Evidence map›Paper›PMID 26989614›Full record

ArticlePeerJ2016

Dynamic gene expression profiles during postnatal development of porcine subcutaneous adipose.

Jie Zhang, Jideng Ma, Keren Long, Long Jin, Yihui Liu, Chaowei Zhou, Shilin Tian, Lei Chen, Zonggang Luo, Qianzi Tang and 7 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

5 citing papers in PubMed, 12 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

17 authors at 4 institutions in 1 country.

Jie Zhang *Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, Sichuan, China.
Jideng Ma *Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, Sichuan, China.
Keren Long *Institute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, Sichuan, China.
Long JinInstitute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, Sichuan, China.
Yihui LiuInstitute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, Sichuan, China.
Chaowei ZhouInstitute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, Sichuan, China.
Shilin TianNovogene Bioinformatics Institute, Beijing, China.
Lei ChenChongqing Academy of Animal Science, Chongqing, China.
Zonggang LuoDepartment of Animal Science, Southwest University at Rongchang, Chongqing, China.
Qianzi TangInstitute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, Sichuan, China.
An'an JiangInstitute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, Sichuan, China.
Xun WangInstitute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, Sichuan, China.
Dawei WangNovogene Bioinformatics Institute, Beijing, China.
Zhi JiangNovogene Bioinformatics Institute, Beijing, China.
Jinyong WangChongqing Academy of Animal Science, Chongqing, China.
Xuewei LiInstitute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, Sichuan, China.
Mingzhou LiInstitute of Animal Genetics and Breeding, College of Animal Science and Technology, Sichuan Agricultural University, Ya'an, Sichuan, China.
Sichuan Agricultural University · CNNovogene Bioinformatics Institute · CNChongqing Academy of Animal Science · CNSouthwest University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A better understanding of the control of lipogenesis is of critical importance for both human and animal physiology. This requires a better knowledge of the changes of gene expression during the process of adipose tissue development. Thus, the objective of the current study was to determine the effects of development on subcutaneous adipose tissue gene expression in growing and adult pigs. Here, we present a comprehensive investigation of mRNA transcriptomes in porcine subcutaneous adipose tissue across four developmental stages using digital gene expression profiling. We identified 3,274 differential expressed genes associated with oxidative stress, immune processes, apoptosis, energy metabolism, insulin stimulus, cell cycle, angiogenesis and translation. A set of universally abundant genes (ATP8, COX2, COX3, ND1, ND2, SCD and TUBA1B) was found across all four developmental stages. This set of genes may play important roles in lipogenesis and development. We also identified development-related gene expression patterns that are linked to the different adipose phenotypes. We showed that genes enriched in significantly up-regulated profiles were associated with phosphorylation and angiogenesis. In contrast, genes enriched in significantly down-regulated profiles were related to cell cycle and cytoskeleton organization, suggesting an important role for these biological processes in adipose growth and development. These results provide a resource for studying adipose development and promote the pig as a model organism for researching the development of human obesity, as well as being used in the pig industry.

Indexed as

DevelopmentGene expressionPigSubcutaneous adipose

Identifiers

PMID26989614
PMCPMC4793310
OpenAlexW2294950701

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.