There are different ways of designing a breeding program, which can be grouped into four categories of complexity. It is important to note that a breeding scheme of a lower complexity level is not inferior to one of higher complexity, and genetic gain for single traits can often be higher in simpler programs.
A breeding program will often increase in complexity over time, as the broodstock improve and more traits are included in the breeding goals.
The simplest types of breeding program is pure broodstock management. The focus is on maintaining genetic diversity and minimizing inbreeding, while performing mass-selection for a few core traits, such as growth.
Integrated breeding programs are slightly more complex than broodstock management. The breeding candidates are grown in parallel to, or along with, animals for commercial production. These programs utilize mass spawning, and usually mass selection for a few core traits. These programs require little in terms of dedicated infrastructure, and can provide immense selection response in key traits such as growth. The design is however limited in the number and type of traits that can be included.
If the breeding goals includes selection for multiple traits, such as disturbance traits (i.e. slaughter yield and disease resistance) in addition to growth, a multi-trait breeding program is required. The usual approach in multi-trait breeding schemes is to utilize family production, implementing selection at a family level for disturbance traits measured on the siblings of breeding candidates, and selection at an individual level for performance traits of the candidate themselves. These breeding programs are more demanding on infrastructure and workload, as a separate broodstock nucleus must be kept in addition to the commercial broodstock. However, such a breeding scheme can produce a high level of genetic improvement in multiple key traits simultaneously.
The highest level of complexity in breeding programs will aim at improving a large number of traits with very high accuracy. Commonly implementing a nucleus scheme with family production, these breeding programs also leverage the use of genomic information for MAS (marker assisted selection) or GS (genomic selection) in order to increase the selection intensity for key traits. These breeding programs require complex infrastructure and highly trained personnel but can produce genetic improvement in a large number of traits simultaneously.
A well-structured breeding program will improve the genetic quality of your broodstock population stepwise for each new generation. The genetic gain per generation is influenced by several factors, as explained by an extended breeder’s equation.
An effective selection requires a broad genetic variation within the breeding population. The effect on selection depends on the amount of additive genetic variance and not on the total genetic variance in general. Thus, it is important to ensure that the breeding population maintains a high level of additive genetic variation for all key traits.
The selection intensity represents the difference between the mean of the selected individuals and the mean of the population, measured in units of the population’s phenotypic standard deviation. The selection intensity will depend on the number of individuals (breeding candidates) available for selection. As the selection intensity increases, so does the genetic gain.
The accuracy of selection indicates how well the selection criteria represent the selected breeding candidates’ true breeding values. Selection based on the breeding candidates’ performance is very efficient for traits with medium to high heritability estimates (i.e. growth). The accuracy of selecting traits with a low heritability is increased by using additional full- and half-sib information.
Selection based on genomic data (i.e. genomic selection) may considerably increase selection accuracy, especially for traits with low heritability. However, genotyping’s high costs will often restrict the number of genotyped breeding candidates available for selection. Thus, care should be taken to avoid a reduction in the selection intensity cancels the increased accuracy of genomic selection.
The generation interval is the average age of the breeding candidates at the birth of their offspring, which will produce the next generation of breeding candidates. The generation interval facilitates the calculation of selection responses per year instead of per generation. Efficient breeding programs should minimize the generation interval.
Most populations have several deleterious recessive alleles hidden in heterozygotes at low frequencies (referred to as a population’s genetic load). Inbreeding, i.e. the mating between individuals related by ancestry, will unmask these deleterious recessive alleles and cause inbreeding depression observed as reduced biological fitness. Thus, efforts should be made to restrict the accumulation of inbreeding in breeding populations.
Through selection, we are improving the population mean for important production efficiency and disease traits.
A well-designed program can significantly improve the genetic gain for each generation, illustrated by the change of the population mean for growth in the Progift Nile tilapia program though 13 generations of selective breeding. Akvaforsk Genetics Center (AFGC), now Benchmark Genetics, has been involved as consultant in this program since the start. Interestingly, the largest animals in the base population were far smaller (about 250 gr) than the smallest animals in the F-12 generation.
By using our expertise, systems and technologies, we are tailoring our services to help our clients optimize the genetic gains of their programs. If you want to learn more about how we can assist you in taking maximizing the genetic potential of your breeding program, please contact us today.
