Many genetic risk variants for autism spectrum disorders (ASD) have been identified, but how these variants alter gene regulation to affect brain development and function remains to be fully understood. In addition to DNA-sequence mutations and epigenetic mechanisms, we are now beginning to appreciate that dynamic RNA modifications are also a critical mode of gene regulation. This emergent mechanism is known as ‘epitranscriptomics.’

N6-methyladenosine (m⁶A) is the most prevalent internal mRNA modification and is dynamically regulated via dedicated writer, eraser and reader proteins that affect RNA splicing, export, localization, translation efficiency and stability. m⁶A is particularly abundant within the brain and transcripts with human-specific m⁶A-tags are enriched in ASD risk genes, but its role in neural development, neuronal functions and brain disorders remain to be explored.

In this project, Hongjun Song’s laboratory will test the overarching hypothesis that epitranscriptomic m⁶A signaling regulates the metabolism of mRNAs, including ASD risk genes, in a cell-type-specific fashion in the nervous system. First, using both animal models of ASD and patient-derived induced pluripotent stem cells (iPSC), Song’s team will generate single-base resolution m⁶A maps and quantitative profiles of the percentage of transcripts per gene that are m⁶A tagged in four ASD-relevant neural cell types. Second, Song’s group will investigate the functional impact of m⁶A tagging on mRNA stability and protein translation in animal models of ASD and in iPSC-based 2-D and 3-D culture models. Third, the team will identify ASD risk variants that overlap with m⁶A loci, a subset of which will be subjected to functional studies using isogenic human iPSC-derived neural progenitors and neurons.

Together, these experiments will generate resources for the ASD research community, including a functionally annotated cell-type-specific m⁶A atlas. The study may also reveal fundamental epitranscriptomic mechanisms involved in brain development and novel insights into how ASD risk-associated genetic risk variants affect mRNA stability and protein translation.