The early days of transcriptome sequencing and functional genomics
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Rapid brain tumor classification from sparse epigenomic data
Although the intraoperative molecular diagnosis of the approximately 100 known brain tumor entities described to date has been a goal of neuropathology for the past decade, achieving this within a clinically relevant timeframe of under 1 h after biopsy collection remains elusive. Advances in third-generation sequencing have brought this goal closer, but established machine learning techniques rely on computationally intensive methods, making them impractical for live diagnostic workflows in clinical applications. Here we present MethyLYZR, a naive Bayesian framework enabling fully tractable, live classification of cancer epigenomes. For evaluation, we used nanopore sequencing to classify over 200 brain tumor samples, including 10 sequenced in a clinical setting next to the operating room, achieving highly accurate results within 15 min of sequencing. MethyLYZR can be run in parallel with an ongoing nanopore experiment with negligible computational overhead. Therefore, the only limiting factors for even faster time to results are DNA extraction time and the nanopore sequencer’s maximum parallel throughput. Although more evidence from prospective studies is needed, our study suggests the potential applicability of MethyLYZR for live molecular classification of nervous system malignancies using nanopore sequencing not only for the neurosurgical intraoperative use case but also for other oncologic indications and the classification of tumors from cell-free DNA in liquid biopsies.
Analysis of microbial composition and sharing in low-biomass human milk samples: a comparison of DNA isolation and sequencing techniques
Human milk microbiome studies are currently hindered by low milk bacterial/human cell ratios and often rely on 16S rRNA gene sequencing, which limits downstream analyses. Here, we aimed to find a method to study milk bacteria and assess bacterial sharing between maternal and infant microbiota. We tested four DNA isolation methods, two bacterial enrichment methods and three sequencing methods on mock communities, milk samples and negative controls. Of the four DNA isolation kits, the DNeasy PowerSoil Pro (PS) and MagMAX Total Nucleic Acid Isolation (MX) kits provided consistent 16S rRNA gene sequencing results with low contamination. Neither enrichment method substantially decreased the human metagenomic sequencing read-depth. Long-read 16S-ITS-23S rRNA gene sequencing biased the mock community composition but provided consistent results for milk samples, with little contamination. In contrast to 16S rRNA gene sequencing, 16S-ITS-23S rRNA gene sequencing of milk, infant oral, infant faecal and maternal faecal DNA from 14 mother-infant pairs provided sufficient resolution to detect significantly more frequent sharing of bacteria between related pairs compared to unrelated pairs. In conclusion, PS or MX kit-DNA isolation followed by 16S rRNA gene sequencing reliably characterises human milk microbiota, and 16S-ITS-23S rRNA gene sequencing enables studies of bacterial transmission in low-biomass samples.
Optimising the mainstreaming of renal genomics: Complementing empirical and theoretical strategies for implementation
To identify and develop complementary implementation strategies that support nephrologists in mainstreaming renal genomic testing. Interviews were conducted with individuals nominated as ‘genomics champions’ and ‘embedded genomics experts’ as part of a mainstreaming project to identify initial barriers and investigate empirical strategies for delivering the project at initial stage. Data were mapped onto implementation science framework to identify complementary theoretical strategies. Interviews with 14 genomics champions and embedded genomics experts (genetic counsellors, nephrologists, renal nurses), identified 34 barriers to incorporating genomic testing into routine care, e.g., lack of long-term multidisciplinary team support and role clarity. In total, 25 empirical implementation strategies were identified such as creating new clinical teams. Using the Consolidated Framework for Implementation Research, 10 complementary theoretical implementation strategies were identified. Our study presents a novel approach complementing empirical strategies with theoretical strategies to support nephrologists in incorporating genomic testing into routine practice. Complementary strategies can potentially address barriers and inform future studies when mainstreaming renal genomics. This process underscored the need for integrating collaborative efforts among health professionals, patients, implementation scientists and the health system to overcome identified challenges to mainstream genomic testing. Future research should explore the applicability of these strategies to support mainstreaming genomic testing in different clinical settings.
Increased early-season productivity drives earlier peak of vegetation photosynthesis across the Northern Hemisphere
Changes in vegetation carbon uptake are largely influenced by the timing and magnitude of the peak of the growing season (POS), when vegetation photosynthesis reaches its maximum. However, the factors controlling the timing of POS remain poorly understood, leaving us uncertain about its future trajectory. Using satellite observations and carbon flux measurements, we show that, in recent decades, increased early-season carbon uptake has been driven by both an earlier onset of the growing season and higher temperatures. In 93% of northern (>30°N) vegetation, these increases in early-season carbon uptake were associated with an advancement of POS. This ongoing shift suggests a developmental constraint on seasonal productivity, potentially limiting carbon uptake later in the season. Our findings provide a mechanistic explanation that reconciles previous observations linking earlier growing season onset, rising temperatures, and shifts in POS timing, and suggest a decrease in late-season carbon uptake with climate warming.
Spotiphy enables single-cell spatial whole transcriptomics across an entire section
Spatial transcriptomics (ST) has advanced our understanding of tissue regionalization by enabling the visualization of gene expression within whole-tissue sections, but current approaches remain plagued by the challenge of achieving single-cell resolution without sacrificing whole-genome coverage. Here we present Spotiphy (spot imager with pseudo-single-cell-resolution histology), a computational toolkit that transforms sequencing-based ST data into single-cell-resolved whole-transcriptome images. Spotiphy delivers the most precise cellular proportions in extensive benchmarking evaluations. Spotiphy-derived inferred single-cell profiles reveal astrocyte and disease-associated microglia regional specifications in Alzheimer’s disease and healthy mouse brains. Spotiphy identifies multiple spatial domains and alterations in tumor–tumor microenvironment interactions in human breast ST data. Spotiphy bridges the information gap and enables visualization of cell localization and transcriptomic profiles throughout entire sections, offering highly informative outputs and an innovative spatial analysis pipeline for exploring complex biological systems.
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