Stochastic Choice of Allelic Expression in Human Neural Stem Cells

Article (PDF Available)inStem Cells 30(9):1938-47 · September 2012with26 Reads
DOI: 10.1002/stem.1155 · Source: PubMed
Monoallelic gene expression, such as genomic imprinting, is well described. Less well-characterized are genes undergoing stochastic monoallelic expression (MA), where specific clones of cells express just one allele at a given locus. We performed genome-wide allelic expression assessment of human clonal neural stem cells derived from cerebral cortex, striatum, and spinal cord, each with differing genotypes. We assayed three separate clonal lines from each donor, distinguishing stochastic MA from genotypic effects. Roughly 2% of genes showed evidence for autosomal MA, and in about half of these, allelic expression was stochastic between different clones. Many of these loci were known neurodevelopmental genes, such as OTX2 and OLIG2. Monoallelic genes also showed increased levels of DNA methylation compared to hypomethylated biallelic loci. Identified monoallelic gene loci showed altered chromatin signatures in fetal brain, suggesting an in vivo correlate of this phenomenon. We conclude that stochastic allelic expression is prevalent in neural stem cells, providing clonal diversity to developing tissues such as the human brain.
Stochastic Choice of Allelic Expression in Human Neural Stem Cells
King’s College London, Institute of Psychiatry, Centre for the Cellular Basis of Behaviour, Department of
Neuroscience and
King’s College London, Institute of Psychiatry, MRC SGDP Research Centre, London, United
Key Words. Neural stem cells
Allelic imbalance
Monoallelic expression
DNA methylation
Monoallelic gene expression, such as genomic imprinting,
is well described. Less well-characterized are genes under-
going stochastic monoallelic expression (MA), where spe-
cific clones of cells express just one allele at a given locus.
We performed genome-wide allelic expression assessment
of human clonal neural stem cells derived from cerebral
cortex, striatum, and spinal cord, each with differing geno-
types. We assayed three separate clonal lines from each
donor, distinguishing stochastic MA from genotypic
effects. Roughly 2% of genes showed evidence for autoso-
mal MA, and in about half of these, allelic expression was
stochastic between different clones. Many of these loci
were known neurodevelopmental genes, such as OTX2 and
OLIG2. Monoallelic genes also showed increased levels of
DNA methylation compared to hypomethylated biallelic
loci. Identified monoallelic gene loci showed altered chro-
matin signatures in fetal brain, suggesting an in vivo cor-
relate of this phenomenon. We conclude that stochastic
allelic expression is prevalent in neural stem cells, provid-
ing clonal diversity to developing tissues such as the
human brain. S
TEM CELLS 2012;30:1938–1947
Disclosure of potential conflicts of interest is found at the end of this article.
Gene expression in diploid eukaryotic cells is generally bial-
lelic, with transcription from both parental alleles. Classic
exceptions are imprinted genes that show monoallelic expres-
sion (MA) in a parent-of-origin-specific manner [1], X-chro-
mosome inactivation in mammalian females [2], and allelic
imbalance through genetic variation in cis [3]. An additional
form of MA occurs randomly, with individual cells expressing
either one or both of the parental alleles. Like genomic
imprinting, this stochastic choice of allelic expression occurs
at the gene level rather than in a chromosome-specific manner
and appears to be stably maintained in cellular progeny [4].
Stochastic choice of allelic expression allows the self-identity
of individual cells and also yields potential functional varia-
tion within individual cells of a complex tissue. Stochastic
MA has classically been described in a small number of gene
families such as odorant receptors [5], immune receptors [6],
and (in the case of the developing nervous system) alpha and
gamma protocadherins [7, 8].
In a genome-wide assessment of allelic expression in clo-
nal human lymphoblastoid cells, Gimelbrant et al. found sto-
chastic MA to be considerably more widespread than previ-
ously believed [9]. Many of these genes were cell surface
molecules and loci characterized by lineage-specific acceler-
ated evolution. If this finding extrapolates to somatic cell pop-
ulations, such as neural stem cells, it could be of considerable
functional importance. Imprinted genes are known to have im-
portant roles in the human brain [10], and recent studies sug-
gest a large number of brain region-specific and cell-specific
imprinted genes in the adult mouse brain [11, 12]. Random
MA, if it exists in the developing nervous system, would add
significant cell-cell variation within a system that commonly
uses cues from neighboring cells for development. Clonal
neural stem cell populations are an ideal resource to test this
hypothesis. However, to our knowledge, no genome-wide
allelic expression assessment of clonally derived human
Author contributions: A.R.J.: conception and design, provision of study material or patients, collection and/or assembly of data, data
analysis and interpretation, manuscript writing, and final approval of manuscript; L.W.P.: provision of study material or patients,
collection and/or assembly of data, data analysis and interpretation, and final approval of manuscript; J.L.: provision of study material or
patients and final approval of manuscript; L.C.S.: data analysis and interpretation and final approval of manuscript; N.J.B.: conception
and design, data analysis and interpretation, manuscript writing, and final approval of manuscript; J.M.: conception and design, financial
support, collection and/or assembly of data, data analysis and interpretation, manuscript writing, and final approval of manuscript; J.P.:
conception and design, financial support, data analysis and interpretation, manuscript writing, and final approval of manuscript.
Correspondence: Aaron R. Jeffries, Ph.D., King’s College London, Institute of Psychiatry, Department of Neuroscience, CCBB, The
James Black Centre, 125 Coldharbour Lane, London SE5 9NU, U.K. Telephone: þ44(0)20-7848-0412; Fax: +44(0)20-7848-0986;
e-mail: Received February 9, 2012; accepted for publication May 24, 2012; first published online in S
CELLS EXPRESS June 19, 2012; available online without subscription through the open access option.
AlphaMed Press 1066-5099/2012/$30.
00/0 doi: 10.1002/stem.1155
STEM CELLS 2012;30:1938–1947
neural stem cells, or indeed any adult stem cell population,
has been made.
In this study, we assessed the frequency of stochastic
choice of allelic expression in human neural cells by perform-
ing a global allelic expression analysis on a series of condi-
tionally immortalized clones derived from human fetal brain.
These neural cells are generated by the transduction of human
fetal brain tissue with a c-mycER
construct encoded in a
retroviral vector [13]. In many ways, the resultant clonal cell
lines accurately represent human neural stem cells. In their
proliferative phase, they are self-replicative, retain their posi-
tional specification (in terms of gene expression and the speci-
ficity of the neurons they generate), and are multipotential,
generating human neurons and glia in differentiating condi-
tions [14, 15]. Importantly, they retain a stable karyotype and
phenotype over extended life in vitro.
Samples consisted of three clonal lines derived from three inde-
pendent donors (nine cDNAs total). A cell line from each donor
was used as reference genomic DNA (gDNA). The cerebral cortex
clones (CTX0E03, CTX0E16, and CTX0E17) and striatal clones
(STR0C05, STR0C08, and STR0C11) were kindly provided by
ReNeuron Ltd., Guildford, U.K., the spinal cord lines (SPC01,
SPC04, and SPC06) were created from fetal cervical spinal cord.
Cells were grown as previously described in Pollock et al. and El-
Akabawy et al. [13, 14]. In brief, derivation consisted of primary
cell isolation from 12-week-old fetal brain. Cells were expanded on
laminin-coated dishes to 60% confluence, transfected with virus
containing c-mycER
for 12 hours, and followed by neomycin
selection of transfected cell colonies. Growth/proliferation of cells
was maintained by the presence of 4-hydroxytamoxifen in the
media. Differentiation was achieved by removal of 4-hydroxyta-
moxifen and growth factors.
Cells were fixed with 4% paraformaldehyde for 10 minutes,
washed with Tris-buffered saline (TBS), and permeabilized using
TBS with 0.1% Triton X-100 and 10% normal donkey serum
before overnight 4
C incubation with primary antibody in TBS
and 1% normal donkey serum. Antibodies for glial fibrillary
acidic protein (Millipore, Billerica, MA,,
Tau (Dako, Cambridgeshire, U.K.), Nestin (Abcam, Cambridge,
U.K.,, and O1 (Sigma-Aldrich, Dorset, U.K., were used. Cells were then washed with
TBS with 0.1% Triton X-100 before 1 hour incubation with sec-
ondary antibody (Alexa Fluor 488, Life Technologies, Paisley,
U.K., Preparations were then washed
with TBS, nuclear stained (Hoescht 33342, Sigma-Aldrich, Dor-
set, U.K.,, and observed on a Leica TCS
SP5 confocal microscope.
Nucleic Acid Extraction
RNA was collected and extracted using Trizol (Life Technolo-
gies, Paisley, U.K.). Five micrograms of RNA was DNase treated
(DNA Turbo free, Life Technologies, Paisley, U.K.,, and RNA quality was assessed with an Agi-
lent Bioanalyser ensuring RNA integrity number > 9. Quantita-
tive PCR was performed on 200 ng DNase-treated RNA to
ensure no gDNA remained. cDNA synthesis was carried out on 1
lg of RNA with random hexamers and Superscript III (Life
Technologies, Paisley, U.K., at 42
for 2 hours.
gDNA was extracted by incubating the cell pellet in sodium
chloride-Tris-EDTA buffer containing 0.5% SDS with RNaseA
(10 lg/ml) for 30 minutes at 37
C followed by Proteinase K (0.2
mg/ml) addition and further incubation at 50
C for 90 minutes.
Phenol/chloroform extraction was then performed.
Allelic Expression Analysis
gDNA (750 ng) for each donor and 1/5 cDNA reaction for each
clonal line were assayed on the Illumina Omni1-Quad beadchip
(Illumina, San Diego, CA, Scans were
imported into Illumina GenomeStudio software (v2010.1) and ge-
notypes called using Illumina’s standard cluster file and a 0.25
gencall threshold. A loss of heterozygosity was noted on chromo-
some 7q of the striatal donor gDNA. gDNA genotypes together
with raw allelic intensity (Illumina Xraw and Yraw fields) for all
samples were exported as comma separated value files. Quantile
normalization of the raw allele intensities between channels (Limma
Bioconductor package— was then per-
formed on cDNA and gDNA datasets before calculating b values
(X/(X þ Y)) for each probe when the intensity (X þ Y)wasabove
background level which, based on homozygous calls in gDNA
appearing as incorrect heterozygous calls in cDNA, we determined
to be 3,000. Unlike genotype calls, b provides a quantitative scale
of allelic expression, where values around 0.5 represent equal repre-
sentation of both alleles (heterozygotes), whereas those closer to 0
or 1 represent single alleles (homozygotes). b values for heterozy-
gous single-nucleotide polymorphisms (SNPs) in the gDNA provide
the ideal biallelic model, with significant deviations of b in the
cDNA representing MA. Allelic expression measurement, delta(b)
or D
, was therefore calculated using b
when the
gDNA SNP is heterozygous. Transcript-based D
estimates used
the mean |D
| of expressed informative SNPs within RefSeq acces-
sioned transcripts. A penalty-based weighting score was applied to
transcripts, where SNP probes with D
> 0.1 scored þ1, whereas
values below 0.1 received a 2 penalty. Genes with a total score
of one or below were rejected. Additional filtering was also applied
based on the expressed SNP probe density. Genes with 2–10 SNPs
required at least 50% SNPs to be detectable above background.
Eleven to nineteen SNPs required at least six detectable SNPs, 20–
29 SNPs required seven, 30–49 SNPs required eight, 50–74 SNPs
required nine, and 75þ SNPs required 10. Monoallelic expressed
genes were then defined by a mean SNP D
> 0.2, whereas bial-
lelic expression was defined as D
< 0.1. Gene expression esti-
mates were made using the mean (Intensity
all SNP probes within the transcript. Identification of intergenic or
chains of SNPs was achieved using Boolean operators in Microsoft
Excel 2010.
SNP probes were annotated using GALAXY (http://main. Transcript-based analysis was performed in an iso-
form-specific manner. SNP probes lying in segmentally duplicated
regions (data track at or defined duplicated
regions [16] were removed from the transcript-based analysis.
Known imprinted genes were identified from and
supplemented with loci identified by Morcos et al. [17]
DNA Methylation Analysis
Seven hundred and fifty nanograms of bisulfite-treated gDNA
from cortical and spinal cord clonal lines was assayed on the Illu-
mina Infinum HumanMethylation27 BeadChip (Illumina, San
Diego, CA, using the standard manufac-
turer’s protocol, with DNA methylation b-values calculated using
the GenomeStudio Methylation module (v1.6.1). DNA methyla-
tion b values were then mapped to the allelic expression results
and statistics carried out in R ( Clonal
bisulfite sequencing for a region upstream of TNFRSF10D was
carried out on bisulfite-treated DNA (EpiTech, Qiagen, Crawley,
U.K., using the primers 5
and 5
. Sixteen clonal sequence reads per
sample were analyzed using BiQ software with the default quality
control parameters [18].
Jeffries, Perfect, Ledderose et al. 1939
Gene ontology analysis was carried out using DAVID (http:// and Ingenuity (
). To avoid bias, the large protocadherin family was removed
from the gene lists. A reference gene set was defined for each do-
nor based on genes with sufficient detectable number of SNPs to
be scored (see Allelic Expression Analysis). EpiGraph (http://epi- was used for genetic and epigenetic (his-
tone measures from lymphocytes) analysis at transcriptional start
sites (1,000 bp upstream and 500 bp downstream) and the full
length of the transcript. The same loci were also used to retrieve
fetal brain epigenomics data from the NIH Epigenomics Atlas.
dN/dS values for human/macaque comparison were obtained from
Ensembl ( DNA methylation fetal brain
values were obtained from the Gene Expression Omnibus (http://¼GSM664920).
Validation Experiments
PCR amplicons between 100 and 300 bp were designed with Primer3-
plus (
plus.cgi) to amplify the informative SNP of interest from cDNA and
gDNA. Amplicons were treated with Exonuclease I (New England
Biolabs, Hertfordshire, U.K., and Rapid Alkaline
Phosphatase (Roche, Welwyn Garden City, U.K.,
prior to downstream analysis. Sanger sequencing was carried out with
the PCR primers (Big-Dye v3.1 chemistry, Applied Biosystems, War-
rington, U.K., or an additional primer
for single primer nucleotide primer extension analysis (SNaPshot mul-
tiplex assay, Applied Biosystems, Warrington, U.K., www.applied- Both were analyzed on an ABI 3130 genotyper/
sequencer (Applied Biosystems, Warrington, U.K., www.appliedbio- Peak heights at the informative SNP were measured
using PeakPicker [19] or GeneMarker (SoftGenetics, State College,
values could then be calculated as
previously described. Quantitative PCR was carried out using EVA-
green mastermix (Solis Biodyne, Tartu, Estonia, on an
MJ Research Chromo 4 thermal cycler (Bio-Rad, Hertfordshire, U.K., Relative gene expression was calculated as
described in Pfaffl [20] using five reference genes.
Illumina Beadchips Provide a Suitable
Platform to Detect MA
We assessed genome-wide allelic expression in nine clonal
neural stem cell lines derived from three different fetal
donors. The three cortical lines (CTX0E03, CTX0E16, and
CTX0E17) came from one donor; three striatal lines
(STR0C05, STR0C08, and STR0C11) from a separate unre-
lated donor, and spinal cord lines (SPC01, SPC04, and
SPC06) from a third donor. Initially, we assessed gene
expression in proliferating undifferentiated cells. In this phase,
all these cell lines express neural stem cell markers such as
Nestin (Fig. 1), Musashi1, and Sox2 [13].
We used the Illumina Infinium Omni1-Quad beadchip to
measure allelic representation at informative heterozygous
SNPs for cDNA and gDNA. A quantitative scale termed D
was used to measure the allelic ratio. This was calculated by
comparing the amount of each expressed SNP allele in cDNA
relative to the same SNP in donor gDNA (representing a
50:50 allelic ratio). Use of total RNA (rather than mRNA
alone) enabled measurements from both exonic and intronic
SNPs when expressed over the background signal. This
resulted in approximately 100,000 autosomal informative
intragenic SNPs in more than 9,000 genes. Biological repro-
ducibility was demonstrated from three replicates for the pro-
totype spinal cord line SPC01 (D
Pearson’s correlation R
between 0.86 and 0.89, Supporting Information Fig. S1),
which is similar to a previous allelic expression study based
on the Illumina platform [3]. We also looked for X-inactiva-
tion in female cell lines as proof of principle (Supporting In-
formation Fig. S2), showing 85% of measurable X-chromo-
some SNPs or 78% (159 out of 202) of genes displaying MA/
X inactivation. This agrees with previous estimates of 75%–
85% of genes undergoing silencing and 15% escaping inacti-
vation in human fibroblasts [21]. Known autosomal imprinted
loci also demonstrated MA (Supporting Information File S1).
Widespread MA Was Observed in Autosomal
Genes, a Subset of Which Show Evidence for
Stochastic Allelic Choice
Having detected monoallelic X inactivation, we sought to dis-
cover whether autosomal genes in clonal lines show similarly
pronounced deviation in allelic expression. Allelic expression
measurements (D
) for autosomal intragenic SNPs appear to
follow a normal distribution but with ‘heavy tails’ (kurtosis
score >5). Normal Q-Q plots of each individual clonal line
showed the tails deviating away from a normal distribution at
values of approximately þ0.07 and þ0.07 (Supporting In-
formation Fig. S2). Biological transcriptome noise is likely to
be represented in a normal distribution, so these deviations at
the distribution tails represent putative loci showing true
allelic imbalances. Similar observations in other allelic
expression studies have led to an accepted D
threshold of
0.1, which represents a theoretical 40:60 allelic ratio, as a rel-
evant allelic imbalance observation [22–24]. We therefore
used this threshold and applied a weighted penalty scoring
system to all transcripts that took into account the density of
informative expressed SNPs within a transcript (see Materials
and Methods). The weighting score provides a scale or rank
of confidence for MA measurements. More than 9,000 genes
Figure 1. Cell surface markers on clonal human neural stem cells
showing multipotentiality. Clonal lines from the spinal cord donor show
expression of the stem cell marker Nestin while they undergo prolifera-
tion. When growth factors are removed, the cells differentiate into neu-
rons (stained with TAU), astrocytes (GFAP), and oligodendrocytes
(O1). Nuclei are stained with 4’,6-diamidino-2-phenylindole. Scale bar
¼ 50 lm. Abbreviation: GFAP, glial fibrillary acidic protein.
1940 Human Neural Stem Cell Allelic Expression
were assayable in each donor, and genes with an overall mean
allelic expression D
> 0.2 (representing an allelic ratio of 26:74
when directly measured in cDNA) were classified as showing
MA (Table 1 and Supporting Information File S2). We observed
that 1.82%, 2.16%, and 1.57% of the examined genes in cortical,
striatal, and spinal cord donors, respectively, had at least one
clone with MA (Table 1). Approximately 0.16% of examined
genes was known imprinted genes, leaving the occurrence of
novel autosomal loci showing MA to be between 1.4% and
2.0%. While some of these genes show the same MA across all
clonal lines from a donor, 0.87%, 1.14%, and 0.47% of cortical,
striatal, and spinal cord assayed genes showed evidence of sto-
chastic allelic choice (St-MA). By stochastic, we mean that one
clone would show MA, while a second sister clone (from the
same donor) may show biallelic expression or MA for the alter-
nate allele. We also identified 2,000 additional genes contain-
ing a single informative SNP, with 5% showing putative MA
(Supporting Information File S3) but excluded these from further
analysis. We refer to genes that showed biallelic expression in all
three clonal lines as BA. Full Allelic expression results are
hosted at for visual inspection
in UCSC Genome Browser.
To independently verify allelic expression measurements, we
sequenced RNA from 12 arbitrarily selected expressed genes
across the clonal lines from the three donors (Fig. 2). Strong cor-
relation was observed between the beadchip and direct sequenc-
ing (Pearson’s correlation R ¼ 0.966), for both allelic discrimina-
tion together with the degree of allelic imbalance.
Independent Samples Show Overlap for Autosomal
Genes Susceptible to MA
We asked whether the same set of MA genes reoccurred in in-
dependent donors. A simulation showed that on average, four
MA genes would be expected by chance to be detected in two
donors, whereas typically zero MA genes would be expected
between three or more donors. Our observed values of between
thirteen to twenty one genes shared by two donors and also
two genes common in all three donors (Fig. 3) indicate that
MA gene expression occurs at a nonrandom/specific set of loci
in these neural stem lines (p < .0001, chi-squared test). Thus,
while the selection of allele might be stochastic, this is not true
Table 1. Results summary for CTX-, STR-, and SPC-derived
clonal stem cells
Assayed genes 10,150 9,417 9,085
MA 185 (1.82%) 203 (2.16%) 143 (1.57%)
Known imprinted 16 (0.16%) 15 (0.16%) 15 (0.17%)
Stochastic allelic
choice (St-MA)
89 (0.87%) 107 (1.14%) 43 (0.47%)
Same allelic choice 19 (0.19%) 22 (0.23%) 25 (0.28%)
Unclassified 65 (0.64%) 61 (0.64%) 62 (0.68%)
Assayed genes are shown (those containing informative
expressed single-nucleotide polymorphisms [SNPs]) together with
the number of genes with one or more clones showing MA,
together with a breakdown of the types of allelic expression
identified (stochastic allelic choice or St-MA, same allelic choice
where all three clones show monoallelic expression in the same
direction, and unclassified where only one or two clones showed
detectable monoallelic gene expression in the same direction).
Note: two identified imprinted genes in CTX and one in STR
and SPC show one out of three clones with biallelic expression,
meaning they are also counted in the St-MA group. Additionally,
two genes in CTX and one gene in STR and SPC show the
presence of one transcript isoform in the St-MA group and an
additional alternate isoform of different SNP composition in the
same allelic choice group.
Abbreviations: CTX, cortical; MA, monoallelic expression; SPC,
spinal cord; STR, striatal.
Figure 2. Validation of allelic expression measurements. (A): Allelic expression D
measurements from the Illumina beadchip (x-axis) plotted
against Sanger sequencing derived values (y-axis) for 12 genes showing measurable expression. A strong correlation is observed (Pearson’s corre-
lation R ¼ 0.966) highlighting the validity of the beadchip allelic analyses. The analysis also illustrates the underestimation of allelic expression
from the beadchip. For example, a D
measurement of 0.20 actually represents a value of 0.24 (with an allelic ratio of 26:74 or a minimum of a
2.85-fold difference between the two alleles). (B): Examples of stochastic allelic choice. The transcription factor OTX2, which plays a pivotal
role in forebrain specification and is thought to be important in modulating synaptic plasticity during the critical period of cortical development,
shows monoallelic expression (MA) in clone STR0C05 and expression of the alternate allele in STR0C11, whereas STR0C08 shows biallelic
expression, with a slight imbalance toward the A allele. A second example, OLIG2—a regulator of neural progenitor cell fate and oligodendro-
cyte development, also shows MA in two clones, albeit with weaker repression of the minor allele in CTX0E03 and CTX0E16.
Jeffries, Perfect, Ledderose et al. 1941
for the selection of the genetic loci, instead suggesting a subset
of loci preferentially susceptible to MA. This is supported by a
2.4–3.8-fold enrichment of monoallelic loci identified by
Gimelbrant et al. [9] overlapping with ours, despite the expres-
sion differences inherent between lymphoblastoid and neural
stem cells (Supporting Information Table S1).
Stochastic Allelic Choice Genes Are Enriched for
Neurodevelopmental Functions
We examined the functional classification of St-MA-expressed
genes for each donor with the functional annotation tools
DAVID [25] and ingenuity pathway analysis. We found that
>30% of the St-MA genes in all three donors was transmem-
brane glycoproteins. Developmental terms were particularly
enriched in St-MA genes identified in the clones derived from
the brain (striatal and cortical clones) and included genes
such as ventral anterior homeobox 1 (VAX1) transcription fac-
tor, neurotrophin-3 (NTF3), and neurexin 3 (NRXN3). The
transcription factor binding sites LHX3 and CHX10 also
ranked very highly in all three donors, being present in more
than 50% of the genes in spinal and striatal, 70% of cortical
genes, although this does only represent a 1.5-fold (spinal and
striatal) to 1.9-fold (cortical) enrichment. Complete annota-
tions are shown in Supporting Information File S4.
Allelic Choice Is Largely Maintained After
Our findings indicate that neural stem cell clones express a
subset of genes with MA expression. The question arises as to
whether the allelic expression pattern is retained when these
progenitor cells differentiate into neurons and glia. To investi-
gate the effect of differentiation on allelic expression, we
allowed cells to differentiate in vitro for 1 week into neurons
and glia, as visualized by their morphological differentiation
and the expression of cell-specific markers (Fig. 1) [13–15].
We measured allelic expression of the genes TMEM132D,
GRID1, TNFSRF10D, and PMP2. Quantitative PCR analysis
showed that although TMEM132D expression remains
unchanged after differentiation, GRID1, TNFSRF10D, and
PMP2 exhibit upregulation (Supporting Information Fig. S3).
Despite gene expression changes, the allelic expression status
of these genes is maintained in the differentiated progeny
(Fig. 4). Thus, any functional impact St-MA expression is
likely to be maintained in the neurons and glia.
MA Found Within Intergenic Regions
of the Genome
As expected, intergenic SNPs existing outside of the classic
transcript boundaries mostly showed low SNP probe inten-
sities. Nevertheless, some regions show detectable, and some-
times MA, expression. We first validated this observation by
successful PCR amplification and sequencing of five monoal-
lelic expressed intergenic SNPs (Supporting Information Fig.
S5). We then identified chains of multiple SNP probes
sequentially positioned on the genome as representing mono-
allelically transcribed regions (Supporting Information Table
S2). In CTX0E17, for example, we identified 164 chains of
three or more monoallelically expressed SNPs, comprising
753 total SNPs. Unsurprisingly, many corresponded to already
identified expressed transcripts. However, 35% of the SNPs
was present within intergenic spaces. Of these, 44% shows
overlap with expressed sequence tags (ESTs) and likely repre-
sent novel transcripts or expressed repetitive elements. Some
may also be explained by their proximity to genes showing
similar allelic expression status, representing unannotated al-
ternative isoforms or antisense transcripts. For example, SNPs
upstream of OTX2 match its MA status in the striatal lines,
an observation likely explained by the overlapping antisense
RNA transcript OTX2OS1 (Supporting Information Fig. S6)
found at this locus. Nonetheless, approximately 56% of the
intergenic SNPs identified does not appear to show any over-
lap with ESTs.
MA Is Commonly Associated with Reduced
Transcript Levels
One impact of MA might be to reduce expression levels: if
one allele is silenced, then overall expression might be
reduced. This was suggested in a clonal lymphoblastoid study
[9]. We used SNP probe intensities to estimate gene expres-
sion that showed good accuracy when compared with quanti-
tative PCR measurements (Pearson’s correlation R ¼ 0.871,
Supporting Information Fig. S3). We therefore examined the
impact of MA on transcript levels for all St-MA genes.
Plotting transcription levels against allelic expression
shows a weak but significant (p-value ¼ .01) negative correla-
tion between the degree of allelic imbalance and total transcript
levels (Pearson’s correlation R ¼0.159), consistent with MA
generally reducing the absolute expression of that gene (Sup-
porting Information Fig. S4). This is also reflected in the abso-
lute counts of monoallelic expressing clones showing either
increased or decreased gene expression relative to their biallelic
counterparts, the result of which indicates a twofold increased
chance of reduced expression (88 upregulated vs. 171 downre-
gulated in monoallelic clones and 50 upregulated vs. 62 down-
regulated in biallelic sister clones, chi-squared test p-value
<.0001). Therefore, MA is more likely to result in reduced
transcript levels, such as in the example shown in Figure 5A
and 5B, although this is not a universal rule.
DNA Sequence and DNA Methylation Differences
Exist Between Monoallelic and Biallelic Gene Loci
A factor that may determine monoallelic and biallelic gene
expression is the local DNA sequence acting in cis. The LINE-
1/L1 transposon family has previously been associated with X-
chromosome inactivation [26] and similarly associated with
autosomal monoallelic genes together with fewer CpG islands
and SINE repeats [27]. We used the tool EpiGraph [28] to look
for any associated DNA sequence differences (Supporting
Figure 3. Relationship of monoallelic genes identified in the three
donors. The Venn diagram shows the number of genes identified with
at least one clone from a donor showing monoallelic expression
(known imprinted genes are excluded). The overlap of monoallelic
genes between both two and three donors represents more than that
would be expected by chance. The two nonimprinted autosomal genes
common to all three donors are ACCS and TNFRSF10D.
1942 Human Neural Stem Cell Allelic Expression
Information File S5). No significant difference was found for
LINE-1 or overall LINE repeat occurrence between MA and
BA expressed genes, although a marginal increased length of
LINE-1 was noted with MA genes (Supporting Information Fig.
S7). We find lower CpG density at transcriptional start sites of
MA expressed genes (Wilcoxon rank sum p-value ¼ .0008) to-
gether with depleted amounts of SINE repeats (p-value ¼ 1.4
) and increased long terminal repeats (p-value ¼ .0001)
across the length of the transcript.
Epigenetic factors can also be deterministic for allelic
expression. The allele-specific expression of imprinted and X-
inactivated loci is associated with allele-specific DNA methyl-
ation (ASM) across discrete differentially methylated regions.
A recent study showed that ASM is common across the ge-
nome and tightly linked to allele-specific expression [29]. We
investigated genome-wide patterns of DNA methylation in the
spinal cord and cortical cell lines using the Illumina 27k
Infinium methylation beadchip that targets CpG sites located
in the proximal promoter regions of transcription start sites.
The results shown in Figure 6A demonstrate that MA gene
loci show increased levels of DNA methylation when com-
pared with BA gene loci. Each pairwise combination shows
high statistical significance (least significant t test p-value ¼
1.12 10
), indicating a strong association between MA
and intermediate DNA methylation levels, as seen in differen-
tially methylated regions, at these gene loci. The St-MA
choice gene TNFRSF10D provides a specific example of this
association across all three donors (Fig. 5C and Supporting
Information S8). A similar association of increased DNA
methylation at our identified MA loci is also observed in fetal
brain tissue (Fig. 6A).
Repressive Chromatin Signatures Associate with
Monoallelic Susceptible Gene Loci in Fetal Brain
Altered chromatin status is another epigenetic signal that may as-
sociate with monoallelic gene expression. We used the MA and
BA gene loci identified in our neural stem cells to interrogate
epigenomic data for a human fetal brain sample produced by the
NIH Epigenomics Roadmap initiative [30]. Direct allelic expres-
sion measurement of a stochastic monoallelic expressing gene
would typically show supposed ‘biallelic’ expression due to the
random nature of allelic choice in a nonclonal tissue. Neverthe-
less, any chromatin signatures associated with the subpopulation
of monoallelic expressing cells should be detectable when com-
pared with the more ‘consistent’ chromatin status of a constitu-
tive biallelic expressing gene. We therefore examined fetal brain
chromatin measures at the transcriptional start sites for loci
defined from our neural stem cell allelic expression data.
Using loci from the cortical donor as an example,
increased chromatin accessibility was evident in BA genes as
a 2.2-fold enrichment of DNase I hypersensitivity sites when
compared with St-MA genes (Fig. 6B). St-MA expressed
genes showed a 2.9-fold enrichment in H3K27me3 repressive
marks, whereas BA genes exhibited 2.2-fold more H3K4me3
and 1.85-fold more H3K9ac, both measures of open/active
chromatin. H3K9me3, a modification often linked with repres-
sion and heterochromatic silencing, showed a 1.85-fold
enrichment in biallelic clones, although it has also been noted
in actively transcribed regions [31, 32]. All comparisons
showed high statistical significance (Wilcoxon rank test-p-
value <2.2 10
). Similar results were also found for the
loci identified in the other two independent donors (Support-
ing Information Fig. S9). A comparison of all MA identified
Figure 4. Allelic expression after differentiation. Allelic expression ratios for four genes were measured in the clonal spinal cord lines SPC01,
SPC04, and SPC06 when in proliferative (Prolif) and differentiated (Diff) states. Measurements for three biological replicates (circles) are shown
and the mean value (horizontal line) indicated.
Jeffries, Perfect, Ledderose et al. 1943
loci compared to BA expressing genes also gave very similar
results. Surprisingly, non-neural tissue also showed similar his-
tone mark associations for H3K27me3 and H3K4me3 (Sup-
porting Information Fig. S10), suggesting a common, rela-
tively stable state of these measures across multiple tissues
types. H3K9me3 enrichment with BA loci, conversely, appears
to be unique to fetal tissue.
Monoallelic Genes Are Associated with Accelerated
Evolutionary Noncoding Sequences
Gimelbrant et al. found that monoallelic genes in clonal lym-
phoblastoid cell lines were more than twice as likely as bial-
lelic genes to be close to presumed regulatory conserved non-
coding sequences believed to be characterized by human-
Figure 5. Measurements from the gene TNFRSF10D that shows stochastic allelic choice in all three donors. (A): D
allelic expression measure-
ments clearly show a number of monoallelic expressing clones (red, labeled MA) and biallelic expression (blue, labeled BA). (B): Gene expres-
sion from quantitative PCR showing increased TNFRSF10D transcript levels in biallelic expressing clones when compared with monoallelic sister
lines from the same donor. (C): Methylation b levels deduced from five probes on the Illumina 27K methylation beadchip are shown for the cort-
ical and spinal cord donors. (D): Genomic structure of TNFRSF10D shown, together with the location of a 5
CpG island, the position of the
methylation probes, and also expressed SNPs showing MA expression. The SNPs are indicated as peaks representing D
measurements. Abbrevia-
tions: BA, biallelic expression; MA, monoallelic expression.
1944 Human Neural Stem Cell Allelic Expression
lineage-specific accelerated evolution [9, 33]. Using three sep-
arate datasets that define sequences [33–35], we confirm that
MA genes are significantly more likely to be located close to
accelerated evolutionary noncoding sequences (Supporting In-
formation Fig. S11). We also looked at positive selection
pressure on the coding gene regions by calculating the nonsy-
nonymous versus synonymous (dN/dS) ratio from a compari-
son of Human and Macaque genome. No significant differ-
ence was found between MA and BA genes.
A number of studies have reported allelic expression imbalan-
ces in non-neuronal cells and highlighted tissue-specific cis
effects [3, 23, 24, 36–38]. Allelic imbalance is also commonly
observed in human brain tissue, although any stochastic
choice of allele within individual cells is likely to be missed
by such analyses [39, 40]. We used a series of clonal human
neural stem cell lines to carry out a global allelic expression
survey, allowing detection of stochastic events in allelic
choice. We have shown that between 1.4% and 2.0% of auto-
somal genes from clonal lines derived from three different tis-
sues are subjected to MA expression. A subset of these
(between 0.47% and 1.14% of assayed genes) show evidence
for St-MA expression, many of which encoded proteins im-
portant in neurodevelopment. This frequency is similar num-
ber to the 1% estimate in a clonal murine neural stem cell
study [41] but lower than that found in mouse and human
lymphoblastoid cell studies [9, 42]. We believe this study
may underestimate the prevalence for the following reasons.
First, we excluded single SNP genes or those with low
expression due to the higher risk of false positives even
though we could validate a number by sequencing. Second,
examples can be found where small transcripts do not contain
sufficient informative heterozygous SNPs to be classified yet
are flanked by monoallelic expressed intergenic SNPs. In such
cases, the transcript would presumably show similar allelic
expression to that of the flanking SNPs due to the shared local
heterochromatin. Finally, our use of three clones from each
donor had limited power due to the limited amount of allelic
Our data suggest that while allelic expression may often
be stochastic, the actual loci undergoing such transcriptional
control is not random, as indicated by the significant overlap
of MA genes between different donors (genotypes) beyond
that expected by chance. Furthermore, there is a significant
overlap between our set of MA genes and those identified in
lymphoblastoid cells by Gimelbrant et al. [9]. Thus, a specific
subset of genes appears to be susceptible to MA regulation
and may also be conserved across multiple cell or tissue
types. A subset of the identified MA genes showed the same
monoallelic choice in all clonal lines within a donor. Genetic
cis-regulatory variants can lead to such an observation in ge-
netically related cell lines, and the use of only three donors
cannot totally rule out some of our observations falling into
this category. Nonetheless, a proportion of these identified
genes and intergenic regions may represent novel imprinted
loci, although confirmation of this status remains to be
Figure 6. Epigenomic measures from fetal brain at cortical donor defined monoallelic and biallelic loci. (A): DNA methylation measures using
the Illumina Methylation 27k beadchip show increased levels of methylation at monoallelic genes when compared with biallelic loci. Average b
values, indicating level of methylation, are shown for monoallelic (white boxes labeled MA) and biallelic expression (gray boxes labeled BA) in
cerebral cortex and spinal cord donors. The methylation status of loci defined in these loci is also shown for a fetal brain sample. (B): Chromatin
measures from a fetal brain sample (human epigenome atlas) at transcriptional start sites of stochastic monoallelic genes (white boxes) and bial-
lelic genes (gray boxes) identified in the cerebral cortex donor for Histone H3 lysine 4, H3 lysine 27, H3 lysine 9 trimethylation, H3 lysine 9
acetylation, and DNase I hypersensitivity sites (Supporting Information Fig. S9 for the other two donors). Abbreviations: BA, biallelic expression;
MA, monoallelic expression.
Jeffries, Perfect, Ledderose et al. 1945
How might the allelic expression we observe in neural
stem cells affect brain development? There are three reasons
for believing that the allelic status of a gene might have a sig-
nificant functional impact. First, we show that the allelic sta-
tus is maintained, at least for a subset of genes, as the neural
progenitor cells differentiate. This could contribute to clonal
phenotypes in the resulting neurons and glia. Second, the St-
MA genes are enriched for a number of genes important in
neurodevelopment, functioning, and disease. Finally, epige-
netic associations observed in human fetal brain infer possible
in vivo occurrence of St-MA gene expression. We have exam-
ined cultured neural stem cells, since it is only in culture that
clonal progenitors can effectively be examined biochemically.
Nonetheless, our observations suggest a subset of genetic loci
have a particular propensity for allelic regulation. We observe
that the promoter regions of MA genes show intermediate lev-
els of DNA methylation in comparison to BA genes, which
are generally hypomethylated, a finding that is also mirrored
in fetal brain. While the methylation assay used in this study
was not allele-specific, these data concur with the notion that
the unexpressed allele is silenced by DNA methylation. Also,
when compared with BA gene loci, MA genes have a distinct
combination of chromatin modifications in fetal brain tissue,
suggesting that they are less ‘open.’ These findings do not
directly prove that these genes are monoallelic in situ in the
developing brain, but indicate that they are distinct from the
BA genes in a manner consistent with what might be
expected if one allele were more permissive to transcription.
Our data support a model in which the developing brain
is a mosaic composed of distinct clones of cells, each with a
unique combination of monoallelic and biallelic expressed
genes. Differing combinations would then allow clonal diver-
sity from either gene dosage variations or functional differen-
ces due to polymorphic variation between the two alleles.
Alternatively, the impact of MA may be the unmasking of re-
cessive alleles or repression of semidominant alleles [43],
which, for example, would be limited to specific clones of
cells due to their ‘salt-and-pepper’ distribution in the brain.
Moreover, the same clonal diversity patterns would not be
precisely reproduced, even between individuals with the same
genotype. This mechanism could explain some of the discord-
ance observed between monozygotic twins for neurobiological
phenotypes and psychiatric disease [44].
Even if this phenomenon is restricted to cells in vitro, it
could have significance in that it might explain some of the
clonal diversity that is invariably observed in stem cell (and
other) clonal lines. Like many others, we have observed that
sister lines, which are demonstrably multipotential and
expressing the requisite combination of markers to be deemed
neural stem cells, nonetheless differ markedly in aspects of
their phenotype. CTX0E16 and CTX0E03, for example, both
have stable phenotype over multiple passages. Nonetheless,
the former reproducibly generates more neurons when differ-
entiated than its sister line. No doubt there are many causes
for this diversity, but the stochastic allelic expression choice
we have observed is likely to be one of them.
To conclude, we have identified widespread MA in clonal
human neural stem cell lines. Stochastic choice of allelic
expression appears evident for a subset of these genes, with
roles associated in nervous system development and function-
ing. The process has potential to allow significant cellular di-
versity within complex tissues such as the brain, although it
still remains to be seen if stochastic allelic choice is wide-
spread in vivo. Nevertheless, supportive epigenomic data
from fetal brain suggest it may be a possibility.
We thank Chloe Wong and Ruth Pidsley for help with the meth-
ylation experiments. We thank Ioannis Ragoussis and Ghazala
Mirza at the Wellcome Trust Centre for Human Genetics unit for
their assistance with the Illumina beadchip studies. This work
was supported by the Charles Wolfson Charitable Trust. J.M. is
supported by NIH Grant AG036039.
JP is a consultant for ReNeuron Ltd., a U.K. stem cell biotech
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    • "Cell surface diversity may therefore be a factor driven by random allelic expression imbalance, allowing alternate isoforms that may encode functional differences to be expressed in a subset of cells. This process would also provide a mechanism to support dosage variation, a phenomenon previously associated with monoallelic expression (Gimelbrant et al. 2007; Jeffries et al. 2012; Li et al. 2012). This may have profound implications for tissues such as the brain where cell identity and cell migration are highly dependent on receptor–ligand or receptor–morphogen interactions. "
    [Show abstract] [Hide abstract] ABSTRACT: Clonal level random allelic expression imbalance and random monoallelic expression provides cellular heterogeneity within tissues by modulating allelic dosage. Although such expression patterns have been observed in multiple cell types, little is known about when in development these stochastic allelic choices are made. We examine allelic expression patterns in human neural progenitor cells before and after epigenetic reprogramming to induced pluripotency, observing that loci previously characterized by random allelic expression imbalance (0.63% of expressed genes) are generally reset to a biallelic state in induced pluripotent stem cells (iPSCs). We subsequently neuralized the iPSCs and profiled isolated clonal neural stem cells, observing that significant random allelic expression imbalance is reestablished at 0.65% of expressed genes, including novel loci not found to show allelic expression imbalance in the original parental neural progenitor cells. Allelic expression imbalance was associated with altered DNA methylation across promoter regulatory regions, with clones characterized by skewed allelic expression being hypermethylated compared to their biallelic sister clones. Our results suggest that random allelic expression imbalance is established during lineage commitment and is associated with increased DNA methylation at the gene promoter.
    Article · Aug 2016
    • "Also, it was observed that exposure to different forms of early life traumas led to similar methylation changes in blood and brain cells (Klengel et al., 2013). It has been proposed that epigenetic changes induced early in development in particular may be present across many different tissues, because they are propagated through cell division (Feinberg & Irizarry, 2010; Jeffries et al., 2012; Mill & Heijmans, 2013). "
    [Show abstract] [Hide abstract] ABSTRACT: Tic disorders are moderately heritable common psychiatric disorders that can be highly troubling, both in childhood and in adulthood. In this study, we report results obtained in the first epigenome-wide association study (EWAS) of tic disorders. The subjects are participants in surveys at the Netherlands Twin Register (NTR) and the NTR biobank project. Tic disorders were measured with a self-report version of the Yale Global Tic Severity Scale Abbreviated version (YGTSS-ABBR), included in the 8th wave NTR data collection (2008). DNA methylation data consisted of 411,169 autosomal methylation sites assessed by the Illumina Infinium HumanMethylation450 BeadChip Kit (HM450k array). Phenotype and DNA methylation data were available in 1,678 subjects (mean age = 41.5). No probes reached genome-wide significance (p < 1.2 × 10-7). The strongest associated probe was cg15583738, located in an intergenic region on chromosome 8 (p = 1.98 × 10-6). Several of the top ranking probes (p < 1 × 10-4) were in or nearby genes previously associated with neurological disorders (e.g., GABBRI, BLM, and ADAM10), warranting their further investigation in relation to tic disorders. The top significantly enriched gene ontology (GO) terms among higher ranking methylation sites included anatomical structure morphogenesis (GO:0009653, p = 4.6 × 10-15) developmental process (GO:0032502, p = 2.96 × 10-12), and cellular developmental process (GO:0048869, p = 1.96 × 10-12). Overall, these results provide a first insight into the epigenetic mechanisms of tic disorders. This first study assesses the role of DNA methylation in tic disorders, and it lays the foundations for future work aiming to unravel the biological mechanisms underlying the architecture of this disorder.
    Full-text · Article · Oct 2015
    • "The functional significance of such a mechanism is not yet fully understood, but it has been proposed that lineage relationships contribute to the establishment of precise canonical microcircuits [1, 5] . Given that retinotopic map formation has been shown to be controlled by molecular gradients (legend continued on next page) and neuronal activity [17, 18], the influence of lineage upon a tectal neuron's functional properties could reflect the inheritance of a particular profile of gene expression [19, 20] and/ or activity-dependent processes [2, 4]. Fundamentally, the fact that clonal relationships influence responses in the optic tectum, an ancient brain structure that is common to all vertebrates , indicates that lineage relationships may represent a general and evolutionarily conserved principle that contributes to the organization of neural circuits. "
    [Show abstract] [Hide abstract] ABSTRACT: Understanding how neurons acquire specific response properties is a major goal in neuroscience. Recent studies in mouse neocortex have shown that "sister neurons" derived from the same cortical progenitor cell have a greater probability of forming synaptic connections with one another [1, 2] and are biased to respond to similar sensory stimuli [3, 4]. However, it is unknown whether such lineage-based rules contribute to functional circuit organization across different species and brain regions [5]. To address this question, we examined the influence of lineage on the response properties of neurons within the optic tectum, a visual brain area found in all vertebrates [6]. Tectal neurons possess well-defined spatial receptive fields (RFs) whose center positions are retinotopically organized [7]. If lineage relationships do not influence the functional properties of tectal neurons, one prediction is that the RF positions of sister neurons should be no more (or less) similar to one another than those of neighboring control neurons. To test this prediction, we developed a protocol to unambiguously identify the daughter neurons derived from single tectal progenitor cells in Xenopus laevis tadpoles. We combined this approach with in vivo two-photon calcium imaging in order to characterize the RF properties of tectal neurons. Our data reveal that the RF centers of sister neurons are significantly more similar than would be expected by chance. Ontogenetic relationships therefore influence the fine-scale topography of the retinotectal map, indicating that lineage relationships may represent a general and evolutionarily conserved principle that contributes to the organization of neural circuits.
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