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September 22, 2019

Interpreting microbial biosynthesis in the genomic age: Biological and practical considerations.

Genome mining has become an increasingly powerful, scalable, and economically accessible tool for the study of natural product biosynthesis and drug discovery. However, there remain important biological and practical problems that can complicate or obscure biosynthetic analysis in genomic and metagenomic sequencing projects. Here, we focus on limitations of available technology as well as computational and experimental strategies to overcome them. We review the unique challenges and approaches in the study of symbiotic and uncultured systems, as well as those associated with biosynthetic gene cluster (BGC) assembly and product prediction. Finally, to explore sequencing parameters that affect the recovery and contiguity of large and repetitive BGCs assembled de novo, we simulate Illumina and PacBio sequencing of the Salinispora tropica genome focusing on assembly of the salinilactam (slm) BGC.

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September 22, 2019

Plant 24-nt reproductive phasiRNAs from intramolecular duplex mRNAs in diverse monocots.

In grasses, two pathways that generate diverse and numerous 21-nt (premeiotic) and 24-nt (meiotic) phased siRNAs are highly enriched in anthers, the male reproductive organs. These “phasiRNAs” are analogous to mammalian piRNAs, yet their functions and evolutionary origins remain largely unknown. The 24-nt meiotic phasiRNAs have only been described in grasses, wherein their biogenesis is dependent on a specialized Dicer (DCL5). To assess how evolution gave rise to this pathway, we examined reproductive phasiRNA pathways in nongrass monocots: garden asparagus, daylily, and lily. The common ancestors of these species diverged approximately 115-117 million years ago (MYA). We found that premeiotic 21-nt and meiotic 24-nt phasiRNAs were abundant in all three species and displayed spatial localization and temporal dynamics similar to grasses. The miR2275-triggered pathway was also present, yielding 24-nt reproductive phasiRNAs, and thus originated more than 117 MYA. In asparagus, unlike in grasses, these siRNAs are largely derived from inverted repeats (IRs); analyses in lily identified thousands of precursor loci, and many were also predicted to form foldback substrates for Dicer processing. Additionally, reproductive phasiRNAs were present in female reproductive organs and thus may function in both male and female germinal development. These data describe several distinct mechanisms of production for 24-nt meiotic phasiRNAs and provide new insights into the evolution of reproductive phasiRNA pathways in monocots.© 2018 Kakrana et al.; Published by Cold Spring Harbor Laboratory Press.

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September 22, 2019

Transcriptome profiling of two ornamental and medicinal papaver herbs.

The Papaver spp. (Papaver rhoeas (Corn poppy) and Papaver nudicaule (Iceland poppy)) genera are ornamental and medicinal plants that are used for the isolation of alkaloid drugs. In this study, we generated 700 Mb of transcriptome sequences with the PacBio platform. They were assembled into 120,926 contigs, and 1185 (82.2%) of the benchmarking universal single-copy orthologs (BUSCO) core genes were completely present in our assembled transcriptome. Furthermore, using 128 Gb of Illumina sequences, the transcript expression was assessed at three stages of Papaver plant development (30, 60, and 90 days), from which we identified 137 differentially expressed transcripts. Furthermore, three co-occurrence heat maps are generated from 51 different plant genomes along with the Papaver transcriptome, i.e., secondary metabolite biosynthesis, isoquinoline alkaloid biosynthesis (BIA) pathway, and cytochrome. Sixty-nine transcripts in the BIA pathway along with 22 different alkaloids (quantified with LC-QTOF-MS/MS) were mapped into the BIA KEGG map (map00950). Finally, we identified 39 full-length cytochrome transcripts and compared them with other genomes. Collectively, this transcriptome data, along with the expression and quantitative metabolite profiles, provides an initial recording of secondary metabolites and their expression related to Papaver plant development. Moreover, these profiles could help to further detail the functional characterization of the various secondary metabolite biosynthesis and Papaver plant development associated problems.

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September 22, 2019

Isoform sequencing provides insight into natural genetic diversity in maize.

W64A, as a member of non-stiff stalk maize, has been used to develop current corn in plant breeding, and serving as one of broadest parent line for the commercial hybrid seed production (Huffman, 1984). The inbred had the characteristics of early flowering, average plant and ear height at its maturity, very strong roots and good stalks (Runge, 2004). In addition, W64A serves as an invaluable germplasm to study gene functions especially in the field of corn nutrition and endosperm texture given its nearly complete vitreousness and hardness (Figure 1a). However, little is known about the background of genetic and genomic information for W64A. With the advent of the revolutionary technology of PacBio long-read sequencing, we can simultaneously obtain a large amount of full-length cDNA up to 20 kb (An et al., 2018). This article is protected by copyright. All rights reserved.This article is protected by copyright. All rights reserved.

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September 22, 2019

Quantitative metaproteomics highlight the metabolic contributions of uncultured phylotypes in a thermophilic anaerobic digester.

In this study, we used multiple meta-omic approaches to characterize the microbial community and the active metabolic pathways of a stable industrial biogas reactor with food waste as the dominant feedstock, operating at thermophilic temperatures (60°C) and elevated levels of free ammonia (367 mg/liter NH3-N). The microbial community was strongly dominated (76% of all 16S rRNA amplicon sequences) by populations closely related to the proteolytic bacterium Coprothermobacter proteolyticus. Multiple Coprothermobacter-affiliated strains were detected, introducing an additional level of complexity seldom explored in biogas studies. Genome reconstructions provided metabolic insight into the microbes that performed biomass deconstruction and fermentation, including the deeply branching phyla Dictyoglomi and Planctomycetes and the candidate phylum “Atribacteria” These biomass degraders were complemented by a synergistic network of microorganisms that convert key fermentation intermediates (fatty acids) via syntrophic interactions with hydrogenotrophic methanogens to ultimately produce methane. Interpretation of the proteomics data also suggested activity of a Methanosaeta phylotype acclimatized to high ammonia levels. In particular, we report multiple novel phylotypes proposed as syntrophic acetate oxidizers, which also exert expression of enzymes needed for both the Wood-Ljungdahl pathway and ß-oxidation of fatty acids to acetyl coenzyme A. Such an arrangement differs from known syntrophic oxidizing bacteria and presents an interesting hypothesis for future studies. Collectively, these findings provide increased insight into active metabolic roles of uncultured phylotypes and presents new synergistic relationships, both of which may contribute to the stability of the biogas reactor.Biogas production through anaerobic digestion of organic waste provides an attractive source of renewable energy and a sustainable waste management strategy. A comprehensive understanding of the microbial community that drives anaerobic digesters is essential to ensure stable and efficient energy production. Here, we characterize the intricate microbial networks and metabolic pathways in a thermophilic biogas reactor. We discuss the impact of frequently encountered microbial populations as well as the metabolism of newly discovered novel phylotypes that seem to play distinct roles within key microbial stages of anaerobic digestion in this stable high-temperature system. In particular, we draft a metabolic scenario whereby multiple uncultured syntrophic acetate-oxidizing bacteria are capable of syntrophically oxidizing acetate as well as longer-chain fatty acids (via the ß-oxidation and Wood-Ljundahl pathways) to hydrogen and carbon dioxide, which methanogens subsequently convert to methane. Copyright © 2016 American Society for Microbiology.

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September 22, 2019

Caught in the middle with multiple displacement amplification: the myth of pooling for avoiding multiple displacement amplification bias in a metagenome.

Shotgun metagenomics has become an important tool for investigating the ecology of microorganisms. Underlying these investigations is the assumption that metagenome sequence data accurately estimates the census of microbial populations. Multiple displacement amplification (MDA) of microbial community DNA is often used in cases where it is difficult to obtain enough DNA for sequencing; however, MDA can result in amplification biases that may impact subsequent estimates of population census from metagenome data. Some have posited that pooling replicate MDA reactions negates these biases and restores the accuracy of population analyses. This assumption has not been empirically tested.Using mock viral communities, we examined the influence of pooling on population-scale analyses. In pooled and single reaction MDA treatments, sequence coverage of viral populations was highly variable and coverage patterns across viral genomes were nearly identical, indicating that initial priming biases were reproducible and that pooling did not alleviate biases. In contrast, control unamplified sequence libraries showed relatively even coverage across phage genomes.MDA should be avoided for metagenomic investigations that require quantitative estimates of microbial taxa and gene functional groups. While MDA is an indispensable technique in applications such as single-cell genomics, amplification biases cannot be overcome by combining replicate MDA reactions. Alternative library preparation techniques should be utilized for quantitative microbial ecology studies utilizing metagenomic sequencing approaches.

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September 22, 2019

High-resolution characterization of the human microbiome.

The human microbiome plays an important and increasingly recognized role in human health. Studies of the microbiome typically use targeted sequencing of the 16S rRNA gene, whole metagenome shotgun sequencing, or other meta-omic technologies to characterize the microbiome’s composition, activity, and dynamics. Processing, analyzing, and interpreting these data involve numerous computational tools that aim to filter, cluster, annotate, and quantify the obtained data and ultimately provide an accurate and interpretable profile of the microbiome’s taxonomy, functional capacity, and behavior. These tools, however, are often limited in resolution and accuracy and may fail to capture many biologically and clinically relevant microbiome features, such as strain-level variation or nuanced functional response to perturbation. Over the past few years, extensive efforts have been invested toward addressing these challenges and developing novel computational methods for accurate and high-resolution characterization of microbiome data. These methods aim to quantify strain-level composition and variation, detect and characterize rare microbiome species, link specific genes to individual taxa, and more accurately characterize the functional capacity and dynamics of the microbiome. These methods and the ability to produce detailed and precise microbiome information are clearly essential for informing microbiome-based personalized therapies. In this review, we survey these methods, highlighting the challenges each method sets out to address and briefly describing methodological approaches. Copyright © 2016 Elsevier Inc. All rights reserved.

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September 22, 2019

Shannon: an information-optimal de novo RNA-Seq assembler

De novo assembly of short RNA-Seq reads into transcripts is challenging due to sequence similarities in transcriptomes arising from gene duplications and alternative splicing of transcripts. We present Shannon, an RNA-Seq assembler with an optimality guarantee derived from principles of information theory: Shannon reconstructs nearly all information-theoretically reconstructable transcripts. Shannon is based on a theory we develop for de novo RNA-Seq assembly that reveals differing abundances among transcripts to be the key, rather than the barrier, to effective assembly. The assembly problem is formulated as a sparsest-flow problem on a transcript graph, and the heart of Shannon is a novel iterative flow-decomposition algorithm. This algorithm provably solves the information-theoretically reconstructable instances in linear-time even though the general sparsest-flow problem is NP-hard. Shannon also incorporates several additional new algorithmic advances: a new error-correction algorithm based on successive cancelation, a multi-bridging algorithm that carefully utilizes read information in the k-mer de Bruijn graph, and an approximate graph partitioning algorithm to split the transcriptome de Bruijn graph into smaller components. In tests on large RNA-Seq datasets, Shannon obtains significant increases in sensitivity along with improvements in specificity in comparison to state-of-the-art assemblers.

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September 22, 2019

Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study.

High-throughput RNA sequencing (RNA-seq) greatly expands the potential for genomics discoveries, but the wide variety of platforms, protocols and performance capabilitites has created the need for comprehensive reference data. Here we describe the Association of Biomolecular Resource Facilities next-generation sequencing (ABRF-NGS) study on RNA-seq. We carried out replicate experiments across 15 laboratory sites using reference RNA standards to test four protocols (poly-A-selected, ribo-depleted, size-selected and degraded) on five sequencing platforms (Illumina HiSeq, Life Technologies PGM and Proton, Pacific Biosciences RS and Roche 454). The results show high intraplatform (Spearman rank R > 0.86) and inter-platform (R > 0.83) concordance for expression measures across the deep-count platforms, but highly variable efficiency and cost for splice junction and variant detection between all platforms. For intact RNA, gene expression profiles from rRNA-depletion and poly-A enrichment are similar. In addition, rRNA depletion enables effective analysis of degraded RNA samples. This study provides a broad foundation for cross-platform standardization, evaluation and improvement of RNA-seq.

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September 22, 2019

A comprehensive approach to expression of L1 loci.

L1 elements represent the only currently active, autonomous retrotransposon in the human genome, and they make major contributions to human genetic instability. The vast majority of the 500 000 L1 elements in the genome are defective, and only a relatively few can contribute to the retrotransposition process. However, there is currently no comprehensive approach to identify the specific loci that are actively transcribed separate from the excess of L1-related sequences that are co-transcribed within genes. We have developed RNA-Seq procedures, as well as a 1200 bp 5? RACE product coupled with PACBio sequencing that can identify the specific L1 loci that contribute most of the L1-related RNA reads. At least 99% of L1-related sequences found in RNA do not arise from the L1 promoter, instead representing pieces of L1 incorporated in other cellular RNAs. In any given cell type a relatively few active L1 loci contribute to the ‘authentic’ L1 transcripts that arise from the L1 promoter, with significantly different loci seen expressed in different tissues.© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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September 22, 2019

Transcriptome-wide investigation of circular RNAs in rice.

Various stable circular RNAs (circRNAs) are newly identified to be the abundance of noncoding RNAs in Archaea, Caenorhabditis elegans, mice, and humans through high-throughput deep sequencing coupled with analysis of massive transcriptional data. CircRNAs play important roles in miRNA function and transcriptional controlling by acting as competing endogenous RNAs or positive regulators on their parent coding genes. However, little is known regarding circRNAs in plants. Here, we report 2354 rice circRNAs that were identified through deep sequencing and computational analysis of ssRNA-seq data. Among them, 1356 are exonic circRNAs. Some circRNAs exhibit tissue-specific expression. Rice circRNAs have a considerable number of isoforms, including alternative backsplicing and alternative splicing circularization patterns. Parental genes with multiple exons are preferentially circularized. Only 484 circRNAs have backsplices derived from known splice sites. In addition, only 92 circRNAs were found to be enriched for miniature inverted-repeat transposable elements (MITEs) in flanking sequences or to be complementary to at least 18-bp flanking intronic sequences, indicating that there are some other production mechanisms in addition to direct backsplicing in rice. Rice circRNAs have no significant enrichment for miRNA target sites. A transgenic study showed that overexpression of a circRNA construct could reduce the expression level of its parental gene in transgenic plants compared with empty-vector control plants. This suggested that circRNA and its linear form might act as a negative regulator of its parental gene. Overall, these analyses reveal the prevalence of circRNAs in rice and provide new biological insights into rice circRNAs.© 2015 Lu et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

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September 22, 2019

Identification and analysis of glutathione S-transferase gene family in sweet potato reveal divergent GST-mediated networks in aboveground and underground tissues in response to abiotic stresses.

Sweet potato, a hexaploid species lacking a reference genome, is one of the most important crops in many developing countries, where abiotic stresses are a primary cause of reduction of crop yield. Glutathione S-transferases (GSTs) are multifunctional enzymes that play important roles in oxidative stress tolerance and cellular detoxification.A total of 42 putative full-length GST genes were identified from two local transcriptome databases and validated by molecular cloning and Sanger sequencing. Sequence and intraspecific phylogenetic analyses revealed extensive differentiation in their coding sequences and divided them into eight subfamilies. Interspecific phylogenetic and comparative analyses indicated that most examined GST paralogs might originate and diverge before the speciation of sweet potato. Results from large-scale RNA-seq and quantitative real-time PCR experiments exhibited extensive variation in gene-expression profiles across different tissues and varieties, which implied strong evolutionary divergence in their gene-expression regulation. Moreover, we performed five manipulated stress experiments and uncovered highly divergent stress-response patterns of sweet potato GST genes in aboveground and underground tissues.Our study identified a large number of sweet potato GST genes, systematically investigated their evolutionary diversification, and provides new insights into the GST-mediated stress-response mechanisms in this worldwide crop.

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September 22, 2019

LSCplus: a fast solution for improving long read accuracy by short read alignment.

The single molecule, real time (SMRT) sequencing technology of Pacific Biosciences enables the acquisition of transcripts from end to end due to its ability to produce extraordinarily long reads (>10 kb). This new method of transcriptome sequencing has been applied to several projects on humans and model organisms. However, the raw data from SMRT sequencing are of relatively low quality, with a random error rate of approximately 15 %, for which error correction using next-generation sequencing (NGS) short reads is typically necessary. Few tools have been designed that apply a hybrid sequencing approach that combines NGS and SMRT data, and the most popular existing tool for error correction, LSC, has computing resource requirements that are too intensive for most laboratory and research groups. These shortcomings severely limit the application of SMRT long reads for transcriptome analysis.Here, we report an improved tool (LSCplus) for error correction with the LSC program as a reference. LSCplus overcomes the disadvantage of LSC’s time consumption and improves quality. Only 1/3-1/4 of the time and 1/20-1/25 of the error correction time is required using LSCplus compared with that required for using LSC.LSCplus is freely available at http://www.herbbol.org:8001/lscplus/ . Sample calculations are provided illustrating the precision and efficiency of this method regarding error correction and isoform detection.

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September 22, 2019

Direct chromosome-length haplotyping by single-cell sequencing.

Haplotypes are fundamental to fully characterize the diploid genome of an individual, yet methods to directly chart the unique genetic makeup of each parental chromosome are lacking. Here we introduce single-cell DNA template strand sequencing (Strand-seq) as a novel approach to phasing diploid genomes along the entire length of all chromosomes. We demonstrate this by building a complete haplotype for a HapMap individual (NA12878) at high accuracy (concordance 99.3%), without using generational information or statistical inference. By use of this approach, we mapped all meiotic recombination events in a family trio with high resolution (median range ~14 kb) and phased larger structural variants like deletions, indels, and balanced rearrangements like inversions. Lastly, the single-cell resolution of Strand-seq allowed us to observe loss of heterozygosity regions in a small number of cells, a significant advantage for studies of heterogeneous cell populations, such as cancer cells. We conclude that Strand-seq is a unique and powerful approach to completely phase individual genomes and map inheritance patterns in families, while preserving haplotype differences between single cells.© 2016 Porubský et al.; Published by Cold Spring Harbor Laboratory Press.

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September 22, 2019

De novo clustering of long-read transcriptome data using a greedy, quality-value based algorithm

Long-read sequencing of transcripts with PacBio Iso-Seq and Oxford Nanopore Technologies has proven to be central to the study of complex isoform landscapes in many organisms. However, current de novo transcript reconstruction algorithms from long-read data are limited, leaving the potential of these technologies unfulfilled. A common bottleneck is the dearth of scalable and accurate algorithms for clustering long reads according to their gene family of origin. To address this challenge, we develop isONclust, a clustering algorithm that is greedy (in order to scale) and makes use of quality values (in order to handle variable error rates). We test isONclust on three simulated and five biological datasets, across a breadth of organisms, technologies, and read depths. Our results demonstrate that isONclust is a substantial improvement over previous approaches, both in terms of overall accuracy and/or scalability to large datasets. Our tool is available at https://github.com/ksahlin/isONclust.

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