In Situ Perturb-Seq of Transcriptomes and RNA Neural Recordings
In this work, we explore the intersection of in situ sequencing, neural recording, and CRISPR screens. An intracellular technology is outlined for encoding neural activity in the form of RNA, theoretically enabling single-cell resolution recording of whole-brain activity. This neural recording syste...
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Format: | Thesis |
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Massachusetts Institute of Technology
2022
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Online Access: | https://hdl.handle.net/1721.1/139207 |
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author | Romero, Cipriano William |
author2 | Boyden, Edward S. |
author_facet | Boyden, Edward S. Romero, Cipriano William |
author_sort | Romero, Cipriano William |
collection | MIT |
description | In this work, we explore the intersection of in situ sequencing, neural recording, and CRISPR screens. An intracellular technology is outlined for encoding neural activity in the form of RNA, theoretically enabling single-cell resolution recording of whole-brain activity. This neural recording system can be coupled with perturb-seq in order to observe high-throughput genetic perturbations of neurons with both temporal and transcriptomic information. Untargeted expansion sequencing (ExSeq) can be used to generate a high-resolution spatiotemporal dataset that includes single guide RNAs (sgRNAs), neural activity, and transcriptomics. Targeted ExSeq, with the inclusion of no-gap padlock probes and SplintR ligase, can be applied to enhance the detection of sgRNA barcodes and targeted transcripts. In vitro and in vivo experimental pipelines are proposed for the fusion of these technologies, in this theoretical thesis. |
first_indexed | 2024-09-23T10:47:35Z |
format | Thesis |
id | mit-1721.1/139207 |
institution | Massachusetts Institute of Technology |
last_indexed | 2024-09-23T10:47:35Z |
publishDate | 2022 |
publisher | Massachusetts Institute of Technology |
record_format | dspace |
spelling | mit-1721.1/1392072022-01-15T03:48:24Z In Situ Perturb-Seq of Transcriptomes and RNA Neural Recordings Romero, Cipriano William Boyden, Edward S. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science In this work, we explore the intersection of in situ sequencing, neural recording, and CRISPR screens. An intracellular technology is outlined for encoding neural activity in the form of RNA, theoretically enabling single-cell resolution recording of whole-brain activity. This neural recording system can be coupled with perturb-seq in order to observe high-throughput genetic perturbations of neurons with both temporal and transcriptomic information. Untargeted expansion sequencing (ExSeq) can be used to generate a high-resolution spatiotemporal dataset that includes single guide RNAs (sgRNAs), neural activity, and transcriptomics. Targeted ExSeq, with the inclusion of no-gap padlock probes and SplintR ligase, can be applied to enhance the detection of sgRNA barcodes and targeted transcripts. In vitro and in vivo experimental pipelines are proposed for the fusion of these technologies, in this theoretical thesis. S.M. 2022-01-14T14:56:41Z 2022-01-14T14:56:41Z 2021-06 2021-06-24T19:39:25.688Z Thesis https://hdl.handle.net/1721.1/139207 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
spellingShingle | Romero, Cipriano William In Situ Perturb-Seq of Transcriptomes and RNA Neural Recordings |
title | In Situ Perturb-Seq of Transcriptomes and RNA Neural Recordings |
title_full | In Situ Perturb-Seq of Transcriptomes and RNA Neural Recordings |
title_fullStr | In Situ Perturb-Seq of Transcriptomes and RNA Neural Recordings |
title_full_unstemmed | In Situ Perturb-Seq of Transcriptomes and RNA Neural Recordings |
title_short | In Situ Perturb-Seq of Transcriptomes and RNA Neural Recordings |
title_sort | in situ perturb seq of transcriptomes and rna neural recordings |
url | https://hdl.handle.net/1721.1/139207 |
work_keys_str_mv | AT romerociprianowilliam insituperturbseqoftranscriptomesandrnaneuralrecordings |