Abstract
To better understand large-effect pathogenic variation associated with autism, we generated long-read sequencing (LRS) data to construct phased and near-complete genome assemblies (average contig N50 = 43 Mbp, QV = 56) for 189 individuals from 51 families with unsolved cases. We applied read- and assembly-based strategies to facilitate comprehensive characterization of de novo mutations, structural variants (SVs), and DNA methylation. Using LRS pangenome controls, we efficiently filtered >97% of common SVs exclusive to 87 offspring. We find no evidence of increased autosomal SV burden for probands when compared to unaffected siblings yet observe a suggestive trend toward an increased SV burden on the X chromosome among affected females. We establish a workflow to prioritize potential pathogenic variants by integrating autism risk genes and putative noncoding regulatory elements defined from ATAC-seq and CUT&Tag data from the developing cortex. In total, we identified three pathogenic variants in TBL1XR1, MECP2, and SYNGAP1, as well as nine candidate de novo and biallelic inherited homozygous SVs, most of which were missed by short-read sequencing. Our work highlights the potential of phased genomes to discover complex more pathogenic mutations and the power of the pangenome to restrict the focus on an increasingly smaller number of SVs for clinical evaluation.
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Data availability
The underlying sequencing data, as well as the processed assembly and alignment files used for analysis in this study for the SSC samples (n = 168) and the complete sample set (n = 189), are available to approved researchers through SFARI Base under Dataset ID DS0000104 and through the National Institute of Mental Health Data Archive (NDA) under Collection ID 3780. Source data are provided with this paper.
Code availability
The code used to perform the analyses and generate results in this study is publicly available and has been deposited in GitHub at https://github.com/EichlerLab/asap, under the MIT license. The specific version of the code associated with this publication is archived in Zenodo and is accessible via https://doi.org/10.5281/zenodo.1814964470. A full list of all software used, along with references, is provided in the Supplementary Notes and Supplementary References. Any additional information required to reanalyze the data reported in this work is available from the lead contact upon request.
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Acknowledgements
We thank all of the individuals who participated in this research. We also thank all contributing investigators to the consortia datasets used here from SSC, SAGE, and Baylor College of Medicine, and the families who participated in this research, without whose contributions, genetic studies would be impossible. We thank Tonia Brown for assistance in editing this manuscript. We thank Tom Mokveld (PacBio) for helpful discussions. This work was supported, in part, by the US National Institutes of Health (NIH R01MH101221 to E.E.E.; R01NS057819 to H.Y.Z.; 1F32HD116501-01 to R.M-S.; and DP5OD033357 to D.E.M.) and the Simons Foundation (SFARI #810018 to E.E.E., H.Y.Z., T.J.N., and A.C.). E.E.E. and H.Y.Z. are investigators of the Howard Hughes Medical Institute. This work was also supported, in part, by the National Natural Science Foundation of China (82201314 and 82471194) to T.W. We would like to acknowledge the National Genome Research Institute (NHGRI) for funding the following grants supporting the creation of the human pangenome reference: U41HG010972, U01HG010971, U01HG013760, U01HG013755, U01HG013748, U01HG013744, R01HG011274, and the Human Pangenome Reference Consortium (BioProject ID: PRJNA730823). This article is subject to HHMI’s Open Access to Publications policy. HHMI lab heads have previously granted a nonexclusive CC BY 4.0 license to the public and a sublicensable license to HHMI in their research articles. Pursuant to those licenses, the author-accepted manuscript of this article can be made freely available under a CC BY 4.0 license immediately upon publication.
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Y.S. and E.E.E. conceptualized the study. K. Ho., R.A.P.P., D.P., and B.S. collected samples. K.M.M., K. Ho., G.H.G., and J.K. generated the data. Y.S., Y.K., I.W., and N.K. performed data quality control. Y.S., J.L., M.D.N., I.W., and N.K. conducted the formal analyses. Y.S. and I.W. created the visualizations. Y.S., J.L., W.T.H., and M.W. developed the methodology. K. He., D.K., J.A.G., D.E.M., and the HPRC provided resources. Y.K., I.W., N.K., and J.W. developed software. Y.S., J.L., I.W., T.W., R.A.P.P., R.M.-S., and F.C. performed validation. Y.S. wrote the original draft. Y.S., E.E.E., H.Y.Z., J.L., M.D.N., Y.K., I.W., N.K., W.T.H., M.W., J.W., K. Ho., K.M.M., G.H.G., J.K., T.W., K. He., D.K., R.A.P.P., R.M.-S., F.C., D.P., B.S., J.A.G., D.E.M., T.J.N., A.C., H.B.-R. and the HPRC reviewed and edited the manuscript. E.E.E., H.Y.Z., A.C., and T.J.N. supervised the study.
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E.E.E. is a scientific advisory board (SAB) member of Variant Bio, Inc. D.E.M. is on SABs at Oxford Nanopore Technologies (ONT) and Basis Genetics, is engaged in research agreements with ONT and PacBio, has received research and travel support from ONT and PacBio, holds stock options in MyOme and Basis Genetics, and is a consultant for MyOme. J.A.G. has received travel support from ONT. H.Y.Z. is a member of the Regeneron Board of Directors and an advisory board member to The Column Group, Cajal Therapeutics (also co-founder), and Lyterian. D.P. provides consulting service to Ionis Pharmaceuticals, M2DS Therapeutics and Acadia Pharmaceuticals. All other authors declare no competing interests.
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Sui, Y., Lin, J., Noyes, M.D. et al. Using the linear references from the pangenome to discover missing autism variants. Nat Commun (2026). https://doi.org/10.1038/s41467-026-68378-4
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DOI: https://doi.org/10.1038/s41467-026-68378-4
