Transcriptomics articles from across Nature Portfolio

We quantified age-related changes in gene regulatory relationships across eight human tissues. Our results reveal that the gene–gene relationships that become stronger with age affect mostly genes that operate on the same cellular processes, whereas relationships that become weaker affect genes involved in different processes.

After a heart attack, cardiac muscle cells at the border between injured and healthy tissue instigate an inflammatory response, which spreads to neighbouring cells and makes the heart wall vulnerable to tearing.

Existing 3D Spatial Transcriptomics reconstruction approaches often overlook spatial information or experiment-induced distortions. Here, authors propose ST-GEARS to bridge the gap between in vivo cell locations and in vitro analysis, accurately recovering spatial profiles.

Kidney injury disrupts the intricate renal architecture and triggers regeneration, inflammation and fibrosis. Here, Polonsky et al. used imaging based spatial transcriptomics (seqFISH) and identified distinct signaling between injured epithelial cells and fibroblasts and initiation of chronic immune responses to kidney injury.

Enrichment and analysis of regulatory-active chromatin cfDNA fragments in blood offer a non-invasive method for monitoring dynamic changes in epigenetic and gene expression patterns, underscoring its potential utility in precision medicine.

Single-cell profiling in the human cortex reveals aging-associated transcriptomic changes across all brain cell types, which overlap with effects with Alzheimer’s disease and show a convergent signature with psychopathology across multiple cell types.

Age-related loss of gene expression coordination may contribute to impaired cellular function. In this study, the authors analyzed age-related trends in gene–gene relationships. They found that expression control often remains intact among genes involved in shared cellular functions while the coordination between functions tends to decline.

Toxicogenomics leverages molecular data to predict toxicological effects. In this Review, the authors summarize innovations in transcriptomics and emerging methods, such as single-cell technologies and multi-omics, that offer detailed insights into toxicological mechanisms to enhance hazard prediction and risk assessment.

We quantified age-related changes in gene regulatory relationships across eight human tissues. Our results reveal that the gene–gene relationships that become stronger with age affect mostly genes that operate on the same cellular processes, whereas relationships that become weaker affect genes involved in different processes.

After a heart attack, cardiac muscle cells at the border between injured and healthy tissue instigate an inflammatory response, which spreads to neighbouring cells and makes the heart wall vulnerable to tearing.

Inspired by the success of large-scale machine learning models in natural language, several groups are adapting these models for cellular data using massive single-cell datasets.

Spatial omics technologies have transformed biomedical research by offering detailed, spatially resolved molecular profiles that elucidate tissue structure and function at unprecedented levels. AI can potentially unlock the full power of spatial omics, facilitating the integration of complex datasets and discovery of novel biomedical insights.