Evidence map›Paper›PMID 35627152›Full record

ArticleGenes2022

Use of Host Feeding Behavior and Gut Microbiome Data in Estimating Variance Components and Predicting Growth and Body Composition Traits in Swine.

Yuqing He, Francesco Tiezzi, Jicai Jiang, Jeremy T Howard, Yijian Huang, Kent Gray, Jung-Woo Choi, Christian Maltecca

Abstract read
In one paragraph

Article in Genes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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

8 authors.

Yuqing HeDepartment of Animal Science, North Carolina State University, 120 W Broughton Dr, Raleigh, NC 27607, USA.
Francesco TiezziDepartment of Animal Science, North Carolina State University, 120 W Broughton Dr, Raleigh, NC 27607, USA.ORCID 0000-0002-4358-9236
Jicai JiangDepartment of Animal Science, North Carolina State University, 120 W Broughton Dr, Raleigh, NC 27607, USA.
Jeremy T HowardSmithfield Premium Genetics, Rose Hill, NC 28458, USA.
Yijian HuangSmithfield Premium Genetics, Rose Hill, NC 28458, USA.
Kent GraySmithfield Premium Genetics, Rose Hill, NC 28458, USA.
Jung-Woo ChoiCollege of Animal Life Sciences, Division of Animal Resource Science, 1 Gangwondaehak-gil, Chuncheon-si 24341, Gangwon-do, Korea.ORCID 0000-0001-7827-5037
Christian MalteccaDepartment of Animal Science, North Carolina State University, 120 W Broughton Dr, Raleigh, NC 27607, USA.ORCID 0000-0002-9996-4680

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study was to investigate the use of feeding behavior in conjunction with gut microbiome sampled at two growth stages in predicting growth and body composition traits of finishing pigs. Six hundred and fifty-one purebred boars of three breeds: Duroc (DR), Landrace (LR), and Large White (LW), were studied. Feeding activities were recorded individually from 99 to 163 days of age. The 16S rRNA gene sequences were obtained from each pig at 123 ± 4 and 158 ± 4 days of age. When pigs reached market weight, body weight (BW), ultrasound backfat thickness (BF), ultrasound loin depth (LD), and ultrasound intramuscular fat (IMF) content were measured on live animals. Three models including feeding behavior (Model_FB), gut microbiota (Model_M), or both (Model_FB_M) as predictors, were investigated. Prediction accuracies were evaluated through cross-validation across genetic backgrounds using the leave-one-breed-out strategy and across rearing environments using the leave-one-room-out approach. The proportions of phenotypic variance of growth and body composition traits explained by feeding behavior ranged from 0.02 to 0.30, and from 0.20 to 0.52 when using gut microbiota composition. Overall prediction accuracy (averaged over traits and time points) of phenotypes was 0.24 and 0.33 for Model_FB, 0.27 and 0.19 for Model_M, and 0.40 and 0.35 for Model_FB_M for the across-breed and across-room scenarios, respectively. This study shows how feeding behavior and gut microbiota composition provide non-redundant information in predicting growth in swine.

Indexed as

Gastrointestinal MicrobiomeAnimalsBody CompositionFeeding BehaviorMalePhenotypeRNA, Ribosomal, 16SSwineRNA, Ribosomal, 16Sbreedsfeeding behaviorgrowthgut microbiome compositionpredictionswine

Identifiers

PMID35627152
PMCPMC9140470

What OpenQuestion holds

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LicenceCC BY
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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.