bioRxivGenomicsPreprint
Genetic architecture of the red blood cell proteome in genetically diverse mice reveals central role of hemoglobin beta cysteine redox status in maintaining circulating glutathione pools
Gregory R. KeeleiD, Monika DzieciątkowskaiD, Ariel M. HayiD, Matthew J. VincentiD, Callan O’ConnoriD, Daniel StephensoniD, Julie A. ReisziD, Travis G. NemkoviD, Kirk Charles HanseniD, Grier P. PageiD, James C. ZimringiD, Gary A. ChurchilliD, Angelo D’AlessandroiD
Abstract
Red blood cells (RBCs) transport oxygen but accumulate oxidative damage over time, reducing function in vivo and during storage--critical for transfusions. To explore genetic influences on RBC resilience, we profiled proteins, metabolites, and lipids from fresh and stored RBCs obtained from 350 genetically diverse mice. Our analysis identified over 6,000 quantitative trait loci (QTL). Compared to other tissues, prevalence of trans genetic effects over cis reflects the absence of de novo protein synthesis in anucleated RBCs. QTL hotspots at Hbb, Hba, Mon1a, and storage-specific Steap3 linked ferroptosis to hemolysis. Proteasome components clustered at multiple loci, underscoring the importance of degrading oxidized proteins. Post-translational modifications (PTMs) mapped predominantly to hemoglobins, particularly cysteine residues. Loss of reactive C93 in humanized mice (HBB C93A) disrupted redox balance, affecting glutathione pools, protein glutathionylation, and redox PTMs. These findings highlight genetic regulation of RBC oxidation, with implications for transfusion biology and oxidative stress-dependent hemolytic disorders. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/640676v1_ufig1.gif" ALT="Figure 1"> View larger version (98K): org.highwire.dtl.DTLVardef@14a3cc2org.highwire.dtl.DTLVardef@daf8b4org.highwire.dtl.DTLVardef@1fe306forg.highwire.dtl.DTLVardef@11de734_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: mouse
- assay: proteomics
- assay: metabolomics
- assay: metagenomics
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: benchmarking
- approach: statistical model
- Citations
- 3
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