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Single-cell RNA-seq variant analysis for exploration of genetic heterogeneity in cancer
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.ORCID iD: 0000-0003-0492-9960
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.ORCID iD: 0000-0001-8993-048X
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Systems Biology.ORCID iD: 0000-0001-6990-1905
2019 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 9524Article in journal (Refereed) Published
Abstract [en]

Inter-and intra-tumour heterogeneity is caused by genetic and non-genetic factors, leading to severe clinical implications. High-throughput sequencing technologies provide unprecedented tools to analyse DNA and RNA in single cells and explore both genetic heterogeneity and phenotypic variation between cells in tissues and tumours. Simultaneous analysis of both DNA and RNA in the same cell is, however, still in its infancy. We have thus developed a method to extract and analyse information regarding genetic heterogeneity that affects cellular biology from single-cell RNA-seq data. The method enables both comparisons and clustering of cells based on genetic variation in single nucleotide variants, revealing cellular subpopulations corroborated by gene expression-based methods. Furthermore, the results show that lymph node metastases have lower levels of genetic heterogeneity compared to their original tumours with respect to variants affecting protein function. The analysis also revealed three previously unknown variants common across cancer cells in glioblastoma patients. These results demonstrate the power and versatility of scRNA-seq variant analysis and highlight it as a useful complement to already existing methods, enabling simultaneous investigations of both gene expression and genetic variation.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP , 2019. Vol. 9, article id 9524
National Category
Medical Genetics
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URN: urn:nbn:se:kth:diva-255413DOI: 10.1038/s41598-019-45934-1ISI: 000473417000015PubMedID: 31267007Scopus ID: 2-s2.0-85069268174OAI: oai:DiVA.org:kth-255413DiVA, id: diva2:1342873
Note

QC 20190814

Available from: 2019-08-14 Created: 2019-08-14 Last updated: 2019-10-16Bibliographically approved

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Fasterius, ErikUhlén, MathiasAl-Khalili Szigyarto, Cristina

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