Furthermore, we found that the best sensitivity was obtained using 25 T poly-T primers (with and without -VN) (Supplementary Figs. Additional 42 ☌ incubation and plate-rotation did not significantly increase the RT efficiency (Supplementary Fig. One hour of incubation at 42 ☌ was necessary for the RT reaction. Maxima RTase showed the highest sensitivity, consistent with previous work 5 (Supplementary Fig. For in-cell RT, reverse transcriptase needs to be resistant to inhibitors that may carry over from fixation and complex intracellular environments. In 55 ☌-RT, the cells were sticky and hard to collect and load. We tested two RT temperatures (42 and 55 ☌), of which 42 ☌-RT had a higher cell recovery rate (Supplementary Fig. In the workflow of Microwell-seq 2.0, cells were first fixed and barcoded (round 1) in RT reactions using well-specific RT primers, corresponding to the given perturbations. The CT value was used for preliminary evaluation of different reaction conditions, and next-generation sequencing (NGS) was used for verification. We established a TaqMan qPCR-based optimization system to speed up the process and dramatically reduce the cost (Supplementary Fig. We carried out a series of optimizations to considerably improve the sensitivity of Microwell-seq 2.0. Yellow corresponds to high-expression levels purple and black correspond to low-expression levels. j A gene expression heatmap shows top differentially expressed genes for small-molecule combinations in i. i PAGA graph shows the potential cell transitions in perturbation of CHIR-99021 (CH), PD173074 (P1), PD0325901 (P0), and Retinoic acid (RA). PAGA plots show cell distribution after treatment with different small-molecule combinations ( h). Forty-eight small-molecule combinations were labeled in the graph generated by FA2 ( g). Five cell-type clusters were labeled in the graph generated by ForceAtlas2 (FA2) ( f). f− h PAGA graphs show the potential cell transitions in chemical perturbation. ![]() ![]() SPG, spermatogonia SPC-L/Z, spermatocyte-leptotene/zygotene SPC-Pach, spermatocyte-pachytene SPC-MD, spermatocyte-meiotic division SPC-Acr, spermatocyte-acrosomal phase rSpd, round spermatid eSpd, elongating spermatid. e t-SNE map of adult mouse testis analyzed by Microwell-seq 2.0. Only 0.69% (purple dots) are human–mouse mixed cells. d Scatter plot of human–mouse mix test using Microwell-seq 2.0. A summary of NGS was listed in Supplementary Table S6. Scatter plot of NGS data shows the transcript number versus the read number of each individual cell ( c). ![]() Data are means ± SD, n = 4 P values were calculated by Student’s t-test ns, no significance ** P < 0.01, *** P < 0.001 ( b). b, c qPCR and NGS analysis using three lysis buffers, respectively: Microwell-seq 1.0 lysis buffer, 2.0 lysis buffer (with 20% and 50% Formamide). S1).Ī Schematic diagram of Microwell-seq 2.0. Combining in-cell RT and Microwell-seq 1.0, we established Microwell-seq 2.0 for cost-effective and high-throughput HTS with single-cell transcriptional profiling (Fig. Our previous works of mouse cell atlas 7 and human cell landscape 8 showed that Microwell-seq 1.0 is a sensitive, robust, and cost-effective scRNA-seq technology with advantages of low batch effects and high cell-type compatibility. In addition, in-cell reverse transcription (RT) reactions can label cells using barcoded primers and significantly increase the throughput of scRNA-seq 4, 5, 6. For HTS, single-cell RNA sequencing (scRNA-seq) has been combined with several cell-labeling strategies, including cellular hashing (e.g., sci-Plex 2) and CRISPR/Cas9 (e.g., Perturb-Seq 3). In recent years, high-throughput single-cell sequencing technology has shown promise in overcoming these limitations in cell-based HTS. However, the readout of conventional HTS assays is restricted to gross phenotypes, including bulk transcriptional profiles, fluorescence signals, morphology, and viability, which cannot reveal subtle and heterogeneous changes in individual cells. Assays suitable for HTS should be sensitive, robust, and economical. Cell-based high-throughput screening (HTS) is an important strategy for discovering a new medicine 1.
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