Evidence map›Paper›PMID 33510859›Full record

ArticleComputational and structural biotechnology journal2021

Gut microbiome mediates host genomic effects on phenotypes: a case study with fat deposition in pigs.

Francesco Tiezzi, Justin Fix, Clint Schwab, Caleb Shull, Christian Maltecca

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
  2. Microbial and Genomic Information Synergistically Contribute to Predicting Swine Performance Across Production Systems.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026
    Article
  3. Multiple-trait genomic prediction for swine meat quality traits using gut microbiome features as a correlated trait.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2025
    Article
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  6. Review
  7. Article
  8. Article
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  13. Review
  14. Article
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

5 authors.

Francesco TiezziDepartment of Animal Science, North Carolina State University, Raleigh, NC, USA.
Justin FixAcuity Ag Solutions, LLC, Carlyle, IL 62230, USA.
Clint SchwabAcuity Ag Solutions, LLC, Carlyle, IL 62230, USA.
Caleb ShullThe Maschhoffs, LLC, Carlyle, IL 62230, USA.
Christian MalteccaDepartment of Animal Science, North Carolina State University, Raleigh, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A large number of studies have highlighted the importance of gut microbiome composition in shaping fat deposition in mammals. Several studies have also highlighted how host genome controls the abundance of certain species that make up the gut microbiota. We propose a systematic approach to infer how the host genome can control the gut microbiome, which in turn contributes to the host phenotype determination. We implemented a mediation test that can be applied to measured and latent dependent variables to describe fat deposition in swine (

Indexed as

BEL, Weight of the belly cutBF1, Backfat depth measured in vivo at the age of 118.1±1.16 dBF2, Backfat depth measured in vivo at the age of 145.9±1.53 dBF3, Backfat depth measured in vivo at the age of 174.3±1.43 dBF4, Backfat depth measured in vivo at the age of 196.6±8.03 dBFt, Backfat measured post mortem (after slaughter at 196.6±8.03 d)Causal effectFat depositionFATg, Latent variable built on BF1, BF2, and BF3FATt, Latent variable built on BF4, BFt, and BELG, host genomic features, represented in this study by SNPGut microbiomeLatent variablesM, gut microbiome features, represented in this study by OUTMod1L, Model 1L, used to estimate the total effect of G onMod1, Model 1, used to estimate the total effect of G on P. Reported in Fig. 1aMod2L, Model 2L, used to estimate the effect of M onMod2, Model 2, used to estimate the effect of M on P. Reported in Fig. 1bMod3, Model 3, used to estimate the effect of G on M. Reported in Fig. S1Mod4L, Model 4, used to estimate the direct and mediated effects of G on. Reported in Fig. 1dMod4, Model 4, used to estimate the direct and mediated effects of G on P. Reported in Fig. 1cOUT, Operational Taxonomic UnitsP, Phenotype recorded on the hostS2a, S2b, S3a, S3b, S3c, Gut microbiome OUT selected used as mediator variables. See Table 2SEM, Structural equation modelSNP, Single Nucleotide Polymorphism markerΠ, Latent variable built on the P variables

Identifiers

PMID33510859
PMCPMC7809165

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

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 Socratic graph.