Comparison of Single Molecule, Real-Time Sequencing and Nanopore Sequencing for Analysis of the Size, End-Motif, and Tissue-of-Origin of Long Cell-Free DNA in Plasma.

BACKGROUND: Recent studies using single molecule, real-time (SMRT) sequencing revealed a substantial population of analyzable long cell-free DNA (cfDNA) in plasma. Potential clinical utilities of such long cfDNA in pregnancy and cancer have been demonstrated. However, the performance of different long-read sequencing platforms for the analysis of long cfDNA remains unknown. METHODS: Size biases of SMRT sequencing by Pacific Biosciences (PacBio) and nanopore sequencing by Oxford Nanopore Technologies (ONT) were evaluated using artificial mixtures of sonicated human and mouse DNA of different sizes. cfDNA from plasma samples of pregnant women at different trimesters, hepatitis B carriers, and patients with hepatocellular carcinoma were sequenced with the 2 platforms. RESULTS: Both platforms showed biases to sequence longer (1500 bp vs 200 bp) DNA fragments, with PacBio showing a stronger bias (5-fold overrepresentation of long fragments vs 2-fold in ONT). Percentages of cfDNA fragments 500 bp were around 6-fold higher in PacBio compared with ONT. End motif profiles of cfDNA from PacBio and ONT were similar, yet exhibited platform-dependent patterns. Tissue-of-origin analysis based on single-molecule methylation patterns showed comparable performance on both platforms. CONCLUSIONS: SMRT sequencing generated data with higher percentages of long cfDNA compared with nanopore sequencing. Yet, a higher number of long cfDNA fragments eligible for the tissue-of-origin analysis could be obtained from nanopore sequencing due to its much higher throughput. When analyzing the size and end motif of cfDNA, one should be aware of the analytical characteristics and possible biases of the sequencing platforms being used.

Identification and characterization of extrachromosomal circular DNA in maternal plasma.

We explored the presence of extrachromosomal circular DNA (eccDNA) in the plasma of pregnant women. Through sequencing following either restriction enzyme or Tn5 transposase treatment, we identified eccDNA molecules in the plasma of pregnant women. These eccDNA molecules showed bimodal size distributions peaking at ∼202 and ∼338 bp with distinct 10-bp periodicity observed throughout the size ranges within both peaks, suggestive of their nucleosomal origin. Also, the predominance of the 338-bp peak of eccDNA indicated that eccDNA had a larger size distribution than linear DNA in human plasma. Moreover, eccDNA of fetal origin were shorter than the maternal eccDNA. Genomic annotation of the overall population of eccDNA molecules revealed a preference of these molecules to be generated from 5'-untranslated regions (5'-UTRs), exonic regions, and CpG island regions. Two sets of trinucleotide repeat motifs flanking the junctional sites of eccDNA supported multiple possible models for eccDNA generation. This work highlights the topologic analysis of plasma DNA, which is an emerging direction for circulating nucleic acid research and applications.

Characteristics of Fetal Extrachromosomal Circular DNA in Maternal Plasma: Methylation Status and Clearance.

BACKGROUND: Although the characterization of cell-free extrachromosomal circular DNA (eccDNA) has gained much research interest, the methylation status of these molecules is yet to be elucidated. We set out to compare the methylation densities of plasma eccDNA of maternal and fetal origins, and between small and large molecules. The clearance of fetal eccDNA from maternal circulation was also investigated. METHODS: We developed a sequencing protocol for eccDNA methylation analysis using tagmentation and enzymatic conversion approaches. A restriction enzyme-based approach was applied to verify the tagmentation results. The efficiency of cell-free fetal eccDNA clearance was investigated by fetal eccDNA fraction evaluations at various postpartum time points. RESULTS: The methylation densities of fetal eccDNA (median: 56.3%; range: 40.5-67.6%) were lower than the maternal eccDNA (median: 66.7%; range: 56.5-75.7%) (P = 0.02, paired t-test). In addition, eccDNA molecules from the smaller peak cluster (180-230 bp) were of lower methylation levels than those from the larger peak cluster (300-450 bp). Both of these findings were confirmed using the restriction enzyme approach. We also observed comparable methylation densities between linear and eccDNA of both maternal and fetal origins. The average half-lives of fetal linear and eccDNA in the maternal blood were 30.2 and 29.7 min, respectively. CONCLUSIONS: We found that fetal eccDNA in plasma was relatively hypomethylated compared to the maternal eccDNA. The methylation densities of eccDNA were positively correlated with their sizes. In addition, fetal eccDNA was found to be rapidly cleared from the maternal blood after delivery, similar to fetal linear DNA.

Knowledge-based analyses reveal new candidate genes associated with risk of hepatitis B virus related hepatocellular carcinoma.

BACKGROUND: Recent genome-wide association studies (GWASs) have suggested several susceptibility loci of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) by statistical analysis at individual single-nucleotide polymorphisms (SNPs). However, these loci only explain a small fraction of HBV-related HCC heritability. In the present study, we aimed to identify additional susceptibility loci of HBV-related HCC using advanced knowledge-based analysis. METHODS: We performed knowledge-based analysis (including gene- and gene-set-based association tests) on variant-level association p-values from two existing GWASs of HBV-related HCC. Five different types of gene-sets were collected for the association analysis. A number of SNPs within the gene prioritized by the knowledge-based association tests were selected to replicate genetic associations in an independent sample of 965 cases and 923 controls. RESULTS: The gene-based association analysis detected four genes significantly or suggestively associated with HBV-related HCC risk: SLC39A8, GOLGA8M, SMIM31, and WHAMMP2. The gene-set-based association analysis prioritized two promising gene sets for HCC, cell cycle G1/S transition and NOTCH1 intracellular domain regulates transcription. Within the gene sets, three promising candidate genes (CDC45, NCOR1 and KAT2A) were further prioritized for HCC. Among genes of liver-specific expression, multiple genes previously implicated in HCC were also highlighted. However, probably due to small sample size, none of the genes prioritized by the knowledge-based association analyses were successfully replicated by variant-level association test in the independent sample. CONCLUSIONS: This comprehensive knowledge-based association mining study suggested several promising genes and gene-sets associated with HBV-related HCC risks, which would facilitate follow-up functional studies on the pathogenic mechanism of HCC.

wKGGSeq: A Comprehensive Strategy-Based and Disease-Targeted Online Framework to Facilitate Exome Sequencing Studies of Inherited Disorders.

With the rapid advances in high-throughput sequencing technologies, exome sequencing and targeted region sequencing have become routine approaches for identifying mutations of inherited disorders in both genetics research and molecular diagnosis. There is an imminent need for comprehensive and easy-to-use downstream analysis tools to isolate causal mutations in exome sequencing studies. We have developed a user-friendly online framework, wKGGSeq, to provide systematic annotation, filtration, prioritization, and visualization functions for characterizing causal mutation(s) in exome sequencing studies of inherited disorders. wKGGSeq provides: (1) a novel strategy-based procedure for downstream analysis of a large amount of exome sequencing data and (2) a disease-targeted analysis procedure to facilitate clinical diagnosis of well-studied genetic diseases. In addition, it is also equipped with abundant online annotation functions for sequence variants. We demonstrate that wKGGSeq either outperforms or is comparable to two popular tools in several real exome sequencing samples. This tool will greatly facilitate the downstream analysis of exome sequencing data and can play a useful role for researchers and clinicians in identifying causal mutations of inherited disorders. The wKGGSeq is freely available at http://statgenpro.psychiatry.hku.hk/wkggseq or http://jjwanglab.org/wkggseq, and will be updated frequently.

Systematic analysis of genomic organization and heterogeneities of miRNA cluster in vertebrates.

The clustering propensity of microRNA genes is a common biological phenomenon in various animal and plant species. To gain novel insight into genomic organization and potential functional heterogeneities of miRNA clusters in vertebrates from a genome scale, we used large scale data and presented a comprehensive analysis to examine various features of genomic organization of miRNA clusters across seven vertebrates by a combination of comparative genomics and bioinformatics approaches. The results of pair-wise distance analysis of same-strand consecutive miRNAs suggested that the fractions of the miRNA gene pairs are higher at relatively short pair-wise distances than those of protein-coding genes and other non-coding RNA genes. Especially relatively small number of miRNAs is more clustered at very short pair-wise distances than expected at random. We further observed significant difference between real miRNA clusters and randomly organized clusters for different aspects, including higher overlap of target genes, fewer seed types and significant enrichment in diseases. However, the extent of these features of clustered miRNAs has a different tendency and largely depends on inter-miRNA distances because of diverse clustering propensity of miRNAs in vertebrates, suggesting that this cooperated function or cooperative effects between miRNAs in clusters perhaps be affected by inter-miRNA distances.

Effects of nucleases on cell-free extrachromosomal circular DNA.

Cell-free extrachromosomal circular DNA (eccDNA) as a distinct topological form from linear DNA has recently gained increasing research interest, with possible clinical applications as a class of biomarkers. In this study, we aimed to explore the relationship between nucleases and eccDNA characteristics in plasma. By using knockout mouse models with deficiencies in deoxyribonuclease 1 (DNASE1) or deoxyribonuclease 1 like 3 (DNASE1L3), we found that cell-free eccDNA in Dnase1l3-/- mice exhibited larger size distributions than that in wild-type mice. Such size alterations were not found in tissue eccDNA of either Dnase1-/- or Dnase1l3-/- mice, suggesting that DNASE1L3 could digest eccDNA extracellularly but did not seem to affect intracellular eccDNA. Using a mouse pregnancy model, we observed that in Dnase1l3-/- mice pregnant with Dnase1l3+/- fetuses, the eccDNA in the maternal plasma was shorter compared with that of Dnase1l3-/- mice carrying Dnase1l3-/- fetuses, highlighting the systemic effects of circulating fetal DNASE1L3 degrading the maternal eccDNA extracellularly. Furthermore, plasma eccDNA in patients with DNASE1L3 mutations also exhibited longer size distributions than that in healthy controls. Taken together, this study provided a hitherto missing link between nuclease activity and the biological manifestations of eccDNA in plasma, paving the way for future biomarker development of this special form of DNA molecules.

FAPI: Fast and accurate P-value Imputation for genome-wide association study.

Imputing individual-level genotypes (or genotype imputation) is now a standard procedure in genome-wide association studies (GWAS) to examine disease associations at untyped common genetic variants. Meta-analysis of publicly available GWAS summary statistics can allow more disease-associated loci to be discovered, but these data are usually provided for various variant sets. Thus imputing these summary statistics of different variant sets into a common reference panel for meta-analyses is impossible using traditional genotype imputation methods. Here we develop a fast and accurate P-value imputation (FAPI) method that utilizes summary statistics of common variants only. Its computational cost is linear with the number of untyped variants and has similar accuracy compared with IMPUTE2 with prephasing, one of the leading methods in genotype imputation. In addition, based on the FAPI idea, we develop a metric to detect abnormal association at a variant and showed that it had a significantly greater power compared with LD-PAC, a method that quantifies the evidence of spurious associations based on likelihood ratio. Our method is implemented in a user-friendly software tool, which is available at http://statgenpro.psychiatry.hku.hk/fapi.

SNPTracker: A Swift Tool for Comprehensive Tracking and Unifying dbSNP rs IDs and Genomic Coordinates of Massive Sequence Variants.

The reference single nucleotide polymorphism (rs) ID in dbSNP (http://www.ncbi.nlm.nih.gov/SNP/) is a key resource identifier, which is widely used in human genetics and genomics studies. However, its application is often complicated by the varied IDs of different versions. Here, we developed a user-friendly tool, SNPTracker, for comprehensively tracking and unifying the rs IDs and genomic coordinates of massive sequence variants at a time. It worked perfectly, and had much higher accuracy and capacity than two alternative utilities in our proof-of-principle examples. SNPTracker will greatly facilitate genetic data exchange and integration in the postgenome-wide association study era.

Inferring potential microRNA-microRNA associations based on targeting propensity and connectivity in the context of protein interaction network.

MicroRNAs (miRNAs) are a group of small non-coding RNAs that play important regulatory roles at the post-transcriptional level. Although several computational methods have been developed to compare miRNAs, it is still a challenging and a badly needed task with the availability of various biological data resources. In this study, we proposed a novel graph theoretic property based computational framework and method, called miRFunSim, for quantifying the associations between miRNAs based on miRNAs targeting propensity and proteins connectivity in the integrated protein-protein interaction network. To evaluate the performance of our method, we applied the miRFunSim method to compute functional similarity scores of miRNA pairs between 100 miRNAs whose target genes have been experimentally supported and found that the functional similarity scores of miRNAs in the same family or in the same cluster are significantly higher compared with other miRNAs which are consistent with prior knowledge. Further validation analysis on experimentally verified miRNA-disease associations suggested that miRFunSim can effectively recover the known miRNA pairs associated with the same disease and achieve a higher AUC of 83.1%. In comparison with similar methods, our miRFunSim method can achieve more effective and more reliable performance for measuring the associations of miRNAs. We also conducted the case study examining liver cancer based on our method, and succeeded in uncovering the candidate liver cancer related miRNAs such as miR-34 which also has been proven in the latest study.

Comparative genomic analysis reveals evolutionary characteristics and patterns of microRNA clusters in vertebrates.

MicroRNAs (miRNAs) are a class of small non-coding RNAs that can play important regulatory roles in many important biological processes. Although clustering patterns of miRNA clusters have been uncovered in animals, the origin and evolution of miRNA clusters in vertebrates are still poorly understood. Here, we performed comparative genomic analyses to construct 51 sets of orthologous miRNA clusters (SOMCs) across seven test vertebrate species, a collection of miRNA clusters from two or more species that are likely to have evolved from a common ancestral miRNA cluster, and used these to systematically examine the evolutionary characteristics and patterns of miRNA clusters in vertebrates. We found that miRNA clusters are continuously generated, and most of them tend to be conserved and maintained in vertebrate genomes, although some adaptive gains and losses of miRNA cluster have occurred during evolution. Furthermore, miRNA clusters appeared relatively early in the evolutionary history might suffer from more complicated adaptive gain-and-loss than those young miRNA clusters. Detailed analysis showed that genomic duplication events of ancestral miRNAs or miRNA clusters are likely to be major driving force and apparently contribute to origin and evolution of miRNA clusters. Comparison of conserved with lineage-specific miRNA clusters revealed that the contribution of duplication events for the formation of miRNA cluster appears to be more important for conserved miRNA clusters than lineage-specific. Our study provides novel insights for further exploring the origins and evolution of miRNA clusters in vertebrates at a genome scale.