit Papua and Strategy Development

Beccariana Botanical Research Bulletin ◽

10.30862/bbrp.v7i1.276 ◽

2010 ◽

Vol 7 (1) ◽

Author(s):

Julius D. Nugroho

Keyword(s):

Genetic Resources ◽

Fruit Tree ◽

Breeding Program ◽

Strategy Development ◽

Local Market ◽

Font Size ◽

Breeding Programs ◽

Irian Jaya ◽

Forest Exploitation ◽

Program Strategy

Matoa (Pometia pinnata) is a local fruit of  Papua (formerly called Irian Jaya) which has high potensial to develop as comercial fruit. Highly significant genetic resources of matoa potentially for breeding program in Papua are being threatened as a result of cutting down trees for fruit harvesting and of forest exploitation for timber. Besides the loss of genetic resources facing now, other major problems should be consider for conservation and domestication of this fruit tree species i.e. lack of silviculture and agronomy knowledge for further breeding programs; matoa production only for local market; and inadequate government policy for matoa breeding program. Strategy developed for matoa conservation and domestication should also concern about time limited due to the fast loss of genetic poll. This paper provides a general overview of strategy for conservation and domestication of Pometia pinnata with special reference to Papua.

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