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

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.

scholarly journals Characterization and Genetic Diversity of Listeria monocytogenes Isolated from Cattle Abortions in Latvia, 2013–2018

2021 ◽  
Vol 8 (9) ◽  
pp. 195
Author(s):  
Žanete Šteingolde ◽  
Irēna Meistere ◽  
Jeļena Avsejenko ◽  
Juris Ķibilds ◽  
Ieva Bergšpica ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Listeria Monocytogenes ◽  
Virulence Factors ◽  
Causative Agent ◽  
Animal Species ◽  
Clonal Complex ◽  
The Third ◽  
Wide Range ◽  
Sequence Types

Listeria monocytogenes can cause disease in humans and in a wide range of animal species, especially in farm ruminants. The aim of the study was to determine the prevalence and genetic diversity of L. monocytogenes related to 1185 cattle abortion cases in Latvia during 2013–2018. The prevalence of L. monocytogenes among cattle abortions was 16.1% (191/1185). The seasonality of L. monocytogenes abortions was observed with significantly higher occurrence (p < 0.01) in spring (March–May). In 61.0% of the cases, the affected cattle were under four years of age. L. monocytogenes abortions were observed during the third (64.6%) and second (33.3%) trimesters of gestation. Overall, 27 different sequence types (ST) were detected, and four of them, ST29 (clonal complex, CC29), ST37 (CC37), ST451 (CC11) and ST7 (CC7), covered more than half of the L. monocytogenes isolates. Key virulence factors like the prfA-dependent virulence cluster and inlA, inlB were observed in all the analyzed isolates, but lntA, inlF, inlJ, vip were associated with individual sequence types. Our results confirmed that L. monocytogenes is the most important causative agent of cattle abortions in Latvia and more than 20 different STs were observed in L. monocytogenes abortions in cattle.

scholarly journals Strategies of Preserving Genetic Diversity While Maximizing Genetic Response From Implementing Genomic Selection in Pulse Breeding Programs

2021 ◽  
Author(s):  
Yongjun Li ◽  
Sukhjiwan Kaur ◽  
Luke W. Pembleton ◽  
Hossein Valipour-Kahrood ◽  
Garry M. Rosewarne ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Grain Yield ◽  
Genomic Selection ◽  
Genetic Gain ◽  
Complex Traits ◽  
Phenotypic Selection ◽  
Breeding Cycle ◽  
Environment Interaction ◽  
Breeding Programs ◽  
Diversity Loss

Abstract Using a stochastic computer simulation, we investigated the benefit of optimization strategies in the context of genomic selection (GS) for pulse breeding programs. We simulated GS for moderately complex to highly complex traits such as disease resistance, grain weight and grain yield in multiple environments with a high level of genotype-by-environment interaction for grain yield. GS led to higher genetic gain per unit of time and higher genetic diversity loss than phenotypic selection by shortening the breeding cycle time. The genetic gain obtained from selecting the segregating parents early in the breeding cycle (at F1 or F2 stages) was substantially higher than selecting at later stages even though prediction accuracy was moderate. Increasing the number of F1 intercross (F1i) families and keeping the total number of progeny of F1i families constant, we observed a decrease in genetic gain and increase in genetic diversity. Whereas increasing the number of progeny per F1i family while keeping a constant number of F1i families increased rate of genetic gain and had higher genetic diversity loss per unit of time. Adding 50 F2 family phenotypes to the training population increased the accuracy of GEBVs and genetic gain per year and decreased the rate of genetic diversity loss. Genetic diversity could be preserved by applying a strategy that restricted both the percentage of alleles fixed and the average relationship of the group of selected parents to preserve long-term genetic improvement in the pulse breeding program.

scholarly journals Population structure and phylogenetic relationships in Brassica rapa L. subspecies by using isozyme markers

2020 ◽  
Author(s):  
R. H. Sammour ◽  
M. A. Karam ◽  
Y. S. Morsi ◽  
R. M. Ali
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Brassica Rapa ◽  
Phylogenetic Relationships ◽  
Fixation Index ◽  
Distribution Area ◽  
Enzyme Analysis ◽  
Breeding Programs ◽  
Expected Heterozygosity ◽  
Wide Range

Abstract The present study aimed to assess population structure and phylogenetic relationships of nine subspecies of Brassica rapa L. represented with thirty-five accessions cover a wide range of species distribution area using isozyme analysis in order to select more diverse accessions as supplementary resources that can be utilized for improvement of B. napus. Enzyme analysis resulted in detecting 14 putative polymorphic loci with 27 alleles. Mean allele frequency 0.04 (rare alleles) was observed in Cat4A and Cat4B in sub species Oleifera accession CR 2204/79 and in subspecies trilocularis accessions CR 2215/88 and CR 2244/88. The highest genetic diversity measures were observed in subspecies dichotoma, accession CR 1585/96 (the highest average of observed (H0) and expected heterozygosity (He), and number of alleles per locus (Ae)). These observations make this accession valuable genetic resource to be included in breeding programs for the improvement of oilseed B. napus. The average fixation index (F) is significantly higher than zero for the analysis accessions indicating a significant deficiency of heteozygosity. The divergence among subspecies indicated very great genetic differentiation (FST = 0.8972) which means that about 90% of genetic diversity is distributed among subspecies, while 10% of the diversity is distributed within subspecies. This coincides with low value of gene flow (Nm = 0.0287). B. rapa ssp. oleifera (turnip rape) and B. rapa ssp. trilocularis (sarson) were grouped under one cluster which coincides with the morphological classification.

scholarly journals Maximizing efficiency of genomic selection in CIMMYT’s tropical maize breeding program

2020 ◽  
Author(s):  
Sikiru Adeniyi Atanda ◽  
Michael Olsen ◽  
Juan Burgueño ◽  
Jose Crossa ◽  
Daniel Dzidzienyo ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Prediction Accuracy ◽  
Large Scale ◽  
Primary Objective ◽  
Breeding Program ◽  
Breeding Cycle ◽  
Training Set ◽  
Maize Breeding ◽  
Phenotypic Data ◽  
Breeding Programs

Abstract Key message Historical data from breeding programs can be efficiently used to improve genomic selection accuracy, especially when the training set is optimized to subset individuals most informative of the target testing set. Abstract The current strategy for large-scale implementation of genomic selection (GS) at the International Maize and Wheat Improvement Center (CIMMYT) global maize breeding program has been to train models using information from full-sibs in a “test-half-predict-half approach.” Although effective, this approach has limitations, as it requires large full-sib populations and limits the ability to shorten variety testing and breeding cycle times. The primary objective of this study was to identify optimal experimental and training set designs to maximize prediction accuracy of GS in CIMMYT’s maize breeding programs. Training set (TS) design strategies were evaluated to determine the most efficient use of phenotypic data collected on relatives for genomic prediction (GP) using datasets containing 849 (DS1) and 1389 (DS2) DH-lines evaluated as testcrosses in 2017 and 2018, respectively. Our results show there is merit in the use of multiple bi-parental populations as TS when selected using algorithms to maximize relatedness between the training and prediction sets. In a breeding program where relevant past breeding information is not readily available, the phenotyping expenditure can be spread across connected bi-parental populations by phenotyping only a small number of lines from each population. This significantly improves prediction accuracy compared to within-population prediction, especially when the TS for within full-sib prediction is small. Finally, we demonstrate that prediction accuracy in either sparse testing or “test-half-predict-half” can further be improved by optimizing which lines are planted for phenotyping and which lines are to be only genotyped for advancement based on GP.

GENIC DIVERSITY OF NATURAL POPULATIONS OF A CLONE- FORMING TREE POPULUS TREMULOIDES

1982 ◽  
Vol 24 (5) ◽  
pp. 611-616 ◽  
Author(s):  
William M. Cheliak ◽  
Bruce P. Dancik
Keyword(s):  
Plant Species ◽  
Populus Tremuloides ◽  
Animal Species ◽  
Woody Plant ◽  
Neutral Theory ◽  
Natural Populations ◽  
Trembling Aspen ◽  
Insufficient Time ◽  
Selection For ◽  
Genic Diversity

Effects of asexual reproduction as a primary reproductive strategy on population structure and levels of variability were investigated electrophoretically in natural populations of a woody plant species, trembling aspen (Populus tremuloides Michx.), from Alberta. As expected, levels of genic diversity, 42%, and proportion of polymorphic loci, 92%, averaged over all clones are considerably greater than those reported for comparable samples of sexually reproducing plant and animal species. These measures of genic variability of a primarily asexual plant species are similar to those reported for asexual species of insects, fish and bacteria. In addition, each of the 222 clones was electrophoretically unique. Since neutral theory would predict each individual clone to be heterozygous for a unique mutation at each gene locus at equilibrium, these results can be interpreted in a number of ways: (i) insufficient time to reach equilibrium, (ii) inability of electrophoresis to detect all variation at a locus, (iii) periodic establishment of sexually derived propagules in the population, and (iv) selection for similar genotypes at each location or against mutations at particular gene loci. Re-invasion of Pleistocene-glaciated areas by trembling aspen likely was by sexual means, with subsequent reproduction being primarily asexual.

scholarly journals Improving short and long term genetic gain by accounting for within family variance in optimal cross selection

2019 ◽  
Author(s):  
Antoine Allier ◽  
Christina Lehermeier ◽  
Alain Charcosset ◽  
Laurence Moreau ◽  
Simon Teyssèdre
Keyword(s):  
Genetic Diversity ◽  
Genomic Selection ◽  
Genetic Gain ◽  
Family Selection ◽  
Breeding Programs ◽  
Short And Long Term ◽  
Inbreeding Rate ◽  
Genetic Value ◽  
Optimal Set

AbstractThe implementation of genomic selection in recurrent breeding programs raised several concerns, especially that a higher inbreeding rate could compromise the long term genetic gain. An optimized mating strategy that maximizes the performance in progeny and maintains diversity for long term genetic gain on current and yet unknown future targets is essential. The optimal cross selection approach aims at identifying the optimal set of crosses maximizing the expected genetic value in the progeny under a constraint on diversity in the progeny. Usually, optimal cross selection does not account for within family selection, i.e. the fact that only a selected fraction of each family serves as candidate parents of the next generation. In this study, we consider within family variance accounting for linkage disequilibrium between quantitative trait loci to predict the expected mean performance and the expected genetic diversity in the selected progeny of a set of crosses. These predictions rely on the method called usefulness criterion parental contribution (UCPC). We compared UCPC based optimal cross selection and optimal cross selection in a long term simulated recurrent genomic selection breeding program considering overlapping generations. UCPC based optimal cross selection proved to be more efficient to convert the genetic diversity into short and long term genetic gains than optimal cross selection. We also showed that using the UCPC based optimal cross selection, the long term genetic gain can be increased with only limited reduction of the short term commercial genetic gain.

scholarly journals 189 Choices ahead for dairy cattle breeding programs

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 22-23
Author(s):  
Michael M Lohuis
Keyword(s):  
Dairy Cattle ◽  
Genomic Selection ◽  
Gene Editing ◽  
New Technologies ◽  
Value Added ◽  
Progeny Testing ◽  
Cattle Breeding ◽  
Breeding Programs ◽  
Dairy Cattle Breeding ◽  
Selection For

Abstract Dairy cattle breeding programs have been transformed from conventional progeny-testing schemes to genomic selection paired with nucleus herd breeding in the span of one decade. This was spurred by the simultaneous advances in low-cost SNP genotyping, genomic selection methodology and reproductive biotechnologies. The rates of genetic progress have approximately doubled in this time but so have increases in inbreeding levels. This was driven by intense competition between AI studs and farmer adherence to common selection indices which has concentrated selection on very elite segments of juvenile age groups. This has led to speculation on the need for alternative indices and selection for novel traits in order to differentiate breeding programs and customize selection for unique farm conditions. This will be made more possible by the advent of on-farm sensor technology and artificial intelligence algorithms. Large commercial dairies are increasingly experimenting with crossbreeding with varying levels of success and this will require a new approach by breeding programs to focus both on purebred and crossbred performance. In addition, the potential exists for use of gene-editing to further enable value-added traits to be added into breeding programs. In parallel with breeding program advancements, consumer trends are also changing to include more interest in specialty dairy products with implied differences in digestibility, health or environmental impacts. Identifying technologies and traits that will add value either on the farm as well as at the consumer level will be a challenge for today’s breeders and producers. Some new technologies, such as gene editing, can pose consumer acceptance challenges if they are perceived to be used carelessly or for the wrong reasons. Careful choices will need to be made to continue to improve profitability, functionality and health of dairy cattle while also meeting higher consumer standards for animal welfare, health and the environment.

scholarly journals AlphaSimR: an R package for breeding program simulations

2020 ◽  
Vol 11 (2) ◽  
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

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.

scholarly journals Genetic diversity structure of western-type carrots

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Katarzyna Stelmach ◽  
Alicja Macko-Podgórni ◽  
Charlotte Allender ◽  
Dariusz Grzebelus
Keyword(s):  
Genetic Diversity ◽  
Gene Pool ◽  
Phenotypic Variability ◽  
Phenotypic Selection ◽  
Snp Markers ◽  
Wide Range ◽  
Passport Data ◽  
The Mean ◽  
Selection For ◽  
Diversity Structure

Abstract Background Carrot is a crop with a wide range of phenotypic and molecular diversity. Within cultivated carrots, the western gene pool comprises types characterized by different storage root morphology. First western carrot cultivars originated from broad-based populations. It was followed by intercrosses among plants representing early open-pollinated cultivars, combined with mass phenotypic selection for traits of interest. Selective breeding improved root uniformity and led to the development of a range of cultivars differing in root shape and size. Based on the root shape and the market use of cultivars, a dozen of market types have been distinguished. Despite their apparent phenotypic variability, several studies have suggested that western cultivated carrot germplasm was genetically non-structured. Results Ninety-three DcS-ILP markers and 2354 SNP markers were used to evaluate the structure of genetic diversity in the collection of 78 western type open-pollinated carrot cultivars, each represented by five plants. The mean percentage of polymorphic loci segregating within a cultivar varied from 31.18 to 89.25% for DcS-ILP markers and from 45.11 to 91.29% for SNP markers, revealing high levels of intra-cultivar heterogeneity, in contrast to its apparent phenotypic stability. Average inbreeding coefficient for all cultivars was negative for both DcS-ILP and SNP, whereas the overall genetic differentiation across all market classes, as measured by FST, was comparable for both marker systems. For DcS-ILPs 90–92% of total genetic variation could be attributed to the differences within the inferred clusters, whereas for SNPs the values ranged between 91 to 93%. Discriminant Analysis of Principal Components enabled the separation of eight groups cultivars depending mostly on their market type affiliation. Three groups of cultivars, i.e. Amsterdam, Chantenay and Imperator, were characterized by high homogeneity regardless of the marker system used for genotyping. Conclusions Both marker systems used in the study enabled detection of substantial variation among carrot plants of different market types, therefore can be used in germplasm characterization and analysis of genome relationships. The presented results likely reveal the actual genetic diversity structure within the western carrot gene pool and point at possible discrepancies within the cultivars’ passport data.

Sign in / Sign up

Export Citation Format

Share Document