Journal
JOURNAL OF PROTEOME RESEARCH
Volume 15, Issue 3, Pages 1011-1022Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.5b01080
Keywords
network medicine; data integration; complex disease; spermatogenesis; Y chromosome; ribosomal proteins; AZF deletion; GWAS
Categories
Funding
- Institute for Research in Fundamental Sciences (IPM) Grant [BS-1393-1-07]
- [BS-1392-1-11]
- [BS-1394-01-08]
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Pinpointing causal genes for spermatogenic failure (SpF) on the Y chromosome has been an ever daunting challenge with setbacks during the past decade. Since complex diseases result from the interaction of multiple genes and also display considerable missing heritability, network analysis is more likely to explicate an etiological molecular basis. We therefore took a network medicine approach by integrating interactome (protein protein interaction (PPI)) and transcriptome data to reconstruct a Y-centric SpF network. Two sets of seed genes (Y genes and SpF-implicated genes (SIGs)) were used for network reconstruction. Since no PPI was observed among Y genes, we identified their common immediate interactors. Interestingly, 81% (N = 175) of these interactors not only interacted directly with SIGs, but also they were enriched for differentially expressed genes (89.6%; N = 43). The SpF network, formed mainly by the dys-regulated interactors and the two seed gene sets, comprised three modules enriched for ribosomal proteins and nuclear receptors for sex hormones. Ribosomal proteins generally showed significant dys-regulation with RPL39L, thought to be expressed at the onset of spermatogenesis, strongly down-regulated. This network is the first global PPI network pertaining to severe SpF and if experimentally validated on independent data sets can lead to more accurate diagnosis and potential fertility recovery of patients.
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