Supplementary sex-specific transcriptome in human cortex
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Supplementary Material
Transcriptome Analysis of Male-Female Differences in Prefrontal Cortical
Development
Cynthia Shannon Weickert, Ph.D.1,2, Michael Elashoff, Ph.D.3, Allen Brent Richards,
Ph.D.1, Duncan Sinclair, BSc.2, Sabine Bahn, Ph.D.4, Svante Paabo, Ph.D.5, Philipp
Khaitovich, Ph.D.5,6, and Maree J. Webster, Ph.D.7
1
MiNDS Unit, CBDB, NIMH, IRP, Bethesda, MD, 20894
Schizophrenia Research Institute (SRI), University of New South Wales, Prince of
Wales Medical Research Institute, Sydney, Australia
3
Cardiodx, Palo Alto, CA 94304
4
Institute of Biotechnology, University of Cambridge, Cambridge, CB2 1QT, UK
5
Department of Evolutionary Genetics, Max Plank Institute for Evolutionary
Anthropology, Leipzig, Germany
6
Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese
Academy of Sciences, 320 YueYang Rd., Shanghai, 200031 China
7
Stanley Medical Research Institute, 9800 Medical Center Drive, Rockville, MD 20850
2
Corresponding Author:
Maree J. Webster
Stanley Medical Research Institute
9800 Medical Center Drive, Suite C-050
Rockville, MD 20850
Phone: 240 499 1171
Fax: 301 251 8602
Email: websterm@stanleyresearch.org
Acknowledgements: We acknowledge the assistance of Dr. H. Ronald Zielke and Robert
Vigorito of the University of Maryland Brain and Tissue Bank for Developmental
Disorders.
Funding: Supported by the Stanley Medical Research Institute, the intramural program
of NIMH, the Schizophrenia Research Institute, the University of New South Wales and
the Prince of Wales Medical Research Institute.
Supplementary sex-specific transcriptome in human cortex
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Supplementary Introduction
Males and female humans differ in their cognitive, psychological and emotional
development; however, it is not known if and when they differ in global gene expression
patterns during brain development. Gender dimorphisms exist in spatial ability and
aggressiveness (1) and in the propensity to develop psychiatric disorders such as autism,
attention deficit hyperactivity disorder (ADHD) and depression (2). Sex differences exist
in cortical complexity (3), in adult regional brain volumes (4) and in childhood gray
matter volumes (5). Divergent development of the male and female brain is believed to
result from the sex-specific development of gonads that indirectly influence the
developing brain via gonadal hormones (6). However, this endocrine mechanism may
work in concert with other more local acting sex specific developmental signals
originating in the brain itself.
Neuronal nuclei of males and females contain a different complement of sex
chromosomes that harbor distinct genes that may directly impact the developing brain.
We hypothesized that gender dimorphisms in human brain development may include
differential cortical expression of genes unique to the sex chromosomes (7, 8) as well as
differential cortical expression of genes on the autosomes. In this study, we first give a
broad overview of differential gene expression across human postnatal development, then
we identify and functionally group 130 transcripts that are differentially expressed in the
brain of developing males compared to females. While we identify thousands of
transcripts that change with age, only a small subset of these change in a sex-specific
manner during development. Therefore, sex does not appear to dictate ubiquitous
transcriptional changes across development, but rather may impact human cortical
Supplementary sex-specific transcriptome in human cortex
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development via selective control of specific genes. The sex-specific changes in gene
expression that we find in the developing human frontal cortex represent part of the
molecular biological substrate that distinguishes the male from the female brain.
Supplementary Material and Methods
Tissue Collection
Sixty cases ranging in age from 6 weeks to 49 years (Supplementary Table 1)
were obtained from the University of Maryland Brain and Tissue Bank for
Developmental Disorders (UMBB; NICHHD contract # NO1-HD8-3283; 37 males and
23 females, 33 African Americans and 27 Caucasians). Frozen tissue samples from 7-13
cases (defined as normal controls by the forensic pathologists at UMBB) were selected
from each of seven developmental periods. Samples were included in the cohort if the
pH was above 6.25 and if the RNA was of good quality [over 5.8, (9)] as determined by
the high resolution Bioanalyzer electrophoresis system (Agilent Technologies, Palo Alto,
CA, USA). The cases used in each experiment did not differ significantly within each age
group according to brain pH or RNA Integrity Number (RIN) value.
Total RNA Isolation
Total RNA was extracted from 300 mg gray matter of the middle frontal gyrus
(Brodman’s area 46) using Trizol reagent (Invitrogen, Carlsbad, CA, USA) according to
the manufacturer’s instructions (10). To assess RNA quality, approximately 100-200 ng
RNA was applied to an RNA 6000 Nano LabChip, without heating prior to loading. The
RIN was calculated by an algorithm incorporating information from the entire
electrophoretic trace and used as an indicator of RNA quality, ranging from 1 (lowest
quality) to 10 (highest quality). cDNA was synthesised in three reactions per sample and
Supplementary sex-specific transcriptome in human cortex
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pooled, from 3 µg of total RNA per 26.25 µl reaction using the Superscript First-Strand
Synthesis Kit (Invitrogen) according to the manufacturer’s protocol.
Microarray Experimental Design
Total RNA from 45 cases was purified through a Qiagen RNA miniKit column
(Qiagen Inc, Valencia CA USA) according to the manufacturers protocol. RNA was
processed through the Affymetrix preparation protocol [www.affymetrix.com, (11)] and
hybridized to HG-U133 version 2.0+ (GeneChips, Affymetrix CA, USA). Hybridized
arrays were subjected to rigorous quality control including analysis of 5’ 3’ ratios
(included range 0.40-0.79), percent present (included range 37-47%), average pair-wise
correlation analysis and principle component analysis (PCA), resulting in the exclusion of
3 individuals.
Affymetrix Microarray Suite (MAS 5.0) was used for image processing and data
acquisition. The Bioconductor package was used to compute normalized expression
values from the Affymetrix.cel files. Statistical analysis was performed using R and
Bioconductor software. Probe sets that met the criteria of being 50% present in at least
one of the age/gender subgroups were retained in the analysis (33 210 probes sets
retained, 61% of total number). Differential gene expression across chronological age and
between males and females were analyzed in a linear regression model including age (log
scale), gender and their interaction as independent factors and gene expression (log scale)
as the dependent variable.
Supplementary sex-specific transcriptome in human cortex
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Microarray Validation
We confirmed selected results from the microarray experiment using quantitative realtime PCR (RT-PCR) from RNA extracted from 58 individuals as more cases were added
to the collection over time (9). We targeted expression levels of a selection of transcripts
that showed large expression changes between genders. Pre-designed TaqMan Gene
Expression Assays (Applied Biosystems, Foster City, CA, USA) with specific primer and
probe combinations were chosen for each of the genes analyzed: SMCY
(Hs01104401_g1), NLGN4Y (Hs01034378_s1), PCDH11X/Y (Hs00263173_m1),
PCDH11X (Hs01673213_m1), HSPA1A (Hs00271229_s1), HSPH1 (Hs00971475_m1),
DNAJB1 (Hs00428680_m1), HSPD1 (Hs01036746_g1), HSPB1 (Hs00356629_g1) and
HSP90AA1 (Hs00743767_sH; Table S5). The location along the transcript that was
targeted by the primer/probe set for each gene was chosen to match as closely as possible
the location along the transcript targeted by the Affymetrix gene chip assay. The Y
version of PCDH11 could not be targeted specifically by qPCR, so we measured both the
"pan" transcript (PCDH11X/Y) and the X version (PCDH11X). The ‘pan’ probe
(Hs00263173_m1) detected mRNA from both PCDH11Y (isoform c) and PCDH11X
(isoforms c and d). The other probe (Hs01673213_m1) was specific to the X
chromosome (PCDH11X isoforms c and d).
Each 10 µl qPCR reaction contained primers (final concentration 900 nmol/L),
FAM-labeled probe (250 nmol/L), and 1.14 ng cDNA in 1x Taqman Universal
Mastermix containing AmpliTaq Gold DNA polymerase, deoxynucleoside triphosphates
(dNTPs), uracil-N-glycosylase and passive reference. The PCR protocol used involved
incubation at 50ºC for 2 min and 95ºC for 10 min, followed by 40 consecutive cycles of
Supplementary sex-specific transcriptome in human cortex
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95ºC for 15 s and 60ºC for 1 min. Serial dilutions of pooled cDNA, synthesized from
seven samples, one from each developmental time point, were included on every qPCR
plate and used by Sequence Detection Software (SDS; Applied Biosystems) to quantify
sample expression by the relative standard curve method. Control wells containing no
cDNA template displayed no amplification in any assay. Efficiencies of the qPCR
reactions ranged from 77% to 104%, with R2 values of between 0.95 and 1.00. All
reactions were performed in triplicate. Samples were excluded if standard deviation of
the triplicates was greater than 30% of the mean. Expression levels were normalized to
the geometric mean of three ’housekeeper’ genes that did not change expression with
development: HMBS (Hs00609297_m1), GUSB (Hs99999908_m1), and PPIA
(Hs99999904_m1; Table S5). A fourth housekeeper gene, UBC (Hs00824723_m1), was
included in normalization of HSPA1A, HSPH1, DNAJB1, HSPD1, HSPB1 and
HSP90AA1 as these qPCRs were run from a different RNA isolation performed later.
Population outliers were excluded if the normalized expression value was greater than 2
standard deviations from the group mean. One-way and two-way ANOVAs were
performed, with gender or gender and age group as independent variables and normalized
expression levels for the gene of interest as the dependent variable. To maximize power
to detect early gender differences in HSP mRNAs by qPCR, we combined the neonate
and infant groups and contrasted this to the post-infancy time points.
Supplementary Results
At each range of alpha level we found many more transcripts to be significantly changed
by subject age than what would be expected by chance (Table S2). We identified a total
of 8061 probe sets (5,136 genes) that changed significantly in expression across postnatal
Supplementary sex-specific transcriptome in human cortex
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development at a fairly conservative threshold (p<0.001, two-sided) Overall, a large
number (24%) of the transcripts expressed in the human prefrontal cortex changed across
development and this level of significance (p<0.001) corresponds to a false discovery rate
of ~0.4% based on a permutation analysis. Therefore, the majority of the developmental
changes detected are expected to be genuine. Transcripts that change in an age-dependent
manner were distributed among many functional GO categories and are also evenly
distributed across the human chromosomes (Table S2).
Of the 8,061 probe sets that changed significantly with age (p<0.001) the
magnitude of the fold change (maximum value vs minimum) in gene expression spanned
a considerable range. Most of the changes in transcript expression were moderate (under
2-fold; 6548 probe sets), many were substantial (over 2-fold but under 5-fold; 1397 probe
sets), and some were quite large (over 5-fold; 116 probe sets). When grouping significant
age-dependent changes (p<0.001) by functional groups or gene ontology (GO) categories
we identified hundreds of functional groups with genes that changed significantly during
the maturation of the frontal cortex. The overall percent of genes that were
developmentally regulated in any given GO category that contained 10 or more members
varied considerably (<1% to 78%, chi-square p<10-6). Thus, significant developmental
changes in gene expression did not occur uniformly across all cellular pathways as
defined by the GO classification. The GO categories were sorted according to the
percentage of transcripts that changed significantly by regression analysis or by ANOVA.
Twenty-one GO categories had at least 50% of their member transcripts changing
significantly with age. They are listed in order of those with the highest percentage of
changed transcripts to the lowest: 1) NADH dehydrogenase activity, 2) NADH
Supplementary sex-specific transcriptome in human cortex
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dehydrogenase (ubiquinone) activity 3) calcium- and calmodulin-dependent protein
kinase activity, 4) synapse, 5) cytosolic large ribosomal subunit (sensu Eukaryota), 6)
neurotransmitter secretion, 7) MAP kinase activity, 8) androgen receptor signaling
pathway, 9) nuclear pore, 10) actin cytoskeleton, 11) protein tyrosine/serine/threonine
phosphatase activity, 12) synaptic vesicle, 13) glycolysis, 14) membrane fusion, 15) actin
filament, 16) thyroid hormone receptor binding, 17) protein kinase binding, 18) axon
guidance, 19) JNK cascade, 20) Ras protein signal transduction and 21) vesicle-mediated
transport.
Sex specific changes in gene expression were not equally distributed among the
chromosomes (Table S2). Sex differences were found among <1% of the transcripts
located on the autosomes. Male versus female differences in expression of genes on the
autosomes were found to remain significant by doing a permutation test excluding X and
Y chromosomal genes. While expression of the Y-linked genes can be 35 times higher in
males as compared to females (Table S3), the fold change is somewhat arbitrary because
the level of expression of the Y-linked genes in the female, as reported by the array
software, corresponds to the background level for those genes.
In order to rule out that gender effects observed in HSP gene expression as
measured by qPCR were associated with a differential cause of death in infant females
we determined that no significant differences in frequencies of specific causes of death
between infant males [SIDS (2/9), asphyxia (4/9), other (3/9)] and infant females [SIDS
(4/5), asphyxia (1/5), other (0/5)] existed by chi-squared analysis (df=2, chisquared=4.71, less than p<0.05). Thus, overall we were able to replicate the gender
difference in HSPs in 4/6 transcripts by qPCR and we determined the gender difference
Supplementary sex-specific transcriptome in human cortex
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was due to an increase in expression in infant females which was not secondary to a
gender difference in the cause of death.
Supplementary Discussion
Protocadherin (PCDH11Y) belongs to a family of cell adhesion molecules that
direct the formation of specific neuronal circuits and synapses (12) in the developing
brain through neuroanatomically restricted expression and gene regulation (13).
PCDH11X differs from PCDH11Y in amino acid structure and function (14, 15). We
found a threefold increase in levels of total PCDH11 in infant males as compared to
females and our data demonstrate that the X-linked form of PCDH11 is expressed at
similar levels in males and females, indicating that the X-linked homolog is not
compensating for gender differences in expression levels by being up-regulated in
females. The increased expression of PCDH11 in the frontal cortex of infant males
suggests that it may play a unique role in the organization of the brain circuits involved in
sexually dimorphic behaviors and perhaps in the propensity to manifest psychiatric
illness in developing males. Protocadherin family members have been proposed as
etiological factors in the development of schizophrenia; however conclusive genetic
evidence linking protocadherin to schizophrenia is lacking (16-18). However, further
investigation of the role of protocadherins in developmental brain disorders that
particularly impact males and involve the prefrontal cortex seems warranted.
The increased mRNA for neuroligin (NLGN4Y) that we detect in males could
also drive male-specific brain development in the infant. NLGN4Y is a member of the
neuroligin family of cell adhesion molecules that can influence neuronal contacts by
changing the balance of excitatory and inhibitory synapses during development (19).
Supplementary sex-specific transcriptome in human cortex
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Genomic mutations in neuroligins have been linked to the human developmental brain
disorder, autism-spectrum disorder (20). The absence of NLGN4Y found by microarray
in females was confirmed by qPCR demonstrating the lack of NLGNY-like transcript
expression in females. Our results suggest that some Y chromosome genes may be more
active in early human life but the reasons for this are unknown. It is possible that the
increased secretion of testosterone that occurs peri-natally (21) and then decreases to low
levels in toddlers and school-age males, impacts the early expression of the protocadherin
and neuroligin gene in the male brain. However, it is unlikely that testosterone alone
controls the expression of these Y chromosome genes up-regulated early in life as they
are not up-regulated again during or after puberty when blood testosterone increases
again. Instead, it is possible that distinct transcription factors, DNA methylation events or
mRNA transcript stability may change as males develop postnatally.
In contrast to the transcripts that increased in infant males, another set of
transcripts was found to have increased in expression specifically in infant females. The
microarray study revealed eight heat shock protein (HSP) genes that differed in
expression levels according to gender. The qPCR analysis confirmed that four HSP genes
were significantly increased in females. The gender difference in expression of these HSP
mRNAs are driven by specific increases in infant females (3-12 months old) relative to
older females and all males. HSPs are known to play a crucial role in the folding,
maturation, translocation to the nucleus and transcription regulatory activity of hormone
receptors in general (22-24), and thus may be acting in a coordinated fashion to mediate
some aspects of gender-specific response to hormones during brain development. More
specifically, since HSP40, HSP70 and HSP90 compose the majority of components that
Supplementary sex-specific transcriptome in human cortex
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are critical for maturation of the glucocorticoid receptor into a high steroid affinity state
(25, 26), the infant female brain may be better equipped to bind, process and modulate
stress hormones than the male brain or than older female brain.
Alternately, HSPs are versatile molecules responsive to more generalized cellular
stress and thus are not only capable of refolding denatured proteins and promoting
cellular survival, but are also active in immune surveillance (27). Hence, the infant
female brain may be more resilient to oxidative damage or immune challenge. Increased
HSP70 expression has been shown to decrease neonatal hypoxic/ischemic brain injury in
a mouse model by moderating the pro-apoptotic effects of apoptosis-inducing factor
(AIF) (28) and cytochrome c (29). These data suggest that gender differences in HSP
expression, acting to oppose apoptotic pathways, may contribute to the decreased risk of
respiratory infant death in females (30). Female levels of HSP expression are twice as
high in rat heart, muscle, and kidney and in human serum (31, 32) suggesting the female
bias in HSP expression is not restricted to the brain. HSP gene transcription is regulated
by estrogen in the brain (33), however infant females have much lower levels of estrogen
as compared to adult females when HSPs are down-regulated suggesting that estrogen
may not be critical for this early gender difference in HSP mRNA expression. In the adult
brain, gender differences in HSP expression are not always apparent, however gender
differences in cortical and hippocampal HSP70 and HSP90 expression in response to
antidepressant administration (34) and in midbrain HSP70 after alcohol-feeding (35) have
been found. Thus, gender differences in HSPs in brain may be restricted to infants unless
provoked by environmental triggers.
Supplementary sex-specific transcriptome in human cortex
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Recent evidence has suggested a role for HSPs in the aetiology of a number of
neurodevelopmental disorders, including schizophrenia and autism. Polymorphisms in
the HSP70 gene have been associated with schizophrenia in a Korean cohort (36), and
increased expression of HSPA1A, HSPA1B and HSPB1 has been observed in the
prefrontal cortex of patients with schizophrenia (37). Increased prevalence of antibodies
against HSP60 (38), HSP70 and HSP90 (39) have been reported in patients with
schizophrenia, with particular increases in HSP60 in female patients (40). HSPA6,
HSPB1, HSPA1A and DNAJB1 have been shown to be increased in expression in
individuals with autism (41). If HSPs contribute to the aetiology of such developmental
brain disorders, gender dimorphism in their expression during development could
contribute to sex differences observed in their onset, prevalence and vulnerability to
neurodevelopmental insults and merit further investigation. For example, the increased
expression of HSP in infant females may serve to protect them from neonatal damage due
to hypoxia or immune challenge, and in so doing reduce the risk of later psychiatric
illness, particularly since foetal hypoxia and 2nd trimester infection are considered risk
factors for schizophrenia (42, 43). Indeed the elevated levels of HSP mRNA found in the
prefrontal cortex of adult patients with schizophrenia have been suggested to be a long
lasting response to early infective immune challenge (37).
Gender difference in cognitive and behavioral development of humans exist and
for the first time we show that gender differences extend to the transcriptome in the
cortex of normal humans, suggesting that there may be a molecular basis for gender
differences in brain function. Psychological differences between males and females are
most prominent in the area of spatial reasoning and verbal function (1). Thus, we suggest
Supplementary sex-specific transcriptome in human cortex
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that part of the biological substrate for these gender differences may be related to
differential expression of genes on the sex chromosomes and on the autosomes. The
early expression of Y chromosome genes in the infant male brain may be a mechanism
that directs male specific development of brain cells. The sexually dimorphic expression
of autosomal genes encoding heat shock proteins may provide insight into the molecular
mechanisms protecting the female brain from early insults. While we have focused here
on gender differences in gene expression across human brain development, the majority
of genes in the frontal cortex are expressed in a similar developmental pattern in both
males and females. Thus, at the molecular level, we find that gene expression in males
and females is more similar than different, which may reflect the fact that there are many
similarities in the overall cognitive and behavioral development of the genders (1).
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42.
Cannon M, Jones PB, Murray RM. Obstetric complications and schizophrenia:
Historical and meta-analytic review. American Journal of Psychiatry 2002;
159(7): 1080-1092.
43.
Cannon M, Clarke MC. Risk for schizophrenia -- broadening the concepts,
pushing back the boundaries. Schizophrenia Research 2005; 79(1): 5-13.
Supplementary sex-specific transcriptome in human cortex
18
Supplementary Table 1. Demographic details. Abbreviation: m, male; f, female; PMI,
postmortem interval defined as interval between death and freezing of the brain; AA,
African American; C, Caucasian; RIN, RNA integrity number.
Group
PMI
(hours)
Gender
Age
(years)
pH
Race
average
RIN
cause of death
neonatea,b
28
m
0.21
6.6
AA
8.5
sids
neonatea,b
11
m
0.15
6.9
C
8.3
congenital heart defect
neonatea,b
17
m
0.15
6.6
AA
8.7
sids
neonateb
19
f
0.18
6.5
C
7.1
asphyxia
neonatea,b
25
m
0.19
6.5
AA
8.0
asphyxia
neonatea,b
27
f
0.16
6.5
AA
7.9
pneumonia
neonatea,b
27
m
0.11
6.5
AA
7.9
asphyxia
neonatea,b
24
f
0.24
6.7
AA
7.7
positional asphyxia
infanta,b
14
f
0.25
6.5
AA
8.8
sids
infanta,b
22
f
0.52
6.8
AA
8.4
sids
infantb
18
f
0.48
6.5
AA
6.5
sids
infanta,b
9
m
0.38
6.5
AA
7.2
sids
infanta,b
18
m
0.91
6.9
AA
8.0
sids
infanta,b
24
m
0.52
6.7
AA
8.2
accident/asphyxia
infanta,b
5
m
0.39
6.8
AA
8.6
asthma
infantb
21
f
0.67
6.6
AA
5.9
sids
infanta,b
22
m
0.33
6.5
C
8.0
bronchoneumonia
b
10
f
0.91
6.4
AA
6.6
bronchiolitis
infantb
19
m
0.32
6.4
C
6.7
asphyxia suffocation
infanta,b
27
m
0.35
6.7
C
8.1
myocarditis
infantb
18
m
0.82
6.65
AA
7.3
hypothermia
toddlera,b
24
f
1.58
6.9
C
7.8
myocarditis
toddlera,b
18
m
4.64
6.9
C
7.0
accident
toddlera,b
19
m
4.86
6.7
AA
8.4
drowning
toddlerb
11
f
2.21
6.9
AA
7.4
meningitis
toddlera,b
22
f
2.45
6.7
AA
7.6
no anatomical cause
toddlerb
13
m
2.00
6.89
AA
6.9
cardiac arhythmia
toddlera,b
44
f
2.71
6.5
C
7.0
drowning
toddlera,b
infant
27
m
2.19
6.6
AA
7.6
asthma
agea,b
17
m
5.39
6.7
C
8.2
drowning
school agea,b
16
m
12.42
6.8
C
8.2
drowning
school
ageb
18
m
7.84
6.8
AA
7.0
accident
school
agea,b
18
f
12.98
6.9
C
7.8
accident
school
ageb
school
12
f
8.92
6.4
C
6.7
cardiac arhythmia
school agea,b
12
f
11.54
6.4
C
7.3
asthma
school
agea,b
20
f
8.14
6.8
C
7.6
asphyxia
school
agea,b
5
m
8.01
6.8
AA
8.2
cardiac arhythmia
Supplementary sex-specific transcriptome in human cortex
19
Group
PMI
(hours)
Gender
Age
(years)
pH
Race
average
RIN
cause of death
teenagea
13
m
15.00
6.8
AA
6.2
accident
teenageb
16
m
17.49
6.7
C
6.5
accident
teenagea
12
m
17.82
6.8
C
9.2
accident/asphyxia
teenagea,b
16
m
17.69
6.8
AA
8.2
accident
teenagea,b
25
m
17.05
6.7
C
7.5
drowning
teenagea,b
19
m
17.38
6.84
C
6.8
accident
teenagea,b
16
f
16.68
6.81
C
7.6
multiple injuries
teenageb
20
f
16.34
6.6
C
6.7
multiple injuries
young
adultb
32
f
25.10
6.54
C
6.8
pulmonary embolism
young
adulta,b
16
f
25.38
6.73
C
8.3
accident
young
adulta,b
4
m
22.92
6.84
AA
8.2
ASCVD
young adulta,b
13
m
21.93
6.96
C
7.8
mva
young
adulta,b
18
m
20.14
6.5
AA
7.2
accident
young
adultb
7
m
21.97
6.25
AA
6.9
obesity
young
adulta,b
7
m
24.93
6.92
C
8.4
mva
young adulta,b
14
f
23.62
6.57
AA
8.1
asthma
adulta,b
18
m
46.18
6.75
AA
7.8
accident
adulta,b
18
m
42.94
6.49
C
7.3
accident
adulta,b
13
m
35.99
6.73
C
8.0
coronary artery dis
adulta,b
8
m
38.63
6.37
AA
7.6
ASCVD
adultb
12
m
47.44
6.56
C
6.4
ASCVD
adulta,b
19
f
38.42
6.98
AA
7.6
HASCVD
adulta,b
7
f
49.22
6.78
AA
7.4
cirrhosis of liver
a sample
b
included in microarray and sex chromosome quantitative PCR experiments
sample included in heat shock protein quantitative PCR experiments
Supplementary sex-specific transcriptome in human cortex
20
Supplementary Table 2. The number of detectable probe sets tabulated according to
chromosome. For each chromosome, the number and percentage of probe sets showing
differential regulation (p<.001) by regression as a function of age, sex and the interaction of
age and sex are shown.
Chromosome
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
X
Y
Probe
Sets
2951
2130
1802
1239
1485
1614
1511
1095
1193
1207
1555
1538
658
990
975
1154
1577
540
1466
802
317
612
934
35
Age Significant
(p<.001)
725
24.6%
590
27.7%
427
23.7%
323
26.1%
425
28.6%
423
26.2%
369
24.4%
329
30.0%
304
25.5%
292
24.2%
391
25.1%
425
27.6%
181
27.5%
230
23.2%
223
22.9%
260
22.5%
380
24.1%
159
29.4%
295
20.1%
208
25.9%
71
22.4%
136
22.2%
244
26.1%
10
28.6%
M vs F Significant
(p<.001)
11
0.37%
6
0.28%
4
0.22%
0
0.00%
1
0.07%
6
0.37%
5
0.33%
1
0.09%
1
0.08%
1
0.08%
3
0.19%
3
0.20%
2
0.30%
7
0.71%
2
0.21%
0
0.00%
5
0.32%
2
0.37%
9
0.61%
1
0.12%
0
0.00%
1
0.16%
16
1.71%
23
65.71%
Interaction Significant
(p<.001)
8
0.27%
7
0.33%
1
0.06%
3
0.24%
1
0.07%
5
0.31%
3
0.20%
1
0.09%
1
0.08%
2
0.17%
2
0.13%
4
0.26%
2
0.30%
3
0.30%
1
0.10%
0
0.00%
3
0.19%
0
0.00%
9
0.61%
0
0.00%
2
0.63%
0
0.00%
3
0.32%
2
5.71%
Supplementary sex-specific transcriptome in human cortex
21
Supplementary Table 3. Genes on the sex chromosomes that show a main effect of sex on expression levels
Abbreviations: C, Chromosome: FC, Fold Change; SEM, standard error of the mean.
Symbol
Name
C
FC
Mean
Female
SEM
Female
Mean
Male
SEM
Male
p-value
M vs F
probe sets
4.07
>0.00001
236694_at
CYorf15A
chromosome Y open reading frame 15A
Y
2.89
29.91
1.75
84.9
CYorf15B
chromosome Y open reading frame 15B
Y
2.06
30.56
1.93
63.51
2.39
>0.00001
214131_at, 223645_s_at, 223646_s_at,
DDX3Y
DEAD (Asp-Glu-Ala-Asp) box polypeptide 3, Y-linked
Y
13.3
29.58
2.42
372.1
12.14
>0.00001
205000_at, 1570360_s_at, 205001_s_at
EIF1AY
eukaryotic translation initiation factor 1A, Y-linked
Y
3.96
30.98
1.96
117.91
5.31
>0.00001
204409_s_at, 204410_at
HSFY1
heat shock transcription factor, Y-linked 1
Y
1.64
31.47
2.11
47.69
2.08
>0.00001
224007_at
NLGN4Y
Neuroligin 4Y
Y
5.85
30
2.21
161.93
6.13
>0.00001
207703_at
PCDH11Y
protocadherin 11Y
Y
1.66
40.06
1.92
62.9
3.53
>0.00001
211227_s_at, 217049_x_at
ribosomal protein S4, Y-linked 1
Y
38.64
29.06
2.1
1045.8
19.3
>0.00001
201909_at
Smcy homolog, Y-linked
Y
8.64
34.03
2.44
264.37
9.28
>0.00001
206700_s_at
TTTY15
testis-specific transcript Y15
Y
3.08
35.04
2.43
91.9
4.7
>0.00001
214983_at
TMSB4Y
thymosin, beta 4, Y-linked
Y
1.61
30.39
2.57
49.68
2.72
>0.001
206769_at
ubiquitin specific protease 9, Y-linked
Y
8.71
30.12
1.88
278.62
7.48
>0.00001
228492_at, 206624_at
UTY
ubiquitously transcribed tetratricopeptide repeat gene, Y-linked
Y
2.17
27.3
1.85
58.15
1.93
>0.00001
211149_at
ZFY
zinc finger protein, Y-linked
Y
3
27.19
2.2
83.5
2.58
>0.00001
230760_at, 207246_at
acetylserotonin O-methyltransferase-like
X/Y
1.26
259.92
7.68
325.42
7.63
>0.0001
36553_at, 36554_at, 209394_at
CD99 antigen
X/Y
1.6
222.08
22.36
336.08
17.23
>0.0001
201029_s_at, 201028_s_at
X
-1.22
1493.7
39.83
1217.61
20.42
>0.0001
201210_at
RPS4Y1
SMCY
USP9Y
ASMTL
CD99
DDX3X
EIF2S3
DEAD (Asp-Glu-Ala-Asp) box polypeptide 3, X-linked
X
-1.18
488.9
15.29
406.5
8.92
>0.001
224936_at
haloacid dehalogenase-like hydrolase domain containing 1A
X
-1.31
137.79
5.38
103.19
3.44
>0.0001
203974_at
oral-facial-digital syndrome 1
X
-1.38
64.05
5.62
51.33
2.11
>0.001
241751_at
PCDH11X
protocadherin 11 X-linked
X
2.56
92.59
8.86
238.97
18.38
>0.00001
210292_s_at, 241772_at
SMCX
Smcy homolog, X-linked
X
-1.35
107.81
4.31
83.15
2.54
>0.0001
239207_at
USP9X
ubiquitin specific protease 9, X-linked
X
-1.16
1233.34
43.33
1119.46
15.47
>0.001
201100_s_at
WBP5
WW domain binding protein 5
X
-1.31
551.46
61.74
471.48
12.76
>0.001
217975_at
XIST
X (inactive)-specific transcript
X
-116.65
3065.43
108.58
27.05
1.37
>0.00001
HDHD1A
OFD1
eukaryotic translation initiation factor 2, subunit 3 gamma, 52kDa
224588_at, 224589_at, 214218_s_at,
221728_x_at, 227671_at, 224590_at,
231592_at
Supplementary sex-specific transcriptome in human cortex
22
Supplementary Table 4. Genes on the autosomes that show a main effect of sex on
expression levels but do not show an effect of age on expression levels (* indicates those
genes that show an interaction between sex and age)
Probe
Name
Symbol
Locus
C
ANOVA p
Transcription Factor/Zinc Finger
202672_s_at
activating transcription factor 3 *
ATF3
467
1
6.44E-06
235963_at
endothelial PAS domain protein 1
EPAS1
2034
2
0.000868918
230056_at
fetal Alzheimer antigen
FALZ
2186
17
0.000109062
0.000846797
209189_at
v-fos FBJ murine osteosarcoma viral oncogene homolog *
FOS
2353
14
201464_x_at
v-jun sarcoma virus 17 oncogene homolog (avian)
JUN
3725
1
0.00033453
228846_at
MXD1
4084
2
0.000121767
228388_at
MAX dimerization protein 1 *
nuclear factor of kappa light polypeptide gene enhancer in B-cells
inhibitor, beta
NFKBIB
4793
19
0.000924997
1569661_at
neuronal PAS domain protein 3
NPAS3
64067
14
0.000585462
219459_at
POLR3B
55703
12
0.00057423
227891_s_at
polymerase (RNA) III (DNA directed) polypeptide B
TAF15 RNA polymerase II, TATA box binding protein (TBP)-associated
factor, 68kDa *
8148
17
0.000323075
1565913_at
zinc finger CCCH-type, antiviral 1
TAF15
ZC3HAV
1
56829
7
0.000716049
223163_s_at
zinc finger, C3HC-type containing 1
51530
7
0.000111222
226650_at
zinc finger, AN1-type domain 2A
ZC3HC1
ZFAND2
A
90637
7
8.01E-07
218401_s_at
zinc finger protein 281
ZNF281
23528
1
6.24E-05
228392_at
zinc finger protein 302
ZNF302
55900
19
0.000266119
225021_at
zinc finger protein 532
ZNF532
55205
18
0.000853887
Intracellular Signalling
236908_at
acid phosphatase-like 2
ACPL2
92370
3
0.000434466
240953_at
acid phosphatase, prostate
ACPP
55
3
0.000187691
0.000790369
237118_at
acidic (leucine-rich) nuclear phosphoprotein 32 family, member A *
ANP32A
8125
15
204170_s_at
CDC28 protein kinase regulatory subunit 2 *
CKS2
1164
9
1.23E-05
234158_at
EPH receptor B2
EPHB2
2048
1
0.000696997
1560094_at
guanine nucleotide binding protein (G protein), beta 5
GNB5
10681
15
0.000394315
232717_at
kalirin, RhoGEF kinase
KALRN
8997
3
0.000301639
212722_s_at
phosphatidylserine receptor
PTDSR
23210
17
0.000364625
202388_at
regulator of G-protein signalling 2, 24kDa
RGS2
5997
1
3.79E-05
235964_x_at
SAM domain and HD domain 1
SAMHD1
25939
20
0.000726604
241737_x_at
vaccinia related kinase 1
VRK1
7443
14
0.000528063
3337
19
2.89E-05
Protein folding/response to stress
200666_s_at
DnaJ (Hsp40) homolog, subfamily B, member 1 *
209304_x_at
growth arrest and DNA-damage-inducible, beta *
DNAJB1
GADD45
B
4616
19
3.27E-05
200800_s_at
heat shock 70kDa protein 1A
HSPA1A
3303
6
0.000879932
202581_at
heat shock 70kDa protein 1B *
HSPA1B
3304
6
3.84E-06
117_at
heat shock 70kDa protein 6 (HSP70B') *
HSPA6
3310
1
1.44E-05
201841_s_at
heat shock 27kDa protein 1 *
3315
7
0.000134513
3320
14
0.000145585
3329
2
5.43E-06
211969_at
heat shock 90kDa protein 1, alpha *
HSPB1
HSP90A
A1
200807_s_at
heat shock 60kDa protein 1 (chaperonin) *
HSPD1
Supplementary sex-specific transcriptome in human cortex
23
Probe
Name
Symbol
Locus
C
ANOVA p
206976_s_at
heat shock 105kDa/110kDa protein 1 *
HSPH1
10808
13
7.98E-05
210691_s_at
calcyclin binding protein
CACYBP
27101
1
0.000961985
204258_at
chromodomain helicase DNA binding protein 1
1105
5
7.36E-05
210387_at
histone 1, H2bg
CHD1
HIST1H2
BG
8339
6
0.000750647
216175_at
polymerase (DNA directed), delta 2, regulatory subunit 50kDa
POLD2
5425
7
0.000568346
201292_at
topoisomerase (DNA) II alpha 170kDa
TOP2A
7153
17
0.000942269
218658_s_at
ARP8 actin-related protein 8 homolog (yeast) *
ACTR8
93973
3
0.0004138
208862_s_at
catenin (cadherin-associated protein), delta 1
CTNND1
1500
11
0.000992209
37966_at
parvin, beta
29780
22
6.45E-05
203690_at
tubulin, gamma complex associated protein 3 *
PARVB
TUBGCP
3
10426
13
0.000720854
Nucleus/DNA Function
Cytoskeleton
RNA processing
230142_s_at
cold inducible RNA binding protein *
CIRBP
1153
19
0.000688481
203694_s_at
DHX16
8449
6
0.000607668
221768_at
DEAH (Asp-Glu-Ala-His) box polypeptide 16 *
splicing factor proline/glutamine-rich (polypyrimidine tract binding
protein associated)
SFPQ
6421
1
0.000601195
206864_s_at
harakiri, BCL2 interacting protein (contains only BH3 domain)
HRK
8739
12
0.00013468
214057_at
myeloid cell leukemia sequence 1 (BCL2-related)
MCL1
4170
1
0.000380653
Apoptosis
Other
209732_at
C-type lectin domain family 2, member B
CLEC2B
9976
12
0.000804517
214328_s_at
EIF3S3
8667
8
0.000249265
1566079_at
eukaryotic translation initiation factor 3, subunit 3 gamma, 40kDa
ELOVL family member 5, elongation of long chain fatty acids
(FEN1/Elo2, SUR4/Elo3-like, yeast) *
ELOVL5
60481
6
0.000488677
217534_at
family with sequence similarity 49, member B
FAM49B
51571
8
0.000817913
0.000356753
218611_at
immediate early response 5
IER5
51278
1
239910_at
pregnancy specific beta-1-glycoprotein 6
PSG6
5675
19
0.00081279
1557477_at
stromal interaction molecule 1
STIM1
6786
11
0.000415669
1552657_a_at
thioredoxin domain containing 2 (spermatozoa)
TXNDC2
84203
18
0.000262761
Unknown Function
226630_at
chromosome 14 open reading frame 106
C14orf10
6
55320
14
0.000169868
222441_x_at
chromosome 20 open reading frame 45
C20orf45
51012
20
9.79E-05
Supplementary sex-specific transcriptome in human cortex
24
Supplementary Table 5 Taqman gene expression assays used for RT-PCR
Gene
SMCY
NLGN4Y
PCDH11X/Y
ABI assay ID
Hs01104401_g1
Hs01034378_s1
Hs00263173_m1
PCDH11X
HMBS
GUSB
PPIA
UBC
HSPA1A
HSPH1
DNAJB1
HSPD1
HSPB1
HSP90AA1
Hs01673213_m1
Hs00609297_m1
Hs99999908_m1
Hs99999904_m1
Hs00824723_m1
Hs00271229_s1
Hs00971475_m1
Hs00428680_m1
Hs01036746_g1
Hs00356629_g1
Hs00743767_sH
GenBank numbers
D87072.1, U52191.1, AK127269.1, AK095923.1
AB023168.1, AF376804.1, BX537428.1
AF206516.1, AF217288.1, AF332218.1, AF332219.1,
AY861433.1, AB037747.1, AF332217.1
AF332219.1, AY861434.1
NM_000190.3 (RefSeq)
M15182.1, CR593823.1, BC014142.2, AK223406.1, DQ896190.1
NM_021130.3 (RefSeq)
AB009010.1, AK026846.1, NM_021009.4 (RefSeq)
BC009322.2, BC002453.2, NM_005345.4 (RefSeq)
AB003333.1, AB003334.1, NM_006644.2 (RefSeq)
D49547.1, X62421.1, NM_006145.1 (RefSeq)
M34664.1, NM_199440.1 (RefSeq), NM_002156.4 (RefSeq)
X54079.1, AL050380.1, X16477.1, NM_001540.2 (RefSeq)
X15183.1, NM_005348.3 (RefSeq), NM_001017963.2 (RefSeq)
Supplementary sex-specific transcriptome in human cortex
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FIGURE LEGENDS:
Figure 1: A principal component analysis (PCA) was conducted using all genes. The plot
shows the first principal component versus age (log scale). Points are colored by the predefined developmental categories. The predominant expression profile in the study was
genes changing in a linear manner over time (log scale). By the nature of PCA, this
profile includes genes having either positive or negative slopes.
Figure 2: Microarray data showing the levels of gene expression (log scale) for eight
genes on the Y chromosome (SMCY, PCDH11Y, TTTY15, CYorf15B, TMSB4Y, CYorf
15A, EIFIAY, NLGN4Y) that vary significantly according to postnatal age (log scale).
Graphs for PCDH11X and PCDH11Y are labeled the same as their associated probe sets
on the affymetric chip. However, these probes sets may detect both X and Y versions of
the gene. The circles represent males (blue lines) and the triangles represent females (red
line, PCDH11X only). The lines represent the line of best fit based on regression. Points
are colored by the predefined developmental categories. Abbreviation; Reg R2, regression
R-squared.