Idiopathic Arterial Pulmonary Hypertension HERV study- BA004
Four lung tissue samples from patients with idiopathic pulmonary arterial hypertension (IAPH) [CC012, ST006, ST022, BA004] and four lung tissue samples from control patients [UC010, VA006, AH014, UA011] were analyzed.    A 0.5cm3 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).  Nucleic acid samples were randomly amplified to generate a cDNA library as previously described (Greninger, et al., PloS ONE 2010), 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 protocol38.  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 300/200 base pair (bp) paired-end sequencing.  Approximately 18.3 million sequencing reads were analyzed using a modified version of SURPI (Sequence-Based Ultra-Rapid Pathogen Identification) (Naccache, et al., 2014, Genome Research 27(7):1180-92), a computational pipeline for detection of microbes, including viruses, from next-generation sequencing data.  After detection of viral sequences aligning to human endogenous retroviruses (HERVs) with an initial run using SURPI, the pipeline was rerun with the following modifications:  (1) raw sequencing reads were preprocessed by adapter trimming and low-quality / low-complexity filtering (generating ~1.3 to 3.5 million reads per sample), (2) the human computational subtraction step was skipped, and (3) preprocessed reads were aligned to the reads to the viral portion of the NCBI (National Center for Biotechnology Information) NT database to detect HERV sequences.  Viral reads were identified as HERVs using a stringent edit distance requirement of 0 (no mismatches) across 75 bp of sequence.  HERV reads were taxonomically classified to the appropriate rank (family, genus, species, or subspecies / strain) by use of an in-house developed classification algorithm using the SNAP nucleotide aligner (v0.15) (Zaharia, 2011, arXiv 1111.5572).  Heat maps were generated using matrix2png (Pavlidis and Noble, (2003) Bioinformatics 19:295-296).         Next-generation sequencing reads were filtered for exclusion of human sequences by both BLASTn alignment at an e-value cutoff of 10^-5 and Bowtie2 high-sensitivity local alignment to the human hg38 reference database.