![The transcriptome and proteome of platelets, neutrophils, monocytes, and CD4 lymphocytes. For all panels, log2 fold change (log2 fold change [logFC]) for gene expression (by RNA-seq) and protein abundance (by MS) was determined by log2-transforming the ratio of the means of individual normalized values of the 5 patients with GPS and 5 control subjects. Negative values represent genes/proteins that are reduced in GPS and vice versa. The threshold for differential abundance/expression was determined by each experimental method and the corresponding analysis used (supplemental Methods). (A) Bar chart showing differentially expressed genes by RNA-seq (left) and differentially abundant proteins by MS (right). The y-axis represents the absolute number of genes or proteins determined by each method, and negative numbers represent significant reduction in GPS cells and vice versa. The most significant GO cellular component terms for the differentially less abundant proteins of each of the cell types is illustrated in the “Proteins” panel. (B) For each individual, the protein abundance was calculated for each of the 9 proteins that are differentially less abundant in at least 3 types of cells and averaged across all of the cells. The results were scaled from −1 to 1 and plotted as a dendrogram with heatmap, such that positive (dark blue) and negative (yellow) values represent higher and lower protein abundance, respectively. Hierarchical clustering was applied by using the complete linkage method, and dissimilarity between rows and columns was based on the Euclidean distance. Each column represents an individual GPS patient or control subject. (C) The comparison of gene expression and protein abundance of platelets (GPS vs control) highlights the high proportion of “alpha-granules” and “releasate” proteins (in red and orange, respectively), which are significantly diminished in GPS platelets at the protein level (P < 2.2 × 10−16), and also shows that proteins normally resident in neutrophil granules (blue) are increased in GPS platelets. (D) The comparison of gene expression and protein abundance of neutrophils (GPS vs control) separated vertically by subcellular localization shows a significantly lower abundance of specific and gelatinase granule proteins in GPS neutrophils (P < 1.3 × 10−8 and < 2.2 × 10−16, respectively).](https://ash.silverchair-cdn.com/ash/content_public/journal/blood/136/17/10.1182_blood.2019004776/1/bloodbld2019004776f3.png?Expires=1735803929&Signature=mnbQXiikAsuIfGQgmaU65QBFKpcQAAjclN8DlXH6TgL4zq64ACLCMCQHsuj24lRffHrmoOKeFLPQXKhLKcRLLJqd92LkwUwiVRtKBE7AK6Y3Yyx7p~1oo708iehgihf1tU1Mo0a6pvk2VzB~6rkE3Lg~w-5lVUZG-4vGYjS~DbXaATf5pshbB68tcmY-w2ppQhO8GUQculWgsWStzqSHmMewoAU2pp~e8BC1EAY5GHehHMc5h2Xqv5V4G2Ol9rFcnBtdDuRYjP-UDolffpqtx7WnfmWR6X3bow0BwXPM4a7~hrFOj-72adwT7eEz3R6AhimMKrsA8C97zac5OLRQiQ__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA)
The transcriptome and proteome of platelets, neutrophils, monocytes, and CD4 lymphocytes. For all panels, log2 fold change (log2 fold change [logFC]) for gene expression (by RNA-seq) and protein abundance (by MS) was determined by log2-transforming the ratio of the means of individual normalized values of the 5 patients with GPS and 5 control subjects. Negative values represent genes/proteins that are reduced in GPS and vice versa. The threshold for differential abundance/expression was determined by each experimental method and the corresponding analysis used (supplemental Methods). (A) Bar chart showing differentially expressed genes by RNA-seq (left) and differentially abundant proteins by MS (right). The y-axis represents the absolute number of genes or proteins determined by each method, and negative numbers represent significant reduction in GPS cells and vice versa. The most significant GO cellular component terms for the differentially less abundant proteins of each of the cell types is illustrated in the “Proteins” panel. (B) For each individual, the protein abundance was calculated for each of the 9 proteins that are differentially less abundant in at least 3 types of cells and averaged across all of the cells. The results were scaled from −1 to 1 and plotted as a dendrogram with heatmap, such that positive (dark blue) and negative (yellow) values represent higher and lower protein abundance, respectively. Hierarchical clustering was applied by using the complete linkage method, and dissimilarity between rows and columns was based on the Euclidean distance. Each column represents an individual GPS patient or control subject. (C) The comparison of gene expression and protein abundance of platelets (GPS vs control) highlights the high proportion of “alpha-granules” and “releasate” proteins (in red and orange, respectively), which are significantly diminished in GPS platelets at the protein level (P < 2.2 × 10−16), and also shows that proteins normally resident in neutrophil granules (blue) are increased in GPS platelets. (D) The comparison of gene expression and protein abundance of neutrophils (GPS vs control) separated vertically by subcellular localization shows a significantly lower abundance of specific and gelatinase granule proteins in GPS neutrophils (P < 1.3 × 10−8 and < 2.2 × 10−16, respectively).