A cis-regulatory atlas in maize at single-cell resolution

Marand, Alexandre P.; Chen, Zongliang; Gallavotti, Andrea; Schmitz, Robert J.

doi:10.1016/j.cell.2021.04.014

Cited by 224 publications

(259 citation statements)

References 97 publications

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“…To further understand the transcriptional regulatory sequences underlying accessible chromatin in distinct cell identities, we performed global motif enrichment analysis across all accessible chromatin regions specific to each cell. Enrichment of motif sequences in accessible chromatin regions relative to background (motif deviation scores) for known regulators were consistent with the predicted cell identities, including WRKY family TFs in the specification of root epidermal progenitors (Marand et al, 2021), MYB in endodermis, cortex and pericycle (Cohen et al, 2020), ULT1…”

Section: Regulatory Consequences Of Lineage-specific Chromatin Accessibilitysupporting

confidence: 69%

“…thaliana root scATAC-seq data sets generated using the commercial 10X Genomics Chromium platform (Farmer et al, 2021;Marand et al, 2021). We uniformly processed all libraries to demultiplex reads, assign cell barcodes, align fragments to the TAIR10 reference genome, remove duplicated fragments, and use the R package Socrates to analyze all three data sets (Methods).…”

Section: Comparison Of Sci-atac-seq and Scatac-seqmentioning

confidence: 99%

“…Recent development of droplet microfluidic device-based single-cell systems have enabled researchers to co-encapsulate individual cells or nuclei with barcode beads in nanoliter water-inoil emulsions, making it possible to perform sequencing at the single-cell level (Lareau et al, 2019;Satpathy et al, 2019). For example, single-cell ATAC-seq (scATAC-seq) assays based on the 10X Genomics Chromium system have been successfully applied to study cell-specific chromatin accessibility in plants (Dorrity et al, 2021;Farmer et al, 2021;Marand et al, 2021;Marand and Schmitz, 2022). However, these commercial single-cell assays often require specialized equipment, trained personnel, and are very expensive, making it difficult for an individual laboratory to perform in house.…”

Section: Introductionmentioning

confidence: 99%

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A combinatorial indexing strategy for epigenomic profiling of plant single cells

Marand

Schmitz

et al. 2021

Preprint

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Understanding how cis-regulatory elements facilitate gene expression is a key question in biology. Recent advances in single-cell genomics have led to the discovery of cell-specific chromatin landscapes that underlie transcription programs. However, the high equipment and reagent costs of commercial systems limit their applications for many laboratories. In this study, we profiled the Arabidopsis root single-cell epigenome using a combinatorial index and dual PCR barcode strategy without the need of any specialized equipment. We generated chromatin accessibility profiles for 13,576 Arabidopsis thaliana root nuclei with an average of 12,784 unique Tn5 integrations per cell and 85% of the Tn5 insertions localizing to discrete accessible chromatin regions. Comparison with data generated from a commercial microfluidic platform revealed that our method is capable of unbiased identification of cell type-specific chromatin accessibility with improved throughput, quality, and efficiency. We anticipate that by removing cost, instrument, and other technical obstacles, this combinatorial indexing method will be a valuable tool for routine investigation of single-cell epigenomes and usher new insight into plant growth, development and their interactions with the environment.

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Section: Regulatory Consequences Of Lineage-specific Chromatin Accessibilitysupporting

confidence: 69%

Section: Comparison Of Sci-atac-seq and Scatac-seqmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A combinatorial indexing strategy for epigenomic profiling of plant single cells

Marand

Schmitz

et al. 2021

Preprint

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“…Single-cell RNA-seq has also moved beyond Arabidopsis, with studies emerging for tomato 26 , rice 27 , maize [28][29][30][31] , and moss 32 . Beyond single-cell RNA-seq, epigenomic profiling afforded by single-cell ATAC-seq has become increasingly used in plants [33][34][35] and is ideally suited to explore gene regulation, elucidate regulatory networks, and even more finely classify cell types. scRNA-seq and scATAC-seq datasets are highly complementary and can be combined effectively 34 .…”

Section: The Technologiesmentioning

confidence: 99%

“…Examples of these approaches include computational strategies to capture "free" information from existing data, including developmental trajectories (e.g., Monocle 71 , Palantir 72 , SlingShot 73 , and CellRank 74 ), RNA dynamics (e.g., RNA velocity 75 and scVelo 76 ), methods to integrate disparate and multimodal datasets (e.g., Seurat 77 , Harmony 78 , Symphony 79 ), methods that implement differential gene expression analysis (e.g., MILO 80 ), and several end-to-end pipelines that implement large collections of tools in a single computational ecosystem (e.g., Seurat 81 , Monocle 71 , scanpy 82 ). While many of the tools already developed for analysis of single-cell data from mammalian tissues will be applicable to analysis of plant data sets, and indeed some tools were specifically developed for the analysis of plant singlecell data (e.g., Asc-Seurat 43 , COPILOT 20 , Socrates 33 ), several computational challenges remain that are unique or of particular consideration to plants and would benefit from the development of still more new tools and databases. For example, as research moves from Arabidopsis roots in the first wave of studies to new species and tissues, how do we know if cell clusters represent true cell types if no high-quality cell type-specific markers are already known?…”

Section: Expressionmentioning

confidence: 99%

Plant single-cell solutions for energy and the environment

et al. 2021

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Progress in sequencing, microfluidics, and analysis strategies has revolutionized the granularity at which multicellular organisms can be studied. In particular, single-cell transcriptomics has led to fundamental new insights into animal biology, such as the discovery of new cell types and cell type-specific disease processes. However, the application of single-cell approaches to plants, fungi, algae, or bacteria (environmental organisms) has been far more limited, largely due to the challenges posed by polysaccharide walls surrounding these species’ cells. In this perspective, we discuss opportunities afforded by single-cell technologies for energy and environmental science and grand challenges that must be tackled to apply these approaches to plants, fungi and algae. We highlight the need to develop better and more comprehensive single-cell technologies, analysis and visualization tools, and tissue preparation methods. We advocate for the creation of a centralized, open-access database to house plant single-cell data. Finally, we consider how such efforts should balance the need for deep characterization of select model species while still capturing the diversity in the plant kingdom. Investments into the development of methods, their application to relevant species, and the creation of resources to support data dissemination will enable groundbreaking insights to propel energy and environmental science forward.

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A Single‐Nucleus Resolution Atlas of Transcriptome and Chromatin Accessibility for Peanut (Arachis Hypogaea L.) Leaves

Liu,

Guo,

Gangurde

et al. 2023

Advanced Biology

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The peanut is an important worldwide cash‐crop for edible oil and protein. However, the kinetic mechanisms that determine gene expression and chromatin accessibility during leaf development in peanut represented allotetraploid leguminous crops are poorly understood at single‐cell resolution. Here, a single‐nucleus atlas of peanut leaves is developed by simultaneously profiling the transcriptome and chromatin accessibility in the same individual‐cell using fluorescence‐activated sorted single‐nuclei. In total, 5930 cells with 50 890 expressed genes are classified into 18 cell‐clusters, and 5315 chromatin fragments are enriched with 26 083 target genes in the chromatin accessible landscape. The developmental trajectory analysis reveals the involvement of the ethylene‐AP2 module in leaf cell differentiation, and cell‐cycle analysis demonstrated that genome replication featured in distinct cell‐types with circadian rhythms transcription factors (TFs). Furthermore, dual‐omics illustrates that the fatty acid pathway modulates epidermal‐guard cells differentiation and providescritical TFs interaction networks for understanding mesophyll development, and the cytokinin module (LHY/LOG) that regulates vascular growth. Additionally, an AT‐hook protein AhAHL11 is identified that promotes leaf area expansion by modulating the auxin content increase. In summary, the simultaneous profiling of transcription and chromatin accessibility landscapes using snRNA/ATAC‐seq provides novel biological insights into the dynamic processes of peanut leaf cell development at the cellular level.

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A cis-regulatory atlas in maize at single-cell resolution

Cited by 224 publications

References 97 publications

A combinatorial indexing strategy for epigenomic profiling of plant single cells

A combinatorial indexing strategy for epigenomic profiling of plant single cells

Plant single-cell solutions for energy and the environment

A Single‐Nucleus Resolution Atlas of Transcriptome and Chromatin Accessibility for Peanut (Arachis Hypogaea L.) Leaves

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