真菌基因组de novo测序组装的方法与实践

真菌基因组较其他真核生物基因组结构简单,长度短,易于测序、组装与注释,因此真菌基因组是研究真核生物基因组的模型。为研究真菌基因组组装策略,本研究基于Illumina HiSeq测序平台对烟曲霉菌株An16007基因组测序,分别使用5种de novo组装软件ABySS、SOAP-denovo、Velvet、MaSuRCA和IDBA-UD组装基因组,然后通过Augustus软件进行基因预测,BUSCO软件评估组装结果。研究发现,5种组装软件对基因组组装结果不同,ABySS组装的基因组较其他4种组装软件具有更高的完整性和准确性,且预测的基因数量较高,因此,ABySS更适合本研究基因组的组装。本研究提供了真菌de novo测序、组装及组装质量评估的技术流程,为基因组<100 Mb的真菌或其他生物基因组的研究提供参考。     

Accuracy of de novo assembly of DNA sequences from double‐digest libraries varies substantially among software

Advances in DNA sequencing have made it feasible to gather genomic data for non‐model organisms and large sets of individuals, often using methods for sequencing subsets of the genome. Several of these methods sequence DNA associated with endonuclease restriction sites (various RAD and GBS methods). For use in taxa without a reference genome, these methods rely on de novo assembly of fragments in the sequencing library. Many of the software options available for this application were originally developed for other assembly types and we do not know their accuracy for reduced representation libraries. To address this important knowledge gap, we simulated data from the Arabidopsis thaliana and Homo sapiens genomes and compared de novo assemblies by six software programs that are commonly used or promising for this purpose (ABySS , CD‐HIT , Stacks , Stacks2 , Velvet and VSEARCH ). We simulated different mutation rates and types of mutations, and then applied the six assemblers to the simulated data sets, varying assembly parameters. We found substantial variation in software performance across simulations and parameter settings. ABySS failed to recover any true genome fragments, and Velvet and VSEARCH performed poorly for most simulations. Stacks and Stacks2 produced accurate assemblies of simulations containing SNPs, but the addition of insertion and deletion mutations decreased their performance. CD‐HIT was the only assembler that consistently recovered a high proportion of true genome fragments. Here, we demonstrate the substantial difference in the accuracy of assemblies from different software programs and the importance of comparing assemblies that result from different parameter settings.     

Assembly and RNA‐free annotation of highly heterozygous genomes: The case of the thick‐billed murre (Uria lomvia)

Thanks to a dramatic reduction in sequencing costs followed by a rapid development of bioinformatics tools, genome assembly and annotation have become accessible to many researchers in recent years. Among tetrapods, birds have genomes that display many features that facilitate their assembly and annotation, such as small genome size, low number of repeats and highly conserved genomic structure. However, we found that high genomic heterozygosity could have a great impact on the quality of the genome assembly of the thick‐billed murre (Uria lomvia), an arctic colonial seabird. In this study, we tested the performance of three genome assemblers, ray /sscape , soapdenovo 2 and platanus , in assembling the highly heterozygous genome of the thick‐billed murre. Our results show that platanus , an assembler specifically designed for heterozygous genomes, outperforms the other two approaches and produces a highly contiguous (N50 = 15.8 Mb) and complete genome assembly (93% presence of genes from the Benchmarking Universal Single Copy Ortholog [BUSCO] gene set). Additionally, we annotated the thick‐billed murre genome using a homology‐based approach that takes advantage of the genomic resources available for birds and other taxa. Our study will be useful for those researchers who are approaching assembly and annotation of highly heterozygous genomes, or genomes of species of conservation concern, and/or who have limited financial resources.     

MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads

An important step in ‘metagenomics’ analysis is the assembly of multiple genomes from mixed sequence reads of multiple species in a microbial community. Most conventional pipelines use a single-genome assembler with carefully optimized parameters. A limitation of a single-genome assembler for de novo metagenome assembly is that sequences of highly abundant species are likely misidentified as repeats in a single genome, resulting in a number of small fragmented scaffolds. We extended a single-genome assembler for short reads, known as ‘Velvet’, to metagenome assembly, which we called ‘MetaVelvet’, for mixed short reads of multiple species. Our fundamental concept was to first decompose a de Bruijn graph constructed from mixed short reads into individual sub-graphs, and second, to build scaffolds based on each decomposed de Bruijn sub-graph as an isolate species genome. We made use of two features, the coverage (abundance) difference and graph connectivity, for the decomposition of the de Bruijn graph. For simulated datasets, MetaVelvet succeeded in generating significantly higher N50 scores than any single-genome assemblers. MetaVelvet also reconstructed relatively low-coverage genome sequences as scaffolds. On real datasets of human gut microbial read data, MetaVelvet produced longer scaffolds and increased the number of predicted genes.     

Evaluating the fidelity of de novo short read metagenomic assembly using simulated data

A frequent step in metagenomic data analysis comprises the assembly of the sequenced reads. Many assembly tools have been published in the last years targeting data coming from next-generation sequencing (NGS) technologies but these assemblers have not been designed for or tested in multi-genome scenarios that characterize metagenomic studies. Here we provide a critical assessment of current de novo short reads assembly tools in multi-genome scenarios using complex simulated metagenomic data. With this approach we tested the fidelity of different assemblers in metagenomic studies demonstrating that even under the simplest compositions the number of chimeric contigs involving different species is noticeable. We further showed that the assembly process reduces the accuracy of the functional classification of the metagenomic data and that these errors can be overcome raising the coverage of the studied metagenome. The results presented here highlight the particular difficulties that de novo genome assemblers face in multi-genome scenarios demonstrating that these difficulties, that often compromise the functional classification of the analyzed data, can be overcome with a high sequencing effort.     

转录本组装与质量评价

转录本组装是基于第二代测序技术研究转录组的关键环节,其质量好坏直接影响到下游结果的可靠性,也是目前的研究热点与难点。转录本组装方法可以分为Genome-guided和de novo两类,它们在理论基础与算法实现方面各有优劣。转录本组装质量的高低依赖于PCR扩增错误率、第二代测序技术准确率、组装算法和参考基因组完整性等方面,而现有的算法还无法完全处理由这些因素带来的影响。本文从转录本组装方法与软件、影响组装质量的因素和对组装质量的评价指标等方面进行讨论,以期能指导纯生物学家对分析软件的选择。     

MetaVelvet-SL: an extension of the Velvet assembler to a de novo metagenomic assembler utilizing supervised learning

The assembly of multiple genomes from mixed sequence reads is a bottleneck in metagenomic analysis. A single-genome assembly program (assembler) is not capable of resolving metagenome sequences, so assemblers designed specifically for metagenomics have been developed. MetaVelvet is an extension of the single-genome assembler Velvet. It has been proved to generate assemblies with higher N50 scores and higher quality than single-genome assemblers such as Velvet and SOAPdenovo when applied to metagenomic sequence reads and is frequently used in this research community. One important open problem for MetaVelvet is its low accuracy and sensitivity in detecting chimeric nodes in the assembly (de Bruijn) graph, which prevents the generation of longer contigs and scaffolds. We have tackled this problem of classifying chimeric nodes using supervised machine learning to significantly improve the performance of MetaVelvet and developed a new tool, called MetaVelvet-SL. A Support Vector Machine is used for learning the classification model based on 94 features extracted from candidate nodes. In extensive experiments, MetaVelvet-SL outperformed the original MetaVelvet and other state-of-the-art metagenomic assemblers, IDBA-UD, Ray Meta and Omega, to reconstruct accurate longer assemblies with higher N50 scores for both simulated data sets and real data sets of human gut microbial sequences.     

A practical comparison of de novo genome assembly software tools for next-generation sequencing technologies

The advent of next-generation sequencing technologies is accompanied with the development of many whole-genome sequence assembly methods and software, especially for de novo fragment assembly. Due to the poor knowledge about the applicability and performance of these software tools, choosing a befitting assembler becomes a tough task. Here, we provide the information of adaptivity for each program, then above all, compare the performance of eight distinct tools against eight groups of simulated datasets from Solexa sequencing platform. Considering the computational time, maximum random access memory (RAM) occupancy, assembly accuracy and integrity, our study indicate that string-based assemblers, overlap-layout-consensus (OLC) assemblers are well-suited for very short reads and longer reads of small genomes respectively. For large datasets of more than hundred millions of short reads, De Bruijn graph-based assemblers would be more appropriate. In terms of software implementation, string-based assemblers are superior to graph-based ones, of which SOAPdenovo is complex for the creation of configuration file. Our comparison study will assist researchers in selecting a well-suited assembler and offer essential information for the improvement of existing assemblers or the developing of novel assemblers.     

Next-Generation Sequence Assembly: Four Stages of Data Processing and Computational Challenges

Decoding DNA symbols using next-generation sequencers was a major breakthrough in genomic research. Despite the many advantages of next-generation sequencers, e.g., the high-throughput sequencing rate and relatively low cost of sequencing, the assembly of the reads produced by these sequencers still remains a major challenge. In this review, we address the basic framework of next-generation genome sequence assemblers, which comprises four basic stages: preprocessing filtering, a graph construction process, a graph simplification process, and postprocessing filtering. Here we discuss them as a framework of four stages for data analysis and processing and survey variety of techniques, algorithms, and software tools used during each stage. We also discuss the challenges that face current assemblers in the next-generation environment to determine the current state-of-the-art. We recommend a layered architecture approach for constructing a general assembler that can handle the sequences generated by different sequencing platforms.     

Mock communities highlight the diversity of host‐associated eukaryotes

Host‐associated microbes are ubiquitous. Every multicellular eukaryote, and even many unicellular eukaryotes (protists), hosts a diverse community of microbes. High‐throughput sequencing (HTS) tools have illuminated the vast diversity of host‐associated microbes and shown that they have widespread influence on host biology, ecology and evolution (McFall‐Ngai et al. 2013 ). Bacteria receive most of the attention, but protists are also important components of microbial communities associated with humans (Parfrey et al. 2011 ) and other hosts. As HTS tools are increasingly used to study eukaryotes, the presence of numerous and diverse host‐associated eukaryotes is emerging as a common theme across ecosystems. Indeed, HTS studies demonstrate that host‐associated lineages account for between 2 and 12% of overall eukaryotic sequences detected in soil, marine and freshwater data sets, with much higher relative abundances observed in some samples (Ramirez et al. 2014 ; Simon et al. 2015 ; de Vargas et al. 2015 ). Previous studies in soil detected large numbers of predominantly parasitic lineages such as Apicomplexa, but did not delve into their origin [e.g. (Ramirez et al. 2014 )]. In this issue of Molecular Ecology, Geisen et al. ( 2015 ) use mock communities to show that many of the eukaryotic organisms detected by environmental sequencing in soils are potentially associated with animal hosts rather than free‐living. By isolating the host‐associated fraction of soil microbial communities, Geisen and colleagues help explain the surprisingly high diversity of parasitic eukaryotic lineages often detected in soil/terrestrial studies using high‐throughput sequencing (HTS) and reinforce the ubiquity of these host‐associated microbes. It is clear that we can no longer assume that organisms detected in bulk environmental sequencing are free‐living, but instead need to design studies that specifically enumerate the diversity and function of host‐associated eukaryotes. Doing so will allow the field to determine the role host‐associated eukaryotes play in soils and other environments and to evaluate hypotheses on assembly of host‐associated communities, disease ecology and more.     

Reevaluating Assembly Evaluations with Feature Response Curves: GAGE and Assemblathons

In just the last decade, a multitude of bio-technologies and software pipelines have emerged to revolutionize genomics. To further their central goal, they aim to accelerate and improve the quality of de novo whole-genome assembly starting from short DNA sequences/reads. However, the performance of each of these tools is contingent on the length and quality of the sequencing data, the structure and complexity of the genome sequence, and the resolution and quality of long-range information. Furthermore, in the absence of any metric that captures the most fundamental “features” of a high-quality assembly, there is no obvious recipe for users to select the most desirable assembler/assembly. This situation has prompted the scientific community to rely on crowd-sourcing through international competitions, such as Assemblathons or GAGE, with the intention of identifying the best assembler(s) and their features. Somewhat circuitously, the only available approach to gauge de novo assemblies and assemblers relies solely on the availability of a high-quality fully assembled reference genome sequence. Still worse, reference-guided evaluations are often both difficult to analyze, leading to conclusions that are difficult to interpret. In this paper, we circumvent many of these issues by relying upon a tool, dubbed , which is capable of evaluating de novo assemblies from the read-layouts even when no reference exists. We extend the FRCurve approach to cases where lay-out information may have been obscured, as is true in many deBruijn-graph-based algorithms. As a by-product, FRCurve now expands its applicability to a much wider class of assemblers – thus, identifying higher-quality members of this group, their inter-relations as well as sensitivity to carefully selected features, with or without the support of a reference sequence or layout for the reads. The paper concludes by reevaluating several recently conducted assembly competitions and the datasets that have resulted from them.     

CISA: Contig Integrator for Sequence Assembly of Bacterial Genomes

A plethora of algorithmic assemblers have been proposed for the de novo assembly of genomes, however, no individual assembler guarantees the optimal assembly for diverse species. Optimizing various parameters in an assembler is often performed in order to generate the most optimal assembly. However, few efforts have been pursued to take advantage of multiple assemblies to yield an assembly of high accuracy. In this study, we employ various state-of-the-art assemblers to generate different sets of contigs for bacterial genomes. A tool, named CISA, has been developed to integrate the assemblies into a hybrid set of contigs, resulting in assemblies of superior contiguity and accuracy, compared with the assemblies generated by the state-of-the-art assemblers and the hybrid assemblies merged by existing tools. This tool is implemented in Python and requires MUMmer and BLAST+ to be installed on the local machine. The source code of CISA and examples of its use are available at http://sb.nhri.org.tw/CISA/.     

Whole genome sequencing of Thaumetopoea pityocampa revealed putative pesticide targets

Insect neuropeptides play a major role in the regulation of the physiological processes. Due to their versatile effects on the development of insects, their corresponding receptors, which are mostly G-protein coupled receptors, are considered as ideal targets for designing next-generation pesticides. In this study, we aimed to find neuropeptide receptors of pine processionary moth (Thaumetopoea pityocampa), a pest in the Mediterranean countries, that feeds on the needles of pine trees. To this aim, Whole Genome Shotgun sequencing technique was used. de novo assembly of the genome was performed using two different assemblers, SGA and MaSuRCA. The results of two assemblers were compared, and MaSuRCA assembler showed higher N50 length. To find some target GPCRs, sequences of Drosophila melanogaster and evolutionarily close species were used as blast queries in the assembled data. Five GPCRs were chosen from the genome and their expression was confirmed in the larval stage of the insect.     

Stacking up RADSeq assembly programs: From complete hit to completely abysmal

Decreasing sequencing costs have driven a rapid expansion of novel genotyping methods. One of these methods is the exploitation of restriction enzyme cut sites to generate genome‐wide but reduced representation sequencing libraries (RRLs), alternatively termed genotyping by sequencing or restriction‐site associated DNA sequencing. Without a reference genome, the resulting short sequence reads must be assembled de novo. There are many possible assembly programs, most not explicitly developed for RRL data, and we know little of their effectiveness. In this issue of Molecular Ecology Resources, LaCava et al. (2020) systematically evaluate six commonly used programs and two commonly varied parameters for complete and accurate assembly of RRLs, using simulated double digests of Homo sapiens and Arabidopsis thaliana genomes with varied mutation rates and types. The authors find substantial variation in performance across assembly programs. The most consistently high‐performing assembler is infrequently used in their literature survey (CD‐HIT; Li and Godzik, 2006), while several others fail to produce complete, accurate assemblies under many conditions. LaCava et al. additionally recommend best practices in parameter choice and evaluation of future assembly programs—advice that molecular ecologists working to assemble sequences of all kinds should take to heart.     

AutoAssemblyD: a graphical user interface system for several genome assemblers

Next-generation sequencing technologies have increased the amount of biological data generated. Thus, bioinformatics has become important because new methods and algorithms are necessary to manipulate and process such data. However, certain challenges have emerged, such as genome assembly using short reads and high-throughput platforms. In this context, several algorithms have been developed, such as Velvet, Abyss, Euler-SR, Mira, Edna, Maq, SHRiMP, Newbler, ALLPATHS, Bowtie and BWA. However, most such assemblers do not have a graphical interface, which makes their use difficult for users without computing experience given the complexity of the assembler syntax. Thus, to make the operation of such assemblers accessible to users without a computing background, we developed AutoAssemblyD, which is a graphical tool for genome assembly submission and remote management by multiple assemblers through XML templates.

Availability

AssemblyD is freely available at https://sourceforge.net/projects/autoassemblyd. It requires Sun jdk 6 or higher.     

Improving the genetic representation of rare taxa within complex microbial communities using DNA normalization methods

Complex microbial communities typically contain a large number of low abundance species, which collectively, comprise a considerable proportion of the community. This ‘rare biosphere’ has been speculated to contain keystone species and act as a repository of genomic diversity to facilitate community adaptation. Many environmental microbes are currently resistant to cultivation, and can only be accessed via culture‐independent approaches. To enhance our understanding of the role of the rare biosphere, we aimed to improve their metagenomic representation using DNA normalization methods, and assess normalization success via shotgun DNA sequencing. A synthetic metagenome was constructed from the genomic DNA of five bacterial species, pooled in a defined ratio spanning three orders of magnitude. The synthetic metagenome was fractionated and thermally renatured, allowing the most abundant sequences to hybridize. Double‐stranded DNA was removed either by hydroxyapatite chromatography, or by a duplex‐specific nuclease (DSN). The chromatographic method failed to enrich for the genomes present in low starting abundance, whereas the DSN method resulted in all genomes reaching near equimolar abundance. The representation of the rarest member was increased by approximately 450‐fold. De novo assembly of the normalized metagenome enabled up to 18.0% of genes from the rarest organism to be assembled, in contrast to the un‐normalized sample, where genes were not able to be assembled at the same sequencing depth. This study has demonstrated that the application of normalization methods to metagenomic samples is a powerful tool to enrich for sequences from rare taxa, which will shed further light on their ecological niches.