High-throughput DNA sequencing is a powerful tool that can provide genome-wide and single-base resolution snapshots of biological activity in virtually any cell type. As sequencing technology has decreased in cost and become more accessible, it has been applied beyond DNA and today, RNA, epigenetic, and even protein profiling is possible. In this defense, will present two novel techniques that improve the efficiency of RNA sequencing and enable multiomic DNA methylation profiling. These advancements allow us to develop new insights in classically elusive biological systems, including non-model microbial samples and human germ cell development.
Highly efficient bacterial mRNA sequencing: One of the limitations for discovery and characterization in microbiomes is the relatively low efficiency of bacterial RNA sequencing compared with eukaryotic workflows. To improve the efficiently of mRNA sequencing in bacterial samples, we developed EMBR-seq (Enrichment of mRNA by Blocked rRNA) to specifically deplete abundant rRNA and minimize uninformative sequencing reads. EMBR-seq is scalable and successfully quantified the transcriptome from samples containing as little as 20 pg of total RNA. It was also applied to three different bacterial species and two co-cultures. From within co-cultures, the bacterial mRNA was enriched sufficiently to enable analysis of differentially expressed genes compared with monoculture conditions, resulting in some of the first observations of F. succinogenes strain UWB7 downregulating cellulolytic machinery in the presence of anaerobic gut fungi.
Simultaneous profiling of 5mC, 5hmC, and RNA: During early embryogenesis in mammals, the DNA modification 5-methyl cytosine (5mC) plays a critical role in establishing cell identity. To better understand the connection between DNA demethylation and gene expression during the maturation of primordial germ cells (PGCs) into gametes, we developed a method to capture 5mC, 5hmC, and RNA simultaneously in single cells (scMTH-seq). In stem cell-derived human PGC-like cells, scMTH-seq identified two distinct transcriptional groups, one of which was demethylating. Based on differential expression between the two groups, the genes DND1 and SOX15 were identified as putative drivers of PGC demethylation and maturation.