bioRxivDevelopmental BiologyPreprint
Codon composition in human oocytes reveals age-associated defects in mRNA decay
Nehemiah S. AlvareziD, Pavla BrachovaiD, Lane K. ChristensoniD
Abstract
Oocytes from women of advanced reproductive age have lower developmental potential, yet the underlying mechanisms of this phenomena are incompletely understood. Oocyte maturation is dependent upon translational control of stored maternal mRNA that were synthesized during oocyte growth. We observed that GC content of mRNA was negatively associated with half-life in oocytes from reproductively young women (< 30 years), contrastingly directly with oocytes from reproductively aged women ([≥] 40 years) where mRNA half-lives were positively associated with GC nucleotide content. Additionally, we observed that mRNA half-lives were negatively associated with protein abundance in young oocytes, while GC content was positively associated with protein abundance in aged oocytes. Examination of codon composition during the GV-to-MII transition revealed that codons that facilitate rapid translation promoted mRNA stability and are considered optimal, while codons that slow translation destabilized mRNA, and are considered non-optimal. GC-containing codons were more optimal in reproductive aging, and also correlated positively with protein abundance. This study indicates that reproductive aging coincides with the stabilization of a subset of mRNA that have the potential to be over-translated during oocyte maturation, this is likely to lead to observed decreases in oocyte quality in older women. Because oocyte mRNA decay is translationally linked, this suggests that maternal aging causes defects in translation, which results in reduced translational efficiency and the retention of maternal mRNA that are normally degraded in oocytes from young women. In the case of oocytes, defects in translation can alter the RNA decay pathways and result in incorrect maternal mRNA dosage, which may negatively impact embryonic development.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 2
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