RESUMEN
The process of cardiac morphogenesis in humans is incompletely understood. Its full characterization requires a deep exploration of the organ-wide orchestration of gene expression with a single-cell spatial resolution. Here, we present a molecular approach that reveals the comprehensive transcriptional landscape of cell types populating the embryonic heart at three developmental stages and that maps cell-type-specific gene expression to specific anatomical domains. Spatial transcriptomics identified unique gene profiles that correspond to distinct anatomical regions in each developmental stage. Human embryonic cardiac cell types identified by single-cell RNA sequencing confirmed and enriched the spatial annotation of embryonic cardiac gene expression. In situ sequencing was then used to refine these results and create a spatial subcellular map for the three developmental phases. Finally, we generated a publicly available web resource of the human developing heart to facilitate future studies on human cardiogenesis.
Asunto(s)
Regulación del Desarrollo de la Expresión Génica , Corazón/embriología , Miocitos Cardíacos/metabolismo , Análisis de la Célula Individual , Transcriptoma , Femenino , Humanos , Masculino , Morfogénesis , Miocitos Cardíacos/citología , RNA-SeqRESUMEN
Today, resequencing of a human genome can be performed in approximately a week using a single instrument. Thanks to a steady logarithmic rate of increase in performance for DNA sequencing platforms over the past seven years, DNA sequencing is one of the fastest developing technology fields. As the process becomes faster, it opens up possibilities within health care, diagnostics, and entirely new fields of research. Immediate genetic characterization of contagious outbreaks has been exemplified, and with such applications for the direct benefit of human health, expectations of future sensitive, rapid, high-throughput, and cost-effective technologies are steadily growing. Simultaneously, some of the limitations of a rapidly growing field have become apparent, and questions regarding the quality of some of the data deposited into databases have been raised. A human genome sequenced in only an hour is likely to become a reality in the future, but its definition may not be as certain.
Asunto(s)
Genoma Humano , Metagenómica/métodos , Análisis de Secuencia de ADN/métodos , Infecciones Bacterianas/epidemiología , Infecciones Bacterianas/microbiología , Genómica/economía , Genómica/métodos , Genómica/tendencias , Humanos , Metagenómica/economía , Metagenómica/tendencias , Análisis de Secuencia de ADN/economía , Análisis de Secuencia de ADN/instrumentación , Análisis de Secuencia de ADN/tendenciasRESUMEN
SUMMARY: Spatially resolved transcriptomics technologies generate gene expression data with retained positional information from a tissue section, often accompanied by a corresponding histological image. Computational tools should make it effortless to incorporate spatial information into data analyses and present analysis results in their histological context. Here, we present semla, an R package for processing, analysis, and visualization of spatially resolved transcriptomics data generated by the Visium platform, that includes interactive web applications for data exploration and tissue annotation. AVAILABILITY AND IMPLEMENTATION: The R package semla is available on GitHub (https://github.com/ludvigla/semla), under the MIT License, and deposited on Zenodo (https://doi.org/10.5281/zenodo.8321645). Documentation and tutorials with detailed descriptions of usage can be found at https://ludvigla.github.io/semla/.
Asunto(s)
Biología Computacional , Transcriptoma , Biología Computacional/métodos , Programas Informáticos , Perfilación de la Expresión Génica , DocumentaciónRESUMEN
BACKGROUND: Basecalling long DNA sequences is a crucial step in nanopore-based DNA sequencing protocols. In recent years, the CTC-RNN model has become the leading basecalling model, supplanting preceding hidden Markov models (HMMs) that relied on pre-segmenting ion current measurements. However, the CTC-RNN model operates independently of prior biological and physical insights. RESULTS: We present a novel basecaller named Lokatt: explicit duration Markov model and residual-LSTM network. It leverages an explicit duration HMM (EDHMM) designed to model the nanopore sequencing processes. Trained on a newly generated library with methylation-free Ecoli samples and MinION R9.4.1 chemistry, the Lokatt basecaller achieves basecalling performances with a median single read identity score of 0.930, a genome coverage ratio of 99.750%, on par with existing state-of-the-art structure when trained on the same datasets. CONCLUSION: Our research underlines the potential of incorporating prior knowledge into the basecalling processes, particularly through integrating HMMs and recurrent neural networks. The Lokatt basecaller showcases the efficacy of a hybrid approach, emphasizing its capacity to achieve high-quality basecalling performance while accommodating the nuances of nanopore sequencing. These outcomes pave the way for advanced basecalling methodologies, with potential implications for enhancing the accuracy and efficiency of nanopore-based DNA sequencing protocols.
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Nanoporos , ADN/genética , Análisis de Secuencia de ADN/métodos , Redes Neurales de la Computación , Secuencia de Bases , Secuenciación de Nucleótidos de Alto Rendimiento/métodosRESUMEN
Spatial and molecular characteristics determine tissue function, yet high-resolution methods to capture both concurrently are lacking. Here, we developed high-definition spatial transcriptomics, which captures RNA from histological tissue sections on a dense, spatially barcoded bead array. Each experiment recovers several hundred thousand transcript-coupled spatial barcodes at 2-µm resolution, as demonstrated in mouse brain and primary breast cancer. This opens the way to high-resolution spatial analysis of cells and tissues.
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Perfilación de la Expresión Génica , Transcriptoma , Animales , Neoplasias de la Mama/patología , Femenino , Humanos , Ratones , Bulbo Olfatorio/citología , Análisis de Secuencia de ARN/métodos , Análisis de la Célula Individual/métodos , Análisis de Matrices TisularesRESUMEN
BACKGROUND: Distinguishing ductal carcinoma in situ (DCIS) from invasive ductal carcinoma (IDC) regions in clinical biopsies constitutes a diagnostic challenge. Spatial transcriptomics (ST) is an in situ capturing method, which allows quantification and visualization of transcriptomes in individual tissue sections. In the past, studies have shown that breast cancer samples can be used to study their transcriptomes with spatial resolution in individual tissue sections. Previously, supervised machine learning methods were used in clinical studies to predict the clinical outcomes for cancer types. METHODS: We used four publicly available ST breast cancer datasets from breast tissue sections annotated by pathologists as non-malignant, DCIS, or IDC. We trained and tested a machine learning method (support vector machine) based on the expert annotation as well as based on automatic selection of cell types by their transcriptome profiles. RESULTS: We identified expression signatures for expert annotated regions (non-malignant, DCIS, and IDC) and build machine learning models. Classification results for 798 expression signature transcripts showed high coincidence with the expert pathologist annotation for DCIS (100%) and IDC (96%). Extending our analysis to include all 25,179 expressed transcripts resulted in an accuracy of 99% for DCIS and 98% for IDC. Further, classification based on an automatically identified expression signature covering all ST spots of tissue sections resulted in prediction accuracy of 95% for DCIS and 91% for IDC. CONCLUSIONS: This concept study suggest that the ST signatures learned from expert selected breast cancer tissue sections can be used to identify breast cancer regions in whole tissue sections including regions not trained on. Furthermore, the identified expression signatures can classify cancer regions in tissue sections not used for training with high accuracy. Expert-generated but even automatically generated cancer signatures from ST data might be able to classify breast cancer regions and provide clinical decision support for pathologists in the future.
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Biomarcadores de Tumor/genética , Neoplasias de la Mama/diagnóstico , Carcinoma Ductal de Mama/diagnóstico , Carcinoma Intraductal no Infiltrante/diagnóstico , Aprendizaje Automático , Tipificación Molecular/métodos , Transcriptoma , Neoplasias de la Mama/clasificación , Neoplasias de la Mama/genética , Carcinoma Ductal de Mama/genética , Carcinoma Intraductal no Infiltrante/genética , Femenino , Humanos , Curva ROC , Análisis EspacialRESUMEN
MOTIVATION: Spatial Transcriptomics (ST) is a technique that combines high-resolution imaging with spatially resolved transcriptome-wide sequencing. This novel type of data opens up many possibilities for analysis and visualization, most of which are either not available with standard tools or too complex for normal users. RESULTS: Here, we present a tool, ST Viewer, which allows real-time interaction, analysis and visualization of Spatial Transcriptomics datasets through a seamless and smooth user interface. AVAILABILITY AND IMPLEMENTATION: The ST Viewer is open source under a MIT license and it is available at https://github.com/SpatialTranscriptomicsResearch/st_viewer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Biología Computacional , Programas Informáticos , TranscriptomaRESUMEN
Motiviation: Spatial Transcriptomics (ST) is a method which combines high resolution tissue imaging with high troughput transcriptome sequencing data. This data must be aligned with the images for correct visualization, a process that involves several manual steps. Results: Here we present ST Spot Detector, a web tool that automates and facilitates this alignment through a user friendly interface. Contact: jose.fernandez.navarro@scilifelab.se. Supplementary information: Supplementary data are available at Bioinformatics online.
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Perfilación de la Expresión Génica/métodos , Interpretación de Imagen Asistida por Computador/métodos , Programas Informáticos , Animales , Humanos , Internet , Plantas , Análisis de Secuencia de ARN/métodos , Análisis EspacialRESUMEN
MOTIVATION: In recent years we have witnessed an increase in novel RNA-seq based techniques for transcriptomics analysis. Spatial transcriptomics is a novel RNA-seq based technique that allows spatial mapping of transcripts in tissue sections. The spatial resolution adds an extra level of complexity, which requires the development of new tools and algorithms for efficient and accurate data processing. RESULTS: Here we present a pipeline to automatically and efficiently process RNA-seq data obtained from spatial transcriptomics experiments to generate datasets for downstream analysis. AVAILABILITY AND IMPLEMENTATION: The ST Pipeline is open source under a MIT license and it is available at https://github.com/SpatialTranscriptomicsResearch/st_pipeline. CONTACT: jose.fernandez.navarro@scilifelab.se. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Perfilación de la Expresión Génica/métodos , Análisis de Secuencia de ARN/métodos , Programas Informáticos , Análisis Espacial , Algoritmos , Especificidad de ÓrganosAsunto(s)
Citocinas/genética , Células Endoteliales/metabolismo , Proteínas de la Matriz Extracelular/genética , Inmunidad/genética , Pericitos/metabolismo , Tendinopatía/genética , Tenocitos/metabolismo , Citocinas/inmunología , Perfilación de la Expresión Génica , Humanos , Inmunidad/inmunología , Análisis de la Célula Individual , Análisis Espacial , Tendinopatía/inmunologíaRESUMEN
On-site DNA analysis for diagnostic or forensic purposes is much anticipated in the future of molecular testing. Yet the challenges to achieve this goal remain large with rapid and inexpensive detection and visualization being key factors for any portable analysis system. We have developed a filter paper-based nucleic acid assay, which is able to identify and distinguish dog and human genomic and mitochondrial samples in a forensic setting. The filter paper material allows for transport by capillary force of the sample DNA through the detection surface, allowing the targets to hybridize specifically to their complementary capture sequences. Coupling micrometer-sized beads to DNA allows the results to be visualized by the naked eye, enabling instant, cost-efficient, and on-site detection, while eliminating the need for advanced expensive instrumentation.
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ADN/análisis , Filtración/instrumentación , Papel , Animales , ADN/química , ADN/aislamiento & purificación , Sondas de ADN/química , Perros , Ciencias Forenses , Humanos , Especificidad de la Especie , Propiedades de Superficie , Factores de TiempoRESUMEN
Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with poor prognosis and limited treatment options. Efforts to identify effective treatments are thwarted by limited understanding of IPF pathogenesis and poor translatability of available preclinical models. Here we generated spatially resolved transcriptome maps of human IPF (n = 4) and bleomycin-induced mouse pulmonary fibrosis (n = 6) to address these limitations. We uncovered distinct fibrotic niches in the IPF lung, characterized by aberrant alveolar epithelial cells in a microenvironment dominated by transforming growth factor beta signaling alongside predicted regulators, such as TP53 and APOE. We also identified a clear divergence between the arrested alveolar regeneration in the IPF fibrotic niches and the active tissue repair in the acutely fibrotic mouse lung. Our study offers in-depth insights into the IPF transcriptional landscape and proposes alveolar regeneration as a promising therapeutic strategy for IPF.
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Bleomicina , Fibrosis Pulmonar Idiopática , Transcriptoma , Animales , Humanos , Ratones , Fibrosis Pulmonar Idiopática/genética , Fibrosis Pulmonar Idiopática/patología , Bleomicina/toxicidad , Modelos Animales de Enfermedad , Factor de Crecimiento Transformador beta/metabolismo , Factor de Crecimiento Transformador beta/genética , Pulmón/metabolismo , Pulmón/patología , Ratones Endogámicos C57BL , Transducción de Señal/genética , Masculino , Perfilación de la Expresión Génica , Células Epiteliales Alveolares/metabolismo , Proteína p53 Supresora de Tumor/genética , Proteína p53 Supresora de Tumor/metabolismo , Regeneración/genética , Apolipoproteínas E/genéticaRESUMEN
Spatial transcriptomics (ST) maps RNA level patterns within a tissue. This technology has not been previously applied to human placental tissue. We demonstrate analysis of human placental samples with ST. Unsupervised clustering revealed that distinct RNA patterns were found corresponding to different morphological structures. Additionally, when focusing upon terminal villi and hemoglobin associated structures, RNA levels differed between placentas from full term healthy pregnancies and those complicated by preeclampsia. The results from this study can provide a benchmark for future ST studies in placenta.
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Placenta , Preeclampsia , Embarazo , Humanos , Femenino , ARN , Transcriptoma , Preeclampsia/genética , Perfilación de la Expresión GénicaRESUMEN
Current methods for epigenomic profiling are limited in their ability to obtain genome-wide information with spatial resolution. We introduce spatial ATAC, a method that integrates transposase-accessible chromatin profiling in tissue sections with barcoded solid-phase capture to perform spatially resolved epigenomics. We show that spatial ATAC enables the discovery of the regulatory programs underlying spatial gene expression during mouse organogenesis, lineage differentiation and in human pathology.
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Cromatina , Transposasas , Animales , Humanos , Ratones , Cromatina/genética , Transposasas/genética , Transposasas/metabolismo , Epigenómica/métodos , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Análisis de Secuencia de ADN/métodosRESUMEN
To date, single-cell studies of human white adipose tissue (WAT) have been based on small cohort sizes and no cellular consensus nomenclature exists. Herein, we performed a comprehensive meta-analysis of publicly available and newly generated single-cell, single-nucleus, and spatial transcriptomic results from human subcutaneous, omental, and perivascular WAT. Our high-resolution map is built on data from ten studies and allowed us to robustly identify >60 subpopulations of adipocytes, fibroblast and adipogenic progenitors, vascular, and immune cells. Using these results, we deconvolved spatial and bulk transcriptomic data from nine additional cohorts to provide spatial and clinical dimensions to the map. This identified cell-cell interactions as well as relationships between specific cell subtypes and insulin resistance, dyslipidemia, adipocyte volume, and lipolysis upon long-term weight changes. Altogether, our meta-map provides a rich resource defining the cellular and microarchitectural landscape of human WAT and describes the associations between specific cell types and metabolic states.
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Tejido Adiposo Blanco , Transcriptoma , Humanos , Transcriptoma/genética , Tejido Adiposo Blanco/metabolismo , Adipocitos/metabolismo , Perfilación de la Expresión Génica , Adipogénesis/genética , Tejido AdiposoRESUMEN
The development of low-cost, accurate, and equipment-free diagnostic tests is crucial to many clinical, laboratory, and field applications, including forensics and medical diagnostics. Cellulose fiber-based paper is an inexpensive, biodegradable, and renewable resource, the use of which as a biomolecule detection matrix and support confers several advantages compared to traditional materials such as glass. In this context, a new, facile method for the preparation of surface functionalized papers bearing single-stranded probe DNA (ssDNA) for rapid target hybridization via capillary transport is presented. Optimized reaction conditions were developed that allowed the direct, one-step activation of standard laboratory filters by the inexpensive and readily available bifunctional linking reagent, 1,4-phenylenediisothiocyanate. Such papers were thus amenable to subsequent coupling of amine-labeled ssDNA under standard conditions widely used for glass-based supports. The intrinsic wicking ability of the paper matrix facilitated rapid sample elution through arrays of probe DNA, leading to significant, detectable hybridization in the time required for the sample liquid to transit the vertical length of the strip (less than 2 min). The broad applicability of these paper test strips as rapid and specific diagnostics in "real-life" situations was exemplified by the discrimination of amplicons generated from canine and human mitochondrial and genomic DNA in mock forensic samples.
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Sondas de ADN/química , Sondas de ADN/genética , ADN de Cadena Simple/química , ADN de Cadena Simple/genética , Hibridación de Ácido Nucleico/métodos , Papel , Aminas/química , Animales , Celulosa/química , Perros , Humanos , Propiedades de Superficie , Factores de TiempoRESUMEN
The inflamed rheumatic joint is a highly heterogeneous and complex tissue with dynamic recruitment and expansion of multiple cell types that interact in multifaceted ways within a localized area. Rheumatoid arthritis synovium has primarily been studied either by immunostaining or by molecular profiling after tissue homogenization. Here, we use Spatial Transcriptomics, where tissue-resident RNA is spatially labeled in situ with barcodes in a transcriptome-wide fashion, to study local tissue interactions at the site of chronic synovial inflammation. We report comprehensive spatial RNA-Seq data coupled to cell type-specific localization patterns at and around organized structures of infiltrating leukocyte cells in the synovium. Combining morphological features and high-throughput spatially resolved transcriptomics may be able to provide higher statistical power and more insights into monitoring disease severity and treatment-specific responses in seropositive and seronegative rheumatoid arthritis.
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Artritis Reumatoide , Transcriptoma , Artritis Reumatoide/genética , Artritis Reumatoide/metabolismo , Humanos , Membrana Sinovial/metabolismoRESUMEN
B cells play a significant role in established Rheumatoid Arthritis (RA). However, it is unclear to what extent differentiated B cells are present in joint tissue already at the onset of disease. Here, we studied synovial biopsies (n = 8) captured from untreated patients at time of diagnosis. 3414 index-sorted B cells underwent RNA sequencing and paired tissue pieces were subjected to spatial transcriptomics (n = 4). We performed extensive bioinformatics analyses to dissect the local B cell composition. Select plasma cell immunoglobulin sequences were expressed as monoclonal antibodies and tested by ELISA. Memory and plasma cells were found irrespective of autoantibody status of the patients. Double negative memory B cells were prominent, but did not display a distinct transcriptional profile. The tissue architecture implicate both local B cell maturation via T cell help and plasma cell survival niches with a strong CXCL12-CXCR4 axis. The immunoglobulin sequence analyses revealed clonality between the memory B and plasma cell pools further supporting local maturation. One of the plasma cell-derived antibodies displayed citrulline autoreactivity, demonstrating local autoreactive plasma cell differentiation in joint biopsies captured from untreated early RA. Hence, plasma cell niches are not a consequence of chronic inflammation, but are already present at the time of diagnosis.
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Artritis Reumatoide , Membrana Sinovial , Autoanticuerpos , Diferenciación Celular , Humanos , Membrana Sinovial/patología , TranscriptomaRESUMEN
Massively parallel DNA sequencing is revolutionizing genomics research throughout the life sciences. However, the reagent costs and labor requirements in current sequencing protocols are still substantial, although improvements are continuously being made. Here, we demonstrate an effective alternative to existing sample titration protocols for the Roche/454 system using Fluorescence Activated Cell Sorting (FACS) technology to determine the optimal DNA-to-bead ratio prior to large-scale sequencing. Our method, which eliminates the need for the costly pilot sequencing of samples during titration is capable of rapidly providing accurate DNA-to-bead ratios that are not biased by the quantification and sedimentation steps included in current protocols. Moreover, we demonstrate that FACS sorting can be readily used to highly enrich fractions of beads carrying template DNA, with near total elimination of empty beads and no downstream sacrifice of DNA sequencing quality. Automated enrichment by FACS is a simple approach to obtain pure samples for bead-based sequencing systems, and offers an efficient, low-cost alternative to current enrichment protocols.