Accurate and sensitive single-cell-level detection of copy number variations by micro-channel multiple displacement amplification (μcMDA)

Nanoscale ◽  
2018 ◽  
Vol 10 (37) ◽  
pp. 17933-17941 ◽  
Author(s):  
Junji Li ◽  
Na Lu ◽  
Yuhan Tao ◽  
Mengqin Duan ◽  
Yi Qiao ◽  
...  
Keyword(s):  
Single Cell ◽  
Copy Number ◽  
High Performance ◽  
Multiple Displacement Amplification ◽  
Copy Number Variations ◽  
Reaction Vessel ◽  
Single Cell Level ◽  
Micro Channel ◽  
Cell Level ◽  
Cnv Detection

An improved multiple displacement amplification (MDA) approach realized by compressing the geometry of the reaction vessel exhibits high performance for single-cell-level CNV detection.

scholarly journals Single cell sequencing of the small and AT-skewed genome of malaria parasites

2020 ◽  
Author(s):  
Shiwei Liu ◽  
Adam C. Huckaby ◽  
Audrey C. Brown ◽  
Christopher C. Moore ◽  
Ian Burbulis ◽  
...  
Keyword(s):  
Single Cell ◽  
Copy Number ◽  
Mammalian Cells ◽  
Copy Number Variations ◽  
Single Cell Level ◽  
Cell Level ◽  
Single Cell Sequencing ◽  
Base Content ◽  
Amplification Method ◽  
Adaptive Mechanisms

AbstractSingle cell genomics is a rapidly advancing field; however, most techniques are designed for mammalian cells. Here, we present a single cell sequencing pipeline for the intracellular parasite, Plasmodium falciparum, which harbors a relatively small genome with an extremely skewed base content. Through optimization of a quasi-linear genome amplification method, we achieve better targeting of the parasite genome over contaminants and generate coverage levels that allow detection of relatively small copy number variations on a single cell level. These improvements are important for expanding accessibility of single cell approaches to new organisms and for improving the study of adaptive mechanisms.

scholarly journals LINE-1 Retrotransposon expression in cancerous, epithelial and neuronal cells revealed by 5’-single cell RNA-Seq

2021 ◽  
Author(s):  
Wilson McKerrow ◽  
Shane A. Evans ◽  
Azucena Rocha ◽  
John Sedivy ◽  
Nicola Neretti ◽  
...  
Keyword(s):  
Single Cell ◽  
Cancer Cells ◽  
Early Development ◽  
Immune Cells ◽  
Copy Number ◽  
Single Cells ◽  
Single Cell Level ◽  
Rna Seq ◽  
Cell Level ◽  
Mouse Hippocampus

AbstractLINE-1 retrotransposons are known to be expressed in early development, in tumors and in the germline. Less is known about LINE-1 expression at the single cell level, especially outside the context of cancer. Because LINE-1 elements are present at a high copy number, many transcripts that are not driven by the LINE-1 promoter nevertheless terminate at the LINE-1 3’ UTR. Thus, 3’ targeted single cell RNA-seq datasets are not appropriate for studying LINE-1. However, 5’ targeted single cell datasets provide an opportunity to analyze LINE-1 expression at the single cell level. Most LINE-1 copies are 5’ truncated, and a transcript that contains the LINE-1 5’ UTR as its 5’ end is likely to have been transcribed from its promoter. We developed a method, L1-sc (LINE-1 expression for single cells), to quantify LINE-1 expression in 5’ targeted 10x genomics single cell RNA-seq datasets. Our method confirms that LINE-1 expression is high in cancer cells, but low or absent from immune cells. We also find that LINE-1 expression is elevated in epithelial compared to immune cells outside of the context of cancer and that it is also elevated in neurons compared to glia in the mouse hippocampus.

scholarly journals sciCNV: High-throughput paired profiling of transcriptomes and DNA copy number variations at single cell resolution

2020 ◽  
Author(s):  
Ali Mahdipour-Shirayeh ◽  
Natalie Erdmann ◽  
Chungyee Leung-Hagesteijn ◽  
Rodger E. Tiedemann
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Copy Number ◽  
Target Genes ◽  
Single Cells ◽  
Copy Number Variations ◽  
Cellular Reprogramming ◽  
Cellular Effects ◽  
Normalization Methods ◽  
Cnv Detection

SUMMARYChromosome copy number variations (CNVs) are a near-universal feature of cancer however their effects on cellular function are incompletely understood. Single cell RNA sequencing (scRNA-seq) can reveal cellular gene expression however cannot directly link this to CNVs. Here we report new normalization methods (RTAM1 and −2) for scRNA-seq that improve gene expression alignment between cells, enhancing gene expression comparisons and the application of scRNA-seq to CNV detection. We also report sciCNV, a pipeline for inferring CNVs from RTAM-normalized data. Together, these tools provide dual profiling of transcriptomes and CNVs at single-cell resolution, enabling exploration of the effects of cancer CNVs on cellular programs. We apply these tools to multiple myeloma (MM) and examine the cellular effects of cancer CNVs +8q. Consistent with prior reports, MM cells with +8q22-24 upregulate MYC, MYC-target genes, mRNA processing and protein synthesis, verifying the approach. Overall, we provide new tools for scRNA-seq that enable matched profiling of the CNV landscape and transcriptome of single cells, facilitate deconstruction of the effects of cancer CNVs on cellular reprogramming within single samples.

scholarly journals Quantitative comparison of single-cell sequencing methods using hippocampal neurons

2014 ◽  
Author(s):  
Luwen Ning ◽  
Guan Wang ◽  
Zhoufang Li ◽  
Wen Hu ◽  
Qingming Hou ◽  
...  
Keyword(s):  
Single Cell ◽  
Copy Number ◽  
Hippocampal Neurons ◽  
Cancer Biology ◽  
Multiple Displacement Amplification ◽  
Genetic Diagnosis ◽  
Genomic Analysis ◽  
Dna Amplification ◽  
Copy Number Variations ◽  
Cell Genome

Single-cell genomic analysis has grown rapidly in recent years and will find widespread applications in various fields of biology, including cancer biology, development, immunology, pre-implantation genetic diagnosis, and neurobiology. In this study, we amplified genomic DNA from individual hippocampal neurons using one of three single-cell DNA amplification methods (multiple annealing and looping-based amplification cycles (MALBAC), multiple displacement amplification (MDA), and GenomePlex whole genome amplification (WGA4)). We then systematically evaluated the genome coverage, GC-bias, reproducibility, and copy number variations among individual neurons. Our results showed that single-cell genome sequencing results obtained from the MALBAC and WGA4 methods are highly reproducible and have a high success rate. Chromosome-level and subchromosomal-level copy number variations among individual neurons can be detected.

scholarly journals Quantitative comparison of single-cell sequencing methods using hippocampal neurons

2014 ◽  
Author(s):  
Luwen Ning ◽  
Guan Wang ◽  
Zhoufang Li ◽  
Wen Hu ◽  
Qingming Hou ◽  
...  
Keyword(s):  
Single Cell ◽  
Copy Number ◽  
Hippocampal Neurons ◽  
Cancer Biology ◽  
Multiple Displacement Amplification ◽  
Genetic Diagnosis ◽  
Genomic Analysis ◽  
Dna Amplification ◽  
Copy Number Variations ◽  
Cell Genome

Single-cell genomic analysis has grown rapidly in recent years and will find widespread applications in various fields of biology, including cancer biology, development, immunology, pre-implantation genetic diagnosis, and neurobiology. In this study, we amplified genomic DNA from individual hippocampal neurons using one of three single-cell DNA amplification methods (multiple annealing and looping-based amplification cycles (MALBAC), multiple displacement amplification (MDA), and GenomePlex whole genome amplification (WGA4)). We then systematically evaluated the genome coverage, GC-bias, reproducibility, and copy number variations among individual neurons. Our results showed that single-cell genome sequencing results obtained from the MALBAC and WGA4 methods are highly reproducible and have a high success rate. Chromosome-level and subchromosomal-level copy number variations among individual neurons can be detected.

scholarly journals Gene Dosage Analysis on the Single-Cell Transcriptomes Linking Cotranslational Protein Targeting to Metastatic Triple-Negative Breast Cancer

2021 ◽  
Vol 14 (9) ◽  
pp. 918
Author(s):  
Yining Liu ◽  
Min Zhao
Keyword(s):  
Breast Cancer ◽  
Single Cell ◽  
Triple Negative Breast Cancer ◽  
Copy Number ◽  
Triple Negative ◽  
Protein Targeting ◽  
Gene Dosage ◽  
Functional Module ◽  
Single Cell Level ◽  
Cell Level

Many recent efforts have been put into the association between expression heterogeneity and different cell types and states using single-cell RNA transcriptome analysis. There is only limited understanding of gene dosage effects for the genetic heterogeneity at the single-cell level. By focusing on concordant copy number variation (CNV) and expression, we presented a computational framework to explore dosage effect for aggressive metastatic triple-negative breast cancer (TNBC) at the single-cell level. In practice, we collected CNV and single-cell expression data from the same patients with independent technologies. By focusing on 47,198 consistent copy number gains (CNG) and gene up-regulation from 1145 single cells, ribosome proteins with important roles in protein targeting were enriched. Independent validation in another metastatic TNBC dataset further prioritized signal recognition particle-dependent protein targeting as the top functional module. More interesting, the increased ribosome gene copies in TNBC may associate with their enhanced stemness and metastatic potential. Indeed, the prioritization of a well-upregulated functional module confirmed by high copy numbers at the single-cell level and contributing to patient survival may indicate the possibility of targeted therapy based on ribosome proteins for TNBC.

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