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C14orf132 gene is possibly related to extremely low birth weight

Overview of attention for article published in BMC Genetics, September 2016
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Title
C14orf132 gene is possibly related to extremely low birth weight
Published in
BMC Genetics, September 2016
DOI 10.1186/s12863-016-0439-5
Pubmed ID
Authors

Airi Tiirats, Triin Viltrop, Margit Nõukas, Ene Reimann, Andres Salumets, Sulev Kõks

Abstract

Despite extensive research the genetic component of extremely low birth weight (ELBW) in newborns has remained obscure. The aim of the case study was to identify candidate gene(s) causing ELBW in newborns and hypotrophy in infants. A family of four was studied: mother, father and two ELBW-phenotype children. Studies were made of the medical conditions of the second child at birth and post-partum - peculiar phenotype, micro-anomalies, recurrent infections, suspicion of autoimmune hepatitis, multifactorial encephalopathy and suspected metabolic and chromosomal abnormalities. Whole genome single nucleotide polymorphism (SNP) genotyping array was used to investigate the genomic rearrangements in both affected children using peripheral blood DNA samples. Whole blood transcriptome was assessed by using RNA sequencing (RNA-seq) in all four family members. RNA-seq identified a single gene - C14orf132 (chromosome 14 open reading frame 132) differentially expressed, with the level of the transcript significantly lower in the blood samples of the children. Copy number variant (CNV) analysis did not reveal any pathogenic CNVs in the region of C14orf132 gene of both affected children. We demonstrated the importance of combining whole genome CNV and transcriptome analysis in identification of the candidate gene(s) in case studies. We propose the C14orf132 gene expression to be associated with the ELBW-phenotype. C14orf132 gene is a novel long non-coding RNA (lincRNA) with unknown function, which might be associated with the pre- and early postnatal developmental delay through the altered gene expression.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 44%
Student > Master 3 17%
Professor 1 6%
Student > Bachelor 1 6%
Other 1 6%
Other 2 11%
Unknown 2 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 22%
Biochemistry, Genetics and Molecular Biology 3 17%
Social Sciences 3 17%
Medicine and Dentistry 3 17%
Psychology 2 11%
Other 0 0%
Unknown 3 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 29 September 2016.
All research outputs
#9,813,699
of 16,638,522 outputs
Outputs from BMC Genetics
#445
of 1,033 outputs
Outputs of similar age
#134,826
of 271,005 outputs
Outputs of similar age from BMC Genetics
#1
of 1 outputs
Altmetric has tracked 16,638,522 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,033 research outputs from this source. They receive a mean Attention Score of 3.8. This one has gotten more attention than average, scoring higher than 52% of its peers.
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We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them