Efficient de novo assembly of single-cell bacterial genomes from short-read data sets

Sequencing-based analysis of microbiomes

Microbiomes occupy a range of niches and, in addition to having diverse compositions, they have varied functional roles that have an impact on agriculture, environmental sciences, and human health and disease. The study of microbiomes has been facilitated by recent technological and analytical advances, such as cheaper and higher-throughput DNA and RNA sequencing, improved long-read sequencing and innovative computational analysis methods. These advances are providing a deeper understanding of microbiomes at the genomic, transcriptional and translational level, generating insights into their function and composition at resolutions beyond the species level.

Multi-enzymatic systems synergize new RCA technique amplified super-long dsDNA from DNA circle

BACKGROUND

In the field of DNA amplification, there are great challenges in the effectively amplify of long-chain amplification, especially amplification up to several hundred kb level.

RESULTS

A novel technique for the unbiased whole genome amplification from a thimbleful of DNA circles, such as low as 10 ng/ 10 μL of the circular cpDNA or low as 5 ng/ 10 μL of the plasmid, is developed, which can amplify an abundance of the whole genome sequences. Specifically, the new technique that combines rolling-amplification and triple-enzyme system presents a tightly controlled process of a series of buffers/reactions and optimized procedures, that applies from the primer-template duplexes to the Elution step. The result of this technique provides a new approach for extending RCA capacity, where it can reach 200 kb from the circular cpDNA amplification and 150 kb from the plasmid DNA amplification, that demonstrates superior breadth and evenness of genome coverage, high reproducibility, small amplification bias with the amplification efficiency.

SIGNIFICANCE AND NOVELTY

This new technique will develop into one of the powerful tools for isothermal DNA amplification in vitro, genome sequencing/analysis, phylogenetic analysis, physical mapping, and other molecular biology applications.

Chimera: The spoiler in multiple displacement amplification

Multiple displacement amplification (MDA) based on isothermal random priming and high fidelity phi29 DNA polymerase-mediated processive extension has revolutionized the field of whole genome amplification by enabling the amplification of minute amounts of DNA, such as from a single cell, generating vast amounts of DNA with high genome coverage. Despite its advantages, MDA has its own challenges, one of the grandest being the formation of chimeric sequences (chimeras), which presents in all MDA products and seriously disturbs the downstream analysis. In this review, we provide a comprehensive overview of current research on MDA chimeras. We first reviewed the mechanisms of chimera formation and chimera detection methods. We then systematically summarized the characteristics of chimeras, including overlap, chimeric distance, chimeric density, and chimeric rate, as found in independently published sequencing data. Finally, we reviewed the methods used to process chimeric sequences and their impacts on the improvement of data utilization efficiency. The information presented in this review will be useful for those interested in understanding the challenges with MDA and in improving its performance.

Identify essential genes based on clustering based synthetic minority oversampling technique

Prediction of essential genes in a life organism is one of the central tasks in synthetic biology. Computational predictors are desired because experimental data is often unavailable. Recently, some sequence-based predictors have been constructed to identify essential genes. However, their predictive performance should be further improved. One key problem is how to effectively extract the sequence-based features, which are able to discriminate the essential genes. Another problem is the imbalanced training set. The amount of essential genes in human cell lines is lower than that of non-essential genes. Therefore, predictors trained with such imbalanced training set tend to identify an unseen sequence as a non-essential gene. Here, a new over-sampling strategy was proposed called Clustering based Synthetic Minority Oversampling Technique (CSMOTE) to overcome the imbalanced data issue. Combining CSMOTE with the Z curve, the global features, and Support Vector Machines, a new protocol called iEsGene-CSMOTE was proposed to identify essential genes. The rigorous jackknife cross validation results indicated that iEsGene-CSMOTE is better than the other competing methods. The proposed method outperformed λ-interval Z curve by 35.48% and 11.25% in terms of Sn and BACC, respectively.

De novo assembly of human genome at single-cell levels

Genome assembly has been benefited from long-read sequencing technologies with higher accuracy and higher continuity. However, most human genome assembly require large amount of DNAs from homogeneous cell lines without keeping cell heterogeneities, since cell heterogeneity could profoundly affect haplotype assembly results. Herein, using single-cell genome long-read sequencing technology (SMOOTH-seq), we have sequenced K562 and HG002 cells on PacBio HiFi and Oxford Nanopore Technologies (ONT) platforms and conducted de novo genome assembly. For the first time, we have completed the human genome assembly with high continuity (with NG50 of ∼2 Mb using 95 individual K562 cells) at single-cell levels, and explored the impact of different assemblers and sequencing strategies on genome assembly. With sequencing data from 30 diploid individual HG002 cells of relatively high genome coverage (average coverage ∼41.7%) on ONT platform, the NG50 can reach over 1.3 Mb. Furthermore, with the assembled genome from K562 single-cell dataset, more complete and accurate set of insertion events and complex structural variations could be identified. This study opened a new chapter on the practice of single-cell genome de novo assembly.

Mitogenome-wise codon usage pattern from comparative analysis of the first mitogenome of Blepharipa sp. (Muga uzifly) with other Oestroid flies

Uziflies (Family: Tachinidae) are dipteran endoparasites of sericigenous insects which cause major economic loss in the silk industry globally. Here, we are presenting the first full mitogenome of Blepharipa sp. (Acc: KY644698, 15,080 bp, A + T = 78.41%), a dipteran parasitoid of Muga silkworm (Antheraea assamensis) found in the Indian states of Assam and Meghalaya. This study has confirmed that Blepharipa sp. mitogenome gene content and arrangement is similar to other Tachinidae and Sarcophagidae flies of Oestroidea superfamily, typical of ancestral Diptera. Although, Calliphoridae and Oestridae flies have undergone tRNA translocation and insertion, forming unique intergenic spacers (IGS) and overlapping regions (OL) and a few of them (IGS, OL) have been conserved across Oestroidea flies. The Tachinidae mitogenomes exhibit more AT content and AT biased codons in their protein-coding genes (PCGs) than the Oestroidea counterpart. About 92.07% of all (3722) codons in PCGs of this new species have A/T in their 3rd codon position. The high proportion of AT and repeats in the control region (CR) affects sequence coverage, resulting in a short CR (Blepharipa sp.: 168 bp) and a smaller tachinid mitogenome. Our research unveils those genes with a high AT content had a reduced effective number of codons, leading to high codon usage bias. The neutrality test shows that natural selection has a stronger influence on codon usage bias than directed mutational pressure. This study also reveals that longer PCGs (e.g., nad5, cox1) have a higher codon usage bias than shorter PCGs (e.g., atp8, nad4l). The divergence rates increase nonlinearly as AT content at the 3rd codon position increases and higher rate of synonymous divergence than nonsynonymous divergence causes strong purifying selection. The phylogenetic analysis explains that Blepharipa sp. is well suited in the family of insectivorous tachinid maggots. It's possible that biased codon usage in the Tachinidae family reduces the effective number of codons, and purifying selection retains the core functions in their mitogenome, which could help with efficient metabolism in their endo-parasitic life style and survival strategy.

Phylogeny and Metabolic Potential of the Candidate Phylum SAR324

The bacterial SAR324 cluster is ubiquitous and abundant in the ocean, especially around hydrothermal vents and in the deep sea, where it can account for up to 30% of the whole bacterial community. According to a new taxonomy generated using multiple universal protein-coding genes (instead of the previously used 16S rRNA single gene marker), the former Deltaproteobacteria cluster SAR324 has been classified since 2018 as its own phylum. Yet, very little is known about its phylogeny and metabolic potential. We downloaded all publicly available SAR324 genomes (65) from all natural environments and reconstructed 18 new genomes using publicly available oceanic metagenomic data and unpublished data from the waters underneath the Ross Ice Shelf. We calculated a global SAR324 phylogenetic tree and identified six clusters (namely 1A, 1B, 2A, 2B, 2C and 2D) within this clade. Genome annotation and metatranscriptome read mapping showed that SAR324 clades possess a flexible array of genes suited for survival in various environments. Clades 2A and 2C are mostly present in the surface mesopelagic layers of global oceans, while clade 2D dominates in deeper regions. Our results show that SAR324 has a very versatile and broad metabolic potential, including many heterotrophic, but also autotrophic pathways. While one surface water associated clade (2A) seems to use proteorhodopsin to gain energy from solar radiation, some deep-sea genomes from clade 2D contain the complete Calvin-Benson-Bassham cycle gene repertoire to fix carbon. This, in addition to a variety of other genes and pathways for both oxic (e.g., dimethylsulfoniopropionate degradation) and anoxic (e.g., dissimilatory sulfate reduction, anaerobic benzoate degradation) conditions, can help explain the ubiquitous presence of SAR324 in aquatic habitats.

Three Draft Single-Cell Genome Sequences of Novel SAR324 Strains Isolated from the Abyssopelagic Southern Ocean

SAR324 is a ubiquitous and phylogenetically distinct clade of Deltaproteobacteria in marine environments. Here, we present three single-cell amplified genome sequences from the SAR324 lineage, obtained from the abyssopelagic zone of the Indian sector of the Southern Ocean.

Using single-cell sequencing technology to detect circulating tumor cells in solid tumors

Circulating tumor cells are tumor cells with high vitality and high metastatic potential that invade and shed into the peripheral blood from primary solid tumors or metastatic foci. Due to the heterogeneity of tumors, it is difficult for high-throughput sequencing analysis of tumor tissues to find the genomic characteristics of low-abundance tumor stem cells. Single-cell sequencing of circulating tumor cells avoids interference from tumor heterogeneity by comparing the differences between single-cell genomes, transcriptomes, and epigenetic groups among circulating tumor cells, primary and metastatic tumors, and metastatic lymph nodes in patients' peripheral blood, providing a new perspective for understanding the biological process of tumors. This article describes the identification, biological characteristics, and single-cell genome-wide variation in circulating tumor cells and summarizes the application of single-cell sequencing technology to tumor typing, metastasis analysis, progression detection, and adjuvant therapy.

Metapangenomics reveals depth-dependent shifts in metabolic potential for the ubiquitous marine bacterial SAR324 lineage

BACKGROUND

Oceanic microbiomes play a pivotal role in the global carbon cycle and are central to the transformation and recycling of carbon and energy in the ocean's interior. SAR324 is a ubiquitous but poorly understood uncultivated clade of Deltaproteobacteria that inhabits the entire water column, from ocean surface waters to its deep interior. Although some progress has been made in elucidating potential metabolic traits of SAR324 in the dark ocean, very little is known about the ecology and the metabolic capabilities of this group in the euphotic and twilight zones. To investigate the comparative genomics, ecology, and physiological potential of the SAR324 clade, we examined the distribution and variability of key genomic features and metabolic pathways in this group from surface waters to the abyss in the North Pacific Subtropical Gyre, one of the largest biomes on Earth.

RESULTS

We leveraged a pangenomic ecological approach, combining spatio-temporally resolved single-amplified genome, metagenomic, and metatranscriptomic datasets. The data revealed substantial genomic diversity throughout the SAR324 clade, with distinct depth and temporal distributions that clearly differentiated ecotypes. Phylogenomic subclade delineation, environmental distributions, genomic feature similarities, and metabolic capacities revealed strong congruence. The four SAR324 ecotypes delineated in this study revealed striking divergence from one another with respect to their habitat-specific metabolic potentials. The ecotypes living in the dark or twilight oceans shared genomic features and metabolic capabilities consistent with a sulfur-based chemolithoautotrophic lifestyle. In contrast, those inhabiting the sunlit ocean displayed higher plasticity energy-related metabolic pathways, supporting a presumptive photoheterotrophic lifestyle. In epipelagic SAR324 ecotypes, we observed the presence of two types of proton-pumping rhodopsins, as well as genomic, transcriptomic, and ecological evidence for active photoheterotrophy, based on xanthorhodopsin-like light-harvesting proteins.

CONCLUSIONS

Combining pangenomic and both metagenomic and metatranscriptomic profiling revealed a striking divergence in the vertical distribution, genomic composition, metabolic potential, and predicted lifestyle strategies of geographically co-located members of the SAR324 bacterial clade. The results highlight the utility of metapangenomic approaches employed across environmental gradients, to decipher the properties and variation in function and ecological traits of specific phylogenetic clades within complex microbiomes. Video abstract.

Empirical evaluation of methods for de novo genome assembly

Technologies for next-generation sequencing (NGS) have stimulated an exponential rise in high-throughput sequencing projects and resulted in the development of new read-assembly algorithms. A drastic reduction in the costs of generating short reads on the genomes of new organisms is attributable to recent advances in NGS technologies such as Ion Torrent, Illumina, and PacBio. Genome research has led to the creation of high-quality reference genomes for several organisms, and de novo assembly is a key initiative that has facilitated gene discovery and other studies. More powerful analytical algorithms are needed to work on the increasing amount of sequence data. We make a thorough comparison of the de novo assembly algorithms to allow new users to clearly understand the assembly algorithms: overlap-layout-consensus and de-Bruijn-graph, string-graph based assembly, and hybrid approach. We also address the computational efficacy of each algorithm's performance, challenges faced by the assem- bly tools used, and the impact of repeats. Our results compare the relative performance of the different assemblers and other related assembly differences with and without the reference genome. We hope that this analysis will contribute to further the application of de novo sequences and help the future growth of assembly algorithms.

EPGA-SC : A Framework for de novo Assembly of Single-Cell Sequencing Reads

Assembling genomes from single-cell sequencing data is essential for single-cell studies. However, single-cell assemblies are challenging due to (i) the highly non-uniform read coverage and (ii) the elevated levels of sequencing errors and chimeric reads. Although several assemblers for single-cell data have been proposed in recent years, most of them fail to construct correct long contigs. In this study, we present a new framework called EPGA-SC for de novo assembly of single-cell sequencing reads. The EPGA assembler has designed strategies to solve the problems caused by sequencing errors, sequencing biases, and repetitive regions. However, the extremely unbalanced and richer error types prevent EPGA to achieve high performance in single-cell sequencing data. In this study, we designed EPGA-SC based on EPGA. The main innovations of EPGA-SC are as follows: (i) classifying reads to reduce the proportion of false reads; (ii) using multiple sets of high precision paired-end reads generated from the high precision assemblies produced by other assembler such as SPAdes to overcome the impact of sequencing biases and repetitive regions; and (iii) developing novel algorithms for removing chimeric errors and extending contigs. We test EPGA-SC with seven datasets. The experimental results show that EPGA-SC can generate better assemblies than most current tools in most time in term of MAX contig, N50, NG50, NA50, and NGA50.

RMI-DBG algorithm: A more agile iterative de Bruijn graph algorithm in short read genome assembly

The de Bruijn Graph algorithm (DBG) as one of the cornerstones algorithms in short read assembly has extended with the rapid advancement of the Next Generation Sequencing (NGS) technologies and low-cost production of millions of high-quality short reads. Erroneous reads, non-uniform coverage, and genomic repeats are three major problems that influence the performance of short read assemblers. To encounter these problems, the iterative DBG algorithm applies multiple [Formula: see text]-mers instead of a single [Formula: see text]-mer, by iterating the DBG graph over a range of [Formula: see text]-mer sizes from the minimum to the maximum. However, the iteration paradigm of iterative DBG deals with complex graphs from the beginning of the algorithm and therefore, causes more potential errors and computational time for resolving various unreal branches. In this research, we propose the Reverse Modified Iterative DBG graph (named RMI-DBG) for short read assembly. RMI-DBG utilizes the DBG algorithm and String graph to achieve the advantages of both algorithms. We present that RMI-DBG performs faster with comparable results in comparison to iterative DBG. Additionally, the quality of the proposed algorithm in terms of continuity and accuracy is evaluated with some commonly-used assemblers via several real datasets of the GAGE-B benchmark.

Opening up the Single-Cell Toolbox for Microbial Natural Products Research

The diverse microbes that produce natural products represent an important source of novel therapeutics, drug leads, and scientific tools. However, the vast majority have not been grown in axenic culture and are members of complex communities. While meta-'omic methods such as metagenomics, -transcriptomics, and -proteomics reveal collective molecular features of this "microbial dark matter", the study of individual microbiome members can be challenging. To address these limits, a number of techniques with single-bacterial resolution have been developed in the last decade and a half. While several of these are embraced by microbial ecologists, there has been less use by researchers interested in mining microbes for natural products. In this review, we discuss the available and emerging techniques for targeted single-cell analysis with a particular focus on applications to the discovery and study of natural products.

Evolution of Microbial Genomics: Conceptual Shifts over a Quarter Century

Prokaryote genomics started in earnest in 1995, with the complete sequences of two small bacterial genomes, those of Haemophilus influenzae and Mycoplasma genitalium. During the next quarter century, the prokaryote genome database has been growing exponentially, with no saturation in sight. For most of these 25 years, genome sequencing remained limited to cultivable microbes. Together with next-generation sequencing methods, advances in metagenomics and single-cell genomics have lifted this limitation, providing for an increasingly unbiased characterization of the global prokaryote diversity. Advances in computational genomics followed the progress of genome sequencing, even if occasionally lagging behind. Several major new branches of bacteria and archaea were discovered, including Asgard archaea, the apparent closest relatives of eukaryotes and expansive groups of bacteria and archaea with small genomes thought to be symbionts of other prokaryotes. Comparative analysis of numerous prokaryote genomes spanning a wide range of evolutionary distances changed the conceptual foundations of microbiology, supplanting the notion of species genomes with fixed gene sets with that of dynamic pangenomes and the notion of a single Tree of Life (ToL) with a statistical tree-like trend among individual gene trees. Strides were also made towards a theory and quantitative laws of prokaryote genome evolution.

PStrain: An Iterative Microbial Strains Profiling Algorithm for Shotgun Metagenomic Sequencing Data

MOTIVATION

The microbial community plays an essential role in human diseases and physiological activities. The functions of microbes can differ due to strain-level differences in the genome sequences. Shotgun metagenomic sequencing allows us to profile the strains in microbial communities practically. However, current methods are underdeveloped due to the highly similar sequences among strains. We observe that strains genotypes at the same single nucleotide variant (SNV) locus can be speculated by the genotype frequencies. Also, the variants in different loci covered by the same reads can provide evidence that they reside on the same strain.

RESULTS

These insights inspire us to design PStrain, an optimization method that utilizes genotype frequencies and the reads which cover multiple SNV loci to profile strains iteratively based on SNVs in a set of MetaPhlAn2 marker genes. Compared to the state-of-art methods, PStrain, on average, improved the performance of inferring strains abundances and genotypes by 87.75% and 59.45%, respectively. We have applied the PStrain package to the dataset with two cohorts of colorectal cancer (CRC) and found that the sequences of Bacteroides coprocola strains are significantly different between CRC and control samples, which is the first time to report the potential role of B. coprocola in the gut microbiota of CRC.

AVAILABILITY

https://github.com/wshuai294/PStrain.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genetic diversity of clinical and environmental Mucorales isolates obtained from an investigation of mucormycosis cases among solid organ transplant recipients

Mucormycoses are invasive infections by Rhizopus species and other Mucorales. Over 10 months, four solid organ transplant (SOT) recipients at our centre developed mucormycosis due to Rhizopus microsporus (n=2), R. arrhizus (n=1) or Lichtheimia corymbifera (n=1), at a median 31.5 days (range: 13-34) post-admission. We performed whole genome sequencing (WGS) on 72 Mucorales isolates (45 R. arrhizus, 19 R. delemar, six R. microsporus, two Lichtheimia species) from these patients, from five patients with community-acquired mucormycosis, and from hospital and regional environments. Isolates were compared by core protein phylogeny and global genomic features, including genome size, guanine-cytosine percentages, shared protein families and paralogue expansions. Patient isolates fell into six core phylogenetic lineages (clades). Phylogenetic and genomic similarities of R. microsporus isolates recovered 7 months apart from two SOT recipients in adjoining hospitals suggested a potential common source exposure. However, isolates from other patients and environmental sites had unique genomes. Many isolates that were indistinguishable by core phylogeny were distinct by one or more global genomic comparisons. Certain clades were recovered throughout the study period, whereas others were found at particular time points. In conclusion, mucormycosis cases could not be genetically linked to a definitive environmental source. Comprehensive genomic analyses eliminated false associations between Mucorales isolates that would have been assigned using core phylogenetic or less extensive genomic comparisons. The genomic diversity of Mucorales mandates that multiple isolates from individual patients and environmental sites undergo WGS during epidemiological investigations. However, exhaustive surveillance of fungal populations in a hospital and surrounding community is probably infeasible.

Enrichment of Comammox and Nitrite-Oxidizing Nitrospira From Acidic Soils

In agricultural soils fertilized with a high amount of ammonium nitrogen, the pH decreases because of the oxidation of ammonia by nitrifiers. Molecular-based analyses have revealed that members of the genus Nitrospira dominate over other nitrifiers in some acidic soils. However, terrestrial Nitrospira are rarely cultivated and little is known about their ecophysiology. In addition, recent studies discovered a single microbe with the potential to oxidize both ammonia and nitrite (complete ammonia oxidizer; comammox) within Nitrospira, which had been previously recognized as a nitrite oxidizer. Despite their broad distribution, there are no enrichment samples of comammox from terrestrial or acidic environments. Here, we report the selective enrichment of both comammox and nitrite-oxidizing Nitrospira from the acidic soil of a heavily fertilized tea field. Long-term enrichment was performed with two individual continuous-feeding bioreactors capable of controlling ammonia or nitrite concentration and pH. We found that excessive ammonium supply was a key factor to enhance the growth of comammox Nitrospira under acidic conditions. Additionally, a low concentration of nitrite was fed to prevent the accumulation of free nitrous acid and inhibition of cell growth under low pH, resulting in the selective enrichment of nitrite-oxidizing Nitrospira. Based on 16S rRNA gene analysis, Nitrospira accounting for only 1.2% in an initial soil increased to approximately 80% of the total microorganisms in both ammonia- and nitrite-fed bioreactors. Furthermore, amoA amplicon sequencing revealed that two phylotypes belonging to comammox clade A were enriched in an ammonia-fed bioreactor. One group was closely related to previously cultivated strains, and the other was classified into a different cluster consisting of only uncultivated representatives. These two groups coexisted in the bioreactor controlled at pH 6.0, but the latter became dominant after the pH decreased to 5.5. Additionally, a physiological experiment revealed that the enrichment sample oxidizes ammonia at pH <4, which is in accordance with the strongly acidic tea field soil; this value is lower than the active pH range of isolated acid-adapted nitrifiers. In conclusion, we successfully enriched multiple phylotypes of comammox and nitrite-oxidizing Nitrospira and revealed that the pH and concentrations of protonated N-compounds were potential niche determinants.

Phenome-Genome Profiling of Single Bacterial Cell by Raman-Activated Gravity-Driven Encapsulation and Sequencing

The small size and low DNA amount of bacterial cells have hindered establishing phenome-genome links in a precisely indexed, one-cell-per-reaction manner. Here, Raman-Activated Gravity-driven single-cell Encapsulation and Sequencing (RAGE-Seq) is presented, where individual cells are phenotypically screened via single-cell Raman spectra (SCRS) in an aquatic, vitality-preserving environment, then the cell with targeted SCRS is precisely packaged in a picoliter microdroplet and readily exported in a precisely indexed, "one-cell-one-tube" manner. Such integration of microdroplet encapsulation to Raman-activated sorting ensures high-coverage one-cell genome sequencing or cultivation that is directly linked to metabolic phenotype. For clinical Escherichia coli isolates, genome assemblies derived from precisely one cell via RAGE-Seq consistently reach >95% coverage. Moreover, directly from a urine sample of urogenital tract infection, metabolic-activity-based antimicrobial susceptibility phenotypes and genome sequence of 99.5% coverage are obtained simultaneously from precisely one cell. This single-cell global mutation map corroborates resistance phenotype and genotype, and unveils epidemiological features with high specificity and sensitivity. The ability to profile and correlate bacterial metabolic phenome and high-quality genome sequences at one-cell resolution suggests broad application of RAGE-Seq.

An Efficient Trimming Algorithm based on Multi-Feature Fusion Scoring Model for NGS Data

Next-generation sequencing (NGS) has enabled an exponential growth rate of sequencing data. However, several sequence artifacts, including error reads (base calling errors and small insertions or deletions) and poor quality reads, which can impose significant impact on the downstream sequence processing and analysis. Here, we present PE-Trimmer, a sensitive and special trimming algorithm for NGS sequence. First, PE-Trimmer removes technical sequences in paired-end reads based on the characteristics of low quality reads in NGS data. Second, PE-Trimmer determines the range of reads that need to be trimmed according to the quality score statistics histogram of reads in the library. To improve the accuracy of this algorithm, we design a light-weight and easy-to-explain scoring model to evaluate candidates in the pattern of trimming step. Finally, PE-Trimmer selects the appropriate trimming strategy to process the low quality reads based on the location determined by the scoring model. PE-Trimmer is able to locate and remove adapter residues from the paired-end reads. It is easily configurable and offers superior throughput in the multi-threaded mode. We test PE-Trimmer on five datasets, and compare it with the current five latest methods. The experimental results demonstrate that PE-Trimmer produces more superior results, compared with other trimmers.

Functional genomics by integrated analysis of transcriptome of sweet potato (Ipomoea batatas (L.) Lam.) during root formation

BACKGROUND

Sweet potato is easily propagated by cuttings. But the molecular biological mechanism of adventitious root formation are not yet clear.

OBJECTIVE

To understand the molecular mechanisms of adventitious root formation from stem cuttings in sweet potato.

METHODS

RNA-seq analysis was performed using un-rooted stem (0 day) and rooted stem (3 days). Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, comparison with Arabidopsis transcription factors (TFs) of DEGs were conducted to investigate the characteristics of genes and TFs involved in root formation. In addition, qRT-PCR analysis using roots at 0, 3, 6, 9, and 12 days after planting was performed to confirm RNA-seq reliability and related genes expression.

RESULTS

42,459 representative transcripts and 2092 DEGs were obtained through the RNA-seq analysis. The DEGs indicated the GO terms related to the single-organism metabolic process and cell periphery, and involved in the biosynthesis of secondary metabolites, and phenylpropanoid biosynthesis in KEGG pathways. The comparison with Arabidopsis thaliana TF database showed that 3 TFs (WRKY, NAC, bHLH) involved in root formation of sweet potato. qRT-PCR analysis, which was conducted to confirm the reliability of RNA-seq analysis, indicated that some metabolisms including oxidative stress and wounding, transport, hormone may be involved in adventitious root formation.

CONCLUSIONS

The detected genes related to secondary metabolism, some hormone (auxin, gibberellin), transports, etc. and 3 TFs (WRKY, NAC, bHLH) may have functions in adventitious roots formation. This results provide valuable resources for future research on the adventitious root formation of sweet potato.

GC bias affects genomic and metagenomic reconstructions, underrepresenting GC-poor organisms

BACKGROUND

Metagenomic sequencing is a well-established tool in the modern biosciences. While it promises unparalleled insights into the genetic content of the biological samples studied, conclusions drawn are at risk from biases inherent to the DNA sequencing methods, including inaccurate abundance estimates as a function of genomic guanine-cytosine (GC) contents.

RESULTS

We explored such GC biases across many commonly used platforms in experiments sequencing multiple genomes (with mean GC contents ranging from 28.9% to 62.4%) and metagenomes. GC bias profiles varied among different library preparation protocols and sequencing platforms. We found that our workflows using MiSeq and NextSeq were hindered by major GC biases, with problems becoming increasingly severe outside the 45-65% GC range, leading to a falsely low coverage in GC-rich and especially GC-poor sequences, where genomic windows with 30% GC content had >10-fold less coverage than windows close to 50% GC content. We also showed that GC content correlates tightly with coverage biases. The PacBio and HiSeq platforms also evidenced similar profiles of GC biases to each other, which were distinct from those seen in the MiSeq and NextSeq workflows. The Oxford Nanopore workflow was not afflicted by GC bias.

CONCLUSIONS

These findings indicate potential sources of difficulty, arising from GC biases, in genome sequencing that could be pre-emptively addressed with methodological optimizations provided that the GC biases inherent to the relevant workflow are understood. Furthermore, it is recommended that a more critical approach be taken in quantitative abundance estimates in metagenomic studies. In the future, metagenomic studies should take steps to account for the effects of GC bias before drawing conclusions, or they should use a demonstrably unbiased workflow.

Improving de novo Assembly Based on Read Classification

Due to sequencing bias, sequencing error, and repeat problems, the genome assemblies usually contain misarrangements and gaps. When tackling these problems, current assemblers commonly consider the read libraries as a whole and adopt the same strategy to deal with them. However, if we can divide reads into different categories and take different assembly strategies for different read categories, we expect to reduce the mutual effects on problems in genome assembly and facilitate to produce satisfactory assemblies. In this paper, we present a new pipeline for genome assembly based on read classification (ARC). ARC classifies reads into three categories according to the frequencies of k-mers they contain. The three categories refer to (1) low depth reads, which contain a certain low frequency k-mers and are often caused by sequencing errors or bias; (2) high depth reads, which contain a certain high frequency k-mers and usually come from repetitive regions; and (3) normal depth reads, which are the rest of reads. After read classification, an existing assembler is used to assemble different read categories separately, which is beneficial to resolve problems in the genome assembly. ARC adopts loose assembly parameters for low depth reads, and strict assembly parameters for normal depth and high depth reads. We test ARC using five datasets. The experimental results show that, assemblers combining with ARC can generate better assemblies in terms of NA50, NGA50, and genome fraction.

Studying the gut virome in the metagenomic era: challenges and perspectives

The human gut harbors a complex ecosystem of microorganisms, including bacteria and viruses. With the rise of next-generation sequencing technologies, we have seen a quantum leap in the study of human-gut-inhabiting bacteria, yet the viruses that infect these bacteria, known as bacteriophages, remain underexplored. In this review, we focus on what is known about the role of bacteriophages in human health and the technical challenges involved in studying the gut virome, of which they are a major component. Lastly, we discuss what can be learned from studies of bacteriophages in other ecosystems.

Novel sequencing technologies to support industrial biotechnology

Industrial biotechnology develops and applies microorganisms for the production of bioproducts and enzymes with applications ranging from food and feed ingredients and processing to bio-based chemicals, biofuels and pharmaceutical products. Next generation DNA sequencing technologies play an increasingly important role in improving and accelerating microbial strain development for existing and novel bio-products via screening, gene and pathway discovery, metabolic engineering and additional optimization and understanding of large-scale manufacturing. In this mini-review, we describe novel DNA sequencing and analysis technologies with a focus on applications to industrial strain development, enzyme discovery and microbial community analysis.

Pan-Genomic and Polymorphic Driven Prediction of Antibiotic Resistance in Elizabethkingia

The Elizabethkingia are a genetically diverse genus of emerging pathogens that exhibit multidrug resistance to a range of common antibiotics. Two representative species, Elizabethkingia bruuniana and E. meningoseptica, were phenotypically tested to determine minimum inhibitory concentrations (MICs) for five antibiotics. Ultra-long read sequencing with Oxford Nanopore Technologies (ONT) and subsequent de novo assembly produced complete, gapless circular genomes for each strain. Alignment based annotation with Prokka identified 5,480 features in E. bruuniana and 5,203 features in E. meningoseptica, where none of these identified genes or gene combinations corresponded to observed phenotypic resistance values. Pan-genomic analysis, performed with an additional 19 Elizabethkingia strains, identified a core-genome size of 2,658,537 bp, 32 uniquely identifiable intrinsic chromosomal antibiotic resistance core-genes and 77 antibiotic resistance pan-genes. Using core-SNPs and pan-genes in combination with six machine learning (ML) algorithms, binary classification of clindamycin and vancomycin resistance achieved f1 scores of 0.94 and 0.84, respectively. Performance on the more challenging multiclass problem for fusidic acid, rifampin and ciprofloxacin resulted in f1 scores of 0.70, 0.75, and 0.54, respectively. By producing two sets of quality biological predictors, pan-genome genes and core-genome SNPs, from long-read sequence data and applying an ensemble of ML techniques, our results demonstrated that accurate phenotypic inference, at multiple AMR resolutions, can be achieved.

On-Site Analysis of Bacterial Communities of the Ultraoligotrophic South Pacific Gyre

The South Pacific Gyre (SPG) covers 10% of the ocean's surface and is often regarded as a marine biological desert. To gain an on-site overview of the remote, ultraoligotrophic microbial community of the SPG, we developed a novel onboard analysis pipeline, which combines next-generation sequencing with fluorescence in situ hybridization and automated cell enumeration. We tested the pipeline during the SO-245 "UltraPac" cruise from Chile to New Zealand and found that the overall microbial community of the SPG was highly similar to those of other oceanic gyres. The SPG was dominated by 20 major bacterial clades, including SAR11, SAR116, the AEGEAN-169 marine group, SAR86, Prochlorococcus, SAR324, SAR406, and SAR202. Most of the bacterial clades showed a strong vertical (20 m to 5,000 m), but only a weak longitudinal (80°W to 160°W), distribution pattern. Surprisingly, in the central gyre, Prochlorococcus, the dominant photosynthetic organism, had only low cellular abundances in the upper waters (20 to 80 m) and was more frequent around the 1% irradiance zone (100 to 150 m). Instead, the surface waters of the central gyre were dominated by the SAR11, SAR86, and SAR116 clades known to harbor light-driven proton pumps. The alphaproteobacterial AEGEAN-169 marine group was particularly abundant in the surface waters of the central gyre, indicating a potentially interesting adaptation to ultraoligotrophic waters and high solar irradiance. In the future, the newly developed community analysis pipeline will allow for on-site insights into a microbial community within 35 h of sampling, which will permit more targeted sampling efforts and hypothesis-driven research.IMPORTANCE The South Pacific Gyre, due to its vast size and remoteness, is one of the least-studied oceanic regions on earth. However, both remote sensing and in situ measurements indicated that the activity of its microbial community contributes significantly to global biogeochemical cycles. Presented here is an unparalleled investigation of the microbial community of the SPG from 20- to 5,000-m depths covering a geographic distance of ∼7,000 km. This insight was achieved through the development of a novel onboard analysis pipeline, which combines next-generation sequencing with fluorescence in situ hybridization and automated cell enumeration. The pipeline is well comparable to onshore systems based on the Illumina platforms and yields microbial community data in less than 35 h after sampling. Going forward, the ability to gain on-site knowledge of a remote microbial community will permit hypothesis-driven research, through the generation of novel scientific questions and subsequent additional targeted sampling efforts.

ChimeraMiner: An Improved Chimeric Read Detection Pipeline and Its Application in Single Cell Sequencing

As the most widely-used single cell whole genome amplification (WGA) approach, multiple displacement amplification (MDA) has a superior performance, due to the high-fidelity and processivity of phi29 DNA polymerase. However, chimeric reads, generated in MDA, cause severe disruption in many single-cell studies. Herein, we constructed ChimeraMiner, an improved chimeric read detection pipeline for analyzing the sequencing data of MDA and classified the chimeric sequences. Two datasets (MDA1 and MDA2) were used for evaluating and comparing the efficiency of ChimeraMiner and previous pipeline. Under the same hardware condition, ChimeraMiner spent only 43.4% (43.8% for MDA1 and 43.0% for MDA2) processing time. Respectively, 24.4 million (6.31%) read pairs out of 773 million reads, and 17.5 million (6.62%) read pairs out of 528 million reads were accurately classified as chimeras by ChimeraMiner. In addition to finding 83.60% (17,639,371) chimeras, which were detected by previous pipelines, ChimeraMiner screened 6,736,168 novel chimeras, most of which were missed by the previous pipeline. Applying in single-cell datasets, all three types of chimera were discovered in each dataset, which introduced plenty of false positives in structural variation (SV) detection. The identification and filtration of chimeras by ChimeraMiner removed most of the false positive SVs (83.8%). ChimeraMiner revealed improved efficiency in discovering chimeric reads, and is promising to be widely used in single-cell sequencing.

Comparative genome analysis reveals the evolution of chloroacetanilide herbicide mineralization in Sphingomonas wittichii DC-6

The environmental fate of the extensively used chloroacetanilide herbicides (CH) has been a cause of increasing concern in the past decade because of their carcinogenic properties. Although microbes play important roles in CH degradation, Sphingomonas wittichii DC-6 was the first reported CH-mineralizing bacterium. In this study, the complete genome of strain DC-6 was sequenced and comparative genomic analysis was performed using strain DC-6 and other three partial CH-degrading bacteria, Sphingobium quisquiliarum DC-2, Sphingobium baderi DE-13, and Sphingobium sp. MEA3-1. 16S rDNA phylogenetic analysis indicated that strain DC-2, MEA3-1, and DE-13 are closely related and DC-6 has relatively distant genetic relationship with the other three strains. The identified CH degradation genes responsible for the upstream and downstream pathway, including cndA, cmeH, meaXY, and meaAB, were all located in conserved DNA fragments (or genetic islands) in the vicinity of mobile element proteins. Protein BLAST in the NCBI database showed that cndA and cmeH were present in the genomes of other sequenced strains isolated from various habitats; however, the gene compositions in these host strains were completely different from those of other sphingomonads, and codon usage of genes for upstream pathway were also different from that of downstream pathway. These results showed that the upstream and downstream pathways of CH degradation in strain DC-6 have evolved by horizontal gene transfer and gene combination. In addition, the genes of the ring-cleavage pathway were not conserved and may have evolved directly from bacterial degradation of hydroxyquinol. The present study provides insights into the evolutionary strategy and microbial catabolic pathway of CH mineralization.

Nanopore ultra-long read sequencing technology for antimicrobial resistance detection in Mannheimia haemolytica

Disruptive innovations in long-range, cost-effective direct template nucleic acid sequencing are transforming clinical and diagnostic medicine. A multidrug resistant strain and a pan-susceptible strain of Mannheimia haemolytica, isolated from pneumonic bovine lung samples, were sequenced at 146× and 111× coverage, respectively with Oxford Nanopore Technologies MinION. De novo assembly produced a complete genome for the non-resistant strain and a nearly complete assembly for the drug resistant strain. Functional annotation using RAST (Rapid Annotations using Subsystems Technology), CARD (Comprehensive Antibiotic Resistance Database) and ResFinder databases identified genes conferring resistance to different classes of antibiotics including β-lactams, tetracyclines, lincosamides, phenicols, aminoglycosides, sulfonamides and macrolides. Resistance phenotypes of the M. haemolytica strains were determined by minimum inhibitory concentration (MIC) of the antibiotics. Sequencing with a highly portable MinION device corresponded to MIC assays with most of the antimicrobial resistant determinants being identified with as few as 5437 reads, except for the genes responsible for resistance to Fluoroquinolones. The resulting quality assemblies and AMR gene annotation highlight the efficiency of ultra-long read, whole-genome sequencing (WGS) as a valuable tool in diagnostic veterinary medicine.

Genome Survey Sequencing of Acer truncatum Bunge to Identify Genomic Information, Simple Sequence Repeat (SSR) Markers and Complete Chloroplast Genome

The Acer truncatum Bunge is a particular forest tree species found in the north of China. Due to the recent discovery that its seeds contain a considerable amount of nervonic acid, this species has received more and more attention. However, there have been no reports of the genome in this species. In this study, we report on the Acer truncatum genome sequence produced by genome survey sequencing. In total, we obtained 61.90 Gbp of high-quality data, representing approximately 116x coverage of the Acer truncatum genome. The genomic characteristics of Acer truncatum include a genome size of 529.88 Mbp, a heterozygosis rate of 1.06% and a repeat rate of 48.8%. A total of 392,961 high-quality genomic SSR markers were developed and a graphical map of the annotated circular chloroplast genome was generated. Thus far, this is the first report of de novo whole genome sequencing and assembly of Acer truncatum. We believe that this genome sequence dataset may provide a new resource for future genomic analysis and molecular breeding studies of Acer truncatum.

Peculiar features of the plastids of the colourless alga Euglena longa and photosynthetic euglenophytes unveiled by transcriptome analyses

Euglenophytes are a familiar algal group with green alga-derived secondary plastids, but the knowledge of euglenophyte plastid function and evolution is still highly incomplete. With this in mind we sequenced and analysed the transcriptome of the non-photosynthetic species Euglena longa. The transcriptomic data confirmed the absence of genes for the photosynthetic machinery, but provided candidate plastid-localised proteins bearing N-terminal bipartite topogenic signals (BTSs) of the characteristic euglenophyte type. Further comparative analyses including transcriptome assemblies available for photosynthetic euglenophytes enabled us to unveil salient aspects of the basic euglenophyte plastid infrastructure, such as plastidial targeting of several proteins as C-terminal translational fusions with other BTS-bearing proteins or replacement of the conventional eubacteria-derived plastidial ribosomal protein L24 by homologs of archaeo-eukaryotic origin. Strikingly, no homologs of any key component of the TOC/TIC system and the plastid division apparatus are discernible in euglenophytes, and the machinery for intraplastidial protein targeting has been simplified by the loss of the cpSRP/cpFtsY system and the SEC2 translocon. Lastly, euglenophytes proved to encode a plastid-targeted homolog of the termination factor Rho horizontally acquired from a Lambdaproteobacteria-related donor. Our study thus further documents a substantial remodelling of the euglenophyte plastid compared to its green algal progenitor.

An Effective Pipeline Based on Relative Coverage for the Genome Assembly of Phytoplasmas and Other Fastidious Prokaryotes

BACKGROUND

For the plant pathogenic phytoplasmas, as well as for several fastidious prokaryotes, axenic cultivation is extremely difficult or not possible yet; therefore, even with second generation sequencing methods, obtaining the sequence of their genomes is challenging due to host sequence contamination.

OBJECTIVE

With the Phytoassembly pipeline here presented, we aim to provide a method to obtain high quality genome drafts for the phytoplasmas and other uncultivable plant pathogens, by exploiting the coverage differential in the ILLUMINA sequences from the pathogen and the host, and using the sequencing of a healthy, isogenic plant as a filter.

VALIDATION

The pipeline has been benchmarked using simulated and real ILLUMINA runs from phytoplasmas whose genome is known, and it was then used to obtain high quality drafts for three new phytoplasma genomes.

CONCLUSION

For phytoplasma infected samples containing >2-4% of pathogen DNA and an isogenic reference healthy sample, the resulting assemblies can be next to complete. The Phytoassembly source code is available on GitHub at https://github.com/cpolano/phytoassembly.

Single-cell metagenomics: challenges and applications

With the development of high throughput sequencing and single-cell genomics technologies, many uncultured bacterial communities have been dissected by combining these two techniques. Especially, by simultaneously leveraging of single-cell genomics and metagenomics, researchers can greatly improve the efficiency and accuracy of obtaining whole genome information from complex microbial communities, which not only allow us to identify microbes but also link function to species, identify subspecies variations, study host-virus interactions and etc. Here, we review recent developments and the challenges need to be addressed in single-cell metagenomics, including potential contamination, uneven sequence coverage, sequence chimera, genome assembly and annotation. With the development of sequencing and computational methods, single-cell metagenomics will undoubtedly broaden its application in various microbiome studies.

Capturing the 'ome': the expanding molecular toolbox for RNA and DNA library construction

All sequencing experiments and most functional genomics screens rely on the generation of libraries to comprehensively capture pools of targeted sequences. In the past decade especially, driven by the progress in the field of massively parallel sequencing, numerous studies have comprehensively assessed the impact of particular manipulations on library complexity and quality, and characterized the activities and specificities of several key enzymes used in library construction. Fortunately, careful protocol design and reagent choice can substantially mitigate many of these biases, and enable reliable representation of sequences in libraries. This review aims to guide the reader through the vast expanse of literature on the subject to promote informed library generation, independent of the application.

Single-cell genomics of multiple uncultured stramenopiles reveals underestimated functional diversity across oceans

Single-celled eukaryotes (protists) are critical players in global biogeochemical cycling of nutrients and energy in the oceans. While their roles as primary producers and grazers are well appreciated, other aspects of their life histories remain obscure due to challenges in culturing and sequencing their natural diversity. Here, we exploit single-cell genomics and metagenomics data from the circumglobal Tara Oceans expedition to analyze the genome content and apparent oceanic distribution of seven prevalent lineages of uncultured heterotrophic stramenopiles. Based on the available data, each sequenced genome or genotype appears to have a specific oceanic distribution, principally correlated with water temperature and depth. The genome content provides hypotheses for specialization in terms of cell motility, food spectra, and trophic stages, including the potential impact on their lifestyles of horizontal gene transfer from prokaryotes. Our results support the idea that prominent heterotrophic marine protists perform diverse functions in ocean ecology.

The biology of many marine protists, such as stramenopiles, remains obscure. Here, the authors exploit single-cell genomics and metagenomics to analyze the genome content and apparent oceanic distribution of seven prevalent lineages of uncultured heterotrophic stramenopiles.

Oral microbiome and health

The oral microbiome is diverse in its composition due to continuous contact of oral cavity with the external environment. Temperatures, diet, pH, feeding habits are important factors that contribute in the establishment of oral microbiome. Both culture dependent and culture independent approaches have been employed in the analysis of oral microbiome. Gene-based methods like PCR amplification techniques, random amplicon cloning, PCR-RELP, T-RELP, DGGE and DNA microarray analysis have been applied to increase oral microbiome related knowledge. Studies revealed that microbes from the phyla Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, Fusobacteria, Neisseria, TM7 predominately inhabits the oral cavity. Culture-independent molecular techniques revealed the presence of genera Megasphaera, Parvimonas and Desulfobulbus in periodontal disease. Bacteria, fungi and protozoa colonize themselves on various surfaces in oral cavity. Microbial biofilms are formed on the buccal mucosa, dorsum of the tongue, tooth surfaces and gingival sulcus. Various studies demonstrate relationship between unbalanced microflora and development of diseases like tooth caries, periodontal diseases, type 2 diabetes, circulatory system related diseases etc. Transcriptome-based remodelling of microbial metabolism in health and disease associated states has been well reported. Human diets and habitat can trigger virus activation and influence phage members of oral microbiome. As it is said, "Mouth, is the gateway to the total body wellness, thus oral microbiome influences overall health of an individual".

Single molecule sequencing of the M13 virus genome without amplification

Next generation sequencing (NGS) has revolutionized life sciences research. However, GC bias and costly, time-intensive library preparation make NGS an ill fit for increasing sequencing demands in the clinic. A new class of third-generation sequencing platforms has arrived to meet this need, capable of directly measuring DNA and RNA sequences at the single-molecule level without amplification. Here, we use the new GenoCare single-molecule sequencing platform from Direct Genomics to sequence the genome of the M13 virus. Our platform detects single-molecule fluorescence by total internal reflection microscopy, with sequencing-by-synthesis chemistry. We sequenced the genome of M13 to a depth of 316x, with 100% coverage. We determined a consensus sequence accuracy of 100%. In contrast to GC bias inherent to NGS results, we demonstrated that our single-molecule sequencing method yields minimal GC bias.

Genome Survey Sequencing of Luffa Cylindrica L. and Microsatellite High Resolution Melting (SSR-HRM) Analysis for Genetic Relationship of Luffa Genotypes

Luffa cylindrica (L.) Roem. is an economically important vegetable crop in China. However, the genomic information on this species is currently unknown. In this study, for the first time, a genome survey of L. cylindrica was carried out using next-generation sequencing (NGS) technology. In total, 43.40 Gb sequence data of L. cylindrica, about 54.94× coverage of the estimated genome size of 789.97 Mb, were obtained from HiSeq 2500 sequencing, in which the guanine plus cytosine (GC) content was calculated to be 37.90%. The heterozygosity of genome sequences was only 0.24%. In total, 1,913,731 contigs (>200 bp) with 525 bp N₅₀ length and 1,410,117 scaffolds (>200 bp) with 885.01 Mb total length were obtained. From the initial assembled L. cylindrica genome, 431,234 microsatellites (SSRs) (≥5 repeats) were identified. The motif types of SSR repeats included 62.88% di-nucleotide, 31.03% tri-nucleotide, 4.59% tetra-nucleotide, 0.96% penta-nucleotide and 0.54% hexa-nucleotide. Eighty genomic SSR markers were developed, and 51/80 primers could be used in both “Zheda 23” and “Zheda 83”. Nineteen SSRs were used to investigate the genetic diversity among 32 accessions through SSR-HRM analysis. The unweighted pair group method analysis (UPGMA) dendrogram tree was built by calculating the SSR-HRM raw data. SSR-HRM could be effectively used for genotype relationship analysis of Luffa species.

An improved filtering algorithm for big read datasets and its application to single-cell assembly

Background

For single-cell or metagenomic sequencing projects, it is necessary to sequence with a very high mean coverage in order to make sure that all parts of the sample DNA get covered by the reads produced. This leads to huge datasets with lots of redundant data. A filtering of this data prior to assembly is advisable. Brown et al. (2012) presented the algorithm Diginorm for this purpose, which filters reads based on the abundance of their k-mers.

Methods

We present Bignorm, a faster and quality-conscious read filtering algorithm. An important new algorithmic feature is the use of phred quality scores together with a detailed analysis of the k-mer counts to decide which reads to keep.

Results

We qualify and recommend parameters for our new read filtering algorithm. Guided by these parameters, we remove in terms of median 97.15% of the reads while keeping the mean phred score of the filtered dataset high. Using the SDAdes assembler, we produce assemblies of high quality from these filtered datasets in a fraction of the time needed for an assembly from the datasets filtered with Diginorm.

Conclusions

We conclude that read filtering is a practical and efficient method for reducing read data and for speeding up the assembly process. This applies not only for single cell assembly, as shown in this paper, but also to other projects with high mean coverage datasets like metagenomic sequencing projects.

Our Bignorm algorithm allows assemblies of competitive quality in comparison to Diginorm, while being much faster. Bignorm is available for download at https://git.informatik.uni-kiel.de/axw/Bignorm.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1724-7) contains supplementary material, which is available to authorized users.

Contribution of Next-Generation Sequencing to Aquatic and Fish Virology

The recent technological advances in nucleic acid sequencing, called next-generation sequencing (NGS), have revolutionized the field of genomics and have also influenced viral research. Aquatic viruses, and especially those infecting fish, have also greatly benefited from NGS technologies, which provide a huge amount of molecular information at a low cost in a relatively short period of time. Here, we review the use of the current high-throughput sequencing platforms with a special focus on the associated challenges (regarding sample preparation and bioinformatics) in their applications to the field of aquatic virology, especially for: (i) discovering novel viruses that may be associated with fish mortalities, (ii) elucidating the mechanisms of pathogenesis, and finally (iii) studying the molecular epidemiology of these pathogens.

A comparative evaluation of genome assembly reconciliation tools

Background

The majority of eukaryotic genomes are unfinished due to the algorithmic challenges of assembling them. A variety of assembly and scaffolding tools are available, but it is not always obvious which tool or parameters to use for a specific genome size and complexity. It is, therefore, common practice to produce multiple assemblies using different assemblers and parameters, then select the best one for public release. A more compelling approach would allow one to merge multiple assemblies with the intent of producing a higher quality consensus assembly, which is the objective of assembly reconciliation.

Results

Several assembly reconciliation tools have been proposed in the literature, but their strengths and weaknesses have never been compared on a common dataset. We fill this need with this work, in which we report on an extensive comparative evaluation of several tools. Specifically, we evaluate contiguity, correctness, coverage, and the duplication ratio of the merged assembly compared to the individual assemblies provided as input.

Conclusions

None of the tools we tested consistently improved the quality of the input GAGE and synthetic assemblies. Our experiments show an increase in contiguity in the consensus assembly when the original assemblies already have high quality. In terms of correctness, the quality of the results depends on the specific tool, as well as on the quality and the ranking of the input assemblies. In general, the number of misassemblies ranges from being comparable to the best of the input assembly to being comparable to the worst of the input assembly.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1213-3) contains supplementary material, which is available to authorized users.

Clinical and biological insights from viral genome sequencing

Whole-genome sequencing (WGS) of pathogens is becoming increasingly important not only for basic research but also for clinical science and practice. In virology, WGS is important for the development of novel treatments and vaccines, and for increasing the power of molecular epidemiology and evolutionary genomics. In this Opinion article, we suggest that WGS of viruses in a clinical setting will become increasingly important for patient care. We give an overview of different WGS methods that are used in virology and summarize their advantages and disadvantages. Although there are only partially addressed technical, financial and ethical issues in regard to the clinical application of viral WGS, this technique provides important insights into virus transmission, evolution and pathogenesis.

Removing the bottleneck in whole genome sequencing of Mycobacterium tuberculosis for rapid drug resistance analysis: a call to action

Whole genome sequencing (WGS) can provide a comprehensive analysis of Mycobacterium tuberculosis mutations that cause resistance to anti-tuberculosis drugs. With the deployment of bench-top sequencers and rapid analytical software, WGS is poised to become a useful tool to guide treatment. However, direct sequencing from clinical specimens to provide a full drug resistance profile remains a serious challenge. This article reviews current practices for extracting M. tuberculosis DNA and possible solutions for sampling sputum. Techniques under consideration include enzymatic digestion, physical disruption, chemical degradation, detergent solubilization, solvent extraction, ligand-coated magnetic beads, silica columns, and oligonucleotide pull-down baits. Selective amplification of genomic bacterial DNA in sputum prior to WGS may provide a solution, and differential lysis to reduce the levels of contaminating human DNA is also being explored. To remove this bottleneck and accelerate access to WGS for patients with suspected drug-resistant tuberculosis, it is suggested that a coordinated and collaborative approach be taken to more rapidly optimize, compare, and validate methodologies for sequencing from patient samples.

Survey of the green picoalga Bathycoccus genomes in the global ocean

Bathycoccus is a cosmopolitan green micro-alga belonging to the Mamiellophyceae, a class of picophytoplankton that contains important contributors to oceanic primary production. A single species of Bathycoccus has been described while the existence of two ecotypes has been proposed based on metagenomic data. A genome is available for one strain corresponding to the described phenotype. We report a second genome assembly obtained by a single cell genomics approach corresponding to the second ecotype. The two Bathycoccus genomes are divergent enough to be unambiguously distinguishable in whole DNA metagenomic data although they possess identical sequence of the 18S rRNA gene including in the V9 region. Analysis of 122 global ocean whole DNA metagenome samples from the Tara-Oceans expedition reveals that populations of Bathycoccus that were previously identified by 18S rRNA V9 metabarcodes are only composed of these two genomes. Bathycoccus is relatively abundant and widely distributed in nutrient rich waters. The two genomes rarely co-occur and occupy distinct oceanic niches in particular with respect to depth. Metatranscriptomic data provide evidence for gain or loss of highly expressed genes in some samples, suggesting that the gene repertoire is modulated by environmental conditions.

Picodroplet partitioned whole genome amplification of low biomass samples preserves genomic diversity for metagenomic analysis

BACKGROUND

Whole genome amplification (WGA) is a challenging, key step in metagenomic studies of samples containing minute amounts of DNA, such as samples from low biomass environments. It is well known that multiple displacement amplification (MDA), the most commonly used WGA method for microbial samples, skews the genomic representation in the sample. We have combined MDA with droplet microfluidics to perform the reaction in a homogeneous emulsion. Each droplet in this emulsion can be considered an individual reaction chamber, allowing partitioning of the MDA reaction into millions of parallel reactions with only one or very few template molecules per droplet.

RESULTS

As a proof-of-concept, we amplified genomic DNA from a synthetic metagenome by MDA either in one bulk reaction or in emulsion and found that after sequencing, the species distribution was better preserved and the coverage depth was more evenly distributed across the genomes when the MDA reaction had been performed in emulsion.

CONCLUSIONS

Partitioning MDA reactions into millions of reactions by droplet microfluidics is a straightforward way to improve the uniformity of MDA reactions for amplifying complex samples with limited amounts of DNA.