Evidence map›Paper›PMID 34074340›Full record

ArticleMicrobiome2021

Joint contributions of the gut microbiota and host genetics to feed efficiency in chickens.

Chaoliang Wen, Wei Yan, Chunning Mai, Zhongyi Duan, Jiangxia Zheng, Congjiao Sun, Ning Yang

Open access · goldAbstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers.

0numbers the graph read from it
0cells of the map it votes in
126citing papers in PubMed
13.8field-weighted citation impact, top 1% of its field
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

126 citing papers in PubMed, 180 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article

66 more citing papers are in PubMed but not listed here.

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 at 3 institutions in 2 countries.

Chaoliang WenNational Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing, 100193, China.ORCID 0000-0002-0514-2847
Wei YanNational Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing, 100193, China.
Chunning MaiNational Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing, 100193, China.
Zhongyi DuanNational Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing, 100193, China.
Jiangxia ZhengNational Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing, 100193, China.
Congjiao SunNational Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing, 100193, China. cjsun@cau.edu.cn.ORCID 0000-0002-9673-9533
Ning YangNational Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing, 100193, China. nyang@cau.edu.cn.ORCID 0000-0001-5772-3320
Ministry of Agriculture and Rural Affairs · CNMinistry of Agriculture · IDNational Animal Husbandry Service · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFeed contributes most to livestock production costs. Improving feed efficiency is crucial to increase profitability and sustainability for animal production. Host genetics and the gut microbiota can both influence the host phenotype. However, the association between the gut microbiota and host genetics and their joint contribution to feed efficiency in chickens is largely unclear.

resultsHere, we examined microbial data from the duodenum, jejunum, ileum, cecum, and feces in 206 chickens and their host genotypes and confirmed that the microbial phenotypes and co-occurrence networks exhibited dramatic spatial heterogeneity along the digestive tract. The correlations between host genetic kinship and gut microbial similarities within different sampling sites were weak, with coefficients ranging from - 0.07 to 0.08. However, microbial genome-wide analysis revealed that genetic markers near or inside the genes MTHFD1L and LARGE1 were associated with the abundances of cecal Megasphaera and Parabacteroides, respectively. The effect of host genetics on residual feed intake (RFI) was 39%. We further identified three independent genetic variations that were related to feed efficiency and had a modest effect on the gut microbiota. The contributions of the gut microbiota from the different parts of the intestinal tract on RFI were distinct. The cecal microbiota accounted for 28% of the RFI variance, a value higher than that explained by the duodenal, jejunal, ileal, and fecal microbiota. Additionally, six bacteria exhibited significant associations with RFI. Specifically, lower abundances of duodenal Akkermansia muciniphila and cecal Parabacteroides and higher abundances of cecal Lactobacillus, Corynebacterium, Coprobacillus, and Slackia were related to better feed efficiency.

conclusionsOur findings solidified the notion that both host genetics and the gut microbiota, especially the cecal microbiota, can drive the variation in feed efficiency. Although host genetics has a limited effect on the entire microbial community, a small fraction of gut microorganisms tends to interact with host genes, jointly contributing to feed efficiency. Therefore, the gut microbiota and host genetic variations can be simultaneously targeted by favoring more-efficient taxa and selective breeding to improve feed efficiency in chickens. Video abstract.

Indexed as

Gastrointestinal MicrobiomeAnimal FeedAnimalsCecumChickensFecesChickenFeed efficiencyGenetic variationsGut microbiotaSpatial heterogeneity

Identifiers

PMID34074340
PMCPMC8171024
OpenAlexW3165439943

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.