Comparative single cell epigenomic analysis of gene regulatory programs in the rodent and primate motor cortex [Macaque]
Sequence divergence of cis-regulatory elements drives species-specific traits, but how this manifests in the evolution of the neocortex at the molecular and cellular level remains to be elucidated. We investigated the gene regulatory programs in the primary motor cortex of human, macaque, marmoset, and mouse with single-cell multiomics assays, generating gene expression, chromatin accessibility, DNA methylome, and chromosomal conformation profiles from a total of over 180,000 cells. For each modality, we determined species-specific, divergent, and conserved gene expression and epigenetic features at multiple levels. We find that cell type-specific gene expression evolves more rapidly than broadly expressed genes and that epigenetic status at distal candidate cis-regulatory elements (cCREs) evolves faster than promoters. Strikingly, transposable elements (TEs) contribute to nearly 80% of the human-specific cCREs in cortical cells. Through machine learning, we develop sequence-based predictors of cCREs in different species and demonstrate that the genomic regulatory syntax is highly preserved from rodents to primates. Lastly, we show that epigenetic conservation combined with sequence similarity helps uncover functional cis-regulatory elements and enhances our ability to interpret genetic variants contributing to neurological disease and traits. Overall design: The motor cortex of  Macaque were disected and nuclei were prepared for library preparation. In-situ 3C treatment was done during the nuclei preparation that allows capturing the chromatin conformation modality as described previously. These steps were carried out using the Arima-3C BETA Kit (Arima Genomics). The nuclei were isolated and sorted into 384-well plates using previous methods. Briefly, single-nuclei were stained with AlexaFluor488-conjugated anti-NeuN antibody (MAB377X, Millipore) and Hoechst 33342 (62249, ThermoFisher) followed by FANS using a BD Influx sorter with single-cell (1 drop single) mode.  The snm3C-seq samples followed the library preparation protocol detailed previously. This protocol has been automated using the Beckman Biomek i7 instrument to facilitate large-scale applications. The snm3C-seq libraries were sequenced on an Illumina NovaSeq 6000 instrument, utilizing one S4 flow cell per 16 384-well plates and employing a 150 bp paired-end mode. This study includes samples in the following series: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE241339 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE219006 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE219113 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE219198 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE219263