Annotation of single-cell clusters using marker genes within and across species DOI

Sanchari Kundu,

Tran Chau,

Dena Saghai Maroof

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 321 - 347

Published: Jan. 1, 2025

Language: Английский

Temperature‐smart plants: A new horizon with omics‐driven plant breeding DOI Creative Commons
Ali Raza, Shanza Bashir, Tushar Khare

et al.

Physiologia Plantarum, Journal Year: 2024, Volume and Issue: 176(1)

Published: Jan. 1, 2024

Abstract The adverse effects of mounting environmental challenges, including extreme temperatures, threaten the global food supply due to their impact on plant growth and productivity. Temperature extremes disrupt genetics, leading significant issues eventually damaging phenotypes. Plants have developed complex signaling networks respond tolerate temperature stimuli, genetic, physiological, biochemical, molecular adaptations. In recent decades, omics tools other strategies rapidly advanced, offering crucial insights a wealth information about how plants adapt stress. This review explores potential an integrated omics‐driven approach understanding temperatures. By leveraging cutting‐edge methods, genomics, transcriptomics, proteomics, metabolomics, miRNAomics, epigenomics, phenomics, ionomics, alongside power machine learning speed breeding data, we can revolutionize practices. These advanced techniques offer promising pathway developing climate‐proof varieties that withstand fluctuations, addressing increasing demand for high‐quality in face changing climate.

Language: Английский

Citations

29

Orthologous marker groups reveal broad cell identity conservation across plant single-cell transcriptomes DOI Creative Commons
Tran N. Chau, Prakash Raj Timilsena,

Sai Pavan Bathala

et al.

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Jan. 2, 2025

Single-cell RNA sequencing (scRNA-seq) is widely used in plant biology and a powerful tool for studying cell identity differentiation. However, the scarcity of known cell-type marker genes divergence expression patterns limit accuracy identification our capacity to investigate conservation many species. To tackle this challenge, we devise novel computational strategy called Orthologous Marker Gene Groups (OMGs), which can identify types both model non-model species allows rapid comparison across published single-cell maps. Our method does not require cross-species data integration, while still accurately determining inter-species cellular similarities. We validate by analyzing from with well-annotated maps, show methods capture majority manually annotated types. The robustness further demonstrated its ability pertinently map clusters 1 million cells, 268 15 diverse reveal 14 dominant groups substantial shared markers monocots dicots. facilitate use broad research community, launch user-friendly web-based OMG browser, simplifies process datasets biologists. A Ortho-Marker (OMGs) was developed enable single data. revealed conserved accessible via browser.

Language: Английский

Citations

2

Single-cell transcriptomic analysis reveals the developmental trajectory and transcriptional regulatory networks of pigment glands in Gossypium bickii DOI Creative Commons
Yue Sun,

Yifei Han,

Kuang Sheng

et al.

Molecular Plant, Journal Year: 2023, Volume and Issue: 16(4), P. 694 - 708

Published: Feb. 10, 2023

Comprehensive utilization of cottonseeds is limited by the presence pigment glands and its inclusion gossypol. The ideal cotton has glandless seeds but a glanded plant, trait found in only few Australian wild species, including Gossypium bickii. Introgression this into cultivated species proved to be difficult. Understanding biological processes toward gland morphogenesis associated underlying molecular mechanisms will facilitate breeding varieties with plant. In study, single-cell RNA sequencing (scRNA-seq) was performed on 12 222 protoplasts isolated from cotyledons germinating G. bickii 48 h after imbibition. Clustered 14 distinct clusters unsupervisedly, these cells could grouped eight cell populations assistance known marker genes. were well separated others parenchyma cells, secretory apoptotic cells. By integrating developmental trajectory, transcription factor regulatory networks, core functional validation, we established model for formation. model, light gibberellin verified promote formation glands. addition, three novel genes, GbiERF114 (ETHYLENE RESPONSE FACTOR 114), GbiZAT11 (ZINC FINGER OF ARABIDOPSIS THALIANA 11), GbiNTL9 (NAC TRANSCRIPTION FACTOR-LIKE 9), affect Collectively, findings provide new insights lay cornerstone future scRNA-seq investigations.

Language: Английский

Citations

43

Cell-type-specific responses to fungal infection in plants revealed by single-cell transcriptomics DOI Creative Commons
Bozeng Tang, Feng Li, Michelle T. Hulin

et al.

Cell Host & Microbe, Journal Year: 2023, Volume and Issue: 31(10), P. 1732 - 1747.e5

Published: Sept. 22, 2023

Pathogen infection is a dynamic process. Here, we employ single-cell transcriptomics to investigate plant response heterogeneity. By generating an Arabidopsis thaliana leaf atlas encompassing 95,040 cells during by fungal pathogen, Colletotrichum higginsianum, unveil cell-type-specific gene expression, notably enrichment of intracellular immune receptors in vasculature cells. Trajectory inference identifies that had different interactions with the invading fungus. This analysis divulges transcriptional reprogramming abscisic acid signaling specifically occurring guard cells, which consistent stomatal closure dependent on direct contact Furthermore, plasticity genes involved glucosinolate biosynthesis at sites, emphasizing contribution epidermis-expressed MYB122 disease resistance. work underscores spatially dynamic, responses pathogen and provides valuable resource supports in-depth investigations plant-pathogen interactions.

Language: Английский

Citations

43

Transcriptional networks regulating suberin and lignin in endodermis link development and ABA response DOI Open Access
Huimin Xu, Peng Liu, Chunhua Wang

et al.

PLANT PHYSIOLOGY, Journal Year: 2022, Volume and Issue: 190(2), P. 1165 - 1181

Published: July 4, 2022

Abstract Vascular tissues are surrounded by an apoplastic barrier formed endodermis that is vital for selective absorption of water and nutrients. Lignification suberization endodermal cell walls fundamental processes in establishing the barrier. Endodermal Arabidopsis (Arabidopsis thaliana) roots presumed to be integration developmental regulation stress responses. In root endodermis, level enhanced when Casparian strip, lignified structure, defective. However, it not entirely clear how lignification interplay they interact with signaling. Here, Arabidopsis, we constructed a hierarchical network mediated SHORT-ROOT (SHR), master regulator development, identified 13 key MYB transcription factors (TFs) form multiple sub-networks. Combined functional analyses, further uncovered TFs mediate feedback or feed-forward loops, thus balancing roots. addition, sub-networks comprising nine were abscisic acid signaling integrate response development. Our data provide insights into mechanisms enhance plant adaptation changing environments.

Language: Английский

Citations

42

Single‐cell RNA sequencing profiles reveal cell type‐specific transcriptional regulation networks conditioning fungal invasion in maize roots DOI Creative Commons

Yanyong Cao,

Juan Ma, Shengbo Han

et al.

Plant Biotechnology Journal, Journal Year: 2023, Volume and Issue: 21(9), P. 1839 - 1859

Published: June 22, 2023

Stalk rot caused by Fusarium verticillioides (Fv) is one of the most destructive diseases in maize production. The defence response root system to Fv invasion important for plant growth and development. Dissection cell type-specific infection its underlying transcription regulatory networks will aid understanding mechanism roots invasion. Here, we reported transcriptomes 29 217 single cells derived from tips two inbred lines inoculated with mock condition, identified seven major types 21 transcriptionally distinct clusters. Through weighted gene co-expression network analysis, 12 Fv-responsive modules 4049 differentially expressed genes (DEGs) that were activated or repressed these types. Using a machining-learning approach, constructed six immune integrating Fv-induced DEGs transcriptomes, 16 known disease-resistant genes, five experimentally validated (ZmWOX5b, ZmPIN1a, ZmPAL6, ZmCCoAOMT2, ZmCOMT), 42 QTL QTN predicted are associated resistance. Taken together, this study provides not only global view fate determination during development but also insights into at single-cell resolution, thus laying foundation dissecting molecular mechanisms disease resistance maize.

Language: Английский

Citations

34

Integrating omics databases for enhanced crop breeding DOI Creative Commons
Haoyu Chao, Shilong Zhang, Yueming Hu

et al.

Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics, Journal Year: 2023, Volume and Issue: 20(4)

Published: July 24, 2023

Abstract Crop plant breeding involves selecting and developing new varieties with desirable traits such as increased yield, improved disease resistance, enhanced nutritional value. With the development of high-throughput technologies, genomics, transcriptomics, metabolomics, crop has entered a era. However, to effectively use these integration multi-omics data from different databases is required. Integration omics provides comprehensive understanding biological processes underlying their interactions. This review highlights importance integrating in breeding, discusses available databases, describes challenges, recent developments potential benefits. Taken together, critical step towards enhancing improving global food security.

Language: Английский

Citations

29

scPlantDB: a comprehensive database for exploring cell types and markers of plant cell atlases DOI Creative Commons
Zhaohui He, Yuting Luo, Xinkai Zhou

et al.

Nucleic Acids Research, Journal Year: 2023, Volume and Issue: 52(D1), P. D1629 - D1638

Published: Aug. 28, 2023

Abstract Recent advancements in single-cell RNA sequencing (scRNA-seq) technology have enabled the comprehensive profiling of gene expression patterns at level, offering unprecedented insights into cellular diversity and heterogeneity within plant tissues. In this study, we present a systematic approach to construct database, scPlantDB, which is publicly available https://biobigdata.nju.edu.cn/scplantdb. We integrated transcriptomic profiles from 67 high-quality datasets across 17 species, comprising approximately 2.5 million cells. The data underwent rigorous collection, manual curation, strict quality control standardized processing public databases. scPlantDB offers interactive visualization facilitating exploration both single-dataset multiple-dataset analyses. It enables comparison functional annotation markers diverse cell types species while providing tools identify compare based on these markers. summary, serves as database for investigating atlases. valuable resource research community.

Language: Английский

Citations

29

Nitrogen sensing and regulatory networks: it's about time and space DOI Creative Commons
Carly M. Shanks, Karin Rothkegel, Matthew D. Brooks

et al.

The Plant Cell, Journal Year: 2024, Volume and Issue: 36(5), P. 1482 - 1503

Published: Feb. 14, 2024

A plant's response to external and internal nitrogen signals/status relies on sensing signaling mechanisms that operate across spatial temporal dimensions. From a comprehensive systems biology perspective, this involves integrating responses in different cell types over long distances ensure organ coordination real time yield practical applications. In prospective review, we focus novel aspects of (N) sensing/signaling uncovered using approaches, largely the model Arabidopsis. The span: transcriptional N-dose mediated by Michaelis-Menten kinetics, role master NLP7 transcription factor as nitrate sensor, its nitrate-dependent TF nuclear retention, "hit-and-run" mode target gene regulation, cascade identified "network walking." Spatial N-sensing/signaling have been type-specific studies roots root-to-shoot communication. We explore new approaches single-cell sequencing data, trajectory inference, pseudotime analysis well machine learning artificial intelligence approaches. Finally, unveiling underlying dynamics networks species from crop could pave way for translational improve nitrogen-use efficiency crops. Such outcomes potentially reduce detrimental effects excessive fertilizer usage groundwater pollution greenhouse gas emissions.

Language: Английский

Citations

14

Advances in the Application of Single-Cell Transcriptomics in Plant Systems and Synthetic Biology DOI Creative Commons
Md Torikul Islam, Yang Liu, Md Mahmudul Hassan

et al.

BioDesign Research, Journal Year: 2024, Volume and Issue: 6, P. 0029 - 0029

Published: Jan. 1, 2024

Plants are complex systems hierarchically organized and composed of various cell types. To understand the molecular underpinnings plant systems, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for revealing high resolution gene expression patterns at cellular level investigating cell-type heterogeneity. Furthermore, scRNA-seq analysis biosystems great potential generating new knowledge to inform design synthetic biology, which aims modify plants genetically/epigenetically through genome editing, engineering, or re-writing based on rational increasing crop yield quality, promoting bioeconomy enhancing environmental sustainability. In particular, data from studies can be utilized facilitate development high-precision Build-Design-Test-Learn capabilities maximizing targeted performance engineered while minimizing unintended side effects. date, been demonstrated in limited number species, including model (e.g., Arabidopsis thaliana), agricultural crops Oryza sativa), bioenergy Populus spp.). It is expected that future technical advancements will reduce cost consequently accelerate application this emerging technology plants. review, we summarize current scRNA-seq, sample preparation, sequencing, analysis, provide guidance how choose appropriate methods different types samples. We then highlight applications both biology research. Finally, discuss challenges opportunities

Language: Английский

Citations

13