Slide-tags: scalable, single-nucleus barcoding for multi-modal spatial genomics
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1022468 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Recent technological innovations have enabled the high-throughput quantification of gene expression and epigenetic regulation within individual cells, transforming our understanding of how complex tissues are constructed. Missing from these measurements, however, is the ability to routinely and easily spatially localise these profiled cells. We developed a strategy, Slide-tags, in which single nuclei within an intact tissue section are ‘tagged’ with spatial barcode oligonucleotides derived from DNA-barcoded beads with known positions. These tagged nuclei can then be used as input into a wide variety of single-nucleus profiling assays. We used Slide-tags to profile two different stages of development in the mouse brain.
2023-10-03 | GSE244355 | GEO
Project description:[Oryza sativa Genome Oligo Set Version 1.0 was designed by Beijing Genomics Institute (BGI) and contain 60,727 70mer oligos representing both indica and japonica genomes. All oligos were designed from cDNAs, expreseed sequence tag (EST) sequences, predicted genes of BGI rice genome build and other public resources. Mapping to TIGR rice genome pseudommolecues release 2 is based on the BLAST results, if a oligo has greater than 97% identity to a gene sequence from TIGR pseudomolecules, the oligo represents that gene. Rice 30K Operon Version 1.0 -70 mer oligos. The array is in 48 pin conformation. It has 25 columns and 25 rows in each of 4 x 12 subarrays. This is the slideA of the two slide sets. Platform_catalog_number: XDEN-A Platform_coating: poly L lysine Platform_manufacture_protocol: Omnigrid 100 contact printer; TeleChem Stealth SMP3 split pins; See http://keck.med.yale.edu/dnaarrays/printing Platform_manufacturer: Keck Biotechnology Resource Lab at Yale Platform_support: glass slide Platform_technology: spotted oligonucleotide ] Series_sample_order: Sample 1-15 Slide A; Sample 16-30 Slide B Keywords: other
2005-05-24 | GSE2691 | GEO
Project description:[Oryza sativa Genome Oligo Set Version 1.0 was designed by Beijing Genomics Institute (BGI) and contain 60,727 70mer oligos representing both indica and japonica genomes. All oligos were designed from cDNAs, expreseed sequence tag (EST) sequences, predicted genes of BGI rice genome build and other public resources. Mapping to TIGR rice genome pseudommolecues release 2 is based on the BLAST results, if a oligo has greater than 97% identity to a gene sequence from TIGR pseudomolecules, the oligo represents that gene. Rice 30K Operon Version 1.0 -70 mer oligos. The array is in 48 pin conformation. It has 25 columns and 25 rows in each of 4 x 12 subarrays. This is the slideA of the two slide sets. Platform_catalog_number: XDEN-A Platform_coating: poly L lysine Platform_manufacture_protocol: Omnigrid 100 contact printer; TeleChem Stealth SMP3 split pins; See http://keck.med.yale.edu/dnaarrays/printing Platform_manufacturer: Keck Biotechnology Resource Lab at Yale Platform_support: glass slide Platform_technology: spotted oligonucleotide ] Series_sample_order: Sample 1-15 Slide A; Sample 16-30 Slide B
2010-06-10 | E-GEOD-2691 | biostudies-arrayexpress
Project description:Detecting strain-specific barcodes with mass spectrometry can facilitate the screening of genetically engineered bacterial libraries. Here, we introduce intact protein barcoding, a method to measure protein-based library barcodes and metabolites using flow-injection mass spectrometry (FI-MS). Protein barcodes are based on ubiquitin with N-terminal tags of six amino acids. We demonstrate that FI-MS detects intact ubiquitin proteins and identifies the mass of N-terminal barcodes. In the same analysis, we measured relative concentrations of primary metabolites. We constructed 6 ubiquitin-barcoded CRISPRi strains targeting metabolic enzymes, and analyzed their metabolic profiles and ubiquitin barcodes. FI-MS detected barcodes and distinct metabolome changes in CRISPRi-targeted pathways. We demonstrate the scalability of intact protein barcoding by measuring 132 ubiquitin barcodes in microtiter plates. These results show that intact protein barcoding enables fast and simultaneous detection of library barcodes and intracellular metabolites, opening up new possibilities for mass spectrometry-based barcoding.
2024-10-30 | MSV000096254 | MassIVE
Project description:Species identification of fragmentary bones remains a challenging task in archeology and forensics. A species identification method for such fragmentary bones that has recently attracted interest is the use of bone collagen proteins. We developed a method similar to DNA barcoding that reads collagen protein sequences in bone and automatically determines the species by performing sequence database searches. We tested our method using bone samples from 30 vertebrate species ranging from mammals to fish.
2023-12-14 | PXD045402 | Pride
Project description:A Scalable Epitope Tagging Approach for High Throughput ChIP-seq Analysis ChIP-seq comparison between CRISPR editing cells using epitope antibody and non-editing cells using endogeneous TF antibody
2016-09-01 | E-GEOD-78064 | biostudies-arrayexpress
Project description:Advances in single-cell genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells. Current sequencing based methods for cell lineage analysis depend on low resolution bulk analysis or rely on extensive single cell sequencing which is not scalable and could be biased by functional dependencies. Here we show an integrated biochemical-computational platform for generic single-cell lineage analysis that is retrospective, cost-effective and scalable. It consists of a biochemical-computational pipeline that inputs individual cells, produces targeted single-cell sequencing data and uses it to generate a lineage tree of the input cells. We validated the platform by applying it to cells sampled from an ex vivo grown tree and analyzed its feasibility landscape by computer simulations. We conclude that the platform may serve as a generic tool for lineage analysis and thus pave the way towards large-scale human cell lineage discovery.
2016-04-18 | E-MTAB-4553 | biostudies-arrayexpress
Project description:We present DEFND-seq (DNA and Expression From Nucleosome Depletion), a scalable method for co-sequencing RNA and DNA from single nuclei. In DEFND-seq we treat nuclei with lithium diiodosalicylate to disrupt chromatin and expose genoimc DNA. The nuclei are then tagmented with Tn5 transposase, which fragments and tags gDNA. Tagmented nuclei are loaded into a microfluidic droplet generator which combines nuclei, beads containing transcriptomic and genomic barcodes, and reverse transcription reagents into single droplets. Ultimately two libraries are created, one for nuclear mRNA and one for genomic DNA, with each library containing barcodes linking it to its nuclei of origin, thus allowing simultaneous analysis of single nuclei transcriptomes and genomes. Once nuclei have been depleted of nucleosomes, all steps can be performed using a 10x Chromium Controller and 10x Multiome Kit without further experimental modification.
2023-02-09 | GSE224149 | GEO
Project description:BackgroundTargeted diagnosis and treatment options are dependent on insights drawn from multi-modal analysis of large-scale biomedical datasets. Advances in genomics sequencing, image processing, and medical data management have supported data collection and management within medical institutions. These efforts have produced large-scale datasets and have enabled integrative analyses that provide a more thorough look of the impact of a disease on the underlying system. The integration of large-scale biomedical data commonly involves several complex data transformation steps, such as combining datasets to build feature vectors for learning analysis. Thus, scalable data integration solutions play a key role in the future of targeted medicine. Though large-scale data processing frameworks have shown promising performance for many domains, they fail to support scalable processing of complex datatypes.SolutionTo address these issues and achieve scalable processing of multi-modal biomedical data, we present TraNCE, a framework that automates the difficulties of designing distributed analyses with complex biomedical data types.PerformanceWe outline research and clinical applications for the platform, including data integration support for building feature sets for classification. We show that the system is capable of outperforming the common alternative, based on "flattening" complex data structures, and runs efficiently when alternative approaches are unable to perform at all.
| S-EPMC8434767 | biostudies-literature