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Chang S, Liu JJ, Zhao Y, Pang T, Zheng X, Song Z, Zhang A, Gao X, Luo L, Guo Y, Liu J, Yang L, Lu L. Whole-genome sequencing identifies novel genes for autism in Chinese trios. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-023-2564-8. [PMID: 39126614 DOI: 10.1007/s11427-023-2564-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 03/16/2024] [Indexed: 08/12/2024]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high genetic heritability but heterogeneity. Fully understanding its genetics requires whole-genome sequencing (WGS), but the ASD studies utilizing WGS data in Chinese population are limited. In this study, we present a WGS study for 334 individuals, including 112 ASD patients and their non-ASD parents. We identified 146 de novo variants in coding regions in 85 cases and 60 inherited variants in coding regions. By integrating these variants with an association model, we identified 33 potential risk genes (P<0.001) enriched in neuron and regulation related biological process. Besides the well-known ASD genes (SCN2A, NF1, SHANK3, CHD8 etc.), several high confidence genes were highlighted by a series of functional analyses, including CTNND1, DGKZ, LRP1, DDN, ZNF483, NR4A2, SMAD6, INTS1, and MRPL12, with more supported evidence from GO enrichment, expression and network analysis. We also integrated RNA-seq data to analyze the effect of the variants on the gene expression and found 12 genes in the individuals with the related variants had relatively biased expression. We further presented the clinical phenotypes of the proband carrying the risk genes in both our samples and Caucasian samples to show the effect of the risk genes on phenotype. Regarding variants in non-coding regions, a total of 74 de novo variants and 30 inherited variants were predicted as pathogenic with high confidence, which were mapped to specific genes or regulatory features. The number of de novo variants found in patient was significantly associated with the parents' ages at the birth of the child, and gender with trend. We also identified small de novo structural variants in ASD trios. The results in this study provided important evidence for understanding the genetic mechanism of ASD.
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Affiliation(s)
- Suhua Chang
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China
- Chinese Academy of Medical Sciences Research Unit (No.2018RU006), Peking University, Beijing, 100191, China
| | - Jia Jia Liu
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China
- School of Nursing, Peking University, Beijing, 100191, China
| | - Yilu Zhao
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China
| | - Tao Pang
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China
| | - Xiangyu Zheng
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China
| | | | - Anyi Zhang
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China
| | - Xuping Gao
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China
| | - Lingxue Luo
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China
| | - Yanqing Guo
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China.
| | - Jing Liu
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China.
| | - Li Yang
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China.
| | - Lin Lu
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Beijing, 100191, China.
- Chinese Academy of Medical Sciences Research Unit (No.2018RU006), Peking University, Beijing, 100191, China.
- National Institute on Drug Dependence, Peking University, Beijing, 100191, China.
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Zambo B, Gogl G, Morlet B, Eberling P, Negroni L, Moine H, Travé G. Comparative analysis of PDZ-binding motifs in the diacylglycerol kinase family. FEBS J 2024; 291:690-704. [PMID: 37942667 DOI: 10.1111/febs.16994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/26/2023] [Accepted: 10/31/2023] [Indexed: 11/10/2023]
Abstract
Diacylglycerol kinases (DGKs) control local and temporal amounts of diacylglycerol (DAG) and phosphatidic acid (PA) by converting DAG to PA through phosphorylation in cells. Certain DGK enzymes possess C-terminal sequences that encode potential PDZ-binding motifs (PBMs), which could be involved in their recruitment into supramolecular signaling complexes. In this study, we used two different interactomic approaches, quantitative native holdup (nHU) and qualitative affinity purification (AP), both coupled to mass spectrometry (MS) to investigate the PDZ partners associated with the potential PBMs of DGKs. Complementing these results with site-specific affinity interactomic data measured on isolated PDZ domain fragments and PBM motifs, as well as evolutionary conservation analysis of the PBMs of DGKs, we explored functional differences within different DGK groups. All our results indicate that putative PBM sequences of type II enzymes, namely DGKδ, DGKη, and DGKκ, are likely to be nonfunctional. In contrast, type IV enzymes, namely DGKζ and DGKι, possess highly promiscuous PBMs that interact with a set of PDZ proteins with very similar affinity interactomes. The combination of various interactomic assays and evolutionary analyses provides a useful strategy for identifying functional domains and motifs within diverse enzyme families.
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Affiliation(s)
- Boglarka Zambo
- Équipe Labellisée Ligue contre le cancer, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U1258/CNRS UMR 7104/Université de Strasbourg, Illkirch, France
| | - Gergo Gogl
- Équipe Labellisée Ligue contre le cancer, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U1258/CNRS UMR 7104/Université de Strasbourg, Illkirch, France
| | - Bastien Morlet
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U1258/CNRS UMR 7104/Université de Strasbourg, Illkirch, France
| | - Pascal Eberling
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U1258/CNRS UMR 7104/Université de Strasbourg, Illkirch, France
| | - Luc Negroni
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U1258/CNRS UMR 7104/Université de Strasbourg, Illkirch, France
| | - Hervé Moine
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U1258/CNRS UMR 7104/Université de Strasbourg, Illkirch, France
| | - Gilles Travé
- Équipe Labellisée Ligue contre le cancer, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U1258/CNRS UMR 7104/Université de Strasbourg, Illkirch, France
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Kim IB, Lee T, Lee J, Kim J, Lee S, Koh IG, Kim JH, An JY, Lee H, Kim WK, Ju YS, Cho Y, Yu SJ, Kim SA, Oh M, Han DW, Kim E, Choi JK, Yoo HJ, Lee JH. Non-coding de novo mutations in chromatin interactions are implicated in autism spectrum disorder. Mol Psychiatry 2022; 27:4680-4694. [PMID: 35840799 DOI: 10.1038/s41380-022-01697-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 06/27/2022] [Accepted: 07/01/2022] [Indexed: 12/14/2022]
Abstract
Three-dimensional chromatin interactions regulate gene expressions. The significance of de novo mutations (DNMs) in chromatin interactions remains poorly understood for autism spectrum disorder (ASD). We generated 813 whole-genome sequences from 242 Korean simplex families to detect DNMs, and identified target genes which were putatively affected by non-coding DNMs in chromatin interactions. Non-coding DNMs in chromatin interactions were significantly involved in transcriptional dysregulations related to ASD risk. Correspondingly, target genes showed spatiotemporal expressions relevant to ASD in developing brains and enrichment in biological pathways implicated in ASD, such as histone modification. Regarding clinical features of ASD, non-coding DNMs in chromatin interactions particularly contributed to low intelligence quotient levels in ASD probands. We further validated our findings using two replication cohorts, Simons Simplex Collection (SSC) and MSSNG, and showed the consistent enrichment of non-coding DNM-disrupted chromatin interactions in ASD probands. Generating human induced pluripotent stem cells in two ASD families, we were able to demonstrate that non-coding DNMs in chromatin interactions alter the expression of target genes at the stage of early neural development. Taken together, our findings indicate that non-coding DNMs in ASD probands lead to early neurodevelopmental disruption implicated in ASD risk via chromatin interactions.
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Affiliation(s)
- Il Bin Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.,Department of Psychiatry, Hanyang University Guri Hospital, Guri, 11923, Republic of Korea
| | - Taeyeop Lee
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.,Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.,Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, 05505, Republic of Korea
| | - Junehawk Lee
- Center for Supercomputing Applications, Division of National Supercomputing, Korea Institute of Science and Technology Information, Daejeon, 34141, Republic of Korea
| | - Jonghun Kim
- Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Suho Lee
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, 34141, Republic of Korea
| | - In Gyeong Koh
- Industry-University Cooperation Foundation, Hanyang University, Seoul, 04763, Republic of Korea
| | - Jae Hyun Kim
- Department of Integrated Biomedical and Life Science, Korea University, Seoul, 02841, Republic of Korea.,BK21FOUR R&E Center for Learning Health Systems, Korea University, Seoul, 02841, Republic of Korea.,School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, 02841, Republic of Korea
| | - Joon-Yong An
- Department of Integrated Biomedical and Life Science, Korea University, Seoul, 02841, Republic of Korea.,BK21FOUR R&E Center for Learning Health Systems, Korea University, Seoul, 02841, Republic of Korea.,School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, 02841, Republic of Korea
| | - Hyunseong Lee
- Department of Stem Cell Biology, School of Medicine, Konkuk University, Seoul, 05030, Republic of Korea
| | - Woo Kyeong Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Young Seok Ju
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Yongseong Cho
- Center for Supercomputing Applications, Division of National Supercomputing, Korea Institute of Science and Technology Information, Daejeon, 34141, Republic of Korea
| | - Seok Jong Yu
- Center for Supercomputing Applications, Division of National Supercomputing, Korea Institute of Science and Technology Information, Daejeon, 34141, Republic of Korea
| | - Soon Ae Kim
- Department of Pharmacology, Eulji University, Daejeon, 13135, Republic of Korea
| | - Miae Oh
- Department of Psychiatry, Kyung Hee University Hospital, Seoul, 02447, Republic of Korea
| | - Dong Wook Han
- School of Biotechnology and Health Sciences, Wuyi University, Jiangmen, 529020, China.,Organoid sciences, Ltd., Bundang-gu, Seongnam, 13488, Republic of Korea
| | - Eunjoon Kim
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, 34141, Republic of Korea. .,Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
| | - Jung Kyoon Choi
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
| | - Hee Jeong Yoo
- Department of Psychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, Republic of Korea. .,Department of Psychiatry, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
| | - Jeong Ho Lee
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea. .,Sovargen Co. Ltd., Daejeon, 34051, Republic of Korea.
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Genetic control of RNA splicing and its distinct role in complex trait variation. Nat Genet 2022; 54:1355-1363. [PMID: 35982161 PMCID: PMC9470536 DOI: 10.1038/s41588-022-01154-4] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 07/08/2022] [Indexed: 12/11/2022]
Abstract
Most genetic variants identified from genome-wide association studies (GWAS) in humans are noncoding, indicating their role in gene regulation. Previous studies have shown considerable links of GWAS signals to expression quantitative trait loci (eQTLs) but the links to other genetic regulatory mechanisms, such as splicing QTLs (sQTLs), are underexplored. Here, we introduce an sQTL mapping method, testing for heterogeneity between isoform-eQTLeffects (THISTLE), with improved power over competing methods. Applying THISTLE together with a complementary sQTL mapping strategy to brain transcriptomic (n = 2,865) and genotype data, we identified 12,794 genes with cis-sQTLs at P < 5 × 10−8, approximately 61% of which were distinct from eQTLs. Integrating the sQTL data into GWAS for 12 brain-related complex traits (including diseases), we identified 244 genes associated with the traits through cis-sQTLs, approximately 61% of which could not be discovered using the corresponding eQTL data. Our study demonstrates the distinct role of most sQTLs in the genetic regulation of transcription and complex trait variation. A powerful method for splicing quantitative trait loci (sQTL) mapping, THISTLE, is presented and applied to a collection of 2,865 brain samples. Integration with GWAS identifies 244 genes associated via cis-sQTLs, of which 61% were not identified using expression QTLs.
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Mezlini AM, Das S, Goldenberg A. Finding associations in a heterogeneous setting: statistical test for aberration enrichment. Genome Med 2021; 13:68. [PMID: 33892787 PMCID: PMC8066476 DOI: 10.1186/s13073-021-00864-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 03/09/2021] [Indexed: 12/16/2022] Open
Abstract
Most two-group statistical tests find broad patterns such as overall shifts in mean, median, or variance. These tests may not have enough power to detect effects in a small subset of samples, e.g., a drug that works well only on a few patients. We developed a novel statistical test targeting such effects relevant for clinical trials, biomarker discovery, feature selection, etc. We focused on finding meaningful associations in complex genetic diseases in gene expression, miRNA expression, and DNA methylation. Our test outperforms traditional statistical tests in simulated and experimental data and detects potentially disease-relevant genes with heterogeneous effects.
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Affiliation(s)
- Aziz M. Mezlini
- Harvard Medical School, Boston, USA
- Department of Neurology, Massachusetts General Hospital, Boston, USA
- Department of Computer Science, University of Toronto, Toronto, Canada
- Genetics and genome biology, Hospital for sick children, Toronto, Canada
- The Vector Institute, Toronto, Canada
- Evidation Health, Inc., San Mateo, CA USA
| | - Sudeshna Das
- Harvard Medical School, Boston, USA
- Department of Neurology, Massachusetts General Hospital, Boston, USA
| | - Anna Goldenberg
- Department of Computer Science, University of Toronto, Toronto, Canada
- Genetics and genome biology, Hospital for sick children, Toronto, Canada
- The Vector Institute, Toronto, Canada
- CIFAR, Toronto, Canada
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