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September 22, 2019  |  

Dynamic regulation of HIV-1 mRNA populations analyzed by single-molecule enrichment and long-read sequencing.

Alternative RNA splicing greatly expands the repertoire of proteins encoded by genomes. Next-generation sequencing (NGS) is attractive for studying alternative splicing because of the efficiency and low cost per base, but short reads typical of NGS only report mRNA fragments containing one or few splice junctions. Here, we used single-molecule amplification and long-read sequencing to study the HIV-1 provirus, which is only 9700 bp in length, but encodes nine major proteins via alternative splicing. Our data showed that the clinical isolate HIV-1(89.6) produces at least 109 different spliced RNAs, including a previously unappreciated ~1 kb class of messages, two of which encode new proteins. HIV-1 message populations differed between cell types, longitudinally during infection, and among T cells from different human donors. These findings open a new window on a little studied aspect of HIV-1 replication, suggest therapeutic opportunities and provide advanced tools for the study of alternative splicing.

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September 22, 2019  |  

Metagenomic binning and association of plasmids with bacterial host genomes using DNA methylation.

Shotgun metagenomics methods enable characterization of microbial communities in human microbiome and environmental samples. Assembly of metagenome sequences does not output whole genomes, so computational binning methods have been developed to cluster sequences into genome ‘bins’. These methods exploit sequence composition, species abundance, or chromosome organization but cannot fully distinguish closely related species and strains. We present a binning method that incorporates bacterial DNA methylation signatures, which are detected using single-molecule real-time sequencing. Our method takes advantage of these endogenous epigenetic barcodes to resolve individual reads and assembled contigs into species- and strain-level bins. We validate our method using synthetic and real microbiome sequences. In addition to genome binning, we show that our method links plasmids and other mobile genetic elements to their host species in a real microbiome sample. Incorporation of DNA methylation information into shotgun metagenomics analyses will complement existing methods to enable more accurate sequence binning.

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September 22, 2019  |  

Clinical PathoScope: rapid alignment and filtration for accurate pathogen identification in clinical samples using unassembled sequencing data.

The use of sequencing technologies to investigate the microbiome of a sample can positively impact patient healthcare by providing therapeutic targets for personalized disease treatment. However, these samples contain genomic sequences from various sources that complicate the identification of pathogens.Here we present Clinical PathoScope, a pipeline to rapidly and accurately remove host contamination, isolate microbial reads, and identify potential disease-causing pathogens. We have accomplished three essential tasks in the development of Clinical PathoScope. First, we developed an optimized framework for pathogen identification using a computational subtraction methodology in concordance with read trimming and ambiguous read reassignment. Second, we have demonstrated the ability of our approach to identify multiple pathogens in a single clinical sample, accurately identify pathogens at the subspecies level, and determine the nearest phylogenetic neighbor of novel or highly mutated pathogens using real clinical sequencing data. Finally, we have shown that Clinical PathoScope outperforms previously published pathogen identification methods with regard to computational speed, sensitivity, and specificity.Clinical PathoScope is the only pathogen identification method currently available that can identify multiple pathogens from mixed samples and distinguish between very closely related species and strains in samples with very few reads per pathogen. Furthermore, Clinical PathoScope does not rely on genome assembly and thus can more rapidly complete the analysis of a clinical sample when compared with current assembly-based methods. Clinical PathoScope is freely available at: http://sourceforge.net/projects/pathoscope/.

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September 22, 2019  |  

Evolution of selective-sequencing approaches for virus discovery and virome analysis.

Recent advances in sequencing technologies have transformed the field of virus discovery and virome analysis. Once mostly confined to the traditional Sanger sequencing based individual virus discovery, is now entirely replaced by high throughput sequencing (HTS) based virus metagenomics that can be used to characterize the nature and composition of entire viromes. To better harness the potential of HTS for the study of viromes, sample preparation methodologies use different approaches to exclude amplification of non-viral components that can overshadow low-titer viruses. These virus-sequence enrichment approaches mostly focus on the sample preparation methods, like enzymatic digestion of non-viral nucleic acids and size exclusion of non-viral constituents by column filtration, ultrafiltration or density gradient centrifugation. However, recently a new approach of virus-sequence enrichment called virome-capture sequencing, focused on the amplification or HTS library preparation stage, was developed to increase the ability of virome characterization. This new approach has the potential to further transform the field of virus discovery and virome analysis, but its technical complexity and sequence-dependence warrants further improvements. In this review we discuss the different methods, their applications and evolution, for selective sequencing based virome analysis and also propose refinements needed to harness the full potential of HTS for virome analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

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September 22, 2019  |  

Global dissection of alternative splicing uncovers transcriptional diversity in tissues and associates with the flavonoid pathway in tea plant (Camellia sinensis).

Alternative splicing (AS) regulates mRNA at the post-transcriptional level to change gene function in organisms. However, little is known about the AS and its roles in tea plant (Camellia sinensis), widely cultivated for making a popular beverage tea.In our study, the AS landscape and dynamics were characterized in eight tissues (bud, young leaf, summer mature leaf, winter old leaf, stem, root, flower, fruit) of tea plant by Illumina RNA-Seq and confirmed by Iso-Seq. The most abundant AS (~?20%) was intron retention and involved in RNA processes. The some alternative splicings were found to be tissue specific in stem and root etc. Thirteen co-expressed modules of AS transcripts were identified, which revealed a similar pattern between the bud and young leaves as well as a distinct pattern between seasons. AS events of structural genes including anthocyanidin reductase and MYB transcription factors were involved in biosynthesis of flavonoid, especially in vegetative tissues. The AS isoforms rather than the full-length ones were the major transcripts involved in flavonoid synthesis pathway, and is positively correlated with the catechins content conferring the tea taste. We propose that the AS is an important functional mechanism in regulating flavonoid metabolites.Our study provides the insight into the AS events underlying tea plant’s uniquely different developmental process and highlights the important contribution and efficacy of alternative splicing regulatory function to biosynthesis of flavonoids.

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September 22, 2019  |  

Genome-wide transcriptome profiling of the medicinal plant Zanthoxylum planispinum using a single-molecule direct RNA sequencing approach.

High-throughput RNA sequencing has revolutionized transcriptome-based studies of candidate genes, key pathways and gene regulation in non-model organisms. We analyzed full-length cDNA sequences in Zanthoxylum planispinum (Z. planispinum), a medicinal herb in major parts of East Asia. The full-length mRNA derived from tissues of leaf, early fruit and maturing fruit stage were sequenced using PacBio RSII platform to identify isoform transcriptome. We obtained 51,402 unigenes, with average 1781?bp per gene in 82.473?Mb gene lengths. Among 51,402, 3963 unigenes showed variety of isoform. By selection of one representative gene among each of the various isoforms, we finalized 46,306 unique gene set for this herb. We identified 76 cytochrome P450 (CYP450) and related isoforms that are of the wide diversity in the molecular function and biological process. These transcriptome data of Z. planispinum will provide a good resource to study metabolic engineering for the production of valuable medicinal drugs and phytochemicals. Copyright © 2018. Published by Elsevier Inc.

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September 22, 2019  |  

Long-read sequencing of the coffee bean transcriptome reveals the diversity of full-length transcripts.

Polyploidization contributes to the complexity of gene expression, resulting in numerous related but different transcripts. This study explored the transcriptome diversity and complexity of the tetraploid Arabica coffee (Coffea arabica) bean. Long-read sequencing (LRS) by Pacbio Isoform sequencing (Iso-seq) was used to obtain full-length transcripts without the difficulty and uncertainty of assembly required for reads from short-read technologies. The tetraploid transcriptome was annotated and compared with data from the sub-genome progenitors. Caffeine and sucrose genes were targeted for case analysis. An isoform-level tetraploid coffee bean reference transcriptome with 95 995 distinct transcripts (average 3236 bp) was obtained. A total of 88 715 sequences (92.42%) were annotated with BLASTx against NCBI non-redundant plant proteins, including 34 719 high-quality annotations. Further BLASTn analysis against NCBI non-redundant nucleotide sequences, Coffea canephora coding sequences with UTR, C. arabica ESTs, and Rfam resulted in 1213 sequences without hits, were potential novel genes in coffee. Longer UTRs were captured, especially in the 5?UTRs, facilitating the identification of upstream open reading frames. The LRS also revealed more and longer transcript variants in key caffeine and sucrose metabolism genes from this polyploid genome. Long sequences (>10 kilo base) were poorly annotated. LRS technology shows the limitation of previous studies. It provides an important tool to produce a reference transcriptome including more of the diversity of full-length transcripts to help understand the biology and support the genetic improvement of polyploid species such as coffee.© The Authors 2017. Published by Oxford University Press.

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September 22, 2019  |  

Improved OTU-picking using long-read 16S rRNA gene amplicon sequencing and generic hierarchical clustering

BACKGROUND: High-throughput bacterial 16S rRNA gene sequencing followed by clustering of short sequences into operational taxonomic units (OTUs) is widely used for microbiome profiling. However, clustering of short 16S rRNA gene reads into biologically meaningful OTUs is challenging, in part because nucleotide variation along the 16S rRNA gene is only partially captured by short reads. The recent emergence of long-read platforms, such as single-molecule real-time (SMRT) sequencing from Pacific Biosciences, offers the potential for improved taxonomic and phylogenetic profiling. Here, we evaluate the performance of long- and short-read 16S rRNA gene sequencing using simulated and experimental data, followed by OTU inference using computational pipelines based on heuristic and complete-linkage hierarchical clustering. RESULTS: In simulated data, long-read sequencing was shown to improve OTU quality and decrease variance. We then profiled 40 human gut microbiome samples using a combination of Illumina MiSeq and Blautia-specific SMRT sequencing, further supporting the notion that long reads can identify additional OTUs. We implemented a complete-linkage hierarchical clustering strategy using a flexible computational pipeline, tailored specifically for PacBio circular consensus sequencing (CCS) data that outperforms heuristic methods in most settings: https://github.com/oscar-franzen/oclust/. CONCLUSION: Our data demonstrate that long reads can improve OTU inference; however, the choice of clustering algorithm and associated clustering thresholds has significant impact on performance.

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September 22, 2019  |  

MetaSort untangles metagenome assembly by reducing microbial community complexity.

Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly. Furthermore, we applied metaSort to an unexplored microflora colonized on the surface of marine kelp and successfully recovered 75 high-quality genomes at one time. This approach will greatly improve access to microbial genomes from complex or novel communities.

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September 22, 2019  |  

Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes.

Pan-bacterial 16S rRNA microbiome surveys performed with massively parallel DNA sequencing technologies have transformed community microbiological studies. Current 16S profiling methods, however, fail to provide sufficient taxonomic resolution and accuracy to adequately perform species-level associative studies for specific conditions. This is due to the amplification and sequencing of only short 16S rRNA gene regions, typically providing for only family- or genus-level taxonomy. Moreover, sequencing errors often inflate the number of taxa present. Pacific Biosciences’ (PacBio’s) long-read technology in particular suffers from high error rates per base. Herein, we present a microbiome analysis pipeline that takes advantage of PacBio circular consensus sequencing (CCS) technology to sequence and error correct full-length bacterial 16S rRNA genes, which provides high-fidelity species-level microbiome data.Analysis of a mock community with 20 bacterial species demonstrated 100% specificity and sensitivity with regard to taxonomic classification. Examination of a 250-plus species mock community demonstrated correct species-level classification of >?90% of taxa, and relative abundances were accurately captured. The majority of the remaining taxa were demonstrated to be multiply, incorrectly, or incompletely classified. Using this methodology, we examined the microgeographic variation present among the microbiomes of six sinonasal sites, by both swab and biopsy, from the anterior nasal cavity to the sphenoid sinus from 12 subjects undergoing trans-sphenoidal hypophysectomy. We found greater variation among subjects than among sites within a subject, although significant within-individual differences were also observed. Propiniobacterium acnes (recently renamed Cutibacterium acnes) was the predominant species throughout, but was found at distinct relative abundances by site.Our microbial composition analysis pipeline for single-molecule real-time 16S rRNA gene sequencing (MCSMRT, https://github.com/jpearl01/mcsmrt ) overcomes deficits of standard marker gene-based microbiome analyses by using CCS of entire 16S rRNA genes to provide increased taxonomic and phylogenetic resolution. Extensions of this approach to other marker genes could help refine taxonomic assignments of microbial species and improve reference databases, as well as strengthen the specificity of associations between microbial communities and dysbiotic states.

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September 22, 2019  |  

CATCh, an ensemble classifier for chimera detection in 16S rRNA sequencing studies.

In ecological studies, microbial diversity is nowadays mostly assessed via the detection of phylogenetic marker genes, such as 16S rRNA. However, PCR amplification of these marker genes produces a significant amount of artificial sequences, often referred to as chimeras. Different algorithms have been developed to remove these chimeras, but efforts to combine different methodologies are limited. Therefore, two machine learning classifiers (reference-based and de novo CATCh) were developed by integrating the output of existing chimera detection tools into a new, more powerful method. When comparing our classifiers with existing tools in either the reference-based or de novo mode, a higher performance of our ensemble method was observed on a wide range of sequencing data, including simulated, 454 pyrosequencing, and Illumina MiSeq data sets. Since our algorithm combines the advantages of different individual chimera detection tools, our approach produces more robust results when challenged with chimeric sequences having a low parent divergence, short length of the chimeric range, and various numbers of parents. Additionally, it could be shown that integrating CATCh in the preprocessing pipeline has a beneficial effect on the quality of the clustering in operational taxonomic units. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

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September 22, 2019  |  

Alternative polyadenylation: methods, findings, and impacts.

Alternative polyadenylation (APA), a phenomenon that RNA molecules with different 3′ ends originate from distinct polyadenylation sites of a single gene, is emerging as a mechanism widely used to regulate gene expression. In the present review, we first summarized various methods prevalently adopted in APA study, mainly focused on the next-generation sequencing (NGS)-based techniques specially designed for APA identification, the related bioinformatics methods, and the strategies for APA study in single cells. Then we summarized the main findings and advances so far based on these methods, including the preferences of alternative polyA (pA) site, the biological processes involved, and the corresponding consequences. We especially categorized the APA changes discovered so far and discussed their potential functions under given conditions, along with the possible underlying molecular mechanisms. With more in-depth studies on extensive samples, more signatures and functions of APA will be revealed, and its diverse roles will gradually heave in sight. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

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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  |  

Limited effects of variable-retention harvesting on fungal communities decomposing fine roots in coastal temperate rainforests.

Fine root litter is the principal source of carbon stored in forest soils and a dominant source of carbon for fungal decomposers. Differences in decomposer capacity between fungal species may be important determinants of fine-root decomposition rates. Variable-retention harvesting (VRH) provides refuge for ectomycorrhizal fungi, but its influence on fine-root decomposers is unknown, as are the effects of functional shifts in these fungal communities on carbon cycling. We compared fungal communities decomposing fine roots (in litter bags) under VRH, clear-cut, and uncut stands at two sites (6 and 13 years postharvest) and two decay stages (43 days and 1 year after burial) in Douglas fir forests in coastal British Columbia, Canada. Fungal species and guilds were identified from decomposed fine roots using high-throughput sequencing. Variable retention had short-term effects on ß-diversity; harvest treatment modified the fungal community composition at the 6-year-postharvest site, but not at the 13-year-postharvest site. Ericoid and ectomycorrhizal guilds were not more abundant under VRH, but stand age significantly structured species composition. Guild composition varied by decay stage, with ruderal species later replaced by saprotrophs and ectomycorrhizae. Ectomycorrhizal abundance on decomposing fine roots may partially explain why fine roots typically decompose more slowly than surface litter. Our results indicate that stand age structures fine-root decomposers but that decay stage is more important in structuring the fungal community than shifts caused by harvesting. The rapid postharvest recovery of fungal communities decomposing fine roots suggests resiliency within this community, at least in these young regenerating stands in coastal British Columbia.IMPORTANCE Globally, fine roots are a dominant source of carbon in forest soils, yet the fungi that decompose this material and that drive the sequestration or respiration of this carbon remain largely uncharacterized. Fungi vary in their capacity to decompose plant litter, suggesting that fungal community composition is an important determinant of decomposition rates. Variable-retention harvesting is a forestry practice that modifies fungal communities by providing refuge for ectomycorrhizal fungi. We evaluated the effects of variable retention and clear-cut harvesting on fungal communities decomposing fine roots at two sites (6 and 13 years postharvest), at two decay stages (43 days and 1 year), and in uncut stands in temperate rainforests. Harvesting impacts on fungal community composition were detected only after 6 years after harvest. We suggest that fungal community composition may be an important factor that reduces fine-root decomposition rates relative to those of above-ground plant litter, which has important consequences for forest carbon cycling. Copyright © 2018 American Society for Microbiology.

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