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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

PhyloPythiaS+: a self-training method for the rapid reconstruction of low-ranking taxonomic bins from metagenomes.

Background. Metagenomics is an approach for characterizing environmental microbial communities in situ, it allows their functional and taxonomic characterization and to recover sequences from uncultured taxa. This is often achieved by a combination of sequence assembly and binning, where sequences are grouped into ‘bins’ representing taxa of the underlying microbial community. Assignment to low-ranking taxonomic bins is an important challenge for binning methods as is scalability to Gb-sized datasets generated with deep sequencing techniques. One of the best available methods for species bins recovery from deep-branching phyla is the expert-trained PhyloPythiaS package, where a human expert decides on the taxa to incorporate in the model and identifies ‘training’ sequences based on marker genes directly from the sample. Due to the manual effort involved, this approach does not scale to multiple metagenome samples and requires substantial expertise, which researchers who are new to the area do not have. Results. We have developed PhyloPythiaS+, a successor to our PhyloPythia(S) software. The new (+) component performs the work previously done by the human expert. PhyloPythiaS+ also includes a new k-mer counting algorithm, which accelerated the simultaneous counting of 4-6-mers used for taxonomic binning 100-fold and reduced the overall execution time of the software by a factor of three. Our software allows to analyze Gb-sized metagenomes with inexpensive hardware, and to recover species or genera-level bins with low error rates in a fully automated fashion. PhyloPythiaS+ was compared to MEGAN, taxator-tk, Kraken and the generic PhyloPythiaS model. The results showed that PhyloPythiaS+ performs especially well for samples originating from novel environments in comparison to the other methods. Availability. PhyloPythiaS+ in a virtual machine is available for installation under Windows, Unix systems or OS X on: https://github.com/algbioi/ppsp/wiki.

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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

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

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

Recurrent structural variation, clustered sites of selection, and disease risk for the complement factor H (CFH) gene family.

Structural variation and single-nucleotide variation of the complement factor H (CFH) gene family underlie several complex genetic diseases, including age-related macular degeneration (AMD) and atypical hemolytic uremic syndrome (AHUS). To understand its diversity and evolution, we performed high-quality sequencing of this ~360-kbp locus in six primate lineages, including multiple human haplotypes. Comparative sequence analyses reveal two distinct periods of gene duplication leading to the emergence of four CFH-related (CFHR) gene paralogs (CFHR2 and CFHR4 ~25-35 Mya and CFHR1 and CFHR3 ~7-13 Mya). Remarkably, all evolutionary breakpoints share a common ~4.8-kbp segment corresponding to an ancestral CFHR gene promoter that has expanded independently throughout primate evolution. This segment is recurrently reused and juxtaposed with a donor duplication containing exons 8 and 9 from ancestral CFH, creating four CFHR fusion genes that include lineage-specific members of the gene family. Combined analysis of >5,000 AMD cases and controls identifies a significant burden of a rare missense mutation that clusters at the N terminus of CFH [P = 5.81 × 10-8, odds ratio (OR) = 9.8 (3.67-Infinity)]. A bipolar clustering pattern of rare nonsynonymous mutations in patients with AMD (P < 10-3) and AHUS (P = 0.0079) maps to functional domains that show evidence of positive selection during primate evolution. Our structural variation analysis in >2,400 individuals reveals five recurrent rearrangement breakpoints that show variable frequency among AMD cases and controls. These data suggest a dynamic and recurrent pattern of mutation critical to the emergence of new CFHR genes but also in the predisposition to complex human genetic disease phenotypes.

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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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September 22, 2019

Effects of metal and metalloid pollutants on the microbiota composition of feces obtained from twelve commercial pig farms across China.

Understanding the metal and metalloid contamination and microbiota composition of pig feces is an important step required to support the design and implementation of effective pollution control and prevention strategies. A survey was implemented in 12 locations across China to investigate the content of metals and metalloids, and the main composition of the microbial communities of commercially reared pigs during two growth periods, defined as the early (Q group) and the later fattening growth phases (H group). These data showed widespread Al, Mn, Cu, Zn, and Fe pollution in pig feces. The concentration of Zn in the Q group feces was nearly two times higher than the levels measured in the H group. The microbial composition of the Q group exhibited greater richness of operational taxonomic units (OTUs) and fewer bacteria associated with zoonotic diseases compared with the microbial composition of the H group. Spearman rank correlation analysis showed that Cu and northern latitudes had a significant positive effect on the richness of bacterial communities in pig feces. Zn and Cd exhibited the biggest impact on microbial community composition based on canonical correspondence analysis. Functional metagenomic prediction indicated that about 0.8% genes present in the pig feces bacteria community are related to human diseases, and significantly more predicted pathogenic genes were detected in the H group than in the Q group. These results support the need to monitor heavy metal contamination and to control for zoonotic pathogens disseminated from pig feces in Chinese pig farms. Copyright © 2018. Published by Elsevier B.V.

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September 22, 2019

Differential expression analysis of olfactory genes based on a combination of sequencing platforms and behavioral investigations in Aphidius gifuensis.

Aphidius gifuensis Ashmead is a dominant endoparasitoid of aphids, such as Myzus persicae and Sitobion avenae, and plays an important role in controlling aphids in various habitats, including tobacco plants and wheat in China. A. gifuensis has been successfully applied for the biological control of aphids, especially M. persicae, in green houses and fields in China. The corresponding parasites, as well as its mate-searching behaviors, are subjects of considerable interest. Previous A. gifuensis transcriptome studies have relied on short-read next-generation sequencing (NGS), and the vast majority of the resulting isotigs do not represent full-length cDNA. Here, we employed a combination of NGS and single-molecule real-time (SMRT) sequencing of virgin females (VFs), mated females (MFs), virgin males (VMs), and mated males (MMs) to comprehensively study the A. gifuensis transcriptome. Behavioral responses to the aphid alarm pheromone (E-ß-farnesene, EBF) as well as to A. gifuensis of the opposite sex were also studied. VMs were found to be attracted by female wasps and MFs were repelled by male wasps, whereas MMs and VFs did not respond to the opposite sex. In addition, VFs, MFs, and MMs were attracted by EBF, while VMs did not respond. According to these results, we performed a personalized differential gene expression analysis of olfactory gene sets (66 odorant receptors, 25 inotropic receptors, 16 odorant-binding proteins, and 12 chemosensory proteins) in virgin and mated A. gifuensis of both sexes, and identified 13 candidate genes whose expression levels were highly consistent with behavioral test results, suggesting potential functions for these genes in pheromone perception.

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September 22, 2019

Influenza virus infection causes global RNAPII termination defects.

Viral infection perturbs host cells and can be used to uncover regulatory mechanisms controlling cellular responses and susceptibility to infections. Using cell biological, biochemical, and genetic tools, we reveal that influenza A virus (IAV) infection induces global transcriptional defects at the 3′ ends of active host genes and RNA polymerase II (RNAPII) run-through into extragenic regions. Deregulated RNAPII leads to expression of aberrant RNAs (3′ extensions and host-gene fusions) that ultimately cause global transcriptional downregulation of physiological transcripts, an effect influencing antiviral response and virulence. This phenomenon occurs with multiple strains of IAV, is dependent on influenza NS1 protein, and can be modulated by SUMOylation of an intrinsically disordered region (IDR) of NS1 expressed by the 1918 pandemic IAV strain. Our data identify a strategy used by IAV to suppress host gene expression and indicate that polymorphisms in IDRs of viral proteins can affect the outcome of an infection.

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September 22, 2019

Antagonism between Staphylococcus epidermidis and Propionibacterium acnes and its genomic basis.

Propionibacterium acnes and Staphylococcus epidermidis live in close proximity on human skin, and both bacterial species can be isolated from normal and acne vulgaris-affected skin sites. The antagonistic interactions between the two species are poorly understood, as well as the potential significance of bacterial interferences for the skin microbiota. Here, we performed simultaneous antagonism assays to detect inhibitory activities between multiple isolates of the two species. Selected strains were sequenced to identify the genomic basis of their antimicrobial phenotypes.First, we screened 77 P. acnes strains isolated from healthy and acne-affected skin, and representing all known phylogenetic clades (I, II, and III), for their antimicrobial activities against 12?S. epidermidis isolates. One particular phylogroup (I-2) exhibited a higher antimicrobial activity than other P. acnes phylogroups. All genomes of type I-2 strains carry an island encoding the biosynthesis of a thiopeptide with possible antimicrobial activity against S. epidermidis. Second, 20?S. epidermidis isolates were examined for inhibitory activity against 25 P. acnes strains. The majority of S. epidermidis strains were able to inhibit P. acnes. Genomes of S. epidermidis strains with strong, medium and no inhibitory activities against P. acnes were sequenced. Genome comparison underlined the diversity of S. epidermidis and detected multiple clade- or strain-specific mobile genetic elements encoding a variety of functions important in antibiotic and stress resistance, biofilm formation and interbacterial competition, including bacteriocins such as epidermin. One isolate with an extraordinary antimicrobial activity against P. acnes harbors a functional ESAT-6 secretion system that might be involved in the antimicrobial activity against P. acnes via the secretion of polymorphic toxins.Taken together, our study suggests that interspecies interactions could potentially jeopardize balances in the skin microbiota. In particular, S. epidermidis strains possess an arsenal of different mechanisms to inhibit P. acnes. However, if such interactions are relevant in skin disorders such as acne vulgaris remains questionable, since no difference in the antimicrobial activity against, or the sensitivity towards S. epidermidis could be detected between health- and acne-associated strains of P. acnes.

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