Chromosome-wise Protein Interaction Patterns and Their Impact on Functional Implications of Large-Scale Genomic Aberrations

Abstract

Gene copy-number changes influence phenotypes through gene-dosage alteration and subsequent changes of protein complex stoichiometry. Human trisomies where gene copy numbers are increased uniformly over entire chromosomes provide generic cases for studying these relationships. In most trisomies, gene and protein level alterations have fatal consequences. We used genome-wide protein-protein interaction data to identify chromosome-specific patterns of protein interactions. We found that some chromosomes encode proteins that interact infrequently with each other, chromosome 21 in particular. We combined the protein interaction data with transcriptome data from human brain tissue to investigate how this pattern of global interactions may affect cellular function. We identified highly connected proteins that also had coordinated gene expression. These proteins were associated with important neurological functions affecting the characteristic phenotypes for Down syndrome and have previously been validated in mouse knockout experiments. Our approach is general and applicable to other gene-dosage changes, such as arm-level amplifications in cancer.

Disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million Danish patients

“…2 contain multiple diagnoses from chapter X (Diseases of the respiratory system) and chapter XVII (Congenital malformations, deformations, and chromosomal abnormalities), whereas the disease trajectories contain no diagnosis from chapter II (Neoplasms) 29 , 30 . These findings may very well relate to the phenotypic effect of gene copy-number, which is rather profound in a trisomy like DS 31 . Moreover, the disease trajectory network topology shown in Fig.…”

Glycolytic repression and reduced GLP-1 secretion by active Farnesoid X Receptor in enteroendocrine L cells achieved via PKLR

“…PKLR, as the only essential enzyme, showed a decrease in co-expression with the other glycolytic enzymes in FXR-activated L cells relative to control. A decrease in co-expression suggests a decrease in activity [19][20][21][22][23] .…”

“…To calculate the co-expression of two arbitrary proteins, we used an approach described previously [19][20][21][22]26 . If proteins x and y were present in the same protein complex and had a physical interaction according to InWeb_IM, we calculated the gene expression correlation between protein x and y using the Pearson's correlation coefficient (PCC xy ):…”

“…In FXR-activated L cells, three glycolytic enzymes show deviating expression patterns from the overall glycolytic coexpression pattern: ALDOB, ENO3 and PKLR (Figure 3C). Reduction in coexpression is a predictor of reduced functional activity [19][20][21][22][23] , which may cause the glycolytic repression. However, the reduced co-expression of ALDOB and ENO3 likely has no functional impact, as correspondingly ALDOA and ENO1-2, can catalyze the same glycolytic steps (Figure 3C, right).…”

“…The relative expression of the protein units in a complex, its stoichiometry, can then be used to assess the activity of each protein complex. High gene co-expression, which infers a balanced protein complex stoichiometry, is an indicator of activity or importance [19][20][21][22][23] . Using a rigorous and untargeted selection scheme, we identify the most robustly co-expressed protein complexes and thus those that are the most active in a specific context.…”