Evidence map›Paper›PMID 20848214›Full record

ArticleMolecular biology reports2011

Screening candidate genes related to tenderness trait in Qinchuan cattle by genome array.

YingYing Zhang, LinSen Zan, HongBao Wang

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular biology reports, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.7field-weighted citation impact, top 12% 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

10 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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 at 1 institution in 1 country.

YingYing ZhangCollege of Animal Science and Technology, Northwest A&F University, No. 22 Xinong Road, Yangling, Shaanxi 712100, China.
LinSen Zan
HongBao Wang
Northwest A&F University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to screen candidate genes related to tenderness trait in Qinchuan cattle, we investigated the gene expression profile of Longuissimus dorsi muscle (LDM) tissue and screened differentially expressed genes in LDM from both male and female Qinchuan cattle at 36 months of age utilising Bovine Genome Array. Significance Analysis of Microarrays (SAM) was used to identify the differentially expressed genes, Go (Gene Ontology) and pathways analysis were conducted on which by a free web-based Molecular Annotation System 2.0 (MAS 2.0). Approximately 11,000 probe sets representing 10,000 genes were detected in LDM of 36 month old Qinchuan cattle. After SAM analysis of the microarray data, 598 genes were shown to be differentially expressed. These genes were predominantly involved in cell adhesion, collagen fibril organization and synthesis, immune responses and cell-matrix adhesion. They included cell adhesion molecules (CAMs) and ECM-receptor interaction molecules. Real-time PCR was performed to validate nine of the differentially expressed genes identified by microarray. The results suggest that at the transcriptional level the residual hardness caused by connective tissues, stroma protein and muscle tissues could mainly result in tenderness differences between male and female Qinchuan cattle.

Indexed as

Genetic Association StudiesGenetic TestingQuantitative Trait, HeritableAnimalsBiomechanical PhenomenaCattleChinaCluster AnalysisFemaleGene Expression ProfilingGene Expression RegulationGenomeMaleMeatMuscle, SkeletalOligonucleotide Array Sequence Analysis

Identifiers

PMID20848214
OpenAlexW1993022617

What Socratic holds

Textmetadata
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 Socratic graph.