Next generation sequencing data of a defined microbial mock community

Abstract

Generating sequence data of a defined community composed of organisms with complete reference genomes is indispensable for the benchmarking of new genome sequence analysis methods, including assembly and binning tools. Moreover the validation of new sequencing library protocols and platforms to assess critical components such as sequencing errors and biases relies on such datasets. We here report the next generation metagenomic sequence data of a defined mock community (Mock Bacteria ARchaea Community; MBARC-26), composed of 23 bacterial and 3 archaeal strains with finished genomes. These strains span 10 phyla and 14 classes, a range of GC contents, genome sizes, repeat content and encompass a diverse abundance profile. Short read Illumina and long-read PacBio SMRT sequences of this mock community are described. These data represent a valuable resource for the scientific community, enabling extensive benchmarking and comparative evaluation of bioinformatics tools without the need to simulate data. As such, these data can aid in improving our current sequence data analysis toolkit and spur interest in the development of new tools.

Nitrogen cycling in Sandusky Bay, Lake Erie: oscillations between strong and weak export and implications for harmful algal blooms

“…Primer design for universal amplification of the V4-V5 region of 16S rDNA was based on Parada et al (2016). Resulting sequences were demultiplexed, and contaminating Illumina adaptor sequences were removed using the k-mer filter in BBDuk (v37.62) following Singer et al (2016). Briefly, BBDuk was used to remove reads containing more than 1 N base or with a quality score < 10 across the read or a length ≤ 51 bp or 33 % of the full length read.…”

“…Briefly, BBDuk was used to remove reads containing more than 1 N base or with a quality score < 10 across the read or a length ≤ 51 bp or 33 % of the full length read. Additional processing using BBMap (http://bbtools.jgi.doe.gov, last access: 19 January 2018) mapped reads to masked human, cat, dog, and mouse references, discarding hits exceeding 93 % identity (Singer et al, 2016).…”

Recovery of genomes from metagenomes via a dereplication, aggregation, and scoring strategy

“…To validate the DAS Tool algorithm, we applied it to data from a synthetic microbial community that was constructed by mixing together DNA of 22 bacteria (including different species from the same genus) and 3 archaea 14 . We predicted bins using five binning tools (ABAWACA 1.07 (https://github.com/CK7/abawaca), CONCOCT 9 , MaxBin 2 11 , MetaBAT 10 and tetranucleotide ESOMs 4 ) and combined the result using DAS Tool.…”

SpaRC: Scalable Sequence Clustering using Apache Spark

“…This is the theoretical limit for overlap-based clustering algorithms. The 163 second data set is two million Illumina short metagenome reads (150bp) sampled from a 164 mock microbial community consisting of 26 genomes described previously [34]. Clusters 165 are defined similarly as above for the PacBio transcriptome data set.…”

“…34 Since current NGS technologies are not able to read the entire sequence of a genome 35 at once, genomes are broken into small DNA/RNA fragments followed by massive 36 parallel high-throughput sequencing. Different technologies produce sequence reads that 37 vary in length.…”