Type 2 and interferon inflammation strongly regulate SARS-CoV-2 related gene expression in the airway epithelium

Satria P. Sajuthi; Peter DeFord; Nathan D. Jackson; Michael T. Montgomery; Jamie L. Everman; Cydney L. Rios; Elmar Pruesse; James D. Nolin; Elizabeth G. Plender; Michael E. Wechsler; Angel CY Mak; Celeste Eng; Sandra Salazar; Vivian Medina; Eric M. Wohlford; Scott Huntsman; Deborah A. Nickerson; Soren Germer; Michael C. Zody; Gonçalo Abecasis; Hyun Min Kang; Kenneth M. Rice; Rajesh Kumar; Sam Oh; Jose Rodriguez-Santana; Esteban G. Burchard; Max A. Seibold

Recruited subjects completed in-person questionnaires detailing medical, 572 environmental, and demographic information. Physical measurements including 573 spirometry were obtained, and subjects provided a blood sample for DNA extraction and 574 later Whole Genome Sequencing. GALA subjects that were part of this analysis were all 575 recruited from Puerto Rico (n=695). A nasal airway inferior turbinate brushing was used 576 to collect airway epithelial cells from these subjects for whole transcriptome sequencing 577 (n=695). Network analyses were performed on all subjects with nasal brushing whole 578 transcriptome sequencing data (n=695) and eQTL analysis was performed on the 579 subset (n=681) with whole genome sequencing generated genotype data. The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.04.09.034454 doi: bioRxiv preprint read length of 150 base pairs, to a minimum of 30X mean genome coverage. Details on 605 DNA sample handling, quality control, library construction, clustering and sequencing, 606 read processing, and sequence data quality control are described elsewhere 35 Furthermore, minClusterSize was set to 20, deepSplit was set to 2, and pamStage was 671 set to TRUE. A total of 54 co-expression networks were identified and described in 672