The combination of single-cell transcriptomics with mitochondrial DNA variant detection can be used to establish lineage relationships in primary human cells, but current methods are not scalable to interrogate complex tissues. A team led by researchers at the Broad Institute of MIT and Harvard have combined common 3′ single-cell RNA-sequencing protocols with mitochondrial transcriptome enrichment to increase coverage by more than 50-fold, enabling high-confidence mutation detection. The method successfully identifies skewed immune-cell expansions in primary human clonal hematopoiesis.
Targeted enrichment of mitochondrial transcripts
enables discrimination between genetic clones
a, Schematic showing the procedures for lineage inference from single-cell transcriptomes using MAESTER. Following mRNA capture and whole-transcriptome amplification, part of the cDNA is used for standard scRNA-seq, and another part is used for PCR-based enrichment of mitochondrial transcripts. The 300-bp sequencing reads maximize mitochondrial genome coverage to call variants. b, Diagram depicting the circular mitochondrial genome with annotated features. The green triangles indicate where MAESTER primers bind. c, Barplot showing the number of mtDNA variants that were detected by ATAC-seq (blue bars) and their recovery by MAESTER (red line). DNA (ATAC) and RNA (MAESTER) were acquired from the same K562 cells using the 10x multiome workflow. d, Barplot showing coverage of the mitochondrial genome with and without amplification from Seq-Well libraries using MAESTER. Mean coverage of 2,482 K562 and BT142 cells is shown. Each transcript (UMI) was sequenced at least three times. e, UMAPs showing the detection of cell type–specific expression of FTL and MET genes from scRNA-seq (top) and homoplasmic mtDNA variants from MAESTER (bottom). f, Heatmap depicting separation of 1,523 K562 and BT142 cells (columns) based on six mtDNA variants (rows). Cell-type annotation from scRNA-seq is shown (top). g, Correlation matrix showing cell similarity based on the allele frequencies of six homoplasmic variants (rows and columns depict 1,523 cells). Unsupervised clustering identified two clusters that correlate with cell annotations from scRNA-seq. h, Heatmap showing variant allele frequency (VAF) of 21 mtDNA variants detected by MAESTER (rows) for 588 K562 cells (columns, 44.4% of all K562 cells) with informative variants. Homoplasmic K562 variant 2141T>C is shown for comparison. Heatmap is organized by clonal structure (Methods). For e–h, only cells with more than threefold coverage of the indicated variants are shown. SMART and NXT are specific primer binding sequences; SA, streptavidin.