Single-nuclei isoform RNA sequencing unlocks barcoded exon connectivity in frozen brain tissue.
Journal
Nature biotechnology
ISSN: 1546-1696
Titre abrégé: Nat Biotechnol
Pays: United States
ID NLM: 9604648
Informations de publication
Date de publication:
07 2022
07 2022
Historique:
received:
29
06
2021
accepted:
20
01
2022
pubmed:
9
3
2022
medline:
20
7
2022
entrez:
8
3
2022
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 35256815
doi: 10.1038/s41587-022-01231-3
pii: 10.1038/s41587-022-01231-3
pmc: PMC9287170
mid: NIHMS1800685
doi:
Substances chimiques
Protein Isoforms
0
RNA
63231-63-0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
1082-1092Subventions
Organisme : NHLBI NIH HHS
ID : R01 HL136520
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM135247
Pays : United States
Organisme : NIAID NIH HHS
ID : UM1 AI164559
Pays : United States
Organisme : NINDS NIH HHS
ID : U54 NS100717
Pays : United States
Organisme : NIDA NIH HHS
ID : U01 DA053625
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS105477
Pays : United States
Organisme : NIDA NIH HHS
ID : R01 DA008259
Pays : United States
Organisme : NIDA NIH HHS
ID : T32 DA039080
Pays : United States
Organisme : NIMH NIH HHS
ID : RF1 MH121267
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH125956
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG072758
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG051390
Pays : United States
Organisme : NINDS NIH HHS
ID : U54 NS117170
Pays : United States
Organisme : Howard Hughes Medical Institute
Pays : United States
Organisme : NICHD NIH HHS
ID : P01 HD067244
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS123562
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG054214
Pays : United States
Organisme : NIA NIH HHS
ID : U19 AG062418
Pays : United States
Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2022. The Author(s).
Références
Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).
pubmed: 26000488
pmcid: 4481139
doi: 10.1016/j.cell.2015.05.002
Klein, A. M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).
pubmed: 26000487
pmcid: 4441768
doi: 10.1016/j.cell.2015.04.044
Zeisel, A. et al. Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347, 1138–1142 (2015).
pubmed: 25700174
doi: 10.1126/science.aaa1934
Sharon, D., Tilgner, H., Grubert, F. & Snyder, M. A single-molecule long-read survey of the human transcriptome. Nat. Biotechnol. 31, 1009–1014 (2013).
pubmed: 24108091
pmcid: 4075632
doi: 10.1038/nbt.2705
Au, K. F. et al. Characterization of the human ESC transcriptome by hybrid sequencing. Proc. Natl Acad. Sci. USA 110, E4821–E4830 (2013).
pubmed: 24282307
pmcid: 3864310
doi: 10.1073/pnas.1320101110
Koren, S. et al. Hybrid error correction and de novo assembly of single-molecule sequencing reads. Nat. Biotechnol. 30, 693–700 (2012).
pubmed: 22750884
pmcid: 3707490
doi: 10.1038/nbt.2280
Tilgner, H. et al. Comprehensive transcriptome analysis using synthetic long-read sequencing reveals molecular co-association of distant splicing events. Nat. Biotechnol. 33, 736–742 (2015).
pubmed: 25985263
pmcid: 4832928
doi: 10.1038/nbt.3242
Oikonomopoulos, S., Wang, Y. C., Djambazian, H., Badescu, D. & Ragoussis, J. Benchmarking of the Oxford Nanopore MinION sequencing for quantitative and qualitative assessment of cDNA populations. Sci. Rep. 6, 31602 (2016).
pubmed: 27554526
pmcid: 4995519
doi: 10.1038/srep31602
Karlsson, K. & Linnarsson, S. Single-cell mRNA isoform diversity in the mouse brain. BMC Genomics 18, 126 (2017).
pubmed: 28158971
pmcid: 5291953
doi: 10.1186/s12864-017-3528-6
Volden, R. et al. Improving nanopore read accuracy with the R2C2 method enables the sequencing of highly multiplexed full-length single-cell cDNA. Proc. Natl. Acad. Sci. USA 115, 9726–9731 (2018).
pubmed: 30201725
pmcid: 6166824
doi: 10.1073/pnas.1806447115
Singh, M. et al. High-throughput targeted long-read single cell sequencing reveals the clonal and transcriptional landscape of lymphocytes. Nat. Commun. 10, 3120 (2019).
pubmed: 31311926
pmcid: 6635368
doi: 10.1038/s41467-019-11049-4
Gupta, I. et al. Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells. Nat. Biotechnol. 36, 1197–1202 (2018).
doi: 10.1038/nbt.4259
Hodge, R. D. et al. Conserved cell types with divergent features in human versus mouse cortex. Nature 573, 61–68 (2019).
pubmed: 31435019
pmcid: 6919571
doi: 10.1038/s41586-019-1506-7
Krishnaswami, S. R. et al. Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons. Nat. Protoc. 11, 499–524 (2016).
pubmed: 26890679
pmcid: 4941947
doi: 10.1038/nprot.2016.015
Lake, B. B. et al. Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain. Science 352, 1586–1590 (2016).
pubmed: 27339989
pmcid: 5038589
doi: 10.1126/science.aaf1204
Bergen, V., Lange, M., Peidli, S., Wolf, F. A. & Theis, F. J. Generalizing RNA velocity to transient cell states through dynamical modeling. Nat. Biotechnol. 38, 1408–1414 (2020).
pubmed: 32747759
doi: 10.1038/s41587-020-0591-3
La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018).
pubmed: 30089906
pmcid: 6130801
doi: 10.1038/s41586-018-0414-6
Lange, M. et al. CellRank for directed single-cell fate mapping. Nat. Methods https://doi.org/10.1038/s41592-021-01346-6 (2022).
Eid, J. et al. Real-time DNA sequencing from single polymerase molecules. Science 323, 133–138 (2009).
pubmed: 19023044
doi: 10.1126/science.1162986
Tilgner, H. et al. Microfluidic isoform sequencing shows widespread splicing coordination in the human transcriptome. Genome Res. 28, 231–242 (2018).
pubmed: 29196558
pmcid: 5793787
doi: 10.1101/gr.230516.117
Anvar, S. Y. et al. Full-length mRNA sequencing uncovers a widespread coupling between transcription initiation and mRNA processing. Genome Biol. 19, 46 (2018).
pubmed: 29598823
pmcid: 5877393
doi: 10.1186/s13059-018-1418-0
Schreiner, D. et al. Targeted combinatorial alternative splicing generates brain region-specific repertoires of neurexins. Neuron 84, 386–398 (2014).
pubmed: 25284007
doi: 10.1016/j.neuron.2014.09.011
Treutlein, B., Gokce, O., Quake, S. R. & Südhof, T. C. Cartography of neurexin alternative splicing mapped by single-molecule long-read mRNA sequencing. Proc. Natl. Acad. Sci. USA 111, E1291–E1299 (2014).
pubmed: 24639501
pmcid: 3977267
doi: 10.1073/pnas.1403244111
Fededa, J. P. et al. A polar mechanism coordinates different regions of alternative splicing within a single gene. Mol. Cell 19, 393–404 (2005).
pubmed: 16061185
doi: 10.1016/j.molcel.2005.06.035
Cramer, P., Pesce, C. G., Baralle, F. E. & Kornblihtt, A. R. Functional association between promoter structure and transcript alternative splicing. Proc. Natl. Acad. Sci. USA 94, 11456–11460 (1997).
pubmed: 9326631
pmcid: 23504
doi: 10.1073/pnas.94.21.11456
Fiszbein, A., Krick, K. S., Begg, B. E. & Burge, C. B. Exon-mediated activation of transcription starts. Cell 179, 1551–1565 (2019).
pubmed: 31787377
pmcid: 7351029
doi: 10.1016/j.cell.2019.11.002
Reimer, K. A., Mimoso, C. A., Adelman, K. & Neugebauer, K. M. Co-transcriptional splicing regulates 3′ end cleavage during mammalian erythropoiesis. Mol. Cell 81, 998–1012 (2021).
pubmed: 33440169
pmcid: 8038867
doi: 10.1016/j.molcel.2020.12.018
Herzel, L., Straube, K. & Neugebauer, K. M. Long-read sequencing of nascent RNA reveals coupling among RNA processing events. Genome Res. 28, 1008–1019 (2018).
pubmed: 29903723
pmcid: 6028129
doi: 10.1101/gr.232025.117
Parras, A. et al. Autism-like phenotype and risk gene mRNA deadenylation by CPEB4 mis-splicing. Nature 560, 441–446 (2018).
pubmed: 30111840
pmcid: 6217926
doi: 10.1038/s41586-018-0423-5
Zhang, Y. et al. Regional variation of splicing QTLs in human brain. Am. J. Hum. Genet. 107, 196–210 (2020).
pubmed: 32589925
pmcid: 7413857
doi: 10.1016/j.ajhg.2020.06.002
Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019).
pubmed: 31178118
pmcid: 6687398
doi: 10.1016/j.cell.2019.05.031
Zheng, G. X. Y. et al. Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 8, 14049 (2017).
pubmed: 28091601
pmcid: 5241818
doi: 10.1038/ncomms14049
Joglekar, A. et al. A spatially resolved brain region- and cell type-specific isoform atlas of the postnatal mouse brain. Nat. Commun. 12, 463 (2021).
pubmed: 33469025
pmcid: 7815907
doi: 10.1038/s41467-020-20343-5
Leung, S. K. et al. Full-length transcript sequencing of human and mouse cerebral cortex identifies widespread isoform diversity and alternative splicing. Cell Rep. 37, 110022 (2021).
pubmed: 34788620
pmcid: 8609283
doi: 10.1016/j.celrep.2021.110022
Irimia, M. et al. A highly conserved program of neuronal microexons is misregulated in autistic brains. Cell 159, 1511–1523 (2014).
pubmed: 25525873
pmcid: 4390143
doi: 10.1016/j.cell.2014.11.035
Li, Y. I., Sanchez-Pulido, L., Haerty, W. & Ponting, C. P. RBFOX and PTBP1 proteins regulate the alternative splicing of micro-exons in human brain transcripts. Genome Res. 25, 1–13 (2015).
pubmed: 25524026
pmcid: 4317164
doi: 10.1101/gr.181990.114
Wang, E. T. et al. Alternative isoform regulation in human tissue transcriptomes. Nature 456, 470–476 (2008).
pubmed: 18978772
pmcid: 2593745
doi: 10.1038/nature07509
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).
pubmed: 28240266
pmcid: 5333373
doi: 10.1038/ncomms14519
Parikshak, N. N. et al. Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism. Nature 540, 423–427 (2016).
pubmed: 27919067
pmcid: 7102905
doi: 10.1038/nature20612
Gonatopoulos-Pournatzis, T. & Blencowe, B. J. Microexons: at the nexus of nervous system development, behaviour and autism spectrum disorder. Curr. Opin. Genet. Dev. 65, 22–33 (2020).
pubmed: 32535349
doi: 10.1016/j.gde.2020.03.007
Wang, Q., Conlon, E. G., Manley, J. L. & Rio, D. C. Widespread intron retention impairs protein homeostasis in C9orf72 ALS brains. Genome Res. 30, 1705–1715 (2020).
pubmed: 33055097
pmcid: 7706729
doi: 10.1101/gr.265298.120
Uszczynska-Ratajczak, B., Lagarde, J., Frankish, A., Guigó, R. & Johnson, R. Towards a complete map of the human long non-coding RNA transcriptome. Nat. Rev. Genet. 19, 535–548 (2018).
pubmed: 29795125
pmcid: 6451964
doi: 10.1038/s41576-018-0017-y
Zhu, C. et al. Single-molecule, full-length transcript isoform sequencing reveals disease-associated RNA isoforms in cardiomyocytes. Nat. Commun. 12, 4203 (2021).
pubmed: 34244519
pmcid: 8270901
doi: 10.1038/s41467-021-24484-z
Parra, G., Blanco, E. & Guigó, R. GeneID in Drosophila. Genome Res. 10, 511–515 (2000).
pubmed: 10779490
pmcid: 310871
doi: 10.1101/gr.10.4.511
Yeo, G. & Burge, C. B. Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals. J. Comput. Biol. 11, 377–394 (2004).
pubmed: 15285897
doi: 10.1089/1066527041410418
Abascal, F. et al. Alternatively spliced homologous exons have ancient origins and are highly expressed at the protein level. PLoS Comput. Biol. 11, e1004325 (2015).
pubmed: 26061177
pmcid: 4465641
doi: 10.1371/journal.pcbi.1004325
Siepel, A. et al. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 15, 1034–1050 (2005).
pubmed: 16024819
pmcid: 1182216
doi: 10.1101/gr.3715005
Liu, G. et al. Netrin requires focal adhesion kinase and Src family kinases for axon outgrowth and attraction. Nat. Neurosci. 7, 1222–1232 (2004).
pubmed: 15494732
pmcid: 2266630
doi: 10.1038/nn1331
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).
pubmed: 19029910
doi: 10.1038/nbt.1511
Zhang, Y. et al. Purification and characterization of progenitor and mature human astrocytes reveals transcriptional and functional differences with mouse. Neuron 89, 37–53 (2016).
pubmed: 26687838
doi: 10.1016/j.neuron.2015.11.013
Habib, N. et al. Massively parallel single-nucleus RNA-seq with DroNc-seq. Nat. Methods 14, 955–958 (2017).
pubmed: 28846088
pmcid: 5623139
doi: 10.1038/nmeth.4407
Grubman, A. et al. A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat. Neurosci. 22, 2087–2097 (2019).
pubmed: 31768052
doi: 10.1038/s41593-019-0539-4
Schmittgen, T. D. & Livak, K. J. Analyzing real-time PCR data by the comparative C
pubmed: 18546601
doi: 10.1038/nprot.2008.73
Lake, B. B. et al. Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain. Nat. Biotechnol. 36, 70–80 (2018).
pubmed: 29227469
doi: 10.1038/nbt.4038
Tasic, B. et al. Shared and distinct transcriptomic cell types across neocortical areas. Nature 563, 72–78 (2018).
pubmed: 30382198
pmcid: 6456269
doi: 10.1038/s41586-018-0654-5
Yao, Z. et al. A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation. Cell 184, 3222–3241 (2021).
pubmed: 34004146
pmcid: 8195859
doi: 10.1016/j.cell.2021.04.021
Lebrigand, K., Magnone, V., Barbry, P. & Waldmann, R. High throughput error corrected Nanopore single cell transcriptome sequencing. Nat. Commun. 11, 4025 (2020).
pubmed: 32788667
pmcid: 7423900
doi: 10.1038/s41467-020-17800-6
Lizio, M. et al. Gateways to the FANTOM5 promoter level mammalian expression atlas. Genome Biol. 16, 22 (2015).
pubmed: 25723102
pmcid: 4310165
doi: 10.1186/s13059-014-0560-6
Herrmann, C. J. et al. PolyASite 2.0: a consolidated atlas of polyadenylation sites from 3′ end sequencing. Nucleic Acids Res. 48, D174–D179 (2019).
pmcid: 7145510
Pollard, K. S., Hubisz, M. J., Rosenbloom, K. R. & Siepel, A. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res. 20, 110–121 (2010).
pubmed: 19858363
pmcid: 2798823
doi: 10.1101/gr.097857.109