Dataset Information

Isolation of nuclei from frozen human subcutaneous adipose tissue for full-length single-nuclei transcriptional profiling.

ABSTRACT: Automated single-cell dispensing is incompatible with white adipose tissue (WAT) due to lipid-laden adipocytes. Single-nuclei RNA-Seq permits transcriptional profiling of all cells from WAT. Human WAT faces unique technical challenges in isolating nuclei compared to rodent tissue due to greater extra-cellular matrix content and larger lipid droplets. In this protocol, we detail how to isolate nuclei from frozen subcutaneous human WAT for single-nuclei RNA-Seq. For complete information on the generation and use of this protocol, please refer to Whytock et al. (2022).¹.

SUBMITTER: Whytock KL

PROVIDER: S-EPMC9876942 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Isolation of nuclei from frozen human subcutaneous adipose tissue for full-length single-nuclei transcriptional profiling.

Whytock Katie L KL Divoux Adeline A Sun Yifei Y Hopf Meghan M Yeo Reichelle X RX Pino Maria F MF Yu GongXin G Smith Steven R SR Walsh Martin J MJ Sparks Lauren M LM

STAR protocols 20230120 1

Automated single-cell dispensing is incompatible with white adipose tissue (WAT) due to lipid-laden adipocytes. Single-nuclei RNA-Seq permits transcriptional profiling of all cells from WAT. Human WAT faces unique technical challenges in isolating nuclei compared to rodent tissue due to greater extra-cellular matrix content and larger lipid droplets. In this protocol, we detail how to isolate nuclei from frozen subcutaneous human WAT for single-nuclei RNA-Seq. For complete information on the gen ...[more]

PMID: 36853719

Similar Datasets

Project description:Adipose tissues have a central role in organisms, and adipose content is a crucial economic trait of poultry. Pekin duck is an ideal model to study the mechanism of abdominal and subcutaneous adipose deposition for its high ability of adipose synthesis and deposition. Alternative splicing contributes to functional diversity in abdominal and subcutaneous adipose. However, there has been no systematic analysis of the dynamics of differential alternative splicing of abdominal and subcutaneous adipose in Pekin duck. In our study, the Pacific Biosciences (PacBio) Iso-Seq technology was applied to explore the transcriptional complexity of abdominal and subcutaneous adipose in Pekin ducks. In total, 143,931 and 111,337 full-length non-chimeric transcriptome sequences of abdominal and subcutaneous adipocytes were obtained from 41.78 GB raw data, respectively. These data led us to identify 19,212 long non-coding RNAs (lncRNAs) and 74,571 alternative splicing events. In addition, combined with the next-generation sequencing technology, we correlated the structure and function annotation with the differential expression profiles of abdominal and subcutaneous adipose transcripts. This study identified lots of novel alternative splicing events and major transcripts of transcription factors related to adipose synthesis. STAT3 was reported as a vital gene for adipogenesis, and we found that its major transcript is STAT3-1, which may play a considerable role in the process of adipose synthesis in Pekin duck. This study greatly increases our understanding of the gene models, genome annotations, genome structures, and the complexity and diversity of abdominal and subcutaneous adipose in Pekin duck. These data provide insights into the regulation of alternative splicing events, which form an essential part of transcript diversity during adipogenesis in poultry. The results of this study provide an invaluable resource for studying alternative splicing and tissue-specific expression.

Dataset Information

Isolation of nuclei from frozen human subcutaneous adipose tissue for full-length single-nuclei transcriptional profiling.

Publications

Isolation of nuclei from frozen human subcutaneous adipose tissue for full-length single-nuclei transcriptional profiling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets