Diane M Bushman’s research while affiliated with The Scripps Research Institute and other places

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Publications (9)


Figure 1: Methodologies used in assessing genomically mosaic AD. (A) Neuronal nuclei were isolated from the prefrontal cortex and cerebellum of postmortem human brain (see ‘Materials and methods’ for samples used) as described (Westra et al., 2008). (B) Nuclear DNA was stained with propidium iodide (PI) and DNA content was quantified using flow cytometric analysis. (C) APP copy number variations were analyzed in small populations of nuclei (∼75 genomes) using custom primers for exon 14 of APP. (D) Single-cell qPCR assessed APP copy number variations in individual neuronal nuclei via TaqMan probes and a modified Biomark integrated fluidic chip system (Fluidigm Corporation, South San Francisco). (E) FISH paints against the whole q arm of chromosome 21 and a point probe against a region on the q arm of 21 (21q22.13-q22.2) were used to double-label and call aneusomies in AD samples. (F) Peptide nucleic acid (PNA) FISH was combined with super resolution microscopy for threshold detection of APP copy number above ∼2 occurring at a single locus. DOI: http://dx.doi.org/10.7554/eLife.05116.003
Figure 2—figure supplement 1.
DNA content shows no correlation with age or post-mortem index (PMI).
(A) Comparison of mean skew values for each sample group, skew determined as: (Mean − Mode/Standard Deviation of the diploid DNA content peak). (B) No correlation was observed between DNA content and Braak score. (C–E) No correlation was observed between DNA content and age across all brains analyzed. (F–H) No correlation was observed between DNA content and post-mortem index across all brains analyzed.
Figure 2: AD cortical nuclei show increased DNA content variation (DCV) by flow cytometry. (A) Histogram displaying gating parameters used in sorting ‘high’ and ‘low’ DNA content populations for validation of DNA content. (B) Validation of DNA content analyses using semi-quantitative MDA whole-genome amplification (WGA) on ‘high’ and ‘low’ DNA content populations of 1000, 500, and 100 nuclei. (C and D) Representative DNA content histograms for lymphocytes (LYM), AD cerebellum (CBL), and AD prefrontal cortex (CTX). Each colored histogram represents a separate sample in each set; CTX and CBL samples are from paired brains. Chicken erythrocyte nuclei (CEN) were used as internal calibration controls. (E) Representative orthogonal view of DNA content vs forward scatter width (FSC-W). For each brain sample, the area to the right of the vertical line indicates a DNA content increase of the population of nuclei. AD-6 CTX is a representative right-hand peak shift and AD-7 is a representative right-hand shoulder (see A for more examples). (F) DNA content changes for all human LYM, ND, and AD brain samples examined (AD CTX N = 32, AD CBL N = 16, LYM N = 15 [20 meta analysis], ND CTX = 21 [36 meta analysis], ND CBL = 11 [12 meta analysis]). Red bars denote average for each group relative to lymphocytes. Averages are as follows (including metadata from Westra et al. (2010)): AD CTX 8.219%; AD CBL −0.1104%; LYM −0.2915%; ND CTX 2.239%; ND CBL −3.358%. (G) DNA content changes of the current study (AVOVA p < 0.0001). (H) DNA content changes of the current study combined with metadata from Westra et al. (2010) (ANOVA p < 0.0001). (I) Comparison of mean coefficient of variation (CV statistic from FlowJo of the population, included metadata from Westra et al., 2010) demonstrates that there is an average increase in the variation of AD samples (ANOVA p < 0.0001). *p = 0.05, **p = 0.01, ***p = 0.001, ****p < 0.0001, See —source data 1 for exact p values. See —figure supplement 1 for age, PMI and Braak score correlations. See —figure supplement 2 for control of nuclear size analysis. DOI: http://dx.doi.org/10.7554/eLife.05116.004 —source data 1. DNA Index (DI) and percent change values and statistics.DOI: http://dx.doi.org/10.7554/eLife.05116.005[elife05116s001.docx] DNA Index (DI) and percent change values and statistics. DOI: http://dx.doi.org/10.7554/eLife.05116.005
Figure 2.
AD cortical nuclei show increased DNA content variation (DCV) by flow cytometry.
(A) Histogram displaying gating parameters used in sorting ‘high’ and ‘low’ DNA content populations for validation of DNA content. (B) Validation of DNA content analyses using semi-quantitative MDA whole-genome amplification (WGA) on ‘high’ and ‘low’ DNA content populations of 1000, 500, and 100 nuclei. (C and D) Representative DNA content histograms for lymphocytes (LYM), AD cerebellum (CBL), and AD prefrontal cortex (CTX). Each colored histogram represents a separate sample in each set; CTX and CBL samples are from paired brains. Chicken erythrocyte nuclei (CEN) were used as internal calibration controls. (E) Representative orthogonal view of DNA content vs forward scatter width (FSC-W). For each brain sample, the area to the right of the vertical line indicates a DNA content increase of the population of nuclei. AD-6 CTX is a representative right-hand peak shift and AD-7 is a representative right-hand shoulder (see Figure 3A for more examples). (F) DNA content changes for all human LYM, ND, and AD brain samples examined (AD CTX N = 32, AD CBL N = 16, LYM N = 15 [20 meta analysis], ND CTX = 21 [36 meta analysis], ND CBL = 11 [12 meta analysis]). Red bars denote average for each group relative to lymphocytes. Averages are as follows (including metadata from Westra et al. (2010)): AD CTX 8.219%; AD CBL −0.1104%; LYM −0.2915%; ND CTX 2.239%; ND CBL −3.358%. (G) DNA content changes of the current study (AVOVA p < 0.0001). (H) DNA content changes of the current study combined with metadata from Westra et al. (2010) (ANOVA p < 0.0001). (I) Comparison of mean coefficient of variation (CV statistic from FlowJo of the population, included metadata from Westra et al., 2010) demonstrates that there is an average increase in the variation of AD samples (ANOVA p < 0.0001). *p = 0.05, **p = 0.01, ***p = 0.001, ****p < 0.0001, See Figure 2—source data 1 for exact p values. See Figure 2—figure supplement 1 for age, PMI and Braak score correlations. See Figure 2—figure supplement 2 for control of nuclear size analysis.
Figure 2—figure supplement 2.
Analysis of nuclear size and DNA content.
(A–C) Representative flow cytometry scatter plots of nuclei. (A) Lymphocytes (LYM), (B) CTX nuclei, (C) CBL nuclei. (D) Overlay of red boxes shown in (A–C), demonstrating that cortical nuclei similar in size to LYM and CBL consistently display a DNA content shift.

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Genomic mosaicism with increased amyloid precursor protein ( APP ) gene copy number in single neurons from sporadic Alzheimer's disease brains
  • Article
  • Full-text available

February 2015

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239 Reads

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99 Citations

eLife

Diane M Bushman

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Gwendolyn E Kaeser

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[...]

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Jerold Chun

Previous reports have shown that individual neurons of the brain can display somatic genomic mosaicism of unknown function. In this study, we report altered genomic mosaicism in single, sporadic Alzheimer's disease (AD) neurons characterized by increases in DNA content and amyloid precursor protein (APP) gene copy number. AD cortical nuclei displayed large variability with average DNA content increases of ∼8% over non-diseased controls that were unrelated to trisomy 21. Two independent single-cell copy number analyses identified amplifications at the APP locus. The use of single-cell qPCR identified up to 12 copies of APP in sampled neurons. Peptide nucleic acid (PNA) probes targeting APP, combined with super-resolution microscopy detected primarily single fluorescent signals of variable intensity that paralleled single-cell qPCR analyses. These data identify somatic genomic changes in single neurons, affecting known and unknown loci, which are increased in sporadic AD, and further indicate functionality for genomic mosaicism in the CNS. DOI: http://dx.doi.org/10.7554/eLife.05116.001

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Figure 1: MIDAS. (a) Each slide contains 16 arrays of 255 microwells each. Cells, lysis solution, denaturing buffer, neutralization buffer and MDA master mix were each added to the microwells with a single pipette pump. Amplicon growth was then visualized with a fluorescent microscope using a real-time MDA system. Microwells showing increasing fluorescence over time were positive amplicons. The amplicons were extracted with fine glass pipettes attached to a micromanipulation system. (b) Scanning electron microscopy of a single E. coli cell displayed at different magnifications. This particular well contains only one cell, and most wells observed also contained no more than one cell. (c) A custom microscope incubation chamber was used for real time MDA. The chamber was temperature and humidity controlled to mitigate evaporation of reagents. Additionally, it prevented contamination during amplicon extraction because the micromanipulation system was self-contained. An image of the entire microwell array is also shown, as well as a micropipette probing a well. (d) Complex three-dimensional MDA amplicons were reduced to linear DNA using DNA polymerase I and Ampligase. This process substantially improved the complexity of the library during sequencing.
Figure 2: Depth of coverage of assembled contigs aligned to the reference E. coli genome. Three single E. coli cells were analyzed using MIDAS. Between 88% and 94% of the genome was assembled from 2–8 million paired-end 100-bp reads. Each colored circle is a histogram of the log2 of average depth of coverage across each assembled contig for one cell. Gaps are represented by blank whitespace in between colored contigs.
Figure 3: Genomic coverage of single cells amplified by MDA in a tube and by MIDAS. The observed multipeak profile for the MDA reactions implies that certain regions may have been amplified with exponentially greater bias compared to the majority of the genome. (a) Comparison of single E. coli cells amplified in a PCR tube for 10 h (top), 2 h (middle) and in a microwell (MIDAS) for 10 h (bottom). Genomic positions were consolidated into 1-kb bins (x axis), and were plotted against the log10 ratio (y axis) of genomic coverage (normalized to the mean). (b) Distribution of coverage of amplified single bacterial cells. The x axis shows the log10 ratio of genomic coverage normalized to the mean. (c) Comparison of single human cells amplified using traditional MDA in a PCR tube for 10 h (top) or in a microwell (MIDAS) for 10 h (middle) to a pool of unamplified human cells (bottom). Genomic positions were consolidated into variable bins of ~60 kb in size, previously determined to contain a similar read count28, and were plotted against the log10 ratio (y axis) of genomic coverage (normalized to the mean). (d) Distribution of coverage of amplified single mammalian cells. The x axis shows the log10 ratio of genomic coverage normalized to the mean.
Figure 4: Detection of CNVs. Genomic positions were consolidated into bins of ~60 kb in size which were previously determined to contain a similar read count28. Estimated copy numbers below were rounded to the nearest whole number. (a) CNVs in a Down syndrome single cell analyzed with MIDAS. The x axis shows genomic position. The y axis shows (on a log2 scale) the estimated copy number as a red line. The arrow indicates trisomy 21, which is clearly visible in this single cell. (b) CNVs in a Down syndrome single cell analyzed with traditional in-tube MDA. The x axis shows genomic position. The y axis shows (on a log2 scale) the estimated copy number as a red line. The arrow marks the expected region of trisomy 21, which is not detectable in these data. (c) CNVs in a Down syndrome single cell with trisomy 21 'spike-ins'. The x axis shows genomic position. The y axis shows (on a log2 scale) the estimated copy number as a red line. At each arrow, before CNV calling, data from a randomly determined 2 Mb section of trisomy chromosome 21 were computationally inserted into the genome, simulating a small gain-of-single-copy event. At each location, a CNV was called, showing that MIDAS can detect 2-Mb CNV accurately. (d) CNV in a Down syndrome single cell with trisomy 21 spike-ins. The x axis shows genomic position. The y axis shows (on a log2 scale) the estimated copy number as a red line. At each arrow, before CNV calling, data from a randomly determined 2 Mb section of trisomy chromosome 21 was computationally inserted into the genome, simulating a small gain-of-single-copy event.
Figure 5: Comparison of MIDAS to previously published data for in-tube MDA32, microfluidic MDA10 and MALBAC33 for diploid regions of pools of two sperm cells and diploid regions of a single SW480 cancer cell processed using MALBAC18. Genomic positions were consolidated into variable bins of ~60 kb in size previously determined to contain a similar read count28 and were plotted against the log10 ratio (y axis) of genomic coverage (normalized to the mean). For the cancer cell data, nondiploid regions have been masked out (white gaps between pink) to remove the bias generated by comparing a highly aneuploid cell to a primarily diploid cell.
Massively parallel polymerase cloning and genome sequencing of single cells using nanoliter microwells

November 2013

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355 Reads

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231 Citations

Nature Biotechnology

Genome sequencing of single cells has a variety of applications, including characterizing difficult-to-culture microorganisms and identifying somatic mutations in single cells from mammalian tissues. A major hurdle in this process is the bias in amplifying the genetic material from a single cell, a procedure known as polymerase cloning. Here we describe the microwell displacement amplification system (MIDAS), a massively parallel polymerase cloning method in which single cells are randomly distributed into hundreds to thousands of nanoliter wells and their genetic material is simultaneously amplified for shotgun sequencing. MIDAS reduces amplification bias because polymerase cloning occurs in physically separated, nanoliter-scale reactors, facilitating the de novo assembly of near-complete microbial genomes from single Escherichia coli cells. In addition, MIDAS allowed us to detect single-copy number changes in primary human adult neurons at 1- to 2-Mb resolution. MIDAS can potentially further the characterization of genomic diversity in many heterogeneous cell populations.


The Genomically Mosaic Brain: Aneuploidy and More in Neural Diversity and Disease

March 2013

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22 Reads

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95 Citations

Seminars in Cell and Developmental Biology

Genomically identical cells have long been assumed to comprise the human brain, with post-genomic mechanisms giving rise to its enormous diversity, complexity, and disease susceptibility. However, the identification of neural cells containing somatically generated mosaic aneuploidy-loss and/or gain of chromosomes from a euploid complement-and other genomic variations including LINE1 retrotransposons and regional patterns of DNA content variation (DCV), demonstrate that the brain is genomically heterogeneous. The precise phenotypes and functions produced by genomic mosaicism are not well understood, although the effects of constitutive aberrations, as observed in Down syndrome, implicate roles for defined mosaic genomes relevant to cellular survival, differentiation potential, stem cell biology, and brain organization. Here we discuss genomic mosaicism as a feature of the normal brain as well as a possible factor in the weak or complex genetic linkages observed for many of the most common forms of neurological and psychiatric diseases.


Aneuploid Cells Are Differentially Susceptible to Caspase-Mediated Death during Embryonic Cerebral Cortical Development

November 2012

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191 Reads

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56 Citations

The Journal of Neuroscience : The Official Journal of the Society for Neuroscience

Neural progenitor cells, neurons, and glia of the normal vertebrate brain are diversely aneuploid, forming mosaics of intermixed aneuploid and euploid cells. The functional significance of neural mosaic aneuploidy is not known; however, the generation of aneuploidy during embryonic neurogenesis, coincident with caspase-dependent programmed cell death (PCD), suggests that a cell's karyotype could influence its survival within the CNS. To address this hypothesis, PCD in the mouse embryonic cerebral cortex was attenuated by global pharmacological inhibition of caspases or genetic removal of caspase-3 or caspase-9. The chromosomal repertoire of individual brain cells was then assessed by chromosome counting, spectral karyotyping, fluorescence in situ hybridization, and DNA content flow cytometry. Reducing PCD resulted in markedly enhanced mosaicism that was comprised of increased numbers of cells with the following: (1) numerical aneuploidy (chromosome losses or gains); (2) extreme forms of numerical aneuploidy (>5 chromosomes lost or gained); and (3) rare karyotypes, including those with coincident chromosome loss and gain, or absence of both members of a chromosome pair (nullisomy). Interestingly, mildly aneuploid (<5 chromosomes lost or gained) populations remained comparatively unchanged. These data demonstrate functional non-equivalence of distinguishable aneuploidies on neural cell survival, providing evidence that somatically generated, cell-autonomous genomic alterations have consequences for neural development and possibly other brain functions.


Normal Human Pluripotent Stem Cell Lines Exhibit Pervasive Mosaic Aneuploidy

August 2011

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209 Reads

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70 Citations

Human pluripotent stem cell (hPSC) lines have been considered to be homogeneously euploid. Here we report that normal hPSC--including induced pluripotent--lines are karyotypic mosaics of euploid cells intermixed with many cells showing non-clonal aneuploidies as identified by chromosome counting, spectral karyotyping (SKY) and fluorescent in situ hybridization (FISH) of interphase/non-mitotic cells. This mosaic aneuploidy resembles that observed in progenitor cells of the developing brain and preimplantation embryos, suggesting that it is a normal, rather than pathological, feature of stem cell lines. The karyotypic heterogeneity generated by mosaic aneuploidy may contribute to the reported functional and phenotypic heterogeneity of hPSCs lines, as well as their therapeutic efficacy and safety following transplantation.



Neuronal DNA Content Variation (DCV) With Regional and Individual Differences in the Human Brain

October 2010

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171 Reads

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107 Citations

The Journal of Comparative Neurology

It is widely assumed that the human brain contains genetically identical cells through which postgenomic mechanisms contribute to its enormous diversity and complexity. The relatively recent identification of neural cells throughout the neuraxis showing somatically generated mosaic aneuploidy indicates that the vertebrate brain can be genomically heterogeneous (Rehen et al. [2001] Proc. Natl. Acad. Sci. U. S. A. 98:13361-13366; Rehen et al. [2005] J. Neurosci. 25:2176-2180; Yurov et al. [2007] PLoS ONE:e558; Westra et al. [2008] J. Comp. Neurol. 507:1944-1951). The extent of human neural aneuploidy is currently unknown because of technically limited sample sizes, but is reported to be small (Iourov et al. [2006] Int. Rev. Cytol. 249:143-191). During efforts to interrogate larger cell populations by using DNA content analyses, a surprising result was obtained: human frontal cortex brain cells were found to display "DNA content variation (DCV)" characterized by an increased range of DNA content both in cell populations and within single cells. On average, DNA content increased by approximately 250 megabases, often representing a substantial fraction of cells within a given sample. DCV within individual human brains showed regional variation, with increased prevalence in the frontal cortex and less variation in the cerebellum. Further, DCV varied between individual brains. These results identify DCV as a new feature of the human brain, encompassing and further extending genomic alterations produced by aneuploidy, which may contribute to neural diversity in normal and pathophysiological states, altered functions of normal and disease-linked genes, and differences among individuals.


Citations (6)


... Somatic APP gene recombination has been shown to occur mosaically in neurons in an age-dependent manner [47], increasing APP expression and, ultimately, Aβ levels. A variable APP copy number in neurons from sporadic AD patients has been reported and suggested to contribute to AD [48]. In ADAD, such recombination (if happening) could amplify mutant APP expression, potentially explaining the earlier-than-predicted onset in APP mutation carriers. ...

Reference:

Spectrum of γ-Secretase dysfunction as a unifying predictor of ADAD age at onset across PSEN1, PSEN2 and APP causal genes
Genomic mosaicism with increased amyloid precursor protein ( APP ) gene copy number in single neurons from sporadic Alzheimer's disease brains

eLife

... Several approaches have been developed to fulfill these requirements based on diverse immobilizing technologies, including active optical, acoustic, and electrical fields, [4][5][6][7][8][9] as well as passive hydrodynamic/mechanical constrictions and interface microengineering. [10][11][12][13][14][15] The combination of most tools above with microfluidics enhances the controllability and throughput of microscale cell capture during the manipulation process and has great potential in searching for novel and pioneering insights into single-cell omics. [16,17] Despite significant advances, the current approaches still have several challenges to overcome. ...

Massively parallel polymerase cloning and genome sequencing of single cells using nanoliter microwells

Nature Biotechnology

... To date, this is the most adequate technique or technological platform for visualizing genome changes in single cells at molecular resolutions [1,2]. There is solid evidence that FISH-based methods are highly applicable in microscopic chromosomal analysis in almost all human cell types (including cancer cells) [3][4][5][6][7]. Additionally, FISH-based chromosomal analysis is required for the definition of chromosome instability and molecular diagnosis of somatic chromosomal abnormalities [8][9][10]. ...

The Genomically Mosaic Brain: Aneuploidy and More in Neural Diversity and Disease
  • Citing Article
  • March 2013

Seminars in Cell and Developmental Biology

... Alternatively, when P53 elimination solely promotes cell survival, a variety of outcomes can be observed. Unfit cells may be removed by alternative cell death mechanisms, or defective cells survive and are observed at later stages (Yang et al., 2003;Peterson et al., 2012;Lang et al., 2016;Shi et al., 2019;Moujalled et al., 2021). In this study, the minimal rescue of cell numbers achieved by deletion of Trp53 in BubR1 cKO mice supports the idea that alternative cell death pathways eliminate unfit cells. ...

Aneuploid Cells Are Differentially Susceptible to Caspase-Mediated Death during Embryonic Cerebral Cortical Development

The Journal of Neuroscience : The Official Journal of the Society for Neuroscience

... The mycoplasma test was negative ( Figure 1D). Long-term iPSC culture involves the accumulation of mutations and genomic integration [13]. Karyotyping was performed using the GTG-band method, and the AD iPSCs were confirmed to have a normal karyotype ( Figure 1E). ...

Normal Human Pluripotent Stem Cell Lines Exhibit Pervasive Mosaic Aneuploidy

... Such genetic variants can arise from natural biological processes such as DNA repair, recombination, replication and retrotransposition. Studies of the human brain report changes in DNA content, DNA copy number variation, somatic gene recombination, and tandem repeat expansions, pointing to accumulation of genomic rearrangements in the brain [2][3][4]. The functional impacts of various structural genetic variants depend on the cell type and region of the genome affected. ...

Neuronal DNA Content Variation (DCV) With Regional and Individual Differences in the Human Brain
  • Citing Article
  • October 2010

The Journal of Comparative Neurology