Identification of Suitable Reference Genes for Lowlanders Exposed to High Altitude and Ladakhi Highlanders.
Vandana SharmaRajeev VarshneyNiroj Kumar SethyPublished in: High altitude medicine & biology (2022)
Sharma, Vandana, Rajeev Varshney, and Niroj Kumar Sethy. Identification of suitable reference genes for lowlanders exposed to high altitude and Ladakhi highlanders. High Alt Med Biol. 00:000-000, 2022. Background: Identifying a stable and reliable reference gene (RG) is a prerequisite for the unbiased and unambiguous analysis of gene expression data. It has become evident that conventionally used housekeeping genes such as beta-actin ( ACTB ), glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ), and peptidylprolyl Isomerase A ( PPIA ) exhibit varied expression patterns under hypoxia. Hence, the identification of stable RGs for humans exposed to hypobaric hypoxia can enhance the accuracy of gene expression studies by limiting the negligent use of random housekeeping genes. Methods: Using TaqMan™ array-based quantitative real-time quantitative polymerase chain reaction, we evaluated the expression of 32 commonly used human RGs among lowlanders at Delhi (altitude 216 m, SL), lowlanders at Leh (altitude 3,524 m) after 1 day (HA-D1) and 7 days (HA-D7), as well as indigenous Ladakhi highlanders at the same altitude. The expression stability of the RGs was evaluated using geNorm, NormFinder, BestKeeper, Delta CT method, and RefFinder algorithms. Results: Our studies identify TATA-box binding protein ( TBP ), proteasome 26S subunit, ATPase 4 ( PSMC4 ), and tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta ( YWHAZ ) as the most stable human RGs for normalizing human gene expression under hypobaric hypoxia. In addition, we report the combination of TBP and cyclin-dependent kinase inhibitor 1B ( CDKN1B ) as the most stable RG for studying lowlander gene expression during high-altitude exposure. In contrast, RPL30 and 18S exhibited maximum variation across study groups and were identified as the least stable RGs.
Keyphrases
- gene expression
- endothelial cells
- binding protein
- bioinformatics analysis
- genome wide
- dna methylation
- poor prognosis
- genome wide identification
- induced pluripotent stem cells
- machine learning
- pluripotent stem cells
- computed tomography
- high resolution
- magnetic resonance
- genome wide analysis
- cell cycle
- magnetic resonance imaging
- high throughput
- mass spectrometry
- case control
- signaling pathway
- cell death
- artificial intelligence
- amino acid
- real time pcr
- pi k akt