Methylation patterns of circulating cell-free DNA (cfDNA) contain rich information about recent cell death events in the body. Here, we present an approach for unbiased determination of the tissue origins of cfDNA, using a reference methylation atlas of 25 human tissues and cell types. The method is validated using in silico simulations as well as in vitro mixes of DNA from different tissue sources at known proportions. We show that plasma cfDNA of healthy donors originates from white blood cells (55%), erythrocyte progenitors (30%), vascular endothelial cells (10%) and hepatocytes (1%). Deconvolution of cfDNA from patients reveals tissue contributions that agree with clinical findings in sepsis, islet transplantation, cancer of the colon, lung, breast and prostate, and cancer of unknown primary. We propose a procedure which can be easily adapted to study the cellular contributors to cfDNA in many settings, opening a broad window into healthy and pathologic human tissue dynamics.

Minimally invasive detection of cell death could prove an invaluable resource in many physiologic and pathologic situations. Cell-free circulating DNA (cfDNA) released from dying cells is emerging as a diagnostic tool for monitoring cancer dynamics and graft failure. However, existing methods rely on differences in DNA sequences in source tissues, so that cell death cannot be identified in tissues with a normal genome. We developed a method of detecting tissue-specific cell death in humans based on tissue-specific methylation patterns in cfDNA. We interrogated tissue-specific methylome databases to identify cell type-specific DNA methylation signatures and developed a method to detect these signatures in mixed DNA samples. We isolated cfDNA from plasma or serum of donors, treated the cfDNA with bisulfite, PCR-amplified the cfDNA, and sequenced it to quantify cfDNA carrying the methylation markers of the cell type of interest. Pancreatic β-cell DNA was identified in the circulation of patients with recently diagnosed type-1 diabetes and islet-graft recipients; oligodendrocyte DNA was identified in patients with relapsing multiple sclerosis; neuronal/glial DNA was identified in patients after traumatic brain injury or cardiac arrest; and exocrine pancreas DNA was identified in patients with pancreatic cancer or pancreatitis. This proof-of-concept study demonstrates that the tissue origins of cfDNA and thus the rate of death of specific cell types can be determined in humans. The approach can be adapted to identify cfDNA derived from any cell type in the body, offering a minimally invasive window for diagnosing and monitoring a broad spectrum of human pathologies as well as providing a better understanding of normal tissue dynamics.

Biallelic inactivation of BRCA1 or BRCA2 is associated with a pattern of genome-wide mutations known as signature 3. By analyzing ∼1,000 breast cancer samples, we confirmed this association and established that germline nonsense and frameshift variants in PALB2, but not in ATM or CHEK2, can also give rise to the same signature. We were able to accurately classify missense BRCA1 or BRCA2 variants known to impair homologous recombination (HR) on the basis of this signature. Finally, we show that epigenetic silencing of RAD51C and BRCA1 by promoter methylation is strongly associated with signature 3 and, in our data set, was highly enriched in basal-like breast cancers in young individuals of African descent.

1Methylation patterns of circulating cell-free DNA (cfDNA) contain rich information about recent 2 cell death events in the body. Here, we present an approach for unbiased determination of the 3 tissue origins of cfDNA, using a reference methylation atlas of 25 human tissues and cell types. 4The method is validated using in silico simulations as well as in vitro mixes of DNA from 5 different tissue sources at known proportions. We show that plasma cfDNA of healthy donors 6 originates from white blood cells (55%), erythrocyte progenitors (30%), vascular endothelial 7 cells (10%) and hepatocytes (1%). Deconvolution of cfDNA from patients reveals tissue 8 contributions that agree with clinical findings in sepsis, islet transplantation, cancer of the 9 colon, lung, breast and prostate, and cancer of unknown primary. We propose a procedure 10 which can be easily adapted to study the cellular contributors to cfDNA in many settings, 11 opening a broad window into healthy and pathologic human tissue dynamics. 12 13

Blood contains cfDNA fragments derived from dying cells 1 . cfDNA has a half-life of ~15 min 2 and, therefore, represents events that occurred close to sampling time. cfDNA analysis is used for assessment of fetus chromosomal aberrations, graft rejection, monitoring tumor dynamics and targeted treatment [3][4][5][6][7] . These applications rely on genetic differences between the host and the tissue of interest. Analysis of CpG methylation in cfDNA is emerging as an alternative independent of genetic alteration 5,[8][9][10][11] . CpG methylation profiles are determined during differentiation and are stable afterwards and, thus, are highly informative about cell identity (for example, liver or lung). However, genetic and methylation-based approaches do not report on recent transcriptional events, as mutations and methylation changes occur over developmental time scales.The basic repeating unit of chromatin is the nucleosome, which is a histone-DNA complex encompassing ~150 base pairs (bp) of DNA 12 . Histone proteins are subject to multiple covalent modifications, which are involved in nearly all aspects of messenger RNA (mRNA) biogenesis [13][14][15][16] . Histone modification patterns reflect recent events related to chromatin regulation and activity of RNA polymerase 13,15 , and different combinations of such modifications mark the location and activity of non-coding regions, enhancers, promoters and gene bodies [17][18][19][20][21][22] . Chromatin immunoprecipitation and sequencing (ChIP-seq) enables genome-wide mapping of histone modifications and provides detailed understanding of the regulatory activity within cells [17][18][19][23][24][25][26][27] .Upon cell death, the genome is fragmented, and chromatin, mostly in the form of nucleosomes, is released into the circulation as cell-free nucleosomes (cf-nucleosomes) 28-30 that retain some histone modifications [31][32][33] . We reasoned that capturing and DNA sequencing of modified nucleosomes from plasma might inform on DNA-related activities, including transcription, within the cells of origin (Fig. 1a). This currently inaccessible epigenetic information extends beyond cfDNA modalities examined to date [4][5][6][7][8][9][10][11][34][35][36][37][38][39][40][41][42][43] .In this study, we performed chromatin immunoprecipitation and sequencing of cell-free nucleosomes directly from human plasma (cfChIP-seq). We show that cfChIP-seq recapitulates the original genomic distribution of modifications associated with transcriptionally active promoters, enhancers and gene bodies, demonstrating that plasma nucleosomes retain the epigenetic information of their

Summary Kinetoplast DNA (kDNA), the trypanosome mitochondrial DNA, contains thousands of minicircles and dozens of maxicircles interlocked in a giant network. Remarkably, Trypanosoma brucei's genome encodes eight PIF1-like helicases, six of which are mitochondrial. We now show that TbPIF2 is essential for maxicircle replication. Maxicircle abundance is controlled by TbPIF2 level, as RNAi of this helicase caused maxicircle loss and its overexpression caused a 3- to 6-fold increase in maxicircle abundance. This regulation of maxicircle level is mediated by the TbHslVU protease. Previous experiments demonstrated that RNAi knockdown of TbHslVU dramatically increased abundance of minicircles and maxicircles, presumably because a positive regulator of their synthesis escaped proteolysis and allowed synthesis to continue. Here we found that TbPIF2 level increases following RNAi of the protease. Therefore this helicase is a TbHslVU substrate and the first example of a positive regulator, thus providing a molecular mechanism for controlling maxicircle replication.

The homologous recombination repair (HRR) pathway repairs DNA double-strand breaks in an error-free manner. Mutations in HRR genes can result in increased mutation rate and genomic rearrangements, and are associated with numerous genetic disorders and cancer. Despite intensive research, the HRR pathway is not yet fully mapped. Phylogenetic profiling analysis, which detects functional linkage between genes using coevolution, is a powerful approach to identify factors in many pathways. Nevertheless, phylogenetic profiling has limited predictive power when analyzing pathways with complex evolutionary dynamics such as the HRR. To map novel HRR genes systematically, we developed clade phylogenetic profiling (CladePP). CladePP detects local coevolution across hundreds of genomes and points to the evolutionary scale (e.g., mammals, vertebrates, animals, plants) at which coevolution occurred. We found that multiscale coevolution analysis is significantly more biologically relevant and sensitive to detect gene function. By using CladePP, we identified dozens of unrecognized genes that coevolved with the HRR pathway, either globally across all eukaryotes or locally in different clades. We validated eight genes in functional biological assays to have a role in DNA repair at both the cellular and organismal levels. These genes are expected to play a role in the HRR pathway and might lead to a better understanding of missing heredity in HRR-associated cancers (e.g., heredity breast and ovarian cancer). Our platform presents an innovative approach to predict gene function, identify novel factors related to different diseases and pathways, and characterize gene evolution.

Background: Tumor-derived circulating cell-free DNA (cfDNA) is present in the plasma of individuals with cancer. Assays aimed at detecting common cancer mutations in cfDNA are being developed for the detection of several cancer types. In breast cancer, however, such assays have failed to detect the disease at a sensitivity relevant for clinical use, in part due to the absence of multiple common mutations that can be co-detected in plasma. Unlike individual mutations that exist only in a subset of tumors, unique DNA methylation patterns are universally present in cells of a common type and therefore may be ideal biomarkers. Here we describe the detection and quantification of breast-derived cfDNA using a breast-specific DNA methylation signature. Patients and methods: We collected plasma from patients with localized breast cancer before and throughout treatment with neoadjuvant chemotherapy and surgery (N ¼ 235 samples). Results: Pretreatment breast cfDNA was detected in patients with localized disease with a sensitivity of 80% at 97% specificity. High breast cfDNA levels were associated with aggressive molecular tumor profiles and metabolic activity of the disease. During neoadjuvant chemotherapy, breast cfDNA levels decreased dramatically. Importantly, the presence of breast cfDNA towards the end of the chemotherapy regimen reflected the existence of residual disease. Conclusion: We propose that breast-specific cfDNA is a universal and powerful marker for the detection and monitoring of breast cancer.