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Evidence for secondary-variant genetic burden and non-random distribution across biological modules in a recessive ciliopathy

Nature Genetics volume 52, pages 1145–1150 (2020)Cite this article

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Abstract

The influence of genetic background on driver mutations is well established; however, the mechanisms by which the background interacts with Mendelian loci remain unclear. We performed a systematic secondary-variant burden analysis of two independent cohorts of patients with Bardet–Biedl syndrome (BBS) with known recessive biallelic pathogenic mutations in one of 17 BBS genes for each individual. We observed a significant enrichment of trans-acting rare nonsynonymous secondary variants in patients with BBS compared with either population controls or a cohort of individuals with a non-BBS diagnosis and recessive variants in the same gene set. Strikingly, we found a significant over-representation of secondary alleles in chaperonin-encoding genes—a finding corroborated by the observation of epistatic interactions involving this complex in vivo. These data indicate a complex genetic architecture for BBS that informs the biological properties of disease modules and presents a model for secondary-variant burden analysis in recessive disorders.

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Fig. 1: Graphical outline of the study and mutational burden across cases and controls.
Fig. 2: Genetic and modular interactions in BBS cases and controls.

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Data availability

A summary of the genotypes presented in the present study is given in Supplementary Table 1. However, restrictions apply to the availability of whole-exome data, patient consent forms and Institutional Review Board instructions. Selected data can be made available from the corresponding author upon reasonable request and inclusion of appropriate Institutional Review Board documentation.

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Acknowledgements

We thank the patients and their families for participating in this study, as well as their caring physicians who provided clinical information and referred the patients for diagnostic analyses. We are grateful to C. Glodosky and A. Krentz from PreventionGenetics and R. Haws from Marshfield Clinic for providing information on clinical BBS exome data. We thank A.-S. Jaeger and M. Antin for technical assistance. This study was supported by NIH grants GM121317-13, HD042601 and DK072301 (to N.K.), grants R35GM127131, R01MH101244 and U01HG00908 (to S.R.S.) and R01 HG004037 (to I.J.), as well as GENCODE Wellcome Trust grant U41 HG007234 (to I.J.). R.A.L. is a senior scientific investigator of research to prevent blindness. N.K. is a distinguished Valerie and George D. Kennedy professor.

Author information

Author notes

  1. These authors contributed equally: Maria Kousi, Onuralp Söylemez.

Authors and Affiliations

  1. Center for Human Disease Modeling, Duke University Medical Center, Durham, NC, USA

    Maria Kousi, Aysegül Ozanturk, Azita Sadeghpour, Kelsey McFadden, Erica E. Davis & Nicholas Katsanis

  2. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Maria Kousi, Onuralp Söylemez, Irwin Jungreis, Maxim Y. Wolf, Manolis Kellis & Shamil R. Sunyaev

  3. MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA

    Maria Kousi, Irwin Jungreis, Maxim Y. Wolf & Manolis Kellis

  4. Division of Genetics, Brigham and Women’s Hospital, Boston, MA, USA

    Onuralp Söylemez, Sebastian Akle, Christopher A. Cassa & Shamil R. Sunyaev

  5. Department of Medicine, Harvard Medical School, Boston, MA, USA

    Onuralp Söylemez, Christopher A. Cassa & Shamil R. Sunyaev

  6. Advanced Center for Translational and Genetic Medicine, Lurie Children’s Hospital, Chicago, IL, USA

    Niki Mourtzi, Erica E. Davis & Nicholas Katsanis

  7. Department of Organismic and Evolutionary Biology, Harvard University, Boston, MA, USA

    Sebastian Akle

  8. Laboratoire de Génétique Médicale, Institut de Génétique Médicale d’Alsace, INSERM U1112, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg, Strasbourg, France

    Jean Muller & Hélène Dollfus

  9. Laboratoire de Diagnostic Génétique, Institut de Génétique Médicale d’Alsace, Hôpitaux Universitaires de Strasbourg, Strasbourg, France

    Jean Muller

  10. Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine and Department of Neurology, Massachusetts General Hospital, Boston, MA, USA

    Harrison Brand & Michael E. Talkowski

  11. Program in Population and Medical Genetics and Genomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Harrison Brand & Michael E. Talkowski

  12. Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA

    Jill Anne Mokry & Richard A. Lewis

  13. Department of Ophthalmology, Baylor College of Medicine, Houston, TX, USA

    Richard A. Lewis

  14. Program in Bioinformatics and Integrative Genomics, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA

    Michael E. Talkowski

  15. Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA

    Shamil R. Sunyaev

  16. Departments of Pediatrics and Cellular and Molecular Biology, Northwestern University School of Medicine, Chicago, IL, USA

    Nicholas Katsanis

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  1. Maria Kousi
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Contributions

M. Kousi, E.E.D., S.R.S. and N.K. designed the study. M. Kousi, A.O. and K.M. performed the experimental work by genotyping and analyzing the sequencing data. O.S., N.M., S.A., C.A.C., M. Kousi, H.B., M.E.T. and S.R.S. performed the statistical analyses assessing mutational burden and population structure. I.J., M.Y.W. and M. Kellis performed the analyses assessing the impact of the identified changes on genomic sequence signatures. J.M., J.A.M., R.A.L. and H.D. contributed the samples that were analyzed in this study. A.S. collated the genetic information of the discovery cohort. M. Kousi performed the collective analysis of genetic data and modular interactions. N.K. and M. Kousi wrote the manuscript. All authors read and commented on the manuscript.

Corresponding author

Correspondence to Nicholas Katsanis.

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Competing interests

N.K. is a founder of, and holds significant stock in, Rescindo Therapeutics.

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Extended data

Extended Data Fig. 1 Distribution of burden-contributing variation across case and control cohorts.

a, Burden-contributing variants across cases of the Discovery cohort (n = 102), Replication cohort (n = 175), and Meta-analysis of all BBS cases (n = 277) across four population-based minor allele frequency (MAF) cutoffs (1%, 0.5%, 0.1%, and 0.001%). b, Values of burden-contributing variation between BBS cases of the Discovery cohort (n = 102) and the cohort of NEU controls (n = 384) showing a 2.5-fold enrichment for ultra-rare (MAF < 0.001%) alleles in cases compared to controls. c, BBS cases of the Replication cohort (n = 175) and the Replication control cohort (n = 488) showing a 2.5-fold enrichment for ultra-rare (MAF < 0.001%) alleles in cases compared to controls. d, Collapsed case, control and “non-BBS recessive” cohorts. e, f, Distribution of individuals with burden-contributing alleles with MAF < 1% (e) and with MAF < 0.001% (f) in control individuals (blue bars) and BBS cases (orange bars).

Extended Data Fig. 2 Distribution of burden-contributing variation across case and control cohorts in each of four discrete MAF bins.

a, The Discovery case cohort shows a 2.5-fold enrichment for ultra-rare (0.001% > MAF > 0%) alleles compared to controls. b, The Replication cohort shows a 2-fold enrichment of such alleles compared to the exome control cohort. c, The BBS case meta-analysis shows a 2.2-fold enrichment compared to the combined control cohorts. d, Collapsed cohorts. a–d show plots across four MAF bins (1% > MAF > 0.5%, 0.5% > MAF > 0.1%, 0.1% > MAF > 0.001%, and 0.001% > MAF > 0%).

Extended Data Fig. 3 Estimate of protein impact for the least disruptive of the diagnostic variants for BBS cases and non-BBS recessive individuals, with at least one missense change in the primary locus.

With high BLOSUM62 scores denoting biochemically similar amino acid changes and lower scores marking radical amino acid changes, the graph shows evidence for bona fide BBS cases harboring more disruptive variants.

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Kousi, M., Söylemez, O., Ozanturk, A. et al. Evidence for secondary-variant genetic burden and non-random distribution across biological modules in a recessive ciliopathy. Nat Genet 52, 1145–1150 (2020). https://doi.org/10.1038/s41588-020-0707-1

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