scholarly journals Modelling selection response in plant breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions

2020 ◽  
Author(s):  
M Cooper ◽  
O Powell ◽  
KP Voss-Fels ◽  
CD Messina ◽  
C Gho ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Plant Breeding ◽  
Complex Traits ◽  
Reference Population ◽  
Breeding Strategy ◽  
Breeding Value ◽  
Breeding Programs ◽  
Genetic Changes ◽  
Crop Models ◽  
Link Functions

AbstractPlant breeding programs are designed and operated over multiple cycles to systematically change the genetic makeup of plants to achieve improved trait performance for a Target Population of Environments (TPE). Within each cycle, selection applied to the standing genetic variation within a structured reference population of genotypes (RPG) is the primary mechanism by which breeding programs make the desired genetic changes. Selection operates to change the frequencies of the alleles of the genes controlling trait variation within the RPG. The structure of the RPG and the TPE has important implications for the design of optimal breeding strategies. The breeder’s equation, together with the quantitative genetic theory behind the equation, informs many of the principles for design of breeding programs. The breeder’s equation can take many forms depending on the details of the breeding strategy. Through the genetic changes achieved by selection, the cultivated varieties of crops (cultivars) are improved for use in agriculture. From a breeding perspective, selection for specific trait combinations requires a quantitative link between the effects of the alleles of the genes impacted by selection and the trait phenotypes of plants and their breeding value. This gene-to-phenotype link function provides the G2P map for one to many traits. For complex traits controlled by many genes, the infinitesimal model for trait genetic variation is the dominant G2P model of quantitative genetics. Here we consider motivations and potential benefits of using the hierarchical structure of crop models as CGM-G2P trait link functions in combination with the infinitesimal model for the design and optimisation of selection in breeding programs.

scholarly journals Modelling selection response in plant breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions

2020 ◽  
Author(s):  
M Cooper ◽  
O Powell ◽  
K P Voss-Fels ◽  
C D Messina ◽  
C Gho ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Plant Breeding ◽  
Complex Traits ◽  
Reference Population ◽  
Breeding Strategy ◽  
Breeding Value ◽  
Breeding Programs ◽  
Genetic Changes ◽  
Crop Models ◽  
Link Functions

Abstract Plant breeding programs are designed and operated over multiple cycles to systematically change the genetic makeup of plants to achieve improved trait performance for a Target Population of Environments (TPE). Within each cycle, selection applied to the standing genetic variation within a structured reference population of genotypes (RPG) is the primary mechanism by which breeding programs make the desired genetic changes. Selection operates to change the frequencies of the alleles of the genes controlling trait variation within the RPG. The structure of the RPG and the TPE has important implications for the design of optimal breeding strategies. The breeder’s equation, together with the quantitative genetic theory behind the equation, informs many of the principles for design of breeding programs. The breeder’s equation can take many forms depending on the details of the breeding strategy. Through the genetic changes achieved by selection, the cultivated varieties of crops (cultivars) are improved for use in agriculture. From a breeding perspective, selection for specific trait combinations requires a quantitative link between the effects of the alleles of the genes impacted by selection and the trait phenotypes of plants and their breeding value. This gene-to-phenotype link function provides the G2P map for one to many traits. For complex traits controlled by many genes, the infinitesimal model for trait genetic variation is the dominant G2P model of quantitative genetics. Here we consider motivations and potential benefits of using the hierarchical structure of crop models as CGM-G2P trait link functions in combination with the infinitesimal model for the design and optimisation of selection in breeding programs.

scholarly journals A multi-part strategy for introgression of exotic germplasm into elite plant breeding programs using genomic selection

2022 ◽  
Author(s):  
Irene S. Breider ◽  
R. Chris Gaynor ◽  
Gregor Gorjanc ◽  
Steve Thorn ◽  
Manish K. Pandey ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Plant Breeding ◽  
Genomic Selection ◽  
Genetic Gain ◽  
Genetic Improvement ◽  
Breeding Strategy ◽  
Breeding Program ◽  
Breeding Programs ◽  
Polygenic Inheritance ◽  
Polygenic Traits

Abstract Some of the most economically important traits in plant breeding show highly polygenic inheritance. Genetic variation is a key determinant of the rates of genetic improvement in selective breeding programs. Rapid progress in genetic improvement comes at the cost of a rapid loss of genetic variation. Germplasm available through expired Plant Variety Protection (exPVP) lines is a potential resource of variation previously lost in elite breeding programs. Introgression for polygenic traits is challenging, as many genes have a small effect on the trait of interest. Here we propose a way to overcome these challenges with a multi-part pre-breeding program that has feedback pathways to optimise recurrent genomic selection. The multi-part breeding program consists of three components, namely a bridging component, population improvement, and product development. Parameters influencing the multi-part program were optimised with the use of a grid search. Haploblock effect and origin were investigated. Results showed that the introgression of exPVP germplasm using an optimised multi-part breeding strategy resulted in 1.53 times higher genetic gain compared to a two-part breeding program. Higher gain was achieved through reducing the performance gap between exPVP and elite germplasm and breaking down linkage drag. Both first and subsequent introgression events showed to be successful. In conclusion, the multi-part breeding strategy has a potential to improve long-term genetic gain for polygenic traits and therefore, potential to contribute to global food security.

scholarly journals Accelerating Tomato Breeding by Exploiting Genomic Selection Approaches

Plants ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1236
Author(s):  
Elisa Cappetta ◽  
Giuseppe Andolfo ◽  
Antonio Di Matteo ◽  
Amalia Barone ◽  
Luigi Frusciante ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Complex Traits ◽  
Breeding Value ◽  
Critical Parameters ◽  
Breeding Programs ◽  
Selection Strategies ◽  
Genome Wide ◽  
Line Selection ◽  
Tomato Breeding ◽  
Accuracy Of Prediction

Genomic selection (GS) is a predictive approach that was built up to increase the rate of genetic gain per unit of time and reduce the generation interval by utilizing genome-wide markers in breeding programs. It has emerged as a valuable method for improving complex traits that are controlled by many genes with small effects. GS enables the prediction of the breeding value of candidate genotypes for selection. In this work, we address important issues related to GS and its implementation in the plant context with special emphasis on tomato breeding. Genomic constraints and critical parameters affecting the accuracy of prediction such as the number of markers, statistical model, phenotyping and complexity of trait, training population size and composition should be carefully evaluated. The comparison of GS approaches for facilitating the selection of tomato superior genotypes during breeding programs is also discussed. GS applied to tomato breeding has already been shown to be feasible. We illustrated how GS can improve the rate of gain in elite line selection, and descendent and backcross schemes. The GS schemes have begun to be delineated and computer science can provide support for future selection strategies. A new promising breeding framework is beginning to emerge for optimizing tomato improvement procedures.

scholarly journals Temporal Variation in the Genetic Composition of an Endangered Marsupial Reflects Reintroduction History

Diversity ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 257
Author(s):  
Rujiporn Thavornkanlapachai ◽  
Harriet R. Mills ◽  
Kym Ottewell ◽  
J. Anthony Friend ◽  
W. Jason Kennington
Keyword(s):  
Genetic Variation ◽  
Genetic Relatedness ◽  
Allelic Diversity ◽  
Genetic Composition ◽  
Effective Population ◽  
Breeding Programs ◽  
Genetic Changes ◽  
Reintroduced Population ◽  
Source Populations ◽  
Conservation Breeding

The loss of genetic variation and genetic divergence from source populations are common problems for reintroductions that use captive animals or a small number of founders to establish a new population. This study evaluated the genetic changes occurring in a captive and a reintroduced population of the dibbler (Parantechinus apicalis) that were established from multiple source populations over a twelve-year period, using 21 microsatellite loci. While the levels of genetic variation within the captive and reintroduced populations were relatively stable, and did not differ significantly from the source populations, their effective population size reduced 10–16-fold over the duration of this study. Evidence of some loss of genetic variation in the reintroduced population coincided with genetic bottlenecks that occurred after the population had become established. Detectable changes in the genetic composition of both captive and reintroduced populations were associated with the origins of the individuals introduced to the population. We show that interbreeding between individuals from different source populations lowered the genetic relatedness among the offspring, but this was short-lived. Our study highlights the importance of sourcing founders from multiple locations in conservation breeding programs to avoid inbreeding and maximize allelic diversity. The manipulation of genetic composition in a captive or reintroduced population is possible with careful management of the origins and timings of founder releases.

scholarly journals Accelerating Tomato Breeding by Exploiting Genomic Selection Approaches

2020 ◽  
Author(s):  
Elisa Cappetta ◽  
Giuseppe Andolfo ◽  
Antonio Di Matteo ◽  
Amalia Barone ◽  
Luigi Frusciante ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Complex Traits ◽  
Breeding Value ◽  
Critical Parameters ◽  
Breeding Programs ◽  
Selection Strategies ◽  
Superior Genotypes ◽  
Tomato Breeding ◽  
Accuracy Of Prediction ◽  
Selection Of

Genomic selection (GS) is a predictive approach that was build up to increase the rate of genetic gain per unit of time in breeding programs. It has emerged as a valuable method for improving complex traits that are controlled by many genes with small effect. GS enables the prediction of breeding value of candidate genotypes for selection. In this work we address important issues related to GS and its implementation in tomato breeding context. Genomic constrains and critical parameters affecting the accuracy of prediction in such crop such as phenotyping, genotyping training population composition and size and statistical method should be carefully evaluated. Comparison of GS approaches for facilitating the selection of tomato superior genotypes during breeding program are also discussed. GS applied to tomato breeding has already shown to be feasible. We illustrated how GS can improve the rate of gain in elite lines selection, descendent and in backcross schemes. The GS schemes begin to be delineated and computer science can provide support for future selection strategies. A new breeding framework is beginning to emerge for optimizing tomato improvement procedures.

scholarly journals Making waves in Breedbase: An integrated spectral data storage and analysis pipeline for plant breeding programs

tppj ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jenna Hershberger ◽  
Nicolas Morales ◽  
Christiano C. Simoes ◽  
Bryan Ellerbrock ◽  
Guillaume Bauchet ◽  
...  
Keyword(s):  
Plant Breeding ◽  
Spectral Data ◽  
Data Storage ◽  
Analysis Pipeline ◽  
Breeding Programs

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.

Assessment of the genetic variability using pedigree analysis of the Sahiwal breed in Kenya

2016 ◽  
Vol 59 ◽  
pp. 7-14 ◽  
Author(s):  
S. Mwangi ◽  
T.K. Muasya ◽  
E.D. Ilatsia ◽  
A.K. Kahi
Keyword(s):  
Genetic Variability ◽  
Genetic Drift ◽  
Reference Population ◽  
Pedigree Analysis ◽  
Breeding Strategy ◽  
Progeny Testing ◽  
Founding Population ◽  
Effective Selection ◽  
Inbreeding Level ◽  
Year 2000

Summary Pedigree analysis using genealogical information of 18 315 animals born between 1949 and 2008 was done to quantify genetic variability of the Sahiwal population in Kenya. Generation intervals for sire pathways were longer than dam pathways and increased over year periods, from about 4–16 years. The later was due to use of old bulls for breeding in the last 2 year groups and cessation of progeny testing in the year 2000. Average inbreeding level in last year period studied was 1.2 percent. Genetic variability of the population as assessed based on gene origin statistics decreased over the years. The ratio of effective number of founders to founders of 0.06 showed unequal contribution of founders to the reference population. However, since the founding population, ancestors contributed equally as shown by the ratio of f e/f a of 0.94, which could also be due to lack of effective selection in this population. The ratio of f g/f a of 0.63 indicated genetic loss of genetic variability occurred through genetic drift in the Kenyan Sahiwal population. The small number of ancestors (16) that accounted for 50 percent of the total variation in the reference population suggested overuse of a small number of some animals as parents over generations. The smaller ratio of f g/f e compared with f a/f e also confirms loss of genetic variability in the population by genetic drift than bottlenecks. Therefore the breeding strategy for the Sahiwal population in Kenya should incorporate tools that balance rate of genetic gain and the future rate of inbreeding.

Integrating Biotechnology into Woody Plant Breeding Programs

1988 ◽  
pp. 433-449 ◽  
Author(s):  
D. E. Riemenschneider ◽  
B. E. Haissig ◽  
E. T. Bingham
Keyword(s):  
Plant Breeding ◽  
Woody Plant ◽  
Breeding Programs
Sign in / Sign up

Export Citation Format

Share Document