Evidence map›Paper›PMID 29273734›Full record

ArticleScientific reports2017

RNA-Seq reveals seven promising candidate genes affecting the proportion of thick egg albumen in layer-type chickens.

Yi Wan, Sihua Jin, Chendong Ma, Zhicheng Wang, Qi Fang, Runshen Jiang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

15 citing papers in PubMed, 39 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Yi WanCollege of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036, China.
Sihua JinCollege of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036, China.
Chendong MaCollege of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036, China.
Zhicheng WangCollege of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036, China.
Qi FangCollege of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036, China.
Runshen JiangCollege of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036, China. jiangrunshen@ahau.edu.cn.
Anhui Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Eggs with a much higher proportion of thick albumen are preferred in the layer industry, as they are favoured by consumers. However, the genetic factors affecting the thick egg albumen trait have not been elucidated. Using RNA sequencing, we explored the magnum transcriptome in 9 Rhode Island white layers: four layers with phenotypes of extremely high ratios of thick to thin albumen (high thick albumen, HTA) and five with extremely low ratios (low thick albumen, LTA). A total of 220 genes were differentially expressed, among which 150 genes were up-regulated and 70 were down-regulated in the HTA group compared with the LTA group. Gene Ontology (GO) analysis revealed that the up-regulated genes in HTA were mainly involved in a wide range of regulatory functions. In addition, a large number of these genes were related to glycosphingolipid biosynthesis, focal adhesion, ECM-receptor interactions and cytokine-cytokine receptor interactions. Based on functional analysis, ST3GAL4, FUT4, ITGA2, SDC3, PRLR, CDH4 and GALNT9 were identified as promising candidate genes for thick albumen synthesis and metabolism during egg formation. These results provide new insights into the molecular mechanisms of egg albumen traits and may contribute to future breeding strategies that optimise the proportion of thick egg albumen.

Indexed as

BreedingEggsEgg WhiteRNAAlbuminsAnimalsChickensFemaleSequence Analysis, RNATranscriptomeAlbuminsRNA

Identifiers

PMID29273734
PMCPMC5741707
OpenAlexW2779954782

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.