Single-cell and spatial transcriptomics technologies have significantly advanced our understanding of the molecular mechanisms underlying crop biology. This review presents an update on the application of these technologies in crop improvement. The heterogeneity of different cell populations within a tissue plays a crucial role in the coordinated response of an organism to its environment. Single-cell transcriptomics enables the dissection of this heterogeneity, offering insights into the cell-specific transcriptomic responses of plants to various environmental stimuli. Spatial transcriptomics technologies complement single-cell approaches by preserving the spatial context of gene expression profiles, allowing for the in situ localization of transcripts. Together, single-cell and spatial transcriptomics facilitate the discovery of novel genes and gene regulatory networks that can be targeted for genetic manipulation and breeding strategies aimed at enhancing crop yield, quality, and resilience. This review highlights significant findings from recent studies, discusses the expanding roles of these technologies, and explores future opportunities for their application in crop improvement.
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http://dx.doi.org/10.3390/plants13243476 | DOI Listing |
Nature
January 2025
Plant Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA.
Plants lack specialized and mobile immune cells. Consequently, any cell type that encounters pathogens must mount immune responses and communicate with surrounding cells for successful defence. However, the diversity, spatial organization and function of cellular immune states in pathogen-infected plants are poorly understood.
View Article and Find Full Text PDFNature
January 2025
The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA, USA.
The development of the human neocortex is highly dynamic, involving complex cellular trajectories controlled by gene regulation. Here we collected paired single-nucleus chromatin accessibility and transcriptome data from 38 human neocortical samples encompassing both the prefrontal cortex and the primary visual cortex. These samples span five main developmental stages, ranging from the first trimester to adolescence.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Nephrology, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of kidney cancer. Although multiple therapeutic agents have been proven effective in KIRC, their clinical application has been hindered by a lack of reliable biomarkers. This study focused on the prognostic value and function of drug absorption, distribution, metabolism, and excretion- (ADME-) related genes (ARGs) in KIRC to enhance personalized therapy.
View Article and Find Full Text PDFNat Commun
January 2025
Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, 70112, USA.
Aging increases the risk for Alzheimer's disease (AD), driving pathological changes like amyloid-β (Aβ) buildup, inflammation, and oxidative stress, especially in the prefrontal cortex (PFC). We present the first subcellular-resolution spatial transcriptome atlas of the human prefrontal cortex (PFC), generated with Stereo-seq from six male AD cases at varying neuropathological stages and six age-matched male controls. Our analyses revealed distinct transcriptional alterations across PFC layers, highlighted disruptions in laminar structure, and exposed AD-related shifts in layer-to-layer and cell-cell interactions.
View Article and Find Full Text PDFEur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, 410008, P.R. China.
Purpose: Temporal lobe epilepsy (TLE) is a brain network disorder closely associated with synaptic loss and has a genetic basis. However, the in vivo whole-brain synaptic changes at the network-level and the underlying gene expression patterns in patients with TLE remain unclear.
Methods: In this study, we utilized a positron emission tomography with the synaptic vesicle glycoprotein 2 A radioligand [F]SynVesT-1 cohort and two independent transcriptome datasets to investigate the topological properties of the synaptic density similarity network (SDSN) in TLE and its correlation with significantly dysregulated risk genes.
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