이전 사이트 이동

This dataset is single-cell RNA sequencing data generated from human cortical organoids with CRISPR-engineered heterozygous and homozygous mutations in USP15, modeling a patient-identified loss-of-function variant associated with autism spectrum disorder. Isogenic human induced pluripotent stem cells were edited using CRISPR/Cas9 and differentiated into cortical organoids under identical culture conditions. Single-cell transcriptomic profiling was performed at a late developmental stage to capture diverse neural progenitor and cortical neuron populations. The dataset includes quality-controlled gene expression matrices and cell-level metadata. Initial analyses indicate genotype-dependent differences in cellular composition and transcriptional states between heterozygous and homozygous USP15 mutant organoids.

genetic modification design

RNA-seq of total RNA

Isogenic human induced pluripotent stem cell (hiPSC) lines, including wild-type controls and CRISPR-engineered heterozygous and homozygous USP15 mutant lines, were maintained under feeder-free conditions and expanded prior to differentiation. Cortical organoids were generated from these hiPSCs using a standardized cerebral organoid differentiation protocol, starting from embryoid body formation followed by neural induction, Matrigel embedding, and long-term three-dimensional culture under continuous agitation. Organoids from all genotypes were differentiated and maintained in parallel under identical culture conditions to minimize technical variability. Organoids were cultured to a late developmental stage (day 107), at which time intact organoids were collected and processed immediately for single-cell RNA sequencing sample preparation.

Cortical organoids were enzymatically and mechanically dissociated into single-cell suspensions immediately prior to library preparation. RNA was captured at the single-cell level as part of the downstream single-cell RNA sequencing workflow without a separate bulk nucleic acid extraction step.

Single-cell RNA sequencing libraries were prepared using the BD Rhapsody Whole Transcriptome Analysis (WTA) Amplification Kit according to the manufacturer's protocol. Individual cells were barcoded, reverse-transcribed, and amplified to generate whole-transcriptome cDNA libraries suitable for high-throughput sequencing.

Prepared single-cell RNA sequencing libraries were sequenced on an Illumina NovaSeq platform using paired-end sequencing. Sequencing depth was sufficient to capture transcriptomic diversity across neural progenitor and neuronal populations.

Sequencing reads were aligned to the human reference genome (GRCh38), and gene-by-cell count matrices were generated. Ambient RNA contamination was corrected, and quality control filtering was applied to remove low-quality cells and predicted doublets. Filtered count matrices were normalized and scaled for downstream analyses. The deposited dataset consists of processed single-cell RNA-seq count matrices provided in MEX format (barcodes, features, and matrix files).