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The spatial distribution of lymphocyte clones within tissues is critical to their development, selection, and expansion. We have developed spatial transcriptomics of variable, diversity, and joining (VDJ) sequences (Spatial VDJ), a method that maps B cell and T cell receptor sequences in human tissue sections. Spatial VDJ captures lymphocyte clones that match canonical B and T cell distributions and amplifies clonal sequences confirmed by orthogonal methods. We found spatial congruency between paired receptor chains, developed a computational framework to predict receptor pairs, and linked the expansion of distinct B cell clones to different tumor-associated gene expression programs. Spatial VDJ delineates B cell clonal diversity and lineage trajectories within their anatomical niche. Thus, Spatial VDJ captures lymphocyte spatial clonal architecture across tissues, providing a platform to harness clonal sequences for therapy., QC 20240102

In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and full-length sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome profiling methods. To that end, we introduce spatial isoform transcriptomics (SiT), an explorative method for characterizing spatial isoform variation and sequence heterogeneity using long-read sequencing. We show in mouse brain how SiT can be used to profile isoform expression and sequence heterogeneity in different areas of the tissue. SiT reveals regional isoform switching of Plp1 gene between different layers of the olfactory bulb, and the use of external single-cell data allows the nomination of cell types expressing each isoform. Furthermore, SiT identifies differential isoform usage for several major genes implicated in brain function (Snap25, Bin1, Gnas) that are independently validated by in situ sequencing. SiT also provides for the first time an in-depth A-to-I RNA editing map of the adult mouse brain. Data exploration can be performed through an online resource, where isoform expression and RNA editing can be visualized in a spatial context., QC 20230602

Purpose: More than half of the familial cutaneous melanomas have unknown genetic predisposition. This study aims at characterizing a novel melanoma susceptibility gene. Methods: We performed exome and targeted sequencing in melanoma-prone families without any known melanoma susceptibility genes. We analyzed the expression of candidate gene DENND5A in melanoma samples in relation to pigmentation and UV signature. Functional studies were carried out using microscopic approaches and zebrafish model. Results: We identified a novel DENND5A truncating variant that segregated with melanoma in a Swedish family and 2 additional rare DENND5A variants, 1 of which segregated with the disease in an American family. We found that DENND5A is significantly enriched in pigmented melanoma tissue. Our functional studies show that loss of DENND5A function leads to decrease in melanin content in vitro and pigmentation defects in vivo. Mechanistically, harboring the truncating variant or being suppressed leads to DENND5A losing its interaction with SNX1 and its ability to transport the SNX1-associated vesicles from melanosomes. Consequently, untethered SNX1-premelanosome protein and redundant tyrosinase are redirected to lysosomal degradation by default, causing decrease in melanin content. Conclusion: Our findings provide evidence of a physiological role of DENND5A in the skin context and link its variants to melanoma susceptibility.

The transcriptome and the cells’ spatial organization are important determinants for the functions of biological systems, such as a tumor, brain, or skin tissue. Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for profiling the transcriptome of individual cells. The nuanced characterization of cell types and states enabled by scRNA-seq has revolutionized our understanding of biological systems. However, these methods rely on the dissociation of tissues into single cells whereby spatial context is lost. Recent advancements have resulted in technologies that retain and associate spatial information with the gene expression of tissues, which has permitted the delineation of biological systems at an unprecedented level. The Spatial Transcriptomics (ST) technology offers transcriptome profiling across thousands of subareas of a tissue section by capturing mRNA in situ and sequencing ex situ. In Paper I, ST was used to explore heterogeneity in lymph node metastases of human cutaneous malignant melanoma. A data-driven analysis approach revealed inter- and intratumor heterogeneity in the examined tumor tissue, whereas the stromal tissue exhibited similar gene expression across patients. Paper II presents an integration of ST, scRNA-seq, and spatial protein analysis to characterize human cutaneous squamous cell carcinoma. The spatial resolution of ST is not at the single-cell level; however, this multimodal approach allowed for the identification of tumor subpopulations and revealed the niches in which they reside. In Paper III, ST and scRNA-seq data were generated to build an atlas of human skin. The combined data was used to map cell-type abundance and intercellular communications in homeostasis. Moreover, cell-of-origin analysis allowed for the identification of candidate cell types accountable for human genetic skin diseases. Paper IV introduces Spatial VDJ, a technique for spatial analysis of B and T cell antigen receptor transcripts, hence determi, Transkriptomet och det spatiala arrangemanget av celler är avgörande faktorer för funktionerna inom biologiska system, såsom en tumör, hjärna eller hudvävnad. Singel-cell RNA sekvensering (scRNA-seq) har visat sig vara ett kraftfullt verktyg för att profilera transkriptomet av individuella celler. Den nyanserade karakteriseringen av celltyper och celltillstånd som möjliggörs av scRNA-seq har revolutionerat vår förståelse av biologiska system. Dessa metoder utgår dock från att vävnad dissocieras till enskilda celler, vilket medför att den spatiala kontexten går förlorad. Framsteg har på senare tid resulterat i teknologier som bevarar och associerar spatial information med genuttrycket av vävnader, vilket gjort att biologiska system kunnat skildras på en nivå som inte varit möjlig tidigare. Med teknologin Spatial Transcriptomics (ST) erhålls transkriptomprofilering från tusentals delområden av ett vävnadssnitt genom att mRNA fångas in situ och sekvenseras ex situ. I Artikel I användes ST för att utforska heterogenitet i lymfkörtelmetastaser av humant malignt melanom i huden. En datadriven analysmetod avslöjade inter- och intratumoral heterogenitet hos den undersökta tumörvävnaden, medan den stromala vävnaden uppvisade liknande genuttryck mellan patienter. Artikel II presenterar en integrering av ST, scRNA-seq och spatial proteinanalys för att karakterisera human skivepitelcancer i huden. ST- teknologins spatiala upplösning är inte detaljerad nog att vara på singelcellnivå, men detta multimodala tillvägagångssätt möjliggjorde identifiering av olika tumörsubpopulationer och avslöjade nischerna de finns i. I Artikel III genererades ST- och scRNA-seq-data för att bygga en atlas av human hud. De kombinerade datatyperna användes för att kartlägga celltypssammansättning och intercellulär kommunikation i homeostas. Därtill identifierades celltyper som driver genetiska hudsjukdomar. Artikel IV introducerar Spatial VDJ, e, QC 2022-04-11

QC 20220728

QC 20230406

Previous large-scale studies have uncovered many features that determine the processing of microRNA (miRNA) precursors; however, they have been conducted in vitro. Here, we introduce MapToCleave, a method to simultaneously profile processing of thousands of distinct RNA structures in living cells. We find that miRNA precursors with a stable lower basal stem are more efficiently processed and also have higher expression in vivo in tissues from 20 animal species. We systematically compare the importance of known and novel sequence and structural features and test biogenesis of miRNA precursors from 10 animal and plant species in human cells. Lastly, we provide evidence that the GHG motif better predicts processing when defined as a structure rather than sequence motif, consistent with recent cryogenic electron microscopy (cryo-EM) studies. In summary, we apply a screening assay in living cells to reveal the importance of lower basal stem stability for miRNA processing and in vivo expression., QC 20211206

In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and full-length sequence heterogeneity cannot be characterized with current methods. Here, we introduce Spatial Isoform Transcriptomics (SiT), an explorative method for characterizing spatial isoform and sequence heterogeneity in tissue sections, and show how it can be used to profile isoform expression and sequence heterogeneity in a tissue context, QC 20210126

To define the cellular composition and architecture of cutaneous squamous cell carcinoma (cSCC), we combined single-cell RNA sequencing with spatial transcriptomics and multiplexed ion beam imaging from a series of human cSCCs and matched normal skin. cSCC exhibited four tumor subpopulations, three recapitulating normal epidermal states, and a tumor-specific keratinocyte (TSK) population unique to cancer, which localized to a fibrovascular niche. Integration of single-cell and spatial data mapped ligand-receptor networks to specific cell types, revealing TSK cells as a hub for intercellular communication. Multiple features of potential immunosuppression were observed, including T regulatory cell (Treg) co-localization with CD8 T cells in compartmentalized tumor stroma. Finally, single-cell characterization of human tumor xenografts and in vivo CRISPR screens identified essential roles for specific tumor subpopulation-enriched gene networks in tumorigenesis. These data define cSCC tumor and stromal cell subpopulations, the spatial niches where they interact, and the communicating gene networks that they engage in cancer., QC 20200818

QC 20200311

Cutaneous malignant melanoma (melanoma) is characterized by a high mutational load, extensive intertumoral and intratumoral genetic heterogeneity, and complex tumor microenvironment (TME) interactions. Further insights into the mechanisms underlying melanoma are crucial for understanding tumor progression and responses to treatment. Here we adapted the technology of spatial transcriptomics (ST) to melanoma lymph node biopsies and successfully sequenced the transcriptomes of over 2,200 tissue domains. Deconvolution combined with traditional approaches for dimensional reduction of transcriptome-wide data enabled us to both visualize the transcriptional landscape within the tissue and identify gene expression profiles linked to specific histologic entities. Our unsupervised analysis revealed a complex spatial intratumoral composition of melanoma metastases that was not evident through morphologic annotation. Each biopsy showed distinct gene expression profiles and included examples of the coexistence of multiple melanoma signatures within a single tumor region as well as shared profiles for lymphoid tissue characterized according to their spatial location and gene expression profiles. The lymphoid area in close proximity to the tumor region displayed a specific expression pattern, which may reflect the TME, a key component to fully understanding tumor progression. In conclusion, using the ST technology to generate gene expression profiles reveals a detailed landscape of melanoma metastases. This should inspire researchers to integrate spatial information into analyses aiming to identify the factors underlying tumor progression and therapy outcome. Significance: Applying ST technology to gene expression profiling in melanoma lymph node metastases reveals a complex transcriptional landscape in a spatial context, which is essential for understanding the multiple components of tumor progression and therapy outcome. (C) 2018 AACR., QC 20181120

QC 20220412

QC 20220412

Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. Here, we provide an unsupervised approach to study spatial genome integrity in situ to gain molecular insight into clonal relationships. We employed spatially resolved transcriptomics to infer spatial copy number variations in >120 000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy., QC 20211116