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September 22, 2019  |  

Differential TGFß pathway targeting by miR-122 in humans and mice affects liver cancer metastasis.

Downregulation of a predominantly hepatocyte-specific miR-122 is associated with human liver cancer metastasis, whereas miR-122-deficient mice display normal liver function. Here we show a functional conservation of miR-122 in the TGFß pathway: miR-122 target site is present in the mouse but not human TGFßR1, whereas a noncanonical target site is present in the TGFß1 5’UTR in humans and other primates. Experimental switch of the miR-122 target between the receptor TGFßR1 and the ligand TGFß1 changes the metastatic properties of mouse and human liver cancer cells. High expression of TGFß1 in human primary liver tumours is associated with poor survival. We identify over 50 other miRNAs orthogonally targeting ligand/receptor pairs in humans and mice, suggesting that these are evolutionarily common events. These results reveal an evolutionary mechanism for miRNA-mediated gene regulation underlying species-specific physiological or pathological phenotype and provide a potentially valuable strategy for treating liver-associated diseases.

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September 22, 2019  |  

Identification and characterization of a carboxypeptidase N1 from red lip mullet (Liza haematocheila); revealing its immune relevance.

Complement system orchestrates the innate and adaptive immunity via the activation, recruitment, and regulation of immune molecules to destroy pathogens. However, regulation of the complement is essential to avoid injuries to the autologous tissues. The present study unveils the characteristic features of an important complement component, anaphylatoxin inactivator from red lip mullet at its molecular and functional level. Mullet carboxypeptidase N1 (MuCPN1) cDNA sequence possessed an open reading frame of 1347 bp, which encoded a protein of 449 amino acids with a predicted molecular weight of 51?kDa. In silico analysis discovered two domains of PM14-Zn carboxypeptidase and a C-terminal domain of M14 N/E carboxypeptidase, two zinc-binding signature motifs, and an N-glycosylation site in the MuCPN1 sequence. Homology analysis revealed that most of the residues in the sequence are conserved among the other selected homologs. Phylogeny analysis showed that MuCPN1 closely cladded with the Maylandia zebra CPN1 and clustered together with the teleostean counterparts. A challenge experiment showed modulated expression of MuCPN1 upon polyinosinic:polycytidylic acid and Lactococcus garviae in head kidney, spleen, gill, and liver tissues. The highest upregulation of MuCPN1 was observed 24?h post infection against poly I:C in each tissue. Moreover, the highest relative expressions upon L. garviae challenge were observed at 24?h post infection in head kidney tissue and 48?h post infection in spleen, gill, and liver tissues. MuCPN1 transfected cells triggered a 2.2-fold increase of nitric oxide (NO) production upon LPS stimulation compared to the un-transfected controls suggesting that MuCPN1 is an active protease which releases arginine from complement C3a, C4a, and C5a. These results have driven certain way towards enhancing the understanding of immune role of MuCPN1 in the complement defense mechanism of red lip mullet. Copyright © 2018 Elsevier Ltd. All rights reserved.

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September 22, 2019  |  

The third revolution in sequencing technology.

Forty years ago the advent of Sanger sequencing was revolutionary as it allowed complete genome sequences to be deciphered for the first time. A second revolution came when next-generation sequencing (NGS) technologies appeared, which made genome sequencing much cheaper and faster. However, NGS methods have several drawbacks and pitfalls, most notably their short reads. Recently, third-generation/long-read methods appeared, which can produce genome assemblies of unprecedented quality. Moreover, these technologies can directly detect epigenetic modifications on native DNA and allow whole-transcript sequencing without the need for assembly. This marks the third revolution in sequencing technology. Here we review and compare the various long-read methods. We discuss their applications and their respective strengths and weaknesses and provide future perspectives. Copyright © 2018 Elsevier Ltd. All rights reserved.

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September 22, 2019  |  

CLK-dependent exon recognition and conjoined gene formation revealed with a novel small molecule inhibitor.

CDC-like kinase phosphorylation of serine/arginine-rich proteins is central to RNA splicing reactions. Yet, the genomic network of CDC-like kinase-dependent RNA processing events remains poorly defined. Here, we explore the connectivity of genomic CDC-like kinase splicing functions by applying graduated, short-exposure, pharmacological CDC-like kinase inhibition using a novel small molecule (T3) with very high potency, selectivity, and cell-based stability. Using RNA-Seq, we define CDC-like kinase-responsive alternative splicing events, the large majority of which monotonically increase or decrease with increasing CDC-like kinase inhibition. We show that distinct RNA-binding motifs are associated with T3 response in skipped exons. Unexpectedly, we observe dose-dependent conjoined gene transcription, which is associated with motif enrichment in the last and second exons of upstream and downstream partners, respectively. siRNA knockdown of CLK2-associated genes significantly increases conjoined gene formation. Collectively, our results reveal an unexpected role for CDC-like kinase in conjoined gene formation, via regulation of 3′-end processing and associated splicing factors.The phosphorylation of serine/arginine-rich proteins by CDC-like kinase is a central regulatory mechanism for RNA splicing reactions. Here, the authors synthesize a novel small molecule CLK inhibitor and map CLK-responsive alternative splicing events and discover an effect on conjoined gene transcription.

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September 22, 2019  |  

Separation and parallel sequencing of the genomes and transcriptomes of single cells using G&T-seq.

Parallel sequencing of a single cell’s genome and transcriptome provides a powerful tool for dissecting genetic variation and its relationship with gene expression. Here we present a detailed protocol for G&T-seq, a method for separation and parallel sequencing of genomic DNA and full-length polyA(+) mRNA from single cells. We provide step-by-step instructions for the isolation and lysis of single cells; the physical separation of polyA(+) mRNA from genomic DNA using a modified oligo-dT bead capture and the respective whole-transcriptome and whole-genome amplifications; and library preparation and sequence analyses of these amplification products. The method allows the detection of thousands of transcripts in parallel with the genetic variants captured by the DNA-seq data from the same single cell. G&T-seq differs from other currently available methods for parallel DNA and RNA sequencing from single cells, as it involves physical separation of the DNA and RNA and does not require bespoke microfluidics platforms. The process can be implemented manually or through automation. When performed manually, paired genome and transcriptome sequencing libraries from eight single cells can be produced in ~3 d by researchers experienced in molecular laboratory work. For users with experience in the programming and operation of liquid-handling robots, paired DNA and RNA libraries from 96 single cells can be produced in the same time frame. Sequence analysis and integration of single-cell G&T-seq DNA and RNA data requires a high level of bioinformatics expertise and familiarity with a wide range of informatics tools.

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September 22, 2019  |  

Androgen receptor variant AR-V9 is co-expressed with AR-V7 in prostate cancer metastases and predicts abiraterone resistance.

Purpose: Androgen receptor (AR) variant AR-V7 is a ligand-independent transcription factor that promotes prostate cancer resistance to AR-targeted therapies.  Accordingly, efforts are underway to develop strategies for monitoring and inhibiting AR-V7 in castration-resistant prostate cancer (CRPC).  The purpose of this study was to understand whether other AR variants may be co-expressed with AR-V7 and promote resistance to AR-targeted therapies. Experimental Design:  We utilized complementary short- and long-read sequencing of intact AR mRNA isoforms to characterize AR expression in CRPC models.  Co-expression of AR-V7 and AR-V9 mRNA in CRPC metastases and circulating tumor cells was assessed by RNA-seq and RT-PCR, respectively.  Expression of AR-V9 protein in CRPC models was evaluated with polyclonal antisera.  Multivariate analysis was performed to test whether AR variant mRNA expression in metastatic tissues was associated with a 12-week progression-free survival endpoint in a prospective clinical trial of 78 CRPC-stage patients initiating therapy with the androgen synthesis inhibitor, abiraterone acetate. Results: AR-V9 was frequently co-expressed with AR-V7.  Both AR variant species were found to share a common 3′ terminal cryptic exon, which rendered AR-V9 susceptible to experimental manipulations that were previously-thought to target AR-V7 uniquely.  AR-V9 promoted ligand-independent growth of prostate cancer cells.  High AR-V9 mRNA expression in CRPC metastases was predictive of primary resistance to abiraterone acetate (HR = 4.0, 95% CI = 1.31-12.2, P = 0.02).   Conclusions:  AR-V9 may be an important component of therapeutic resistance in CRPC. Copyright ©2017, American Association for Cancer Research.

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September 22, 2019  |  

L_RNA_scaffolder: scaffolding genomes with transcripts.

Generation of large mate-pair libraries is necessary for de novo genome assembly but the procedure is complex and time-consuming. Furthermore, in some complex genomes, it is hard to increase the N50 length even with large mate-pair libraries, which leads to low transcript coverage. Thus, it is necessary to develop other simple scaffolding approaches, to at least solve the elongation of transcribed fragments.We describe L_RNA_scaffolder, a novel genome scaffolding method that uses long transcriptome reads to order, orient and combine genomic fragments into larger sequences. To demonstrate the accuracy of the method, the zebrafish genome was scaffolded. With expanded human transcriptome data, the N50 of human genome was doubled and L_RNA_scaffolder out-performed most scaffolding results by existing scaffolders which employ mate-pair libraries. In these two examples, the transcript coverage was almost complete, especially for long transcripts. We applied L_RNA_scaffolder to the highly polymorphic pearl oyster draft genome and the gene model length significantly increased.The simplicity and high-throughput of RNA-seq data makes this approach suitable for genome scaffolding. L_RNA_scaffolder is available at http://www.fishbrowser.org/software/L_RNA_scaffolder.

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September 22, 2019  |  

Bayesian nonparametric discovery of isoforms and individual specific quantification.

Most human protein-coding genes can be transcribed into multiple distinct mRNA isoforms. These alternative splicing patterns encourage molecular diversity, and dysregulation of isoform expression plays an important role in disease etiology. However, isoforms are difficult to characterize from short-read RNA-seq data because they share identical subsequences and occur in different frequencies across tissues and samples. Here, we develop BIISQ, a Bayesian nonparametric model for isoform discovery and individual specific quantification from short-read RNA-seq data. BIISQ does not require isoform reference sequences but instead estimates an isoform catalog shared across samples. We use stochastic variational inference for efficient posterior estimates and demonstrate superior precision and recall for simulations compared to state-of-the-art isoform reconstruction methods. BIISQ shows the most gains for low abundance isoforms, with 36% more isoforms correctly inferred at low coverage versus a multi-sample method and 170% more versus single-sample methods. We estimate isoforms in the GEUVADIS RNA-seq data and validate inferred isoforms by associating genetic variants with isoform ratios.

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September 22, 2019  |  

Transcriptome profiling using single-molecule direct RNA sequencing approach for in-depth understanding of genes in secondary metabolism pathways of Camellia sinensis.

Characteristic secondary metabolites, including flavonoids, theanine and caffeine, are important components of Camellia sinensis, and their biosynthesis has attracted widespread interest. Previous studies on the biosynthesis of these major secondary metabolites using next-generation sequencing technologies limited the accurately prediction of full-length (FL) splice isoforms. Herein, we applied single-molecule sequencing to pooled tea plant tissues, to provide a more complete transcriptome of C. sinensis. Moreover, we identified 94 FL transcripts and four alternative splicing events for enzyme-coding genes involved in the biosynthesis of flavonoids, theanine and caffeine. According to the comparison between long-read isoforms and assemble transcripts, we improved the quality and accuracy of genes sequenced by short-read next-generation sequencing technology. The resulting FL transcripts, together with the improved assembled transcripts and identified alternative splicing events, enhance our understanding of genes involved in the biosynthesis of characteristic secondary metabolites in C. sinensis.

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September 22, 2019  |  

PacBio full-length transcriptome profiling of insect mitochondrial gene expression.

In this study, we sequenced the first full-length insect transcriptome using the Erthesina fullo Thunberg based on the PacBio platform. We constructed the first quantitative transcription map of animal mitochondrial genomes and built a straightforward and concise methodology to investigate mitochondrial gene transcription, RNA processing, mRNA maturation and several other related topics. Most of the results were consistent with the previous studies, while to the best of our knowledge some findings were reported for the first time in this study. The new findings included the high levels of mitochondrial gene expression, the 3′ polyadenylation and possible 5′ m(7)G caps of rRNAs, the isoform diversity of 12S rRNA, the polycistronic transcripts and natural antisense transcripts of mitochondrial genes et al. These findings could challenge and enrich fundamental concepts of mitochondrial gene transcription and RNA processing, particularly of the rRNA primary (sequence) structure. The methodology constructed in this study can also be used to study gene expression or RNA processing of nuclear genomes.

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September 22, 2019  |  

Computational identification of novel genes: current and future perspectives.

While it has long been thought that all genomic novelties are derived from the existing material, many genes lacking homology to known genes were found in recent genome projects. Some of these novel genes were proposed to have evolved de novo, ie, out of noncoding sequences, whereas some have been shown to follow a duplication and divergence process. Their discovery called for an extension of the historical hypotheses about gene origination. Besides the theoretical breakthrough, increasing evidence accumulated that novel genes play important roles in evolutionary processes, including adaptation and speciation events. Different techniques are available to identify genes and classify them as novel. Their classification as novel is usually based on their similarity to known genes, or lack thereof, detected by comparative genomics or against databases. Computational approaches are further prime methods that can be based on existing models or leveraging biological evidences from experiments. Identification of novel genes remains however a challenging task. With the constant software and technologies updates, no gold standard, and no available benchmark, evaluation and characterization of genomic novelty is a vibrant field. In this review, the classical and state-of-the-art tools for gene prediction are introduced. The current methods for novel gene detection are presented; the methodological strategies and their limits are discussed along with perspective approaches for further studies.

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September 22, 2019  |  

Single-molecule long-read transcriptome profiling of Platysternon megacephalum mitochondrial genome with gene rearrangement and control region duplication.

Platysternon megacephalum is the sole living representative of the poorly studied turtle lineage Platysternidae. Their mitochondrial genome has been subject to gene rearrangement and control region duplication, resulting in a unique mitochondrial gene order in vertebrates. In this study, we sequenced the first full-length turtle (P. megacephalum) liver transcriptome using single-molecule real-time sequencing to study the transcriptional mechanisms of its mitochondrial genome. ND5 and ND6 anti-sense (ND6AS) forms a single transcript with the same expression in the human mitochondrial genome, but here we demonstrated differential expression of the rearranged ND5 and ND6AS genes in P. megacephalum. And some polycistronic transcripts were also reported in this study. Notably, we detected some novel long non-coding RNAs with alternative polyadenylation from the duplicated control region, and a novel ND6AS transcript composed of a long non-coding sequence, ND6AS, and tRNA-GluAS. These results provide the first description of a mtDNA transcriptome with gene rearrangement and control region duplication. These findings further our understanding of the fundamental concepts of mitochondrial gene transcription and RNA processing, and provide a new insight into the mechanism of transcription regulation of the mitochondrial genome.

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September 22, 2019  |  

High-confidence coding and noncoding transcriptome maps.

The advent of high-throughput RNA sequencing (RNA-seq) has led to the discovery of unprecedentedly immense transcriptomes encoded by eukaryotic genomes. However, the transcriptome maps are still incomplete partly because they were mostly reconstructed based on RNA-seq reads that lack their orientations (known as unstranded reads) and certain boundary information. Methods to expand the usability of unstranded RNA-seq data by predetermining the orientation of the reads and precisely determining the boundaries of assembled transcripts could significantly benefit the quality of the resulting transcriptome maps. Here, we present a high-performing transcriptome assembly pipeline, called CAFE, that significantly improves the original assemblies, respectively assembled with stranded and/or unstranded RNA-seq data, by orienting unstranded reads using the maximum likelihood estimation and by integrating information about transcription start sites and cleavage and polyadenylation sites. Applying large-scale transcriptomic data comprising 230 billion RNA-seq reads from the ENCODE, Human BodyMap 2.0, The Cancer Genome Atlas, and GTEx projects, CAFE enabled us to predict the directions of about 220 billion unstranded reads, which led to the construction of more accurate transcriptome maps, comparable to the manually curated map, and a comprehensive lncRNA catalog that includes thousands of novel lncRNAs. Our pipeline should not only help to build comprehensive, precise transcriptome maps from complex genomes but also to expand the universe of noncoding genomes.© 2017 You et al.; Published by Cold Spring Harbor Laboratory Press.

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September 22, 2019  |  

SparseIso: a novel Bayesian approach to identify alternatively spliced isoforms from RNA-seq data.

Recent advances in high-throughput RNA sequencing (RNA-seq) technologies have made it possible to reconstruct the full transcriptome of various types of cells. It is important to accurately assemble transcripts or identify isoforms for an improved understanding of molecular mechanisms in biological systems.We have developed a novel Bayesian method, SparseIso, to reliably identify spliced isoforms from RNA-seq data. A spike-and-slab prior is incorporated into the Bayesian model to enforce the sparsity for isoform identification, effectively alleviating the problem of overfitting. A Gibbs sampling procedure is further developed to simultaneously identify and quantify transcripts from RNA-seq data. With the sampling approach, SparseIso estimates the joint distribution of all candidate transcripts, resulting in a significantly improved performance in detecting lowly expressed transcripts and multiple expressed isoforms of genes. Both simulation study and real data analysis have demonstrated that the proposed SparseIso method significantly outperforms existing methods for improved transcript assembly and isoform identification.The SparseIso package is available at http://github.com/henryxushi/SparseIso.xuan@vt.edu.Supplementary data are available at Bioinformatics online.© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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September 22, 2019  |  

wtf genes are prolific dual poison-antidote meiotic drivers.

Meiotic drivers are selfish genes that bias their transmission into gametes, defying Mendelian inheritance. Despite the significant impact of these genomic parasites on evolution and infertility, few meiotic drive loci have been identified or mechanistically characterized. Here, we demonstrate a complex landscape of meiotic drive genes on chromosome 3 of the fission yeasts Schizosaccharomyces kambucha and S. pombe. We identify S. kambucha wtf4 as one of these genes that acts to kill gametes (known as spores in yeast) that do not inherit the gene from heterozygotes. wtf4 utilizes dual, overlapping transcripts to encode both a gamete-killing poison and an antidote to the poison. To enact drive, all gametes are poisoned, whereas only those that inherit wtf4 are rescued by the antidote. Our work suggests that the wtf multigene family proliferated due to meiotic drive and highlights the power of selfish genes to shape genomes, even while imposing tremendous costs to fertility.

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