Project Summary / Abstract The hematopoietic tree contains cells of varying sizes, functions, and proliferation kinetics, and each cell type has a tightly regulated number of ribosomes. Ribosomal RNA (rRNA) forms the majority of ribosome mass, and is the most abundant cellular RNA, but rRNA/rDNA are often ignored in high-throughput studies due to a lack of suitable bioinformatic tools. In this proposal, we ask fundamental questions about rRNA regulation in human hematopoiesis by re-mapping existing datasets to custom genome assemblies generated by our lab. rDNA alleles are present in 200-600 repeat copies, and a subset is transcribed by Pol I into nascent rRNA. Transcription of rRNA is the rate-limiting step of ribosome biogenesis, and shows >10-fold variation across hematopoietic cell types. The mechanisms controlling this variation are understudied, and even though every high-throughput library contains rRNA/rDNA reads, standard mapping algorithms discard these reads. We recently generated custom genomes for rDNA mapping by masking rDNA fragments from human/mouse assemblies and adding a single ~45-kb reference rDNA sequence as a new “chromosome R”. We used this approach to map an atlas of hematopoietic transcription factor (TF)-rDNA binding encompassing ~2200 ChIP-Seq tracks for ~250 factors. We identified that the myeloid TF CEBPA binds rDNA and promotes rRNA transcription. Our overarching model is that rRNA is regulated across hematopoiesis through a combination of differential rDNA repeat activation and regulation by lineage-specific TFs. We will interrogate this model through novel analyses of existing and publicly-available human datasets. Specific Aim 1: We will quantify dynamics of rDNA copy activation in human hematopoiesis as follows: (A) Since inactive rDNA copies are heavily methylated, we will map whole genome bisulfite sequencing datasets to our custom genome to quantify rDNA methylation dynamics in the trajectory from HSCs to myeloid cells. (B) Since active rDNA copies show broad MNase-accessibility, we will use ATAC-Seq datasets to quantify changes in rDNA accessibility from HSCs to myeloid cells. Impact: Determining whether rDNA repeats are differentially activated at key transitions will guide studies on whether modulating rDNA methylation affects cell fate. Specific Aim 2: We will identify regulators of rRNA levels in human HSPCs as follows: (A) We will map HSPC single-cell (sc) RNA-Seq datasets to our custom genome to quantify 18S, 28S levels in addition to the broader transcriptome. We will assess whether rDNA-binding TFs, chromatin factors, or signatures of HSC quiescence correlate with rRNA levels. (B) We will map data from a Perturb-Seq study that combined CRISPR-interference screen with scRNA-Seq in K562 cells to profile mRNA effects of perturbations in ~10K genes. We will map this dataset to identify factors whose repression alters 18S, 28S levels. Impact: These studies will establish a single cell ribosome abundance ma...