Mosaicism in Preimplantation Human Embryos: When Chromosomal Abnormalities Are the Norm

McCoy, Rajiv C.

doi:10.1016/j.tig.2017.04.001

Cited by 186 publications

(168 citation statements)

References 112 publications

(172 reference statements)

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“…Such mitotic aneuploidies may propagate to descendant cells in a clonal manner and may also contribute to fitness variation. While severe chromosomal mosaicism is lethal to early embryos (McCoy et al 2015b;Ottolini et al 2017) , low levels of mosaicism appear compatible, and perhaps even common, with live birth (Greco et al 2015;McCoy 2017) .…”

Section: Introductionmentioning

confidence: 99%

Single-cell analysis of human embryos reveals diverse patterns of aneuploidy and mosaicism

Starostik

Sosina

McCoy

2020

Preprint

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Less than half of human zygotes survive to live birth, primarily due to aneuploidies of meiotic or mitotic origin. Mitotic errors lead to chromosomal mosaicism, defined by multiple cell lineages with distinct chromosome complements. The incidence and fitness consequences of chromosomal mosaicism in human embryos remain controversial, with most previous studies based on bulk DNA assays or comparisons of multiple biopsies of a few embryonic cells. Single-cell genomic data provide an opportunity to quantify mosaicism on an embryo-wide scale. To this end, we extended an approach to infer aneuploidies based on chromosome dosage-associated changes in gene expression by integrating signatures of allelic imbalance. We applied this method to published single-cell RNA sequencing data from 74 disaggregated human embryos, spanning the morula to blastocyst stages. Our analysis revealed widespread mosaic aneuploidies across preimplantation development, with 59 of 74 (80%) embryos harboring at least one aneuploid cell (1% FDR). By clustering copy number calls, we reconstructed histories of chromosome mis-segregation, distinguishing meiotic and early mitotic errors from those occurring after lineage differentiation. We observed no significant enrichment of aneuploid cells in the trophectoderm compared to the inner cell mass, though we do detect such an enrichment in published data from later post-implantation stages. Finally, we observed that aneuploid cells exhibit upregulation of immune response genes, as well as downregulation of genes involved in proliferation, metabolism, and protein processing, consistent with stress responses previously documented in other stages and systems. Together, our work provides a high-resolution view of aneuploidy in preimplantation embryos and supports the conclusion that low-level mosaicism is a common feature of early human development.

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Section: Introductionmentioning

confidence: 99%

Single-cell analysis of human embryos reveals diverse patterns of aneuploidy and mosaicism

Starostik

Sosina

McCoy

2020

Preprint

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“…This type of analysis can also identify sex chromosome mosaicism (Johnson et al 2010;Fragouli 792 et al 2011;McCoy 2017) and large structural variants involving the sex chromosomes. In the 793 results section we have shown that mosaics are outliers from the four defined clusters 794 observed in the intensity based chromosome sex determination plot (Figure 1).…”

Section: Minimuga As a Tool For Discovery 781mentioning

confidence: 99%

Content and performance of the MiniMUGA genotyping array, a new tool to improve rigor and reproducibility in mouse research

Sigmon¹,

Blanchard²,

Baric³

et al. 2020

Preprint

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The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well annotated genome, wealth of genetic resources and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost effective, informative and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole genome sequencing. Here we describe the content and performance of a new Mouse Universal Genotyping Array (MUGA). MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: 1) chromosomal sex determination, 2) discrimination between substrains from multiple commercial vendors, 3) diagnostic SNPs for popular laboratory strains, 4) detection of constructs used in genetically engineered mice, and 5) an easy to interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA we genotyped 6,899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived and recombinant inbred lines. Here we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, the extension of the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. There is preliminary but striking evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the main stock for a significant action of the genotyped inbred samples. We conclude that MiniMUGA is a valuable platform for genetic QC and important new tool to the increase rigor and reproducibility of mouse research.

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“…These repetitive arrays and the flanking 5 segments, together the Centromere Proximal Regions (CPRs), play critical roles in the integrity of mitotic and meiotic inheritance (2). In somatic tissues, chromosome instability, including loss and gain of chromosomes, plays large and complex roles in aging, cancer (3), and human embryonic survival (4). Sequence variation in CPRs can affect meiotic pairing (3,4), kinetochore formation (5,6) and nonrandom segregation (3,4,6).…”

Section: Main Textmentioning

confidence: 99%

“…In somatic tissues, chromosome instability, including loss and gain of chromosomes, plays large and complex roles in aging, cancer (3), and human embryonic survival (4). Sequence variation in CPRs can affect meiotic pairing (3,4), kinetochore formation (5,6) and nonrandom segregation (3,4,6). Aneuploidy in the germline, typically 10 arising during meiosis, is a large component of genetic disease (9).…”

Section: Main Textmentioning

confidence: 99%

Haplotypes spanning centromeric regions reveal persistence of large blocks of archaic DNA

Langley

Miga

Karpen

et al. 2018

Preprint

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Despite critical roles in chromosome segregation and disease, the repetitive structure and vast 15 size of centromeres and their surrounding heterochromatic regions impede studies of genomic variation. We report here large-scale haplotypes (cenhaps) in humans that span the centromereproximal regions of all metacentric chromosomes, including the arrays of highly repeated αsatellites on which centromeres form. Cenhaps reveal surprisingly deep diversity, including entire introgressed Neanderthal centromeres and equally ancient lineages among Africans. These 20 centromere-spanning haplotypes contain variants, including large differences in α-satellite DNA

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Mosaicism in Preimplantation Human Embryos: When Chromosomal Abnormalities Are the Norm

Cited by 186 publications

References 112 publications

Single-cell analysis of human embryos reveals diverse patterns of aneuploidy and mosaicism

Single-cell analysis of human embryos reveals diverse patterns of aneuploidy and mosaicism

Content and performance of the MiniMUGA genotyping array, a new tool to improve rigor and reproducibility in mouse research

Haplotypes spanning centromeric regions reveal persistence of large blocks of archaic DNA

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