Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism
Open accessAbstract
Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases. Autism spectrum disorder (ASD) is a complex genetic trait that encompasses a range of neurodevelopmental disorders. Here, the authors clone brain-expressed alternatively-spliced isoforms of ASD risk factors and construct a network of protein interactions that provides further insight into the disease aetiology.
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Genes within ASD CNVs are highly connected with each other and with other ASD genes.
“Studies of large CNVs in ASD have shown that genes within ASD CNVs are highly connected with each other (Corominas et al., 2014) and with other ASD genes (Pinto et al., 2014).”
From Getting to the cores of autism (2019) · cites this paper as Corominas et al., 2014
The results suggest that misregulation of microexons, and of longer alternative exons, may affect protein interaction networks needed for normal neuronal development and synaptic function.
“the results suggest that the misregulation of microexons, as well as of longer alternative exons (Corominas et al., 2014; Voineagu et al., 2011), may impact protein interaction networks that are required for normal neuronal development and synaptic function”
From A Highly Conserved Program of Neuronal Microexons Is Misregulated in Autistic Brains (2014) · cites this paper as Corominas et al., 2014
This dominant transcript finding has direct consequences for differential isoform usage between CNS cell types and for progression of neurological disorders affecting protein-protein interactions, as exemplified in the Autism Spliceform Interaction Network.
“This has direct consequences for differential isoform usage between CNS cell types and for the progression of neurological disorders affecting protein-protein interactions, as exemplified in the Autism Spliceform Interaction Network72.”
From Decoding neuroproteomics: integrating the genome, translatome and functional anatomy (2014) · cites this paper as [72]
Recent studies have highlighted the importance of aberrant alternative splicing of mRNA in the brains of subjects with an ASD diagnosis.
“Recent studies have highlighted the importance of aberrant alternative splicing of mRNA in the brains of subjects with an ASD diagnosis (Corominas et al., 2014; Gandal et al., 2018; Irimia et al., 2014; Parikshak et al., 2016; Voineagu et al., 2011).”
From Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice (2019) · cites this paper as Corominas et al., 2014
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InfluentialSelf-citationCommon variants at VRK2 and TCF4 conferring risk of schizophrenia
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“Recently, de novo point mutations of TCF4 have been implicated in developmental delay 41–43 and autism 35 , and common variants of TCF4 were recurrently implicated in schizophrenia 44,45 .”
Design and application of a cytokine-receptor-based interaction trap
Eyckerman, S., Verhee, A., der Heyden, J. V., Lemmens, I. H., Ostade, X. V., Vandekerckhove, J. S., & Tavernier, J. H. (2001) · Nature Cell Biology · doi:10.1038/ncb1201-1114 · Cited by 209 · see citing works
Self-citationAutism genetics: searching for specificity and convergence
Berg, J. M., & Geschwind, D. H. (2012) · Genome Biology · doi:10.1186/gb-2012-13-7-247 · Cited by 192 · cited 3× · see citing works
“11 ; Fig.”
Rare structural variation of synapse and neurotransmission genes in autism
Gai, X., Xie, H. M., Perin, J. C., Takahashi, N., Murphy, K., Wenocur, A. S., D'arcy, M., O'Hara, R. J., Goldmuntz, E., Grice, D. E., et al. (2012) · Molecular Psychiatry · doi:10.1038/mp.2011.10 · Cited by 177 · see citing works
High-Quality Binary Interactome Mapping
Dreze, M., Monachello, D., Claire Lurin, A., Cusick, M. E., HILL, D. E., Vidal, M., & Falter‐Braun, P. (2010) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/s0076-6879(10)70012-4 · Cited by 148 · cited 1× · see citing works
“1 prey in the AD vector) following standard Y2H protocols 58 .”
Self-citationNetworks of Neuronal Genes Affected by Common and Rare Variants in Autism Spectrum Disorders
Ben-David, E., & Shifman, S. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002556 · Cited by 145 · cited 1× · see citing works
“The experimental and computational approaches including gene coexpression 12,13 , functional annotations 14,15 , mouse model phenotypes 16 and protein–protein interactions (PPIs) 3,17,18 were used to search for molecular processes and pathways shared by the ASD risk factors.”
Linking the SWI/SNF complex to prostate cancer
Lee, R. S., & Roberts, C. W. M. (2013) · Nature Genetics · doi:10.1038/ng.2805 · Cited by 138 · see citing works
The completion of the Mammalian Gene Collection (MGC)Preprint
The MGC Project Team, Temple, G. F., Gerhard, D. S., Rasooly, R. S., Feingold, E. A., Good, P. J., Robinson, C., Mandich, A., Derge, J. G., Lewis, J., et al. (2009) · Genome Research · doi:10.1101/gr.095976.109 · Cited by 134 · cited 1× · see citing works
“To assess isoform novelty, unique isoform sets were compared with ORF structures of mRNAs from several major databases including CCDS, RefSeq, UCSC, Gencode (Ensembl), MGC 56 and human ORFeome 57 .”
Self-citationRaychaudhuri, S., Korn, J. M., McCarroll, S. A., The International Schizophrenia Consortium, Altshuler, D., Sklar, P., Purcell, S., & Daly, M. J. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1001097 · Cited by 131 · cited 1× · see citing works
“66)) were compared using a method developed by Raychaudhuri et al. 67 .”
Autism genetics: searching for specificity and convergence
Berg, J. M., & Geschwind, D. H. (2012) · Genome biology · doi:10.1186/gb4034 · Cited by 87 · see citing works
Noh, H. J., Ponting, C. P., Boulding, H. C., Meader, S., Betancur, C., Buxbaum, J. D., Pinto, D., Marshall, C. R., Lionel, A. C., Scherer, S. W., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003523 · Cited by 54 · cited 1× · see citing works
“The experimental and computational approaches including gene coexpression 12,13 , functional annotations 14,15 , mouse model phenotypes 16 and protein–protein interactions (PPIs) 3,17,18 were used to search for molecular processes and pathways shared by the ASD risk factors.”
Isoform discovery by targeted cloning, 'deep-well' pooling and parallel sequencing
Salehi‐Ashtiani, K., Yang, X., Derti, A., Tian, W., Hao, T., Lin, C., Makowski, K. A., Shen, L., Murray, R. R., Szeto, D. P., et al. (2008) · Nature Methods · doi:10.1038/nmeth.1224 · Cited by 29 · cited 3× · see citing works
“…purified from the pooled foetal and adult whole brain samples (Methods) and applying a high-throughput isoform discovery pipeline and deep-well next-generation sequencing 26 , we successfully cloned 373 brain-expressed splicing isoforms corresponding to 124 autism candidate genes (Supplementary Fig.”
InfluentialSelf-citationDOMMINO: a database of macromolecular interactions
Kuang, X., Han, J. G., Zhao, N., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1128 · Cited by 27 · see citing works
Self-citationHamdan, F. F., Daoud, H., Patry, L., Dionne‐Laporte, A., Spiegelman, D., Dobrzeniecka, S., Rouleau, G. A., & Michaud, J. L. (2012) · Clinical Genetics · doi:10.1111/j.1399-0004.2012.01890.x · Cited by 20 · cited 1× · see citing works
“Recently, de novo point mutations of TCF4 have been implicated in developmental delay 41–43 and autism 35 , and common variants of TCF4 were recurrently implicated in schizophrenia 44,45 .”
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Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice
Sharon, G., Cruz, N. J., Kang, D.-W., Gandal, M. J., Wang, B., Kim, Y.-M., Zink, E. M., Casey, C. P., Taylor, B. C., Lane, C. J., et al. (2019) · Cell · doi:10.1016/j.cell.2019.05.004 · Cited by 1,182 · see citing works
“Recent studies have highlighted the importance of aberrant alternative splicing of mRNA in the brains of subjects with an ASD diagnosis (Corominas et al., 2014; Gandal et al., 2018; Irimia et al., 2014; Parikshak et al., 2016; Voineagu et al., 2011).”
Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder
C Yuen, R. K., Merico, D., Bookman, M., L Howe, J., Thiruvahindrapuram, B., Patel, R. V., Whitney, J., Deflaux, N., Bingham, J., Wang, Z., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4524 · Cited by 844 · see citing works
“3b ), isoforms of single genes 48 and their regulatory elements 27,49 , and they can include noncoding genes such as the known ASD-risk gene PTCHD1-AS ( Fig.”
Inferring the molecular and phenotypic impact of amino acid variants with MutPred2
Pejaver, V., Urresti, J., Lugo-Martinez, J., Pagel, K. A., Lin, G. N., Nam, H.-J., Mort, M., Cooper, D. N., Sebat, J., Iakoucheva, L. M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19669-x · Cited by 923 · see citing works
Self-citationThe BioGRID interaction database: 2015 update
Chatr‐aryamontri, A., Breitkreutz, B., Oughtred, R., Boucher, L., Heinicke, S., Chen, D., Stark, C., Breitkreutz, A., Kolas, N. K., O’Donnell, L., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1204 · Cited by 884 · see citing works
A Highly Conserved Program of Neuronal Microexons Is Misregulated in Autistic Brains
Irimia, M., Weatheritt, R. J., Ellis, J. D., Parikshak, N. N., Gonatopoulos-Pournatzis, T., Babor, M., Quesnel-Vallières, M., Tapial, J., Raj, B., O’Hanlon, D., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.035 · Cited by 693 · see citing works
“Taken together with data in Figures 5 and 6, the results suggest that themisregulation ofmicroexons, as well as of longer alternative exons (Corominas et al., 2014; Voineagu et al., 2011), may impact protein-interaction networks that are required for normal neuronal development and synaptic…”
ResultSelf-citationWidespread Expansion of Protein Interaction Capabilities by Alternative Splicing
Yang, X., Coulombe-Huntington, J., Kang, S., Sheynkman, G. M., Hao, T., Richardson, A., Sun, S., Yang, F., Shen, Y. A., Murray, R. R., et al. (2016) · Cell · doi:10.1016/j.cell.2016.01.029 · Cited by 583 · see citing works
“Although systematic functional studies of protein isoforms have been described for selected groups of genes (Corominas et al., 2014), most recorded functional annotations and protein interactions are at gene-level resolution.”
Self-citationDefining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders
Sullivan, P. F., & Geschwind, D. H. (2019) · Cell · doi:10.1016/j.cell.2019.01.015 · Cited by 452 · see citing works
“These efforts point at similar pathways and/or convergence of risk loci on similar biological processes (Corominas et al., 2014; Gilman et al., 2012; Li et al., 2014).”
BackgroundSystems biology and gene networks in neurodevelopmental and neurodegenerative disorders
Parikshak, N. N., Gandal, M. J., & Geschwind, D. H. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3934 · Cited by 430 · see citing works
“Another Y2H study assessed a larger seed set of ASD candidate genes that corresponded to spliced isoforms identified by whole-brain RNA-seq 125 , hypothesizing that isoform-level PPIs would allow for the discovery of tissue-specific PPI networks 126 .”
BackgroundInfluentialKrishnan, A., Zhang, R., Yao, V., Theesfeld, C. L., Wong, A. K., Tadych, A., Volfovsky, N., Packer, A. I., Lash, A., & Troyanskaya, O. G. (2016) · Nature Neuroscience · doi:10.1038/nn.4353 · Cited by 427 · see citing works
“We used these sets of genes—proband recurrent LGD (27), proband LGD (350) and sibling LGD (174)—to benchmark our genome-wide autism-associated gene ranking.”
MethodBabu, M. M. (2016) · Biochemical Society Transactions · doi:10.1042/bst20160172 · Cited by 408 · see citing works
Getting to the cores of autism
Iakoucheva, L. M., Muotri, A. R., & Sebat, J. (2019) · Cell · doi:10.1016/j.cell.2019.07.037 · Cited by 260 · see citing works
“Studies of large CNVs in ASD have shown that genes within ASD CNVs are highly connected with each other (Corominas et al., 2014) and with other ASD genes (Pinto et al.”
BackgroundSelf-citationThe discovery of integrated gene networks for autism and related disorders
Hormozdiari, F., Penn, O., Borenstein, E., & Eichler, E. E. (2015) · Genome Research · doi:10.1101/gr.178855.114 · Cited by 249 · see citing works
“a single splicing isoform (Corominas et al. 2014).”
BackgroundDefective control of pre–messenger RNA splicing in human disease
Chabot, B., & Shkreta, L. (2016) · The Journal of Cell Biology · doi:10.1083/jcb.201510032 · Cited by 209 · see citing works
“In the mouse brain, the depletion of RBF OX proteins alters the alternative splicing of transcripts implicated in ASD (Weyn-Vanhentenryck et al., 2014).”
BackgroundInfluentialLin, G. N., Corominas, R., Lemmens, I., Yang, X., Tavernier, J., Hill, D. E., Vidal, M., Sebat, J., & Iakoucheva, L. M. (2015) · Neuron · doi:10.1016/j.neuron.2015.01.010 · Cited by 155 · see citing works
“HIC was assembled to include the interactions from two datasets: the Human Interactome II-14 (HI-II-14) (Rolland et al., 2014) containing 14,000 novel physical binary interactions between 4,300 human proteins and the gene-level binary interactions from the Autism Spliceform Interaction Network (ASIN) (Corominas et al.…”
BackgroundMethodInfluentialSelf-citationAutism spectrum disorder: insights into convergent mechanisms from transcriptomics
Quesnel-Vallières, M., Weatheritt, R. J., Cordes, S. P., & Blencowe, B. J. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0066-2 · Cited by 160 · see citing works
Integrated systems analysis reveals a molecular network underlying autism spectrum disorders
Li, J., Shi, M., Ma, Z., Zhao, S., Euskirchen, G., Ziskin, J., Urban, A., Hallmayer, J., & Snyder, M. (2014) · Molecular Systems Biology · doi:10.15252/msb.20145487 · Cited by 132 · see citing works
“Related studies were focused on a set of proteins potentially implicated in ASD and characterized their inter-acting partners to identify molecular pathways underlying ASD (Sakai et al , 2011; Corominas et al , 2014; Cristino et al , 2014).”
The impact of age on genetic risk for common diseases
Jiang, X., Holmes, C. C., & McVean, G. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009723 · Cited by 108 · see citing works
“Discussion Genetic factors influence lifetime risk for common and complex diseases through modulating a large number of molecular, cellular and tissue phenotypes, many of which are also likely to be affected by acute exposure and persistent environment (Bønnelykke & Ober, 2016; Corominas et al., 2014; Stranger et al.,…”
BackgroundPooled‐matrix protein interaction screens using Barcode Fusion Genetics
Yachie, N., Petsalaki, E., Mellor, J. C., Weile, J., Jacob, Y., Verby, M., Ozturk, S. B., Li, S., Coté, A. G., Mosca, R., et al. (2016) · Molecular Systems Biology · doi:10.15252/msb.20156660 · Cited by 108 · see citing works
Self-citationGrauel, M., Maglione, M., Reddy-Alla, S., Willmes, C., Brockmann, M. M., Trimbuch, T., Rosenmund, T., Pangalos, M., Vardar, G., Stumpf, A., et al. (2016) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.1605256113 · Cited by 89 · see citing works
Network Medicine in Pathobiology
Lee, L. Y.-H., & Loscalzo, J. (2019) · The American Journal of Pathology · doi:10.1016/j.ajpath.2019.03.009 · Cited by 95 · see citing works
The emerging era of genomic data integration for analyzing splice isoform function
Li, H. D., Menon, R., Omenn, G. S., & Guan, Y. (2014) · Trends in Genetics · doi:10.1016/j.tig.2014.05.005 · Cited by 86 · see citing works
“These limitations have previously been addressed by small-scale investigations focusing on individual isoforms [20, 21, 66], but systematic, genome-scale predictive studies for isoform functions based on functional genomic data has been limited until recently [16, 67, 68].”
BackgroundMapping, modeling, and characterization of protein–protein interactions on a proteomic scale
Cafarelli, T. M., Desbuleux, A., Wang, Y., Choi, S. G., Ridder, D. D., & Vidal, M. (2017) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2017.05.003 · Cited by 72 · see citing works
Self-citationYoo, M. H., Kim, T.-Y., Yoon, Y. H., & Koh, J. (2016) · Scientific Reports · doi:10.1038/srep28548 · Cited by 70 · see citing works
Genetic heterogeneity in autism: From single gene to a pathway perspective
An, J., & Claudianos, C. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.06.013 · Cited by 64 · see citing works
Murtaza, N., Cheng, A. A., Brown, C. O., Meka, D. P., Hong, S., Uy, J. A., El-Hajjar, J., Pipko, N., Unda, B. K., Schwanke, B., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111678 · Cited by 67 · see citing works
Decoding neuroproteomics: integrating the genome, translatome and functional anatomy
Kitchen, R. R., Rozowsky, J. S., Gerstein, M. B., & Nairn, A. C. (2014) · Nature Neuroscience · doi:10.1038/nn.3829 · Cited by 63 · see citing works
An autism-linked missense mutation in SHANK3 reveals the modularity of Shank3 function
Wang, L., Pang, K., Han, K., Adamski, C. J., Wang, W., He, L.-J., Lai, J. K. H., Bondar, V. V., Duman, J. G., Richman, R., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-018-0324-x · Cited by 65 · see citing works
“(ConsensusPathDB, GeneMANIA, HIPPIE, InWeb, mentha, OPHID, Pathway Commons, STRING and UniHI) and two publications [34, 41].”
Identification of protein features encoded by alternative exons using Exon OntologyPreprint
Tranchevent, L.-C., Aubé, F., Dulaurier, L., Benoit‐Pilven, C., Rey, A., Poret, A., Chautard, É., Mortada, H., Desmet, F.-O., Chakrama, F. Z., et al. (2017) · Genome Research · doi:10.1101/gr.212696.116 · Cited by 64 · see citing works
De novo Mutations (DNMs) in Autism Spectrum Disorder (ASD): Pathway and Network Analysis
Alonso-González, A., Rodriguez‐Fontenla, C., & Carracedo, Á. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00406 · Cited by 65 · see citing works
“Moreover, this approach allows gene sub-networks to be redefined whose involvement in ASD has previously been reported (Corominas et al., 2014).”
BackgroundUncovering the impacts of alternative splicing on the proteome with current omics techniques
Reixachs‐Solé, M., & Eyras, E. (2022) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1707 · Cited by 61 · see citing works
“In addition, yeast-two-hybrid experiments revealed how to splice variants expand the network of interactions in the autism spectrum disorders (Corominas et al., 2014).”
BackgroundAdvances in Analyzing Virus-Induced Alterations of Host Cell Splicing
Ashraf, U., Benoit‐Pilven, C., Lacroix, V., Navratil, V., & Naffakh, N. (2018) · Trends in Microbiology · doi:10.1016/j.tim.2018.11.004 · Cited by 62 · see citing works
Kandoth, P. K., Liu, S., Prenger, E. M., Ludwig, A., Lakhssassi, N., Heinz, R. D., Zhou, Z., Howland, A. D., Gunther, J., Eidson, S., et al. (2017) · PLANT PHYSIOLOGY · doi:10.1104/pp.17.00553 · Cited by 57 · see citing works
Self-citationLi, J., Ma, Z., Shi, M., Malty, R. H., Aoki, H., Minić, Z., Phanse, S., Jin, K., Wall, D. P., Zhang, Z., et al. (2015) · Cell Systems · doi:10.1016/j.cels.2015.11.002 · Cited by 48 · see citing works
“For example, the most recent Y2H screen identified five proteins interacting with FMRP(Corominas et al., 2014), whereas an earlier Y2H screen identified 22 with FMRP(Sakai et al.”
BackgroundMethodResultInfluentialYudin, N. S., Larkin, D. M., & Ignatieva, E. V. (2017) · BMC Genetics · doi:10.1186/s12863-017-0580-9 · Cited by 45 · see citing works
“Some genes from its FAM family were associated with osteosarcoma in humans [65] and some were a part of the Autism Spliceform Interaction Network [66].”
Chau, K. K., Zhang, P., Urresti, J., Amar, M., Pramod, A. B., Chen, J., Thomas, A. E., Corominas, R., Lin, G. N., & Iakoucheva, L. M. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109631 · Cited by 42 · see citing works
“In addition, our recent work demonstrated that isoform-level networks of autism risk genes and copy number variants provide better resolution and depth around disease proteins (Corominas et al., 2014).”
Self-citationMiR-980 Is a Memory Suppressor MicroRNA that Regulates the Autism-Susceptibility Gene A2bp1
Guven-Ozkan, T., Busto, G. U., Schutte, S. S., Cervantes-Sandoval, I., O’Dowd, D. K., & Davis, R. L. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.01.040 · Cited by 43 · see citing works
Kikuchi, M., Sekiya, M., Hara, N., Miyashita, A., Kuwano, R., Ikeuchi, T., Iijima, K., & Nakaya, A. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddz320 · Cited by 44 · see citing works
“PINs have diverse structures among different tissues and cell types and between normal and disease states (15,16).”
BackgroundAltered social behavior in mice carrying a corticalFoxp2deletion
Medvedeva, V. P., Rieger, M. A., Vieth, B., Mombereau, C., Ziegenhain, C., Ghosh, T., Cressant, A., Enard, W., Granon, S., Dougherty, J. D., et al. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy372 · Cited by 40 · see citing works
Kahraman, A., Karakulak, T., Szklarczyk, D., & von Mering, C. (2020) · Scientific Reports · doi:10.1038/s41598-020-71221-5 · Cited by 40 · see citing works
The Many Faces of Microbiota-Gut-Brain Axis in Autism Spectrum Disorder
Gonçalves, C. L., Doifode, T., Rezende, V. L., Costa, M. A., Rhoads, J. M., & Soutullo, C. A. (2024) · Life Sciences · doi:10.1016/j.lfs.2023.122357 · Cited by 42 · see citing works
Laukens, K., Naulaerts, S., & Berghe, W. V. (2014) · PROTEOMICS · doi:10.1002/pmic.201400296 · Cited by 38 · see citing works
“In interactomics this property may be an observed interaction with a bait protein [27–29].”
BackgroundMORC4 Promotes Chemoresistance of Luminal A/B Breast Cancer via STAT3-Mediated MID2 Upregulation
Luo, J., Zeng, S., & Tian, C. (2020) · OncoTargets and Therapy · doi:10.2147/ott.s260509 · Cited by 38 · see citing works
Parkin and mitochondrial signalling
Connelly, E. M., Frankel, K. S., & Shaw, G. S. (2023) · Cellular Signalling · doi:10.1016/j.cellsig.2023.110631 · Cited by 37 · see citing works
Precision medicine — networks to the rescue
Yadav, A., Vidal, M., & Luck, K. (2020) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2020.02.005 · Cited by 36 · see citing works
“For example, network data were employed to study the genes and biological processes that are likely affected by inherited and de novo variants from individuals diagnosed with Autism Spectrum Disorder (ASD) [44].”
BackgroundSelf-citationFan, C.-X., Gao, Y., Liang, G., Huang, L., Wang, J., Yang, X., Shi, Y., Dräger, U. C., Zhong, M., Gao, T., et al. (2020) · Molecular Autism · doi:10.1186/s13229-020-0318-9 · Cited by 35 · see citing works
“Together with our collaborators, we searched for common molecular mechanism by constructing a protein-protein interaction network for autism from 191 autism candidate genes by screening the whole human orfeome in 2014 [23].”
MethodSelf-citationIdentification of the BRD1 interaction network and its impact on mental disorder risk
Fryland, T., Christensen, J., Pallesen, J., Mattheisen, M., Palmfeldt, J., Bak, M., Grove, J., Demontis, D., Blechingberg, J., Ooi, H., et al. (2016) · Genome Medicine · doi:10.1186/s13073-016-0308-x · Cited by 35 · see citing works
“Our results support a recently published large-scale study of autism risk genes which demonstrates the importance of considering splice isoforms when exploring disease networks [74].”
ResultThe Pleiotropic MET Receptor Network: Circuit Development and the Neural-Medical Interface of Autism
Eagleson, K., Xie, Z., & Levitt, P. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.08.035 · Cited by 31 · see citing works
Wilkinson, B., Evgrafov, O. V., Zheng, D., Hartel, N. G., Knowles, J. A., Graham, N. A., Ichida, J. K., & Coba, M. P. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.05.009 · Cited by 33 · see citing works
FDR-Corrected Sparse Canonical Correlation Analysis With Applications to Imaging Genomics
Gossmann, A., Zillé, P., Calhoun, V. D., & Wang, Y. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2018.2815583 · Cited by 34 · see citing works
“FHIT Cognitive ability: [47]; autism spectrum disorders: [48], [49]; attention deficit hyperactivity disorder: [50].”
BackgroundThe variation game: Cracking complex genetic disorders with NGS and omics data
Cui, H., Dhroso, A., Johnson, N. T., & Korkin, D. (2015) · Methods · doi:10.1016/j.ymeth.2015.04.018 · Cited by 34 · see citing works
Self-citationFirouzabadi, S. G., Kariminejad, R., Vameghi, R., Darvish, H., Ghaedi, H., Banihashemi, S., Moghadam, M. F., Jamali, P., Tehrani, H. F. M., Dehghani, H., et al. (2016) · Molecular Neurobiology · doi:10.1007/s12035-016-0202-y · Cited by 34 · see citing works
ASpedia: a comprehensive encyclopedia of human alternative splicing
Hyung, D., Kim, J., Cho, S. Y., & Park, C. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1014 · Cited by 33 · see citing works
“An isoform-specific protein interaction database was integrated from genome-wide yeast two-hybrids and the protein interaction database iRefIndex (14,31,32).”
MethodKurusu, R., Fujimoto, Y., Morishita, H., Noshiro, D., Takada, S., Yamano, K., Tanaka, H., Arai, R., Kageyama, S., Funakoshi, T., et al. (2023) · Developmental Cell · doi:10.1016/j.devcel.2023.04.015 · Cited by 32 · see citing works
Proteome-scale Binary Interactomics in Human Cells
Lievens, S., der Heyden, J. V., Masschaele, D., Ceuninck, L. D., Πέττα, Ι., Gupta, S., Puysseleyr, V. D., Vauthier, V., Lemmens, I., Clercq, D. J. H. D., et al. (2016) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m116.061994 · Cited by 30 · see citing works
Self-citationNahas, L. D., Datta, A., Alsamman, A. M., Adly, M. H., Al-Dewik, N. I. E., Sekaran, K., Sasikumar, K., Verma, K., Doss, C. G. P., & Zayed, H. (2023) · Metabolic Brain Disease · doi:10.1007/s11011-023-01322-3 · Cited by 30 · see citing works
Hartwig, C. L., Monis, W. J., Chen, X., Dickman, D. K., Pazour, G. J., & Faúndez, V. (2017) · Developmental Neurobiology · doi:10.1002/dneu.22542 · Cited by 29 · see citing works
Lu, R., Mucaki, E. J., & Rogan, P. K. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1036 · Cited by 29 · see citing works
“The derived iPWMs confirmed genome-wide interactions between 22 cofactors and 102 primary TFs (Table 1), which were supported by the previous studies (3, 5, 6, 15, 27-93) .”
MethodMurtaza, N., Uy, J. A., & Singh, K. K. (2020) · Molecular Autism · doi:10.1186/s13229-020-00334-5 · Cited by 29 · see citing works
“later used Y2H on 422 splicing isoforms from 168 autism candidate genes and identified 506 protein-protein interactions between 71 bait and 291 prey proteins [59].”
MethodThe coming era of proteomics-driven precision medicine
Jiang, Y., Wang, J., Sun, A., Zhang, H., Yu, X.-B., Qin, W., Ying, W.-T., Li, Y., Chang, C., Wang, X., et al. (2025) · National Science Review · doi:10.1093/nsr/nwaf278 · Cited by 27 · see citing works
“By comparing mutated and normal protein assemblies, new candidate disease interactions can be inferred, such as in the case of cancer [59 ,60 ] and autism [61 ].”
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“Moreover, recent interactome mapping studies also implicated Zeb2 as a probable genetic risk factor of autism [46], a developmental brain disorder which shares symptoms with ADHD including inattentiveness [47].”
BackgroundFunctional characterization of rare FOXP2 variants in neurodevelopmental disorder
Estruch, S. B., Graham, S. A., Chinnappa, S. M., Deriziotis, P., & Fisher, S. E. (2016) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-016-9177-2 · Cited by 27 · see citing works
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A reference map of the human protein interactomePreprint
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“Furthermore, MID2 is a novel protein-interacting partner for breast cancer 1, early-onset (BRCA1), a nuclear phosphoprotein that functions as a major tumor suppressor in breast cancer [33].”
BackgroundLiao, C., Moysés‐Oliveira, M., de Esch, C. E., Bhavsar, R., Nuttle, X., Li, A., Yu, A., Burt, N. D., Erdin, S., Fu, J. M., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100277 · Cited by 24 · see citing works
Jinawath, N., Bunbanjerdsuk, S., Chayanupatkul, M., Ngamphaiboon, N., Asavapanumas, N., Svasti, J., & Charoensawan, V. (2016) · Journal of Translational Medicine · doi:10.1186/s12967-016-1078-3 · Cited by 24 · see citing works
“In these cases, mutations in multiple relevant genes lead to abnormal protein interactions, and disrupt networks (see [29, 30, 36, 37] for details).”
BackgroundZhang-James, Y., Vaudel, M., Mjaavatten, O., Berven, F., Haavik, J., & Faraone, S. (2019) · ADHD Attention Deficit and Hyperactivity Disorders · doi:10.1007/s12402-018-0281-x · Cited by 16 · see citing works
PANDA: Prioritization of autism‐genes using network‐based deep‐learning approach
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“…we fi nd similar trends to alternative exons and Poly(A) sites demonstrating that cortex contains more signi fi cant isoform alternative usage than WM across age (Cortex: 25.32%, 95%-con- fi dence intervals [13.40, 37.24]; WM: 2.78%, 95%-con fi dence intervals [1.70, 3.85]; Supplementary Fig.”
InfluentialSelf-citationTissue differences revealed by gene expression profiles of various cell lines
Chen, L., Pan, X., Zhang, Y., Kong, X., Huang, T., & Cai, Y. (2018) · Journal of Cellular Biochemistry · doi:10.1002/jcb.27977 · Cited by 22 · see citing works
“42 This gene may distinguish brain tissues from other tissue subtypes, thereby validating the efficacy and accuracy of our prediction.”
BackgroundApplying the new genomics to alcohol dependence
Farris, S. P., Pietrzykowski, A. Z., Miles, M. F., O'Brien, M. A., Sanna, P. P., Zakhari, S., Mayfield, R. D., & Harris, R. A. (2015) · Alcohol · doi:10.1016/j.alcohol.2015.03.001 · Cited by 19 · see citing works
“However, constructing human brain spliceform networks may be critical for interpreting aberrant biology in human diseases (Corominas et al., 2014).”
BackgroundA Network of Splice Isoforms for the Mouse
Li, H.-D., Menon, R., Eksi, R., et al. (2016) · Scientific Reports · doi:10.1038/srep24507 · Cited by 20 · see citing works
Discovering heritable modes of MEG spectral power
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“, 2012), and fragile histidine triad (Corominas et al., 2014).”
Wang, J., Gao, Y., Xiao, L., Lin, Y., Huang, L., Chen, J., Liang, G., Li, W., Yi, W., Lao, J., et al. (2023) · iScience · doi:10.1016/j.isci.2023.107476 · Cited by 15 · see citing works
“GABRA4 and GABRB1 are associated with autism.(13,38) The expression level of GABRB1 is down-regulated in autistic brains.”
BackgroundSelf-citationLi, C., Pu, B., Gu, L., Zhang, M., Shen, H., Yuan, Y., & Liao, L. (2021) · FEBS Open Bio · doi:10.1002/2211-5463.13078 · Cited by 15 · see citing works
Proteins with amino acid repeats constitute a rapidly evolvable and human-specific essentialome
Singh, A. K., Amar, I., Ramadasan, H., Kappagantula, K. S., & Chavali, S. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112811 · Cited by 14 · see citing works
iTRAQ-Based Proteomics Analysis of Rat Cerebral Cortex Exposed to Valproic Acid before Delivery
Jing, L., Zhang, K., Cao, X., Zhao, Y., Khan, N. U., Liu, X., Tang, X., Chen, M., Zhang, H., & Shen, L. (2022) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.1c00800 · Cited by 14 · see citing works
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“Evidence suggests that although ASD genes are 50 functionally diverse they are connected through protein interaction networks [12] and 51”
BackgroundTranslating molecular advances in Down syndrome and Fragile X syndrome into therapies
Faúndez, V., Toma, I. D., Bardoni, B., Bartesaghi, R., Nižetić, D., de la Torre, R., Kadosh, R. C., Hérault, Y., Dierssen, M., Potier, M., et al. (2018) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2018.03.006 · Cited by 13 · see citing works
“The interactome was obtained from six published proteome-wide interactomes datasets (Shannon et al. , 2003; Camargo et al. , 2007; Warde-Farley et al. , 2010; Wang et al. , 2011; Havugimana et al. , 2012; Corominas et al. , 2014; Huttlin et al. , 2015; Wan et al. , 2015).”
Gao, K., Zhang, Y., Zhang, L., Kong, W., Xie, H., Wang, J., Wu, Y., Wu, X., Liu, X., Zhang, Y., et al. (2018) · Advances in neurobiology · doi:10.1007/978-3-319-94593-4_9 · Cited by 13 · see citing works
ST-Steiner: a spatio-temporal gene discovery algorithm
Norman, U., & Çiçek, A. E. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz110 · Cited by 14 · see citing works
The Consequences of Abnormal Gene Dosage: Lessons from Chromosome 18
Cody, J. D. (2020) · Trends in Genetics · doi:10.1016/j.tig.2020.06.006 · Cited by 12 · see citing works
DMIL-III: Isoform-isoform interaction prediction using deep multi-instance learning method
Zeng, J., Yu, G.-X., Wang, J., Guo, M.-Z., & Zhang, X.-L. (2019) · IEEE International Conference on Bioinformatics and Biomedicine · doi:10.1109/bibm47256.2019.8982956 · Cited by 13 · see citing works
Narykov, O., Johnson, N. T., & Korkin, D. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.110045 · Cited by 11 · see citing works
Self-citationGnanasekaran, H., Chandrasekar, S. P., Kandeeban, S., et al. (2023) · Clinical Genetics · doi:10.1111/cge.14398 · Cited by 11 · see citing works
“Physical interaction of TSPOAP1 with ciliary genes DISC1, CEP76, and NDE1 has been previously demonstrated.(34) Interestingly, DISC1 gene has been shown to interact with BBS4(37) and also forms a complex with Pericentriolar material protein 1 (PCM1) that is involved in cortical development.”
BackgroundAshitha, S. N. M., & Ramachandra, N. B. (2020) · Neuroscience · doi:10.1016/j.neuroscience.2020.04.051 · Cited by 10 · see citing works
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Self-citationIdentifying and characterising key alternative splicing events in Drosophila development
Lees, J. G., Ranea, J. A. G., & Orengo, C. A. (2015) · BMC Genomics · doi:10.1186/s12864-015-1674-2 · Cited by 10 · see citing works
“Furthermore, specific transcript isoforms are thought to be important for gene regulation (e.g. [4 ]) with roles in human diseases such as cancer [5] and autism [6].”
BackgroundFirouzabadi, S. G., Vameghi, R., Kariminejad, R., Darvish, H., Banihashemi, S., Moghadam, M. F., Jamali, P., Tehrani, H. F. M., Dehghani, H., Raeisoon, M. R., et al. (2016) · PubMed Central · Cited by 10 · see citing works
Integration and Weighing of Omics Data for Obesity
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“Volume 7 • Issue 7 • 1000690 J Diabetes Metab ISSN: 2155-6156 JDM, an open access journal network of alternatively spliced isoforms from brain connects genetic risk factors for autism or neurodegenerative disorders [83].”
BackgroundWill, T., & Helms, V. (2017) · BMC Systems Biology · doi:10.1186/s12918-017-0400-x · Cited by 9 · see citing works
“The contribution of AS, however, certainly depends on the developmental system under study and is likely to be higher in the human brain [78, 79], for example.”
BackgroundShen, J., Lincoln, S. A., & Miller, D. T. (2014) · Current Genetic Medicine Reports · doi:10.1007/s40142-014-0047-5 · Cited by 8 · see citing works
“New evidence suggests that alternatively spliced isoforms from brain contributes to 30 % of unknown protein–protein interactions [68].”
Alternative splicing in autism spectrum disorder: Recent insights from mechanisms to therapy
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The Unique Evolutionary Signature of Genes Associated with Autism Spectrum Disorder
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“…through a large number of rare susceptibility alleles (Krumm et al. 2015) and/or through genetic variations that exert deleterious effect only under certain genetic or environmental backgrounds (i.e., GxG or GxE interactions) (Tordjman et al. 2014; Chaste and Leboyer 2012; Corominas et al. 2014).”
BackgroundLinear motif specificity in signaling through p38α and ERK2 mitogen–activated protein kinases
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Vellingiri, B., Bharathi, G., Jayaramayya, K., Venugopal, A., Iyer, M., Narayanasamy, A., Bharathi, A., Gopalakrishnan, A. V., Kumar, N. S., & Subramaniam, M. D. (2021) · Brain Disorders · doi:10.1016/j.dscb.2021.100024 · Cited by 8 · see citing works
Beyond the gene: decoding alternative isoforms
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Network Biology and Medicine to Rescue: Applications for Retinal Disease Mechanisms and Therapy
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- Authors
- Corominas, R., Yang, X., Lin, G. N., Kang, S., Shen, Y., Ghamsari, L., Broly, M., Rodriguez, M., Tam, S., Wanamaker, S. A., Fan, C., Yi, S., Tasan, M., Lemmens, I., Kuang, X., Zhao, N., Malhotra, D., Michaelson, J. J., Vacic, V., Calderwood, M. A., Roth, F. P., Tavernier, J., Horvath, S., Salehi-Ashtiani, K., Korkin, D., Sebat, J., Hill, D. E., Hao, T., Vidal, M., & Iakoucheva, L. M.
- Affiliations
- University of California San Diego (US)
- Harvard University (US)
- Salk Institute for Biological Studies (US)
- Mount Sinai Hospital (CA)
- Ghent University (BE)
- University of Missouri (US)
- University of Iowa (US)
- New York Genome Center (US)
- University of California, Los Angeles (US)
- Corresponding author
- Hao, Tong
- Vidal, Marc
- Iakoucheva, Lilia M.
- ORCID
- Corominas, Roser
- Yang, Xinping
- Lin, Guan Ning
- Ghamsari, Lila
- Broly, Martin
- Tam, Stanley
- Wanamaker, Shelly A.
- Yi, Song
- Lemmens, Irma
- Zhao, Nan
- Malhotra, Dheeraj
- Michaelson, Jacob J.
- Vacic, Vladimir
- Calderwood, Michael A.
- Roth, Frederick P.
- Tavernier, Jan
- Horvath, Steve
- Korkin, Dmitry
- Sebat, Jonathan
- Hill, David E.
- Hao, Tong
- Vidal, Marc
- Iakoucheva, Lilia M.
- Venue
- Nature Communications
- Published
- 2014-04-11
- Volume
- 5
- Issue
- 1
- Pages
- 3650-3650
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC3996537
- OpenAlex
- W2138397090
- Semantic Scholar
- b1fa66a767c08e5e05402b9a1980794edaf84d6a
- Cited by
- 140
- References
- 73
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 1 · 2023: 18 · 2022: 7 · 2021: 9 · 2020: 16 · 2019: 14 · 2018: 12 · 2017: 11 · 2016: 26 · 2015: 10 · 2014: 8
- FWCI
- 10.22
- Type
- journal article
- Language
- en
- Update notices
- correction (2023-02-02)
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature Communications (publishedVersion, cc-by-nc-sa)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion, public-domain)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona) (submittedVersion, public-domain)
- Funders
- National Science Foundation (0845196, 1126992)
- Simons Foundation (275724)
- Dana-Farber Cancer Institute
- Simons Foundation Autism Research Initiative
- Fonds De La Recherche Scientifique - FNRS
- Canada Excellence Research Chairs, Government of Canada
- Fonds Wetenschappelijk Onderzoek
- Vlaamse regering
- National Institutes of Health
- National Institute of Mental Health (R01MH091350, MH076431, R01MH076431)
- National Human Genome Research Institute (U01HG001715, R01HG001715, P50HG004233)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD065288, ARRA R01HD065288)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- autism spectrum disorder, protein-protein interaction network, alternative splicing, splicing isoforms, autism risk genes, de novo copy number variants, interactome mapping, genetic susceptibility loci, etiology
- MeSH terms
- Autistic Disorder, Humans, Molecular Sequence Data, Risk Factors, Alternative Splicing, Genetic Predisposition to Disease, Protein Isoforms, Protein Interaction Maps
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