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Conditional independence mapping of DIGE data reveals PDIA3 protein species as key nodes associated with muscle aerobic capacity

Burniston, JG, Kenyani, J, Gray, D, Guadagnin, E, Jarman, IH, Cobley, JN, Cuthbertson, DJ, Chen, Y-W, Wastling, JM, Lisboa, PJ, Koch, LG and Britton, SL (2014) Conditional independence mapping of DIGE data reveals PDIA3 protein species as key nodes associated with muscle aerobic capacity. Journal of Proteomics, 106. pp. 230-245. ISSN 1874-3919

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Abstract

Profiling of protein species is important because gene polymorphisms, splice variations and post-translational modifications may combine and give rise to multiple protein species that have different effects on cellular function. Two-dimensional gel electrophoresis is one of the most robust methods for differential analysis of protein species, but bioinformatic interrogation is challenging because the consequences of changes in the abundance of individual protein species on cell function are unknown and cannot be predicted. We conducted DIGE of soleus muscle from male and female rats artificially selected as either high- or low-capacity runners (HCR and LCR, respectively). In total 696 protein species were resolved and LC–MS/MS identified proteins in 337 spots. Forty protein species were differentially (P < 0.05, FDR < 10%) expressed between HCR and LCR and conditional independence mapping found distinct networks within these data, which brought insight beyond that achieved by functional annotation. Protein disulphide isomerase A3 emerged as a key node segregating with differences in aerobic capacity and unsupervised bibliometric analysis highlighted further links to signal transducer and activator of transcription 3, which were confirmed by western blotting. Thus, conditional independence mapping is a useful technique for interrogating DIGE data that is capable of highlighting latent features.

Item Type: Article
Uncontrolled Keywords: 0601 Biochemistry And Cell Biology
Subjects: Q Science > QA Mathematics
R Medicine > RC Internal medicine > RC1200 Sports Medicine
Divisions: Applied Mathematics
Sports & Exercise Sciences
Publisher: Elsevier
Related URLs:
Date Deposited: 22 Jan 2020 10:05
Last Modified: 22 Jan 2020 10:15
DOI or Identification number: 10.1016/j.jprot.2014.04.015
URI: http://researchonline.ljmu.ac.uk/id/eprint/4171

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