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PLoS Genet. 2008 October; 4(10): e1000226. Published online 2008 October 17. doi: 10.1371/journal.pgen.1000226. | PMCID: PMC2562519 |
Copyright Huettel et al. This is an open-access article distributed under the
terms of the Creative Commons Attribution License, which permits unrestricted use,
distribution, and reproduction in any medium, provided the original author and
source are credited. Effects of Aneuploidy on Genome Structure, Expression, and Interphase
Organization in Arabidopsis thaliana Bruno Huettel,#1¤ David P. Kreil,#2 Marjori Matzke,1* and Antonius J. M. Matzke1 1Gregor Mendel Institute of Molecular Plant Biology, Austrian Academy of
Sciences, Vienna, Austria 2Chair of Bioinformatics, Boku University Vienna, Vienna,
Austria Joseph R. Ecker, Editor The Salk Institute for Biological Studies, United States of America Received February 13, 2008; Accepted September 15, 2008. Aneuploidy refers to losses and/or gains of individual chromosomes from the
normal chromosome set. The resulting gene dosage imbalance has a noticeable
affect on the phenotype, as illustrated by aneuploid syndromes, including Down
syndrome in humans, and by human solid tumor cells, which are highly aneuploid.
Although the phenotypic manifestations of aneuploidy are usually apparent,
information about the underlying alterations in structure, expression, and
interphase organization of unbalanced chromosome sets is still sparse. Plants
generally tolerate aneuploidy better than animals, and, through colchicine
treatment and breeding strategies, it is possible to obtain inbred sibling
plants with different numbers of chromosomes. This possibility, combined with
the genetic and genomics tools available for Arabidopsis
thaliana, provides a powerful means to assess systematically the
molecular and cytological consequences of aberrant numbers of specific
chromosomes. Here, we report on the generation of Arabidopsis
plants in which chromosome 5 is present in triplicate. We compare the global
transcript profiles of normal diploids and chromosome 5 trisomics, and assess
genome integrity using array comparative genome hybridization. We use live cell
imaging to determine the interphase 3D arrangement of transgene-encoded
fluorescent tags on chromosome 5 in trisomic and triploid plants. The results
indicate that trisomy 5 disrupts gene expression throughout the genome and
supports the production and/or retention of truncated copies of chromosome 5.
Although trisomy 5 does not grossly distort the interphase arrangement of
fluorescent-tagged sites on chromosome 5, it may somewhat enhance associations
between transgene alleles. Our analysis reveals the complex genomic changes that
can occur in aneuploids and underscores the importance of using multiple
experimental approaches to investigate how chromosome numerical changes
condition abnormal phenotypes and progressive genome instability. Most plants and animals have two copies of each chromosome in the normal
chromosome set. Unbalanced numerical changes resulting from gains or losses of
individual chromosomes (aneuploidy) usually have deleterious consequences. For
example, Down syndrome in humans is caused by an extra (triplicate) copy of
chromosome 21. Human tumor cells usually display numerous alterations in
chromosome number and structure. Little is known about how changes in chromosome
number influence gene activity and chromosome integrity, thereby perturbing
physiology and development. We have used the model plant A.
thaliana to study how triplication of chromosome 5 affects gene
expression, chromosome structure, and chromosome packaging in the nucleus. The
results indicate that the presence of an extra chromosome 5 has multiple
effects: (1) substantial changes in gene expression occur, primarily on the
triplicated chromosome 5 but also on the four non-triplicated chromosomes; (2)
broken derivatives of chromosome 5 can be retained in the presence of two normal
copies; and (3) two copies of the triplicated chromosome 5 may show a slightly
enhanced tendency to associate with each other, perhaps to spatially compensate
for the chromosome imbalance. The detrimental effects of aneuploidy are likely
due to concurrent changes in gene expression, chromosome structure, and
arrangement. Changes in the number of chromosomes from the normal diploid set can be grouped into
two types: polyploidy and aneuploidy. Polyploidy refers to whole genome duplications
whereas aneuploidy refers to unbalanced losses and/or gains of individual
chromosomes, or parts of chromosomes, from the basic chromosome set. Early work on
plants and insects revealed that aneuploidy has a greater effect on phenotype than
polyploidy [1], [2]. These observations can be explained in terms of
the gene balance hypothesis, which posits that dosage imbalances of genes encoding
regulatory molecules disturb their stoichiometry within multi-protein complexes and
disrupt cellular processes [2]. Consistent with this hypothesis, work in
Drosophila has indicated that genes encoding transcription
factors and members of signal transduction cascades are primarily responsible for
dosage effects on the phenotype [1]. The gene balance hypothesis provides a conceptual framework for investigating in
greater detail the molecular and cytological consequences of aneuploidy. This
information is important for understanding the coordinated operation and expression
of the genome as well as syndromes and disease states associated with abnormal
chromosome numbers. The latter is exemplified by human solid tumour cells, which are
highly aneuploid. The karyotypes of advanced tumour cells typically feature not only
a plethora of chromosome numerical aberrations but also extensive structural
alterations, including translocations and deletions [3]. The co-existence of
chromosome numerical and structural changes in tumour cell nuclei hints that they
are linked in some way, but the basis of this connection is unclear. The genomes of
tumour cells often display a distinctive DNA methylation profile that is
characterized by global hypomethylation accompanied by aberrant hypermethylation of
CpG islands within promoter regions [4], [5]. That aneuploidy might be at the root of these
diverse genomic and epigenomic changes was suggested by a study on trisomic tobacco
plants, in which the chromosome present in triplicate was prone to breakage, local
increases in DNA methylation, and gene silencing [6], [7]. Another aspect of aneuploidy concerns interphase chromosome arrangement and dynamics,
which are increasingly regarded as factors influencing gene activity [8]. Down
syndrome in humans, which is caused by triplication of chromosome 21 (trisomy 21),
is relevant in this context. Chromosome 21 is the smallest human autosome [9], not
the most gene-poor (a distinction that belongs to chromosome 13 [10]), and
it is the only autosome that is compatible with extended life after birth when
triplicated [11]. These observations might be partially explained
if extra chromosomes interfere with chromosome packaging or mechanics such that
triplication of the smallest is the least harmful. However, the ways in which extra
or missing chromosomes in aneuploids might perturb the three-dimensional (3D)
architecture and dynamics of interphase chromosomes are not understood. The consequences of aneuploidy for global gene expression patterns are only beginning
to be assessed. With respect to Down syndrome, the naïve expectation is
that genes on the triplicated chromosome 21 will be expressed at 1.5 times the level
found in chromosome 21 disomics according to the increase in gene dosage. However,
only a subset of expressed genes on triplicated chromosome 21 appears to be
up-regulated in the expected manner whereas the expression of many genes is adjusted
to the disomic level, indicating dosage compensation [12]. The extent of
trans or secondary effects, in which genes on non-triplicated chromosomes are
misregulated, is still not fully resolved with respect to trisomy 21 [13]– [15]. Trans effects have been
documented in aneuploids of maize [16], [17] and yeast [18],
demonstrating that changes in expression are not restricted to genes on the
numerically altered chromosome. However, information about how global patterns of
gene expression are adjusted following chromosome-wide alterations in gene dosages
is still limited. This issue is complex because unique expression profiles are
likely to result from numerical changes of specific chromosomes or chromosome
regions. Plants have traditionally provided excellent systems for studying aneuploidy. The
terms trisome and monosome were coined by Blakeslee, Belling and coworkers from
their classic work in the 1920's on the twelve trisomics of Datura
stramonium (Jimson weed), each of which displays a distinctive
phenotype [2]. With respect to mechanisms of epigenetic regulation
and genome composition, plants are arguably more similar to mammals than are yeasts
or Drosophila. For example, both plants and mammals have DNA
methylation, histone H3 lysine 9 and lysine 27 methylation, and proteins of the RNAi
machinery; moreover, their genomes contain substantial amounts of repetitive DNA,
which can potentially affect gene expression and chromosome structural stability
[19].
Insights gained from plants can thus be informative for understanding the effects of
aneuploidy in mammalian cells. Plants have the advantage of generally tolerating
aneuploidy better than mammals, and their chromosome numbers can be more easily
manipulated to allow systematic analyses of the consequences of chromosome numerical
aberrations. We are using the model plant Arabidopsis thaliana
(2n  = 10) to investigate the impact of aneuploidy
on genome structure, expression and 3D organization of interphase chromosomes. All
five trisomics of Arabidopsis
(2n = 10+1) are viable and have a
distinctive phenotype [20]. The genetics and genomics resources available
for Arabidopsis are unsurpassed in the plant kingdom. In addition,
transgenic Arabidopsis lines are available in which distinct
chromosome sites are tagged with fluorescent markers [21], [22], allowing the
identification of specific trisomics at an early stage and subsequent live cell
imaging of fluorescent-tagged sites in interphase nuclei in intact plants. Here we
report the results of experiments using these tools to analyze the molecular and
cytological consequences of chromosome 5 triplication in
Arabidopsis. Identification of Chromosome 5 Trisomic Plants in F2 and F3 Generations The strategy for obtaining chromosome 5 trisomics and for subsequent analysis of
these plants is shown in . We started with a diploid parental line that was homozygous for DsRed
(R) and YFP (Y) fluorescent tags on chromosome 5, which is one of the largest
chromosomes in Arabidopsis (). From a cross between the diploid
parent and a tetraploid derivative produced by colchicine treatment, we obtained
triploid plants (F1 generation). Self-fertilization of F1 triploids produced F2
progeny, 33 of which were selected for more detailed investigation. Screening
root nuclei in F2 seedlings for chromosome 5 fluorescent tags allowed us to
predict whether individual F2 plants might be diploid (2R 2Y), chromosome 5
trisomic/triploid (3R 3Y) or chromosome 5 tetrasomic/tetraploid (4R 4Y). The
actual chromosome numbers were subsequently determined by counting metaphase
chromosomes, and the presence of unbalanced chromosome sets was assessed by
array comparative genome hybridization (CGH) ( Table S1). The F2 progeny comprised a complex population containing chromosomally balanced
diploids, triploids and tetraploids, as well as chromosomally unbalanced
trisomics (the most frequently observed chromosome constitution), double
trisomics (2n = 10+1+1), and
near triploids (3X = 15+/−1
or 15+1+1) (). As expected from the screen of chromosome 5 fluorescent
tags, we obtained a number of plants with a triplicated chromosome 5 (3R 3Y);
however, subsequent array CGH and metaphase chromosome counts revealed that only
three of these were true triploids (plants 8-5, 8-6, 9-1; plant 11-5 had 15
chromosomes, but one copy of chromosome 1 was truncated; see below) and just two
were simple chromosome 5 trisomics (plants 6-5 and 6-7) ( Table S1A).
The remaining ‘3R 3Y’ plants had an additional extra
chromosome(s), the most common being either chromosome 2 or 4, which are the
smallest of the Arabidopsis chromosome set (). Representatives of the next generation (F3) were obtained by self-fertilization
of the two trisomic F2 plants (6-5 and 6-7) and two diploid F2 siblings (6-4 and
7-2). From each of the two trisomic F2 parents, we selected around a dozen F3
progeny that were identified by fluorescence microscopy as potential chromosome
5 trisomics (3R 3Y) ( Table S1B). Extra copies of chromosome 5 were
confirmed in these plants by array CGH and, in most cases, the expected
chromosome number (2n = 10+1) was
established by counting metaphase chromosomes. From each of the two diploid
parents, we selected for further analysis four F3 progeny that were chromosome 5
disomics (2R 2Y) and confirmed the expected diploid chromosome number by
counting metaphase chromosomes ( Table S1B). Genome Structural Integrity in Chromosome 5 Trisomics Previous work with a trisomic tobacco line suggested that the chromosome present
in triplicate was vulnerable to breakage [6]. Here we used array
CGH to assess genome integrity in selected progeny of
Arabidopsis triploids, including chromosome 5 trisomics from
the F2 and F3 generations ( Table S1). Array CGH can detect not only
imbalances of intact chromosomes but also parts of chromosomes resulting from
breakage, thereby revealing the approximate location of a breakpoint. The first chromosome break we detected was in a triploid plant from the F2
generation (11-5; Table S1), which contained a truncated copy
of chromosome 1 lacking part of the top arm ( and ). The two trisomic F2 plants, 6-5 and 6-7,
had structurally intact genomes as assessed by array CGH. In the F3 generation,
however, we detected chromosome breaks in two trisomic plants (out of 26 tested
by array CGH; Table S1B), one from each trisomic F2 parent. Both of these breaks
affected the triplicated chromosome 5. In one case essentially the entire top
arm of chromosome 5 was deleted (plant 6-5-22), suggesting a break around the
centromere. In the second case, the break occurred in the vicinity of the
DsRed transgene locus, such that the tip of the bottom arm
of chromosome 5 was lost (plant 6-7-10) ( and ). Although derived from a relatively small sample size, these findings support the
idea that trisomics show enhanced breakage of the chromosome present in
triplicate and/or retention of a fractured chromosome when two intact copies are
present. Because the truncated versions of chromosome 5 appeared in individual
trisomic F3 progeny, they were likely generated during meiosis in the trisomic
F2 parent. The possibility that breaks of the triplicated chromosome occur more
frequently in somatic cells of trisomics than of diploids [23] can be studied in
the future by performing single cell array CGH [24], [25]. Whether the trisomic plants containing truncated versions of chromosome 5 would
transmit the broken chromosome to the next generation is not yet known. In a
pilot study, a second generation chromosome 5 trisomic plant harbouring a break,
again in the vicinity of the DsRed transgene locus (plant
12-16; ),
transmitted the truncated chromosome to trisomic progeny. However, array CGH of
five trisomic progeny plants did not detect further deletions of chromosome 5
(data not shown). A more comprehensive study analyzing additional breakpoints in
progeny plants across several generations might uncover evidence for progressive
structural changes after formation of an initial break and reveal whether any
specific DNA sequence features are associated with breakpoints. The current data
suggest that repetitive regions, for example around the centromere and the
DsRed transgene locus, which contains lac
operator repeats [21], [22], are preferential
sites of breakage in trisomics. The chromosome 1 break in the triploid plant
11-5 occurred in an intergenic, nonrepetitive region that does not contain
conspicuous features. Transcript Expression Profiling To assess the impact of chromosome 5 triplication on global gene expression, we
carried out gene expression profiling using Affymetrix ATH1 microarrays, which
report on about 21,000 Arabidopsis transcripts of the current
TAIR genome annotation (v7). We were interested in comparing chromosome 5
trisomics and diploid plants with respect to the expression of genes on
triplicated chromosome 5 (primary or cis effects) and the expression of genes on
the four non-triplicated chromosomes (secondary or trans effects). All plants
used for the transcriptome analysis (F2 trisomics 6-5, 6-7 and eight F3 progeny;
F2 diploids 6-4, 7-2 and three F3 progeny) had intact genomes as assessed by
array CGH ( Table
S1A,B). Microarray hybridization signals not only showed a strong systemic effect for the
trisomic chromosome 5 but also a wide range of clear trans effects for
transcripts on the disomic chromosomes () consistent across the relatively
large number of biological replicates analysed. It is noteworthy that many
popular normalization transforms are not appropriate for data sets with
large-scale expression level shifts as seen here because these violate
underlying assumptions of many methods. The consequential distortions and signal
dampening are illustrated for reference in the Supporting Information ( Text S1)
and Online Supplement ( http://bioinf.boku.ac.at/pub/trisomy2008), where we also discuss
alternative normalization methods ranging from popular established tools used in
previous studies [17], [18] to specialized
approaches such as exploiting CGH data as reference. Observed expression levels of most transcripts on chromosome 5 reflected the
dosage effect of its increased copy number in chromosome 5 trisomics, whereas
most transcripts on other chromosomes did not change. Examination of expression
differences as a function of average signal intensities in a traditional
M(A)-plot, however, revealed an unexpected intensity
dependence that has no biological explanation (): Each transcript is represented by
a dot and error bar, with the difference in expression (trisomics minus
disomics) shown on the y-axis, and the average expression on
the x-axis. Green marks the transcripts on chromosome 5.
Magenta and orange trend lines respectively show the intensity dependence
plus/minus one standard deviation for chromosome 5 and the other chromosomes.
The deviation of the magenta centre trend line from a line parallel to the
horizontal reflects the non-linear response of the detection system. The figure
shows that differential expression is most accurately surveyed when using the
microarray platform for sufficiently strongly expressed transcripts. We thus
focused on the transcripts to the right of the dashed line (roughly half:
2,452/4,790 on chromosome 5 and 7,355/15,725 others), best reflecting the true
trends for all the genes ( cf.
Text S1
and Online Supplement for discussion). Both average response and significant
deviations from the chromosomal trends were studied. Only a minor degree of dosage compensation was observed, with the percentage of
genes on chromosome 5 classed as having similar expression levels in both
trisomic and diploid plants ranging from 3% (by convex decreasing
density estimate [26]) to 11–15%
(89% differential expression for Benjamini-Yekutieli FDR
q<5%). Interestingly, despite the increased
gene dosage, 1% of transcripts on chromosome 5 had significantly
lower expression levels than in the diploid. Whether the observed
down-regulation is due to epigenetic silencing, altered transcription factor
availability, or other mechanism is not yet known. The down-regulated genes,
which are for the most part rather uniformly distributed along chromosome 5
(), do not
appear to have any conspicuous common features. In contrast to the modest number of dosage-compensated and down-regulated genes,
the highest proportion of chromosome 5 transcripts (86–88%)
showed a significant increase in expression (partial or full dosage effect),
reflecting the extra copy of chromosome 5 in the trisomics (88%
significantly upregulated; 14% of expression changes below the trend;
both with Benjamini-Yekutieli FDR q<5%). The
expression increase of 12–13% of transcripts on chromosome
5 was even significantly above the average trend (hyper-dosage effect) for this
chromosome (13% with Benjamini-Yekutieli FDR
q<5%). To verify this general trend also for chromosome 5 genes with lower expression
levels, we used more sensitive quantitative RT-PCR (qRT-PCR) to quantify
transcript levels of four moderately expressed genes on this chromosome,
selected for their minimal variation during development ( http://www.weigelworld.org/resources/microarray/AtGenExpress/)
and five lowly expressed genes. Consistent with the general chromosome 5 trend,
a higher steady-state transcript level in trisomics was indeed observed for the
majority of these genes, confirming a dosage effect ( Figures S1
and S2). A different picture emerged for the secondary or trans effects on the other
chromosomes: While the 12–13% ratio of transcripts
up-regulated relative to the trend was similar, only 8–9%
of transcripts on other chromosomes were significantly down-regulated, giving a
strong 3 ![[ratio]](/corehtml/pmc/pmcents/x2236.gif) 2 skew favoring up-regulation vs
down-regulation. Trans-effects were equally distributed across all chromosomes
(,
Fisher's exact test,
p= 33%),
indicating that trisomy 5 has a genome-wide effect on gene expression. Stress response genes and transcription factors were significantly
overrepresented among the genes involved in trans-effects ( Table 1). Indeed, the ten
most-significant trans-effects included four transcription factors, of which
three were strongly up-regulated (AGL19, ANAC019, AtMYB47) and one
down-regulated (MEE3). The prominence of transcription factors in the strongest
trans effects supports the gene balance hypothesis [2]. For the cis
effects, genes involved in responses to abiotic or biotic stimulus and cell wall
components were significantly affected whereas for dosage-compensated genes on
chromosome 5, genes involved in structural roles and ribosome biogenesis were
significantly over-represented ( Table 1). | Table 1GOslim categories significantly over-represented (odds
ratio>1) or under-represented (odds ratio<1) in the test
group relative to the entire chip (Fisher's exact test, Holm
(more ...) |
Changes in the expression of genes encoding transcription factors may alter the
expression of numerous target genes and hence contribute to the genome-wide
changes in expression observed in chromosome 5 trisomics. Similarly, changes in
genes encoding epigenetic modifiers might also be expected to influence the
expression of multiple target genes distributed throughout the genome.
Chromosome 5 genes encoding known epigenetic modifiers showed the higher
expression levels of the expected dosage effect in chromosome 5 trisomics. These
include the DNA methyltransferases DRM2, DRM1, and MET1; the histone modifying
enzymes HDA6 and SUVH4; and the SNF2-like chromatin remodeling protein DDM1
( Figure
S3). In addition, epigenetic modifiers encoded on non-triplicated
chromosomes were also involved in the trisomy 5 response. These include two
genes on chromosome 2: ROS1, which encodes a DNA
glycosylase-lyase protein involved in active demethylation of cytosines in DNA
and hence acts antagonistically to MET1, DRM2 and DRM1 [27]; and
RDR5, which encodes an RNA-dependent RNA polymerase related to
those acting in RNAi-mediated pathways in plants [28] ( Figure S4).
Previous work has shown a link between components required for DNA methylation
and those for active demethylation of DNA [29]. For example, in
met1 mutants, which have decreased levels of DNA
methylation, ROS1 expression is significantly reduced [29], [30]. One possibility
is that the increased expression of DNA methyltransferases encoded on chromosome
5 might be counterbalanced by increased ROS1 expression to
maintain global DNA methylation at a level compatible with plant viability.
Further work is needed to test this hypothesis. In summary, transcript expression profiling by microarrays revealed that while
the increased expression of the majority of transcripts
(86–88%) on chromosome 5 reflected a partial, full, or
hyper-dosage effect due to the triplication of this chromosome, there was a
small set of transcripts (3–15%) for which there was
evidence of dosage compensation. In contrast, there were
12–13% of transcripts across all
chromosomes that were up-regulated with respect to their chromosomal
neighborhoods. While there were at least as many transcripts
(13–14%) on chromosome 5 down-regulated relative to the
chromosome trend, down-regulation on other chromosomes was only observed for
8–9% of transcripts. Generally elevated expression levels reflecting dosage effects for the
triplicated chromosome, a genome-wide 3 2 skew favoring up-regulation
vs down-regulation in gene specific response, and
dosage-compensation for some genes on chromosome 5 can together account for all
these observations. Transcription of ROS1 and RDR5 in Other Trisomics To determine whether the up-regulation of ROS1 and
RDR5 in chromosome 5 trisomics is a generic response to an
increased chromosome number or is specific for chromosome 5 trisomics, we used
qRT-PCR to investigate expression of these genes in other F2 trisomics obtained
from self-fertilization of the triploid F1 parents (; Table S1). Despite their similar behaviour in individual chromosome 5 trisomics (, top and middle, left,
compare diploid lanes 1–6 with trisomic lanes
7–12) , ROS1 and RDR5 showed
independent responses in other trisomics. For example, triplication of
chromosome 2 (three plants available for testing) resulted in higher expression
of RDR5 at a level consistent with the increased gene dosage
(, top, right, lanes
chr. 2) while ROS1 expression was slightly below the
diploid level, suggesting dosage compensation of this gene in the triplicated
state (, middle, right,
lanes chr. 2). Both genes were sharply down-regulated in chromosome 3
and chromosome 4 trisomics, although only single plants were available for
testing (, top and middle,
right, lanes chr. 3 and chr. 4). In three plants harbouring
triplications of both chromosome 4 and chromosome 5 (double trisomics), an
intermediate level of ROS1 expression (around that observed in
diploids) was observed (,
middle, right, lanes chrs. 4+5). By contrast,
RDR5 was expressed in the double trisomics at a level
comparable to chromosome 5 single trisomics (, top, compare lanes chrs. 4+5,
right, with trisomic lanes 7–12, left). One interpretation
of these results is that positive regulators of ROS1 and
RDR5 are on chromosome 5, and in addition, a negative
regulator of ROS1 is on chromosome 4. The data on ROS1 and RDR5 expression illustrate
the complex variations in the expression of single genes in aneuploids of
different chromosome constitutions. Genes encoding epigenetic modifiers can
change expression independently, regardless of whether they are present on a
numerically altered chromosome. These findings suggest that different
aneuploidies might variably affect epigenetic mechanisms, creating diverse
patterns of epigenetic modifications depending on the chromosome constitution.
Additional work to determine genome-wide distributions of various epigenetic
modifications in different aneuploids is required to test this conjecture. Expression of DsRed-LacI and TetR-YFP
Transgenes on Chromosome 5 We also used qRT-PCR to examine the expression of DsRed-LacI and
TetR-YFP transgenes, which are present on chromosome 5 but
not represented on the ATH1 microarray. Interestingly, even though the
DsRed-LacI and TetR-YFP transgenes are
both transcribed by the cauliflower mosaic virus 35S promoter [21], [22], they respond
differently to triplication of chromosome 5. The TetR-YFP gene
was strongly down-regulated in chromosome 5 trisomics compared to diploids
(, bottom, right,
diploid lanes 1–6, trisomic lanes 7–12). By
contrast, the average expression of the DsRed-LacI gene
remained at roughly the same level in both diploid and chromosome 5 trisomic
plants, consistent with dosage compensation of this transgene when triplicated
(, bottom, left,
diploid lanes 1–6, trisomic lanes 7–12). The
expression of Ds-Red-LacI appears to display more
plant-to-plant variability in trisomics than in diploids, however, suggesting a
stochastic element to the dosage compensation mechanism (, bottom, left, diploid lanes 1–6,
trisomic lanes 7–12). It is unknown why the two 35S promoter-driven transgenes reacted differently upon
triplication of chromosome 5 nor is it clear why the TetR-YFP
transgene undergoes such a steep reduction in expression when triplicated.
Silencing and methylation of a transgene encoding neomycin phosphotransferase in
tobacco was observed when the transgene locus was present on all three copies of
a triplicated chromosome [6]. Both the TetR-YFP and
DsRed-LacI transgene loci comprise complex inserts of the
respective transgene construct [22]. The TetR-YFP transgene is
integrated near a cluster of silent transposon-related sequences and tRNA genes
(At5g20852 to At5g20858) that give rise to numerous small RNAs ( http://mpss.udel.edu). By contrast, the DsRed-LacI
transgene is inserted into two overlapping, moderately expressed protein-coding
genes (At5g58140 and At5g58150) in a gene-rich region [21]. Perhaps the
repetitive and silent genomic environment enhances silencing of the
TetR-YFP transgene in trisomics. The basis of
TetR-YFP silencing and whether repressive epigenetic
modifications and/or small RNAs are involved remain to be determined. Although
most down-regulated endogenous genes on triplicated chromosome 5 are not in
repetitive regions, two of the most robustly down-regulated predicted genes
(At5g35480, At5g35490; http://bioinf.boku.ac.at/pub/trisomy2008/nonorm2/down.cis.minA.ldiff.triVsWT.EBFWER.txt)
are divergently transcribed from a common promoter and associated with
transposon-related sequences and numerous small RNAs ( http://mpss.udel.edu). 3D Arrangement of Fluorescent-Tagged Sites on Chromosome 5 The fluorescent-tagged sites on chromosome 5 are useful for identifying
chromosome 5 trisomics at an early stage of development before the
characteristic phenotype of trisomy 5 is visible. In addition, high resolution
measurements of distances between DsRed and
YFP transgene alleles can be made in interphase nuclei of
living cells and subsequent 3D reconstructions of optical sections of nuclei can
reveal the relative arrangements of the fluorescent tags. In a previous study of
16 different fluorescent-tagged sites distributed throughout the genome in
diploid plants, random arrangements were observed in interphase nuclei of root
cells. There was no indication of allelic pairing (defined as an inter-allelic
distance of ≤ 0.5 µm) or for preferential associations of
ectopic chromosome sites in diploid plants [21]. In the present
study, we compared chromosome 5 trisomics with triploids, both of which have
three YFP dots and three DsRed dots in the context of a chromosomally unbalanced
or balanced genome, respectively (). We examined whether the extra copy of chromosome 5 in
trisomics produced any distinctive arrangements of chromosome 5 fluorescent tags
that differed from those observed in the triploid genome. Six distances – connecting the three YFP dots and the three DsRed dots
– were measured in selected root nuclei in which fluorescent signals
were visible ( Figure S5). In sibling triploid and trisomic seedlings of the F2
generation, the distances between the YFP dots and DsRed dots usually differed
within a given nucleus and considerable inter-nuclear variability in distance
measurements was observed for both fluorescent tags ( Table
S2A,B). Thus, in both trisomics and triploids, chromosome 5 fluorescent
tags display similar random arrangements. In trisomics, however, we observed an
increased incidence of inter-allelic distances around 0.5 µm ( Table S2B).
Although these results might suggest enhanced allelic pairing in trisomics, they
could also reflect the generally smaller inter-allelic distances in these plants
( Table
S2), which in turn is probably due to smaller nuclei in trisomics than in
triploids [21]. The possibility of enhanced allelic
associations in trisomics was supported, however, by 3D reconstructions of
nuclei, which indicated that two of the three alleles of either
DsRed or YFP were more likely to be close to
each other in trisomics than in triploids (group I, Table S2;
Figure
S6). A similar trend was observed in trisomic F3 progeny; however,
analysis of these plants was compromised by problems with epigenetic silencing
of the LacI-DsRed and TetR-YFP transgenes and
by the lack of F3 triploid siblings for comparison ( Table S1B
and data not shown). Although the analysis has involved a limited number of root cell nuclei, it
appears that the presence of an extra chromosome 5 in unbalanced trisomics does
not substantially alter the interphase arrangement of chromosome 5 fluorescent
tags as compared to those observed in chromosomally balanced triploids. A subtle
difference, however, may be a slightly enhanced tendency for two copies of the
triplicated chromosome to be more closely apposed, at least partially along
their lengths, in trisomics than in triploids. This possibility can be studied
in the future with a larger set of trisomic plants and the use of emerging
strategies that minimize silencing of the reporter transgenes [22]. General Summary and Conclusions Our studies on the influence of chromosome 5 triplication on chromosome
structural stability, gene expression, and interphase arrangement of chromosome
5 fluorescence tags in Arabidopsis have demonstrated that
trisomy 5 disrupts the genome in a number of ways: 1. Chromosome structural stability: Truncated derivatives of the triplicated
chromosome 5 were regularly observed in trisomic plants. The triplicated
chromosome may be vulnerable to breakage, particularly in vicinity of repetitive
regions, and a truncated chromosome is more likely to be retained when two
intact copies are present. The possibility of structural as well as numerical
deviations in aneuploids underscores the need to perform array CGH for proper
analysis and intepretation of the transcriptome data [31]. The formation and
inheritance of chromosome structural variants in aneuploids might have
evolutionary implications if restructured chromosomes are transmitted to progeny
and eventually fixed in the population [32]. Enhanced
structural instability of aneuploid genomes in somatic cells could have
relevance for human cancer cells, which display progressive chromosome numerical
and structural changes as the tumour evolves [7], [23]. 2. Complex changes in gene expression: The transcriptome analysis revealed that
the expression of many genes is affected in chromosome 5 trisomics, primarily on
the triplicated chromosome (cis effects) but also on non-triplicated chromosomes
(trans effects). Most genes on chromosome 5 genes showed higher expression
reflecting a dosage effect, but cases of apparent dosage compensation and even
down-regulation were also observed. Genes involved in responses to stress and
other stimuli were over-represented among genes differentially regulated
relative to the average chromosome trends, and transcription factors were
over-represented in the trans effects. The use of qRT-PCR to analyze expression
of single genes demonstrated variable expression depending on the chromosome
number and constitution, and on the features of individual genes: As shown with
the epigenetic regulators ROS1 and RDR5, genes
on the same chromosome can vary independently in their expression in different
trisomics. In addition, genes under the control of the same promoter can vary in
their response to triplication, as indicated by the two 35S promoter-driven
transgenes, TetR-YFP and DsRed-LacI, on
chromosome 5. The observed variations in gene expression probably depend on
multiple factors including, but not limited to, changes in the dosages of
regulatory molecules and epigenetic factors, and sensitivity of repetitive
regions to copy number changes and gene silencing mechanisms. Transcriptional
changes resulting from aneuploidy must be described in terms of chromosomes
and/or chromosome regions that are numerically altered and whether changes in
expression are in cis or trans regions. Clearly, the choice of microarray data
analysis methods has a substantial impact on results and, in particular,
normalization methods that are robust to large-scale shifts in gene expression
need to be applied in studies of aneuploidy. Although not studied here, cell and
tissue-type differences in gene expression in a given aneuploid might also be
expected [15]. 3. 3D organization of fluorescent-tagged sites: Overall, chromosomally unbalanced
trisomics and balanced triploids display equally random interphase arrangements
of fluorescent tagged sites on chromosome 5; however, there may be a slight
tendency for two transgene alleles on the triplicated chromosome to be more
closely associated in trisomics than in triploids. If such associations occur
regularly in trisomics, they might help to induce dosage compensation mechanisms
[33] or spatially compensate for the extra chromosome
in interphase nuclei. Aneuploidy is usually studied for its developmentally detrimental or pathological
consequences but it also may be important in normal contexts. Recent work has
identified a significant fraction of aneuploid cells in the normal brain
although their physiological significance is not yet known [34]. Given the
strong effect of aneuploidy on global gene expression patterns, it is
conceivable that the formation of aneuploid neurons increases the phenotypic
variability of these cells and their capacity to perform diverse neural
functions. Plant Material The plant material in all experiments was Arabidopsis thaliana
landrace Col-0 (the accession used for the design of the ATH1 array). The
transgenic line with YFP and DsRed fluorescent tags on chromosome 5 was
described previously [21]. Seeds were germinated on sterile, solid
Murashige and Skoog medium in plastic petri dishes. Root nuclei in living
seedlings were monitored for YFP and DsRed fluorescence signals as detailed in
previous reports [21], [22]. Seedlings were
then transferred to pots containing a mixture of Huminsubstrat N3 and Vermiculit
Nr.2 (2 1 v/v) (purchased from a local supplier), and placed in a
culture room with natural light (3000 lux). The photoperiod was 16 h and
temperature was maintained at 23°C. Single leaves were cut from the
plants at a stage of approximately ten rosette leaves (>1 cm in length),
except for plants with extreme aberrant phenotypes, which late were found to
contain an extra copy of chromosome 1. The first cut leaf was selected for RNA
and the second for DNA isolation in order to minimize wounding effects. Production of Tetraploids, Metaphase, and Interphase Chromosome Analysis Seedlings were treated with colchicine to produce tetraploid progeny according to
an unpublished protocol (Ramon Angel Torres Ruiz, personal communication).
Metaphase chromosome counts were performed using pistil material as described in
protocols 5.2 and 5.3 in a previous publication [35]. Inter-allelic distances and 3D arrangements of fluorescent tagged sites on
chromosome 5 in root interphase nuclei of living, untreated seedlings were
determined using fluorescence microscopy as described previously [21], [22]. The tagged sites
harbor transgene complexes that encode repressor protein-fluorescent protein
fusions proteins (either Tet-YFP or DsRed-LacI) as well as arrays of either
tet or lac operator repeats, to which the
respective repressor protein-fluorescent protein fusion protein can bind [21], [22]. Comparative Genome Hybridization with Microarrays Isolation of genomic DNA (DNeasy mini kit, Qiagen, Hilden, Germany), biotin
labelling of DNA (BioPrime DNA labelling, Invitrogen, Lofer, Austria), and gDNA
hybridization were performed as described [36]. The DNA
concentration was quantified by spectrophotometry (Nanodrop ND-1000; Peqlab,
Erlangen, Germany) and adjusted for gDNA hyridization to 15 µg. ATH1
microarrays were scanned with an Affymetrix GC3000 system and analysed with GCOS
version 1.4 (Affymetrix, High Wycombe, U.K.). For chromosome copy number
variation the disomic transgenic plant, from which all triploid, tetraploid, and
trisomic plants were derived, served as the reference microarray. The array
signals from the derived plants were scaled in GCOS and compared to the diploid
progenitor. Extra chromosomes or chromosomal deletions were then identified
after sorting for probe sets with a “change p-value” call
“Increase” for supernumerical chromosomes or a
“Decrease” call for deletions. In all cases the default
settings were chosen. After excluding probe sets matching to several gene models
(TAIR7) the remaining probe sets were mapped to the Arabidopsis
chromosomes (chromosome map tool at www.arabidopsis.org).
Typically, extra chromosomes are identified by mapping 95% to
98% of probe sets with an “Increase” call to a
unique chromosome e.g. chromosome 5 in case of chromosome 5 trisomy. Mapping Deletion to Chromosomes Microarrays were normalized and log transformed by the RMAExpress0.5 tool
( http://rmaexpress.bmbolstad.com/). The log ratios of the signal
values were mapped to their chromosomal position. Data on probe set location was
also extracted from TAIR v7 (see microarray data analysis section). Only probe
sets matching to a unique gene model (TAIR7) were selected. Quantitative Real-Time PCR Analysis RNA extraction (RNeasy mini kit, Qiagen, Hilden, Germany) and cDNA synthesis
(RevertAid H Minus First strand cDNA synthesis kit, MBI Fermentas, St. Leon-Rot,
Germany) were performed as described previously [37]. The cDNA was
diluted to 75 µl with DEPC-treated double distilled water, and 2
µl was used in a 20 ul PCR reaction. The mixture was set up with 10
µl of QuantiFast SYBR Green PCR (Qiagen, Hilden, Germany), 2
µl cDNA, and 2 µl of each primer (1 µM final
concentration). PCR was performed after a preincubation as suggested by the
supplier (95° C for 5 min) by 40 two-step cycles of denaturation at
95° C for 10 s, and annealing/extension at 60° C for 30 s. The
comparative threshold cycle (Ct) method was used to determine relative RNA
levels (User Bulletin no. 2, Applied Biosystems). GAPC-2 (At1g13440) was chosen
as the internal reference gene (see also [38] for a
comprehensive analysis of reference genes), and expression levels are relative
to a randomly chosen disomic plant. Sequence of the primer sets are shown in
Table
S3. Transcriptome Analysis Total RNA was extracted from rosette leaves (>1 cm in length) using an
RNeasy mini kit (Qiagen, Hilden, Germany). Transcriptomes were analysed using 1
µg of total RNA as starting material. Targets were prepared with the
one-cycle cDNA synthesis kit followed by biotin-labelling with the IVT labelling
kit (GeneChip One-cycle target labelling and control reagents, Affymetrix, High
Wycombe, U.K.) and hybridized for 16 h as recommended by the supplier (Gene
expression analysis manual, Affymetrix). All transcriptome data (CEL and CHP
files) were submitted to a public repository database ( http://www.ebi.ac.uk/microarray/, ArrayExpress accession number:
E-MEXP-1454. Microarray Data Analysis Low-Level Analysis and Transforms A total of 19 samples from 15 individual plants (2×2 trisomics|F2,
2×2 disomics|F2, 8 trisomics|F3, 3 disomics|F3 was hybridized to
Affymetrix ATH1-type GeneChips and scanned as described above. Low-level
CEL-file analysis included re-assignment of probes to a current TAIR genome
annotation, removal of probe-sequence specific effects, chip-to-chip
normalization, and a robust expression signal summary of probe sets using a
multi-chip model to down-weight random outlier probes. The original ATH1 design comprised probe sets for 22,810 transcripts. Probe
set size ranged from 8 to 20 probes per target, with a mean of
11.0±0.3. Depending on the target organism, however, the ongoing
improvements in genome annotation can considerably affect differential
expression estimates for 30–40% of all the targets of
an Affymetrix chip [39]. The necessary re-assignment and
re-annotation of probes consistent with a current genome annotation (TAIR
v7) resulted in 21,089 probe sets (custom assignment v10). Data on
transcript chromosomal locations and start and end coordinates were also
extracted from TAIR for probe-set annotation. Further examination revealed
several probe sets with probes perfectly matching multiple chromosomal
locations, which we wanted to exclude for this study. This finally left
20,515 probe sets ranging in size from 3 to 32 probes per target, with a
mean of 10.8±1.4. Probe specific effects have been fit using an Empirical Bayes
‘affinities’ model for removing both probe-specific
background and adjusting perfect-match signal intensities for probe-specific
affinities [40]. Probe level signals were conservatively
normalized for different backgrounds and overall hybridization intensities
of individual chips using an iterative 20%-trimmed least squares
fit of a generative model with additive-multiplicative noise [41].
This approach is robust both to outliers and to systemic large-scale shifts,
as could be seen from estimating transform parameters from all data or only
from genes not on chromosome 5 (data not shown). The variance-stabilizing
generalized log transform for this model was calibrated for asymptotic
equivalence to a standard log 2 transformation. We refrained from
further transforms in a first examination of data characteristics. As can be
seen from the
conditions for many popular more aggressive normalization methods (such as
quantile–quantile normalization or M(A)-Loess)
were not satisfied. Transcript expression estimates were obtained by robust fits of linear
multi-chip probe level intensity models [42]. A number of diagnostic plots are provided in the Online Supplement (e.g.
pair-wise Q–Q and M(A), spatial
residual trends). We also investigated the effect of alternative
normalization options, including standard methods like quantile
normalization and specialized approaches like attempting to exploit CGH
hybridization signals for normalization. Results corroborate our choice of
conservative normalization. See Methods section of Text S1
and the Online Supplement at http://bioinf.boku.ac.at/pub/trisomy2008/. Analysis of Differential Expression For every gene, linear models were fit to obtain a contrast between
chromosome 5 trisomic and normal diploids, correctly weighted for unbalanced
design and independently for F2 and F3 progeny. We then studied the average
contrast for F2 and F3 progeny. In an examination of chromosome-wide trends, instead of the constant increase
in expression expected for transcripts on chromosome 5, a clear and strong
intensity dependence could be observed, which cannot be explained by
biological effects. shows expression change as a function of average expression in a
standard M(A)-plot. Transcripts on chromosome 5 are
coloured green, and the intensity dependent trend plus/minus standard
deviation is plotted in magenta. The trend for other transcripts is shown in
orange. Intensity-local trend lines and standard deviations were computed in
R by a Loess smoother with span 0.4. The increased expression of transcripts
on chromosome 5 becomes clearer with higher average expression
(x-axis), with the trends being separated by 1+1
standard deviations where the lower magenta and the upper orange lines
cross. We denote this intensity by
A1+1, marked by a vertical dashed line.
The separation continues to grow with the average intensity, peaks, and then
decreases but without falling below the amount at
A1+1. As a consequence, an analysis
of expression changes will be most accurate for
A>A1+1. For
our analysis of trends we therefore focused on this regime. For an analysis of deviations from the average trend of transcripts on
chromosome 5, we performed a calibration by subtracting the average trend as
fitted by the Loess smoother. Deviations could then be tested as deviations
from zero (see Results section of the Online Supplement). We tested for differential expression of each gene applying an Empirical
Bayes regularized t-test [43]. Unless
mentioned otherwise in the text, p-values used in the
generation of lists and graphs were corrected for multiple testing using the
conservative approach by Holm [44], providing strong control of the family
wise error rate (FWER), when assessing change, and by the more powerful
approach of Benjamini and Yekutieli [45], providing
strong control of the false discovery rate (FDR), in the case of testing for
non-change, each with a threshold of 5%, yielding conservative
conclusions in either case. Trend estimates used the Benjamini-Yekutieli
(BY) approach, considering the 5% upper bound of the FDR to
calculate a lower bound of the detected true positive range. For an overview of functional gene categories affected current
‘GOslim’ annotation was extracted from TAIR,
v.2007-12-29 [46], and subset enrichment tested for
significance (Fisher's exact test, Holm FWER
p<5%). Contingency tables are available
from the Results section of the Online Supplement at http://bioinf.boku.ac.at/pub/trisomy2008/. Figure S1 qRT-PCR of low to moderately expressed genes on chromosome 5. (0.06 MB DOC) Figure S2 qRT-PCR of low expressed genes on chromosome 5. (0.08 MB DOC) Figure S3 Chromosome 5 calibrated cis effects. (0.23 MB DOC) Figure S4 Trans effects on expression of genes on chromosome 2. (0.20 MB DOC) Figure S5 Examples of connected YFP and DsRed dots for measurements of interallelic
distances in three dimensions. (0.04 MB PDF) Figure S6 Boxplot of normalized shortest interallelic distance. (0.03 MB DOC) Table S1 List of plants. (0.18 MB DOC) Table S2 Interallelic distance measurements. (0.36 MB DOC) Table S3 Primers. (0.03 MB DOC) Text S1 Supporting information text. (0.27 MB PDF) We thank Johannes van der Winden for technical assistance. 1. Birchler JA. Biological consequences of dosage dependent gene regulatory
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