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Systems biology surveillance decrypts pathological transcriptome remodeling

Overview of attention for article published in BMC Systems Biology, July 2015
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Title
Systems biology surveillance decrypts pathological transcriptome remodeling
Published in
BMC Systems Biology, July 2015
DOI 10.1186/s12918-015-0177-8
Pubmed ID
Authors

Randolph S. Faustino, Saranya P. Wyles, Jody Groenendyk, Marek Michalak, Andre Terzic, Carmen Perez-Terzic

Abstract

Pathological cardiac development is precipitated by dysregulation of calreticulin, an endoplasmic reticulum (ER)-resident calcium binding chaperone and critical contributor to cardiogenesis and embryonic viability. However, pleiotropic phenotype derangements induced by calreticulin deficiency challenge the identification of specific downstream transcriptome elements that direct proper cardiac formation. Here, differential transcriptome navigation was used to diagnose high priority calreticulin domain-specific gene expression changes and decrypt complex cardiac-specific molecular responses elicited by discrete functional regions of calreticulin. Wild type (WT), calreticulin-deficient (CALR(-/-)), and calreticulin truncation variant (CALR(-/-)-NP and CALR(-/-)-PC) pluripotent stem cells were used to investigate molecular remodeling underlying a model of cardiopathology. Bioinformatic deconvolution of isolated transcriptomes was performed to identify predominant expression trends, gene ontology prioritizations, and molecular network features characteristic of discrete cell types. Stem cell lines with wild type (WT), calreticulin-deficient (CALR(-/-)) genomes, as well as calreticulin truncation variants exclusively expressing either the chaperoning (CALR(-/-)-NP) or the calcium binding (CALR(-/-)-PC) domain exhibited characteristic molecular signatures determined by unsupervised agglomerative clustering. Kohonen mapping of RNA expression changes identified transcriptome dynamics that segregated into 12 discrete gene expression meta-profiles which were enriched for regulation of Eukaryotic Initiation Factor 2 (EIF2) signaling. Focused examination of domain-specific gene ontology remodeling revealed a general enrichment of Cardiovascular Development in the truncation variants, with unique prioritization of "Cardiovascular Disease" exclusive to the cohort of down regulated genes of the PC truncation variant. Molecular cartography of genes that comprised this cardiopathological category revealed uncharacterized and novel gene relationships, with identification of Pitx2 as a critical hub within the topology of a CALR(-/-) compromised network. Diagnostic surveillance, through an algorithm that integrates pluripotent stem cell transcriptomes with advanced high throughput assays and computational bioinformatics, revealed collective gene expression network changes that underlie differential phenotype development. Stem cell transcriptomes provide a deep collective molecular index that reflects ad hoc robustness of the pluripotent gene network. Remodeling events such as monogenic lesions provide a background by which high priority candidate disease effectors and regulators can be identified, demonstrated here by a molecular profiling algorithm that decrypts pluripotent wild type versus disrupted genomes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 30%
Student > Ph. D. Student 4 15%
Student > Bachelor 3 11%
Student > Master 3 11%
Other 2 7%
Other 1 4%
Unknown 6 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 30%
Agricultural and Biological Sciences 4 15%
Computer Science 3 11%
Medicine and Dentistry 3 11%
Engineering 2 7%
Other 1 4%
Unknown 6 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 28 March 2016.
All research outputs
#7,251,219
of 23,622,736 outputs
Outputs from BMC Systems Biology
#267
of 1,135 outputs
Outputs of similar age
#73,930
of 235,544 outputs
Outputs of similar age from BMC Systems Biology
#6
of 30 outputs
Altmetric has tracked 23,622,736 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 1,135 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 74% 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 235,544 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 67% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.