2017
DOI: 10.1186/s13059-016-1133-7
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Single-cell epigenomic variability reveals functional cancer heterogeneity

Abstract: BackgroundCell-to-cell heterogeneity is a major driver of cancer evolution, progression, and emergence of drug resistance. Epigenomic variation at the single-cell level can rapidly create cancer heterogeneity but is difficult to detect and assess functionally.ResultsWe develop a strategy to bridge the gap between measurement and function in single-cell epigenomics. Using single-cell chromatin accessibility and RNA-seq data in K562 leukemic cells, we identify the cell surface marker CD24 as co-varying with chro… Show more

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Cited by 98 publications
(82 citation statements)
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References 60 publications
(54 reference statements)
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“…Switching of surface antigens in parasites may be particularly favorable to parasites under stressful conditions, perhaps including the stress of an immune response, thereby enabling evasion of host immunity. Regardless, these results show that scRNA-seq can reveal rare parasite variants that are, presumably, a result of spontaneous epigenetic changes similar to what has been described in cancer cells 61 or transcriptional noise which was previously characterized in Escherichia coli 62 . An important difference from the situation with cancer cells, however, is that these individual variants may be non-viable and so impossible to obtain as a stable line; thus scRNA-seq may be uniquely able to provide a detailed understanding of their very interesting and informative gene expression.…”
Section: Discussionsupporting
confidence: 70%
“…Switching of surface antigens in parasites may be particularly favorable to parasites under stressful conditions, perhaps including the stress of an immune response, thereby enabling evasion of host immunity. Regardless, these results show that scRNA-seq can reveal rare parasite variants that are, presumably, a result of spontaneous epigenetic changes similar to what has been described in cancer cells 61 or transcriptional noise which was previously characterized in Escherichia coli 62 . An important difference from the situation with cancer cells, however, is that these individual variants may be non-viable and so impossible to obtain as a stable line; thus scRNA-seq may be uniquely able to provide a detailed understanding of their very interesting and informative gene expression.…”
Section: Discussionsupporting
confidence: 70%
“…Advances in cell isolation and single-cell RNA-seq have proven invaluable for elucidating cell-type specific transcriptional signatures, often defined by an ensemble of genes rather than high expression of any single gene ( Dueck et al, 2016 ; Tasic et al, 2016 ), during single time-point embryonic and adult neurogenic events ( Chu et al, 2016 ; DeLaughter et al, 2016 ; Nelson et al, 2016 ; Scholz et al, 2016 ; Tirosh et al, 2016a , 2016b ; Dulken et al, 2017 ; Litzenburger et al, 2017 ). However, the identification of distinct transcriptional signatures associated with dynamic cell populations during cell migratory events has remained challenging and unclear.…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, DE genes can be inferred to be regulated by TF associated with specific motifs or footprints in open chromatin. At the single cell level, Litzenburger et al attempted to combine scRNA-seq and scATAC-seq to identify the target genes whose expression varies when GATA binding site accessibility changes [160]. Cao et al used a LASSO regression model to identify distal peaks which account for the target gene expression change [161].…”
Section: Integration With Rna-seqmentioning
confidence: 99%