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.

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.

Efficient crop improvement depends on the application of accurate genetic information contained in diverse germplasm resources. Here we report a reference-grade genome of wild soybean accession W05, with a final assembled genome size of 1013.2 Mb and a contig N50 of 3.3 Mb. The analytical power of the W05 genome is demonstrated by several examples. First, we identify an inversion at the locus determining seed coat color during domestication. Second, a translocation event between chromosomes 11 and 13 of some genotypes is shown to interfere with the assignment of QTLs. Third, we find a region containing copy number variations of the Kunitz trypsin inhibitor (KTI) genes. Such findings illustrate the power of this assembly in the analysis of large structural variations in soybean germplasm collections. The wild soybean genome assembly has wide applications in comparative genomic and evolutionary studies, as well as in crop breeding and improvement programs.

Statistical models have been used to quantify the relationship between gene expression and transcription factor (TF) binding signals. Here we apply the models to the large-scale data generated by the ENCODE project to study transcriptional regulation by TFs. Our results reveal a notable difference in the prediction accuracy of expression levels of transcription start sites (TSSs) captured by different technologies and RNA extraction protocols. In general, the expression levels of TSSs with high CpG content are more predictable than those with low CpG content. For genes with alternative TSSs, the expression levels of downstream TSSs are more predictable than those of the upstream ones. Different TF categories and specific TFs vary substantially in their contributions to predicting expression. Between two cell lines, the differential expression of TSS can be precisely reflected by the difference of TF-binding signals in a quantitative manner, arguing against the conventional on-and-off model of TF binding. Finally, we explore the relationships between TF-binding signals and other chromatin features such as histone modifications and DNase hypersensitivity for determining expression. The models imply that these features regulate transcription in a highly coordinated manner.

mibnn2002, identified from an allele screen, shows early segmentation defect and severe cell death phenotypes, which are different from those of other described mib mutant alleles. We have previously reported its defects in somitogenesis and identified its origin of mutation, a large deletion in LG2. The report here is a continuous study, where we applied the bioinformatics analysis to profile the genetic background of mibnn2002 mutants. By comparing the transcriptomic data of mibnn2002 mutants with those of AB wild-type, a total of 1945 differentially expressed genes were identified, including 685 up- and 1260 down-regulated genes. The Database for Annotation, Visualization and Integrated Discovery (DAVID) analysis and Ingenuity Pathway Analysis (IPA) identified the enriched pathways and their related biological functions. Our data further demonstrated that the defects in the somitogenesis were related to the down-regulated segmentation genes, such as foxc1a, smyhc1, myod1 and mylpfa.

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/ .

Antibiotic resistance is an emerging public health issue. Plasmids are one of the popular carriers to disseminate resistance genes among pathogens. However, the response of plasmid-carrying bacteria to antibiotic treatment and how these bacteria evolve to increase their resistance remain elusive. In this study, we conjugated plasmid pNDM-HK to E. coli J53 recipient cells and selected survivors using different concentrations of the broad spectrum antibiotic meropenem. After selection, transconjugants conferred varying minimum inhibitory concentrations with respect to carbapenems. We sequenced and compared the transcriptomes of transconjugants that exhibited distinct carbapenem susceptibilities, and found that the loss of outer membrane proteins led to antibiotic resistance. Moreover, we identified a novel mutation, G63S, in transcription factor OmpR which moderates the expression of outer membrane proteins. The loss of porins was due to incapability of phosphorylation, which is essential for porin transcription and carbapenem resistance. We also characterized other genes that are regulated by ompR in this mutant, which contributed to bacterial antibiotic resistance. Overall, our studies suggest antibiotic pressure after conjugation might be an alternative pathway to promote antimicrobial resistance.

cDNA library preparation is important for many high-throughput sequencing applications, such as RNA G-quadruplex structure sequencing (rG4-seq). A systematic evaluation of the procedures of the experimental pipeline, however, is lacking. Herein, we perform a comprehensive assessment of the 5 key experimental steps involved in the cDNA library preparation of rG4-seq, and identify better reaction conditions and/or enzymes to carry out each of these key steps. Notably, we apply the improved methods to fragmented cellular RNA, and show reduced RNA input requirement, lower transcript abundance variations between biological replicates, as well as lower transcript coverage bias when compared to prior arts. In addition, the time to perform these steps is substantially reduced to hours. Our method and results can be directly applied in protocols that require cDNA library preparation, and provide insights to the further development of simple and efficient cDNA library preparation for different biological applications.

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.

Enhancers are important non-coding elements, but they have traditionally been hard to characterize experimentally. The development of massively parallel assays allows the characterization of large numbers of enhancers for the first time. Here, we developed a framework using Drosophila STARR-seq to create shape-matching filters based on meta-profiles of epigenetic features. We integrated these features with supervised machine-learning algorithms to predict enhancers. We further demonstrated that our model could be transferred to predict enhancers in mammals. We comprehensively validated the predictions using a combination of in vivo and in vitro approaches, involving transgenic assays in mice and transduction-based reporter assays in human cell lines (153 enhancers in total). The results confirmed that our model can accurately predict enhancers in different species without re-parameterization. Finally, we examined the transcription factor binding patterns at predicted enhancers versus promoters. We demonstrated that these patterns enable the construction of a secondary model that effectively distinguishes enhancers and promoters.

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.

mib(nn2002), found from an allele screen, showed early segmentation defect and severe cell death phenotypes, which are different from previously known mib mutants. Despite distinct morphological phenotypes, the typical mib molecular phenotypes: her4 down-regulation, neurogenic phenotype and cold sensitive dlc expression pattern, still remained. The linkage analysis also indicated that mib(nn2002) is a new mib allele. Failure of specification in anterior 7-10 somites is likely due to lack of foxc1a expression in mib(nn2002) homozygotes. Somites and somite markers gradually appeared after 7-10 somite stage, suggesting that foxc1a is only essential for the formation of anterior 7-10 somites. Apoptosis began around 16-somite stage with p53 up-regulation. To find the possible links of mib, foxc1a and apoptosis, transcriptome analysis was employed. About 140 genes, including wnt3a, foxc1a and mib, were not detected in the homozygotes. Overexpression of foxc1a mRNA in mib(nn2002) homozygotes partially rescued the anterior somite specification. In the process of characterizing mib(nn2002) mutation, we integrated the scaffolds containing mib locus into chromosome 2 (or linkage group 2, LG2) based on synteny comparison and transcriptome results. Genomic PCR analysis further supported the conclusion and showed that mib(nn2002) has a chromosomal deletion with the size of about 9.6 Mbp.

The marine medaka Oryzias melastigma has been demonstrated as a novel model for marine ecotoxicological studies. However, the lack of genome and transcriptome reference has largely restricted the use of O. melastigma in the assessment of in vivo molecular responses to environmental stresses and the analysis of biological toxicity in the marine environment. Although O. melastigma is believed to be phylogenetically closely related to Oryzias latipes, the divergence between these two species is still largely unknown. Using Illumina high-throughput RNA sequencing followed by de novo assembly and comprehensive gene annotation, we provided transcriptomic resources for the brain, liver, ovary and testis of O. melastigma. We also investigated the possible extent of divergence between O. melastigma and O. latipes at the transcriptome level.

Treacher Collins Syndrome (TCS) is a rare congenital birth disorder (1 in 50,000 live births) characterized by severe craniofacial defects, including the downward slanting palpebral fissures, hypoplasia of the facial bones, and cleft palate (CP). Over 90% of patients with TCS have a mutation in the TCOF1 gene. However, some patients exhibit mutations in two new causative genes, POLR1C and POLR1D, which encode subunits of RNA polymerases I and III, that affect ribosome biogenesis. In this study, we examine the role of POLR1C in TCS using zebrafish as a model system. Our data confirmed that polr1c is highly expressed in the facial region, and dysfunction of this gene by knockdown or knock-out resulted in mis-expression of neural crest cells during early development that leads to TCS phenotype. Next generation sequencing and bioinformatics analysis of the polr1c mutants further demonstrated the up-regulated p53 pathway and predicted skeletal disorders. Lastly, we partially rescued the TCS facial phenotype in the background of p53 mutants, which supported the hypothesis that POLR1C-dependent type 3 TCS is associated with the p53 pathway.

Natural small compounds comprise most cellular molecules and bind proteins as substrates, products, cofactors, and ligands. However, a large-scale investigation of in vivo protein-small metabolite interactions has not been performed. We developed a mass spectrometry assay for the large-scale identification of in vivo protein-hydrophobic small metabolite interactions in yeast and analyzed compounds that bind ergosterol biosynthetic proteins and protein kinases. Many of these proteins bind small metabolites; a few interactions were previously known, but the vast majority are new. Importantly, many key regulatory proteins such as protein kinases bind metabolites. Ergosterol was found to bind many proteins and may function as a general regulator. It is required for the activity of Ypk1, a mammalian AKT/SGK kinase homolog. Our study defines potential key regulatory steps in lipid biosynthetic pathways and suggests that small metabolites may play a more general role as regulators of protein activity and function than previously appreciated.

We propose a method to predict yeast transcription factor targets by integrating histone modification profiles with transcription factor binding motif information. It shows improved predictive power compared to a binding motif-only method. We find that transcription factors cluster into histone-sensitive and -insensitive classes. The target genes of histone-sensitive transcription factors have stronger histone modification signals than those of histone-insensitive ones. The two classes also differ in tendency to interact with histone modifiers, degree of connectivity in protein-protein interaction networks, position in the transcriptional regulation hierarchy, and in a number of additional features, indicating possible differences in their transcriptional regulation mechanisms.

Insertional mutagenesis from virus infection is an important pathogenic risk for the development of cancer. Despite the advent of high-throughput sequencing, discovery of viral integration sites and expressed viral fusion events are still limited. Here, we present ViralFusionSeq (VFS), which combines soft-clipping information, read-pair analysis and targeted de novo assembly to discover and annotate viral-human fusions. VFS was used in an RNA-Seq experiment, simulated DNA-Seq experiment and re-analysis of published DNA-Seq datasets. Our experiments demonstrated that VFS is both sensitive and highly accurate.

Transcription factors function by binding different classes of regulatory elements. The Encyclopedia of DNA Elements (ENCODE) project has recently produced binding data for more than 100 transcription factors from about 500 ChIP-seq experiments in multiple cell types. While this large amount of data creates a valuable resource, it is nonetheless overwhelmingly complex and simultaneously incomplete since it covers only a small fraction of all human transcription factors.

Diabetes and obesity are complex diseases associated with insulin resistance and fatty liver. The latter is characterized by dysregulation of the Akt, AMP-activated protein kinase (AMPK), and IGF-I pathways and expression of microRNAs (miRNAs). In China, multicomponent traditional Chinese medicine (TCM) has been used to treat diabetes for centuries. In this study, we used a three-herb, berberine-containing TCM to treat male Zucker diabetic fatty rats. TCM showed sustained glucose-lowering effects for 1 week after a single-dose treatment. Two-week treatment attenuated insulin resistance and fatty degeneration, with hepatocyte regeneration lasting for 1 month posttreatment. These beneficial effects persisted for 1 year after 1-month treatment. Two-week treatment with TCM was associated with activation of AMPK, Akt, and insulin-like growth factor-binding protein (IGFBP)1 pathways, with downregulation of miR29-b and expression of a gene network implicated in cell cycle, intermediary, and NADPH metabolism with normalization of CYP7a1 and IGFBP1 expression. These concerted changes in mRNA, miRNA, and proteins may explain the sustained effects of TCM in favor of cell survival, increased glucose uptake, and lipid oxidation/catabolism with improved insulin sensitivity and liver regeneration. These novel findings suggest that multicomponent TCM may be a useful tool to unravel genome regulation and expression in complex diseases.

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.