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

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Dec. 3, 2023

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) browsers, have played a pivotal role on communication gene expression data across many species. However, although widely used by community, browser 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 browsers 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. Highlight ggPlantmap, new addition toolbox, allows graphical images representation R.

Language: Английский

From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis DOI
Yirui Zhang, Kai Chang, Babatunde Ogunlade

et al.

ACS Nano, Journal Year: 2024, Volume and Issue: 18(28), P. 18101 - 18117

Published: July 1, 2024

Raman spectroscopy has made significant progress in biosensing and clinical research. Here, we describe how surface-enhanced (SERS) assisted with machine learning (ML) can expand its capabilities to enable interpretable insights into the transcriptome, proteome, metabolome at single-cell level. We first review advances nanophotonics-including plasmonics, metamaterials, metasurfaces-enhance scattering for rapid, strong label-free spectroscopy. then discuss ML approaches precise spectral analysis, including neural networks, perturbation gradient algorithms, transfer learning. provide illustrative examples of phenotyping using nanophotonics ML, bacterial antibiotic susceptibility predictions, stem cell expression profiles, cancer diagnostics, immunotherapy efficacy toxicity predictions. Lastly, exciting prospects future spectroscopy, instrumentation, self-driving laboratories, data banks, uncovering biological insights.

Language: Английский

Citations

22
Harnessing metabolomics for enhanced crop drought tolerance DOI Creative Commons
Ali Raza, Muhammad Anas, Savita Bhardwaj

et al.

The Crop Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

5
Plant metabolomics: applications and challenges in the era of multi-omics big data DOI Creative Commons

Yingchen Hao,

Zhonghui Zhang,

Erping Luo

et al.

aBIOTECH, Journal Year: 2025, Volume and Issue: 6(1), P. 116 - 132

Published: Jan. 23, 2025

Abstract Plant metabolites are crucial for the growth, development, environmental adaptation, and nutritional quality of plants. metabolomics, a key branch systems biology, involves comprehensive analysis interpretation composition, variation, functions these metabolites. Advances in technology have transformed plant metabolomics into sophisticated process involving sample collection, metabolite extraction, high-throughput analysis, data processing, multidimensional statistical analysis. In today’s era big data, field is witnessing an explosion acquisition, offering insight complexity dynamics metabolism. Moreover, multiple omics strategies can be integrated to reveal interactions regulatory networks across different molecular levels, deepening our understanding biological processes. this review, we highlight recent advances challenges emphasizing roles technique improving crop varieties, enhancing value, increasing stress resistance. We also explore scientific foundations its applications medicine, ecological conservation.

Language: Английский

Citations

3
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

7
Single-cell technology for studying plant–microbe interactions DOI
Rachid Lahlali, Bekri Xhemali, Touseef Hussain

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 89 - 109

Published: Jan. 1, 2025

Language: Английский

Citations

1
Navigating the challenges of engineering composite specialized metabolite pathways in plants DOI Creative Commons
Sachin A. Gharat, Vaijayanti A. Tamhane, Ashok P. Giri

et al.

The Plant Journal, Journal Year: 2025, Volume and Issue: 121(6)

Published: March 1, 2025

SUMMARY Plants are a valuable source of diverse specialized metabolites with numerous applications. However, these compounds often produced in limited quantities, particularly under unfavorable ecological conditions. To achieve sufficient levels target metabolites, alternative strategies such as pathway engineering heterologous systems like microbes (e.g., bacteria and fungi) or cell‐free can be employed. Another approach is plant engineering, which aims to either enhance the native production original reconstruct model system. Although increasing metabolite promising strategy, plants exotic pose significant challenges for genetic manipulation. Effective requires comprehensive prior knowledge genes enzymes involved, well precursor, intermediate, branching, final metabolites. Thus, thorough elucidation biosynthetic closely linked successful metabolic host systems. In this review, we highlight recent advances engineering. We focus on efforts engineer complex, multi‐step pathways that require expression at least eight transient three stable transformation. Reports complex stably transformed remain relatively scarce. discuss major hurdles overcoming them, followed by an overview achievements, challenges, solutions reconstitution through Recent including computer‐based predictions offer platforms sustainable plants.

Language: Английский

Citations

1
Single-cell technology for crop breeding DOI
Dwaipayan Sinha, Swastika Banerjee,

Indrani Paul

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 189 - 219

Published: Jan. 1, 2025

Language: Английский

Citations

0
Single-cell technology for plant metabolomics DOI
Dibyendu Seth, Ankan Das, Sandip Debnath

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 221 - 246

Published: Jan. 1, 2025

Language: Английский

Citations

0
Single-cell technology for disease-resistant plants DOI

Lingaraj Dip,

Akbar Hossain, Srikrushna Behera

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 111 - 132

Published: Jan. 1, 2025

Language: Английский

Citations

0
Plant Sample Preparation for Metabolomics, Lipidomics, Ionomics, Fluxomics, and Peptidomics DOI Creative Commons
W.B. Silva, Gabriel Felipe Hispagnol, Emanuel Victor dos Santos Nunes

et al.

Separations, Journal Year: 2025, Volume and Issue: 12(2), P. 21 - 21

Published: Jan. 24, 2025

Plant metabolomics, lipidomics, ionomics, fluxomics, and peptidomics are essential approaches for exploring how plants respond to epigenetic, pathological, environmental stimuli through comprehensive chemical profiling. Over the past decades, significant progress has been made in protocols methodologies address challenges sample collection extraction. Despite these advancements, preparation remains intricate, with ongoing debates about most effective strategies. This review emphasizes importance of clear research questions well-designed experiments minimize complexity, save time, enhance reproducibility. It provides an overview key steps fields, including harvesting, drying, extraction, data pre-acquisition major analytical platforms. By discussing best practices common challenges, this aims streamline methods promote more consistent reliable outcomes.

Language: Английский

Citations

0