Posterior urethral valves (PUV) are the commonest cause of end-stage renal disease in children, but the genetic architecture of this rare disorder remains unknown. We performed a sequencing-based genome-wide association study (seqGWAS) in 132 unrelated male PUV cases and 23,727 controls of diverse ancestry, identifying statistically significant associations with common variants at 12q24.21 (P=7.8x10-12; OR 0.4) and rare variants at 6p21.1 (P=2.0x10-8; OR 7.2), that were replicated in an independent European cohort of 395 cases and 4,151 controls. Fine-mapping and functional genomic data mapped these loci to the transcription factor TBX5 and planar cell polarity gene PTK7, respectively, the encoded proteins of which were detected in the developing urinary tract of human embryos. We also observed enrichment of rare structural variation intersecting with candidate cis-regulatory elements, particularly inversions predicted to affect chromatin looping (P=3.1x10-5). These findings represent the first robust genetic associations of PUV, providing novel insights into the underlying biology of this poorly understood disorder and demonstrate how a diverse ancestry seqGWAS can be used for disease locus discovery in a rare disease.
All genetic and phenotypic data from the 100,000 Genomes Project and can be accessed by application to Genomics England Ltd (https://www.genomicsengland.co.uk/about-gecip/joining-research-community/). Access is free for academic research institutions and universities as well as public and private healthcare organsisations that undertake significant research activity. This dataset includes de-identified, linked information for each participant including genome sequence data, variant call files, phenotype/clinical data and Hospital Episode Statistics (HES) with access gained through a secure Research Environment. No sequencing or identifiable personal data is available for download.The full GWAS summary statistics have been uploaded to the NHGRI-EBI GWAS Catalog prior to publication.Source Data files have been provided for Figures 2, 6, 9 and 10 containing the numerical data used to generate figures.Custom R Code for the case-control ancestry-matching algorithm can be found at https://github.com/APLevine/PCA_Matching.Code for SAIGE and SAIGE-GENE can be found at https://github.com/weizhouUMICH/SAIGE.Code for PAINTOR is available at https://github.com/gkichaev/PAINTOR_V3.0.Functional annotation and MAGMA gene and gene-set analysis were performed using the web-based platform FUMA (https://fuma.ctglab.nl).Custom R code for the structural variant burden analysis has been uploaded as SV Burden Testing - Source Code 1.
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- Melanie Mai Yee Chan
- Omid Sadeghi-Alavijeh
- Adrian S Woolf
- Daniel P Gale
- Adam P Levine
- Glenda M Beaman
- William G Newman
- Adrian S Woolf
- Alina C Hilger
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: Ethical approval for the 100,000 Genomes Project was granted by the Research Ethics Committee for East of England - Cambridge South (REC Ref 14/EE/1112). Written informed consent was obtained from all participants and/or their guardians.Human embryonic tissues, collected after maternal consent and ethical approval (REC18/NE/0290), were sourced from the Medical Research Council and Wellcome Trust Human Developmental Biology Resource (https://www.hdbr.org/).
- Gregory G Germino, National Institutes of Health, United States
© 2022, Chan et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
SAS‑6 (SASS6) is essential for centriole formation in human cells and other organisms but its function in mouse is unclear. Here, we report that Sass6‑mutant mouse embryos lack centrioles, activate the mitotic surveillance cell death pathway and arrest at mid‑gestation. In contrast, SAS‑6 is not required for centriole formation in mouse embryonic stem cells (mESCs), but is essential to maintain centriole architecture. Of note, centrioles appeared after just one day of culture of Sass6‑mutant blastocysts, from which mESCs are derived. Conversely, the number of cells with centrosomes is drastically decreased upon the exit from a mESC pluripotent state. At the mechanistic level, the activity of the master kinase in centriole formation, PLK4, associated with increased centriolar and centrosomal protein levels, endow mESCs with the robustness in using SAS‑6‑independent centriole-duplication pathways. Collectively, our data suggest a differential requirement for mouse SAS‑6 in centriole formation or integrity depending on PLK4 and centrosome composition.
The Hydra nervous system is the paradigm of a ‘simple nerve net’. Nerve cells in Hydra, as in many cnidarian polyps, are organized in a nerve net extending throughout the body column. This nerve net is required for control of spontaneous behavior: elimination of nerve cells leads to polyps that do not move and are incapable of capturing and ingesting prey (Campbell, 1976). We have re-examined the structure of the Hydra nerve net by immunostaining fixed polyps with a novel antibody that stains all nerve cells in Hydra. Confocal imaging shows that there are two distinct nerve nets, one in the ectoderm and one in the endoderm, with the unexpected absence of nerve cells in the endoderm of the tentacles. The nerve nets in the ectoderm and endoderm do not contact each other. High-resolution TEM (transmission electron microscopy) and serial block face SEM (scanning electron microscopy) show that the nerve nets consist of bundles of parallel overlapping neurites. Results from transgenic lines show that neurite bundles include different neural circuits and hence that neurites in bundles require circuit-specific recognition. Nerve cell-specific innexins indicate that gap junctions can provide this specificity. The occurrence of bundles of neurites supports a model for continuous growth and differentiation of the nerve net by lateral addition of new nerve cells to the existing net. This model was confirmed by tracking newly differentiated nerve cells.