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Gene signature-based mapping of immunological systems and diseases.

Liu H, Liu J, Toups M, Soos T, Arendt C - BMC Bioinformatics (2016)

Bottom Line: An in silico approach has been developed to characterize immune cell subsets and diseases based on the gene signatures that most differentiate them from other biological states.This modular 'biomap' reveals the linkages between different diseases and immune subtypes, and provides evidence for the presence of specific immunocyte subsets in mixed tissues.The over-represented genes in disease signatures of interest can be further investigated for their functions in both host defense and disease.

View Article: PubMed Central - PubMed

Affiliation: Bio-Innovation, Sanofi Global Biotherapeutics, 38 Sidney Street, Cambridge, MA, 02139, USA. hong.liu@sanofi.com.

ABSTRACT

Background: The immune system is multifaceted, structured by diverse components that interconnect using multilayered dynamic cellular processes. Genomic technologies provide a means for investigating, at the molecular level, the adaptations of the immune system in host defense and its dysregulation in pathological conditions. A critical aspect of intersecting and investigating complex datasets is determining how to best integrate genomic data from diverse platforms and heterogeneous sample populations to capture immunological signatures in health and disease.

Result: We focus on gene signatures, representing highly enriched genes of immune cell subsets from both diseased and healthy tissues. From these, we construct a series of biomaps that illustrate the molecular linkages between cell subsets from different lineages, the connectivity between different immunological diseases, and the enrichment of cell subset signatures in diseased tissues. Finally, we overlay the downstream genes of drug targets with disease gene signatures to display the potential therapeutic applications for these approaches.

Conclusion: An in silico approach has been developed to characterize immune cell subsets and diseases based on the gene signatures that most differentiate them from other biological states. This modular 'biomap' reveals the linkages between different diseases and immune subtypes, and provides evidence for the presence of specific immunocyte subsets in mixed tissues. The over-represented genes in disease signatures of interest can be further investigated for their functions in both host defense and disease.

No MeSH data available.


Related in: MedlinePlus

Similarity matrix of immune cell type gene signatures from human and mouse. Seventy-eight immune cell type gene signatures (20 human and 58 mouse) were paired against each other. Similarity was calculated by Fisher’s exact test of overlapping genes for each pair. Gene signatures were positioned according to their common cell lineage. Color represents the –log (P value of Fisher’s exact test), with red color indicating high similarity, and blue color indicating less/no similarity. Solid line black boxes group the gene signatures from the same lineage in either human or mouse, while dotted line black boxes group those from the same lineage between human and mouse. HSC hematopoietic stem cell, GN granulocyte, MO monocyte
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Fig1: Similarity matrix of immune cell type gene signatures from human and mouse. Seventy-eight immune cell type gene signatures (20 human and 58 mouse) were paired against each other. Similarity was calculated by Fisher’s exact test of overlapping genes for each pair. Gene signatures were positioned according to their common cell lineage. Color represents the –log (P value of Fisher’s exact test), with red color indicating high similarity, and blue color indicating less/no similarity. Solid line black boxes group the gene signatures from the same lineage in either human or mouse, while dotted line black boxes group those from the same lineage between human and mouse. HSC hematopoietic stem cell, GN granulocyte, MO monocyte

Mentions: Shay et al. [7] evaluated the conservation of genome-wide expression profiles of human vs. mouse cell types through correlation analysis, assessing the relatedness of matched lineages across species. A recent study by Godec et al. suggests that the lineage specific differences in human and mouse hematopoietic cells can be recapitulated by gene sets [8]. We sought to extend those approaches to formulate cell lineage- and subtype-specific gene sets that could serve as highly enriched ‘signatures’ in additional multivariate analyses. Two methods were evaluated to select these ‘signature’ gene sets, the first collecting the 2 % of genes with the highest expression values in a given subtype, and the second representing the 2 % of genes with the highest specific expression across all subtypes [9]. Gene sets generated from specific subtypes show high similarity across different cell lineages, but less conservation between human and mouse (data not shown). In contrast, gene sets generated across all subtypes are more conserved between species while showing more restricted similarity within the same cell lineage (Fig. 1 and Additional file 1: Figure S1). Since we were most interested in gene signatures with the capacity to discriminate between immune cell lineages, we focused our subsequent studies on gene sets generated across all subtypes.Fig. 1


Gene signature-based mapping of immunological systems and diseases.

Liu H, Liu J, Toups M, Soos T, Arendt C - BMC Bioinformatics (2016)

Similarity matrix of immune cell type gene signatures from human and mouse. Seventy-eight immune cell type gene signatures (20 human and 58 mouse) were paired against each other. Similarity was calculated by Fisher’s exact test of overlapping genes for each pair. Gene signatures were positioned according to their common cell lineage. Color represents the –log (P value of Fisher’s exact test), with red color indicating high similarity, and blue color indicating less/no similarity. Solid line black boxes group the gene signatures from the same lineage in either human or mouse, while dotted line black boxes group those from the same lineage between human and mouse. HSC hematopoietic stem cell, GN granulocyte, MO monocyte
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4836068&req=5

Fig1: Similarity matrix of immune cell type gene signatures from human and mouse. Seventy-eight immune cell type gene signatures (20 human and 58 mouse) were paired against each other. Similarity was calculated by Fisher’s exact test of overlapping genes for each pair. Gene signatures were positioned according to their common cell lineage. Color represents the –log (P value of Fisher’s exact test), with red color indicating high similarity, and blue color indicating less/no similarity. Solid line black boxes group the gene signatures from the same lineage in either human or mouse, while dotted line black boxes group those from the same lineage between human and mouse. HSC hematopoietic stem cell, GN granulocyte, MO monocyte
Mentions: Shay et al. [7] evaluated the conservation of genome-wide expression profiles of human vs. mouse cell types through correlation analysis, assessing the relatedness of matched lineages across species. A recent study by Godec et al. suggests that the lineage specific differences in human and mouse hematopoietic cells can be recapitulated by gene sets [8]. We sought to extend those approaches to formulate cell lineage- and subtype-specific gene sets that could serve as highly enriched ‘signatures’ in additional multivariate analyses. Two methods were evaluated to select these ‘signature’ gene sets, the first collecting the 2 % of genes with the highest expression values in a given subtype, and the second representing the 2 % of genes with the highest specific expression across all subtypes [9]. Gene sets generated from specific subtypes show high similarity across different cell lineages, but less conservation between human and mouse (data not shown). In contrast, gene sets generated across all subtypes are more conserved between species while showing more restricted similarity within the same cell lineage (Fig. 1 and Additional file 1: Figure S1). Since we were most interested in gene signatures with the capacity to discriminate between immune cell lineages, we focused our subsequent studies on gene sets generated across all subtypes.Fig. 1

Bottom Line: An in silico approach has been developed to characterize immune cell subsets and diseases based on the gene signatures that most differentiate them from other biological states.This modular 'biomap' reveals the linkages between different diseases and immune subtypes, and provides evidence for the presence of specific immunocyte subsets in mixed tissues.The over-represented genes in disease signatures of interest can be further investigated for their functions in both host defense and disease.

View Article: PubMed Central - PubMed

Affiliation: Bio-Innovation, Sanofi Global Biotherapeutics, 38 Sidney Street, Cambridge, MA, 02139, USA. hong.liu@sanofi.com.

ABSTRACT

Background: The immune system is multifaceted, structured by diverse components that interconnect using multilayered dynamic cellular processes. Genomic technologies provide a means for investigating, at the molecular level, the adaptations of the immune system in host defense and its dysregulation in pathological conditions. A critical aspect of intersecting and investigating complex datasets is determining how to best integrate genomic data from diverse platforms and heterogeneous sample populations to capture immunological signatures in health and disease.

Result: We focus on gene signatures, representing highly enriched genes of immune cell subsets from both diseased and healthy tissues. From these, we construct a series of biomaps that illustrate the molecular linkages between cell subsets from different lineages, the connectivity between different immunological diseases, and the enrichment of cell subset signatures in diseased tissues. Finally, we overlay the downstream genes of drug targets with disease gene signatures to display the potential therapeutic applications for these approaches.

Conclusion: An in silico approach has been developed to characterize immune cell subsets and diseases based on the gene signatures that most differentiate them from other biological states. This modular 'biomap' reveals the linkages between different diseases and immune subtypes, and provides evidence for the presence of specific immunocyte subsets in mixed tissues. The over-represented genes in disease signatures of interest can be further investigated for their functions in both host defense and disease.

No MeSH data available.


Related in: MedlinePlus