A direct comparison of interphase FISH versus low-coverage single cell sequencing to detect aneuploidy reveals respective strengths and weaknesses

Quantitative FISHing: Implications for Chromosomal Analysis

Quantifying signals substantially increases the efficiency of fluorescence in situ hybridization (FISH). Quantitative FISH analysis or QFISHing may be useful for differentiation between chromosome loss and chromosomal associations, detection of amplification of chromosomal loci, and/or quantification of chromosomal heteromorphisms (chromosomal DNAs). The latter is applicable to uncovering the parental origin of chromosomes, which is an important FISH application in genome research. In summary, one may acknowledge that QFISHing has a variety of applications in cancer chromosome research. Accordingly, a protocol for this technique is certainly required. Here, QFISHing protocol is described step-by-step.

Chromosome instability and aneuploidy in the mammalian brain

This review investigates the role of aneuploidy and chromosome instability (CIN) in the aging brain. Aneuploidy refers to an abnormal chromosomal count, deviating from the normal diploid set. It can manifest as either a deficiency or excess of chromosomes. CIN encompasses a broader range of chromosomal alterations, including aneuploidy as well as structural modifications in DNA. We provide an overview of the state-of-the-art methodologies utilized for studying aneuploidy and CIN in non-tumor somatic tissues devoid of clonally expanded populations of aneuploid cells.CIN and aneuploidy, well-established hallmarks of cancer cells, are also associated with the aging process. In non-transformed cells, aneuploidy can contribute to functional impairment and developmental disorders. Despite the importance of understanding the prevalence and specific consequences of aneuploidy and CIN in the aging brain, these aspects remain incompletely understood, emphasizing the need for further scientific investigations.This comprehensive review consolidates the present understanding, addresses discrepancies in the literature, and provides valuable insights for future research efforts.

Somatic copy number variant load in neurons of healthy controls and Alzheimer's disease patients

The possible role of somatic copy number variations (CNVs) in Alzheimer's disease (AD) aetiology has been controversial. Although cytogenetic studies suggested increased CNV loads in AD brains, a recent single-cell whole-genome sequencing (scWGS) experiment, studying frontal cortex brain samples, found no such evidence. Here we readdressed this issue using low-coverage scWGS on pyramidal neurons dissected via both laser capture microdissection (LCM) and fluorescence activated cell sorting (FACS) across five brain regions: entorhinal cortex, temporal cortex, hippocampal CA1, hippocampal CA3, and the cerebellum. Among reliably detected somatic CNVs identified in 1301 cells obtained from the brains of 13 AD patients and 7 healthy controls, deletions were more frequent compared to duplications. Interestingly, we observed slightly higher frequencies of CNV events in cells from AD compared to similar numbers of cells from controls (4.1% vs. 1.4%, or 0.9% vs. 0.7%, using different filtering approaches), although the differences were not statistically significant. On the technical aspects, we observed that LCM-isolated cells show higher within-cell read depth variation compared to cells isolated with FACS. To reduce within-cell read depth variation, we proposed a principal component analysis-based denoising approach that significantly improves signal-to-noise ratios. Lastly, we showed that LCM-isolated neurons in AD harbour slightly more read depth variability than neurons of controls, which might be related to the reported hyperploid profiles of some AD-affected neurons.

FISHing for Chromosome Instability and Aneuploidy in the Alzheimer's Disease Brain

Fluorescence in situ hybridization (FISH) is the method of choice for visualizing chromosomal DNA in post-mitotic cells. The availability of chromosome-enumeration (centromeric), site-specific, and multicolor-banding DNA probes offers opportunities to uncover genomic changes, at the chromosomal level, in single interphase nuclei. Alzheimer's disease (AD) has been associated repeatedly with (sub)chromosome instability and aneuploidy, likely affecting the brain. Although the types and rates of chromosome instability in the AD brain remain a matter of debate, molecular cytogenetic analysis of brain cells appears to be important for uncovering mechanisms of neurodegeneration. Here, we describe a FISH protocol for studying chromosome instability and aneuploidy in the AD brain.

Reducing the aneuploid cell burden - cell competition and the ribosome connection

Aneuploidy, the gain or loss of chromosomes, is the cause of birth defects and miscarriage and is almost ubiquitous in cancer cells. Mosaic aneuploidy causes cancer predisposition, as well as age-related disorders. Despite the cell-intrinsic mechanisms that prevent aneuploidy, sporadic aneuploid cells do arise in otherwise normal tissues. These aneuploid cells can differ from normal cells in the copy number of specific dose-sensitive genes, and may also experience proteotoxic stress associated with mismatched expression levels of many proteins. These differences may mark aneuploid cells for recognition and elimination. The ribosomal protein gene dose in aneuploid cells could be important because, in Drosophila, haploinsufficiency for these genes leads to elimination by the process of cell competition. Constitutive haploinsufficiency for human ribosomal protein genes causes Diamond Blackfan anemia, but it is not yet known whether ribosomal protein gene dose contributes to aneuploid cell elimination in mammals. In this Review, we discuss whether cell competition on the basis of ribosomal protein gene dose is a tumor suppressor mechanism, reducing the accumulation of aneuploid cells. We also discuss how this might relate to the tumor suppressor function of p53 and the p53-mediated elimination of aneuploid cells from murine embryos, and how cell competition defects could contribute to the cancer predisposition of Diamond Blackfan anemia.

Longer metaphase and fewer chromosome segregation errors in modern human than Neanderthal brain development

Since the ancestors of modern humans separated from those of Neanderthals, around 100 amino acid substitutions spread to essentially all modern humans. The biological significance of these changes is largely unknown. Here, we examine all six such amino acid substitutions in three proteins known to have key roles in kinetochore function and chromosome segregation and to be highly expressed in the stem cells of the developing neocortex. When we introduce these modern human-specific substitutions in mice, three substitutions in two of these proteins, KIF18a and KNL1, cause metaphase prolongation and fewer chromosome segregation errors in apical progenitors of the developing neocortex. Conversely, the ancestral substitutions cause shorter metaphase length and more chromosome segregation errors in human brain organoids, similar to what we find in chimpanzee organoids. These results imply that the fidelity of chromosome segregation during neocortex development improved in modern humans after their divergence from Neanderthals.

High throughput single-cell genome sequencing gives insights into the generation and evolution of mosaic aneuploidy in Leishmania donovani

Leishmania, a unicellular eukaryotic parasite, is a unique model for aneuploidy and cellular heterogeneity, along with their potential role in adaptation to environmental stresses. Somy variation within clonal populations was previously explored in a small subset of chromosomes using fluorescence hybridization methods. This phenomenon, termed mosaic aneuploidy (MA), might have important evolutionary and functional implications but remains under-explored due to technological limitations. Here, we applied and validated a high throughput single-cell genome sequencing method to study for the first time the extent and dynamics of whole karyotype heterogeneity in two clonal populations of Leishmania promastigotes representing different stages of MA evolution in vitro. We found that drastic changes in karyotypes quickly emerge in a population stemming from an almost euploid founder cell. This possibly involves polyploidization/hybridization at an early stage of population expansion, followed by assorted ploidy reduction. During further stages of expansion, MA increases by moderate and gradual karyotypic alterations, affecting a defined subset of chromosomes. Our data provide the first complete characterization of MA in Leishmania and pave the way for further functional studies.

Reconstructing and counting genomic fragments through tagmentation-based haploid phasing

Single-cell sequencing provides a new level of granularity in studying the heterogeneous nature of cancer cells. For some cancers, this heterogeneity is the result of copy number changes of genes within the cellular genomes. The ability to accurately determine such copy number changes is critical in tracing and understanding tumorigenesis. Current single-cell genome sequencing methodologies infer copy numbers based on statistical approaches followed by rounding decimal numbers to integer values. Such methodologies are sample dependent, have varying calling sensitivities which heavily depend on the sample’s ploidy and are sensitive to noise in sequencing data. In this paper we have demonstrated the concept of integer-counting by using a novel bioinformatic algorithm built on our library construction chemistry in order to detect the discrete nature of the genome.

A technology of a different sort: microraft arrays

A common procedure performed throughout biomedical research is the selection and isolation of biological entities such as organelles, cells and organoids from a mixed population. In this review, we describe the development and application of microraft arrays, an analysis and isolation platform which enables a vast range of criteria and strategies to be used when separating biological entities. The microraft arrays are comprised of elastomeric microwells with detachable polymer bases (microrafts) that act as capture and culture sites as well as supporting carriers during cell isolation. The technology is elegant in its simplicity and can be implemented for samples possessing tens to millions of objects yielding a flexible platform for applications such as single-cell RNA sequencing, subcellular organelle capture and assay, high-throughput screening and development of CRISPR gene-edited cell lines, and organoid manipulation and selection. The transparent arrays are compatible with a multitude of imaging modalities enabling selection based on 2D or 3D spatial phenotypes or temporal properties. Each microraft can be individually isolated on demand with retention of high viability due to the near zero hydrodynamic stress imposed upon the cells during microraft release, capture and deposition. The platform has been utilized as a simple manual add-on to a standard microscope or incorporated into fully automated instruments that implement state-of-the-art imaging algorithms and machine learning. The vast array of selection criteria enables separations not possible with conventional sorting methods, thus garnering widespread interest in the biological and pharmaceutical sciences.

Pathogenic Mechanisms of Somatic Mutation and Genome Mosaicism in Aging

Age-related accumulation of postzygotic DNA mutations results in tissue genetic heterogeneity known as somatic mosaicism. Although implicated in aging as early as the 1950s, somatic mutations in normal tissue have been difficult to study because of their low allele fractions. With the recent emergence of cost-effective high-throughput sequencing down to the single-cell level, enormous progress has been made in our capability to quantitatively analyze somatic mutations in human tissue in relation to aging and disease. Here we first review how recent technological progress has opened up this field, providing the first broad sets of quantitative information on somatic mutations in vivo necessary to gain insight into their possible causal role in human aging and disease. We then propose three major mechanisms that can lead from accumulated de novo mutations across tissues to cell functional loss and human disease.

Aneuploidy: An Opportunity Within Single-Cell RNA Sequencing Analysis

Single-cell sequencing data has transformed the understanding of biological heterogeneity. While many flavors of single-cell sequencing have been developed, single-cell RNA sequencing (scRNA-seq) is currently the most prolific form in published literature. Bioinformatic analysis of differential biology within the population of cells studied relies on inferences and grouping of cells due to the spotty nature of data within individual cell scRNA-seq gene counts. One biologically relevant variable is readily inferred from scRNA-seq gene count tables regardless of individual gene representation within single cells: aneuploidy. Since hundreds of genes are present on chromosome arms, high-quality inferences of aneuploidy can be made from scRNA-seq datasets. This viewpoint summarizes how utilization of these bioinformatic pipelines can benefit scRNA-seq studies, particularly in oncology wherein aneuploidy is both rampant and a hallmark of the studied disease. Awareness and use of these analytical pipelines will improve each field's ability to understand the studied diseases. Authors are encouraged to attempt these aneuploid analyses when reporting scRNA-seq data, much like copy-number variants are commonly reported in bulk genome sequencing data.

Single-cell analysis of copy-number alterations in serous ovarian cancer reveals substantial heterogeneity in both low- and high-grade tumors

Unusually high aneuploidy is a hallmark of epithelial serous ovarian cancer (SOC). Previous analyses have focused on aneuploidy on average across all tumor cells. With the expansion of single-cell sequencing technologies, however, an analysis of copy number heterogeneity cell-to-cell is now technically feasible. Here, we describe an analysis of single-cell RNA sequencing (scRNA-seq) data to infer arm-level aneuploidy in individual serous ovarian cancer cells. By first clustering high-quality sequenced epithelial versus non-epithelial cells, high-confidence tumor cell populations were identified. InferCNV was used to predict segmented copy-number alterations (CNAs), which were then used to determine arm-level aneuploidy at the single-cell level. Control comparisons of normal cells to normal cells showed zero arm-level aneuploidy, whereas a median of four aneuploid events were detectable in cancer cells. A heterogeneity analysis of high-grade tumor cells compared to low-grade tumor cells showed similar levels of cell-to-cell variation between cancer grades. Metastatic tumors potentially showed selection pressure with reduced cell-to-cell variation compared to cells from primary tumors. Minor cell populations with CNAs similar to metastatic cells were identified within the matched primary tumors. Taken together, these results provide a minimum estimate for single-cell aneuploidy in serous ovarian cancer and demonstrate the utility of single-cell sequencing for CNA analysis.

Aneuploid IMR90 cells induced by depletion of pRB, DNMT1 and MAD2 show a common gene expression signature

Chromosome segregation defects lead to aneuploidy which is a major feature of solid tumors. How diploid cells face chromosome mis-segregation and how aneuploidy is tolerated in tumor cells are not completely defined yet. Thus, an important goal of cancer genetics is to identify gene networks that underlie aneuploidy and are involved in its tolerance. To this aim, we induced aneuploidy in IMR90 human primary cells by depleting pRB, DNMT1 and MAD2 and analyzed their gene expression profiles by microarray analysis. Bioinformatic analysis revealed a common gene expression profile of IMR90 cells that became aneuploid. Gene Set Enrichment Analysis (GSEA) also revealed gene-sets/pathways that are shared by aneuploid IMR90 cells that may be exploited for novel therapeutic approaches in cancer. Furthermore, Protein-Protein Interaction (PPI) network analysis identified TOP2A and KIF4A as hub genes that may be important for aneuploidy establishment.