Dataset Information

LDscaff: LD-based scaffolding of de novo genome assemblies.

ABSTRACT:

Background

Genome assembly is fundamental for de novo genome analysis. Hybrid assembly, utilizing various sequencing technologies increases both contiguity and accuracy. While such approaches require extra costly sequencing efforts, the information provided millions of existed whole-genome sequencing data have not been fully utilized to resolve the task of scaffolding. Genetic recombination patterns in population data indicate non-random association among alleles at different loci, can provide physical distance signals to guide scaffolding.

Results

In this paper, we propose LDscaff for draft genome assembly incorporating linkage disequilibrium information in population data. We evaluated the performance of our method with both simulated data and real data. We simulated scaffolds by splitting the pig reference genome and reassembled them. Gaps between scaffolds were introduced ranging from 0 to 100 KB. The genome misassembly rate is 2.43% when there is no gap. Then we implemented our method to refine the Giant Panda genome and the donkey genome, which are purely assembled by NGS data. After LDscaff treatment, the resulting Panda assembly has scaffold N50 of 3.6 MB, 2.5 times larger than the original N50 (1.3 MB). The re-assembled donkey assembly has an improved N50 length of 32.1 MB from 23.8 MB.

Conclusions

Our method effectively improves the assemblies with existed re-sequencing data, and is an potential alternative to the existing assemblers required for the collection of new data.

SUBMITTER: Zhao Z

PROVIDER: S-EPMC7768660 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

LDscaff: LD-based scaffolding of de novo genome assemblies.

Zhao Zicheng Z Zhou Yingxiao Y Wang Shuai S Zhang Xiuqing X Wang Changfa C Li Shuaicheng S

BMC bioinformatics 20201228 Suppl 21

<h4>Background</h4>Genome assembly is fundamental for de novo genome analysis. Hybrid assembly, utilizing various sequencing technologies increases both contiguity and accuracy. While such approaches require extra costly sequencing efforts, the information provided millions of existed whole-genome sequencing data have not been fully utilized to resolve the task of scaffolding. Genetic recombination patterns in population data indicate non-random association among alleles at different loci, can p ...[more]

PMID: 33371875

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Project description:The current revolution in genomics has been made possible by software tools called genome assemblers, which stitch together DNA fragments "read" by sequencing machines into complete or nearly complete genome sequences. Despite decades of research in this field and the development of dozens of genome assemblers, assessing and comparing the quality of assembled genome sequences still relies on the availability of independently determined standards, such as manually curated genome sequences, or independently produced mapping data. These "gold standards" can be expensive to produce and may only cover a small fraction of the genome, which limits their applicability to newly generated genome sequences. Here we introduce a de novo? probabilistic measure of assembly quality which allows for an objective comparison of multiple assemblies generated from the same set of reads. We define the quality of a sequence produced by an assembler as the conditional probability of observing the sequenced reads from the assembled sequence. A key property of our metric is that the true genome sequence maximizes the score, unlike other commonly used metrics.We demonstrate that our de novo? score can be computed quickly and accurately in a practical setting even for large datasets, by estimating the score from a relatively small sample of the reads. To demonstrate the benefits of our score, we measure the quality of the assemblies generated in the GAGE and Assemblathon 1 assembly "bake-offs" with our metric. Even without knowledge of the true reference sequence, our de novo? metric closely matches the reference-based evaluation metrics used in the studies and outperforms other de novo? metrics traditionally used to measure assembly quality (such as N50). Finally, we highlight the application of our score to optimize assembly parameters used in genome assemblers, which enables better assemblies to be produced, even without prior knowledge of the genome being assembled.Likelihood-based measures, such as ours proposed here, will become the new standard for de novo? assembly evaluation.

Project description:With the increasing affordability and accessibility of genome sequencing data, de novo genome assembly is an important first step to a wide variety of downstream studies and analyses. Therefore, bioinformatics tools that enable the generation of high-quality genome assemblies in a computationally efficient manner are essential. Recent developments in long-read sequencing technologies have greatly benefited genome assembly work, including scaffolding, by providing long-range evidence that can aid in resolving the challenging repetitive regions of complex genomes. ntLink is a flexible and resource-efficient genome scaffolding tool that utilizes long-read sequencing data to improve upon draft genome assemblies built from any sequencing technologies, including the same long reads. Instead of using read alignments to identify candidate joins, ntLink utilizes minimizer-based mappings to infer how input sequences should be ordered and oriented into scaffolds. Recent improvements to ntLink have added important features such as overlap detection, gap-filling, and in-code scaffolding iterations. Here, we present three basic protocols demonstrating how to use each of these new features to yield highly contiguous genome assemblies, while still maintaining ntLink's proven computational efficiency. Further, as we illustrate in the alternate protocols, the lightweight minimizer-based mappings that enable ntLink scaffolding can also be utilized for other downstream applications, such as misassembly detection. With its modularity and multiple modes of execution, ntLink has broad benefit to the genomics community, from genome scaffolding and beyond. ntLink is an open-source project and is freely available from https://github.com/bcgsc/ntLink. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: ntLink scaffolding using overlap detection Basic Protocol 2: ntLink scaffolding with gap-filling Basic Protocol 3: Running in-code iterations of ntLink scaffolding Alternate Protocol 1: Generating long-read to contig mappings with ntLink Alternate Protocol 2: Using ntLink mappings for genome assembly correction with Tigmint-long Support Protocol: Installing ntLink.

Dataset Information

LDscaff: LD-based scaffolding of de novo genome assemblies.

Background

Results

Conclusions

Publications

LDscaff: LD-based scaffolding of de novo genome assemblies.

Similar Datasets

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