Gene Expression Nebulas
A data portal of transcriptomic profiles analyzed by a unified pipeline across multiple species

Gene Expression Nebulas

A data portal of transcriptome profiles across multiple species

PRJNA382695: Single-cell Multi-omics Sequencing and Analyses of Human Colorectal Cancer

Source: NCBI / GSE97693
Submission Date: Jul 08 2017
Release Date: Nov 29 2018
Update Date: Nov 30 2018

Summary: Although genomic instability, epigenetic abnormality, and gene expression dysregulation are hallmarks of colorectal cancer, these features have not been simultaneously analyzed at single-cell resolution. Using optimized single-cell multi-omics sequencing together with multi-regional sampling of the primary tumor, lymphatic and distant metastases, we provide insights beyond intratumoral heterogeneity. Genome-wide DNA methylation levels were relatively consistent within a single genetic sub-lineage. The genome-wide DNA demethylation patterns of cancer cells were consistent in all 10 sequenced patients. Our work demonstrates the feasibility of reconstructing genetic lineages, and tracing their epigenomic and transcriptomic dynamics with single-cell multi-omics sequencing.

Overall Design: Single cell RNA-seq and Bisulfite-seq on whole cells or by TrioSeq2.

GEN Datasets:
GEND000035
Strategy:
Species:
Tissue:
Healthy Condition:
Protocol
Growth Protocol: -
Treatment Protocol: Informed consent was obtained from all patients preoperatively. Multi-regional sampling tissues were collected. For each tumor, 3-6 regions, including both surface and center areas, were sampled. Except for the MP of CRC01 which was sampled after six cycles of chemotherapy, other tumors were all sampled before treatment. Patient-derived tumors and adjacent normal tissue were collected and processed immediately after surgical resection. The dissected tissues were then mechanically dissociated and enzymatically digested to single-cell suspension using collagenase type II (Invitrogen, cat. #17101015) and collagenase type IV (Invitrogen, cat. #17104019). For 5 patients (CRC11, CRC12, CRC13, CRC14, and CRC15), leukocytes were depleted by magnetic-activated cell sorting (MACS) (CD45 Microbeads, Miltenyi Biotec, cat. #130-045-801) or fluorescence-activated cell sorting (FACS) (BV421 Mouse Anti-Human CD45, BD Horizon, cat. #563879).
Extract Protocol: The single viable cells were individually picked into 200-uL tubes containing lysis buffer. For scTrio-seq2, we used magnetic beads (Invitrogen, cat. #65011) to separate the nucleus and RNA of one single cell. We added 0.2 ?L magnetic beads to each single-cell lysis buffer. Then the single cells were lysed and vortexed for 1 min to release RNA. The lysis products were then centrifuged at 1,000 × g for 5 min at 4°C, and placed on the magnetic rack for 5 min. The magnetic beads can aggregate on the surface of the nucleus to maintain the nucleus in the pellet, while the RNA was released in the supernatants. The supernatants containing RNA were transferred to a new tube for transcriptome sequencing. The remaining beads containing a single nucleus were re-suspended with lysis buffer of scBS-seq for DNA methylation sequencing"
Library Construction Protocol: For single-cell whole-genome bisulfite sequencing, the scBS-seq libraries were constructed according to the published protocol as described in 2017 (Clark et al., 2017). For CRC01 and CRC02, the transcriptome sequencing libraries were constructed according to Tang protocol (Tang et al., 2009); for the remaining patients, the transcriptome sequencing libraries were constructed according to a multiplexed scRNA-seq method, in which the poly T primers were combined with barcodes and unique molecule identifiers (UMIs) (Dong et al., 2018)."
Sequencing
Molecule Type: poly(A)+ RNA
Library Source:
Library Layout: PAIRED; SINGLE
Library Strand: -; Reverse; Forward
Platform: Illumina
Instrument Model: Illumina HiSeq 4000
Strand-Specific: Unspecific; Specific
Samples
Basic Information:
Sample Characteristic:
Biological Condition:
Experimental Variables:
Protocol:
Sequencing:
Assessing Quality:
Analysis:
Data Resource GEN Sample ID GEN Dataset ID Project ID BioProject ID Sample ID Sample Name BioSample ID Sample Accession Experiment Accession Release Date Submission Date Update Date Species Race Ethnicity Age Age Unit Gender Source Name Tissue Cell Type Cell Subtype Cell Line Disease Disease State Development Stage Mutation Phenotype Case Detail Control Detail Growth Protocol Treatment Protocol Extract Protocol Library Construction Protocol Molecule Type Library Layout Strand-Specific Library Strand Spike-In Strategy Platform Instrument Model Cell Number Reads Number Gbases AvgSpotLen1 AvgSpotLen2 Uniq Mapping Rate Multiple Mapping Rate Coverage Rate
Publications
Single-cell multiomics sequencing and analyses of human colorectal cancer.
Science (New York, N.Y.) . 2018-11-01 [PMID: 30498128]