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Development of a structural growth curve model that considers the causal effect of initial phenotypes
- Source :
- Genetics Selection Evolution, Vol 51, Iss 1, Pp 1-9 (2019), Genetics Selection Evolution, Genetics Selection Evolution, BioMed Central, 2019, 51 (1), pp.19. ⟨10.1186/s12711-019-0461-y⟩, Genetics, Selection, Evolution : GSE, SC30202005080007, NARO成果DBd
- Publication Year :
- 2019
- Publisher :
- BMC, 2019.
-
Abstract
- Background Growth curves have been widely used in genetic analyses to gain insights into the growth characteristics of both animals and plants. However, several questions remain unanswered, including how the initial phenotypes affect growth and what is the duration of any such impact. For beef cattle production in Japan, calves are procured from farms that specialize in reproduction and then moved to other farms where they are fattened to achieve their market/purchase value. However, the causal effect of growth, while calves are on the reproductive farms, on their growth during fattening remains unclear. To investigate this, we developed a model that combines a structural equation with a growth curve model. The causal effect was modeled with B-splines, which allows inference of the effect as a curve. We fitted the proposed structural growth curve model to repeated measures of body weight from a Japanese beef cattle population (n = 3831) to estimate the curve of the causal effect of the calves’ initial weight on their trajectory of growth when they are on fattening farms. Results Maternal and reproduction farm effects explained 26% of the phenotypic variance of initial weight at fattening farms. The structural growth curve model was fitted to remove the effects of these factors in growth curve analysis at fattening farms. The estimated curve of causal effects remained at approximately 0.8 for 200 d after the calves entered the fattening farms, which means that 64% of the phenotypic variance was explained by the initial weight. Then, the effect decreased linearly and disappeared approximately 620 d after entering the fattening farms, which corresponded to an average age of 871.5 d. Conclusions The proposed model is expected to provide more accurate estimates of genetic values for growth patterns because the confounding causal factors such as maternal and reproduction farm effects are removed. Moreover, examination of the inferred curve of the causal effect enabled us to estimate the effect of a calf’s initial weight at arbitrary times during growth, which could provide suitable information for decision-making when shifting the time of slaughter, building models for genetic evaluation, and selecting calves for market. Electronic supplementary material The online version of this article (10.1186/s12711-019-0461-y) contains supplementary material, which is available to authorized users.
- Subjects :
- lcsh:QH426-470
media_common.quotation_subject
[SDV]Life Sciences [q-bio]
animal diseases
Population
Cattle Diseases
Biology
Beef cattle
Body weight
03 medical and health sciences
Japan
Statistics
Genetics
Animals
Computer Simulation
Animal Husbandry
Growth Charts
education
Ecology, Evolution, Behavior and Systematics
030304 developmental biology
media_common
lcsh:SF1-1100
2. Zero hunger
0303 health sciences
education.field_of_study
Reproduction
Causal effect
Confounding
Body Weight
0402 animal and dairy science
Repeated measures design
04 agricultural and veterinary sciences
General Medicine
Growth curve (biology)
040201 dairy & animal science
lcsh:Genetics
Phenotype
Animal Science and Zoology
Cattle
lcsh:Animal culture
Research Article
Subjects
Details
- Language :
- German
- ISSN :
- 12979686 and 0999193X
- Volume :
- 51
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Genetics Selection Evolution
- Accession number :
- edsair.doi.dedup.....c86a5908ea2140353de4e351e9087f00
- Full Text :
- https://doi.org/10.1186/s12711-019-0461-y