Chromosome segregation errors during cell divisions generate aneuploidies and micronuclei, which can undergo extensive chromosomal rearrangements such as chromothripsis1-5. Selective pressures then shape distinct aneuploidy and rearrangement patterns-for example, in cancer6,7-but it is unknown whether initial biases in segregation errors and micronucleation exist for particular chromosomes. Using single-cell DNA sequencing8 after an error-prone mitosis in untransformed, diploid cell lines and organoids, we show that chromosomes have different segregation error frequencies that result in non-random aneuploidy landscapes. Isolation and sequencing of single micronuclei from these cells showed that mis-segregating chromosomes frequently also preferentially become entrapped in micronuclei. A similar bias was found in naturally occurring micronuclei of two cancer cell lines. We find that segregation error frequencies of individual chromosomes correlate with their location in the interphase nucleus, and show that this is highest for peripheral chromosomes behind spindle poles. Randomization of chromosome positions, Cas9-mediated live tracking and forced repositioning of individual chromosomes showed that a greater distance from the nuclear centre directly increases the propensity to mis-segregate. Accordingly, chromothripsis in cancer genomes9 and aneuploidies in early development10 occur more frequently for larger chromosomes, which are preferentially located near the nuclear periphery. Our findings reveal a direct link between nuclear chromosome positions, segregation error frequencies and micronucleus content, with implications for our understanding of tumour genome evolution and the origins of specific aneuploidies during development.
Journal article
Nature
07/2022
607
604 - 609
Aneuploidy, CRISPR-Associated Protein 9, Cell Line, Cell Line, Tumor, Chromosome Positioning, Chromosome Segregation, Chromosomes, Chromothripsis, Growth and Development, Humans, Interphase, Micronuclei, Chromosome-Defective, Mitosis, Neoplasms, Organoids, Sequence Analysis, DNA, Single-Cell Analysis