Advances in Bioscience and Biotechnology, 2013, 4, 75-88 ABB Published Online October 2013 (
Genetic analysis of the human hair roots as a tool for
spaceflight experiments*
Masahiro Terada1#, Masaya Seki2, Akira Higashibata1, Shin Yamada1, Rika Takahashi2,
Hideyuki J. Majima3, Takashi Yamazaki1, Tomomi Watanabe-Asaka1, Maki Niihori1, Chiaki Mukai1,
Noriaki Ishioka1
1Japan Aerospace Exploration Agency, Tsukuba City, Japan
2Advanced Engineering Services Co., Ltd., Tsukuba City, Japan
3Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima City, Japan
Received 5 August 2013; revised 5 September 2013; accepted 5 October 2013
Copyright © 2013 Masahiro Terada et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The use of hair roots as experimental samples has
been a research focus for understanding the effects of
spaceflight on astronauts, because it has many advan-
tages, one of which is the fact that hair matrix cells
actively divide in a hair follicle and sensitively reflect
the physical conditions of the human body. In 2009, a
research program focusing on the analysis of astro-
nauts’ hairs was initiated to examine the effects of
long-term spaceflight on the gene expression and mi-
neral metabolism in the human body. Since the num-
ber of samples per astronaut is limited to 5 strands of
hairs at each sampling point, due to the ethical view-
point of astronauts or limited resources in space, it is
important to develop an effective method for the mo-
lecular analysis of small amounts of hair roots. In this
study, mRNA successfully extracted from 1, 5, and 10
hair follicles was amplified and subjected to the DNA
microarray analysis to compare the gene expression
within subjects. The results indicated that (1) it was
possible to perform the genetic analysis on hair sam-
ples stored at 80˚C, even without a fixation buffer
and (2) the newly modified method of mRNA extrac-
tion and analysis was effective in detecting differen-
tial gene expression in samples containing only 5 hairs.
In conclusion, RNA was efficiently extracted from 5
hair roots, which is the same number of hair roots us-
ed in the space experiment; therefore, this method
can be applied to genetically analyze astronauts’ hair
amples. s
Keywords: Hair Root; Microarray; Space; Astronaut;
RNA; Gene Expression
Examination of the human hair serves as an effective tool
for determining stress levels and metabolic conditions in
the human body in response to the microgravity envi-
ronment and cosmic radiation. In December 2009, the Ja-
pan Aerospace Exploration Agency (JAXA) initiated the
“HAIR” research program to analyze the properties of
and changes in astronauts’ hair during spaceflight [1], the
purpose of which is to elucidate the effects of long-term
exposure to spaceflight on the gene expression and min-
eral metabolism in human hair. In the frame of the
“HAIR” experiment, 10 astronauts from the International
Space Station (ISS) crews will be subjected to hair sam-
pling and analysis. Such an experiment will be the first to
examine the fine clear effect of long-term exposure to
spaceflight on exodermal tissues.
Hair matrix cells actively divide in a hair follicle [2,3]
and are known to sensitively reflect the host’s physical
conditions [4-6]. Akashi et al. [2010] reported that the
circadian phase of clock gene expression in hair follicle
cells corresponds to that of individual behavioral rhy-
thms and therefore is effective for evaluating the proper-
ties of the human peripheral circadian clock. In addition,
the hair shaft has also been shown to record the metabo-
lic changes in the organism in response to changing envi-
ronments [7,8]. For example, high levels of toxic metals,
such as mercury, cadmium, arsenic, and lead, have been
observed in the hair of people exposed to toxic metal
pollution [9]. The hair mineral analysis has also been
widely used for forensic science, the assessment of envi-
*Conflict of interest: The authors declare that there is no conflict o
#Corresponding author.
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88
ronmental exposure [10-13], the evaluation of nutritional
statuses, and disease diagnosis [14,15]. It was previously
reported that 14 days of hindlimb suspension (a simula-
ted microgravity model of skeletal muscle) led to chang-
es in the levels of 26 minerals in rat body hair [1], sup-
porting that hair samples would be an informative tool
for examining the effect of spaceflight on humans, espe-
cially taking into account that no special complex hard-
ware and handling are required for hair collection.
In the frame of the “HAIR” experiment, both hair
roots and hair shafts collected from the ISS crews are
subjected to the analysis. It is known that the expression
of immunoglobulin heavy-chain mRNA in the amphibian
Pleurodeles waltl changes during spaceflight [16]. Space-
flight has also been shown to cause gene expression
changes in rat and mouse skeletal muscles [17-19]. In
addition, studies have suggested that spaceflight affects
the organization of microtubules and mitochondria, there-
by resulting in increased apoptosis [20]. Therefore, along
with the analysis of hair roots, nucleic acids (RNA and
mitochondrial DNA) will be extracted from the collected
hair roots and subjected to the analysis of gene expres-
sion changes during spaceflight. The extracted total RNA
will be analyzed by the DNA microarray technique, and
the effects of spaceflight on the expression levels of stress-
related genes, such as oxidative stress gene networks,
will be further examined. In addition, the multiple effects
of microgravity and cosmic radiation on the copy num-
ber of mitochondrial DNA will also be investigated.
Moreover, immune system-related genes will be ana-
lyzed using a human immunological cDNA chip. Fur-
thermore, to examine trace element metabolism in the
human body, the contents of minerals (e.g., Na, K, and
Ca) and trace elements (e.g., mercury) in the hair shaft of
ISS crews will be analyzed using an electron probe mi-
However, in the “HAIR” experiment, the number of
hair samples is limited to only 5 strands from each as-
tronaut, due to the ethical viewpoint of astronauts or lim-
ited resources in space. Therefore, it is essential to deve-
lop a method to effectively analyze the gene expression
with a limited number of hair roots. To achieve this pur-
pose, in the current study, the microarray analysis was
performed using RNA extracted from 1, 5, or 10 hair
2.1. Hair Sample Preparation
One, 5, and 10 strands of hair were taken several times
from each of 2 healthy voluntary male subjects (age, 33 -
36 years). Individual hairs were grasped as near to the
scalp as possible and pulled out by pulling several times
with tweezers in the direction of hair growth without da-
maging hair roots. Samples were stored at 80˚C until
analysis. Similar biological conditions for material stor-
age will be employed for the HAIR experiment during
spaceflight. This study was approved by the Committee
on Human Care and Use at the JAXA Institutional Re-
view Board. All the participants provided written inform-
ed consent.
2.2. RNA Extraction
Hair roots (approximately 2 - 3 mm) were used as the
sources for mRNA extraction and were cut into about 15
fragments (0.1 - 0.2 mm each) using a microsurgical
knife under a stereoscopic microscope. Collected frag-
ments were immersed in 800 μl of ISOGEN Reagent
(Nippon Gene, Toyama, Japan) in tubes and stirred (15 s
× 2 times) using the sonication device, Bioruptor UCD-
250 (Cosmo Bio, Tokyo, Japan). Next, RNA was purified
from hair lysates with the ISOGEN Kit as described pre-
viously [21]. Briefly, tubes were kept at room tempera-
ture for 5 min, followed by addition of 200 μl of chloro-
form. Subsequent processes of RNA purification were
performed according to the manufacturer’s instructions.
After isolation, RNA pellets were washed with 70% etha-
nol, air dried, and resuspended in 10 μl of RNA-free wa-
ter (Gibco-BRL, Gaithersburg, MD). Total RNA was
quantified at 260 nm using the NanoDrop ND-1000 spec-
trophotometer (NanoDrop Technologies Inc., Wilming-
ton, DE). The RNA quality was determined using the
Agilent Bioanalyzer 2100 (Agilent Technologies, Palo
Alto, CA). The 28S:18S rRNA ratio and the RNA integ-
rity number (RIN) were calculated with the 2100 Expert
software and the RIN Beta Version software (Agilent Te-
chnologies), respectively. RIN was calculated by allow-
ing the classification of total RNA, based on a number-
ing system from 1 (most degraded) to 10 (most intact)
2.3. RNA Amplification
Due to the small amount of RNA extracted from hair
samples, a double RNA amplification step was incorpo-
rated prior to microarray hybridization. Total RNA was
amplified using the Ambion MessageAmp aRNA Kit as
described previously [24]. Briefly, first- and second-
strand cDNA was synthesized. Unlabeled aRNA was ge-
nerated by in vitro transcription with unbiotinylated NTPs.
For probe preparation, aRNA was reverse transcribed
with second-round primers. The second-strand cDNA was
synthesized with the T7 oligo (dT) primer and purified.
Biotin-labeled cRNA was generated by in vitro transcrip-
tion and then purified with the RNeasy Kit (Qiagen, Ven-
lo, The Netherlands).
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M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 77
2.4. Generation and Mining of Microarray Data
Amplified RNA was processed and hybridized to the
Whole Human Genome (8 × 60 K) Oligo Microarray
(Agilent Technologies), according to the manufacturer’s
protocol. Slide scanning was performed using the Agilent
DNA Microarray Scanner (Agilent Technologies) by
DNA Chip Research Inc. (Yokohama, Japan). Expression
profiles were collected in triplicate at each time point,
and scanning data were normalized with Agilent’s Fea-
ture Extraction software (Agilent Technologies). Data
preprocessing and analysis were performed using the
GeneSpring software 11.0.1 (Agilent Technologies). Pre-
processing procedures were performed according to the
manufacturer’s recommendations and the MicroArray
Quality Control project reports [25]. Briefly, a decision
matrix determines whether each transcript is reliably de-
tected (i.e., present), marginally detected (i.e., marginal),
or not detected (i.e., absent) and calculates signal intensi-
ties. Normalization was carried out to the 75th percentile
of each array, and each gene to the median, with Gene
Spring’s normalization option. The hierarchical cluster
analysis was performed using the principal component
analysis (PCA), the rank correlation of log ratios, and the
condition tree clustering option of GeneSpring. The pro-
bability was 0.1 and was adjusted by the false-discovery
rate for corrections of multiple tests. All raw fluorescen-
ce intensity data and microarray image files were depos-
ited within the public repository for microarray-based
gene expression data, the “Gene Expression Omnibus”
(GEO) (, complying
with the minimum information requirement for microbar-
ray experiments. The GEO accession number for the cur-
rent experiment is GSE46809.
3.1. RNA Yield and Quality
Table 1 shows the yield and quality parameters of the ex-
tracted RNA. The average total yield of RNA per hair
root was 317.3 ng/follicle, and the average yields of
RNA from a single hair root each from 2 subjects were
286.7 ng/follicle and 409.3 ng/follicle (Table 1(a)). The
average total yield of RNA from 5 strands of hair roots
was 524.6 ng (128.2 ng/follicle), and the average yields
of RNA from 2 subject were 882.7 ng (176.6 ng/follicle)
and 273.9 ng (54.7 ng/follicle) (Table 1(b)). The average
yield of 10 strands of hair roots was 418.7 ng (41.9 ng/
follicle), and the average yields of RNA from 2 subjects
were 507.4 ng (50.7 ng/follicle) and 285.6 ng (28.6 ng/
follicle) (Table 1(c)). For the information, the average
total yield of RNA from 3 strands of hair roots was 623.5
ng (207.8 ng/follicle), and the average yields of RNA
from a single hair root each from 2 subjects were 608.2
ng (202.7 ng/follicle) and 688.7 ng (229.6 ng/follicle)
(data not shown).
The sample quality was determined using the Agilent
Bioanalyzer 2100 by calculating the RNA integrity num-
ber (RIN). However, RIN is calculated based on the bio-
analyzer traces typically produced by hair follicle RNAs;
therefore, when a sample had a lower 28S rRNA peak
but no degradation peaks (Figure 1), the bioanalyzer
could not consider the sample as a normal total RNA
electropherogram trace. In consequence, RIN for most
hair follicle RNA samples were not able to be calculated
using default parameters (Table 1). Therefore, in addi-
tion to RIN, 28S and 18S clear peaks were also used for
determining the RNA quality.
Based on RIN or 28S/18S ratios (2 detected peaks,
Figure 1), 14 RNA samples in total were chosen for pre-
amplification for microarray hybridization (6, 7, and 1
samples from 1, 5, and 10 follicles, respectively) (Tables
1 and 2). Among these 14 samples, 7 did not yield RINs,
whereas others had RINs ranging from 6.1 to 7.8 (Table
1). Table 2 shows the enrichment of RNA from these
samples following 2 rounds of pre-amplification prior to
the microarray analysis. After the first pre-amplification
performed on 100 ng of extracted RNA, the average
amount of RNA was 2.56 μg (25.6 ng/μl × 100 μl), which
was 25.6 fold of the starting material. The average amount
of RNA after second amplification was 156.6 μg (1556
ng/μl × 100 μl), which was 78.3 fold of the amount after
first amplification. Of these 14 pre-amplified samples, 13
(1 μg each) were selected for DNA microarray analysis
(Table 2).
3.2. Gene Expression Affinity Analysis
The RNA data from a single hair root were compared to
those from 5 or 10 pieces of hair roots. Unlike the
Figure 1. Representative electropherograms produced by the
Agilent Bioanalyzer. (a) An electropherogram with RNA peaks
that can be used to calculate RIN; (b) An electropherogram
with RNA peaks not suitable for RIN calculation.
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Table 1. Yield and quality of RNA samples. N.D., not detected; subjected to amplification or microarray analysis.
Number of hair strands Subject Total RNA yield (ng)Mean yield (ng/follicle) RIN Amplification DNA microarray
2126.2 2126.2 1.5
846.2 846.2 N.D.
588.6 588.6 N.D.
37.1 37.1 N.D.
65.5 65.5 N.D.
67 67 N.D.
61.2 61.2 N.D.
80 80 6
73.7 73.7 N.D.
69.2 69.2 N.D.
711.7 711.7 N.D.
91.5 91.5 N.D.
175.8 175.8 N.D.
630.5 630.5 7.8
556.9 556.9 7
197.3 197.3 N.D.
270.2 270.2 N.D.
302.1 302.1 7.7
460.2 460.2 N.D.
185 185 6.1
94.2 94.2 N.D.
365.9 365.9 6.2
93.8 93.8 N.D.
137.3 137.3 N.D.
79.4 79.4 N.D.
67 67 N.D.
122.9 122.9 N.D.
111.7 111.7 N.D.
228.8 228.8 N.D.
270.5 270.5 N.D.
124.6 124.6 N.D.
130.6 130.6 N.D.
37.5 37.5 N.D.
277.9 277.9 N.D.
338.4 338.4 N.D.
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 79
846 846 N.D.
2110.2 2110.2 6.4
54.9 54.9 N.D.
58.1 58.1 N.D.
172.5 172.5 N.D.
57.3 57.3 N.D.
69.6 69.6 N.D.
459.2 459.2 N.D.
58.2 58.2 N.D.
Average 317.3272727 317.3272727
S.D. 454.2560974 454.2560974
S.E. 69.27340542 69.27340542
Average for subject A 286.669697 286.669697
Average for subject B 409.3 409.3
Number of hair strands Subject Total RNA yield (ng)Mean yield (ng/follicle) RIN Amplification DNA microarray
898.8 179.8 6.8
727.8 145.6 6.7
1521.5 304.3 7.1
1836.8 367.4 6.6
304.8 61 7.5
353.6 70.7 3.1
535.5 107.1 7.8
363.8 72.8 N.D.
513.5 102.7 6.1
270.9 54.2 N.D.
230.3 46.1 N.D.
131.2 26.2 N.D.
156.4 31.3 N.D.
163.5 32.7 N.D.
459.2 91.4 N.D.
204.7 40.9 N.D.
245.7 49.1 N.D.
Average 524.5882 128.1583333
S.D. 484.5583 106.9410497
S.E. 121.1396 32.24393968
Average for subject A 882.6857 176.5571429
Average for subject B 273.92 54.74
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Number of hair strands Subject Total RNA yield (ng) Mean yield (ng/follicle)RIN Amplification DNA microarray
613.1 61.3 1.6
260.4 26 N.D. A
648.7 64.9 N.D.
180.4 18 N.D.
390.8 39.1 1
Average 418.68 41.86
S.D. 208.15592 20.839938
S.E. 104.07796 10.419969
Average for subject A 507.4 50.733333
Average for subject B 285.6 28.55
Table 2. RNA yield after amplification.
Amplification (ng/μl)
Number of
hair strands Subject Extracted concentration
(ng/μl) (× 10)
Mean yield
(ng/follicle) 1st (× 100) 2nd (× 100)
DNA microarray
63.05 630.5 67.93 1933.1
55.69 556.9 113.98 1895.43
27.02 270.2 10.15 1879.84
30.21 302.1 5.55 1562.34
1 A
18.5 185 4.87 1043.56
3.048 6.096 25.03 1787.98
5.355 10.71 15.97 1354.34
15.215 30.43 19.71 1350.56
5 A
18.368 18.368 16.26 1597.09
10 A 64.87 648.7 15.83 1676.85
1 B 4.592 45.92 12.66 1118.27
3.638 7.276 17.64 1805.3
5.135 10.27 12.42 1589.98 5 B
2.709 5.418 20.27 1330.05
Average 25.5907143 1566.0493
S.D. 29.6345159 288.55833
S.E. 8.21913588 80.031682
amount of RNA initially extracted from these hair roots,
the amount of amplified RNA was sufficient for mi-
croarray analyses. To analyze the sample-specific pat-
terns in gene expression profiles, the PCA analysis, the
rank correlation of log ratios, and hierarchical clusters
analysis were applied. PCA was used to demonstrate the
homogeneity level of the transcriptional profiles of ana-
lyzed samples. In a PCA plot, samples with similar ex-
pression profiles are positioned in the proximity to each
other [26,27]. The position of each sample was plotted
against the X-, Y-, and Z-axes in a three-dimensional (3D)
space (Figure 2), in which the closer distance of the
samples to each other in 3D; therefore, the homology
between samples is high. As shown in Figure 2, the ex-
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 81
Figure 2. Three-dimensional images of principal component analysis (PCA). The closer the distance between samples, the higher the
homology is between them.
pression data from RNA samples extracted from 5 folli-
cles, but not a single follicle, were found to have higher
levels of homogeneity. On the other hand, large variabil-
ity was observed among the samples derived from 1 fol-
The variability among samples was also evaluated us-
ing the rank correlation of log ratios. As shown in Figure
3, spots colored in red represent discrepancy in the sam-
ples; in other words, the variability among samples was
relatively low. These results also suggest that the smaller
the number of follicles from which RNA is extracted, the
larger the variability is among samples. Notably, sample-
specific differences were still present even when RNA
was extracted from the same number of follicles (Figure
To evaluate the homogeneity among multiple genes in
all samples, the hierarchical analysis was performed us-
ing condition tree clustering (Figure 4). The results indi-
cate clear resolution between the subjects, as well as large
differences between samples originating from a single
follicle. As for the samples derived from 5 follicles, the
level of variability was low, and therefore, the gene
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M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88
Figure 3. Correlation plot as a comparison of rank concordance.
The more red between each sample, homology between sam-
ples is high. Darker shades depict lower rank correlations.
Figure 4. Hierarchical cluster analysis by condition tree clu-
stering. The characteristics of individual subjects were separa-
expression data were considered to be reproducible and
significant (Figure 4). On the other hand, the samples
derived from 1 follicle showed large variability, so the
sample of subject A was separated as the group of subject
3.3. Certification of Hair Gene Expressions
To confirm the integrity of RNA extracted from the hair,
the expression levels of hair-specific genes in these sam-
ples were analyzed. Hair root-specific genes were chosen
by referencing reports by Ohyama et al. [2006] and Klo-
epper et al. [2008]. In the sub-bulge region of hair roots,
22 out of 24 reported genes were expressed in the sam-
ples (Table 3(a)). As for the hair bulge region, the ex-
pression of 16 out of 17 genes was confirmed (Table
3(b)). In addition, the expression of 18 out of 22 genes
related to immunophenotyping of the human bulge re-
gion was also detected (Table 3(c)).
Several groups have extracted RNA from rodent and hu-
man hair follicles [24,28-34]. In most cases, the hair
samples were stored in dissolution buffers, such as RNA
later [24] or RN easy [28], prior to the analysis. However,
for the HAIR experiment, the hair samples from astro-
nauts must be stored without buffers at 80˚C, due to the
limited resource in space. Therefore, the same storage
method was employed in this study. The quality of RNA
extracted from the samples stored at 80˚C was first in-
vestigated, followed by examination of whether the ex-
tracted RNA was of sufficient quality and quantity for
subsequent DNA microarray analysis.
In this study, different RNA samples extracted from 1,
5, and 10 strands of hair follicles using ISOGEN Reagent
were compared. Extracted RNA was then amplified prior
to the DNA microarray analysis. As shown in Table 1,
some amount of RNA could be extracted even from 1
hair follicle. Notably, the yields were somewhat variable,
and the amount of extracted RNA was not dependent on
the number of hair follicles. While the reason for these
results is unclear, it is likely that the device (NanoDrop
ND-1000 spectrophotometer) was unable to correctly de-
tect the amounts of RNA that were near to or less than its
limit of detection. On the other hand, the electrophero-
grams of these samples indicated intactness and good
quality (Figure 1). Studies have shown that less than 5
ng of total RNA could be amplified and used for micro-
array hybridization [24,35,36]. With the incorporation of
a pre-amplification process, the RNA samples were am-
plified effectively to provide sufficient materials for mi-
croarray hybridization (Table 2).
In the current study, the RNA yields from the hair
samples were >18 ng per hair follicle, which is similar to
the results reported by some researchers [24,37]. Al-
though the amount of extracted RNA was insufficient for
direct microarray analysis, the RNA amplification proce-
dure allowed us to perform the microarray profiling,
even on the samples that had only small amounts of RNA
(Tables 1 and 2) [24,38-41]. In addition, the quality of
RNA is important for judging whether the samples could
be applied to the microarray analysis. In this study, the
quality of RNA was evaluated on the basis of RIN (Table
1). RNA, although thermodynamically stable, is rapidly
degraded by ubiquitous RNase enzymes [23]; as a result,
short fragments of degraded RNA appear in the samples
42,43]. Using agarose gel electrophoresis, 2 RNA bands [
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Table 3. List of hair root-related genes. Genes shown in dark columns were not detected in the samples. a) Sub-bulge; b) Bulge; c)
Immunophenotype of the human bulge region.
Gene symbol Description
SDC2 Homo sapiens syndecan 2 (SDC2), mRNA [NM_002998]
ANGPTL7 H. sapiens angiopoietin-like 7 (ANGPTL7), mRNA [NM_021146]
SLC1A4 H. sapiens solute carrier family 1 (glutamate/neutral amino acid transporter), member 4 (SLC1A4),
transcript variant 1, mRNA [NM_003038]
TYMS H. sapiens thymidylate synthetase (TYMS), mRNA [NM_001071]
CDK1 H. sapiens cyclin-dependent kinase 1 (CDK1), transcript variant 1, mRNA [NM_001786]
TOP2A H. sapiens topoisomerase (DNA) II alpha 170kDa (TOP2A), mRNA [NM_001067]
VAV3 H. sapiens vav 3 guanine nucleotide exchange factor (VAV3), transcript variant 1, mRNA [NM_006113]
GPC4 H. sapiens glypican 4 (GPC4), mRNA [NM_001448]
MCAM H. sapiens melanoma cell adhesion molecule (MCAM), mRNA [NM_006500]
SLC4A7 H. sapiens solute carrier family 4, sodium bicarbonate cotransporter, member 7 (SLC4A7), mRNA [NM_003615]
FEN1 H. sapiens flap structure-specific endonuclease 1 (FEN1), mRNA [NM_004111]
TIMP3 H. sapiens TIMP metallopeptidase inhibitor 3 (TIMP3), mRNA [NM_000362]
LAMB1 Laminin, beta 1 [Source: HGNC symbol; Acc:6486] [ENST00000393559]
FGF18 H. sapiens fibroblast growth factor 18 (FGF18), mRNA [NM_003862]
COMP H. sapiens cartilage oligomeric matrix protein (COMP), mRNA [NM_000095]
PDGFC H. sapiens platelet derived growth factor C (PDGFC), transcript variant 1, mRNA [NM_016205]
LAMB1 H. sapiens laminin, beta 1, mRNA (cDNA clone IMAGE: 4889995) containing frame-shift errors [BC044633]
KPNA2 H. sapiens karyopherin alpha 2 (RAG cohort 1, importin alpha 1) (KPNA2), mRNA [NM_002266]
PRC1 H. sapiens protein regulator of cytokinesis 1 (PRC1), transcript variant 1, mRNA [NM_003981]
LAMB1 H. sapiens laminin, beta 1 (LAMB1), mRNA [NM_002291]
COL11A1 H. sapiens collagen, type XI, alpha 1 (COL11A1), transcript variant B, mRNA [NM_080629]
SLC7A1 H. sapiens solute carrier family 7 (cationic amino acid transporter, y+ system), member 1 (SLC7A1), mRNA [NM_003045]
PCDH8 H. sapiens protocadherin 8 (PCDH8), transcript variant 1, mRNA [NM_002590]
RRM2 H. sapiens ribonucleotide reductase M2 (RRM2), transcript variant 2, mRNA [NM_001034]
Gene symbol Description
DIO2 H. sapiens deiodinase, iodothyronine, type II (DIO2), transcript variant 1, mRNA [NM_013989]
DPYSL2 H. sapiens dihydropyrimidinase-like 2 (DPYSL2), transcript variant 2, mRNA [NM_001386]
FST H. sapiens follistatin (FST), transcript variant FST344, mRNA [NM_013409]
FZD1 H. sapiens frizzled family receptor 1 (FZD1), mRNA [NM_003505]
DCT H. sapiens dopachrome tautomerase (dopachrome delta-isomerase, tyrosine-related protein 2) (DCT),
transcript variant 1, mRNA [NM_001922]
DPYSL3 H. sapiens dihydropyrimidinase-like 3 (DPYSL3), transcript variant 2, mRNA [NM_001387]
DCN H. sapiens decorin (DCN), transcript variant A1, mRNA [NM_001920]
SERPINF1 H. sapiens serpin peptidase inhibitor, clade F (alpha-2 antiplasmin, pigment epithelium derived factor),
member 1 (SERPINF1), mRNA [NM_002615]
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88
WIF1 H. sapiens WNT inhibitory factor 1 (WIF1), mRNA [NM_007191]
KRT15 H. sapiens keratin 15 (KRT15), mRNA [NM_002275]
PHLDA1 H. sapiens pleckstrin homology-like domain, family A, member 1 (PHLDA1), mRNA [NM_007350]
DKK3 H. sapiens dickkopf homolog 3 (Xenopus laevis) (DKK3), transcript variant 1, mRNA [NM_015881]
PHLDA1 Pleckstrin homology-like domain, family A, member 1 [Source: HGNC symbol; Acc:8933] [ENST00000266671]
TGFB2 H. sapiens transforming growth factor, beta 2 (TGFB2), transcript variant 2, mRNA [NM_003238]
DKK3 H. sapiens dickkopf homolog 3 (X. laevis) (DKK3), transcript variant 1, mRNA [NM_015881]
ANGPTL2 H. sapiens angiopoietin-like 2 (ANGPTL2), mRNA [NM_012098]
DIO2 H. sapiens deiodinase, iodothyronine, type II (DIO2), transcript variant 4, mRNA [NM_001242502]
Gene symbol Description
TNC H. sapiens tenascin C (TNC), mRNA [NM_002160]
GJA1 H. sapiens gap junction protein, alpha 1, 43kDa (GJA1), mRNA [NM_000165]
FBN1 H. sapiens fibrillin 1 (FBN1), mRNA [NM_000138]
NES H. sapiens nestin (NES), mRNA [NM_006617]
CD200 H. sapiens CD200 molecule (CD200), transcript variant 2, mRNA [NM_001004196]
ITGB1 H. sapiens integrin, beta 1 (fibronectin receptor, beta polypeptide, antigen CD29 includes MDF2, MSK12) (ITGB1),
transcript variant 1E, mRNA [NM_133376]
NID2 Nidogen 2 (osteonidogen) [Source: HGNC symbol; Acc:13389] [ENST00000395707]
FN1 H. sapiens fibronectin 1 (FN1), transcript variant 7, mRNA [NM_054034]
ITGA6 H. sapiens integrin, alpha 6 (ITGA6), transcript variant 2, mRNA [NM_000210]
CD34 H. sapiens CD34 molecule (CD34), transcript variant 1, mRNA [NM_001025109]
LHX2 H. sapiens LIM homeobox 2 (LHX2), mRNA [NM_004789]
NID1 H. sapiens nidogen 1 (NID1), mRNA [NM_002508]
FBN2 H. sapiens fibrillin 2 (FBN2), mRNA [NM_001999]
LTBP1 H. sapiens latent transforming growth factor beta binding protein 1 (LTBP1), transcript variant 1, mRNA [NM_206943]
NES H. sapiens nestin (NES), mRNA [NM_006617]
ITGA6 H. sapiens integrin, alpha 6 (ITGA6), transcript variant 2, mRNA [NM_000210]
LTBP1 H. sapiens latent transforming growth factor beta binding protein 1 (LTBP1), transcript variant 1, mRNA [NM_206943]
FBN3 H. sapiens fibrillin 3 (FBN3), mRNA [NM_032447]
KRT15 H. sapiens keratin 15 (KRT15), mRNA [NM_002275]
CD200 H. sapiens CD200 molecule (CD200), transcript variant 2, mRNA [NM_001004196]
NID2 H. sapiens nidogen 2 (osteonidogen) (NID2), mRNA [NM_007361]
CD34 H. sapiens CD34 molecule (CD34), transcript variant 2, mRNA [NM_001773]
comprising 28S and 18S ribosomal RNA can be readily
visualized in gel images. RNA is considered of high
quality when the ratio of 28S: 18S bands are more than 2.
The RIN numbers are calculated by allowing the classi-
fication of total RNA, based on a numbering system
from 1 (the most degraded) to 10 (the most intact) [22,
23]. Generally, RNA sample with a RIN number of more
than 7 are considered suitable for genetic analyses [43].
Interestingly, some researchers reported that with care,
meaningful microarray data could be obtained from RNA
Copyright © 2013 SciRes. OPEN ACCESS
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88 85
samples of impaired quality [44], whereas others sugges-
ted that degradation does not preclude the microarray
analysis if comparison is done between samples with
comparable RNA integrity [42]. In this study, Agilent
Bioanalyzer 2100 was used to determine the sample
quality by calculating RIN, based on the Bioanalyzer
traces typically yielded by hair follicle RNAs. Therefore,
when a sample had a lower 28S rRNA peak but no deg-
radation peaks (Figure 1), the system could not consider
the sample as a normal total RNA electropherogram trace.
Another issue was the existence of a 5S rRNA or tRNA
peak in the Bioanalyzer electropherogram (Figure 1),
which may affect the calculation of RIN when these
peaks are larger than that of 18S or 28S ribosomal RNA
[23]. In this study, RNA was extracted using ISOGEN
Reagent, which could not remove 5S rRNA or tRNA due
to the lack of column elution steps. As a result, RIN was
unable to be calculated for most hair follicle RNA sam-
ples using default parameters (Table 1).
Based on RIN or 28S/18S ratios, a total of 14 RNA
samples (6, 7, and 1 samples from 1, 5, and 10 follicles,
respectively) were chosen for pre-amplification of micro-
array hybridization (Tables 1 and 2). Notably, 19,361
genes were expressed in more than 1 sample from among
all samples. In total, 10,593 genes were expressed in all
samples. By referencing publically available data set from
previous microarray analyses [27,45,46], the differences
depending on the number of hair follicles were compared
by the clustering analysis of the microarray data. Using
the PCA analysis, similarities and differences that were
dependent on the number of hair follicles were also ob-
served (Figure 2). In the PCA plot, 4 spots from 1 folli-
cle of 1 subject were scattered, whereas some spots from
5 follicles of 2 subjects were located closely for respec-
tive individuals. These phenomena suggest that the ho-
mogeneity of gene expression is largely dependent on the
number of cells from which RNA is extracted. That is, as
the number of hair follicles is increased, the homology
and uniformity are increased. The variability among sam-
ples was also evaluated using the rank correlation of log
ratios. As shown in Figure 3, the color between the sam-
ples from 5 hair follicles became redder than that be-
tween the samples from 1 hair follicle. In agreement with
the PCA results, the rank correlation of log ratios analy-
sis suggests that the homogeneity is increased, as the
number of hair follicles is increased. These results seem
to be reasonable, because the hereditary properties of in-
dividual hair follicles would disappear when being aver-
aged by the increasing number of hair cells. This finding
is advantageous for the HAIR experiment on astronauts,
since the goal of the experiment is to detect gene expres-
sion changes in the body during spaceflight, but not the
single hair-specific patterns. The hierarchical cluster ana-
lysis was also performed by applying condition tree clu-
stering (Figure 4), through which the mRNA expression
profiles of the 2 subjects could be distinguished. This re-
sult will be informative for successful implementation of
the HAIR experiment, because the focus of the study is
on the individual data, rather than the average data, from
the subjects. Human hair analysis will be further devel-
oped along the same lines as a method to evaluate the
health conditions of astronauts because it allows the ex-
amination of astronaut-specific patterns in space. Using
the hierarchical cluster analysis, Kim et al. [2006] pre-
viously reported no difference in the gene expression in
hair roots between males and females. Interestingly, 2
subjects in this study were males, and their individual
characteristics could be separated (Figure 4). While Kim
et al. obtained their samples at the same time from many
subjects, the samples in this study were collected at va-
rious times from 2 subjects. This margin may reflect the
differences between their results and ours.
Next, to confirm the integrity of mRNA in the samples,
the expression of hair follicle-specific genes was analyz-
ed (Table 3). For hair sub-bulge-related genes, the ex-
pression of 22 out of 24 reported genes was detected
(Table 3(a)). Out of 17 genes of hair bulge, the expres-
sion of 16 genes was confirmed (Table 3(b)). In addition,
18 out of 22 genes related to human epithelial hair folli-
cle stem cells and bulge niche markers were found to be
expressed (Table 3(c)). Together, these results suggest
that hair root-related genes were expressed in the sam-
ples tested in this study. Therefore, it is desirable that the
genes of other organs except hair roots are included in
our samples, and there is not any problem. In this time,
because we can confirm at least the existence of genes
related with hair roots in our samples, there are no me-
thodologically problems. Nevertheless, the newly devel-
oped methods are appropriate for analyzing biological
samples derived from astronauts in the HAIR experi-
It is worth noting that the gene expression in the skin
has been shown to be different between subjects who had
hyperkeratotic skin lesions and those who did not [47].
In addition, Yin et al. also suggested that DNA damage
was induced in the mouse skin upon exposure to ultra-
violet radiation [48]. These results suggested that the
skin, which contains hair follicles, receive the effects on
gene condition by physiological changes or extraordinary
environments. Although these studies were not perform-
ed on human hair follicles, it is indeed possible to inves-
tigate the effects of various space environments (i.e., mi-
crogravity, space radiation, physiological changes, or men-
tal conditions) on astronauts by analyzing the gene ex-
pression in their hair follicles.
Taken together, these results suggest the following points.
First, it is possible to perform a robust gene expression
Copyright © 2013 SciRes. OPEN ACCESS
M. Terada et al. / Advances in Bioscience and Biotechnology 4 (2013) 75-88
analysis on hair samples stored at 80˚C, even without a
fixation buffer. Second, the newly modified method of
mRNA extraction and analysis is effective in detecting
differential genes expression in samples containing only
5 hairs.
The hair samples provided useful physiological infor-
mation for examining the effect of spaceflight. A novel
method was developed to extract and amplify RNA from
5 hair roots, which is the same number of hair roots used
in the space experiment; therefore, the method can be ap-
plied for genetic analysis of astronauts’ hair samples.
Currently, sufficient samples are being gathered from as-
tronauts. The analysis of hair roots from the ISS crews
will support the development of a simple and effective
diagnostic measure for metabolic changes and help eva-
luate astronauts’ health conditions in response to long-
term spaceflight.
This study was supported in part by the JAXA-ISS Space Medicine
Program Grant from the Japan Aerospace Exploration Agency and a
Grant-in-Aid for Young Scientists (B-21800096, M.T.) from the Japan
Society for the Promotion of Science.
We thank Tohko Hashizume for the useful comments on and support
for our study. We would also like to express our appreciation to Dr. Hi-
roshi Ohshima and Dr. Toshiko Ohta for their constructive advice and
supervision of this manuscript.
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JAXA: Japan Aerospace Exploration Agency
ISS: International Space Station
PCA: Principal Component Analysis
GEO: Gene Expression Omnibus
RIN: RNA Integrity Number