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Whole-transcriptome analysis delineates the human placenta gene network and its associations with fetal growth

Overview of attention for article published in BMC Genomics, July 2017
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  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

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Title
Whole-transcriptome analysis delineates the human placenta gene network and its associations with fetal growth
Published in
BMC Genomics, July 2017
DOI 10.1186/s12864-017-3878-0
Pubmed ID
Authors

Maya A. Deyssenroth, Shouneng Peng, Ke Hao, Luca Lambertini, Carmen J. Marsit, Jia Chen

Abstract

The placenta is the principal organ regulating intrauterine growth and development, performing critical functions on behalf of the developing fetus. The delineation of functional networks and pathways driving placental processes has the potential to provide key insight into intrauterine perturbations that result in adverse birth as well as later life health outcomes. We generated the transcriptome-wide profile of 200 term human placenta using the Illumina HiSeq 2500 platform and characterized the functional placental gene network using weighted gene coexpression network analysis (WGCNA). We identified 17 placental coexpression network modules that were dominated by functional processes including growth, organ development, gas exchange and immune response. Five network modules, enriched for processes including cellular respiration, amino acid transport, hormone signaling, histone modifications and gene expression, were associated with birth weight; hub genes of all five modules (CREB3, DDX3X, DNAJC14, GRHL1 and C21orf91) were significantly associated with fetal growth restriction, and one hub gene (CREB3) was additionally associated with fetal overgrowth. In this largest RNA-Seq based transcriptome-wide profiling study of human term placenta conducted to date, we delineated a placental gene network with functional relevance to fetal growth using a network-based approach with superior scale reduction capacity. Our study findings not only implicate potential molecular mechanisms underlying fetal growth but also provide a reference placenta gene network to inform future studies investigating placental dysfunction as a route to future disease endpoints.

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The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 18%
Student > Master 12 18%
Researcher 10 15%
Student > Bachelor 8 12%
Student > Doctoral Student 7 11%
Other 6 9%
Unknown 11 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 24%
Medicine and Dentistry 13 20%
Agricultural and Biological Sciences 8 12%
Nursing and Health Professions 4 6%
Immunology and Microbiology 3 5%
Other 10 15%
Unknown 12 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 March 2018.
All research outputs
#13,326,031
of 22,988,380 outputs
Outputs from BMC Genomics
#4,793
of 10,690 outputs
Outputs of similar age
#154,007
of 312,577 outputs
Outputs of similar age from BMC Genomics
#97
of 227 outputs
Altmetric has tracked 22,988,380 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,690 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 53% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 312,577 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 227 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.