Evidence map›Paper›PMID 33167870›Full record

ArticleGenetics, selection, evolution : GSE2020

Gene networks for three feed efficiency criteria reveal shared and specific biological processes.

Sébastien Taussat, Mekki Boussaha, Yuliaxis Ramayo-Caldas, Pauline Martin, Eric Venot, Gonzalo Cantalapiedra-Hijar, Chris Hozé, Sébastien Fritz, Gilles Renand

Abstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Genome-Wide Association Study of Feed Efficiency Related Traits in Ducks.Animals : an open access journal from MDPI · 2022
    Article
  12. Article
  13. 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

9 authors.

Sébastien TaussatUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France. sebastien.taussat@inrae.fr.ORCID http://orcid.org/0000-0002-3101-9471
Mekki BoussahaUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Yuliaxis Ramayo-CaldasUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Pauline MartinUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Eric VenotUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Gonzalo Cantalapiedra-HijarINRAE, Université Clermont Auvergne, Vetagro Sup, UMRH, 63122, Saint-Genès-Champanelle, France.
Chris HozéUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Sébastien FritzUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.
Gilles RenandUniversité Paris-Saclay, INRAE, AgroParisTech, GABI, 78350, Jouy-en-Josas, France.

Funding

H2020 Marie Skłodowska-Curie Actions 6655919
6 · The paper itself

Abstract

backgroundFrench beef producers suffer from the decrease in profitability of their farms mainly because of the continuous increase in feed costs. Selection for feed efficiency in beef cattle represents a relevant solution to face this problem. However, feed efficiency is a complex trait that can be assessed by three major criteria: residual feed intake (RFI), residual gain (RG) and feed efficiency ratio (FE), which involve different genetic determinisms. An analysis that combines phenotype and whole-genome sequence data provides a unique framework for genomic studies. The aim of our study was to identify the gene networks and the biological processes that are responsible for the genetic determinism that is shared between these three feed efficiency criteria.

resultsA population of 1477 French Charolais young bulls was phenotyped for feed intake (FI), average daily gain (ADG) and final weight (FW) to estimate RFI, RG and FE. A subset of 789 young bulls was genotyped on the BovineSNP50 single nucleotide polymorphism (SNP) array and imputed at the sequence level using RUN6 of the 1000 Bull Genomes Project. We conducted a genome-wide association study (GWAS) to estimate the individual effect of 8.5 million SNPs and applied an association weight matrix (AWM) approach to analyse the results, one for each feed efficiency criterion. The results highlighted co-association networks including 626 genes for RFI, 426 for RG and 564 for FE. Enrichment assessment revealed the biological processes that show the strongest association with RFI, RG and FE, i.e. digestive tract (salivary, gastric and mucin secretion) and metabolic processes (cellular and cardiovascular). Energetic functions were more associated with RFI and FE and cardio-vascular and cellular processes with RG. Several hormones such as apelin, glucagon, insulin, aldosterone, the gonadotrophin releasing hormone and the thyroid hormone were also identified, and these should be tested in future studies as candidate biomarkers for feed efficiency.

conclusionsThe combination of network and pathway analyses at the sequence level led to the identification of both common and specific mechanisms that are involved in RFI, RG and FE, and to a better understanding of the genetic determinism underlying these three criteria. The effects of the genes involved in each of the identified processes need to be tested in genomic evaluations to confirm the potential gain in reliability of using functional variants to select animals for feed efficiency.

Indexed as

Animal FeedGene Regulatory NetworksAnimal Nutritional Physiological PhenomenaAnimalsBody WeightCattleDigestionEatingEnergy MetabolismPolymorphism, Single NucleotideQuantitative Trait, Heritable

Identifiers

PMID33167870
PMCPMC7653997

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.