Commonly used software tools produce conflicting and overly-optimistic AUPRC values

The precision-recall curve (PRC) and the area under the precision-recall curve (AUPRC) are useful for quantifying classification performance. They are commonly used in situations with imbalanced classes, such as cancer diagnosis and cell type annotation. We evaluate 10 popular tools for plotting PRC and computing AUPRC, which were collectively used in more than 3000 published studies. We find the AUPRC values computed by the tools rank classifiers differently and some tools produce overly-optimistic results.

A long-read sequencing strategy with overlapping linkers on adjacent fragments (OLAF-Seq) for targeted resequencing and enrichment

In this report, we present OLAF-Seq, a novel strategy to construct a long-read sequencing library such that adjacent fragments are linked with end-terminal duplications. We use the CRISPR-Cas9 nickase enzyme and a pool of multiple sgRNAs to perform non-random fragmentation of targeted long DNA molecules (> 300kb) into smaller library-sized fragments (about 20 kbp) in a manner so as to retain physical linkage information (up to 1000 bp) between adjacent fragments. DNA molecules targeted for fragmentation are preferentially ligated with adaptors for sequencing, so this method can enrich targeted regions while taking advantage of the long-read sequencing platforms. This enables the sequencing of target regions with significantly lower total coverage, and the genome sequence within linker regions provides information for assembly and phasing. We demonstrated the validity and efficacy of the method first using phage and then by sequencing a panel of 100 full-length cancer-related genes (including both exons and introns) in the human genome. When the designed linkers contained heterozygous genetic variants, long haplotypes could be established. This sequencing strategy can be readily applied in both PacBio and Oxford Nanopore platforms for both long and short genes with an easy protocol. This economically viable approach is useful for targeted enrichment of hundreds of target genomic regions and where long no-gap contigs need deep sequencing.

Commonly used software tools produce conflicting and overly-optimistic AUPRC values

The precision-recall curve (PRC) and the area under it (AUPRC) are useful for quantifying classification performance. They are commonly used in situations with imbalanced classes, such as cancer diagnosis and cell type annotation. We evaluated 10 popular tools for plotting PRC and computing AUPRC, which were collectively used in >3,000 published studies. We found the AUPRC values computed by the tools rank classifiers differently and some tools produce overly-optimistic results.

Accurate identification of structural variations from cancer samples

Structural variations (SVs) are commonly found in cancer genomes. They can cause gene amplification, deletion and fusion, among other functional consequences. With an average read length of hundreds of kilobases, nano-channel-based optical DNA mapping is powerful in detecting large SVs. However, existing SV calling methods are not tailored for cancer samples, which have special properties such as mixed cell types and sub-clones. Here we propose the Cancer Optical Mapping for detecting Structural Variations (COMSV) method that is specifically designed for cancer samples. It shows high sensitivity and specificity in benchmark comparisons. Applying to cancer cell lines and patient samples, COMSV identifies hundreds of novel SVs per sample.

DNA methylation markers for kidney function and progression of diabetic kidney disease

Epigenetic markers are potential biomarkers for diabetes and related complications. Using a prospective cohort from the Hong Kong Diabetes Register, we perform two independent epigenome-wide association studies to identify methylation markers associated with baseline estimated glomerular filtration rate (eGFR) and subsequent decline in kidney function (eGFR slope), respectively, in 1,271 type 2 diabetes subjects. Here we show 40 (30 previously unidentified) and eight (all previously unidentified) CpG sites individually reach epigenome-wide significance for baseline eGFR and eGFR slope, respectively. We also develop a multisite analysis method, which selects 64 and 37 CpG sites for baseline eGFR and eGFR slope, respectively. These models are validated in an independent cohort of Native Americans with type 2 diabetes. Our identified CpG sites are near genes enriched for functional roles in kidney diseases, and some show association with renal damage. This study highlights the potential of methylation markers in risk stratification of kidney disease among type 2 diabetes individuals.

The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles

A promising alternative to comprehensively performing genomics experiments is to, instead, perform a subset of experiments and use computational methods to impute the remainder. However, identifying the best imputation methods and what measures meaningfully evaluate performance are open questions. We address these questions by comprehensively analyzing 23 methods from the ENCODE Imputation Challenge. We find that imputation evaluations are challenging and confounded by distributional shifts from differences in data collection and processing over time, the amount of available data, and redundancy among performance measures. Our analyses suggest simple steps for overcoming these issues and promising directions for more robust research.

ICI efficacy information portal: a knowledgebase for responder prediction to immune checkpoint inhibitors

Immune checkpoint inhibitors (ICIs) have led to durable responses in cancer patients, yet their efficacy varies significantly across cancer types and patients. To stratify patients based on their potential clinical benefits, there have been substantial research efforts in identifying biomarkers and computational models that can predict the efficacy of ICIs, and it has become difficult to keep track of all of them. It is also difficult to compare findings of different studies since they involve different cancer types, ICIs, and various other details. To make it easy to access the latest information about ICI efficacy, we have developed a knowledgebase and a corresponding web-based portal (https://iciefficacy.org/). Our knowledgebase systematically records information about latest publications related to ICI efficacy, predictors proposed, and datasets used to test them. All information recorded is checked carefully by a manual curation process. The web-based portal provides functions to browse, search, filter, and sort the information. Digests of method details are provided based on the original descriptions in the publications. Evaluation results of the effectiveness of the predictors reported in the publications are summarized for quick overviews. Overall, our resource provides centralized access to the burst of information produced by the vibrant research on ICI efficacy.

Hypomorphic and dominant-negative impact of truncated SOX9 dysregulates Hedgehog-Wnt signaling, causing campomelia

Haploinsufficiency for SOX9, the master chondrogenesis transcription factor, can underlie campomelic dysplasia (CD), an autosomal dominant skeletal malformation syndrome, because heterozygous Sox9 null mice recapitulate the bent limb (campomelia) and some other phenotypes associated with CD. However, in vitro cell assays suggest haploinsufficiency may not apply for certain mutations, notably those that truncate the protein, but in these cases in vivo evidence is lacking and underlying mechanisms are unknown. Here, using conditional mouse mutants, we compared the impact of a heterozygous Sox9 null mutation (Sox9+/-) with the Sox9+/Y440X CD mutation that truncates the C-terminal transactivation domain but spares the DNA-binding domain. While some Sox9+/Y440X mice survived, all Sox9+/- mice died perinatally. However, the skeletal defects were more severe and IHH signaling in developing limb cartilage was significantly enhanced in Sox9+/Y440X compared with Sox9+/-. Activating Sox9Y440X specifically in the chondrocyte-osteoblast lineage caused milder campomelia, and revealed cell- and noncell autonomous mechanisms acting on chondrocyte differentiation and osteogenesis in the perichondrium. Transcriptome analyses of developing Sox9+/Y440X limbs revealed dysregulated expression of genes for the extracellular matrix, as well as changes consistent with aberrant WNT and HH signaling. SOX9Y440X failed to interact with β-catenin and was unable to suppress transactivation of Ihh in cell-based assays. We propose enhanced HH signaling in the adjacent perichondrium induces asymmetrically localized excessive perichondrial osteogenesis resulting in campomelia. Our study implicates combined haploinsufficiency/hypomorphic and dominant-negative actions of SOX9Y440X, cell-autonomous and noncell autonomous mechanisms, and dysregulated WNT and HH signaling, as the cause of human campomelia.

Accurate reconstruction of viral genomes in human cells from short reads using iterative refinement

BACKGROUND

After an infection, human cells may contain viral genomes in the form of episomes or integrated DNA. Comparing the genomic sequences of different strains of a virus in human cells can often provide useful insights into its behaviour, activity and pathology, and may help develop methods for disease prevention and treatment. To support such comparative analyses, the viral genomes need to be accurately reconstructed from a large number of samples. Previous efforts either rely on customized experimental protocols or require high similarity between the sequenced genomes and a reference, both of which limit the general applicability of these approaches. In this study, we propose a pipeline, named ASPIRE, for reconstructing viral genomes accurately from short reads data of human samples, which are increasingly available from genome projects and personal genomics. ASPIRE contains a basic part that involves de novo assembly, tiling and gap filling, and additional components for iterative refinement, sequence corrections and wrapping.

RESULTS

Evaluated by the alignment quality of sequencing reads to the reconstructed genomes, these additional components improve the assembly quality in general, and in some particular samples quite substantially, especially when the sequenced genome is significantly different from the reference. We use ASPIRE to reconstruct the genomes of Epstein Barr Virus (EBV) from the whole-genome sequencing data of 61 nasopharyngeal carcinoma (NPC) samples and provide these sequences as a resource for EBV research.

CONCLUSIONS

ASPIRE improves the quality of the reconstructed EBV genomes in published studies and outperforms TRACESPipe in some samples considered.

Deep learning identifies and quantifies recombination hotspot determinants

MOTIVATION

Recombination is one of the essential genetic processes for sexually reproducing organisms, which can happen more frequently in some regions, called recombination hotspots. Although several factors, such as PRDM9 binding motifs, are known to be related to the hotspots, their contributions to the recombination hotspots have not been quantified, and other determinants are yet to be elucidated. Here, we propose a computational method, RHSNet, based on deep learning and signal processing, to identify and quantify the hotspot determinants in a purely data-driven manner, utilizing datasets from various studies, populations, sexes and species.

RESULTS

RHSNet can significantly outperform other sequence-based methods on multiple datasets across different species, sexes and studies. In addition to being able to identify hotspot regions and the well-known determinants accurately, more importantly, RHSNet can quantify the determinants that contribute significantly to the recombination hotspot formation in the relation between PRDM9 binding motif, histone modification and GC content. Further cross-sex, cross-population and cross-species studies suggest that the proposed method has the generalization power and potential to identify and quantify the evolutionary determinant motifs.

AVAILABILITY AND IMPLEMENTATION

https://github.com/frankchen121212/RHSNet.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Quantifying full-length circular RNAs in cancer

Circular RNAs (circRNAs) are abundantly expressed in cancer. Their resistance to exonucleases enables them to have potentially stable interactions with different types of biomolecules. Alternative splicing can create different circRNA isoforms that have different sequences and unequal interaction potentials. The study of circRNA function thus requires knowledge of complete circRNA sequences. Here we describe psirc, a method that can identify full-length circRNA isoforms and quantify their expression levels from RNA sequencing data. We confirm the effectiveness and computational efficiency of psirc using both simulated and actual experimental data. Applying psirc on transcriptome profiles from nasopharyngeal carcinoma and normal nasopharynx samples, we discover and validate circRNA isoforms differentially expressed between the two groups. Compared with the assumed circular isoforms derived from linear transcript annotations, some of the alternatively spliced circular isoforms have 100 times higher expression and contain substantially fewer microRNA response elements, showing the importance of quantifying full-length circRNA isoforms.

Sirtuin 7 super-enhancer drives epigenomic reprogramming in hepatocarcinogenesis

Hepatocellular carcinoma (HCC) is a major cancer burden worldwide with increasing incidence in many developed countries. Super-enhancers (SEs) drive gene expressions required for cell type-specificity and tumor cell identity. However, their roles in HCC remain unclear because of data scarcity from primary tumors. Herein, chromatin profiling of non-alcoholic fatty liver disease (NAFLD)-associated HCCs and matched liver tissues uncovered an average of ∼500 somatically-acquired SEs per patient. The identified SE-target genes were functionally enriched for aberrant metabolism and cancer phenotypes, especially chromatin regulators including deacetylases and Polycomb repressive complexes. Notably, all examined tumors exhibited SE activation of Sirtuin 7 (SIRT7), genome-wide promoter H3K18 deacetylation and concurrent H3K27me3, as well as tumor-suppressor gene silencing. Depletion of SIRT7 SE in hepatoma cells induced global H3K18 acetylation and reactivated key metabolic and immune regulators, leading to marked suppression of tumorigenicity in vitro and in vivo. In concordance, SIRT7 physically interacted with the methyltransferase EZH2, and they were co-expressed in primary HCCs. In summary, our integrative analysis establishes a compendium of SEs in NAFLD-associated HCCs and uncovers SIRT7-driven chromatin regulatory network as potential druggable vulnerability of this increasingly prevalent cancer.

Identification and characterization of a novel Epstein-Barr Virus-encoded circular RNA from LMP-2 Gene

Epstein-Barr virus (EBV) has been recently found to generate novel circular RNAs (circRNAs) through backsplicing. However, comprehensive catalogs of EBV circRNAs in other cell lines and their functional characterization are still lacking. In this study, we have identified a list of putative EBV circRNAs in GM12878, an EBV-transformed lymphoblastoid cell line, with a significant majority encoded from the EBV latent genes. A novel EBV circRNA derived from the exon 5 of LMP-2 gene which exhibited highest prevalence, was further validated using RNase R assay and Sanger sequencing. This circRNA, which we term circLMP-2_e5, can be universally detected in a panel of EBV-positive cell lines modelling different latency programs. It ranges from lower expression in nasopharyngeal carcinoma (NPC) cells to higher expression in B cells, and is localized to both the cytoplasm and the nucleus. We provide evidence that circLMP-2_e5 is expressed concomitantly with its cognate linear LMP-2 RNA upon EBV lytic reactivation, and may be produced as a result of exon skipping, with its circularization possibly occurring without the involvement of cis elements in the short flanking introns. Furthermore, we show that circLMP-2_e5 is not involved in regulating cell proliferation, host innate immune response, its linear parental transcripts, or EBV lytic reactivation. Taken together, our study expands the current repertoire of putative EBV circRNAs, broadens our understanding of the biology of EBV circRNAs, and lays the foundation for further investigation of their function in the EBV life cycle and disease development.

Whole-genome profiling of nasopharyngeal carcinoma reveals viral-host co-operation in inflammatory NF-κB activation and immune escape

Interplay between EBV infection and acquired genetic alterations during nasopharyngeal carcinoma (NPC) development remains vague. Here we report a comprehensive genomic analysis of 70 NPCs, combining whole-genome sequencing (WGS) of microdissected tumor cells with EBV oncogene expression to reveal multiple aspects of cellular-viral co-operation in tumorigenesis. Genomic aberrations along with EBV-encoded LMP1 expression underpin constitutive NF-κB activation in 90% of NPCs. A similar spectrum of somatic aberrations and viral gene expression undermine innate immunity in 79% of cases and adaptive immunity in 47% of cases; mechanisms by which NPC may evade immune surveillance despite its pro-inflammatory phenotype. Additionally, genomic changes impairing TGFBR2 promote oncogenesis and stabilize EBV infection in tumor cells. Fine-mapping of CDKN2A/CDKN2B deletion breakpoints reveals homozygous MTAP deletions in 32-34% of NPCs that confer marked sensitivity to MAT2A inhibition. Our work concludes that NPC is a homogeneously NF-κB-driven and immune-protected, yet potentially druggable, cancer.

A general near-exact k-mer counting method with low memory consumption enables de novo assembly of 106× human sequence data in 2.7 hours

MOTIVATION

In de novo sequence assembly, a standard pre-processing step is k-mer counting, which computes the number of occurrences of every length-k sub-sequence in the sequencing reads. Sequencing errors can produce many k-mers that do not appear in the genome, leading to the need for an excessive amount of memory during counting. This issue is particularly serious when the genome to be assembled is large, the sequencing depth is high, or when the memory available is limited.

RESULTS

Here, we propose a fast near-exact k-mer counting method, CQF-deNoise, which has a module for dynamically removing noisy false k-mers. It automatically determines the suitable time and number of rounds of noise removal according to a user-specified wrong removal rate. We tested CQF-deNoise comprehensively using data generated from a diverse set of genomes with various data properties, and found that the memory consumed was almost constant regardless of the sequencing errors while the noise removal procedure had minimal effects on counting accuracy. Compared with four state-of-the-art k-mer counting methods, CQF-deNoise consistently performed the best in terms of memory usage, consuming 49-76% less memory than the second best method. When counting the k-mers from a human dataset with around 60× coverage, the peak memory usage of CQF-deNoise was only 10.9 GB (gigabytes) for k = 28 and 21.5 GB for k = 55. De novo assembly of 106× human sequencing data using CQF-deNoise for k-mer counting required only 2.7 h and 90 GB peak memory.

AVAILABILITY AND IMPLEMENTATION

The source codes of CQF-deNoise and SH-assembly are available at https://github.com/Christina-hshi/CQF-deNoise.git and https://github.com/Christina-hshi/SH-assembly.git, respectively, both under the BSD 3-Clause license.

Horseshoe crab genomes reveal the evolution of genes and microRNAs after three rounds of whole genome duplication

Whole genome duplication (WGD) has occurred in relatively few sexually reproducing invertebrates. Consequently, the WGD that occurred in the common ancestor of horseshoe crabs ~135 million years ago provides a rare opportunity to decipher the evolutionary consequences of a duplicated invertebrate genome. Here, we present a high-quality genome assembly for the mangrove horseshoe crab Carcinoscorpius rotundicauda (1.7 Gb, N50 = 90.2 Mb, with 89.8% sequences anchored to 16 pseudomolecules, 2n = 32), and a resequenced genome of the tri-spine horseshoe crab Tachypleus tridentatus (1.7 Gb, N50 = 109.7 Mb). Analyses of gene families, microRNAs, and synteny show that horseshoe crabs have undergone three rounds (3R) of WGD. Comparison of C. rotundicauda and T. tridentatus genomes from populations from several geographic locations further elucidates the diverse fates of both coding and noncoding genes. Together, the present study represents a cornerstone for improving our understanding of invertebrate WGD events on the evolutionary fates of genes and microRNAs, at both the individual and population level. We also provide improved genomic resources for horseshoe crabs, of applied value for breeding programs and conservation of this fascinating and unusual invertebrate lineage.

G9a Plays Distinct Roles in Maintaining DNA Methylation, Retrotransposon Silencing, and Chromatin Looping

G9a is a lysine methyltransferase that regulates epigenetic modifications, transcription, and genome organization. However, whether these properties are dependent on one another or represent distinct functions of G9a remains unclear. In this study, we observe widespread DNA methylation loss in G9a depleted and catalytic mutant embryonic stem cells. Furthermore, we define how G9a regulates chromatin accessibility, epigenetic modifications, and transcriptional silencing in both catalytic-dependent and -independent manners. Reactivated retrotransposons provide alternative promoters and splice sites leading to the upregulation of neighboring genes and the production of chimeric transcripts. Moreover, while topologically associated domains and compartment A/B definitions are largely unaffected, the loss of G9a leads to altered chromatin states, aberrant CTCF and cohesin binding, and differential chromatin looping, especially at retrotransposons. Taken together, our findings reveal how G9a regulates the epigenome, transcriptome, and higher-order chromatin structures in distinct mechanisms.

Detection of Hole Pockets in the Candidate Type-II Weyl Semimetal MoTe_{2} from Shubnikov-de Haas Quantum Oscillations

The bulk electronic structure of T_{d}-MoTe_{2} features large hole Fermi pockets at the Brillouin zone center (Γ) and two electron Fermi surfaces along the Γ-X direction. However, the large hole pockets, whose existence has important implications for the Weyl physics of T_{d}-MoTe_{2}, has never been conclusively detected in quantum oscillations. This raises doubt about the realizability of Majorana states in T_{d}-MoTe_{2}, because these exotic states rely on the existence of Weyl points, which originated from the same band structure predicted by density functional theory (DFT). Here, we report an unambiguous detection of these elusive hole pockets via Shubnikov-de Haas (SdH) quantum oscillations. At ambient pressure, the quantum oscillation frequencies for these pockets are 988 and 1513 T, when the magnetic field is applied along the c axis. The quasiparticle effective masses m^{*} associated with these frequencies are 1.50 and 2.77 m_{e}, respectively, indicating the importance of Coulomb interactions in this system. We further measure the SdH oscillations under pressure. At 13 kbar, we detected a peak at 1798 T with m^{*}=2.86m_{e}. Relative to the oscillation data at a lower pressure, the amplitude of this peak experienced an enhancement, which can be attributed to the reduced curvature of the hole pockets under pressure. Combining our experimental data with DFT+U calculations, where U is the Hubbard parameter, our results shed light on why these important hole pockets have not been detected until now.

Flexible k-mers with variable-length indels for identifying binding sequences of protein dimers

Many DNA-binding proteins interact with partner proteins. Recently, based on the high-throughput consecutive affinity-purification systematic evolution of ligands by exponential enrichment (CAP-SELEX) method, many such protein pairs have been found to bind DNA with flexible spacing between their individual binding motifs. Most existing motif representations were not designed to capture such flexibly spaced regions. In order to computationally discover more co-binding events without prior knowledge about the identities of the co-binding proteins, a new representation is needed. We propose a new class of sequence patterns that flexibly model such variable regions and corresponding algorithms that identify co-bound sequences using these patterns. Based on both simulated and CAP-SELEX data, features derived from our sequence patterns lead to better classification performance than patterns that do not explicitly model the variable regions. We also show that even for standard ChIP-seq data, this new class of sequence patterns can help discover co-bound events in a subset of sequences in an unsupervised manner. The open-source software is available at https://github.com/kevingroup/glk-SVM.

A comprehensive web tool for toehold switch design

Motivation

Toehold switches are a class of RNAs with a hairpin loop that can be unfolded upon binding a trigger RNA, thereby exposing a ribosome binding site (RBS) and permitting translation of the reporter protein. They have been shown very useful in detecting a variety of targets including RNAs from Zika and Ebola viruses. The base complementation between the toehold switch and the trigger RNA also makes it sensitive to sequence variations. Design of toehold switches involves a series of considerations related to their sequence properties, structures and specificities.

Results

Here we present the first comprehensive web tool for designing toehold switches. We also propose a score for predicting the efficacy of designed toehold switches based on properties learned from ∼180 experimentally tested switches.

Availability and implementation

The toehold switch web tool is available at https://yiplab.cse.cuhk.edu.hk/toehold/.

A network approach to exploring the functional basis of gene-gene epistatic interactions in disease susceptibility

Motivation

Individual genetic variants explain only a small fraction of heritability in some diseases. Some variants have weak marginal effects on disease risk, but their joint effects are significantly stronger when occurring together. Most studies on such epistatic interactions have focused on methods for identifying the interactions and interpreting individual cases, but few have explored their general functional basis. This was due to the lack of a comprehensive list of epistatic interactions and uncertainties in associating variants to genes.

Results

We conducted a large-scale survey of published research articles to compile the first comprehensive list of epistatic interactions in human diseases with detailed annotations. We used various methods to associate these variants to genes to ensure robustness. We found that these genes are significantly more connected in protein interaction networks, are more co-expressed and participate more often in the same pathways. We demonstrate using the list to discover novel disease pathways.

Contact

kevinyip@cse.cuhk.edu.hk.

Supplementary information

Supplementary data are available at Bioinformatics online.

Loss of tumor suppressor IGFBP4 drives epigenetic reprogramming in hepatic carcinogenesis

Genomic sequencing of hepatocellular carcinoma (HCC) uncovers a paucity of actionable mutations, underscoring the necessity to exploit epigenetic vulnerabilities for therapeutics. In HCC, EZH2-mediated H3K27me3 represents a major oncogenic chromatin modification, but how it modulates the therapeutic vulnerability of signaling pathways remains unknown. Here, we show EZH2 acts antagonistically to AKT signaling in maintaining H3K27 methylome through epigenetic silencing of IGFBP4. ChIP-seq revealed enrichment of Ezh2/H3K27me3 at silenced loci in HBx-transgenic mouse-derived HCCs, including Igfbp4 whose down-regulation significantly correlated with EZH2 overexpression and poor survivals of HCC patients. Functional characterizations demonstrated potent growth- and invasion-suppressive functions of IGFBP4, which was associated with transcriptomic alterations leading to deregulation of multiple signaling pathways. Mechanistically, IGFBP4 stimulated AKT/EZH2 phosphorylation to abrogate H3K27me3-mediated silencing, forming a reciprocal feedback loop that suppressed core transcription factor networks (FOXA1/HNF1A/HNF4A/KLF9/NR1H4) for normal liver homeostasis. Consequently, the in vivo tumorigenicity of IGFBP4-silenced HCC cells was vulnerable to pharmacological inhibition of EZH2, but not AKT. Our study unveils chromatin regulation of a novel liver tumor suppressor IGFBP4, which constitutes an AKT-EZH2 reciprocal loop in driving H3K27me3-mediated epigenetic reprogramming. Defining the aberrant chromatin landscape of HCC sheds light into the mechanistic basis of effective EZH2-targeted inhibition.

OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps

BACKGROUND

Optical mapping is an emerging technology that complements sequencing-based methods in genome analysis. It is widely used in improving genome assemblies and detecting structural variations by providing information over much longer (up to 1 Mb) reads. Current standards in optical mapping analysis involve assembling optical maps into contigs and aligning them to a reference, which is limited to pairwise comparison and becomes bias-prone when analyzing multiple samples.

FINDINGS

We present a new method, OMMA, that extends optical mapping to the study of complex genomic features by simultaneously interrogating optical maps across many samples in a reference-independent manner. OMMA captures and characterizes complex genomic features, e.g., multiple haplotypes, copy number variations, and subtelomeric structures when applied to 154 human samples across the 26 populations sequenced in the 1000 Genomes Project. For small genomes such as pathogenic bacteria, OMMA accurately reconstructs the phylogenomic relationships and identifies functional elements across 21 Acinetobacter baumannii strains.

CONCLUSIONS

With the increasing data throughput of optical mapping system, the use of this technology in comparative genome analysis across many samples will become feasible. OMMA is a timely solution that can address such computational need. The OMMA software is available at https://github.com/TF-Chan-Lab/OMTools.

Shaping the nebulous enhancer in the era of high-throughput assays and genome editing

Since the 1st discovery of transcriptional enhancers in 1981, their textbook definition has remained largely unchanged in the past 37 years. With the emergence of high-throughput assays and genome editing, which are switching the paradigm from bottom-up discovery and testing of individual enhancers to top-down profiling of enhancer activities genome-wide, it has become increasingly evidenced that this classical definition has left substantial gray areas in different aspects. Here we survey a representative set of recent research articles and report the definitions of enhancers they have adopted. The results reveal that a wide spectrum of definitions is used usually without the definition stated explicitly, which could lead to difficulties in data interpretation and downstream analyses. Based on these findings, we discuss the practical implications and suggestions for future studies.

New guidelines for DNA methylome studies regarding 5-hydroxymethylcytosine for understanding transcriptional regulation

Many DNA methylome profiling methods cannot distinguish between 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). Because 5mC typically acts as a repressive mark whereas 5hmC is an intermediate form during active demethylation, the inability to separate their signals could lead to incorrect interpretation of the data. Is the extra information contained in 5hmC signals worth the additional experimental and computational costs? Here we combine whole-genome bisulfite sequencing (WGBS) and oxidative WGBS (oxWGBS) data in various human tissues to investigate the quantitative relationships between gene expression and the two forms of DNA methylation at promoters, transcript bodies, and immediate downstream regions. We find that 5mC and 5hmC signals correlate with gene expression in the same direction in most samples. Considering both types of signals increases the accuracy of expression levels inferred from methylation data by a median of 18.2% as compared to having only WGBS data, showing that the two forms of methylation provide complementary information about gene expression. Differential analysis between matched tumor and normal pairs is particularly affected by the superposition of 5mC and 5hmC signals in WGBS data, with at least 25%–40% of the differentially methylated regions (DMRs) identified from 5mC signals not detected from WGBS data. Our results also confirm a previous finding that methylation signals at transcript bodies are more indicative of gene expression levels than promoter methylation signals. Overall, our study provides data for evaluating the cost-effectiveness of some experimental and analysis options in the study of DNA methylation in normal and cancer samples.

Establishment and characterization of new tumor xenografts and cancer cell lines from EBV-positive nasopharyngeal carcinoma

The lack of representative nasopharyngeal carcinoma (NPC) models has seriously hampered research on EBV carcinogenesis and preclinical studies in NPC. Here we report the successful growth of five NPC patient-derived xenografts (PDXs) from fifty-eight attempts of transplantation of NPC specimens into NOD/SCID mice. The take rates for primary and recurrent NPC are 4.9% and 17.6%, respectively. Successful establishment of a new EBV-positive NPC cell line, NPC43, is achieved directly from patient NPC tissues by including Rho-associated coiled-coil containing kinases inhibitor (Y-27632) in culture medium. Spontaneous lytic reactivation of EBV can be observed in NPC43 upon withdrawal of Y-27632. Whole-exome sequencing (WES) reveals a close similarity in mutational profiles of these NPC PDXs with their corresponding patient NPC. Whole-genome sequencing (WGS) further delineates the genomic landscape and sequences of EBV genomes in these newly established NPC models, which supports their potential use in future studies of NPC.

The lack of appropriate models restricts pre-clinical research for nasopharyngeal carcinoma (NPC). Here the authors report the development and characterization of NPC patient-derived xenografts (PDXs), and EBV positive NPC cell line from patient tumor, and suggest their potential use in future NPC research.

OMBlast: alignment tool for optical mapping using a seed-and-extend approach

Motivation

Optical mapping is a technique for capturing fluorescent signal patterns of long DNA molecules (in the range of 0.1–1 Mbp). Recently, it has been complementing the widely used short-read sequencing technology by assisting with scaffolding and detecting large and complex structural variations (SVs). Here, we introduce a fast, robust and accurate tool called OMBlast for aligning optical maps, the set of signal locations on the molecules generated from optical mapping. Our method is based on the seed-and-extend approach from sequence alignment, with modifications specific to optical mapping.

Results

Experiments with both synthetic and our real data demonstrate that OMBlast has higher accuracy and faster mapping speed than existing alignment methods. Our tool also shows significant improvement when aligning data with SVs.

Availability and Implementation

OMBlast is implemented for Java 1.7 and is released under a GPL license. OMBlast can be downloaded from https://github.com/aldenleung/OMBlast and run directly on machines equipped with a Java virtual machine.

Supplementary information

Supplementary data are available at Bioinformatics online

Abstract 482: Epstein-Barr virus-encoded miRNAs target ATM-mediated response in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a highly invasive epithelial malignancy that is prevalence in southern China and Southeast Asia. It is well-known to be associated with latent Epstein-Barr virus (EBV) infection. By using small RNA sequencing, we previously established a comprehensive miRNA profile in a panel of NPC samples and revealed that the EBV-encoded miRNAs derived from BamHI-A rightward transcripts (miR-BARTs) are abundantly expressed. The important roles of miR-BARTs in cancer development have been reported extensively. In the present study, we identified multiple putative binding sites of miR-BART5-5p, BART7-3p, BART9-3p and BART14-3p on the 3'-UTR of a critical DNA double-strand break (DSB) repair gene, Ataxia-Telangiectasia-Mutant (ATM). Notably, the expression of these 4 miR-BARTs represented more than 10% of all EBV-encoded miRNAs in NPC cells while downregulation of ATM expression was observed in our local primary NPC samples in both qRT-PCR and immunohistochemical (IHC) staining analysis. In addition, the abilities of miR-BARTs to downregulate ATM expression were demonstrated in the transient transfection experiments. By manipulating the miR-BARTs expression in epithelial cell lines, we further revealed that these four viral miRNAs could inhibit both ionizing radiation (IR)-induced ATM kinase activity and BZLF1-induced viral lytic reactivation. In conclusion, our findings suggest that miR-BART5-5p, BART7-3p, BART9-3p and BART14-3p work co-operatively to modulate DNA damage response and to maintain viral latency, contributing to the NPC tumorigenesis. Acknowledgement: Theme-based Research Scheme (T12-401/13-R) and GRF (14104415 and 14138016), Research Grant Council, Hong Kong.

Citation Format: Raymond W. Lung, Po-Man Hau, Joanna H. Tong, Ka-Hei Lam, Anthony W. Chan, Kevin Y. Yip, George S. Tsao, Kwok-Wai Lo, Ka-Fai To. Epstein-Barr virus-encoded miRNAs target ATM-mediated response in nasopharyngeal carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 482.

OMTools: a software package for visualizing and processing optical mapping data

Summary

Optical mapping is a molecular technique capturing specific patterns of fluorescent labels along DNA molecules. It has been widely applied in assisted-scaffolding in sequence assemblies, microbial strain typing and detection of structural variations. Various computational methods have been developed to analyze optical mapping data. However, existing tools for processing and visualizing optical map data still have many shortcomings. Here, we present OMTools, an efficient and intuitive data processing and visualization suite to handle and explore large-scale optical mapping profiles. OMTools includes modules for visualization (OMView), data processing and simulation. These modules together form an accessible and convenient pipeline for optical mapping analyses.

Availability and implementation

OMTools is implemented in Java 1.8 and released under a GPL license. OMTools can be downloaded from https://github.com/aldenleung/OMTools and run on any standard desktop computer equipped with a Java virtual machine.

Supplementary information

Supplementary data are available at Bioinformatics online.

Case Report: Exome sequencing reveals recurrent RETSAT mutations and a loss-of-function POLDIP2 mutation in a rare undifferentiated tongue sarcoma

Soft tissue sarcoma of the tongue represents a very rare head and neck cancer with connective tissue features, and the genetics underlying this rare cancer are largely unknown. There are less than 20 cases reported in the literature thus far. Here, we reported the first whole-exome characterization (>×200 depth) of an undifferentiated sarcoma of the tongue in a 31-year-old male. Even with a very good sequencing depth, only 19 nonsynonymous mutations were found, indicating a relatively low mutation rate of this rare cancer (lower than that of human papillomavirus (HPV)-positive head and neck cancer). Yet, among the few genes that are somatically mutated in this HPV-negative undifferentiated tongue sarcoma, a noticeable deleterious frameshift mutation (with a very high allele frequency of >93%) of a gene for DNA replication and repair, namely POLDIP2 (DNA polymerase delta interacting protein 2), and two recurrent mutations of the adipogenesis and adipocyte differentiation gene RETSAT (retinol saturase), were identified. Thus, somatic events likely affecting adipogenesis and differentiation, as well as potential stem mutations to POLDIP2, may be implicated in the formation of this rare cancer. This identified somatic whole-exome sequencing profile appears to be distinct from that of other reported adult sarcomas from The Cancer Genome Atlas, suggesting a potential unique genetic profile for this rare sarcoma of the tongue. Interestingly, this low somatic mutation rate is unexpectedly found to be accompanied by multiple tumor protein p53 and NOTCH1 germline mutations of the patient’s blood DNA. This may explain the very early age of onset of head and neck cancer, with likely hereditary predisposition. Our findings are, to our knowledge, the first to reveal a unique genetic profile of this very rare undifferentiated sarcoma of the tongue.

EBV-encoded miRNAs target ATM-mediated response in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a highly invasive epithelial malignancy that is prevalent in southern China and Southeast Asia. It is consistently associated with latent Epstein-Barr virus (EBV) infection. In NPC, miR-BARTs, the EBV-encoded miRNAs derived from BamH1-A rightward transcripts, are abundantly expressed and contribute to cancer development by targeting various cellular and viral genes. In this study, we establish a comprehensive transcriptional profile of EBV-encoded miRNAs in a panel of NPC patient-derived xenografts and an EBV-positive NPC cell line by small RNA sequencing. Among the 40 miR-BARTs, predominant expression of 22 miRNAs was consistently detected in these tumors. Among the abundantly expressed EBV-miRNAs, BART5-5p, BART7-3p, BART9-3p, and BART14-3p could negatively regulate the expression of a key DNA double-strand break (DSB) repair gene, ataxia telangiectasia mutated (ATM), by binding to multiple sites on its 3'-UTR. Notably, the expression of these four miR-BARTs represented more than 10% of all EBV-encoded miRNAs in tumor cells, while downregulation of ATM expression was commonly detected in all of our tested sequenced samples. In addition, downregulation of ATM was also observed in primary NPC tissues in both qRT-PCR (16 NP and 45 NPC cases) and immunohistochemical staining (35 NP and 46 NPC cases) analysis. Modulation of ATM expression by BART5-5p, BART7-3p, BART9-3p, and BART14-3p was demonstrated in the transient transfection assays. These findings suggest that EBV uses miRNA machinery as a key mechanism to control the ATM signaling pathway in NPC cells. By suppressing these endogenous miR-BARTs in EBV-positive NPC cells, we further demonstrated the novel function of miR-BARTs in inhibiting Zta-induced lytic reactivation. These findings imply that the four viral miRNAs work co-operatively to modulate ATM activity in response to DNA damage and to maintain viral latency, contributing to the tumorigenesis of NPC. © 2017 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps

We present a new method, OMSV, for accurately and comprehensively identifying structural variations (SVs) from optical maps. OMSV detects both homozygous and heterozygous SVs, SVs of various types and sizes, and SVs with or without creating or destroying restriction sites. We show that OMSV has high sensitivity and specificity, with clear performance gains over the latest method. Applying OMSV to a human cell line, we identified hundreds of SVs >2 kbp, with 68 % of them missed by sequencing-based callers. Independent experimental validation confirmed the high accuracy of these SVs. The OMSV software is available at http://yiplab.cse.cuhk.edu.hk/omsv/ .

Maximizing T c by tuning nematicity and magnetism in FeSe1-x S x superconductors

A fundamental issue concerning iron-based superconductivity is the roles of electronic nematicity and magnetism in realising high transition temperature (T c). To address this issue, FeSe is a key material, as it exhibits a unique pressure phase diagram involving non-magnetic nematic and pressure-induced antiferromagnetic ordered phases. However, as these two phases in FeSe have considerable overlap, how each order affects superconductivity remains perplexing. Here we construct the three-dimensional electronic phase diagram, temperature (T) against pressure (P) and isovalent S-substitution (x), for FeSe1-x S x . By simultaneously tuning chemical and physical pressures, against which the chalcogen height shows a contrasting variation, we achieve a complete separation of nematic and antiferromagnetic phases. In between, an extended non-magnetic tetragonal phase emerges, where T c shows a striking enhancement. The completed phase diagram uncovers that high-T c superconductivity lies near both ends of the dome-shaped antiferromagnetic phase, whereas T c remains low near the nematic critical point.

START: a system for flexible analysis of hundreds of genomic signal tracks in few lines of SQL-like queries

BACKGROUND

A genomic signal track is a set of genomic intervals associated with values of various types, such as measurements from high-throughput experiments. Analysis of signal tracks requires complex computational methods, which often make the analysts focus too much on the detailed computational steps rather than on their biological questions.

RESULTS

Here we propose Signal Track Query Language (STQL) for simple analysis of signal tracks. It is a Structured Query Language (SQL)-like declarative language, which means one only specifies what computations need to be done but not how these computations are to be carried out. STQL provides a rich set of constructs for manipulating genomic intervals and their values. To run STQL queries, we have developed the Signal Track Analytical Research Tool (START, http://yiplab.cse.cuhk.edu.hk/start/ ), a system that includes a Web-based user interface and a back-end execution system. The user interface helps users select data from our database of around 10,000 commonly-used public signal tracks, manage their own tracks, and construct, store and share STQL queries. The back-end system automatically translates STQL queries into optimized low-level programs and runs them on a computer cluster in parallel. We use STQL to perform 14 representative analytical tasks. By repeating these analyses using bedtools, Galaxy and custom Python scripts, we show that the STQL solution is usually the simplest, and the parallel execution achieves significant speed-up with large data files. Finally, we describe how a biologist with minimal formal training in computer programming self-learned STQL to analyze DNA methylation data we produced from 60 pairs of hepatocellular carcinoma (HCC) samples.

CONCLUSIONS

Overall, STQL and START provide a generic way for analyzing a large number of genomic signal tracks in parallel easily.

Reconstruction of enhancer-target networks in 935 samples of human primary cells, tissues and cell lines

We propose a new method for determining the target genes of transcriptional enhancers in specific cells and tissues. It combines global trends across many samples and sample-specific information, and considers the joint effect of multiple enhancers. Our method outperforms existing methods when predicting the target genes of enhancers in unseen samples, as evaluated by independent experimental data. Requiring few types of input data, we are able to apply our method to reconstruct the enhancer-target networks in 935 samples of human primary cells, tissues and cell lines, which constitute by far the largest set of enhancer-target networks. The similarity of these networks from different samples closely follows their cell and tissue lineages. We discover three major co-regulation modes of enhancers and find defense-related genes often simultaneously regulated by multiple enhancers bound by different transcription factors. We also identify differentially methylated enhancers in hepatocellular carcinoma (HCC) and experimentally confirm their altered regulation of HCC-related genes.

Quasilinear quantum magnetoresistance in pressure-induced nonsymmorphic superconductor chromium arsenide

In conventional metals, modification of electron trajectories under magnetic field gives rise to a magnetoresistance that varies quadratically at low field, followed by a saturation at high field for closed orbits on the Fermi surface. Deviations from the conventional behaviour, for example, the observation of a linear magnetoresistance, or a non-saturating magnetoresistance, have been attributed to exotic electron scattering mechanisms. Recently, linear magnetoresistance has been observed in many Dirac materials, in which the electron–electron correlation is relatively weak. The strongly correlated helimagnet CrAs undergoes a quantum phase transition to a nonmagnetic superconductor under pressure. Here we observe, near the magnetic instability, a large and non-saturating quasilinear magnetoresistance from the upper critical field to 14 T at low temperatures. We show that the quasilinear magnetoresistance may arise from an intricate interplay between a nontrivial band crossing protected by nonsymmorphic crystal symmetry and strong magnetic fluctuations.

The electronic structure of the helimagnet CrAs is unusual due to its nonsymmorphic crystal symmetry. Here, the authors observe quasilinear magnetoresistance close to a pressure-driven superconducting transition, which may arise from the interaction of the band structure and magnetic fluctuations.

Exome and genome sequencing of nasopharynx cancer identifies NF-κB pathway activating mutations

Nasopharyngeal carcinoma (NPC) is an aggressive head and neck cancer characterized by Epstein-Barr virus (EBV) infection and dense lymphocyte infiltration. The scarcity of NPC genomic data hinders the understanding of NPC biology, disease progression and rational therapy design. Here we performed whole-exome sequencing (WES) on 111 micro-dissected EBV-positive NPCs, with 15 cases subjected to further whole-genome sequencing (WGS), to determine its mutational landscape. We identified enrichment for genomic aberrations of multiple negative regulators of the NF-κB pathway, including CYLD, TRAF3, NFKBIA and NLRC5, in a total of 41% of cases. Functional analysis confirmed inactivating CYLD mutations as drivers for NPC cell growth. The EBV oncoprotein latent membrane protein 1 (LMP1) functions to constitutively activate NF-κB signalling, and we observed mutual exclusivity among tumours with somatic NF-κB pathway aberrations and LMP1-overexpression, suggesting that NF-κB activation is selected for by both somatic and viral events during NPC pathogenesis.

Nasopharyngeal cancer is frequently characterized by Epstein-Barr virus infection. Here, using genomic analyses, the authors find that the tumours harbour mutations in genes involved in the NF-κB signalling pathway or overexpress a viral oncoprotein, latent membrane protein 1.

Yin Yang 1-mediated epigenetic silencing of tumour-suppressive microRNAs activates nuclear factor-κB in hepatocellular carcinoma

Enhancer of zeste homolog 2 (EZH2) catalyses histone H3 lysine 27 trimethylation (H3K27me3) to silence tumour-suppressor genes in hepatocellular carcinoma (HCC) but the process of locus-specific recruitment remains elusive. Here we investigated the transcription factors involved and the molecular consequences in HCC development. The genome-wide distribution of H3K27me3 was determined by chromatin immunoprecipitation coupled with high-throughput sequencing or promoter array analyses in HCC cells from hepatitis B virus (HBV) X protein transgenic mouse and human cell models. Transcription factor binding site analysis was performed to identify EZH2-interacting transcription factors followed by functional characterization. Our cross-species integrative analysis revealed a crucial link between Yin Yang 1 (YY1) and EZH2-mediated H3K27me3 in HCC. Gene expression analysis of human HBV-associated HCC specimens demonstrated concordant overexpression of YY1 and EZH2, which correlated with poor survival of patients in advanced stages. The YY1 binding motif was significantly enriched in both in vivo and in vitro H3K27me3-occupied genes, including genes for 15 tumour-suppressive microRNAs. Knockdown of YY1 reduced not only global H3K27me3 levels, but also EZH2 and H3K27me3 promoter occupancy and DNA methylation, leading to the transcriptional up-regulation of microRNA-9 isoforms in HCC cells. Concurrent EZH2 knockdown and 5-aza-2'-deoxycytidine treatment synergistically increased the levels of microRNA-9, which reduced the expression and transcriptional activity of nuclear factor-κB (NF-κB). Functionally, YY1 promoted HCC tumourigenicity and inhibited apoptosis of HCC cells, at least partially through NF-κB activation. In conclusion, YY1 overexpression contributes to EZH2 recruitment for H3K27me3-mediated silencing of tumour-suppressive microRNAs, thereby activating NF-κB signalling in hepatocarcinogenesis.

A novel method for discovering local spatial clusters of genomic regions with functional relationships from DNA contact maps

Motivation: The three-dimensional structure of genomes makes it possible for genomic regions not adjacent in the primary sequence to be spatially proximal. These DNA contacts have been found to be related to various molecular activities. Previous methods for analyzing DNA contact maps obtained from Hi-C experiments have largely focused on studying individual interactions, forming spatial clusters composed of contiguous blocks of genomic locations, or classifying these clusters into general categories based on some global properties of the contact maps.

Results: Here, we describe a novel computational method that can flexibly identify small clusters of spatially proximal genomic regions based on their local contact patterns. Using simulated data that highly resemble Hi-C data obtained from real genome structures, we demonstrate that our method identifies spatial clusters that are more compact than methods previously used for clustering genomic regions based on DNA contact maps. The clusters identified by our method enable us to confirm functionally related genomic regions previously reported to be spatially proximal in different species. We further show that each genomic region can be assigned a numeric affinity value that indicates its degree of participation in each local cluster, and these affinity values correlate quantitatively with DNase I hypersensitivity, gene expression, super enhancer activities and replication timing in a cell type specific manner. We also show that these cluster affinity values can precisely define boundaries of reported topologically associating domains, and further define local sub-domains within each domain.

Availability and implementation: The source code of BNMF and tutorials on how to use the software to extract local clusters from contact maps are available at http://yiplab.cse.cuhk.edu.hk/bnmf/.

Contact:kevinyip@cse.cuhk.edu.hk

Supplementary information:Supplementary data are available at Bioinformatics online.

FunSeq2: a framework for prioritizing noncoding regulatory variants in cancer

Identification of noncoding drivers from thousands of somatic alterations in a typical tumor is a difficult and unsolved problem. We report a computational framework, FunSeq2, to annotate and prioritize these mutations. The framework combines an adjustable data context integrating large-scale genomics and cancer resources with a streamlined variant-prioritization pipeline. The pipeline has a weighted scoring system combining: inter- and intra-species conservation; loss- and gain-of-function events for transcription-factor binding; enhancer-gene linkages and network centrality; and per-element recurrence across samples. We further highlight putative drivers with information specific to a particular sample, such as differential expression. FunSeq2 is available from funseq2.gersteinlab.org.

Abstract 4854: A computational framework for prioritizing noncoding regulatory variants in cancer

Mutations in key regulatory sequences have been suggested to cause oncogenesis. However, identification of noncoding cancer “drivers” from thousands of somatic alterations is a difficult and unsolved problem. We report a computational framework, FunSeq, to annotate and prioritize these mutations. The framework combines an adjustable data context integrating large-scale genomics (e.g. ENCODE) and cancer resources with a streamlined variant-prioritization pipeline. The pipeline has a weighted scoring system combining: inter- and intra-species (we used patterns of natural polymorphisms to identify human-specific conserved elements) conservation; loss- and gain-of function events for transcription-factor binding; enhancer-gene linkages and network centrality; and per-element recurrence across samples. We further highlight putative drivers with information specific to a particular sample, such as differential gene expression. When applied to an individual tumor genome, our method is able to prioritize the TERT promoter mutation. We then evaluated our framework on a larger-scale first by doing various comparisons with other existing noncoding variant-prioritization tools. Next, we used the recurrence of somatic mutations to validate some of our prioritized mutations. Finally, we developed the recurrence analysis into a database combining all whole-genome sequenced cancer samples and used this to provide higher confidence in mutation prioritization. FunSeq is available from funseq.gersteinlab.org.

Note: This abstract was not presented at the meeting.

Citation Format: Yao Fu, Zhu Liu, Shaoke Lou, Vincenza Colonna, Jason Bedford, Xinmeng Mu, Kevin Y. Yip, Hyun Min Kang, Tuuli Lappalainen, Andrea Sboner, Haiyuan Yu, 1000 Genomes Project Consortium, Mark Rubin, Chris Tyler-Smith, Ekta Khurana, Mark Gerstein. A computational framework for prioritizing noncoding regulatory variants in cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4854. doi:10.1158/1538-7445.AM2015-4854

Improved prediction of RNA secondary structure by integrating the free energy model with restraints derived from experimental probing data

Recently, several experimental techniques have emerged for probing RNA structures based on high-throughput sequencing. However, most secondary structure prediction tools that incorporate probing data are designed and optimized for particular types of experiments. For example, RNAstructure-Fold is optimized for SHAPE data, while SeqFold is optimized for PARS data. Here, we report a new RNA secondary structure prediction method, restrained MaxExpect (RME), which can incorporate multiple types of experimental probing data and is based on a free energy model and an MEA (maximizing expected accuracy) algorithm. We first demonstrated that RME substantially improved secondary structure prediction with perfect restraints (base pair information of known structures). Next, we collected structure-probing data from diverse experiments (e.g. SHAPE, PARS and DMS-seq) and transformed them into a unified set of pairing probabilities with a posterior probabilistic model. By using the probability scores as restraints in RME, we compared its secondary structure prediction performance with two other well-known tools, RNAstructure-Fold (based on a free energy minimization algorithm) and SeqFold (based on a sampling algorithm). For SHAPE data, RME and RNAstructure-Fold performed better than SeqFold, because they markedly altered the energy model with the experimental restraints. For high-throughput data (e.g. PARS and DMS-seq) with lower probing efficiency, the secondary structure prediction performances of the tested tools were comparable, with performance improvements for only a portion of the tested RNAs. However, when the effects of tertiary structure and protein interactions were removed, RME showed the highest prediction accuracy in the DMS-accessible regions by incorporating in vivo DMS-seq data.

Systematic exploration of autonomous modules in noisy microRNA-target networks for testing the generality of the ceRNA hypothesis

BACKGROUND

In the competing endogenous RNA (ceRNA) hypothesis, different transcripts communicate through a competition for their common targeting microRNAs (miRNAs). Individual examples have clearly shown the functional importance of ceRNA in gene regulation and cancer biology. It remains unclear to what extent gene expression levels are regulated by ceRNA in general. One major hurdle to studying this problem is the intertwined connections in miRNA-target networks, which makes it difficult to isolate the effects of individual miRNAs.

RESULTS

Here we propose computational methods for decomposing a complex miRNA-target network into largely autonomous modules called microRNA-target biclusters (MTBs). Each MTB contains a relatively small number of densely connected miRNAs and mRNAs with few connections to other miRNAs and mRNAs. Each MTB can thus be individually analyzed with minimal crosstalk with other MTBs. Our approach differs from previous methods for finding modules in miRNA-target networks by not making any pre-assumptions about expression patterns, thereby providing objective information for testing the ceRNA hypothesis. We show that the expression levels of miRNAs and mRNAs in an MTB are significantly more anti-correlated than random miRNA-mRNA pairs and other validated and predicted miRNA-target pairs, demonstrating the biological relevance of MTBs. We further show that there is widespread correlation of expression between mRNAs in same MTBs under a wide variety of parameter settings, and the correlation remains even when co-regulatory effects are controlled for, which suggests potential widespread expression buffering between these mRNAs, which is consistent with the ceRNA hypothesis. Lastly, we also propose a potential use of MTBs in functional annotation of miRNAs.

CONCLUSIONS

MTBs can be used to help identify autonomous miRNA-target modules for testing the generality of the ceRNA hypothesis experimentally. The identified modules can also be used to test other properties of miRNA-target networks in general.

Are special read alignment strategies necessary and cost-effective when handling sequencing reads from patient-derived tumor xenografts?

BACKGROUND

Patient-derived tumor xenografts in mice are widely used in cancer research and have become important in developing personalized therapies. When these xenografts are subject to DNA sequencing, the samples could contain various amounts of mouse DNA. It has been unclear how the mouse reads would affect data analyses. We conducted comprehensive simulations to compare three alignment strategies at different mutation rates, read lengths, sequencing error rates, human-mouse mixing ratios and sequenced regions. We also sequenced a nasopharyngeal carcinoma xenograft and a cell line to test how the strategies work on real data.

RESULTS

We found the "filtering" and "combined reference" strategies performed better than aligning reads directly to human reference in terms of alignment and variant calling accuracies. The combined reference strategy was particularly good at reducing false negative variants calls without significantly increasing the false positive rate. In some scenarios the performance gain of these two special handling strategies was too small for special handling to be cost-effective, but it was found crucial when false non-synonymous SNVs should be minimized, especially in exome sequencing.

CONCLUSIONS

Our study systematically analyzes the effects of mouse contamination in the sequencing data of human-in-mouse xenografts. Our findings provide information for designing data analysis pipelines for these data.

A common set of distinct features that characterize noncoding RNAs across multiple species

To find signature features shared by various ncRNA sub-types and characterize novel ncRNAs, we have developed a method, RNAfeature, to investigate >600 sets of genomic and epigenomic data with various evolutionary and biophysical scores. RNAfeature utilizes a fine-tuned intra-species wrapper algorithm that is followed by a novel feature selection strategy across species. It considers long distance effect of certain features (e.g. histone modification at the promoter region). We finally narrow down on 10 informative features (including sequences, structures, expression profiles and epigenetic signals). These features are complementary to each other and as a whole can accurately distinguish canonical ncRNAs from CDSs and UTRs (accuracies: >92% in human, mouse, worm and fly). Moreover, the feature pattern is conserved across multiple species. For instance, the supervised 10-feature model derived from animal species can predict ncRNAs in Arabidopsis (accuracy: 82%). Subsequently, we integrate the 10 features to define a set of noncoding potential scores, which can identify, evaluate and characterize novel noncoding RNAs. The score covers all transcribed regions (including unconserved ncRNAs), without requiring assembly of the full-length transcripts. Importantly, the noncoding potential allows us to identify and characterize potential functional domains with feature patterns similar to canonical ncRNAs (e.g. tRNA, snRNA, miRNA, etc) on ∼70% of human long ncRNAs (lncRNAs).

The Essential Component in DNA-Based Information Storage System: Robust Error-Tolerating Module

The size of digital data is ever increasing and is expected to grow to 40,000 EB by 2020, yet the estimated global information storage capacity in 2011 is <300 EB, indicating that most of the data are transient. DNA, as a very stable nano-molecule, is an ideal massive storage device for long-term data archive. The two most notable illustrations are from Church et al. and Goldman et al., whose approaches are well-optimized for most sequencing platforms - short synthesized DNA fragments without homopolymer. Here, we suggested improvements on error handling methodology that could enable the integration of DNA-based computational process, e.g., algorithms based on self-assembly of DNA. As a proof of concept, a picture of size 438 bytes was encoded to DNA with low-density parity-check error-correction code. We salvaged a significant portion of sequencing reads with mutations generated during DNA synthesis and sequencing and successfully reconstructed the entire picture. A modular-based programing framework - DNAcodec with an eXtensible Markup Language-based data format was also introduced. Our experiments demonstrated the practicability of long DNA message recovery with high error tolerance, which opens the field to biocomputing and synthetic biology.

VAS: a convenient web portal for efficient integration of genomic features with millions of genetic variants

Background

High-throughput experimental methods have fostered the systematic detection of millions of genetic variants from any human genome. To help explore the potential biological implications of these genetic variants, software tools have been previously developed for integrating various types of information about these genomic regions from multiple data sources. Most of these tools were designed either for studying a small number of variants at a time, or for local execution on powerful machines.

Results

To make exploration of whole lists of genetic variants simple and accessible, we have developed a new Web-based system called VAS (Variant Annotation System, available at https://yiplab.cse.cuhk.edu.hk/vas/). It provides a large variety of information useful for studying both coding and non-coding variants, including whole-genome transcription factor binding, open chromatin and transcription data from the ENCODE consortium. By means of data compression, millions of variants can be uploaded from a client machine to the server in less than 50 megabytes of data. On the server side, our customized data integration algorithms can efficiently link millions of variants with tens of whole-genome datasets. These two enabling technologies make VAS a practical tool for annotating genetic variants from large genomic studies. We demonstrate the use of VAS in annotating genetic variants obtained from a migraine meta-analysis study and multiple data sets from the Personal Genomes Project. We also compare the running time of annotating 6.4 million SNPs of the CEU trio by VAS and another tool, showing that VAS is efficient in handling new variant lists without requiring any pre-computations.

Conclusions

VAS is specially designed to handle annotation tasks with long lists of genetic variants and large numbers of annotating features efficiently. It is complementary to other existing tools with more specific aims such as evaluating the potential impacts of genetic variants in terms of disease risk. We recommend using VAS for a quick first-pass identification of potentially interesting genetic variants, to minimize the time required for other more in-depth downstream analyses.

Whole-genome bisulfite sequencing of multiple individuals reveals complementary roles of promoter and gene body methylation in transcriptional regulation

BACKGROUND

DNA methylation is an important type of epigenetic modification involved in gene regulation. Although strong DNA methylation at promoters is widely recognized to be associated with transcriptional repression, many aspects of DNA methylation remain not fully understood, including the quantitative relationships between DNA methylation and expression levels, and the individual roles of promoter and gene body methylation.

RESULTS

Here we present an integrated analysis of whole-genome bisulfite sequencing and RNA sequencing data from human samples and cell lines. We find that while promoter methylation inversely correlates with gene expression as generally observed, the repressive effect is clear only on genes with a very high DNA methylation level. By means of statistical modeling, we find that DNA methylation is indicative of the expression class of a gene in general, but gene body methylation is a better indicator than promoter methylation. These findings are general in that a model constructed from a sample or cell line could accurately fit the unseen data from another. We further find that promoter and gene body methylation have minimal redundancy, and either one is sufficient to signify low expression. Finally, we obtain increased modeling power by integrating histone modification data with the DNA methylation data, showing that neither type of information fully subsumes the other.

CONCLUSION

Our results suggest that DNA methylation outside promoters also plays critical roles in gene regulation. Future studies on gene regulatory mechanisms and disease-associated differential methylation should pay more attention to DNA methylation at gene bodies and other non-promoter regions.