Evidence map›Paper›PMID 32318090›Full record

ArticleFrontiers in genetics2020

New Insights From Imputed Whole-Genome Sequence-Based Genome-Wide Association Analysis and Transcriptome Analysis: The Genetic Mechanisms Underlying Residual Feed Intake in Chickens.

Shaopan Ye, Zi-Tao Chen, Rongrong Zheng, Shuqi Diao, Jinyan Teng, Xiaolong Yuan, Hao Zhang, Zanmou Chen, Xiquan Zhang, Jiaqi Li and 1 more

Abstract read
In one paragraph

Article in Frontiers in genetics, 2020. 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. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  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

11 authors.

Shaopan YeGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China.
Zi-Tao ChenGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China.
Rongrong ZhengGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China.
Shuqi DiaoGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China.
Jinyan TengGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China.
Xiaolong YuanGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China.
Hao ZhangGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China.
Zanmou ChenGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China.
Xiquan ZhangGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China.
Jiaqi LiGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China.
Zhe ZhangGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Poultry feed constitutes the largest cost in poultry production, estimated to be up to 70% of the total cost. Moreover, there is pressure on the poultry industry to increase production to meet the protein demand of humans and simultaneously reduce emissions to protect the environment. Therefore, improving feed efficiency plays an important role to improve profits and the environmental footprint in broiler production. In this study, using imputed whole-genome sequencing data, genome-wide association analysis (GWAS) was performed to identify single-nucleotide polymorphisms (SNPs) and genes associated with residual feed intake (RFI) and its component traits. Furthermore, a transcriptomic analysis between the high-RFI and the low-RFI groups was performed to validate the candidate genes from GWAS. The results showed that the heritability estimates of average daily gain (ADG), average daily feed intake (ADFI), and RFI were 0.29 (0.004), 0.37 (0.005), and 0.38 (0.004), respectively. Using imputed sequence-based GWAS, we identified seven significant SNPs and five candidate genes [MTSS I-BAR domain containing 1, folliculin, COP9 signalosome subunit 3, 5',3'-nucleotidase (mitochondrial), and gametocyte-specific factor 1] associated with RFI, 20 significant SNPs and one candidate gene (inositol polyphosphate multikinase) associated with ADG, and one significant SNP and one candidate gene (coatomer protein complex subunit alpha) associated with ADFI. After performing a transcriptomic analysis between the high-RFI and the low-RFI groups, both 38 up-regulated and 26 down-regulated genes were identified in the high-RFI group. Furthermore, integrating regional conditional GWAS and transcriptome analysis, ras-related dexamethasone induced 1 was the only overlapped gene associated with RFI, which also suggested that the region (GGA14: 4767015-4882318) is a new quantitative trait locus associated with RFI. In conclusion, using imputed sequence-based GWAS is an efficient method to identify significant SNPs and candidate genes in chicken. Our results provide valuable insights into the genetic mechanisms of RFI and its component traits, which would further improve the genetic gain of feed efficiency rapidly and cost-effectively in the context of marker-assisted breeding selection.

Indexed as

chickensfeed efficiencyGWASimputed WGS datatranscriptome analysis

Identifiers

PMID32318090
PMCPMC7147382

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.