Nature Biotechnology

P?ll Melsted, A. Sina Booeshaghi, Lauren Liu, Fan Gao, Lambda Lu, Kyung Hoi (Joseph) Min, Eduardo da Veiga Beltrame, Kristj?n Eldj?rn Hj?rleifsson, Jase Gehring & Lior Pachter

doi : 10.1038/s41587-021-00870-2

Nature Biotechnology volume 39, pages813–818 (2021)

We describe a workflow for preprocessing of single-cell RNA-sequencing data that balances efficiency and accuracy. Our workflow is based on the kallisto and bustools programs, and is near optimal in speed with a constant memory requirement providing scalability for arbitrarily large datasets. The workflow is modular, and we demonstrate its flexibility by showing how it can be used for RNA velocity analyses.

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Single-cell CUT&Tag analysis of chromatin modifications in differentiation and tumor progression

Steven J. Wu, Scott N. Furlan, Anca B. Mihalas, Hatice S. Kaya-Okur, Abdullah H. Feroze, Samuel N. Emerson, Ye Zheng, Kalee Carson, Patrick J. Cimino, C. Dirk Keene, Jay F. Sarthy, Raphael Gottardo, Kami Ahmad, Steven Henikoff & Anoop P. Patel

doi : 10.1038/s41587-021-00865-z

Nature Biotechnology volume 39, pages819–824 (2021)

Methods for quantifying gene expression1 and chromatin accessibility2 in single cells are well established, but single-cell analysis of chromatin regions with specific histone modifications has been technically challenging. In this study, we adapted the CUT&Tag method3 to scalable nanowell and droplet-based single-cell platforms to profile chromatin landscapes in single cells (scCUT&Tag) from complex tissues and during the differentiation of human embryonic stem cells. We focused on profiling polycomb group (PcG) silenced regions marked by histone H3 Lys27 trimethylation (H3K27me3) in single cells as an orthogonal approach to chromatin accessibility for identifying cell states. We show that scCUT&Tag profiling of H3K27me3 distinguishes cell types in human blood and allows the generation of cell-type-specific PcG landscapes from heterogeneous tissues. Furthermore, we used scCUT&Tag to profile H3K27me3 in a patient with a brain tumor before and after treatment, identifying cell types in the tumor microenvironment and heterogeneity in PcG activity in the primary sample and after treatment.

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Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues

Marek Bartosovic, Mukund Kabbe & Gonçalo Castelo-Branco

doi : 10.1038/s41587-021-00869-9

Nature Biotechnology volume 39, pages825–835 (2021)

In contrast to single-cell approaches for measuring gene expression and DNA accessibility, single-cell methods for analyzing histone modifications are limited by low sensitivity and throughput. Here, we combine the CUT&Tag technology, developed to measure bulk histone modifications, with droplet-based single-cell library preparation to produce high-quality single-cell data on chromatin modifications. We apply single-cell CUT&Tag (scCUT&Tag) to tens of thousands of cells of the mouse central nervous system and probe histone modifications characteristic of active promoters, enhancers and gene bodies (H3K4me3, H3K27ac and H3K36me3) and inactive regions (H3K27me3). These scCUT&Tag profiles were sufficient to determine cell identity and deconvolute regulatory principles such as promoter bivalency, spreading of H3K4me3 and promoter–enhancer connectivity. We also used scCUT&Tag to investigate the single-cell chromatin occupancy of transcription factor OLIG2 and the cohesin complex component RAD21. Our results indicate that analysis of histone modifications and transcription factor occupancy at single-cell resolution provides unique insights into epigenomic landscapes in the central nervous system.

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Comprehensive profiling of circular RNAs with nanopore sequencing and CIRI-long

Jinyang Zhang, Lingling Hou, Zhenqiang Zuo, Peifeng Ji, Xiaorong Zhang, Yuanchao Xue & Fangqing Zhao

doi : 10.1038/s41587-021-00842-6

Nature Biotechnology volume 39, pages836–845 (2021)

Reconstructing the sequence of circular RNAs (circRNAs) from short RNA sequencing reads has proved challenging given the similarity of circRNAs and their corresponding linear messenger RNAs. Previous sequencing methods were unable to achieve high-throughput detection of full-length circRNAs. Here we describe a protocol for enrichment and full-length sequencing of circRNA isoforms using nanopore technology. Circular reverse transcription and size selection achieves a 20-fold higher enrichment of circRNAs from total RNA compared to previous methods. We developed an algorithm, called circRNA identifier using long-read sequencing data (CIRI-long), to reconstruct the sequence of circRNAs. The workflow was validated with simulated data and by comparison to Illumina sequencing as well as quantitative real-time RT–PCR. We used CIRI-long to analyze adult mouse brain samples and systematically profile circRNAs, including mitochondria-derived and transcriptional read-through circRNAs. We identified a new type of intronic self-ligated circRNA that exhibits special splicing and expression patterns. Our method takes advantage of nanopore long reads and enables unbiased reconstruction of full-length circRNA sequences.

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Ultra-fast proteomics with Scanning SWATH

Christoph B. Messner, Vadim Demichev, Nic Bloomfield, Jason S. L. Yu, Matthew White, Marco Kreidl, Anna-Sophia Egger, Anja Freiwald, Gordana Ivosev, Fras Wasim, Aleksej Zelezniak, Linda Jürgens, Norbert Suttorp, Leif Erik Sander, Florian Kurth, Kathryn S. Lilley, Michael Mülleder, Stephen Tate & Markus Ralser

doi : 10.1038/s41587-021-00860-4

Nature Biotechnology volume 39, pages846–854 (2021)

Accurate quantification of the proteome remains challenging for large sample series and longitudinal experiments. We report a data-independent acquisition method, Scanning SWATH, that accelerates mass spectrometric (MS) duty cycles, yielding quantitative proteomes in combination with short gradients and high-flow (800?µl?min–1) chromatography. Exploiting a continuous movement of the precursor isolation window to assign precursor masses to tandem mass spectrometry (MS/MS) fragment traces, Scanning SWATH increases precursor identifications by ~70% compared to conventional data-independent acquisition (DIA) methods on 0.5–5-min chromatographic gradients. We demonstrate the application of ultra-fast proteomics in drug mode-of-action screening and plasma proteomics. Scanning SWATH proteomes capture the mode of action of fungistatic azoles and statins. Moreover, we confirm 43 and identify 11?new plasma proteome biomarkers of COVID-19 severity, advancing patient classification and biomarker discovery. Thus, our results demonstrate a substantial acceleration and increased depth in fast proteomic experiments that facilitate proteomic drug screens and clinical studies.

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Monitoring deep-tissue oxygenation with a millimeter-scale ultrasonic implant

Soner Sonmezoglu, Jeffrey R. Fineman, Emin Maltepe & Michel M. Maharbiz

doi : 10.1038/s41587-021-00866-y

Nature Biotechnology volume 39, pages855–864 (2021)

Vascular complications following solid organ transplantation may lead to graft ischemia, dysfunction or loss. Imaging approaches can provide intermittent assessments of graft perfusion, but require highly skilled practitioners and do not directly assess graft oxygenation. Existing systems for monitoring tissue oxygenation are limited by the need for wired connections, the inability to provide real-time data or operation restricted to surface tissues. Here, we present a minimally invasive system to monitor deep-tissue O2 that reports continuous real-time data from centimeter-scale depths in sheep and up to a 10-cm depth in ex vivo porcine tissue. The system is composed of a millimeter-sized, wireless, ultrasound-powered implantable luminescence O2 sensor and an external transceiver for bidirectional data transfer, enabling deep-tissue oxygenation monitoring for surgical or critical care indications.

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Variability within rare cell states enables multiple paths toward drug resistance

Benjamin L. Emert, Christopher J. Cote, Eduardo A. Torre, Ian P. Dardani, Connie L. Jiang, Naveen Jain, Sydney M. Shaffer & Arjun Raj

doi : 10.1038/s41587-021-00837-3

Nature Biotechnology volume 39, pages865–876 (2021)

Molecular differences between individual cells can lead to dramatic differences in cell fate, such as death versus survival of cancer cells upon drug treatment. These originating differences remain largely hidden due to difficulties in determining precisely what variable molecular features lead to which cellular fates. Thus, we developed Rewind, a methodology that combines genetic barcoding with RNA fluorescence in situ hybridization to directly capture rare cells that give rise to cellular behaviors of interest. Applying Rewind to BRAFV600E melanoma, we trace drug-resistant cell fates back to single-cell gene expression differences in their drug-naive precursors (initial frequency of ~1:1,000–1:10,000 cells) and relative persistence of MAP kinase signaling soon after drug treatment. Within this rare subpopulation, we uncover a rich substructure in which molecular differences among several distinct subpopulations predict future differences in phenotypic behavior, such as proliferative capacity of distinct resistant clones after drug treatment. Our results reveal hidden, rare-cell variability that underlies a range of latent phenotypic outcomes upon drug exposure.

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Robust integration of multiple single-cell RNA sequencing datasets using a single reference space

Yang Liu, Tao Wang, Bin Zhou & Deyou Zheng

doi : 10.1038/s41587-021-00859-x

Nature Biotechnology volume 39, pages877–884 (2021)

In many biological applications of single-cell RNA sequencing (scRNA-seq), an integrated analysis of data from multiple batches or studies is necessary. Current methods typically achieve integration using shared cell types or covariance correlation between datasets, which can distort biological signals. Here we introduce an algorithm that uses the gene eigenvectors from a reference dataset to establish a global frame for integration. Using simulated and real datasets, we demonstrate that this approach, called Reference Principal Component Integration (RPCI), consistently outperforms other methods by multiple metrics, with clear advantages in preserving genuine cross-sample gene expression differences in matching cell types, such as those present in cells at distinct developmental stages or in perturbated versus control studies. Moreover, RPCI maintains this robust performance when multiple datasets are integrated. Finally, we applied RPCI to scRNA-seq data for mouse gut endoderm development and revealed temporal emergence of genetic programs helping establish the anterior–posterior axis in visceral endoderm.

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A unified haplotype-based method for accurate and comprehensive variant calling

Daniel P. Cooke, David C. Wedge & Gerton Lunter

doi : 10.1038/s41587-021-00861-3

Nature Biotechnology volume 39, pages885–892 (2021)

Almost all haplotype-based variant callers were designed specifically for detecting common germline variation in diploid populations, and give suboptimal results in other scenarios. Here we present Octopus, a variant caller that uses a polymorphic Bayesian genotyping model capable of modeling sequencing data from a range of experimental designs within a unified haplotype-aware framework. Octopus combines sequencing reads and prior information to phase-called genotypes of arbitrary ploidy, including those with somatic mutations. We show that Octopus accurately calls germline variants in individuals, including single nucleotide variants, indels and small complex replacements such as microinversions. Using a synthetic tumor data set derived from clean sequencing data from a sample with known germline haplotypes and observed mutations in a large cohort of tumor samples, we show that Octopus is more sensitive to low-frequency somatic variation, yet calls considerably fewer false positives than other methods. Octopus also outputs realigned evidence BAM files to aid validation and interpretation.

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Author Correction: Comprehensive profiling of circular RNAs with nanopore sequencing and CIRI-long

Jinyang Zhang, Lingling Hou, Zhenqiang Zuo, Peifeng Ji, Xiaorong Zhang, Yuanchao Xue & Fangqing Zhao

doi : 10.1038/s41587-021-00934-3

Nature Biotechnology volume 39, page893 (2021)

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Publisher Correction: Questions swirl around failures of disease-modifying Huntington’s drugs

Cormac Sheridan

doi : 10.1038/s41587-021-00987-4

Nature Biotechnology volume 39, page893 (2021)

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Publisher Correction: ‘Super-antibodies’ could curb COVID-19 and help avert future pandemics

Elie Dolgin

doi : 10.1038/s41587-021-00997-2

Nature Biotechnology volume 39, page893 (2021)

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People

doi : 10.1038/s41587-021-00977-6

Nature Biotechnology volume 39, page894 (2021)

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