Hao Qin

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

BackgroundDNA 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.ResultsHere 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.ConclusionOur 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.

Hepatocellular carcinoma-derived exosomes promote motility of immortalized hepatocyte through transfer of oncogenic proteins and RNAs

Exosomes are increasingly recognized as important mediators of cell-cell communication in cancer progression through the horizontal transfer of RNAs and proteins to neighboring or distant cells. Hepatocellular carcinoma (HCC) is a highly malignant cancer, whose metastasis is largely influenced by the tumor microenvironment. The possible role of exosomes in the interactions between HCC tumor cell and its surrounding hepatic milieu are however largely unknown. In this study, we comprehensively characterized the exosomal RNA and proteome contents derived from three HCC cell lines (HKCI-C3, HKCI-8 and MHCC97L) and an immortalized hepatocyte line (MIHA) using Ion Torrent sequencing and mass spectrometry, respectively. RNA deep sequencing and proteomic analysis revealed exosomes derived from metastatic HCC cell lines carried a large number of protumorigenic RNAs and proteins, such as MET protooncogene, S100 family members and the caveolins. Of interest, we found that exosomes from motile HCC cell lines could significantly enhance the migratory and invasive abilities of non-motile MIHA cell. We further demonstrated that uptake of these shuttled molecules could trigger PI3K/AKT and MAPK signaling pathways in MIHA with increased secretion of active MMP-2 and MMP-9. Our study showed for the first time that HCC-derived exosomes could mobilize normal hepatocyte, which may have implication in facilitating the protrusive activity of HCC cells through liver parenchyma during the process of metastasis.

Deep sequencing of small RNA transcriptome reveals novel non-coding RNAs in hepatocellular carcinoma.

BACKGROUND & AIMS Small non-coding RNAs (ncRNA) are increasingly recognized to play important roles in tumorigenesis. With the advent of deep sequencing, efforts have been put forth to profile the miRNome in a number of human malignancies. However, information on ncRNA in hepatocellular carcinoma (HCC), especially the non-microRNA transcripts, is still lacking. METHODS Small RNA transcriptomes of two HCC cell lines (HKCI-4 and HKCI-8) and an immortalized hepatocyte line (MIHA) were examined using Illumina massively parallel sequencing. Dysregulated ncRNAs were verified in paired HCC tumors and non-tumoral livers (n=73) by quantitative reverse transcription-polymerase chain reaction. Clinicopathologic correlations and in vitro functional investigations were further carried out. RESULTS The combined bioinformatic and biological analyses showed the presence of ncRNAs and the involvement of a new PIWI-interacting RNA (piRNA), piR-Hep1, in liver tumorigenesis. piR-Hep1 was found to be upregulated in 46.6% of HCC tumors compared to the corresponding adjacent non-tumoral liver. Silencing of piR-Hep1 inhibited cell viability, motility, and invasiveness, with a concomitant reduction in the level of active AKT phosphorylation. In the analysis of miRNA, we showed for the first time, the abundant expression of miR-1323 in HCC and its distinct association in tumors arising from a cirrhotic background. Furthermore, miR-1323 overexpression in cirrhotic HCC correlated with poorer disease-free and overall survivals of patients (p<0.009). CONCLUSIONS Our study demonstrated the value of next-generation sequencing in dissecting the ncRNome in cancer. The comprehensive definition of transcriptome unveils virtually all types of ncRNAs and provides new insight into liver carcinogenetic events.

Identification of small RNAs in Mycobacterium smegmatis using heterologous Hfq

Gene regulation by small RNAs (sRNAs) has been extensively studied in various bacteria. However, the presence and roles of sRNAs in mycobacteria remain largely unclear. Immunoprecipitation of RNA chaperone Hfq to enrich for sRNAs is one of the effective methods to isolate sRNAs. However, the lack of an identified mycobacterial hfq restricts the feasibility of this approach. We developed a novel method that takes advantage of the conserved inherent sRNAs-binding capability of heterologous Hfq from Escherichia coli to enrich sRNAs from Mycobacterium smegmatis, a model organism for studying Mycobacterium tuberculosis. We validated 12 trans-encoded and 12 cis-encoded novel sRNAs in M. smegmatis. Many of these sRNAs are differentially expressed at exponential phase compared with stationary phase, suggesting that sRNAs are involved in the growth of mycobacteria. Intriguingly, five of the cis-encoded novel sRNAs target known transposases. Phylogenetic conservation analysis shows that these sRNAs are pathogenicity dependent. We believe that our findings will serve as an important reference for future analysis of sRNAs regulation in mycobacteria and will contribute significantly to the development of sRNAs prediction programs. Moreover, this novel method of using heterologous Hfq for sRNAs enrichment can be of general use for the discovery of bacterial sRNAs in which no endogenous Hfq is identified.

Using RNA-Seq Data to Evaluate Reference Genes Suitable for Gene Expression Studies in Soybean

Differential gene expression profiles often provide important clues for gene functions. While reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is an important tool, the validity of the results depends heavily on the choice of proper reference genes. In this study, we employed new and published RNA-sequencing (RNA-Seq) datasets (26 sequencing libraries in total) to evaluate reference genes reported in previous soybean studies. In silico PCR showed that 13 out of 37 previously reported primer sets have multiple targets, and 4 of them have amplicons with different sizes. Using a probabilistic approach, we identified new and improved candidate reference genes. We further performed 2 validation tests (with 26 RNA samples) on 8 commonly used reference genes and 7 newly identified candidates, using RT-qPCR. In general, the new candidate reference genes exhibited more stable expression levels under the tested experimental conditions. The three newly identified candidate reference genes Bic-C2, F-box protein2, and VPS-like gave the best overall performance, together with the commonly used ELF1b. It is expected that the proposed probabilistic model could serve as an important tool to identify stable reference genes when more soybean RNA-Seq data from different growth stages and treatments are used.

Detection of splicing events and multiread locations from RNA-seq data based on a geometric-tail (GT) distribution of intron length

BackgroundRNA sequencing (RNA-seq) measures gene expression levels and permits splicing analysis. Many existing aligners are capable of mapping millions of sequencing reads onto a reference genome. For reads that can be mapped to multiple positions along the reference genome (multireads), these aligners may either randomly assign them to a location, or discard them altogether. Either way could bias downstream analyses. Meanwhile, challenges remain in the alignment of reads spanning across splice junctions. Existing splicing-aware aligners that rely on the read-count method in identifying junction sites are inevitably affected by sequencing depths.ResultsThe distance between aligned positions of paired-end (PE) reads or two parts of a spliced read is dependent on the experiment protocol and gene structures. We here proposed a new method that employs an empirical geometric-tail (GT) distribution of intron lengths to make a rational choice in multireads selection and splice-sites detection, according to the aligned distances from PE and sliced reads.ConclusionsGT models that combine sequence similarity from alignment, and together with the probability of length distribution, could accurately determine the location of both multireads and spliced reads.

Comparative transcriptomics of multidrug-resistant Acinetobacter baumannii in response to antibiotic treatments

Multidrug-resistant Acinetobacter baumannii, a major hospital-acquired pathogen, is a serious health threat and poses a great challenge to healthcare providers. Although there have been many genomic studies on the evolution and antibiotic resistance of this species, there have been very limited transcriptome studies on its responses to antibiotics. We conducted a comparative transcriptomic study on 12 strains with different growth rates and antibiotic resistance profiles, including 3 fast-growing pan-drug-resistant strains, under separate treatment with 3 antibiotics, namely amikacin, imipenem, and meropenem. We performed deep sequencing using a strand-specific RNA-sequencing protocol, and used de novo transcriptome assembly to analyze gene expression in the form of polycistronic transcripts. Our results indicated that genes associated with transposable elements generally showed higher levels of expression under antibiotic-treated conditions, and many of these transposon-associated genes have previously been linked to drug resistance. Using co-expressed transposon genes as markers, we further identified and experimentally validated two novel genes of which overexpression conferred significant increases in amikacin resistance. To the best of our knowledge, this study represents the first comparative transcriptomic analysis of multidrug-resistant A. baumannii under different antibiotic treatments, and revealed a new relationship between transposons and antibiotic resistance.

Experimental verification of microRNA targets is essential, prediction alone is insufficient

Dear Sir, We refer to recent ‘Letter-to-the-Editor’ from Ma N and Gao X regarding the use of β-actin, a predicted target of hsa-miR-145, as housekeeping control in our earlier published article (1). The authors suggested four target prediction tools, namely TargetScan, miRanda, PicTar and miRGen, could identify β-actin as a potential target of hsa-miR-145 and hence questioned its suitability as internal control in western blot analysis. In response to the authors’ concern, we first would like to draw attention to some practical aspects of computational micro RNA (miRNA) target analysis. It is widely known that many current algorithms used for the identification of miRNA targets have limited positive predictive value (2,3). In fact, most predicted results would require careful scrutiny of target:miRNA complementarity, and experimental validation to confirm target association and influence on gene expression. We surveyed the four proposed target prediction tools for the energy score between hsa-miR-145 and β-actin. Using the developer’s criteria for classifying a ‘successful predicted target’ of each tool, we found only TargetScan and miRanda would regard β-actin as a potential target of hsa-miR-145 with energy value above the cutoff threshold. More importantly, validity of predicted miRNA targets can only be established in validation experiments. In our earlier publication on hsa-miR-145 in hepatocellular carcinoma (1), we have taken precaution in realizing that some housekeeping genes can be influenced by miRNA re-expression. We had assessed both β-actin and glyceraldehyde 3-phosphate dehydrogenasein the presence of hsa-miR-145 mimic, and found stable protein expression of β-actin in repeated experiments. Of interest, glyceraldehyde 3-phosphate dehydrogenase, not a predicted target of hsa-miR-145, was shown to be consistently downregulated; suggesting the probable indirect effect from hsamiR-145. The protein loading in these experiments was controlled by Bradford quantitation and results from hsa-miR-145 mimic were compared with mock control (1). In support of our finding, published articles of hsa-miR-145 in other cancer types also utilized β-actin as housekeeping control for western blot experiments (4,5). Moreover, experimentally validated hsa-miR-145 targets from miRTarBase (6) documented many genes but not β-actin. Overall, these results would suggest β-actin is unlikely a true target of hsa-miR-145. In sum, we believe computational software can assist in predicting potential target genes of miRNA; however, they remain candidates until proven experimentally.

Comparison of Small RNA Profiles of Glycine max and Glycine soja at Early Developmental Stages

Small RNAs, including microRNAs (miRNAs) and phased small interfering RNAs (phasiRNAs; from PHAS loci), play key roles in plant development. Cultivated soybean, Glycine max, contributes a great deal to food production, but, compared to its wild kin, Glycine soja, it may lose some genetic information during domestication. In this work, we analyzed the sRNA profiles of different tissues in both cultivated (C08) and wild soybeans (W05) at three stages of development. A total of 443 known miRNAs and 15 novel miRNAs showed varying abundances between different samples, but the miRNA profiles were generally similar in both accessions. Based on a sliding window analysis workflow that we developed, 50 PHAS loci generating 55 21-nucleotide phasiRNAs were identified in C08, and 46 phasiRNAs from 41 PHAS loci were identified in W05. In germinated seedlings, phasiRNAs were more abundant in C08 than in W05. Disease resistant TIR-NB-LRR genes constitute a very large family of PHAS loci. PhasiRNAs were also generated from several loci that encode for NAC transcription factors, Dicer-like 2 (DCL2), Pentatricopeptide Repeat (PPR), and Auxin Signaling F-box 3 (AFB3) proteins. To investigate the possible involvement of miRNAs in initiating the PHAS-phasiRNA pathway, miRNA target predictions were performed and 17 C08 miRNAs and 15 W05 miRNAs were predicted to trigger phasiRNAs biogenesis. In summary, we provide a comprehensive description of the sRNA profiles of wild versus cultivated soybeans, and discuss the possible roles of sRNAs during soybean germination.