Molecular evolutionary patterns of NAD+/Sirtuin aging signaling pathway across taxa.
Uma GaurJianbo TuDiyan LiYue GaoTing LianBoyuan SunDeying YangXiaolan FanMingyao YangPublished in: PloS one (2017)
A deeper understanding of the conserved molecular mechanisms in different taxa have been made possible only because of the evolutionary conservation of crucial signaling pathways. In the present study, we explored the molecular evolutionary pattern of selection signatures in 51 species for 10 genes which are important components of NAD+/Sirtuin pathway and have already been directly linked to lifespan extension in worms and mice. Selection pressure analysis using PAML program revealed that MRPS5 and PPARGC1A were under significant constraints because of their functional significance. FOXO3a also displayed strong purifying selection. All three sirtuins, which were SIRT1, SIRT2 and SIRT6, displayed a great degree of conservation between taxa, which is consistent with the previous report. A significant evolutionary constraint is seen on the anti-oxidant gene, SOD3. As expected, TP53 gene was under significant selection pressure in mammals, owing to its major role in tumor progression. Poly-ADP-ribose polymerase (PARP) genes displayed the most sites under positive selection. Further 3D structural analysis of PARP1 and PARP2 protein revealed that some of these positively selected sites caused a change in the electrostatic potential of the protein structure, which may allow a change in its interaction with other proteins and molecules ultimately leading to difference in the function. Although the functional significance of the positively selected sites could not be established in the variants databases, yet it will be interesting to see if these sites actually affect the function of PARP1 and PARP2.
Keyphrases
- genome wide
- signaling pathway
- dna damage
- dna repair
- copy number
- dna methylation
- oxidative stress
- pi k akt
- genome wide identification
- ischemia reperfusion injury
- epithelial mesenchymal transition
- poor prognosis
- type diabetes
- induced apoptosis
- adipose tissue
- machine learning
- deep learning
- skeletal muscle
- metabolic syndrome
- endoplasmic reticulum stress
- climate change