Systems biology surveillance decrypts pathological transcriptome remodeling
Randolph S Faustino1, Saranya P Wyles2, Jody Groenendyk3
1Division of Cardiovascular Diseases, Departments of Medicine, Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. Faustino.Randolph@mayo.edu.
Insights
Calreticulin deficiency causes pathological cardiac development. This study used stem cell transcriptomes to identify gene networks underlying cardiac disease, revealing Pitx2 as a key regulator in calreticulin-compromised networks.
Area of Science:
- Cardiovascular Biology
- Stem Cell Biology
- Molecular Genetics
Background:
- Calreticulin (CALR) is an endoplasmic reticulum chaperone crucial for cardiogenesis.
- CALR dysregulation leads to pathological cardiac development and embryonic lethality.
- Understanding CALR's domain-specific functions is vital for deciphering cardiac formation pathways.
Purpose of the Study:
- To investigate the molecular mechanisms of cardiac development affected by CALR deficiency.
- To identify specific gene expression changes and regulatory networks influenced by CALR domains.
- To decrypt the role of CALR in cardiopathology using pluripotent stem cells.
Main Methods:
- Utilized wild type, CALR-deficient, and CALR truncation variant pluripotent stem cells.
- Performed bioinformatic deconvolution of transcriptomes to identify expression trends and gene networks.
- Employed unsupervised clustering and Kohonen mapping for RNA expression analysis.
Main Results:
- CALR variants exhibited distinct molecular signatures.
- Transcriptome analysis revealed 12 gene expression meta-profiles enriched for Eukaryotic Initiation Factor 2 (EIF2) signaling.
- Cardiovascular Disease pathways were uniquely downregulated in the CALR-PC variant, highlighting Pitx2 as a critical network hub.
Conclusions:
- An integrated algorithm of stem cell transcriptomes and bioinformatics can identify disease effectors.
- Stem cell transcriptomes serve as a molecular index for gene network robustness.
- This approach effectively decrypts gene expression changes in disrupted genomes for disease insight.
Background:
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.
Methods:
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.
Results:
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.
Conclusions:
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.
