Metagenomic next-generatoin sequencing of IPAH and control lung tissues for pan-viral detection and discovery
A 0.5 cm3 piece of previously snap frozen lung tissue was placed in a 2ml tube with RLT Buffer (Qiagen, Hilden Germany) and 0.1mm silica beads (MPBiomedicals, Solon OH). Next, the samples were homogenized using an Omni Bead Ruptor (Omni Intl.Kennesaw, GA), and cellular debris was pelleted.  Total RNA was extracted using the EZ1 RNA Universal Tissue kit (Qiagen). An on-instrument DNase treatment was performed to minimize any background genomic DNA, followed by enrichment for polyadenylated mRNA using OligoTex (Qiagen).  The nucleic acid samples were randomly amplified to generate a cDNA library, and the quality and size distributions of the libraries was examined by 2% agarose gel electrophoresis.  Metagenomic sequencing libraries were then generated using a modified Illumina TruSeq protocol.  The BioAnalyzer High-Sensitivity DNA kit (Agilent, Santa Clara, CA) was used to assess library size and the Kapa Universal qPCR kit (Kapa Biosystems, Woburn, MA) was used to quantitate the library concentration. After validation, samples were sequenced on an Illumina MiSeq instrument using 300/200bp paired-end sequencing. Raw sequencing reads were analyzed using SURPI (Naccache, et al., 2014, Genome Research, 24(7):1180-1192), a computational pathogen detection pipeline developed at the University of California, San Francisco to classify the reads bioinformatically by their origin.  The core pipeline is based on a computational subtraction approach that uses the SNAP nucleotide aligner (Zaharia, arXiv:1111.5572v1) to first filter out reads that align to human host background sequences, and then identify reads corresponding to viruses, bacteria, and other pathogens on the basis of alignments to the National Center for Biotechnology Information (NCBI) non-redundant nucleotide (NT) database. Reads that do not align to any sequence in the NT database can be further analyzed using RAPSearch, an amino acid aligner that aligns translated reads to a viral protein database. Alignment at the protein level (instead of nucleotide level) facilitates the identification of novel viruses which exhibit high sequence divergence.     For the purposes of this analysis, the pipeline was also modified to specificially analyze the human endogenous retrovirus (HERV) component of these samples.  Since HERV sequences align to the human genome, the SNAP alignment to human portion of the pipeline was eliminated.  Instead, SNAP was used to directly align preprocessed reads (after adapter trimming and quality / low-complexity filtering) to the NCBI viral database.  Taxonomic classification on the SNAP-aligned reads was performed for HERV reads with perfect matches (edit distance d=0) using the least common ancestor algorithm.      Human reads have been removed for all of the submitted FASTQ files to minimize or eliminate potential identifing genomic information.