Long-read single-cell sequencing reveals expressions of hypermutation clusters of isoforms in human liver cancer cells.

computational biology human mutation evolution pathway mutation gene expression mutation isoform expression single-cell synthetic long-read sequencing single-molecule mutation evolution systems biology

Journal

eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614

Informations de publication

Date de publication:
11 Jan 2024
Historique:
medline: 12 1 2024
pubmed: 11 1 2024
entrez: 11 1 2024
Statut: epublish

Résumé

The protein diversity of mammalian cells is determined by arrays of isoforms from genes. Genetic mutation is essential in species evolution and cancer development. Accurate long-read transcriptome sequencing at single-cell level is required to decipher the spectrum of protein expressions in mammalian organisms. In this report, we developed a synthetic long-read single-cell sequencing technology based on LOOPSeq technique. We applied this technology to analyze 447 transcriptomes of hepatocellular carcinoma (HCC) and benign liver from an individual. Through Uniform Manifold Approximation and Projection analysis, we identified a panel of mutation mRNA isoforms highly specific to HCC cells. The evolution pathways that led to the hyper-mutation clusters in single human leukocyte antigen molecules were identified. Novel fusion transcripts were detected. The combination of gene expressions, fusion gene transcripts, and mutation gene expressions significantly improved the classification of liver cancer cells versus benign hepatocytes. In conclusion, LOOPSeq single-cell technology may hold promise to provide a new level of precision analysis on the mammalian transcriptome.

Identifiants

pubmed: 38206124
doi: 10.7554/eLife.87607
pii: 87607
doi:
pii:

Substances chimiques

Protein Isoforms 0

Banques de données

GEO
['GSE223743']

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NCI NIH HHS
ID : 1R56CA229262-01
Pays : United States
Organisme : NIDDK NIH HHS
ID : P30- DK120531-01
Pays : United States
Organisme : NIH HHS
ID : UL1TR001857 and S10OD028483
Pays : United States

Informations de copyright

© 2023, Liu et al.

Déclaration de conflit d'intérêts

SL, YY, BR, WW, AO, AS, JL No competing interests declared, TB He is an employee of Element Biosciences, Inc, CO She is an employee of Element Biosciences, Inc, MS MS is an employee of Element Biosciences, Inc

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Auteurs

Silvia Liu (S)

Department of Pathology, University of Pittsburgh, Pittsburgh, United States.
High Throughput Genome Center, University of Pittsburgh, Pittsburgh, United States.
Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States.

Yan-Ping Yu (YP)

Department of Pathology, University of Pittsburgh, Pittsburgh, United States.
High Throughput Genome Center, University of Pittsburgh, Pittsburgh, United States.
Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States.

Bao-Guo Ren (BG)

Department of Pathology, University of Pittsburgh, Pittsburgh, United States.
High Throughput Genome Center, University of Pittsburgh, Pittsburgh, United States.
Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States.

Tuval Ben-Yehezkel (T)

Element Biosciences Inc, San Diego, United States.

Caroline Obert (C)

Element Biosciences Inc, San Diego, United States.

Mat Smith (M)

Element Biosciences Inc, San Diego, United States.

Wenjia Wang (W)

Biostatistics, University of Pittsburgh, Pittsburgh, United States.

Alina Ostrowska (A)

Department of Pathology, University of Pittsburgh, Pittsburgh, United States.
Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States.

Alejandro Soto-Gutierrez (A)

Department of Pathology, University of Pittsburgh, Pittsburgh, United States.
Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States.

Jian-Hua Luo (JH)

Department of Pathology, University of Pittsburgh, Pittsburgh, United States.
High Throughput Genome Center, University of Pittsburgh, Pittsburgh, United States.
Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States.

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