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Identification of cis-suppression of human disease mutations by comparative genomics

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Abstract

Patterns of amino acid conservation have served as a tool for understanding protein evolution1. The same principles have also found broad application in human genomics, driven by the need to interpret the pathogenic potential of variants in patients2. Here we performed a systematic comparative genomics analysis of human disease-causing missense variants. We found that an appreciable fraction of disease-causing alleles are fixed in the genomes of other species, suggesting a role for genomic context. We developed a model of genetic interactions that predicts most of these to be simple pairwise compensations. Functional testing of this model on two known human disease genes3,4 revealed discrete cis amino acid residues that, although benign on their own, could rescue the human mutations in vivo. This approach was also applied to ab initio gene discovery to support the identification of a de novo disease driver in BTG2 that is subject to protective cis-modification in more than 50 species. Finally, on the basis of our data and models, we developed a computational tool to predict candidate residues subject to compensation. Taken together, our data highlight the importance of cis-genomic context as a contributor to protein evolution; they provide an insight into the complexity of allele effect on phenotype; and they are likely to assist methods for predicting allele pathogenicity5,6.

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Figure 1: Distribution of variants found in sequence alignments.
Figure 2: Relationship between variants and evolutionary distance.
Figure 3: Compensatory mutations rescue pathogenic alleles in BBS4 and RPGRIP1L.
Figure 4: A de novo BTG2 p.V141M-encoding allele causes microcephaly.

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Acknowledgements

We thank Y. Liu and D. Balick for helpful discussions, M. Kousi for assistance with the NCL mutational list, and M. Talkowski, A. Kondrashov and G. Lyon for critical review of the manuscript. This work was supported by grants R01HD04260, R01DK072301 and R01DK075972 (N.K.); R01 GM078598, R01 MH101244, R01 DK095721 and U01 HG006500 (S.R.S.); R01EY021872 (E.E.D.); and a NARSAD Young Investigator Award (C.G.). N.K. is a Distinguished Brumley Professor.

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Authors and Affiliations

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Contributions

D.M.J., S.G.F., S.R.S. and N.K. designed the overall study. D.M.J., C.A.C. and S.R.S. conceptualized the principle of CPDs and performed all computational analyses. S.G.F., E.E.D. and N.K. conceptualized the biological properties of CPDs and implemented in vivo testing with the assistance of C.G. J.K. referred the index patient and evaluated clinical data in the context of molecular discoveries. The Task Force for Neonatal Genomics constructed the platforms and methods for recruitment, ascertainment and evaluation of clinical and molecular data and return of results.

Corresponding authors

Correspondence to Shamil R. Sunyaev or Nicholas Katsanis.

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The authors declare no competing financial interests.

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Lists of participants and their affiliations appear in the Supplementary Information.

Extended data figures and tables

Extended Data Figure 1 Different alignment methodologies with HumVar and ClinVar produce qualitatively similar alignments.

a, b, Distributions of missense variants annotated as neutral (a) or pathogenic (b) in the HumVar and ClinVar data sets, with each of the five alignment strategies described in the text (MultiZ unfiltered, MultiZ mammals-only, EPO, MultiZ with alignment quality filter, MultiZ with >1 sequence filter). All distributions are quantitatively similar. Compare with Fig. 2c, d.

Extended Data Figure 2 Protein domain structure of functionally tested human disease genes.

a, Schematic of BBS4 (519 amino acids) is depicted with eight tetratricopeptide (TPR) domains (yellow); b, RPGRIP1L (1,315 amino acids) has multiple coiled-coil domains (green rectangles) and two protein kinase C conserved region 2 (C2) domains (green hexagons); and c, BTG2 (158 amino acids) has one BTG1 domain (purple pentagon). Disease-causing alleles are shown with red stars; complementing alleles are represented with blue stars; amino acid number scale in increments of 100 is shown below each schematic.

Extended Data Figure 3 Evaluation of btg2 and nos2a/b MOs.

ac, Schematic of the D. rerio btg2, nos2a and nos2b loci. Blue boxes, exons; dashed lines, introns; white boxes, untranslated regions; red boxes, MOs; ATG indicates the translational start site; arrows, polymerase chain reaction with reverse transcription (RT–PCR) primers; number indicates the targeted exon. d, e, Agarose gel images of nos2a/b RT–PCR products.

Extended Data Figure 4 HuC/HuD staining and quantification of 2 dpf zebrafish embryos confirms pathogenicity of BTG2 V141M.

a, Suppression of btg2 leads to a decrease of HuC/HuD levels at 2 dpf. Representative ventral images of control, btg2 morphants (images show unilateral or absent HuC/HuD expression), and a rescued embryo injected with a btg2 MO plus human BTG2 wild-type (WT) mRNA. Scale bar, 250 μm. b, Percentage of embryos with normal, bilateral HuC/HuD protein levels in the anterior forebrain or decreased/unilateral HuC/HuD protein levels in embryos injected with btg2 MOs alone or MOs plus human BTG2 wild-type or variant mRNAs (p.V141M, index case; p.A126S and p.R145Q, control alleles). *P < 0.05 (two-tailed t-test comparisons between MO-injected and rescued embryos; n = 38–78 per injection batch).

Supplementary information

Supplementary Information

This file contains Supplementary Text and Supplementary Tables 1-11. (PDF 992 kb)

Supplementary Data

This file contains the Predictor Code, the source code for the publically accessible online prediction algorithm. (TXT 6 kb)

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Jordan, D., Frangakis, S., Golzio, C. et al. Identification of cis-suppression of human disease mutations by comparative genomics. Nature 524, 225–229 (2015). https://doi.org/10.1038/nature14497

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