Targeted rRNA depletion enables efficient mRNA sequencing in diverse bacterial species and complex co-cultures.

Microbes present one of the most diverse sources of biochemistry in nature, and mRNA sequencing provides a comprehensive view of this biological activity by quantitatively measuring microbial transcriptomes. However, efficient mRNA capture for sequencing presents significant challenges in prokaryotes as mRNAs are not poly-adenylated and typically make up less than 5% of total RNA compared with rRNAs that exceed 80%. Recently developed methods for sequencing bacterial mRNA typically rely on depleting rRNA by tiling large probe sets against rRNAs; however, such approaches are expensive, time-consuming, and challenging to scale to varied bacterial species and complex microbial communities.

Integrated single-cell sequencing of 5-hydroxymethylcytosine and genomic DNA using scH&G-seq.

The asymmetric distribution of 5-hydroxymethylcytosine (5hmC) between two DNA strands of a chromosome enables endogenous reconstruction of cellular lineages at an individual-cell-division resolution. Further, when integrated with data on genomic variants to infer clonal lineages, this combinatorial information accurately reconstructs larger lineage trees. Here, we provide a detailed protocol for single-cell 5-hydroxymethylcytosine and genomic DNA sequencing (scH&G-seq) to simultaneously quantify 5hmC and genomic DNA from the same cell to reconstruct lineage trees at a single-cell-division resolution.

A probabilistic framework for cellular lineage reconstruction using integrated single-cell 5-hydroxymethylcytosine and genomic DNA sequencing.

Lineage reconstruction is central to understanding tissue development and maintenance. To overcome the limitations of current techniques that typically reconstruct clonal trees using genetically encoded reporters, we report scPECLR, a probabilistic algorithm to endogenously infer lineage trees at a single-cell-division resolution by using 5-hydroxymethylcytosine (5hmC). When applied to 8-cell pre-implantation mouse embryos, scPECLR predicts the full lineage tree with greater than 95% accuracy.

Efficient and cost-effective bacterial mRNA sequencing from low input samples through ribosomal RNA depletion.

Background: RNA sequencing is a powerful approach to quantify the genome-wide distribution of mRNA molecules in a population to gain deeper understanding of cellular functions and phenotypes. However, unlike eukaryotic cells, mRNA sequencing of bacterial samples is more challenging due to the absence of a poly-A tail that typically enables efficient capture and enrichment of mRNA from the abundant rRNA molecules in a cell. Moreover, bacterial cells frequently contain 100-fold lower quantities of RNA compared to mammalian cells, which further complicates mRNA sequencing from non-cultivable and non-model bacterial species.