Phenotypes from cell-free DNA

Zukowski, Alexis; Rao, Satyanarayan; Ramachandran, Srinivas

doi:10.1098/rsob.200119

Cited by 12 publications

(14 citation statements)

References 99 publications

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“…Next, let us consider the distributions of DNA fragment sizes. Previous studies reported that cancer cfDNA appears to have shorter fragments that are more strongly digested (Snyder et al 2016;Underhill et al 2016;Mouliere et al 2018a;Sun et al 2018;Markus et al 2021;Guo et al 2020;Zukowski et al 2020). Our results do show differences in cfDNA fragment size distributions, most notably for lupus (Fig.…”

Section: Utility and Discussionsupporting

confidence: 54%

“…New types of liquid biopsy tests based on nucleosome positioning-inspired analysis of cfDNA are sometimes termed "fragmentomics" and "nucleosomics" (Im et al 2021). Fragmentomics analyses have been focused on the distribution of sizes of cfDNA fragments (Snyder et al 2016;Underhill et al 2016;Mouliere et al 2018a;Sun et al 2018;Markus et al 2021;Guo et al 2020;Zukowski et al 2020) as well as the nucleotide patterns at their cut sites (Chandrananda et al 2015). Sizes of cfDNA fragments reflect the contributions of different biological processes such as apoptosis, necrosis and NETosis.…”

Section: Short-termmentioning

confidence: 99%

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NucPosDB: a database of nucleosome positioning in vivo and nucleosomics of cell-free DNA

et al. 2022

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Nucleosome positioning is involved in many gene regulatory processes happening in the cell, and it may change as cells differentiate or respond to the changing microenvironment in a healthy or diseased organism. One important implication of nucleosome positioning in clinical epigenetics is its use in the “nucleosomics” analysis of cell-free DNA (cfDNA) for the purpose of patient diagnostics in liquid biopsies. The rationale for this is that the apoptotic nucleases that digest chromatin of the dying cells mostly cut DNA between nucleosomes. Thus, the short pieces of DNA in body fluids reflect the positions of nucleosomes in the cells of origin. Here, we report a systematic nucleosomics database — NucPosDB — curating published nucleosome positioning datasets in vivo as well as datasets of sequenced cell-free DNA (cfDNA) that reflect nucleosome positioning in situ in the cells of origin. Users can select subsets of the database by a number of criteria and then obtain raw or processed data. NucPosDB also reports the originally determined regions with stable nucleosome occupancy across several individuals with a given condition. An additional section provides a catalogue of computational tools for the analysis of nucleosome positioning or cfDNA experiments and theoretical algorithms for the prediction of nucleosome positioning preferences from DNA sequence. We provide an overview of the field, describe the structure of the database in this context, and demonstrate data variability using examples of different medical conditions. NucPosDB is useful both for the analysis of fundamental gene regulation processes and the training of computational models for patient diagnostics based on cfDNA. The database currently curates ~ 400 publications on nucleosome positioning in cell lines and in situ as well as cfDNA from > 10,000 patients and healthy volunteers. For open-access cfDNA datasets as well as key MNase-seq datasets in human cells, NucPosDB allows downloading processed mapped data in addition to the regions with stable nucleosome occupancy. NucPosDB is available at https://generegulation.org/nucposdb/.

show abstract

Section: Utility and Discussionsupporting

confidence: 54%

Section: Short-termmentioning

confidence: 99%

NucPosDB: a database of nucleosome positioning in vivo and nucleosomics of cell-free DNA

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Next, let us consider the distributions of DNA fragment sizes. Previous studies reported that cancer cfDNA appears to have shorter fragments that are more strongly digested (Snyder et al 2016; Underhill et al 2016; Mouliere et al 2018a; Sun et al 2018; Markus et al 2019; Guo et al 2020; Zukowski et al 2020). Our results do show differences in cfDNA fragment size distributions, most notably for lupus (Figure 4B).…”

Section: Utility and Discussionmentioning

confidence: 99%

“…New types of liquid biopsy tests based on nucleosome positioning-inspired analysis of cfDNA are sometimes termed “fragmentomics” and “nucleosomics” (Im et al 2020). Fragmentomics analyses have been focused on the distribution of sizes of cfDNA fragments (Snyder et al 2016; Underhill et al 2016; Mouliere et al 2018a; Sun et al 2018; Markus et al 2019; Guo et al 2020; Zukowski et al 2020) as well as the nucleotide patterns at their cut sites (Chandrananda et al 2015). Sizes of cfDNA fragments reflect the contributions of different biological processes such as apoptosis, necrosis and NETosis.…”

Section: Introductionmentioning

confidence: 99%

NucPosDB: a database of nucleosome positioning in vivo and nucleosomics of cell-free DNA

Shtumpf

Piroeva

Agrawal

et al. 2021

Preprint

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Nucleosome positioning is involved in many gene regulatory processes happening in the cell and it may change as cells differentiate or respond to the changing microenvironment in a healthy or diseased organism. One important implication of nucleosome positioning in clinical epigenetics is its use in the “nucleosomics” analysis of cell-free DNA (cfDNA) for the purpose of patient diagnostics in liquid biopsies. The rationale for this is that the apoptotic nucleases that digest chromatin of the dying cells mostly cut DNA between nucleosomes. Thus, the short pieces of DNA in body fluids reflect the positions of nucleosomes in the cells of origin. Here we report a systematic nucleosomics database – NucPosDB, curating published nucleosome positioning datasets in vivo as well as datasets of sequenced cell-free DNA (cfDNA) that reflect nucleosome positioning in situ in the cells of origin. Users can select subsets of the database by a number of criteria and then obtain raw or processed data. NucPosDB also reports the originally determined regions with stable nucleosome occupancy across several individuals with a given condition. An additional section provides a catalogue of computational tools for the analysis of nucleosome positioning or cfDNA experiments and theoretical algorithms for the prediction of nucleosome positioning from DNA sequence. We provide an overview of the field, describe the structure of the database in this context and demonstrate data variability using examples of different medical conditions. NucPosDB is useful both for analysis of fundamental gene regulation processes and training computational models for patient diagnostics based on cfDNA. The database currently curates ∼400 publications on nucleosome positioning in cell lines and in situ as well as cfDNA from >10,000 patients and healthy volunteers. For open-access cfDNA datasets as well as key MNase-seq datasets in human cells, NucPosDB allows downloading processed mapped data in addition to the stable-nucleosome regions. NucPosDB is available at https://generegulation.org/nucposdb/.

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“…Interaction of TFs with DNA is fundamental to gene regulation and distinct cell types are defined by unique TF-binding profiles. It is known that cfDNA fragments in plasma maintain information regarding chromatin dynamics and TF binding (61). Previous approaches have averaged the coverage of short and long cfDNA fragments from 1000s of sites in order to infer binding of a single TF (23,29).…”

Section: Discussionmentioning

confidence: 99%

Mapping Transcription Factor-Nucleosome Dynamics from Plasma cfDNA

Rao¹,

Zukowski³

et al. 2021

Preprint

Self Cite

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Cell-free DNA (cfDNA) contains a composite map of the epigenomes of its cells-of-origin. Tissue-specific transcription factor (TF) binding inferred from cfDNA could enable us to track disease states in humans in a minimally invasive manner. Here, by enriching for short cfDNA fragments, we directly map TF footprints at single binding sites from plasma. We show that the enrichment of TF footprints in plasma reflects the binding strength of the TF in cfDNA tissue-of-origin. Based on this principle, we were able to identify the subset of genome-wide binding sites for selected TFs that leave TF-specific footprints in plasma. These footprints enabled us to not only identify the tissue-of-origin of cfDNA but also map the chromatin structure around the factor-bound sites in their cells-of-origin. To ask if we can use these plasma TF footprints to map cancer states, we first defined pure tumor TF signatures in plasma in vivo using estrogen receptor-positive (ER+) breast cancer xenografts. We found that the tumor-specific cfDNA protections of ER-α could distinguish WT, ER-amplified, and ER-mutated xenografts. Further, tumor-specific cfDNA protections of ER-α and FOXA1 reflect TF-specific accessibility across human breast tumors, demonstrating our ability to capture tumor TF binding in plasma. We then scored TF binding in human plasma samples and identified specific binding sites whose plasma TF protections can identify the presence of cancer and specifically breast cancer. Thus, plasma TF footprints enable minimally invasive mapping of the regulatory landscape of cancer in humans.

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Phenotypes from cell-free DNA

Cited by 12 publications

References 99 publications

NucPosDB: a database of nucleosome positioning in vivo and nucleosomics of cell-free DNA

NucPosDB: a database of nucleosome positioning in vivo and nucleosomics of cell-free DNA

NucPosDB: a database of nucleosome positioning in vivo and nucleosomics of cell-free DNA

Mapping Transcription Factor-Nucleosome Dynamics from Plasma cfDNA

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