Evidence map›Paper›PMID 23073784›Full record

ArticleMolecular biology reports2013

Comparative analysis of differentially expressed genes in Sika deer antler at different stages.

Yu Zhao, Baojin Yao, Mei Zhang, Siming Wang, Hui Zhang, Wei Xiao

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Molecular biology reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  15. Transcriptome analysis of sika deer in China.Molecular genetics and genomics : MGG · 2016
    Article
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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.

Yu ZhaoCenter for New Medicine Research, Changchun University of Chinese Medicine, Changchun, 130117, China.
Baojin Yao
Mei Zhang
Siming Wang
Hui Zhang
Wei Xiao

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deer antlers serve as useful models of rapid growth and mineralization in mammals. During the period of rapid growth, the antlers of many species of deer will elongate by more than 2 cm per day, after which the antlers gradually ossify. However, little is known about the genes that are involved in their development, particularly the molecular mechanisms responsible for rapid growth and ossification. In our previous studies, we have reported on the transcriptome analysis of deer antlers at rapid growth and ossification stages. With the aim to get a comprehensive understanding of gene expression patterns during antler growth, in the present study, we performed a rigorous algorithm to identify differentially expressed genes between two different stages (60 and 90 days) during antler growth. A total of 16,905 significantly changed transcripts were identified. Those sequences were mapped to 5,573 genes with 2,217 genes up-regulated and 3,356 genes down-regulated (60 days vs. 90 days), including ribosomal proteins, translation initiation and elongation factors, transcription factors, signaling molecules and extracellular matrix proteins. We also performed the gene ontology (GO) functional enrichment and pathway enrichment analysis of gene expression patterns with hypergeometric test and Bonferroni Correction. Both the two stages were enriched with members of GO categories and distinct pathways. Our data represent the most comprehensive sequence resource available for the deer antler and provide a basis for further research on deer antler molecular genetics and functional genomics.

Indexed as

TranscriptomeAnimalsAntlersDeerGene Expression Regulation, DevelopmentalGene LibraryGenesGenetic Association StudiesMolecular Sequence AnnotationReal-Time Polymerase Chain ReactionSequence Analysis, DNA

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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.