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Published on: August 20, 2021
Assessment of metagenomic assembly using simulated next generation sequencing data
Daniel R Mende1, Alison S Waller, Shinichi Sunagawa
1European Molecular Biology Laboratory, Heidelberg, Germany.
Plos One
|March 3, 2012
Summary
Simulating metagenomic sequences is crucial for analyzing microbial communities. Our study shows Illumina sequencing offers superior assembly accuracy for complex communities, with scaffolding enhancing gene completeness.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Metagenomic sequence simulation is vital for evaluating bioinformatics tools due to complex microbial communities.
- Existing tools require robust testing against simulated data reflecting diverse community structures and sequencing technologies.
Purpose of the Study:
- To develop and utilize metagenomic read simulators with platform-specific error models.
- To assess the performance of different sequencing technologies (Sanger, pyrosequencing, Illumina) and data analysis methods on simulated metagenomes of varying complexity.
- To evaluate the impact of quality control and scaffolding on metagenomic assembly.
Main Methods:
- Development of metagenomic read simulators incorporating Sanger, pyrosequencing, and Illumina base-error models.
- Simulation of metagenomes representing simple (10 genomes), complex (100 genomes), and highly complex (400 genomes) microbial communities.
- Comparative analysis of assembly quality, functional composition accuracy, and contig length across sequencing platforms.
- Evaluation of the effect of rigorous quality filtering and paired-end read scaffolding on assembly outcomes.
Main Results:
- Quality filtering significantly improved Illumina data assembly accuracy and contig length, despite data loss.
- For simple communities, all technologies performed similarly; for complex communities, Illumina yielded superior assemblies and functional representation.
- In highly complex communities, assembly was limited, but Sanger reads provided reasonable functional composition due to longer read lengths.
- Scaffolding with paired-end Illumina reads substantially increased contig lengths, especially for simpler communities, improving gene completeness and functional repertoire characterization, albeit with increased chimericity.
Conclusions:
- Illumina sequencing, particularly with quality control and scaffolding, provides the most accurate metagenomic assemblies for complex microbial communities.
- Metagenomic simulators are valuable tools for benchmarking sequencing technologies and assembly algorithms.
- The developed metagenomic simulators are freely available for research use.
Related Concept Videos
03:36Genome Annotation and Assembly
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
03:00Next-generation Sequencing
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
03:21RNA-seq
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...