Advances in Single-Cell Transcriptome Sequencing and Spatial Transcriptome Sequencing in Plants DOI Creative Commons

Zhuo Lv,

Shuaijun Jiang,

Shuxin Kong

et al.

Plants, Journal Year: 2024, Volume and Issue: 13(12), P. 1679 - 1679

Published: June 18, 2024

“Omics” typically involves exploration of the structure and function entire composition a biological system at specific level using high-throughput analytical methods to probe analyze large amounts data, including genomics, transcriptomics, proteomics, metabolomics, among other types. Genomics characterizes quantifies all genes an organism collectively, studying their interrelationships impacts on organism. However, conventional transcriptomic sequencing techniques target population cells, results only reflect average expression levels in as they are unable reveal gene heterogeneity spatial individual thus masking specificity between different cells. Single-cell transcriptome cells plant or animal tissues, enabling understanding each cell’s metabolites expressed genes. Consequently, statistical analysis corresponding tissues can be performed, with purpose achieving cell classification, evolutionary growth, physiological pathological analyses. This article provides overview research progress single-cell well applications challenges plants. Furthermore, prospects for development transcriptomics proposed.

Language: Английский

Large language models in plant biology DOI
Hilbert Yuen In Lam, Xing Er Ong, Marek Mutwil

et al.

Trends in Plant Science, Journal Year: 2024, Volume and Issue: 29(10), P. 1145 - 1155

Published: May 26, 2024

Language: Английский

Citations

16
Spatially resolved transcriptomic analysis of the germinating barley grain DOI Creative Commons
Marta Peirats‐Llobet, Changyu Yi, Lim Chee Liew

et al.

Nucleic Acids Research, Journal Year: 2023, Volume and Issue: 51(15), P. 7798 - 7819

Published: June 23, 2023

Seeds are a vital source of calories for humans and unique stage in the life cycle flowering plants. During seed germination, embryo undergoes major developmental transitions to become seedling. Studying gene expression individual cell types has been challenging due lack spatial information or low throughput existing methods. To overcome these limitations, transcriptomics workflow was developed germinating barley grain. This approach enabled high-throughput analysis expression, revealing specific patterns various functional categories at sub-tissue level. study revealed over 14 000 genes differentially regulated during first 24 h after imbibition. Individual genes, such as aquaporin family, starch degradation, wall modification, transport processes, ribosomal proteins transcription factors, were found have time. Using autocorrelation algorithms, we identified auxin that had increasingly focused within subdomains time, suggesting their role establishing axis. Overall, our provides an unprecedented spatially resolved cellular map germination identifies genomics targets better understand restricted processes germination. The data can be viewed https://spatial.latrobe.edu.au/.

Language: Английский

Citations

25
Understanding plant pathogen interactions using spatial and single-cell technologies DOI Creative Commons
Jie Zhu, Alba Moreno‐Pérez, Gitta Coaker

et al.

Communications Biology, Journal Year: 2023, Volume and Issue: 6(1)

Published: Aug. 4, 2023

Plants are in contact with diverse pathogens and microorganisms. Intense investigation over the last 30 years has resulted identification of multiple immune receptors model crop species as well signaling overlap surface-localized intracellular receptors. However, scientists still have a limited understanding how plants respond to spatial cellular resolution. Recent advancements single-cell, single-nucleus technologies can now be applied plant-pathogen interactions. Here, we outline current state these highlight outstanding biological questions that addressed future.

Language: Английский

Citations

25
Single-cell transcriptomics reveals heterogeneity in plant responses to the environment: a focus on biotic and abiotic interactions DOI
Rubén Tenorio Berrío, Marieke Dubois

Journal of Experimental Botany, Journal Year: 2024, Volume and Issue: 75(17), P. 5188 - 5203

Published: March 11, 2024

Biotic and abiotic environmental cues are major factors influencing plant growth productivity. Interactions with biotic (e.g. symbionts pathogens) changes in temperature, water, or nutrient availability) trigger signaling downstream transcriptome adjustments plants. While bulk RNA-sequencing technologies have traditionally been used to profile these transcriptional changes, tissue homogenization may mask heterogeneity of responses resulting from the cellular complexity organs. Thus, whether different cell types respond equally fluctuations, subsets cell-type specific, long-lasting questions biology. The recent breakthrough single-cell transcriptomics research offers an unprecedented view under changing conditions. In this review, we discuss contribution understanding cell-type-specific interactions. Besides biological findings, present some technical challenges coupled studies plant-environment interactions, proposing possible solutions exciting paths for future research.

Language: Английский

Citations

11
Lost in space: what single-cell RNA sequencing cannot tell you DOI Creative Commons
Kelvin Adema, Michael A. Schon, Michael D. Nodine

et al.

Trends in Plant Science, Journal Year: 2024, Volume and Issue: 29(9), P. 1018 - 1028

Published: April 2, 2024

Plant scientists are rapidly integrating single-cell RNA sequencing (scRNA-seq) into their workflows. Maximizing the potential of scRNA-seq requires a proper understanding spatiotemporal context cells. However, positional information is inherently lost during scRNA-seq, limiting its to characterize complex biological systems. In this review we highlight how current analysis pipelines cannot completely recover spatial information, which confounds interpretation. Various strategies exist identify location RNA, from classical in situ hybridization transcriptomics. Herein discuss possibility utilizing supervise analyses. An integrative approach will maximize each technology, and lead insights go beyond capability individual technology.

Language: Английский

Citations

11
A spatially resolved multi-omic single-cell atlas of soybean development DOI
Xuan Zhang, Ziliang Luo, Alexandre P. Marand

et al.

Cell, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 1, 2024

Language: Английский

Citations

8
A single-nuclei transcriptome census of the Arabidopsis maturing root identifies that MYB67 controls phellem cell maturation DOI Creative Commons
Charlotte Miller,

Sean Jarrell-Hurtado,

Michael Haag

et al.

Developmental Cell, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

The periderm provides a protective barrier in many seed plant species. development of the suberized phellem, which forms outermost layer this important tissue, has become trait interest for enhancing both resilience to stresses and plant-mediated CO

Language: Английский

Citations

1
ggPlantmap: an open-source R package for the creation of informative and quantitative ggplot maps derived from plant images DOI Creative Commons
Leonardo Jo, Kaisa Kajala

Journal of Experimental Botany, Journal Year: 2024, Volume and Issue: 75(17), P. 5366 - 5376

Published: Feb. 8, 2024

Abstract As plant research generates an ever-growing volume of spatial quantitative data, the need for decentralized and user-friendly visualization tools to explore large complex datasets becomes crucial. Existing resources, such as Plant eFP (electronic Fluorescent Pictograph) viewer, have played a pivotal role on communication gene expression data across many species. However, although widely used by community, viewer lacks open creation customized maps independently. biologists with less coding experience can often encounter challenges when attempting ways communicate their own data. We present ‘ggPlantmap’ open-source R package designed address this challenge providing easy method ggplot representative from images. ggPlantmap is built in R, one most languages biology, empower scientists create customize eFP-like viewers tailored experimental Here, we provide overview tutorials that are accessible even users minimal programming experience. hope assist science fostering innovation, improving our understanding development function.

Language: Английский

Citations

6
A spatially resolved multiomic single-cell atlas of soybean development DOI
Xuan Zhang, Ziliang Luo, Alexandre P. Marand

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: July 3, 2024

Summary Cis -regulatory elements (CREs) precisely control spatiotemporal gene expression in cells. Using a spatially resolved single-cell atlas of with chromatin accessibility across ten soybean tissues, we identified 103 distinct cell types and 303,199 accessible regions (ACRs). Nearly 40% the ACRs showed cell-type-specific patterns were enriched for transcription factor (TF) motifs defining diverse identities. We de novo TF explored conservation regulatory networks underpinning legume symbiotic nitrogen fixation. With comprehensive developmental trajectories endosperm embryo, uncovered functional transition three sub-cell endosperm, 13 sucrose transporters sharing DOF11 motif that co-up-regulated late peripheral key embryo cell-type specification regulators during embryogenesis, including homeobox promotes cotyledon parenchyma identity. This resource provides valuable foundation analyzing programs tissues life stages.

Language: Английский

Citations

6
A rapid and sensitive, multiplex, whole mount RNA fluorescence in situ hybridization and immunohistochemistry protocol DOI Creative Commons
Tian Huang, Bruno Guillotin, Ramin Rahni

et al.

Plant Methods, Journal Year: 2023, Volume and Issue: 19(1)

Published: Nov. 22, 2023

In the past few years, there has been an explosion in single-cell transcriptomics datasets, yet vivo confirmation of these datasets is hampered plants due to lack robust validation methods. Likewise, modeling plant development by paucity spatial gene expression data. RNA fluorescence situ hybridization (FISH) enables investigation context tissue type. Despite FISH methods for plants, easy and reliable whole mount protocols have not reported.We adapt a 3-day RNA-FISH method species based on combination prior that employs chain reaction (HCR), which amplifies probe signal antibody-free manner. Our HCR shows expected signals with low background transcripts known patterns Arabidopsis inflorescences monocot roots. It allows simultaneous detection three 3D. We also show can be combined endogenous fluorescent protein our improved immunohistochemistry (IHC) protocol.The IHC allow 3D entire tissues.

Language: Английский

Citations

13