scMitoMut for calling mitochondrial lineage-related mutations in single cells

Tracing cell lineages has become a valuable tool for studying biological processes. Among the available tools for human data, mitochondrial DNA (mtDNA) has a high potential due to its ability to be used in conjunction with single-cell chromatin accessibility data, giving access to the cell phenotype...

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Vydáno v:Briefings in bioinformatics Ročník 26; číslo 1
Hlavní autoři: Sun, Wenjie, van Ginneken, Daphne, Perié, Leïla
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Oxford University Press (OUP) 22.11.2024
Oxford University Press
Témata:
Cell Lineage - genetics
Colorectal Neoplasms - genetics
DNA, Mitochondrial - genetics
Humans
Life Sciences
Mitochondria - genetics
Mutation
Problem Solving Protocol
Single-Cell Analysis - methods
Software
single-cell sequencing
mitochondrial mutation
lineage tracing
mitochondrial mutation lineage tracing single-cell sequencing
ISSN:1467-5463, 1477-4054, 1477-4054
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Shrnutí:Tracing cell lineages has become a valuable tool for studying biological processes. Among the available tools for human data, mitochondrial DNA (mtDNA) has a high potential due to its ability to be used in conjunction with single-cell chromatin accessibility data, giving access to the cell phenotype. Nonetheless, the existing mutation calling tools are ill-equipped to deal with the polyploid nature of the mtDNA and lack a robust statistical framework. Here we introduce scMitoMut, an innovative R package that leverages statistical methodologies to accurately identify mitochondrial lineage-related mutations at the single-cell level. scMitoMut assigns a mutation quality q-value based on beta-binomial distribution to each mutation at each locus within individual cells, ensuring higher sensitivity and precision of lineage-related mutation calling in comparison to current methodologies. We tested scMitoMut using single-cell DNA sequencing, single-cell transposase-accessible chromatin (scATAC) sequencing, and 10× Genomics single-cell multiome datasets. Using a single-cell DNA sequencing dataset from a mixed population of cell lines, scMitoMut demonstrated superior sensitivity in identifying a small proportion of cancer cell line compared to existing methods. In a human colorectal cancer scATAC dataset, scMitoMut identified more mutations than state-of-the-art methods. Applied to 10× Genomics multiome datasets, scMitoMut effectively measured the lineage distance in cells from blood or brain tissues. Thus, the scMitoMut is a freely available, and well-engineered toolkit (https://www.bioconductor.org/packages/devel/bioc/html/scMitoMut.html) for mtDNA mutation calling with high memory and computational efficiency. Consequently, it will significantly advance the application of single-cell sequencing, facilitating the precise delineation of mitochondrial mutations for lineage-tracing purposes in development, tumour, and stem cell biology.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1467-5463
1477-4054
1477-4054
DOI:10.1093/bib/bbaf072