scholarly journals Optimum breeding strategies using genomic and phenotypic selection for the simultaneous improvement of two traits

2021 ◽  
Author(s):  
Jose J. Marulanda ◽  
Xuefei Mi ◽  
H. Friedrich Utz ◽  
Albrecht E. Melchinger ◽  
Tobias Würschum ◽  
...  
Keyword(s):  
Variance Components ◽  
Phenotypic Selection ◽  
R Package ◽  
Breeding Strategy ◽  
Breeding Strategies ◽  
Selection Gain ◽  
One Stage ◽  
Individual Traits ◽  
Economic Weights ◽  
Selection Indices

Abstract Key message A breeding strategy combining genomic with one-stage phenotypic selection maximizes annual selection gain for net merit. Choice of the selection index strongly affects the selection gain expected in individual traits. Abstract Selection indices using genomic information have been proposed in crop-specific scenarios. Routine use of genomic selection (GS) for simultaneous improvement of multiple traits requires information about the impact of the available economic and logistic resources and genetic properties (variances, trait correlations, and prediction accuracies) of the breeding population on the expected selection gain. We extended the R package “selectiongain” from single trait to index selection to optimize and compare breeding strategies for simultaneous improvement of two traits. We focused on the expected annual selection gain (ΔGa) for traits differing in their genetic correlation, economic weights, variance components, and prediction accuracies of GS. For all scenarios considered, breeding strategy GSrapid (one-stage GS followed by one-stage phenotypic selection) achieved higher ΔGa than classical two-stage phenotypic selection, regardless of the index chosen to combine the two traits and the prediction accuracy of GS. The Smith–Hazel or base index delivered higher ΔGa for net merit and individual traits compared to selection by independent culling levels, whereas the restricted index led to lower ΔGa in net merit and divergent results for selection gain of individual traits. The differences among the indices depended strongly on the correlation of traits, their variance components, and economic weights, underpinning the importance of choosing the selection indices according to the goal of the breeding program. We demonstrate our theoretical derivations and extensions of the R package “selectiongain” with an example from hybrid wheat by designing indices to simultaneously improve grain yield and grain protein content or sedimentation volume.

scholarly journals Evidence for use of both capital and income breeding strategies in the mangrove tree crab, Aratus pisonii

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jade Carver ◽  
Morgan Meidell ◽  
Zachary J. Cannizzo ◽  
Blaine D. Griffen
Keyword(s):  
Breeding Season ◽  
Breeding Strategy ◽  
Reproductive Period ◽  
Breeding Strategies ◽  
Mangrove Tree ◽  
Income Breeding ◽  
Aratus Pisonii ◽  
Breeding Seasons ◽  
And Storage ◽  
Capital And Income Breeding

AbstractTwo common strategies organisms use to finance reproduction are capital breeding (using energy stored prior to reproduction) and income breeding (using energy gathered during the reproductive period). Understanding which of these two strategies a species uses can help in predicting its population dynamics and how it will respond to environmental change. Brachyuran crabs have historically been considered capital breeders as a group, but recent evidence has challenged this assumption. Here, we focus on the mangrove tree crab, Aratus pisonii, and examine its breeding strategy on the Atlantic Florida coast. We collected crabs during and after their breeding season (March–October) and dissected them to discern how energy was stored and utilized for reproduction. We found patterns of reproduction and energy storage that are consistent with both the use of stored energy (capital) and energy acquired (income) during the breeding season. We also found that energy acquisition and storage patterns that supported reproduction were influenced by unequal tidal patterns associated with the syzygy tide inequality cycle. Contrary to previous assumptions for crabs, we suggest that species of crab that produce multiple clutches of eggs during long breeding seasons (many tropical and subtropical species) may commonly use income breeding strategies.

scholarly journals A New Breeding Strategy towards Introgression and Characterization of Stay-Green QTL for Drought Tolerance in Sorghum

Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 598
Author(s):  
Nasrein Mohamed Kamal ◽  
Yasir Serag Alnor Gorafi ◽  
Hanan Abdeltwab ◽  
Ishtiag Abdalla ◽  
Hisashi Tsujimoto ◽  
...  
Keyword(s):  
Phenotypic Expression ◽  
Phenotypic Selection ◽  
Breeding Strategy ◽  
Stay Green ◽  
Breeding Programs ◽  
The Public ◽  
Drought Tolerant ◽  
Selection Step ◽  
The Cost

Several marker-assisted selection (MAS) or backcrossing (MAB) approaches exist for polygenic trait improvement. However, the implementation of MAB remains a challenge in many breeding programs, especially in the public sector. In MAB introgression programs, which usually do not include phenotypic selection, undesired donor traits may unexpectedly turn up regardless of how expensive and theoretically powerful a backcross scheme may be. Therefore, combining genotyping and phenotyping during selection will improve understanding of QTL interactions with the environment, especially for minor alleles that maximize the phenotypic expression of the traits. Here, we describe the introgression of stay-green QTL (Stg1–Stg4) from B35 into two sorghum backgrounds through an MAB that combines genotypic and phenotypic (C-MAB) selection during early backcross cycles. The background selection step is excluded. Since it is necessary to decrease further the cost associated with molecular marker assays, the costs of C-MAB were estimated. Lines with stay-green trait and good performance were identified at an early backcross generation, backcross two (BC2). Developed BC2F4 lines were evaluated under irrigated and drought as well as three rainfed environments varied in drought timing and severity. Under drought conditions, the mean grain yield of the most C-MAB-introgression lines was consistently higher than that of the recurrent parents. This study is one of the real applications of the successful use of C-MAB for the development of drought-tolerant sorghum lines for drought-prone areas.

scholarly journals Strategies to Assure Optimal Trade-Offs Among Competing Objectives for the Genetic Improvement of Soybean

2021 ◽  
Vol 12 ◽  
Author(s):  
Vishnu Ramasubramanian ◽  
William D. Beavis
Keyword(s):  
Genomic Selection ◽  
Genetic Improvement ◽  
Genetic Variance ◽  
Phenotypic Selection ◽  
Breeding Strategies ◽  
Short Term ◽  
Mating Design ◽  
Breeding Populations ◽  
Hub Network

Plant breeding is a decision-making discipline based on understanding project objectives. Genetic improvement projects can have two competing objectives: maximize the rate of genetic improvement and minimize the loss of useful genetic variance. For commercial plant breeders, competition in the marketplace forces greater emphasis on maximizing immediate genetic improvements. In contrast, public plant breeders have an opportunity, perhaps an obligation, to place greater emphasis on minimizing the loss of useful genetic variance while realizing genetic improvements. Considerable research indicates that short-term genetic gains from genomic selection are much greater than phenotypic selection, while phenotypic selection provides better long-term genetic gains because it retains useful genetic diversity during the early cycles of selection. With limited resources, must a soybean breeder choose between the two extreme responses provided by genomic selection or phenotypic selection? Or is it possible to develop novel breeding strategies that will provide a desirable compromise between the competing objectives? To address these questions, we decomposed breeding strategies into decisions about selection methods, mating designs, and whether the breeding population should be organized as family islands. For breeding populations organized into islands, decisions about possible migration rules among family islands were included. From among 60 possible strategies, genetic improvement is maximized for the first five to 10 cycles using genomic selection and a hub network mating design, where the hub parents with the largest selection metric make large parental contributions. It also requires that the breeding populations be organized as fully connected family islands, where every island is connected to every other island, and migration rules allow the exchange of two lines among islands every other cycle of selection. If the objectives are to maximize both short-term and long-term gains, then the best compromise strategy is similar except that the mating design could be hub network, chain rule, or a multi-objective optimization method-based mating design. Weighted genomic selection applied to centralized populations also resulted in the realization of the greatest proportion of the genetic potential of the founders but required more cycles than the best compromise strategy.

Statistical Sampling Properties of the Coefficients of Three Phenotypic Selection Indices

Crop Science ◽  
2016 ◽  
Vol 56 (1) ◽  
pp. 51-58 ◽  
Author(s):  
J. Jesus Cerón-Rojas ◽  
José Crossa ◽  
Jaime Sahagún-Castellanos
Keyword(s):  
Phenotypic Selection ◽  
Statistical Sampling ◽  
Selection Indices

scholarly journals Forests as promoters of terrestrial life-history strategies in East African amphibians

2013 ◽  
Vol 9 (3) ◽  
pp. 20121146 ◽  
Author(s):  
Hendrik Müller ◽  
H. Christoph Liedtke ◽  
Michele Menegon ◽  
Jan Beck ◽  
Liliana Ballesteros-Mejia ◽  
...  
Keyword(s):  
Montane Forest ◽  
Breeding Strategy ◽  
Life History Strategies ◽  
Strongly Correlated ◽  
Breeding Strategies ◽  
East African ◽  
Amphibian Species ◽  
Terrestrial Life ◽  
Potential Factor ◽  
Forest Habitats

Many amphibian lineages show terrestrialization of their reproductive strategy and breeding is partially or completely independent of water. A number of causal factors have been proposed for the evolution of terrestrialized breeding. While predation has received repeated attention as a potential factor, the influence of other factors such as habitat has never been tested using appropriate data or methods. Using a dataset that comprises 180 amphibian species from various East African habitats, we tested whether species occurring in different habitats show different patterns of terrestrialization in their breeding strategy. We recovered a significant association between terrestrialized breeding strategies and forest habitats. In general, forest seems to act as a facilitator, providing a permissive environment for the evolution of terrestrialized breeding strategies. However, while terrestrial oviposition is strongly correlated with lowland and montane forest habitat, complete terrestrial development is significantly correlated with montane forest only, indicating different selective pressures acting at different steps towards complete terrestrial development.

scholarly journals DeepGS: Predicting phenotypes from genotypes using Deep Learning

2017 ◽  
Author(s):  
Wenlong Ma ◽  
Zhixu Qiu ◽  
Jie Song ◽  
Qian Cheng ◽  
Chuang Ma
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Prediction Models ◽  
Linear Regression Analysis ◽  
Hidden Variables ◽  
R Package ◽  
Breeding Strategy ◽  
Simulation Experiments ◽  
Linear Relationships ◽  
Genome Wide

AbstractMotivationGenomic selection (GS) is a new breeding strategy by which the phenotypes of quantitative traits are usually predicted based on genome-wide markers of genotypes using conventional statistical models. However, the GS prediction models typically make strong assumptions and perform linear regression analysis, limiting their accuracies since they do not capture the complex, non-linear relationships within genotypes, and between genotypes and phenotypes.ResultsWe present a deep learning method, named DeepGS, to predict phenotypes from genotypes. Using a deep convolutional neural network, DeepGS uses hidden variables that jointly represent features in genotypic markers when making predictions; it also employs convolution, sampling and dropout strategies to reduce the complexity of high-dimensional marker data. We used a large GS dataset to train DeepGS and compare its performance with other methods. In terms of mean normalized discounted cumulative gain value, DeepGS achieves an increase of 27.70%~246.34% over a conventional neural network in selecting top-ranked 1% individuals with high phenotypic values for the eight tested traits. Additionally, compared with the widely used method RR-BLUP, DeepGS still yields a relative improvement ranging from 1.44% to 65.24%. Through extensive simulation experiments, we also demonstrated the effectiveness and robustness of DeepGS for the absent of outlier individuals and subsets of genotypic markers. Finally, we illustrated the complementarity of DeepGS and RR-BLUP with an ensemble learning approach for further improving prediction performance.AvailabilityDeepGS is provided as an open source R package available at https://github.com/cma2015/DeepGS.

scholarly journals Genotypic Variation in and Environmental Variance Components of Sugar Composition in Japanese Pear Fruit

HortScience ◽  
2019 ◽  
Vol 54 (9) ◽  
pp. 1465-1469
Author(s):  
Toshihiro Saito ◽  
Norio Takada ◽  
Hidenori Kato ◽  
Shingo Terakami ◽  
Sogo Nishio
Keyword(s):  
Variance Components ◽  
Fruit Juice ◽  
Sugar Content ◽  
Genotypic Variation ◽  
Phenotypic Selection ◽  
Japanese Pear ◽  
Sugar Composition ◽  
Pear Fruit ◽  
Environmental Variance ◽  
Total Sugar Content

Genotypic variations in and environmental variance components of the total sugar content (TSC) and sugar composition, including sucrose (SUC), fructose (FRU), glucose (GLU), and sorbitol (SOR), in the fruit juice of 13 Japanese pear cultivars were analyzed. The TSC of ‘Kanta’ and TSC of ‘Hoshiakari’ were high (both >14.5 g/100 mL). The contents of SUC and FRU were higher than those of the other sugars. The SUC contents were ranked as follows: ‘Gold Nijisseiki’, 7.3 g/100 mL; ‘Shuurei’, 6.2 g/100 mL; and ‘Akizuki’, 6.1 g/100 mL. The FRU content in ‘Kanta’ was the highest among all monomeric sugars evaluated (6.8 g/100 mL). These results suggest that ‘Kanta’ is superior in terms of both TSC and sugar composition, which determine sweetness. The yearly environmental variance components were negligible for all traits. The genotype × year ranged from 4.4% to 13.7% of the total variance. Within-tree variance was 17.1% for TSC, whereas that for the sugar composition ranged from 1.4% to 6.1%. The tree × year ranged from 2.7% to 7.4%. Variance among fruits within trees was the largest environmental variance component—except for FRU—and ranged from 8.8% to 35.6%. Broad-sense heritability (hB2) values based on single tree, single year, and single fruit measurements were 0.33, 0.64, 0.69, 0.71, and 0.76 for TSC, SUC, FRU, GLU, and SOR, respectively. These results suggest that it would be easier to estimate genetic differences in sugar components with a higher level of precision than those in TSC. Increasing the fruit number up to five, in combination with yearly repetition increased to two (without tree repetition), significantly increased the hB2 of all traits undergoing study. The information obtained during this study will be useful for improving the accuracy of phenotypic selection and future genomic-based breeding studies performed to improve the sweetness of Japanese pear fruits.

scholarly journals THE IMPACT OF MOLECULAR GENETICS IN PLANT BREEDING: REALITIES AND PERSPECTIVES

2019 ◽  
Vol 30 (1) ◽  
pp. 11-15
Author(s):  
A. Zambelli
Keyword(s):  
Plant Breeding ◽  
Molecular Genetics ◽  
Molecular Breeding ◽  
Recurrent Selection ◽  
Phenotypic Selection ◽  
Selection Marker ◽  
Breeding Strategies ◽  
Practical Applications ◽  
Dna Technology ◽  
The Impact

Even when conventional breeding was effective in achieving a continuous improvement in yield, Molecular Genetics tools applied in plant breeding contributed to maximize genetic gain. Thus, the use of DNA technology applied in agronomic improvement gave rise to Molecular Breeding, discipline which groups the different breeding strategies where genotypic selection, based on DNA markers, are used in combination with or in replacement of phenotypic selection. These strategies can be listed as: marker-assisted selection; marker-assisted backcrossing; marker assisted recurrent selection; and genomic selection. Strong arguments have been made about the potential advantages that Molecular Breeding brings, although little has been devoted to discussing its feasibility in practical applications. The consequence of the lack of a deep analysis when implementing a strategy of Molecular Breeding is its failure, leading to many undesirable outcomes and discouraging breeders from using the technology. The aim of this work is to trigger a debate about the convenience of the use of Molecular Breeding strategies in a breeding program considering the DNA technology of choice, the complexity of the trait of agronomic interest to be improved, the expected accuracy in the selection, and the demanded resources. Key words: DNA marker, selection, plant improvement.

scholarly journals The Relative Efficiency of Two Multistage Linear Phenotypic Selection Indices to Predict the Net Genetic Merit

Crop Science ◽  
2019 ◽  
Vol 59 (3) ◽  
pp. 1037-1051 ◽  
Author(s):  
J. Jesus Cerón-Rojas ◽  
Fernando H. Toledo ◽  
Jose Crossa
Keyword(s):  
Relative Efficiency ◽  
Phenotypic Selection ◽  
Genetic Merit ◽  
Selection Indices
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