TY - JOUR
T1 - Mapping genomic regulation of kidney disease and traits through high-resolution and interpretable eQTLs
AU - Nephrotic Syndrome Study Network (NEPTUNE)
AU - Han, Seong Kyu
AU - McNulty, Michelle T.
AU - Benway, Christopher J.
AU - Wen, Pei
AU - Greenberg, Anya
AU - Onuchic-Whitford, Ana C.
AU - Jang, Dongkeun
AU - Flannick, Jason
AU - Burtt, Noël P.
AU - Wilson, Parker C.
AU - Humphreys, Benjamin D.
AU - Wen, Xiaoquan
AU - Han, Zhe
AU - Lee, Dongwon
AU - Sampson, Matthew G.
N1 - Funding Information:
The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The data used for the analyses described in this manuscript were obtained from the GTEx Portal on 03/16/2021. This research is benefited by the data generated by the ENCODE consortium. We thank Dr. Chakravarti for sharing unpublished adult kidney bulk ATAC-seq data. The authors would like to acknowledge Boston Children’s Hospital’s High-Performance Computing Resources BCH HPC Clusters Enkefalos 2 (E2) and Massachusetts Green High-Performance Computing (MGHPCC) made available for conducting the research reported in this publication. Software used in the project was installed and configured by BioGrids (cite: eLife 2013;2:e01456, Collaboration gets the most out of software.) M.G.S. is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK119380 and RC2DK122397) and the Pura Vida Kidney Foundation. D.L. is supported by the NEPTUNE Career Development Fellowship, Boston Children’s Hospital OFD/BTREC/CTREC Faculty Development Fellowship, and a Manton Center Endowed Scholar Award. Z.H. is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK098410, R01DK120908, & R01DK119380). A.C.O. is supported by the National Institutes of Health F32 Ruth L. Kirschstein Postdoctoral Individual National Research Service Award (F32DK122766). P.C.W. is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (1K08DK126847-01A1). X.W. is supported by The National Institute of General Medical Sciences (R35GM138121) and The National Institute of Environmental Health Sciences (R01ES033634). JF, NPB, DKJ were supported by The National Human Genome Research Institute (U24HG011453) and National Institute of Diabetes and Digestive and Kidney Diseases (UM1DK105554). NEPTUNE: The Nephrotic Syndrome Rare Disease Clinical Research Network III (NEPTUNE) is part of the Rare Diseases Clinical Research Network (RDCRN), which is funded by the National Institutes of Health (NIH) and led by the National Center for Advancing Translational Sciences (NCATS) through its Office of Rare Diseases Research (ORDR). NEPTUNE is funded under grant number U54DK083912 as a collaboration between NCATS and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Additional funding and/or programmatic support for this project has also been provided by the University of Michigan, NephCure Kidney International and the Halpin Foundation. All RDCRN consortia are supported by the network’s Data Management and Coordinating Center (DMCC) (U2CTR002818). Funding support for the DMCC is provided by NCATS and the National Institute of Neurological Disorders and Stroke (NINDS).
Funding Information:
The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The data used for the analyses described in this manuscript were obtained from the GTEx Portal on 03/16/2021. This research is benefited by the data generated by the ENCODE consortium. We thank Dr. Chakravarti for sharing unpublished adult kidney bulk ATAC-seq data. The authors would like to acknowledge Boston Children’s Hospital’s High-Performance Computing Resources BCH HPC Clusters Enkefalos 2 (E2) and Massachusetts Green High-Performance Computing (MGHPCC) made available for conducting the research reported in this publication. Software used in the project was installed and configured by BioGrids (cite: eLife 2013;2:e01456, Collaboration gets the most out of software.) M.G.S. is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK119380 and RC2DK122397) and the Pura Vida Kidney Foundation. D.L. is supported by the NEPTUNE Career Development Fellowship, Boston Children’s Hospital OFD/BTREC/CTREC Faculty Development Fellowship, and a Manton Center Endowed Scholar Award. Z.H. is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK098410, R01DK120908, & R01DK119380). A.C.O. is supported by the National Institutes of Health F32 Ruth L. Kirschstein Postdoctoral Individual National Research Service Award (F32DK122766). P.C.W. is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (1K08DK126847-01A1). X.W. is supported by The National Institute of General Medical Sciences (R35GM138121) and The National Institute of Environmental Health Sciences (R01ES033634). JF, NPB, DKJ were supported by The National Human Genome Research Institute (U24HG011453) and National Institute of Diabetes and Digestive and Kidney Diseases (UM1DK105554). NEPTUNE: The Nephrotic Syndrome Rare Disease Clinical Research Network III (NEPTUNE) is part of the Rare Diseases Clinical Research Network (RDCRN), which is funded by the National Institutes of Health (NIH) and led by the National Center for Advancing Translational Sciences (NCATS) through its Office of Rare Diseases Research (ORDR). NEPTUNE is funded under grant number U54DK083912 as a collaboration between NCATS and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Additional funding and/or programmatic support for this project has also been provided by the University of Michigan, NephCure Kidney International and the Halpin Foundation. All RDCRN consortia are supported by the network’s Data Management and Coordinating Center (DMCC) (U2CTR002818). Funding support for the DMCC is provided by NCATS and the National Institute of Neurological Disorders and Stroke (NINDS).
Publisher Copyright:
© 2023, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - Expression quantitative trait locus (eQTL) studies illuminate genomic variants that regulate specific genes and contribute to fine-mapped loci discovered via genome-wide association studies (GWAS). Efforts to maximize their accuracy are ongoing. Using 240 glomerular (GLOM) and 311 tubulointerstitial (TUBE) micro-dissected samples from human kidney biopsies, we discovered 5371 GLOM and 9787 TUBE genes with at least one variant significantly associated with expression (eGene) by incorporating kidney single-nucleus open chromatin data and transcription start site distance as an “integrative prior” for Bayesian statistical fine-mapping. The use of an integrative prior resulted in higher resolution eQTLs illustrated by (1) smaller numbers of variants in credible sets with greater confidence, (2) increased enrichment of partitioned heritability for GWAS of two kidney traits, (3) an increased number of variants colocalized with the GWAS loci, and (4) enrichment of computationally predicted functional regulatory variants. A subset of variants and genes were validated experimentally in vitro and using a Drosophila nephrocyte model. More broadly, this study demonstrates that tissue-specific eQTL maps informed by single-nucleus open chromatin data have enhanced utility for diverse downstream analyses.
AB - Expression quantitative trait locus (eQTL) studies illuminate genomic variants that regulate specific genes and contribute to fine-mapped loci discovered via genome-wide association studies (GWAS). Efforts to maximize their accuracy are ongoing. Using 240 glomerular (GLOM) and 311 tubulointerstitial (TUBE) micro-dissected samples from human kidney biopsies, we discovered 5371 GLOM and 9787 TUBE genes with at least one variant significantly associated with expression (eGene) by incorporating kidney single-nucleus open chromatin data and transcription start site distance as an “integrative prior” for Bayesian statistical fine-mapping. The use of an integrative prior resulted in higher resolution eQTLs illustrated by (1) smaller numbers of variants in credible sets with greater confidence, (2) increased enrichment of partitioned heritability for GWAS of two kidney traits, (3) an increased number of variants colocalized with the GWAS loci, and (4) enrichment of computationally predicted functional regulatory variants. A subset of variants and genes were validated experimentally in vitro and using a Drosophila nephrocyte model. More broadly, this study demonstrates that tissue-specific eQTL maps informed by single-nucleus open chromatin data have enhanced utility for diverse downstream analyses.
UR - http://www.scopus.com/inward/record.url?scp=85152979278&partnerID=8YFLogxK
U2 - 10.1038/s41467-023-37691-7
DO - 10.1038/s41467-023-37691-7
M3 - Article
C2 - 37076491
AN - SCOPUS:85152979278
SN - 2041-1723
VL - 14
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 2229
ER -