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Development of a structural growth curve model that considers the causal effect of initial phenotypes

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 catt...

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Autores principales: Onogi, Akio, Ogino, Atsushi, Sato, Ayako, Kurogi, Kazuhito, Yasumori, Takanori, Togashi, Kenji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6498631/
https://www.ncbi.nlm.nih.gov/pubmed/31046678
http://dx.doi.org/10.1186/s12711-019-0461-y
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author Onogi, Akio
Ogino, Atsushi
Sato, Ayako
Kurogi, Kazuhito
Yasumori, Takanori
Togashi, Kenji
author_facet Onogi, Akio
Ogino, Atsushi
Sato, Ayako
Kurogi, Kazuhito
Yasumori, Takanori
Togashi, Kenji
author_sort Onogi, Akio
collection PubMed
description 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.
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spelling pubmed-64986312019-05-09 Development of a structural growth curve model that considers the causal effect of initial phenotypes Onogi, Akio Ogino, Atsushi Sato, Ayako Kurogi, Kazuhito Yasumori, Takanori Togashi, Kenji Genet Sel Evol Research Article 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. BioMed Central 2019-05-02 /pmc/articles/PMC6498631/ /pubmed/31046678 http://dx.doi.org/10.1186/s12711-019-0461-y Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Onogi, Akio
Ogino, Atsushi
Sato, Ayako
Kurogi, Kazuhito
Yasumori, Takanori
Togashi, Kenji
Development of a structural growth curve model that considers the causal effect of initial phenotypes
title Development of a structural growth curve model that considers the causal effect of initial phenotypes
title_full Development of a structural growth curve model that considers the causal effect of initial phenotypes
title_fullStr Development of a structural growth curve model that considers the causal effect of initial phenotypes
title_full_unstemmed Development of a structural growth curve model that considers the causal effect of initial phenotypes
title_short Development of a structural growth curve model that considers the causal effect of initial phenotypes
title_sort development of a structural growth curve model that considers the causal effect of initial phenotypes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6498631/
https://www.ncbi.nlm.nih.gov/pubmed/31046678
http://dx.doi.org/10.1186/s12711-019-0461-y
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