GWAS summary statistics for gut bacterial variable structural variation

Data accompanying the paper by Zhernakova <em>et al.</em> "Host Genetic Regulation of Human Gut Microbial Structural Variation", Nature 2023. <strong>Dataset description</strong> This study involved 9,015 Dutch individuals for whom both metagenomic and host genetic data were available. We used SGV-Finder (Zeevi <em>et al.</em>, 2019) to generate structural variation (SV) profiles for variable SVs (vSVs) and deletion SVs (dSVs) from human gut metagenomic sequencing data. To ensure statistical power for association with host genetics, we selected vSVs detected in at least 10% of samples and dSVs with deletion rates between 5% and 95%. This resulted in 3,552 SVs including 1,666 dSVs and 1,886 vSVs from 49 bacterial taxa. Next, we associated these 3,552 SVs with more than 6 million human SNPs per cohort, followed by a meta-analysis. Association analysis was performed using fastGWA from the GCTA toolbox (version 1.94.1), per cohort per SV. For dSVs, we used the generalized linear mixed model-based version of the tool (--fastGWA-mlm-binary). In the association analyses, we used a sparse genetic relationship matrix (GRM) created from the full GRM built on genotyped (non-imputed) SNPs with MAF &gt; 5% using GCTA with default options (--make-grm and --make-bK-sparse 0.05). The following covariates were added to the model: age, sex, total metagenomic sequencing read number, and CLR-transformed species abundance. The total read count was standardized to have a mean of zero and a variance of one. Meta-analysis was performed using the Metal software with default options (weighting cohort-based p-values according to sample size). <strong>File description</strong> Files contain full GWAS summary statistics for the association between bacterial variable SVs and human SNP genotypes from the meta-analysis of 4 Dutch cohorts. Per-SV results are combined into files per species. SV annotation can be found in the "Gut microbial structural variation profile" folder in the same collection. <em>See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6877849</em> <strong>Funding statement</strong><br> This study is supported by Netherlands Organization for Scientific Research (NWO)-VICI grant VI.C.202.022 (J.F.), NWO-VIDI grant 016.178.056 (A.Z.), NWO-VENI grant 194.006 (D.V.Z.), NWO-VENI grant 222.016 (D.W.), European Research Council (ERC)-Consolidator grant 101001678 (J.F.), ERC Starting Grant 715772 (A.Z.), and Dutch Heart Foundation grant IN-CONTROL (CVON2018-27 to J.F., A.Z., M.G.N., L.A.B.J., J.H.W.R, N.P.R). In addition, C.W. and J.F. are supported by the Netherlands Organ-on-Chip Initiative, an NWO Gravitation project (024.003.001) funded by the Ministry of Education, Culture and Science of the government of the Netherlands. J.F. is supported by the AMMODO Science Award 2023 for Biomedical Sciences from Stichting Ammodo. A.Z. is further supported by the NWO Gravitation grant Exposome-NL (024.004.017), and EU Horizon Europe Program grant INITIALISE (101094099). The 300TZ cohort received funding from the Joint Programming Initiative, A Healthy Diet for a Healthy Life (JPI‐HDHL; project 529051018, TransMic) and ZonMw (the Netherlands Organization for Health Research and Development). S.S. is supported by Next Generation EU grant Project Age-It (DM MUR 1557 11.10.2022), ERC Starting Grant 2022 (101075624), and NutrAGE grant (DM MUR 844 16.07.2021). R.K.W. is supported by the Seerave foundation and NWO. L.L. is supported by a joint fellowship from the University Medical Center Groningen and China Scholarship Council (CSC) with grant number CSC201908320432. Y.Z. is supported by a joint fellowship from the University Medical Center Groningen and CSC with grant number CSC202006170040. N.P. is supported by a grant of the Graduate School of Medical Sciences of the University of Groningen, the Netherlands. H.P is supported by a joint fellowship from the University Medical Center Groningen and CSC with grant number CSC202208060107.