Mengjie Chen

Tdrkh is essential for spermatogenesis and participates in primary piRNA biogenesis in the germline

Piwi proteins and Piwi‐interacting RNAs (piRNAs) repress transposition, regulate translation, and guide epigenetic programming in the germline. Here, we show that an evolutionarily conserved Tudor and KH domain‐containing protein, Tdrkh (a.k.a. Tdrd2), is required for spermatogenesis and involved in piRNA biogenesis. Tdrkh partners with Miwi and Miwi2 via symmetrically dimethylated arginine residues in Miwi and Miwi2. Tdrkh is a mitochondrial protein often juxtaposed to pi‐bodies and piP‐bodies and is required for Tdrd1 cytoplasmic localization and Miwi2 nuclear localization. Tdrkh mutants display meiotic arrest at the zygotene stage, attenuate methylation of Line1 DNA, and upregulate Line1 RNA and protein, without inducing apoptosis. Furthermore, Tdrkh mutants have severely reduced levels of mature piRNAs but accumulate a distinct population of 1′U‐containing, 2′O‐methylated 31–37 nt RNAs that largely complement the missing mature piRNAs. Our results demonstrate that the primary piRNA biogenesis pathway involves 3′→5′ processing of 31–37 nt intermediates and that Tdrkh promotes this final step of piRNA biogenesis but not the ping‐pong cycle. These results shed light on mechanisms underlying primary piRNA biogenesis, an area in which information is conspicuously absent.

Novel HBsAg markers tightly correlate with occult HBV infection and strongly affect HBsAg detection

Occult HBV infection (OBI) is a threat for the safety of blood-supply, and has been associated with the onset of HBV-related hepatocellular carcinoma and lymphomagenesis. Nevertheless, genetic markers in HBsAg (particularly in D-genotype, the most common in Europe) significantly associated with OBI in vivo are missing. Thus, the goal of this study is to define: (i) prevalence and clinical profile of OBI among blood-donors; (ii) HBsAg-mutations associated with OBI; (iii) their impact on HBsAg-detection. OBI was searched among 422,278 blood-donors screened by Nucleic-Acid-Testing. Following Taormina-OBI-definition, 26 (0.006%) OBI-patients were identified. Despite viremia <50IU/ml, HBsAg-sequences were obtained for 25/26 patients (24/25 genotype-D). OBI-associated mutations were identified by comparing OBI-HBsAg with that of 82 chronically-infected (genotype-D) patients as control. Twenty HBsAg-mutations significantly correlated for the first time with OBI. By structural analysis, they localized in the major HBV B-cell-epitope, and in HBsAg-capsid interaction region. 14/24 OBI-patients (58.8%) carried in median 3 such mutations (IQR:2.0-6.0) against 0 in chronically-infected patients. By co-variation analysis, correlations were observed for R122P+S167L (phi=0.68, P=0.01), T116N+S143L (phi=0.53, P=0.03), and Y100S+S143L (phi=0.67, p<0.001). Mutants (obtained by site-directed mutagenesis) carrying T116N, T116N+S143L, R122P, R122P+Q101R, or R122P+S167L strongly decreased HBsAg-reactivity (54.9±22.6S/CO, 31.2±12.0S/CO, 6.1±2.4S/CO, 3.0±1.0S/CO and 3.9±1.3S/CO, respectively) compared to wild-type (306.8±64.1S/CO). Even more, Y100S and Y100S+S143L supernatants show no detectable-HBsAg (experiments in quadruplicate). In conclusions, unique HBsAg-mutations in genotype-D, different than those described in genotypes B/C (rarely found in western countries), tightly correlate with OBI, and strongly affect HBsAg-detection. By altering HBV-antigenicity and/or viral-particle maturation, they may affect full-reliability of universal diagnostic-assays for HBsAg-detection.

SomatiCA: Identifying, Characterizing and Quantifying Somatic Copy Number Aberrations from Cancer Genome Sequencing Data

Whole genome sequencing of matched tumor-normal sample pairs is becoming routine in cancer research. However, analysis of somatic copy-number changes from sequencing data is still challenging because of insufficient sequencing coverage, unknown tumor sample purity and subclonal heterogeneity. Here we describe a computational framework, named SomatiCA, which explicitly accounts for tumor purity and subclonality in the analysis of somatic copy-number profiles. Taking read depths (RD) and lesser allele frequencies (LAF) as input, SomatiCA will output 1) admixture rate for each tumor sample, 2) somatic allelic copy-number for each genomic segment, 3) fraction of tumor cells with subclonal change in each somatic copy number aberration (SCNA), and 4) a list of substantial genomic aberration events including gain, loss and LOH. SomatiCA is available as a Bioconductor R package at http://www.bioconductor.org/packages/2.13/bioc/html/SomatiCA.html.

Comprehensive analysis of the Cancer Genome Atlas reveals a unique gene and non-coding RNA signature of fibrolamellar carcinoma

Fibrolamellar carcinoma (FLC) is a unique liver cancer primarily affecting young adults and characterized by a fusion event between DNAJB1 and PRKACA. By analyzing RNA-sequencing data from The Cancer Genome Atlas (TCGA) for >9,100 tumors across ~30 cancer types, we show that the DNAJB1-PRKACA fusion is specific to FLCs. We demonstrate that FLC tumors (n = 6) exhibit distinct messenger RNA (mRNA) and long intergenic non-coding RNA (lincRNA) profiles compared to hepatocellular carcinoma (n = 263) and cholangiocarcinoma (n = 36), the two most common liver cancers. We also identify a set of mRNAs (n = 16) and lincRNAs (n = 4), including LINC00473, that distinguish FLC from ~25 other liver and non-liver cancer types. We confirm this unique FLC signature by analysis of two independent FLC cohorts (n = 20 and 34). Lastly, we validate the overexpression of one specific gene in the FLC signature, carbonic anhydrase XII (CA12), at the protein level by western blot and immunohistochemistry. Both the mRNA and lincRNA signatures support a major role for protein kinase A (PKA) signaling in shaping the FLC gene expression landscape, and present novel candidate FLC oncogenes that merit further investigation.

Genomic analysis of oesophageal squamous-cell carcinoma identifies alcohol drinking-related mutation signature and genomic alterations

Approximately half of the worlds 500,000 new oesophageal squamous-cell carcinoma (ESCC) cases each year occur in China. Here, we show whole-genome sequencing of DNA and RNA in 94 Chinese individuals with ESCC. We identify six mutational signatures (E1–E6), and Signature E4 is unique in ESCC linked to alcohol intake and genetic variants in alcohol-metabolizing enzymes. We discover significantly recurrent mutations in 20 protein-coding genes, 4 long non-coding RNAs and 10 untranslational regions. Functional analyses show six genes that have recurrent copy-number variants in three squamous-cell carcinomas (oesophageal, head and neck and lung) significantly promote cancer cell proliferation, migration and invasion. The most frequently affected genes by structural variation are LRP1B and TTC28. The aberrant cell cycle and PI3K-AKT pathways seem critical in ESCC. These results establish a comprehensive genomic landscape of ESCC and provide potential targets for precision treatment and prevention of the cancer.

Detecting and understanding genetic and structural features in HIV-1 B subtype V3 underlying HIV-1 co-receptor usage

MOTIVATION To define V3 genetic elements and structural features underlying different HIV-1 co-receptor usage in vivo. RESULTS By probabilistically modeling mutations in the viruses isolated from HIV-1 B subtype patients, we present a unique statistical procedure that would first identify V3 determinants associated with the usage of different co-receptors cooperatively or independently, and then delineate the complicated interactions among mutations functioning cooperatively. We built a model based on dual usage of CXCR4 and CCR5 co-receptors. The molecular basis of our statistical predictions is further confirmed by phenotypic and molecular modeling analyses. Our results provide new insights on molecular basis of different HIV-1 co-receptor usage. This is critical to optimize the use of genotypic tropism testing in clinical practice and to obtain molecular-implication for design of vaccine and new entry-inhibitors.

A hidden Markov random field-based Bayesian method for the detection of long-range chromosomal interactions in Hi-C data

MOTIVATION Advances in chromosome conformation capture and next-generation sequencing technologies are enabling genome-wide investigation of dynamic chromatin interactions. For example, Hi-C experiments generate genome-wide contact frequencies between pairs of loci by sequencing DNA segments ligated from loci in close spatial proximity. One essential task in such studies is peak calling, that is, detecting non-random interactions between loci from the two-dimensional contact frequency matrix. Successful fulfillment of this task has many important implications including identifying long-range interactions that assist interpreting a sizable fraction of the results from genome-wide association studies. The task - distinguishing biologically meaningful chromatin interactions from massive numbers of random interactions - poses great challenges both statistically and computationally. Model-based methods to address this challenge are still lacking. In particular, no statistical model exists that takes the underlying dependency structure into consideration. RESULTS In this paper, we propose a hidden Markov random field (HMRF) based Bayesian method to rigorously model interaction probabilities in the two-dimensional space based on the contact frequency matrix. By borrowing information from neighboring loci pairs, our method demonstrates superior reproducibility and statistical power in both simulation studies and real data analysis. AVAILABILITY AND IMPLEMENTATION The Source codes can be downloaded at: http://www.unc.edu/∼yunmli/HMRFBayesHiC CONTACT: ming.hu@nyumc.org or yunli@med.unc.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Asymptotically Normal and Efficient Estimation of Covariate-Adjusted Gaussian Graphical Model

We propose an asymptotically normal and efficient procedure to estimate every finite subgraph for covariate-adjusted Gaussian graphical model. As a consequence, a confidence interval as well as p-value can be obtained for each edge. The procedure is tuning-free and enjoys easy implementation and efficient computation through parallel estimation on subgraphs or edges. We apply the asymptotic normality result to perform support recovery through edge-wise adaptive thresholding. This support recovery procedure is called ANTAC, standing for asymptotically normal estimation with thresholding after adjusting covariates. ANTAC outperforms other methodologies in the literature in a range of simulation studies. We apply ANTAC to identify gene–gene interactions using an eQTL dataset. Our result achieves better interpretability and accuracy in comparison with a state-of-the-art method. Supplementary materials for the article are available online.

SynthEx: a synthetic-normal-based DNA sequencing tool for copy number alteration detection and tumor heterogeneity profiling

Changes in the quantity of genetic material, known as somatic copy number alterations (CNAs), can drive tumorigenesis. Many methods exist for assessing CNAs using microarrays, but considerable technical issues limit current CNA calling based upon DNA sequencing. We present SynthEx, a novel tool for detecting CNAs from whole exome and genome sequencing. SynthEx utilizes a “synthetic-normal” strategy to overcome technical and financial issues. In terms of accuracy and precision, SynthEx is highly comparable to array-based methods and outperforms sequencing-based CNA detection tools. SynthEx robustly identifies CNAs using sequencing data without the additional costs associated with matched normal specimens.

Reassessment of Piwi binding to the genome and Piwi impact on RNA polymerase II distribution

Drosophila Piwi was reported by Huang et al. (2013) to be guided by piRNAs to piRNA-complementary sites in the genome, which then recruits heterochromatin protein 1a and histone methyltransferase Su(Var)3-9 to the sites. Among additional findings, Huang et al. (2013) also reported Piwi binding sites in the genome and the reduction of RNA polymerase II in euchromatin but its increase in pericentric regions in piwi mutants. Marinov et al. (2015) disputed the validity of the Huang et al. bioinformatic pipeline that led to the last two claims. Here we report our independent reanalysis of the data using current bioinformatic methods. Our reanalysis agrees with Marinov et al. (2015) that Piwis genomic targets still remain to be identified but confirms the Huang et al. claim that Piwi influences RNA polymerase II distribution in the genome. This Matters Arising Response addresses the Marinov et al. (2015) Matters Arising, published concurrently in this issue of Developmental Cell.