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Identification of a RAI1-associated disease network through integration of exome sequencing, transcriptomics, and 3D genomics

Overview of attention for article published in Genome Medicine, November 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (72nd percentile)

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Title
Identification of a RAI1-associated disease network through integration of exome sequencing, transcriptomics, and 3D genomics
Published in
Genome Medicine, November 2016
DOI 10.1186/s13073-016-0359-z
Pubmed ID
Authors

Maria Nicla Loviglio, Christine R. Beck, Janson J. White, Marion Leleu, Tamar Harel, Nicolas Guex, Anne Niknejad, Weimin Bi, Edward S. Chen, Isaac Crespo, Jiong Yan, Wu-Lin Charng, Shen Gu, Ping Fang, Zeynep Coban-Akdemir, Chad A. Shaw, Shalini N. Jhangiani, Donna M. Muzny, Richard A. Gibbs, Jacques Rougemont, Ioannis Xenarios, James R. Lupski, Alexandre Reymond

Abstract

Smith-Magenis syndrome (SMS) is a developmental disability/multiple congenital anomaly disorder resulting from haploinsufficiency of RAI1. It is characterized by distinctive facial features, brachydactyly, sleep disturbances, and stereotypic behaviors. We investigated a cohort of 15 individuals with a clinical suspicion of SMS who showed neither deletion in the SMS critical region nor damaging variants in RAI1 using whole exome sequencing. A combination of network analysis (co-expression and biomedical text mining), transcriptomics, and circularized chromatin conformation capture (4C-seq) was applied to verify whether modified genes are part of the same disease network as known SMS-causing genes. Potentially deleterious variants were identified in nine of these individuals using whole-exome sequencing. Eight of these changes affect KMT2D, ZEB2, MAP2K2, GLDC, CASK, MECP2, KDM5C, and POGZ, known to be associated with Kabuki syndrome 1, Mowat-Wilson syndrome, cardiofaciocutaneous syndrome, glycine encephalopathy, mental retardation and microcephaly with pontine and cerebellar hypoplasia, X-linked mental retardation 13, X-linked mental retardation Claes-Jensen type, and White-Sutton syndrome, respectively. The ninth individual carries a de novo variant in JAKMIP1, a regulator of neuronal translation that was recently found deleted in a patient with autism spectrum disorder. Analyses of co-expression and biomedical text mining suggest that these pathologies and SMS are part of the same disease network. Further support for this hypothesis was obtained from transcriptome profiling that showed that the expression levels of both Zeb2 and Map2k2 are perturbed in Rai1 (-/-) mice. As an orthogonal approach to potentially contributory disease gene variants, we used chromatin conformation capture to reveal chromatin contacts between RAI1 and the loci flanking ZEB2 and GLDC, as well as between RAI1 and human orthologs of the genes that show perturbed expression in our Rai1 (-/-) mouse model. These holistic studies of RAI1 and its interactions allow insights into SMS and other disorders associated with intellectual disability and behavioral abnormalities. Our findings support a pan-genomic approach to the molecular diagnosis of a distinctive disorder.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 99 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 16%
Researcher 15 15%
Student > Doctoral Student 11 11%
Student > Master 10 10%
Student > Bachelor 7 7%
Other 15 15%
Unknown 25 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 25 25%
Medicine and Dentistry 13 13%
Agricultural and Biological Sciences 11 11%
Neuroscience 7 7%
Psychology 6 6%
Other 12 12%
Unknown 25 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 08 March 2018.
All research outputs
#5,545,320
of 22,899,952 outputs
Outputs from Genome Medicine
#965
of 1,443 outputs
Outputs of similar age
#83,991
of 311,687 outputs
Outputs of similar age from Genome Medicine
#24
of 34 outputs
Altmetric has tracked 22,899,952 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,443 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.8. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
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 311,687 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.