Evidence map›Paper›PMID 31046678›Full record

ArticleGenetics, selection, evolution : GSE2019

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

Akio Onogi, Atsushi Ogino, Ayako Sato, Kazuhito Kurogi, Takanori Yasumori, Kenji Togashi

Abstract read
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Article in Genetics, selection, evolution : GSE, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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  3. Modeling soybean growth: A mixed model approach.PLoS computational biology · 2024
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Akio OnogiInstitute of Crop Science, National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki, 305-8518, Japan. onogiakio@gmail.com.ORCID http://orcid.org/0000-0003-1707-9539
Atsushi OginoMaebashi Institute of Animal Science, Livestock Improvement Association of Japan, Inc, Maebashi, 371-0121, Japan.
Ayako SatoCattle Breeding Department, Livestock Improvement Association of Japan, Inc, Tokyo, 135-0041, Japan.
Kazuhito KurogiMaebashi Institute of Animal Science, Livestock Improvement Association of Japan, Inc, Maebashi, 371-0121, Japan.
Takanori YasumoriCattle Breeding Department, Livestock Improvement Association of Japan, Inc, Tokyo, 135-0041, Japan.
Kenji TogashiMaebashi Institute of Animal Science, Livestock Improvement Association of Japan, Inc, Maebashi, 371-0121, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGrowth 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.

resultsMaternal 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.

conclusionsThe 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.

Indexed as

Growth ChartsAnimal HusbandryAnimalsBody WeightCattleCattle DiseasesComputer SimulationJapanPhenotypeReproduction

Identifiers

PMID31046678
PMCPMC6498631

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.