Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Mar;29(3):418-427.
doi: 10.1101/gr.242719.118.

Orientation-aware plasma cell-free DNA fragmentation analysis in open chromatin regions informs tissue of origin

Kun Sun  1   2 , Peiyong Jiang  1   2 , Suk Hang Cheng  1   2 , Timothy H T Cheng  1   2 , John Wong  3 , Vincent W S Wong  4 , Simon S M Ng  3 , Brigette B Y Ma  5 , Tak Y Leung  6 , Stephen L Chan  5 , Tony S K Mok  5 , Paul B S Lai  3 , Henry L Y Chan  4 , Hao Sun  1   2 , K C Allen Chan  1   2 , Rossa W K Chiu  1   2 , Y M Dennis Lo  1   2
Affiliations

Orientation-aware plasma cell-free DNA fragmentation analysis in open chromatin regions informs tissue of origin

Kun Sun et al. Genome Res. 2019 Mar.

Abstract

Cell-free DNA (cfDNA) in human plasma is a class of biomarkers with many current and potential future diagnostic applications. Recent studies have shown that cfDNA molecules are not randomly fragmented and possess information related to their tissues of origin. Pathologies causing death of cells from particular tissues result in perturbations in the relative distribution of DNA from the affected tissues. Such tissue-of-origin analysis is particularly useful in the development of liquid biopsies for cancer. It is therefore of value to accurately determine the relative contributions of the tissues to the plasma DNA pool in a simultaneous manner. In this work, we report that in open chromatin regions, cfDNA molecules show characteristic fragmentation patterns reflected by sequencing coverage imbalance and differentially phased fragment end signals. The latter refers to differences in the read densities of sequences corresponding to the orientation of the upstream and downstream ends of cfDNA molecules in relation to the reference genome. Such cfDNA fragmentation patterns preferentially occur in tissue-specific open chromatin regions where the corresponding tissues contributed DNA into the plasma. Quantitative analyses of such signals allow measurement of the relative contributions of various tissues toward the plasma DNA pool. These findings were validated by plasma DNA sequencing data obtained from pregnant women, organ transplantation recipients, and cancer patients. Orientation-aware plasma DNA fragmentation analysis therefore has potential diagnostic applications in noninvasive prenatal testing, organ transplantation monitoring, and cancer liquid biopsy.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Conceptual framework of cell-free DNA (cfDNA) fragmentation analysis. (A) Illustration of nucleosomes with wrapped DNA (yellow line), linkers (brown line), and open chromatin regions (green line). An abstraction of nucleosome positioning and illustration of cutting events (scissors) during apoptosis were also provided. (B) Illustration of cfDNA generated from apoptotic DNA fragmentation. DNA wrapped around the nucleosomes is preserved, and that in the linkers and open chromatin regions will be cleaved into small pieces (gray line) that cannot be sequenced efficiently. (C) Illustration of the sequenced reads and extraction of the ends. Red and blue represent upstream (U) and downstream (D) fragment ends, respectively. (D) Genomic coverage; (E) U and D end profiles of cfDNA in relation to the reference genome. (F) Smoothened cfDNA end signals and deduced nucleosome positioning. Purple, brown, and green lines represent nucleosomes, linkers, and open chromatin regions, respectively.
Figure 2.
Figure 2.
cfDNA fragmentation patterns in a nucleosome array region (Chr 12p11.1) in pooled healthy nonpregnant subjects. (A) Raw signal. (B) Smoothened signal. Green dots at the bottom represent the predicted nucleosome center loci by Snyder et al. (2016). (C) Deduced nucleosome positioning.
Figure 3.
Figure 3.
cfDNA fragmentation patterns in pooled healthy nonpregnant subjects in common open chromatin regions (shared by T cells and the liver; deduced nucleosome positioning was also plotted) (A) and embryonic stem cell (ESC)-specific open chromatin regions (B). (C) Illustration of the concept of orientation-aware cfDNA fragmentation (OCF) value. We focused on the center of tissue-specific open chromatin regions and measured the differences between U and D signals in the shaded regions as the OCF value for the corresponding tissue.
Figure 4.
Figure 4.
Quantification of cfDNA fragmentation patterns (OCF values) among various tissues in healthy nonpregnant subjects.
Figure 5.
Figure 5.
Application of cfDNA fragmentation pattern analysis in noninvasive prenatal testing. (A) cfDNA fragmentation patterns in the placenta-specific open chromatin regions in one pregnant case. (B,C) Comparison of OCF values between healthy nonpregnant subjects and pregnant women: (B) T cells; (C) placenta. (D) Correlation between OCF values for the placenta and fetal DNA fractions in a cohort of 26 pregnant women.
Figure 6.
Figure 6.
Application of cfDNA fragmentation pattern analysis in liver transplantation and hepatocellular carcinoma (HCC) patients. (A) Correlation between OCF values for the liver and donor DNA fractions in liver transplantation patients; (B) tumor DNA fraction in HCC cases. (C) Comparison of OCF values for T cells; (D) the liver among healthy nonpregnant subjects and HCC cases (separated into two groups based on the tumor DNA load in plasma).
Figure 7.
Figure 7.
Application of cfDNA fragmentation pattern analysis in colorectal cancer (CRC) and lung cancer patients. (A,B) Comparison of OCF values between healthy nonpregnant subjects and CRC patients: (A) T cells; (B) intestines. (C) Correlation between OCF values for intestines and colonic DNA fractions (deduced by plasma DNA tissue mapping method) in CRC patients. (D,E) Comparison of OCF values between healthy nonpregnant subjects and lung cancer patients: (D) T cells; (E) lungs.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ. 2013. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat Methods 10: 1213–1218. 10.1038/nmeth.2688 - DOI - PMC - PubMed
    1. Bujold D, Morais DAL, Gauthier C, Côté C, Caron M, Kwan T, Chen KC, Laperle J, Markovits AN, Pastinen T, et al. 2016. The International Human Epigenome Consortium data portal. Cell Syst 3: 496–499.e2. 10.1016/j.cels.2016.10.019 - DOI - PubMed
    1. Chan KCA, Jiang P, Chan CW, Sun K, Wong J, Hui EP, Chan SL, Chan WC, Hui DS, Ng SS, et al. 2013a. Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing. Proc Natl Acad Sci 110: 18761–18768. 10.1073/pnas.1313995110 - DOI - PMC - PubMed
    1. Chan KCA, Jiang P, Zheng YW, Liao GJ, Sun H, Wong J, Siu SS, Chan WC, Chan SL, Chan AT, et al. 2013b. Cancer genome scanning in plasma: detection of tumor-associated copy number aberrations, single-nucleotide variants, and tumoral heterogeneity by massively parallel sequencing. Clin Chem 59: 211–224. 10.1373/clinchem.2012.196014 - DOI - PubMed
    1. Chan KCA, Jiang P, Sun K, Cheng YK, Tong YK, Cheng SH, Wong AI, Hudecova I, Leung TY, Chiu RW, et al. 2016. Second generation noninvasive fetal genome analysis reveals de novo mutations, single-base parental inheritance, and preferred DNA ends. Proc Natl Acad Sci 113: E8159–E8168. 10.1073/pnas.1615800113 - DOI - PMC - PubMed

Publication types

LinkOut - more resources