A prenatal window for enhancing spatial resolution of cortical barrel maps
Precise mapping of peripheral inputs onto cortical areas is essential for accurate sensory processing. In the mouse primary somatosensory cortex, mystacial whiskers correspond to large, well-defined barrels, while upper lip whiskers form smaller, less distinct barrels. These differences are traditionally attributed to variations in whisker input type and receptor density, but prenatal activity and transcriptional programs also impact somatosensory map development independently of sensory experience. Here, we demonstrate that prenatal ablation of mystacial whiskers leads to a remapping of cortical territories, enhancing the functional and anatomical definition of upper lip whisker barrels. This reorganization occurs without altering peripheral receptor types. Instead, thalamic neurons that receive upper lip inputs adopt a mystacial-like transcriptional profile. Our findings unveil a regulated prenatal mechanism in the thalamus that ensures sufficient cortical barrel size and spatial resolution for sensory processing, irrespective of peripheral receptor type or density, highlighting a critical developmental process in sensory mapping. Overall design: Bulk RNA sequencing was performed on the postero-medial barrel subfield (PMBSF) and antero-lateral barrel subfield (ALBSF) territories of the thalamic ventroposterior medial (VPM) nucleus in control and embWPC P0 pups. The PMBSF corresponds to the whisker pad input-receiving VPM (wpVPM), while the ALBSF corresponds to the upper-lip input-receiving VPM (ulVPM). The bulk tissue was microdissected (five brains were pooled for each sample) and the total RNA was extracted as in the previous publication (Moreno-Juan et al., 2017). Library construction and sequencing were performed at Novogene Co. Ltd. Genomics core facility (Cambridge, UK). The library was checked with Qubit and real-time PCR for quantification and bioanalyzer for size distribution detection. Libraries were pooled and sequenced in 2x150bp paired-end mode on a S4 flowcell in the Illumina Novaseq6000 platform. A minimum of 40 million reads were generated from each library. The RNA-seq analysis were performed as previously described (Herrero-Navarro et. al. 2021) with minor modifications: quality control of the raw data was performed with FastQC (v.0.11.9). RNA-seq reads were mapped to the Mouse genome (GRCm39) using STAR (v2.7.9a) and SAM/BAM files were further processed using SAMtools (v1.15). Aligned reads were counted and assigned to genes using Ensembl release 104 gene annotation and FeatureCounts, Subread (v2.0.1). Normalization of read counts and differential expression analyses were performed using DESeq2 (v1.32), Bioconductor (v3.15) in the R statistical computing and graphics platform (v4.2.2 “Innocent and Trusting”).