De novo assembly of the Indian blue peacock (<i>Pavo cristatus</i>) genome using Oxford Nanopore technology and Illumina sequencing

Dhar, Ruby; Seethy, Ashikh; Pethusamy, Karthikeyan; Singh, Sunil Kumar; Rohil, Vishwajeet; Purkayastha, Kakali; Mukherjee, Indrani; Goswami, Sandeep; Singh, Rakesh; Raj, Ankita; Srivastava, Tryambak; Acharya, Sovon; Rajashekhar, Balaji; Karmakar, Subhradip

doi:10.1093/gigascience/giz038

Cited by 30 publications

(61 citation statements)

References 47 publications

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“…The mock communities were composed by the same ten microorganisms, but in different proportions (Table 1). With the aim of reducing the computational resources needed for the first screening of the selected assemblers, the GridION and Prome-thION datasets were subsampled to obtain an output comparable with recent genomic or metagenomic studies based on MinION (approximately 3 Gbp and 6 Gbp) 9,[34][35][36][37][38][39] . In general, mean read length remained the same in the subsampled datasets in comparison to the original sequencing data 15 .…”

Section: Resultsmentioning

confidence: 99%

“…These platforms follow the same sequencing principles as MinION, but they have a significantly higher output. For that reason, the datasets were subsampled in order to adapt their output to the current yield offered by MinION (3-6 Gbp) 9,[34][35][36][37][38][39] , then extending the study to higher yields comparable with other recent works 46 . Despite the relatively low complexity of the mock communities analyzed in this evaluation study, our results show that there is a huge variation in assembly results depending on the software chosen to perform the analysis.…”

Section: Discussionmentioning

confidence: 99%

“…In order to reduce the computational effort, we performed an initial subsampling of this data. In particular, GridION and PromethION datasets were subsampled at two different sequencing depths (3 Gbp and 6 Gbp) to recreate MinION runs with different outputs, and the yield matched the output described in recent shotgun sequencing experiments based on MinION 9, [34][35][36][37][38][39] . Subsampling was performed by selecting the top lines of the FASTQ files.…”

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Assembly methods for nanopore-based metagenomic sequencing: a comparative study

Latorre‐Pérez¹,

Villalba-Bermell²,

Pascual³

et al. 2020

Sci Rep

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Metagenomic sequencing has allowed for the recovery of previously unexplored microbial genomes. Whereas short-read sequencing platforms often result in highly fragmented metagenomes, nanoporebased sequencers could lead to more contiguous assemblies due to their potential to generate long reads. Nevertheless, there is a lack of updated and systematic studies evaluating the performance of different assembly tools on nanopore data. In this study, we have benchmarked the ability of different assemblers to reconstruct two different commercially-available mock communities that have been sequenced using Oxford Nanopore Technologies platforms. Among the tested tools, only metaFlye, Raven, and Canu performed well in all the datasets. These tools retrieved highly contiguous genomes (or even complete genomes) directly from the metagenomic data. Despite the intrinsic high error of nanopore sequencing, final assemblies reached high accuracy (~ 99.5 to 99.8% of consensus accuracy). Polishing strategies demonstrated to be necessary for reducing the number of indels, and this had an impact on the prediction of biosynthetic gene clusters. correction with high quality short reads did not always result in higher quality draft assemblies. Overall, nanopore metagenomic sequencing data-adapted to MinION's current output-proved sufficient for assembling and characterizing lowcomplexity microbial communities. Background Metagenomic sequencing has revolutionized the way we study and characterize microbial communities. This culture-independent technique based on shotgun sequencing has been applied in a broad range of biological fields, ranging from microbial ecology 1 to evolution 2 , or even clinical microbiology 3. In recent years, metagenomics has also become a powerful tool for recovering individual genomes directly from complex microbiomes 2,4,5 , leading to the identification and description of new-and mostly unculturable-taxa with meaningful implications 6. Illumina has been the most widely used platform for metagenomic studies. Illumina reads are characterized by their short length (75-300 bp) and high accuracy (~ 0.1% of basecalling errors) 7. When performing de novo assemblies, Illumina sequences often result in highly fragmented genomes, even when sequencing pure cultures 8,9. This is a consequence of the inability to correctly assemble genomic regions containing repetitive elements that are longer than the read length 9. This fragmentation problem is magnified when handling metagenomic sequences due to the existence of intergenomic repeats that are shared by more than one taxon present in the microbial community 10. It has to be noted that microbial communities often contain related species or sub-species in different-and unknown-abundances, resulting in extensive intergenomic overlaps that can hinder the assembly process 11,12. Third generation sequencing platforms have recently emerged as a solution to resolve ambiguous repetitive regions and to improve genome contiguity. Despite the considerable error associated to these te...

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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Assembly methods for nanopore-based metagenomic sequencing: a comparative study

Latorre‐Pérez¹,

Villalba-Bermell²,

Pascual³

et al. 2020

Sci Rep

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“…These sequencers follow the same sequencing principles than MinION, but they have a significantly higher output. For that reason, we decided to subsample the datasets to adequate their output to the current yield offered by MinION (3-6 Gbps) (Goldstein et al, 2019;Dhar et al, 2019;Parajuli et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…With the recent adoption of Guppy (Oxford Nanopore Technologies) as the lead basecaller for all the ONT sequencers, the main difference between GridION, PromethION and MinION is the final output of each platform. MinION (Goldstein et al, 2019;Dhar et al, 2019;Parajuli et al, 2019).…”

Section: Dataset Descriptionmentioning

confidence: 99%

Assembly methods for nanopore-based metagenomic sequencing: a comparative study

Latorre-Pérez¹,

Villalba-Bermell²,

Pascual³

et al. 2019

Preprint

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BackgroundMetagenomic sequencing has lead to the recovery of previously unexplored microbial genomes. In this sense, short-reads sequencing platforms often result in highly fragmented metagenomes, thus complicating downstream analyses. Third generation sequencing technologies, such as MinION, could lead to more contiguous assemblies due to their ability to generate long reads. Nevertheless, there is a lack of studies evaluating the suitability of the available assembly tools for this new type of data.FindingsWe benchmarked the ability of different short-reads and long-reads tools to assembly two different commercially available mock communities, and observed remarkable differences in the resulting assemblies depending on the software of choice. Short-reads metagenomic assemblers proved unsuitable for MinION data. Among the long-reads assemblers tested, Flye and Canu were the only ones performing well in all the datasets. These tools were able to retrieve complete individual genomes directly from the metagenome, and assembled a bacterial genome in only two contigs in the best scenario. Despite the intrinsic high error of long-reads technologies, Canu and Flye lead to high accurate assemblies (~99.4-99.8 % of accuracy). However, errors still had an impact on the prediction of biosynthetic gene clusters.ConclusionsMinION metagenomic sequencing data proved sufficient for assembling low-complex microbial communities, leading to the recovery of highly complete and contiguous individual genomes. This work is the first systematic evaluation of the performance of different assembly tools on MinION data, and may help other researchers willing to use this technology to choose the most appropriate software depending on their goals. Future work is still needed in order to assess the performance of Oxford Nanopore MinION data on more complex microbiomes.

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