Sequencing

11th Annual Sequencing, Finishing, and Analysis in the Future Meeting
ANALYSIS OF THE FUNCTIONAL CONTENTS OF
MICROBIAL COMMUNITIES USING A NOVEL QIAGEN
BIOINFORMATICS PIPELINE
Thursday, 2nd June 16:50 La Fonda Ballroom Tech Talk (TT‐2.05)
Andreas Sand Pedersen, Francesco Strino, Aske Simon Christensen, Martin Bundgaard
Qiagen Bioinformatics
The field of microbial ecology is currently being revolutionized through next generation sequencing
studies, revealing unprecedented detailed insight into environmental as well as host‐associated
microbiomes. But still, very few tools offer efficient and user‐friendly analysis of the functional genomic
contents of microbiomes.
We have implemented a unique pipeline of tools for functional and comparative analysis of microbiomes
as a component in QIAGEN Bioinformatics’ comprehensive solution for microbial genomics
‐ CLC Microbial Genomics Module. First step in this pipeline produces high‐quality metagenome
contigs using a novel fast and highly memory efficient metagenome de novo assembler. The resulting
contigs are subsequently CDS‐annotated using the MetaGeneMark plugin for CLC Genomics Workbench,
and CDSs are annotated with PFAM protein families, GO terms and/or top BLAST hits
(using e.g. UniProt). Finally, the relative abundance of each identified functional genomic element
is computed and presented to the user in a user‐friendly manner.
The functional contents of individual samples can be studied in a tabular format or visualized as
pie charts, while visual comparison of multiple samples is done using stacked bar charts, layered
area charts and principal coordinate plots. Finally, statistical comparison of multiple microbiome
samples can be done to back‐up our observations. All visualisations and statistical analysis can be
performed in the context of user‐defined meta‐information such as patient/control data.
We will present benchmarks of this pipeline, performed on both previously published mock community
datasets and several recently published simulated microbiome datasets, designed for benchmarking
of microbiome analysis solutions.
We demonstrate that QIAGEN Bioinformatics’ new metagenome de novo assembler runs as fast as the
fastest alternative (MegaHit) but uses only a fraction of the memory required by any other
benchmarked de novo assembler. At the same time it produces contigs that are both longer than
the contigs produced by other popular metagenome assemblers (e.g. MegaHit and IDBA_UD) and
are of significantly higher quality than the contigs produced by any other benchmarked de novo
assembler.
We furthermore demonstrate that the high‐quality contigs produced by our metagenome de novo
assembler enables taxonomic and functional profiling of very high quality.
And finally, we show that the complete analysis pipeline producing functional profiles from raw
microbiome read datasets in five easy steps is able to reliably detect changes in the functional
content of microbiomes with statistical significance.
122