Single-nuclei isoform RNA sequencing unlocks barcoded exon connectivity in frozen brain tissue
Open accessAbstract
Single-nuclei RNA sequencing characterizes cell types at the gene level. However, compared to single-cell approaches, many single-nuclei cDNAs are purely intronic, lack barcodes and hinder the study of isoforms. Here we present single-nuclei isoform RNA sequencing (SnISOr-Seq). Using microfluidics, PCR-based artifact removal, target enrichment and long-read sequencing, SnISOr-Seq increased barcoded, exon-spanning long reads 7.5-fold compared to naive long-read single-nuclei sequencing. We applied SnISOr-Seq to adult human frontal cortex and found that exons associated with autism exhibit coordinated and highly cell-type-specific inclusion. We found two distinct combination patterns: those distinguishing neural cell types, enriched in TSS-exon, exon-polyadenylation-site and non-adjacent exon pairs, and those with multiple configurations within one cell type, enriched in adjacent exon pairs. Finally, we observed that human-specific exons are almost as tightly coordinated as conserved exons, implying that coordination can be rapidly established during evolution. SnISOr-Seq enables cell-type-specific long-read isoform analysis in human brain and in any frozen or hard-to-dissociate sample.
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Emerging long-read sequencing approaches enable profiling cellular transcriptomes at isoform resolution.
“Emerging long-read sequencing approaches enable us to profile cellular transcriptomes at isoform resolution,8,31,32,33 thus providing new opportunities to model the relationships between isoforms using co-expression network analysis.”
From hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data (2023) · cites this paper as [33]
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Analyzing real-time PCR data by the comparative CT method
Schmittgen, T. D., & Livak, K. J. (2008) · Nature Protocols · doi:10.1038/nprot.2008.73 · Cited by 26,190 · see citing works
Comprehensive Integration of Single-Cell Data
Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019) · Cell · doi:10.1016/j.cell.2019.05.031 · Cited by 15,453 · see citing works
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855 · see citing works
Massively parallel digital transcriptional profiling of single cells
Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14049 · Cited by 7,353 · see citing works
Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110 · see citing works
Alternative isoform regulation in human tissue transcriptomes
Wang, E. T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S. F., Schroth, G. P., & Burge, C. B. (2008) · Nature · doi:10.1038/nature07509 · Cited by 5,181 · see citing works
Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes
Siepel, A., Bejerano, G., Pedersen, J. S., Hinrichs, A. S., Hou, M., Rosenbloom, K., Clawson, H., Spieth, J., Hillier, L. W., Richards, S., et al. (2005) · Genome Research · doi:10.1101/gr.3715005 · Cited by 4,408 · see citing works
La Manno, G., Soldatov, R., Zeisel, A., Braun, E., Hochgerner, H., Petukhov, V., Lidschreiber, K., Kastriti, M. E., Lönnerberg, P., Furlan, A., et al. (2018) · Nature · doi:10.1038/s41586-018-0414-6 · Cited by 4,118 · see citing works
Real-Time DNA Sequencing from Single Polymerase Molecules
Eid, J., Fehr, A., Gray, J., Luong, K., Lyle, J., Otto, G., Peluso, P., Rank, D., Baybayan, P., Bettman, B., et al. (2009) · Science · doi:10.1126/science.1162986 · Cited by 3,732 · see citing works
Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells
Klein, A. M., Mazutis, L., Akartuna, I., Tallapragada, N., Veres, A., Li, V., Peshkin, L., Weitz, D. A., & Kirschner, M. W. (2015) · Cell · doi:10.1016/j.cell.2015.04.044 · Cited by 3,356 · see citing works
Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
Zeisel, A., Muñoz-Manchado, A. B., Codeluppi, S., Lönnerberg, P., La Manno, G., Juréus, A., Marques, S., Munguba, H., He, L., Betsholtz, C., et al. (2015) · Science · doi:10.1126/science.aaa1934 · Cited by 3,124 · see citing works
Generalizing RNA velocity to transient cell states through dynamical modeling
Bergen, V., Lange, M., Peidli, S., Wolf, F. A., & Theis, F. J. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0591-3 · Cited by 2,951 · see citing works
Detection of nonneutral substitution rates on mammalian phylogenies
Pollard, K. S., Hubisz, M. J., Rosenbloom, K. R., & Siepel, A. (2010) · Genome Research · doi:10.1101/gr.097857.109 · Cited by 2,353 · see citing works
Zhang, Y., Sloan, S. A., Clarke, L. E., Caneda, C., Plaza, C. A., Blumenthal, P. D., Vogel, H., Steinberg, G. K., Edwards, M. S. B., Li, G., et al. (2016) · Neuron · doi:10.1016/j.neuron.2015.11.013 · Cited by 2,295 · see citing works
Self-citationMaximum Entropy Modeling of Short Sequence Motifs with Applications to RNA Splicing Signals
Yeo, G. W.-M., & Burge, C. B. (2004) · Journal of Computational Biology · doi:10.1089/1066527041410418 · Cited by 2,042 · see citing works
Conserved cell types with divergent features in human versus mouse cortex
Hodge, R. D., Bakken, T. E., Miller, J. A., Smith, K. A., Barkan, E. R., Graybuck, L. T., Close, J. L., Long, B., Johansen, N., Penn, O., et al. (2019) · Nature · doi:10.1038/s41586-019-1506-7 · Cited by 1,775 · see citing works
Shared and distinct transcriptomic cell types across neocortical areas
Tasic, B., Yao, Z., Graybuck, L. T., Smith, K. A., Nguyen, T. N., Bertagnolli, D., Goldy, J., Garren, E., Economo, M. N., Viswanathan, S., et al. (2018) · Nature · doi:10.1038/s41586-018-0654-5 · Cited by 1,746 · see citing works
Massively parallel single-nucleus RNA-seq with DroNc-seq
Habib, N., Avraham-Davidi, I., Basu, A., Burks, T., Shekhar, K., Hofree, M., Choudhury, S. R., Aguet, F., Gelfand, E., Ardlie, K., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4407 · Cited by 1,069 · see citing works
A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation
Yao, Z., van Velthoven, C. T. J., Nguyen, T. N., Goldy, J., Sedeno-Cortes, A. E., Baftizadeh, F., Bertagnolli, D., Casper, T., Chiang, M., Crichton, K., et al. (2021) · Cell · doi:10.1016/j.cell.2021.04.021 · Cited by 1,065 · see citing works
Hybrid error correction and de novo assembly of single-molecule sequencing reads
Koren, S., Schatz, M. C., Walenz, B. P., Martin, J. V., Howard, J. T., Ganapathy, G., Wang, Z., Rasko, D. A., McCombie, W. R., Jarvis, E. D., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2280 · Cited by 993 · see citing works
Self-citationIntegrative single-cell analysis of transcriptional and epigenetic states in the human adult brain
Lake, B. B., Chen, S., Sos, B. C., Fan, J., Kaeser, G. E., Yung, Y. C., Duong, T. E., Gao, D., Chun, J., Kharchenko, P. V., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4038 · Cited by 983 · see citing works
Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain
Lake, B. B., Ai, R., Kaeser, G. E., Salathia, N. S., Yung, Y. C., Liu, R., Wildberg, A., Gao, D., Fung, H.-L., Chen, S., et al. (2016) · Science · doi:10.1126/science.aaf1204 · Cited by 957 · see citing works
Grubman, A., Chew, G., Ouyang, J. F., Sun, G., Choo, X. Y., McLean, C., Simmons, R. K., Buckberry, S., Vargas-Landin, D. B., Poppe, D., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0539-4 · Cited by 956 · see citing works
Gateways to the FANTOM5 promoter level mammalian expression atlas
Lizio, M., Harshbarger, J., Shimoji, H., Severin, J., Kasukawa, T., Sahin, S., Abugessaisa, I., Fukuda, S., Hori, F., Ishikawa-Kato, S., et al. (2015) · Genome Biology · doi:10.1186/s13059-014-0560-6 · Cited by 871 · see citing works
CellRank for directed single-cell fate mapping
Lange, M., Bergen, V., Klein, M., Setty, M. N., Reuter, B., Bakhti, M., Lickert, H., Ansari, M., Gote-Schniering, J., Schiller, H. B., et al. (2022) · Nature Methods · doi:10.1038/s41592-021-01346-6 · Cited by 735 · see citing works
A single-molecule long-read survey of the human transcriptome
Sharon, D., Tilgner, H., Grubert, F., & Snyder, M. (2013) · Nature Biotechnology · doi:10.1038/nbt.2705 · Cited by 701 · see citing works
Self-citationA 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
Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism
Parikshak, N. N., Swarup, V., Belgard, T. G., Irimia, M., Ramaswami, G., Gandal, M. J., Hartl, C., Leppa, V., Ubieta, L. D. L. T., Huang, J., et al. (2016) · Nature · doi:10.1038/nature20612 · Cited by 685 · see citing works
Towards a complete map of the human long non-coding RNA transcriptome
Uszczyńska-Ratajczak, B., Lagarde, J., Frankish, A., Guigó, R., & Johnson, R. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0017-y · Cited by 611 · see citing works
Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons
Krishnaswami, S. R., Grindberg, R. V., Novotny, M., Venepally, P., Lacar, B., Bhutani, K., Linker, S. B., Pham, S., Erwin, J. A., Miller, J. A., et al. (2016) · Nature Protocols · doi:10.1038/nprot.2016.015 · Cited by 445 · see citing works
GeneID in DrosophilaPreprint
Parra, G., Blanco, E., & Guigó, R. (2000) · Genome Research · doi:10.1101/gr.10.4.511 · Cited by 394 · see citing works
Cartography of neurexin alternative splicing mapped by single-molecule long-read mRNA sequencing
Treutlein, B., Gokce, O., Quake, S. R., & Südhof, T. C. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1403244111 · Cited by 348 · see citing works
Functional association between promoter structure and transcript alternative splicing
Cramer, P., Pesce, C. G., Baralle, F. E., & Kornblihtt, A. R. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.21.11456 · Cited by 344 · see citing works
Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells
Gupta, I., Collier, P. G., Haase, B., Mahfouz, A., Joglekar, A., Floyd, T., Koopmans, F., Barres, B., Smit, A. B., Sloan, S. A., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4259 · Cited by 343 · see citing works
Self-citationCharacterization of the human ESC transcriptome by hybrid sequencing
Au, K. F., Sebastiano, V., Afshar, P. T., Durruthy, J. D., Lee, L., Williams, B. A., van Bakel, H., Schadt, E. E., Reijo-Pera, R. A., Underwood, J. G., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1320101110 · Cited by 341 · see citing works
Singh, M., Al-Eryani, G., Carswell, S., Ferguson, J. M., Blackburn, J., Barton, K., Roden, D., Luciani, F., Giang Phan, T., Junankar, S., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11049-4 · Cited by 308 · see citing works
Netrin requires focal adhesion kinase and Src family kinases for axon outgrowth and attraction
Liu, G., Beggs, H. E., Jürgensen, C., Park, H.-T., Tang, H., Gorski, J. A., Jones, K. R., Reichardt, L. F., Wu, J. Y., & Rao, Y. (2004) · Nature Neuroscience · doi:10.1038/nn1331 · Cited by 259 · see citing works
High throughput error corrected Nanopore single cell transcriptome sequencing
Lebrigand, K., Magnone, V., Barbry, P., & Waldmann, R. (2020) · Nature Communications · doi:10.1038/s41467-020-17800-6 · Cited by 236 · see citing works
RBFOX and PTBP1 proteins regulate the alternative splicing of micro-exons in human brain transcriptsPreprint
Li, Y., Sánchez‐Pulido, L., Haerty, W., & Ponting, C. P. (2014) · Genome Research · doi:10.1101/gr.181990.114 · Cited by 231 · see citing works
A spatially resolved brain region- and cell type-specific isoform atlas of the postnatal mouse brain
Joglekar, A., Prjibelski, A., Mahfouz, A., Collier, P., Lin, S., Schlusche, A. K., Marrocco, J., Williams, S. R., Haase, B., Hayes, A., et al. (2021) · Nature Communications · doi:10.1038/s41467-020-20343-5 · Cited by 229 · see citing works
Self-citationVolden, R., Palmer, T., Byrne, A., Cole, C., Schmitz, R. J., Green, R. E., & Vollmers, C. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1806447115 · Cited by 228 · see citing works
Tilgner, H., Jahanbani, F., Blauwkamp, T., Moshrefi, A., Jaeger, E., Chen, F., Harel, I., Bustamante, C. D., Rasmussen, M., & Snyder, M. P. (2015) · Nature Biotechnology · doi:10.1038/nbt.3242 · Cited by 223 · see citing works
Self-citationTakata, A., Matsumoto, N., & Kato, T. (2017) · Nature Communications · doi:10.1038/ncomms14519 · Cited by 184 · see citing works
Targeted Combinatorial Alternative Splicing Generates Brain Region-Specific Repertoires of Neurexins
Schreiner, D., Nguyen, T.-M., Russo, G., Heber, S., Patrignani, A., Ahrné, E., & Scheiffele, P. (2014) · Neuron · doi:10.1016/j.neuron.2014.09.011 · Cited by 183 · see citing works
Co-transcriptional splicing regulates 3′ end cleavage during mammalian erythropoiesis
Reimer, K. A., Mimoso, C. A., Adelman, K., & Neugebauer, K. M. (2021) · Molecular Cell · doi:10.1016/j.molcel.2020.12.018 · Cited by 180 · see citing works
Autism-like phenotype and risk gene mRNA deadenylation by CPEB4 mis-splicing
Parras, A., Anta, H., Santos‐Galindo, M., Swarup, V., Elorza, A., Nieto-González, J. L., Picó, S., Hernández, I. H., Díaz‐Hernandéz, J. I., Belloc, E., et al. (2018) · Nature · doi:10.1038/s41586-018-0423-5 · Cited by 172 · see citing works
Leung, S. K., Jeffries, A. R., Castanho, I., Jordan, B. T., Moore, K., Davies, J. P., Dempster, E. L., Bray, N. J., O’Neill, P., Tseng, E., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.110022 · Cited by 168 · see citing works
Oikonomopoulos, S., Wang, Y. C., Djambazian, H. H. V., Badescu, D., & Ragoussis, J. (2016) · Scientific Reports · doi:10.1038/srep31602 · Cited by 153 · see citing works
Anvar, S. Y., Allard, G., Tseng, E., Sheynkman, G. M., de Klerk, E., Vermaat, M., Yin, R. H., Johansson, H. E., Ariyurek, Y., den Dunnen, J. T., et al. (2018) · Genome Biology · doi:10.1186/s13059-018-1418-0 · Cited by 118 · see citing works
Long-read sequencing of nascent RNA reveals coupling among RNA processing eventsPreprint
Herzel, L., Straube, K., & Neugebauer, K. M. (2018) · Genome Research · doi:10.1101/gr.232025.117 · Cited by 107 · see citing works
Exon-Mediated Activation of Transcription Starts
Fiszbein, A., Krick, K. S., Begg, B. E., & Burge, C. B. (2019) · Cell · doi:10.1016/j.cell.2019.11.002 · Cited by 104 · see citing works
Abascal, F., Ezkurdia, I., Rodriguez-Rivas, J., Rodrı́guez, J. M., del Pozo, Á., Vázquez, J., Valencia, A., & Tress, M. L. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004325 · Cited by 84 · see citing works
Microexons: at the nexus of nervous system development, behaviour and autism spectrum disorder
Gonatopoulos-Pournatzis, T., & Blencowe, B. J. (2020) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2020.03.007 · Cited by 77 · see citing works
Single-cell mRNA isoform diversity in the mouse brain
Karlsson, K., & Linnarsson, S. (2017) · BMC Genomics · doi:10.1186/s12864-017-3528-6 · Cited by 76 · see citing works
Microfluidic isoform sequencing shows widespread splicing coordination in the human transcriptome
Tilgner, H., Jahanbani, F., Gupta, I., Collier, P., Wei, E., Rasmussen, M., & Snyder, M. (2018) · Genome Research · doi:10.1101/gr.230516.117 · Cited by 71 · see citing works
Self-citationA Polar Mechanism Coordinates Different Regions of Alternative Splicing within a Single Gene
Fededa, J. P., Petrillo, E., Gelfand, M. S., Neverov, A. D., Kadener, S., Nogués, G., Pelisch, F., Baralle, F. E., Muro, A. F., & Kornblihtt, A. R. (2005) · Molecular Cell · doi:10.1016/j.molcel.2005.06.035 · Cited by 67 · see citing works
Zhu, C., Wu, J., Sun, H., Briganti, F., Meder, B., Wu, W., & Steinmetz, L. M. (2021) · Nature Communications · doi:10.1038/s41467-021-24484-z · Cited by 51 · see citing works
Regional Variation of Splicing QTLs in Human Brain
Zhang, Y., Yang, H. T., Kadash-Edmondson, K. E., Pan, Y., Pan, Z., Davidson, B. L., & Xing, Y. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.06.002 · Cited by 46 · see citing works
Widespread intron retention impairs protein homeostasis in C9orf72 ALS brainsPreprint
Wang, Q., Conlon, E. G., Manley, J. L., & Rio, D. C. (2020) · Genome Research · doi:10.1101/gr.265298.120 · Cited by 46 · see citing works
Jeffries, A. R., Leung, S., Castanho, I., Moore, K., Davies, J. P., Dempster, E. L., Bray, N. J., O‘Neill, P., Tseng, E., Ahmed, Z., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.10.14.339200 · Cited by 7 · see citing works
Flagged first, then by citations
Research works printed but not linked: 11
- [5]Cox J & Mann M MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol 26, 1367– 1372 (2008). 19029910
- [6]Stuart T Comprehensive Integration of Single-Cell Data. Cell 177, 1888– 1902.e21 (2019). 31178118 PMC6687398
- [7]Hodge RD Conserved cell types with divergent features in human versus mouse cortex. Nature 573, 61– 68 (2019). 31435019 PMC6919571
- [11]Joglekar A A spatially resolved brain region- and cell type-specific isoform atlas of the postnatal mouse brain. Nat. Commun 12, 463 (2021). 33469025 PMC7815907
- [14]Herrmann CJ PolyASite 2.0: a consolidated atlas of polyadenylation sites from 3′ end sequencing. Nucleic Acids Res. 48, D174– D179 (2019). PMC7145510 31617559
- [16]Siepel A Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 15, 1034– 1050 (2005). 16024819 PMC1182216
- [17]Parikshak NN Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism. Nature 540, 423– 427 (2016). 27919067 PMC7102905
- [18]Irimia M A highly conserved program of neuronal microexons is misregulated in autistic brains. Cell 159, 1511– 1523 (2014). 25525873 PMC4390143
- [19]Gonatopoulos-Pournatzis T & Blencowe BJ Microexons: at the nexus of nervous system development, behaviour and autism spectrum disorder. Curr. Opin. Genet. Dev 65, 22– 33 (2020). 32535349
- [20]Takata A, Matsumoto N & Kato T Genome-wide identification of splicing QTLs in the human brain and their enrichment among schizophrenia-associated loci. Nat. Commun 8, 14519 (2017). 28240266 PMC5333373
- [21]Wang Q, Conlon EG, Manley JL & Rio DC Widespread intron retention impairs protein homeostasis in C9orf72 ALS brains. Genome Res. 30, 1705– 1715 (2020). 33055097 PMC7706729
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A guide to the BRAIN Initiative Cell Census Network data ecosystem
Hawrylycz, M., Martone, M. E., Ascoli, G. A., Bjaalie, J. G., Dong, H., Ghosh, S., Gillis, J. A., Hertzano, R. P., Haynor, D. R., Hof, P. R., et al. (2023) · PLoS Biology · doi:10.1371/journal.pbio.3002133 · Cited by 55 · see citing works
Self-citationDondi, A., Lischetti, U., Jacob, F., Singer, F., Borgsmüller, N., Coelho, R., Aebersold, R. H., Ak, M., Alquaddoomi, F., Albert, S. I., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43387-9 · Cited by 53 · see citing works
Steering research on mRNA splicing in cancer towards clinical translation
Anczuków, O., Allain, F. H. ‐., Angarola, B. L., Black, D. L., Brooks, A. N., Cheng, C., Conesa, A., Crosse, E. I., Eyras, E., Guccione, E., et al. (2024) · Nature reviews. Cancer · doi:10.1038/s41568-024-00750-2 · Cited by 48 · see citing works
Advances in single-cell long-read sequencing technologies
Gupta, P., O’Neill, H., Wolvetang, E. J., Chatterjee, A., & Gupta, I. (2024) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqae047 · Cited by 49 · see citing works
Kim, S., Lee, J., Koh, I. G., Ji, J., Kim, H. J., Kim, E., Park, J., Park, J.-E., & An, J. (2024) · Experimental & Molecular Medicine · doi:10.1038/s12276-024-01328-6 · Cited by 44 · see citing works
Review: Challenges and perspectives in applying single nuclei RNA-seq technology in plant biology
Cervantes-Pérez, S. A., Thibivilliers, S., Tennant, S., & Libault, M. (2022) · Plant Science · doi:10.1016/j.plantsci.2022.111486 · Cited by 41 · see citing works
Genome annotation: From human genetics to biodiversity genomics
Guigó, R. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100375 · Cited by 41 · see citing works
Single-cell long-read targeted sequencing reveals transcriptional variation in ovarian cancer
Byrne, A., Le, D., Sereti, K., Menon, H., Vaidya, S., Patel, N., Lund, J. M., Xavier‐Magalhães, A., Shi, M., Liang, Y., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-51252-6 · Cited by 42 · see citing works
From computational models of the splicing code to regulatory mechanisms and therapeutic implications
Capitanchik, C., Wilkins, O. G., Wagner, N., Gagneur, J., & Ule, J. (2024) · Nature Reviews Genetics · doi:10.1038/s41576-024-00774-2 · Cited by 42 · see citing works
Zhang, Z., Bae, B., Dredge, W. H., & Miura, P. (2023) · Nature Communications · doi:10.1038/s41467-023-41207-8 · Cited by 40 · see citing works
Yang, Y., Yang, R., Kang, B., Qian, S., He, X., & Zhang, X. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113335 · Cited by 41 · see citing works
Mikheenko, A., Prjibelski, A. D., Joglekar, A., & Tilgner, H. (2022) · Genome Research · doi:10.1101/gr.276405.121 · Cited by 40 · see citing works
Self-citationGFAP-isoforms in the nervous system: Understanding the need for diversity
de Reus, A. J. E. M., Başak, O., Dykstra, W., van Asperen, J. V., van Bodegraven, E. J., & Hol, E. M. (2024) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2024.102340 · Cited by 35 · see citing works
The variables on RNA molecules: concert or cacophony? Answers in long-read sequencing
Foord, C., Hsu, J., Jarroux, J., Hu, W., Belchikov, N., Pollard, S., He, Y., Joglekar, A., & Tilgner, H. (2023) · Nature Methods · doi:10.1038/s41592-022-01715-9 · Cited by 31 · see citing works
Self-citationApproaches for single-cell RNA sequencing across tissues and cell types
Sant, P., Rippe, K., & Mallm, J. (2023) · Transcription · doi:10.1080/21541264.2023.2200721 · Cited by 34 · see citing works
A molecular brain atlas reveals cellular shifts during the repair phase of stroke
Weber, R., Buil, B. A., Rentsch, N. H., Bosworth, A., Zhang, M., Kisler, K., Tackenberg, C., & Rust, R. (2025) · Journal of Neuroinflammation · doi:10.1186/s12974-025-03437-z · Cited by 32 · see citing works
C9orf72 hexanucleotide repeat expansions impair microglial response in ALS
Masrori, P., Bijnens, B., Fumagalli, L., Davie, K., Poovathingal, S. K., Meese, T. S., Storm, A., Hersmus, N., Fazal, R., van den Biggelaar, D., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-02075-1 · Cited by 30 · see citing works
Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq
Stokes, T., Cen, H. H., Kapranov, P., Gallagher, I. J., Pitsillides, A. A., Volmar, C., Kraus, W. E., Johnson, J. D., Phillips, S. M., Wahlestedt, C., et al. (2023) · Advanced Genetics · doi:10.1002/ggn2.202200024 · Cited by 26 · see citing works
Quantifying transcriptome diversity: a review
Jones, E. F., Haldar, A., Oza, V. H., & Lasseigne, B. N. (2023) · Briefings in Functional Genomics · doi:10.1093/bfgp/elad019 · Cited by 27 · see citing works
ScisorWiz: visualizing differential isoform expression in single-cell long-read data
Stein, A. N., Joglekar, A., Poon, C.-L., & Tilgner, H. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac340 · Cited by 24 · see citing works
Self-citationAre we there yet? Exploring astrocyte heterogeneity one cell at a time
O’Dea, M. R., & Hasel, P. (2024) · Glia · doi:10.1002/glia.24621 · Cited by 27 · see citing works
Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing
Yuan, C. U., Quah, F. X., & Hemberg, M. (2024) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2024.101255 · Cited by 25 · see citing works
mRNA initiation and termination are spatially coordinated
Calvo-Roitberg, E., Carroll, C. L., Kim, G., Sanabria, V. C., Venev, S. V., Mick, S. T., Paquette, J. D., Urióstegui-Arcos, M., Dekker, J., Fiszbein, A., et al. (2025) · Science · doi:10.1126/science.ado8279 · Cited by 23 · see citing works
Belchikov, N., Hsu, J., Li, X. J., Jarroux, J., Hu, W., Joglekar, A., & Tilgner, H. (2024) · Genome Research · doi:10.1101/gr.279640.124 · Cited by 25 · see citing works
Self-citationMicrofluidic single‐cell multiomics analysis
Xu, X., Zhang, Q., Li, M., Lin, S., Liang, S., Cai, L., Zhu, H., Su, R. J., & Yang, C. J. (2022) · Open Research (University of Surrey) · doi:10.1002/viw.20220034 · Cited by 23 · see citing works
Foord, C., Prjibelski, A. D., Hu, W., Michielsen, L., Vandelli, A., Narykov, O., Evans, B., Hsu, J., Belchikov, N., Jarroux, J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-63301-9 · Cited by 22 · see citing works
Self-citationRelapse to cocaine seeking is regulated by medial habenula NR4A2/NURR1 in mice
Childs, J. E., Morabito, S., Das, S., Santelli, C., Pham, V., Kusche, K. M., Vera, V. A., Reese, F., Campbell, R. R., Matheos, D. P., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113956 · Cited by 20 · see citing works
Regulation of alternative splicing and polyadenylation in neurons
Lee, S., Aubee, J. I., & Lai, E. C. (2023) · Life Science Alliance · doi:10.26508/lsa.202302000 · Cited by 21 · see citing works
From words to complete phrases: insight into single-cell isoforms using short and long reads
Joglekar, A., Foord, C., Jarroux, J., Pollard, S., & Tilgner, H. (2023) · Transcription · doi:10.1080/21541264.2023.2213514 · Cited by 20 · see citing works
Self-citationExpression and splicing mediate distinct biological signals
Dam, S. H., Olsen, L. R., & Vitting‐Seerup, K. (2023) · BMC Biology · doi:10.1186/s12915-023-01724-w · Cited by 19 · see citing works
Analyzing alternative splicing in Alzheimer’s disease postmortem brain: a cell-level perspective
Farhadieh, M., & Ghaedi, K. (2023) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2023.1237874 · Cited by 18 · see citing works
Poison exons: tuning RNA splicing for targeted gene regulation
Neil, C. R., Schaening-Burgos, C., Alexis, M. S., Reynolds, D. J., Smith, P. G., Seiler, M., Vaillancourt, F. H., & Agrawal, A. A. (2025) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2025.01.002 · Cited by 19 · see citing works
A single-cell atlas to map sex-specific gene-expression changes in blood upon neurodegeneration
Grandke, F., Fehlmann, T., Kern, F., Gate, D., Wolff, T. W., Leventhal, O., Channappa, D., Hirsch, P., Wilson, E. N., Meese, E. U., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56833-7 · Cited by 17 · see citing works
Single-cell omics sequencing technologies: the long-read generation
Wen, L., & Tang, F. (2025) · Trends in Genetics · doi:10.1016/j.tig.2025.07.012 · Cited by 17 · see citing works
Hodonsky, C. J., Turner, A. W., Khan, M. D., Barrientos, N. B., Methorst, R., Ma, L., Lopez, N. G., Mosquera, J. V., Auguste, G. E., Farber, E., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100465 · Cited by 19 · see citing works
Flotho, M., Amand, J., Hirsch, P., Grandke, F., Wyss‐Coray, T., Keller, A., & Kern, F. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad990 · Cited by 16 · see citing works
Targeted DNA-seq and RNA-seq of Reference Samples with Short-read and Long-read Sequencing
Gong, B., Li, D., Łabaj, P. P., Pan, B., Novoradovskaya, N., Thierry‐Mieg, D., Thierry‐Mieg, J., Chen, G., Lucas, A. B., LoCoco, J. S., et al. (2024) · Scientific Data · doi:10.1038/s41597-024-03741-y · Cited by 15 · see citing works
Self-citationJoglekar, A., Hu, W., Zhang, B., Narykov, O., Diekhans, M., Balacco, J., Ndhlovu, L. C., Milner, T. A., Fedrigo, O. D., Jarvis, E. D., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.02.535281 · Cited by 13 · see citing works
Self-citationWang, Y., Perez‐Rosello, T., Smukowski, S. N., Surmeier, D. J., & Savas, J. N. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02493-w · Cited by 15 · see citing works
The multicellular compartmentation of plant specialized metabolism
Shen, X., Guan, Z., Zhang, C., Yan, Z., & Sun, C. (2024) · Current Opinion in Plant Biology · doi:10.1016/j.pbi.2024.102616 · Cited by 11 · see citing works
Wu, X., Xiong, D., Liu, R., Lai, X., Tian, Y., Xie, Z., Chen, L., Hu, L., Duan, J., Gao, X., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-58275-7 · Cited by 11 · see citing works
Hu, W., Foord, C., Hsu, J., Fan, L., Corley, M. J., Lanjewar, S. N., Xu, S., Belchikov, N., He, Y., Pang, A. P. S., et al. (2025) · Nature Biotechnology · doi:10.1038/s41587-025-02734-5 · Cited by 14 · see citing works
Self-citationElucidating the coordination of RNA processing using short-read and long-read RNA-sequencing methods
Alfonso-Gonzalez, C., & Hilgers, V. (2025) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-025-00895-4 · Cited by 13 · see citing works
In-Depth Temporal Transcriptome Profiling of an Alphaherpesvirus Using Nanopore Sequencing
Tombácz, D., Kakuk, B., Torma, G., Csabai, Z., Gulyás, G. M., Tamás, V., Zádori, Z., Jefferson, V. A., Meyer, F., & Boldogkői, Z. (2022) · Viruses · doi:10.3390/v14061289 · Cited by 10 · see citing works
Self-citationGrand, Q. L., Tsuchida, A., Koch, A., Imtiaz, M. A., Aziz, N. A., Vigneron, C., Zago, L., Lathrop, M. G., Dubrac, A., Couffinhal, T., et al. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02604-7 · Cited by 10 · see citing works
Long-read RNA-seq demarcates cis- and trans-directed alternative RNA splicing
Quinones-Valdez, G., Amoah, K., & Xiao, X. G. (2025) · Nature Communications · doi:10.1038/s41467-025-64605-6 · Cited by 10 · see citing works
Comparing 10x Genomics single-cell 3’ and 5’ assay in short-and long-read sequencingPreprint
Hsu, J., Jarroux, J., Joglekar, A., Romero, J. P., Nemec, C. M., Reyes, D., Royall, A., He, Y., Belchikov, N., Leo, K. T., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.27.514084 · Cited by 13 · see citing works
Self-citationBelchikov, N., Hu, W., Fan, L., Joglekar, A., He, Y., Foord, C., Jarroux, J., Hsu, J., Pollard, S., Amin, S., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116198 · Cited by 9 · see citing works
Self-citationGaiti, F., Chamely, P., Hawkins, A. G., Cortés-López, M., Swett, A. D., Ganesan, S., Mouhieddine, T. H., Dai, X., Kluegel, L., Chen, C. Y., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.08.495292 · Cited by 9 · see citing works
Alternative splicing in autism spectrum disorder: Recent insights from mechanisms to therapy
Zheng, M., Bao, N., Wang, Z., Song, C., & Jin, Y. (2025) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2025.104501 · Cited by 8 · see citing works
Tools and tactics for studying alternative splicing
Sousa‐Luís, R., & Carmo‐Fonseca, M. (2026) · Nature Reviews Genetics · doi:10.1038/s41576-026-00952-4 · Cited by 8 · see citing works
RNA Isoform Diversity in Human Neurodegenerative Diseases
Liu, C. S., Park, C. Y., Ngo, T., Saikumar, J., Palmer, C. R., Shahnaee, A., Romanow, W. J., & Chun, J. J. M. (2024) · eNeuro · doi:10.1523/eneuro.0296-24.2024 · Cited by 8 · see citing works
Genetic regulation of nascent RNA maturation revealed by direct RNA nanopore sequencingPreprint
Choquet, K., Chaumont, L.-P., Bache, S., Baxter‐Koenigs, A. R., & Churchman, L. S. (2025) · Genome Research · doi:10.1101/gr.279203.124 · Cited by 8 · see citing works
The ANTsX ecosystem for mapping the mouse brain
Tustison, N. J., Chen, M., Kronman, F. N., Duda, J., Gamlin, C. R., Tustison, M. G., Kunst, M., Dalley, R. A., Sorensen, S. A., Wang, Q., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-66741-5 · Cited by 7 · see citing works
Beyond the gene: decoding alternative isoforms
Mattioli, K., & Bulyk, M. L. (2025) · Trends in Genetics · doi:10.1016/j.tig.2025.11.003 · Cited by 9 · see citing works
Leveraging Single-Cell Technologies to Advance Understanding of Myocardial Disease
Gardner, R. S., Tucker, N. R., & Amancherla, K. V. (2026) · Circulation Research · doi:10.1161/circresaha.125.326002 · Cited by 8 · see citing works
The BRAIN Initiative Cell Census Network Data Ecosystem: A User’s GuidePreprint
Hawrylycz, M., Martone, M. E., Hof, P. R., Lein, E. S., Regev, A., Ascoli, G. A., Bjaalie, J. G., Dong, H., Ghosh, S., Gillis, J. A., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.26.513573 · Cited by 7 · see citing works
Self-citationWorf, K., Matosin, N., Gerstner, N., Fröhlich, A. S., Koller, A. C., Degenhardt, F., Thiele, H., Rietschel, M., Udawela, M., Scarr, E., et al. (2025) · Translational Psychiatry · doi:10.1038/s41398-025-03366-8 · Cited by 9 · see citing works
Sehgal, P. D., Naqvi, A. S., Higgins, M., Liu, J., Harvey, K., Jarroux, J., Kim, T. W., Mankaliye, B., Mishra, P., Watterson, G., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116099 · Cited by 5 · see citing works
Self-citationDetecting gene expression in Caenorhabditis elegans
Calarco, J. A., Taylor, S. R., & Miller, D. M. (2024) · Genetics · doi:10.1093/genetics/iyae167 · Cited by 6 · see citing works
Mouse Single-Cell Long-Read Splicing Atlas by Ouro-SeqPreprint
An, H., Choi, S. Y., Yi, J., Lim, C., Shin, S.-I., Oh, S., Lee, R. H., & Park, J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.01.17.633678 · Cited by 6 · see citing works
Isoform-specific m6A deposition and coordinated splicing shape mammalian transcriptome evolution
Rodriguez, G. S., Srivastava, A., Ravindran, A., Oyelami, F. O., Ip, C. K., Gupta, P., Villanueva, J., King, H. A., Grootveld, A. K., Sneddon, A., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-72124-1 · Cited by 5 · see citing works
Aucouturier, C., Soirat, N., Castéra, L., Bertrand, D., Atkinson, A., Lavolé, T., Goardon, N., Quesnelle, C., Levilly, J., Barbachou, S., et al. (2024) · BMC Genomics · doi:10.1186/s12864-024-10741-0 · Cited by 5 · see citing works
Michielsen, L., Prjibelski, A. D., Foord, C., Spiegelman, Y., Kim, T., Hu, W., Jarroux, J., Hsu, J., Pfeil, R., Zhang, X., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.25.661563 · Cited by 5 · see citing works
Self-citationNeuronal RNA processing: cross-talk between transcriptional regulation and RNA-binding proteins
Ozbulut, H. C., & Hilgers, V. (2024) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2024.1426410 · Cited by 4 · see citing works
Moakley, D. F., Campbell, M., Anglada-Girotto, M., Feng, H., Califano, A., Au, E., & Zhang, C. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115898 · Cited by 4 · see citing works
Ágoston, D. V. (2024) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2024.1374864 · Cited by 4 · see citing works
Hu, W., Foord, C., Hsu, J., Fan, L., Corley, M. J., Bhatia, T. N., Xu, S., Belchikov, N., He, Y., Pang, A. P. S., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.24.581897 · Cited by 4 · see citing works
Self-citationMichielsen, L., Hsu, J., Joglekar, A., Belchikov, N., Reinders, M. J. T., Tilgner, H., & Mahfouz, A. E. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.03.18.585465 · Cited by 4 · see citing works
Self-citationThe exon junction complex coordinates the cotranscriptional inclusion of blocks of neighboring exonsPreprint
Bergfort, A., Gordon, J. M., Gazzara, M. R., Hung, C.-T., Lee, B., Barash, Y., & Neugebauer, K. M. (2025) · Genes & Development · doi:10.1101/gad.353081.125 · Cited by 4 · see citing works
Multi-omic profiling of pathogen-stimulated primary immune cells
Salz, R., Vorsteveld, E. E., van der Made, C. I., Kersten, S., Stemerdink, M., Riepe, T., Hsieh, T.-H., Mhlanga, M. M., Netea, M. G., Volders, P., et al. (2024) · iScience · doi:10.1016/j.isci.2024.110471 · Cited by 3 · see citing works
Moakley, D. F., Campbell, M., Anglada-Girotto, M., Feng, H., Califano, A., Au, E., & Zhang, C. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.13.597128 · Cited by 3 · see citing works
Iso-Seq enables discovery of novel isoform variants in human retina at single cell resolutionPreprint
Wang, L., Urrutia-Cabrera, D., Hung, S. S. C., Hewitt, A. W., Lukowski, S. W., Foord, C., Wang, P., Tilgner, H., & Wong, R. C. B. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.08.607267 · Cited by 3 · see citing works
Self-citationThe Role of mRNA Alternative Processing in Mammalian Neurodevelopment
Liu, X., Zuo, J. J., Zhang, G., Han, X., & Tian, Y. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms262211075 · Cited by 3 · see citing works
Michielsen, L., Prjibelski, A. D., Foord, C., Spiegelman, Y., Kim, T., Hu, W., Jarroux, J., Hsu, J., Pfeil, R., Zhang, X., et al. (2026) · Nature Methods · doi:10.1038/s41592-026-03211-w · Cited by 6 · see citing works
Self-citationThe Use of Single-Cell and Spatial Omics to Study Copy Number Variants
Malwade, S., Ingason, A., & Khodosevich, K. (2025) · Biological Psychiatry · doi:10.1016/j.biopsych.2025.06.010 · Cited by 2 · see citing works
A million shades of green: understanding and harnessing plant metabolic diversity
Payet, R. D., Aouidate, A., Casson, R., Houghton, A., Pham, M., & Osbourn, A. (2025) · The EMBO Journal · doi:10.1038/s44318-025-00496-z · Cited by 2 · see citing works
Expression and Splicing Mediate Distinct Biological SignalsPreprint
Dam, S. H., Olsen, L. R., & Vitting‐Seerup, K. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.29.505720 · Cited by 2 · see citing works
The conserved landscape of RNA modifications and transcript diversity across mammalian evolutionPreprint
Rodriguez, G. S., Srivastava, A., Ravindran, A., Oyelami, F. O., Ip, C. K., Gupta, P., Villanueva, J. E., King, H., Grootveld, A. K., Blackburn, J., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.24.624934 · Cited by 3 · see citing works
Yu, H., Georgescu, C. H., Khorgade, A., Al‐Eryani, G., Bartlett, D. A., Brookhart, A., Koçkan, C., Webber, J. T., Shin, A., White, E., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.12.705617 · Cited by 5 · see citing works
Decoding the human PBMC isonome: isoform-level resolution with single-cell long-read transcriptomics
Doyle, P. H., Page, M. L., Brandon, J. A., Heberle, B. A., White, B. J., Stowe, A. M., & Ebbert, M. (2026) · Frontiers in Genetics · doi:10.3389/fgene.2026.1782221 · Cited by 1 · see citing works
A Single-Cell Omics Technical Guide for Advancing Neuropsychiatric Research
Casmey, K., Zimmermann, M., Xie, Y., Codeluppi-Arrowsmith, S. A., & Turecki, G. (2025) · Genes · doi:10.3390/genes16121394 · Cited by 2 · see citing works
Xu, N., Rynard, K. M., Radley, E., Tian, A., Arshad, M., Long, C., Ly, J., Luo, H., Hogan, E., Fafouti, M. E., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-76675-1 · Cited by 1 · see citing works
isoSeQL: comparing long-read isoforms across multiple datasets
Liu, C. S., & Chun, J. J. M. (2025) · Bioinformatics · doi:10.1093/bioinformatics/btaf680 · Cited by 1 · see citing works
Shahnaee, A., Liu, C. S., Ngo, T., Palmer, C. R., Ziomek, D., Park, C. S., Tan, V. P., Jimenez, N. A., & Chun, J. J. M. (2026) · Communications Biology · doi:10.1038/s42003-026-09759-9 · Cited by 1 · see citing works
Beyond the gene: isoform diversity as a key contributor to human brain disorders
Ma, Y., Jops, C. T., & Gandal, M. J. (2026) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2026.102497 · Cited by 1 · see citing works
RNA regulation in brain function and disease 2022 (NeuroRNA): A conference report
Piwecka, M., Fiszer, A., Rolle, K., & Olejniczak, M. (2023) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2023.1133209 · Cited by 1 · see citing works
Hybrid exons evolved by coupling transcription initiation and splicing at the nucleotide level
Mick, S. T., Carroll, C. L., Urióstegui-Arcos, M., & Fiszbein, A. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1251 · Cited by 1 · see citing works
- Authors
- Hardwick, S. A., Hu, W., Joglekar, A., Fan, L., Collier, P. G., Foord, C., Balacco, J., Lanjewar, S., Sampson, M. M., Koopmans, F., Prjibelski, A. D., Mikheenko, A., Belchikov, N., Jarroux, J., Lucas, A. B., Palkovits, M., Luo, W., Milner, T. A., Ndhlovu, L. C., Smit, A. B., Trojanowski, J. Q., Lee, V. M. Y., Fedrigo, O., Sloan, S. A., Tombácz, D., Ross, M. E., Jarvis, E., Boldogkői, Z., Gan, L., & Tilgner, H. U.
- Affiliations
- Weill Cornell Medicine (US)
- Rockefeller University (US)
- Emory University (US)
- Amsterdam Neuroscience (NL)
- St Petersburg University (RU)
- Agilent Technologies (United States) (US)
- Semmelweis University (HU)
- University of Pennsylvania (US)
- University of Szeged (HU)
- Corresponding author
- Tilgner, Hagen U.
- ORCID
- Hardwick, Simon A.
- Hu, Wen
- Joglekar, Anoushka
- Fan, Li
- Foord, Careen
- Balacco, Jennifer
- Lanjewar, Samantha
- Sampson, Maureen McGuirk
- Koopmans, Frank
- Prjibelski, Andrey D.
- Mikheenko, Alla
- Belchikov, Natan
- Jarroux, Julien
- Palkovits, Miklós
- Luo, Wenjie
- Milner, Teresa A.
- Ndhlovu, Lishomwa C.
- Smit, August B.
- Trojanowski, John Q.
- Lee, Virginia M. Y.
- Fedrigo, Olivier
- Sloan, Steven A.
- Tombácz, Dóra
- Ross, M. Elizabeth
- Jarvis, Erich
- Boldogkői, Zsolt
- Gan, Li
- Tilgner, Hagen U.
- Venue
- Nature Biotechnology
- Published
- 2022-03-07
- Volume
- 40
- Issue
- 7
- Pages
- 1082-1092
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC9287170
- OpenAlex
- W4220958064
- Cited by
- 119
- References
- 59
- Citations by year
- 2026: 18 · 2025: 32 · 2024: 32 · 2023: 26 · 2022: 11
- FWCI
- 8.41
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature Biotechnology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- SZTE Publicatio Repozitórium (University of Szeged) (acceptedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- Department of Health | National Health and Medical Research Council (APP1156531)
- Saint Petersburg State University (PURE 73023672)
- Semmelweis Egyetem (2017-1.2.1-NKP-2017-00002)
- Hungarian Brain Research Program, The Human Brain Tissue Bank, Semmelweis University
- U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (DA08259, U01 DA53625, U01 DA053625-01)
- U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (HL136520)
- U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (UM1AI164599)
- U.S. Department of Health & Human Services | National Institutes of Health (U19 AG062418, R01AG051390, U54NS100717, R01AG054214)
- Howard Hughes Medical Institute
- U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (R01MH125956, 1RF1MH121267-01)
- Brain and Behavior Research Foundation (28172)
- Nemzeti Kutatási, Fejlesztési és Innovációs Hivatal (FK128252, K128247)
- U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (1R01NS105477, U54NS11717)
- U.S. Department of Health & Human Services | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (P01HD067244)
- Feil Family Foundation
- JPB Foundation
- U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (1R01GM135247-01)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- alternative splicing, barcoding, frozen brain tissue, human frontal cortex, autism spectrum disorder, long-read sequencing, microfluidics, target enrichment
- MeSH terms
- Brain, Exons, Humans, RNA, Alternative Splicing, Sequence Analysis, RNA, Protein Isoforms
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