Single neuron analysis of aging associated changes in learning reveals escalating impairments in transcriptional plasticity

Molecular mechanisms underlying aging associated impairments in learning and long-term memory storage are poorly understood. Here we leveraged an identified motor neuron L7, mediating long-term sensitization of siphon-withdrawal reflex, a form of non-associative learning in sea slug Aplysia, to assess the impact of aging on transcriptional changes during learning. RNAseq analysis of single L7 motor neuron isolated following short-term or long-term sensitization training from 8,10 and 12 months old Aplysia corresponding to mature, late mature and senescent stages have identified progressive impairments in transcriptional plasticity during aging. Specifically, we uncover modulation of the expression of multiple lncRNAs, and mRNAs encoding transcription factors, regulators of translation, RNA methylation, and cytoskeletal rearrangements during learning and their deficits during aging. Our comparative gene expression analysis also revealed the recruitment of specific transcriptional changes in two other neurons, a motor neuron L11 and giant cholinergic neuron R2 whose roles in long-term sensitization were previously not known. Taken together, our analyses establish cell type specific escalating impairments in the expression of learning and LTM relevant components of transcriptomes during aging. Overall design: Single neuron (L7MN) isolated from long-term or short-term sensitized or untrained Aplysia that are of 8,10 and 12 months old were used for total RNAseq Analysis.

Identifier
Source https://data.blue-cloud.org/search-details?step=~0127846189B0E67C50D0B499E5EF7614ABEE6491E84
Metadata Access https://data.blue-cloud.org/api/collections/7846189B0E67C50D0B499E5EF7614ABEE6491E84
Provenance
Instrument NextSeq 500; ILLUMINA
Publisher Blue-Cloud Data Discovery & Access service; ELIXIR-ENA
Contributor Institute for Genome Sciences, Institute of Genome
Publication Year 2024
OpenAccess true
Contact blue-cloud-support(at)maris.nl
Representation
Discipline Marine Science