Single-cell spatial transcriptomics unravels the cellular landscape of abdominal aortic aneurysm.

Abdominal aortic aneurysm (AAA) is a life-threatening vascular disease with no effective pharmacological interventions. While single-cell transcriptomics has advanced our understanding of AAA, it lacks spatial context. Here, we employed Seq-Scope, an ultra-high-resolution spatial transcriptomic technology, to decipher the spatial landscape of angiotensin II-induced AAA in Apoe-/- mice.

Spatial omics enters the microscopic realm: opportunities and challenges.

Spatial transcriptomics (ST) enables systematic profiling of whole-transcriptome gene expression in tissues while preserving spatial context. Recent advances in sequencing- and imaging-based ST technologies have ushered in the era of microscopic-resolution ST (μST), allowing transcriptome mapping at cellular and even subcellular scales with unprecedented precision. Despite these advances, μST faces substantial challenges, including sparse transcript discovery per submicron (or micron)-sized spatial units and data fragmentation across platforms, hindering integration and analysis.

Seq-Scope-eXpanded: Spatial Omics Beyond Optical Resolution.

Sequencing-based spatial transcriptomics (sST) enables transcriptome-wide gene expression mapping but falls short of reaching the optical resolution (200-300 nm) of imaging-based methods. Here, we present Seq-Scope-X (Seq-Scope-eXpanded), which empowers submicrometer-resolution Seq-Scope with tissue expansion to surpass this limitation. By physically enlarging tissues, Seq-Scope-X minimizes transcript diffusion effects and increases spatial feature density by an additional order of magnitude.

Seq-Scope: repurposing Illumina sequencing flow cells for high-resolution spatial transcriptomics.

Spatial transcriptomics technologies aim to advance gene expression studies by profiling the entire transcriptome with intact spatial information from a single histological slide. However, the application of spatial transcriptomics is limited by low resolution, limited transcript coverage, complex procedures, poor scalability and high costs of initial setup and/or individual experiments. Seq-Scope repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, overcoming these limitations.

Seq-Scope Protocol: Repurposing Illumina Sequencing Flow Cells for High-Resolution Spatial Transcriptomics.

Spatial transcriptomics (ST) technologies represent a significant advance in gene expression studies, aiming to profile the entire transcriptome from a single histological slide. These techniques are designed to overcome the constraints faced by traditional methods such as immunostaining and RNA hybridization, which are capable of analyzing only a few target genes simultaneously. However, the application of ST in histopathological analysis is also limited by several factors, including low resolution, a limited range of genes, scalability issues, high cost, and the need for sophisticated equipment and complex methodologies.

Scalable segmentation-free analysis of submicron resolution spatial transcriptomics.

Spatial transcriptomics (ST) technologies have advanced to enable transcriptome-wide gene expression analysis at submicron resolution over large areas. Analysis of high-resolution ST data relies heavily on image-based cell segmentation or gridding, which often fails in complex tissues due to diversity and irregularity of cell size and shape. Existing segmentation-free analysis methods scale only to small regions and a small number of genes, limiting their utility in high-throughput studies.

Inferring CpG methylation signatures accumulated along human history from genetic variation catalogs.

Understanding the DNA methylation patterns in the human genome is a key step to decipher gene regulatory mechanisms and model mutation rate heterogeneity in the human genome. While methylation rates can be measured e.g.

Microscopic examination of spatial transcriptome using Seq-Scope.

Spatial barcoding technologies have the potential to reveal histological details of transcriptomic profiles; however, they are currently limited by their low resolution. Here, we report Seq-Scope, a spatial barcoding technology with a resolution comparable to an optical microscope. Seq-Scope is based on a solid-phase amplification of randomly barcoded single-molecule oligonucleotides using an Illumina sequencing platform.

Why are rare variants hard to impute? Coalescent models reveal theoretical limits in existing algorithms.

Genotype imputation is an indispensable step in human genetic studies. Large reference panels with deeply sequenced genomes now allow interrogating variants with minor allele frequency < 1% without sequencing. Although it is critical to consider limits of this approach, imputation methods for rare variants have only done so empirically; the theoretical basis of their imputation accuracy has not been explored.