Evidence map›Paper›PMID 39028536›Full record

ArticleJournal of animal science2024

Genotype-by-gestational thermal environment interaction and its impact on the future performance of tropical composite beef cattle offspring.

Matheus Gomes Rodrigues Cardoso, Annaiza Braga Bignardi, Rodrigo Junqueira Pereira, Joanir Pereira Eler, José Bento Sterman Ferraz, Luiz Fernando Brito, Mário Luiz Santana

Abstract read
In one paragraph

Article in Journal of animal science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Matheus Gomes Rodrigues CardosoGrupo de Melhoramento Animal de Mato Grosso, Instituto de Ciências Agrárias e Tecnológicas, Universidade Federal de Rondonópolis, Rondonópolis, MT, 78736-900, Brazil.
Annaiza Braga BignardiGrupo de Melhoramento Animal de Mato Grosso, Instituto de Ciências Agrárias e Tecnológicas, Universidade Federal de Rondonópolis, Rondonópolis, MT, 78736-900, Brazil.ORCID 0000-0002-8756-2182
Rodrigo Junqueira PereiraGrupo de Melhoramento Animal de Mato Grosso, Instituto de Ciências Agrárias e Tecnológicas, Universidade Federal de Rondonópolis, Rondonópolis, MT, 78736-900, Brazil.
Joanir Pereira ElerDepartamento de Medicina Veterinária, Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de São Paulo, Pirassununga, SP, 13635-900, Brazil.
José Bento Sterman FerrazDepartamento de Medicina Veterinária, Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de São Paulo, Pirassununga, SP, 13635-900, Brazil.ORCID 0000-0002-3874-3104
Luiz Fernando BritoDepartment of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA.ORCID 0000-0002-5819-0922
Mário Luiz SantanaGrupo de Melhoramento Animal de Mato Grosso, Instituto de Ciências Agrárias e Tecnológicas, Universidade Federal de Rondonópolis, Rondonópolis, MT, 78736-900, Brazil.ORCID 0000-0001-8392-1304

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With global warming, there are growing challenges for raising taurine and composite beef cattle populations in tropical regions, including elevated temperatures, limited forage availability, parasite infestation, and infectious diseases. These environmental factors can trigger specific physiological responses in the developing fetus, which may have long-term implications on its performance. Therefore, the main objective of this study was to assess the influence of naturally induced thermal stress during the gestation period on the subsequent performance of tropical composite beef cattle progeny. Furthermore, we aimed to investigate the impact of genotype-by-gestational thermal environment interaction (G×Eg) on traits under selection pressure in the breeding population. A total of 157,414 animals from 58 farms located in various Brazilian states were recorded for birth weight (BW), preweaning weight gain (PWG), yearling weight (YW), hip height (HH), scrotal circumference (SC), and days to first calving (DFC). We first applied a linear regression model to the BW data, which revealed that the last 40 d of gestation were suitable for calculating the mean temperature humidity index (THIg). Subsequent regression analyses revealed that for every 10-unit increase in THIg, detrimental effects of approximately 1.13% to 16.34% are expected for all traits evaluated. Genetic parameters were estimated through a reaction norm model using THIg as the environmental descriptor. The posterior means of heritability estimates (SD) were 0.35 (0.07), 0.25 (0.03), 0.31 (0.03), 0.37 (0.01), 0.29 (0.07), and 0.20 (0.09) for the direct effect of BW, PWG, YW, HH, SC, and DFC, respectively. These estimates varied along the range of THIg values, suggesting a variable response to selection depending on the thermal environment during gestation. Genetic correlation estimates between more divergent THIg values were low or negative for YW, PWG, and DFC, indicating that the best-performing individuals at low THIg values may not perform as well at high THIg values and vice versa. Overall, thermal stress during gestation impacts the future performance of beef cattle offspring. Our results indicate the need for developing effective breeding strategies that take into account G×Eg effects and the re-ranking of breeding animals along the THIg scale, particularly for traits such as DFC that are highly sensitive to thermal stress.

Indexed as

GenotypeAnimalsBirth WeightBrazilBreedingCattleFemaleMalePregnancyTemperatureTropical ClimateWeight Gaincrossbredfetal programminggenotype-by-environment interactionheat stressreaction norm

Identifiers

PMID39028536
PMCPMC11303872

What OpenQuestion holds

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Registered trials

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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.