Evidence map›Paper›PMID 24082823›Full record

ArticleCurrent genomics2013

Overview of Genomic Insights into Chicken Growth Traits Based on Genome-Wide Association Study and microRNA Regulation.

Zhenqiang Xu, Qinghua Nie, Xiquan Zhang

Abstract read
In one paragraph

Article in Current genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. In silico screening of the chicken genome for overlaps between genomic regions: microRNA genes, coding and non-coding transcriptional units, QTL, and genetic variations.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2016
    Article
  11. Article
  12. 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

3 authors.

Zhenqiang XuGuangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, and Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, South China Agricultural University, Guangzhou 510642, Guang-dong, China.
Qinghua Nie
Xiquan Zhang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the two past decades, a significant number of studies have observed animal growth traits to examine animal genetic mechanisms due to their ease of measurement and high heritability. Chicken which has a significant impact on fundamental biology is a major source of protein worldwide, making it an ideal model for examining animal growth trait development. The genetic mechanisms of chicken growth traits have been studied using quantitative trait loci mapping through genome-scan and candidate gene approaches, genome-wide association studies (GWAS), comparative genomic strategies, microRNA (miRNA) regulation of growth development analysis, and epigenomic analysis. This review focuses on chicken GWAS and miRNA regulation of growth traits. Several recently published GWAS reports showed that most genome-wide significant single nucleotide polymorphisms are located on chromosomes 1 and 4 in chickens. Chicken growth, particularly skeletal muscle growth and development, is greatly regulated by miRNA. Using dwarf and normal chickens, let-7b was found to be involved in determining chicken dwarf phenotypes by regulating growth hormone receptor gene expression.

Indexed as

ChickenGenome-wide association study (GWAS)Growth traitsmicroRNA (miRNA) regulationQuantitative trait loci (QTL)Single nucleotide polymorphisms (SNPs).

Identifiers

PMID24082823
PMCPMC3637678

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.