Transcriptional profiling of liver tissues in chicken embryo at day 16 and 20 using RNA sequencing reveals differential antioxidant enzyme activity
Transcriptional profiling of liver tissues in chicken embryo at day 16 and 20 using RNA sequencing reveals differential antioxidant enzyme activity
Shaohua Yang 1 2 3
Lu Lu Wang 1 2 3
Zhaoyuan Shi 1 2 3
Xiaoqian Ou 1 2 3
Wei Wang 0 1 3
Xue Chen 1 2 3
Guoqing Liu 1 2 3
0 Agricultural Products Quality and Safety Supervision and Management Bureau , Xuancheng, Anhui , P. R. China
1 Fundamental Research Funds for Industry- University-Research in Hefei University of Technology (XC2016JZBZ03), the Fundamental Research Funds for the Central Universities
2 College of Food Science and Engineering, Hefei University of Technology , Hefei, Anhui , P. R. China
3 Editor: Salah A. Sheweita, Alexandria University , EGYPT
Considering the high proportion of polyunsaturated fatty acids, the antioxidant defense of chick embryo tissues is vital during the oxidative stress experienced at hatching. In order to better understand the mechanisms of the defense system during chicken embryo development, we detected the activity of antioxidant enzymes during the incubation of chicken embryo. Results showed that the activity of superoxide dismutase (SOD) and (GSH-PX) in livers were higher than those in hearts. Based on these results, liver tissues were used as the follow-up study materials, which were obtained from chicken embryo at day 16 and day 20. Thus, we used RNA sequencing (RNA-Seq) analysis to identify the transcriptome from 6 liver tissues. In total, we obtained 45,552,777±45,462,856 uniquely mapped reads and 18,837 mRNA transcripts, across the 6 liver samples. Among these, 1,154 differentially expressed genes (p<0.05, foldchange 1) were identified between the high and low groups, and 1,069 GO terms were significantly enriched (p<0.05). Of these, 10 GO terms were related to active oxygen defense and antioxidant enzyme activity. GO enrichment and KEGG pathway analysis indicated that GSTA2, GSTA4, MGST1, GPX3, and HAO2 participated in glutathione metabolism, and were considered as the most promising candidate genes affecting the antioxidant enzyme activity of chicken embryo at day 16 and day 20. Using RNA-Seq and differential gene expression, our study here investigated the complexity of the liver transcriptome in chick embryos and analyzed the key genes associated with the antioxidant enzyme.
Oxidative stress is always common in poultry production. During embryo growth, more
oxygen is required to provide energy. However, elevated oxygen concentrations lead to high levels
of reactive oxygen species (ROS) [
], which may which may cause protein and lipid oxidation
]. Therefore, ROS has been proposed to cause many diseases and pathological changes
(JZ2017HGTA0228), the innovation Project for
College Students (2017CXCYS235), Wanjiang
Institute of Poultry Technology (XC2015AKKG002),
and the Science and Technology Bureau of AnHui
during chick embryo development [
], especially in the cardiovascular system. Wells showed
that excess ROS could have a teratogenic effect on developing embryos[
] as well as induce
neural tube defects[
]. Meanwhile, it was found that ROS can also cause myocardial
hypertrophy in the developing chick embryo [
]. The damaging effects of ROS can be exerted on the
developing embryos in a directly or indirect style. Thus, antioxidant defences play a very
important role in chick embryonic development.
In fact, the integrated antioxidant systems within the egg and embryonic tissues are crucial
for the protection of chick embryo in its development. Of these, the main antioxidant enzymes,
superoxide dismutases (SOD), glutathione peroxidase (GSH-PX), glutathione S transferases
(GSTs), Peroxidase (POD) and catalase(CAT), can clearly serve as a major defense line against
ROS during the oxidative stress experienced at hatching in chick embryo[
]. During the
incubation period, SOD converts highly reactive superoxide anions into H2O2 and O2, Catalase
(CAT) catalyzes the dismutation of H2O2 to form the neutral products O2 and H2O, and
GSH-PX catalyzes the reductive destruction of hydrogen and lipid hydroperoxides with
glutathione as an electron donor [
]. Meanwhile, the end product of SOD is decomposed then to
scavenge ROS [
]. Additionally, GSH-PX degrades hydrogen peroxide and other peroxides.
The activities of these antioxidant enzymes are close relevant to higher levels of
environmental oxygen. Using the chick embryo, van Golde et al[
] investigated the relations between
hyperoxia and antioxidant enzyme activity, and found that SOD activity had a 2- to
10-foldincrease and Catalase and GPx enzyme activities remain almost the same in heart, liver, intestine
and lungs during incubation at different time points. Starrs et al [
] examined the activities of
catalase, SOD and GPx in the developing lungs of the chicken and showed that SOD activity
decreased, whereas catalase and GPx activities were significantly increased in late incubation.
Nevertheless, Dhage et al [
] revealed there was a significant increase of the SOD activity in
the chick embryo from Day 4±11 (units/mg protein), respectively. Considering these
inconsistent results, we still do not know the mechanism of genes that regulate antioxidant activity
(SOD, CAT, and GSH-PX) during embryo development. Therefore, clarification of the
differential gene expression underlying antioxidant enzyme activity in embryo development will
have both biological and economic significance.
As a research method, RNA-Seq provides a comprehensive and accurate tool for gene
expression pattern analysis [
]. Among these, RNA-Seq results show gene structure, gene
biological function, and new transcripts[14±15]. There have been several studies on various types
of transcriptomes using RNA-Seq techniques, such as on fish [16±17], mice[
]. However, no studies on the chicken embryo transcriptome by RNA-Seq have been
published. Thus, for a better understanding of the adaptive mechanism of antioxidant enzyme
activity during the oxidative stress experienced at hatching in embryos, we examined liver
transcriptome data from different incubation days in order to determine the key genes that
were associated with antioxidant enzyme activity.
Materials and methods
All procedures for animal handling were reviewed and approved by the Institutional Animal
Care and Use Committee (IACUC) of Hefei University of Technology (Permit Number:
Fertilized eggs were purchased from a hatchery (Changlv Native Products, Nanjing, China),
and were incubated at 37.8ÊC and 60% relative humidity in an incubator (Photoshop Solar
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Energy Co., Zibo, China). Fertilized eggs were studied at day 14, 15, 16, 17, 18, 19, and 20 of
incubation. SOD, GSH-PX, Peroxidase (POD) and total protein quantitative assay kits were
provided by Jiancheng Bioengineering Institute (Nanjing, Jiangsu, China).
Preparation of tissues
Fertilized eggs at day 14, 15, 16, 17, 18, 19, and 20 of incubation were obtained, peeled, and the
heart and liver tissues were removed, respectively. The removed tissues were rinsed with cold
saline (0.86%) to remove the blood, immediately frozen in liquid nitrogen, and placed in a
centrifuge stored in an ultra-low temperature freezer.
Determination of activity of antioxidant enzymes
The collected tissue samples were weighed and made into a 20% tissue homogenate by adding
the appropriate amount of saline (0.86%), according to the weight of the volume, then
centrifuged at 4,000 rpm/min for 10 min at 4ÊC. The supernatant was obtained for further analysis.
The activities of SOD, POD and GSH-PX were measured using commercial assay kits
purchased from Nanjing Jiancheng Bioengineering Institute (Nanjing, Jiangsu, China). The
antioxidant experiment was conducted in triplicate, and results were analyzed using SPSS 16.0
software (SPSS, Inc, Chicago, IL, USA). Comparison between groups was analyzed by
Oneway analysis of variance (ANOVA) followed by Duncan's multiple range tests and the results
were considered statistically significant at P < 0.05.
RNA isolation and quality assessment
Liver tissues at day16 and day 20 were chosen for transcriptome study. The total RNA was
extracted from the embryo tissues using the Trizol method (Invitrogen, Carlsbad, CA)
according to the manufacturer's instructions. RNA degradation and contamination was monitored
on 1% agarose gels. Furthermore, the Nanophotometer (IMPLEN, CA, USA) was used to
check RNA purity, and RNA concentration was measured using Qubit RNA Assay Kit in
Qubit 2.0 Fluorometer (Life Technologies, CA, USA). The RNA integrity was assessed with the
RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA, USA).
Library construction and RNA sequencing
A total amount of 3 μg RNA per sample was used as input material for the RNA sample
preparations. Sequencing libraries were processed using NEBNext1 Ultra™ RNA Library Prep Kit
for Illumina1 (NEB, USA), following the manufacturer's recommendations. Cluster
generation of the index-coded samples was conducted on a cBot Cluster Generation System using
Tru Seq PE Cluster Kit v3-c Bot-HS (Illumia) according to the manufacturer's instructions.
After cluster generation, the library preparations were sequenced on an Illumina Hiseq
platform, and 125-bp/150-bp paired-end reads were generated.
Raw data (raw reads) of Fastq format were first processed through in-house perl scripts. In this
step, clean data (clean reads) were acquired by removing reads containing adapter, reads
containing ploy-N, and low quality reads from raw data. At the same time, Q20 (the proportion of
bases with a phredbase quality score greater than 20; i.e., the proportion of read bases whose
error rate is less than 1%), Q30 (the proportion of bases with a phredbase quality score greater
than 30; i.e., the proportion of read bases whose error rate is less than 1%), and GC content of
the clean data were calculated. All the downstream analyses were based on the clean data.
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Reference genome and gene model annotation files were downloaded from a genome website
directly (ftp://ftp.ensembl.org/pub/release-83/gtf/gallus_gallus/). Index of the reference
genome was established using Bowtie v2.2.3. Because TopHat can generate a database of splice
junctions based on the gene model annotation file (which possesses better mapping results
than other non-splice mapping tools), paired-end clean reads were aligned to the reference
genome using TopHat v2.0.12.
Quantification of gene expression level
The number of reads mapped to each gene was calculated by HTSeq v0.6.1. FPKM, expected
number of Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced, is
currently the most commonly used method for estimating gene expression levels. FPKM of
each gene was calculated based on the length of the gene and reads count mapped to this gene.
Differential expression analysis
Differential expression analysis was conducted using the DESeq R package (1.18.0). DESeq
facilitates accurate comparisons between antioxidant enzyme activity of liver tissues by
normalizing the number of reads, and provides statistical routines for determining differential
expression in digital gene expression date using a model based on the negative binomial
distribution. The resulting P-values were adjusted using the Benjamini and Hochberg's approach
for controlling the false discovery rate. Genes with an adjusted P-value <0.05 and log2 (Fold
change) 1 found by DESeq were assigned as differentially expressed.
GO and KEGG enrichment analysis of differentially expressed genes
Gene Ontology (GO) enrichment analysis of differentially expressed genes was performed by
the GOseq R package, in which gene length bias was corrected. GO terms with P< 0.05 were
considered significantly enriched by differentially expressed genes.
KEGG provides comprehensive database resources for research of high-level functions and
utilities of biological systems (http://www.genome.jp/kegg/). Statistical enrichment of
differential expression genes in KEGG pathways was evaluated by KOBAS software.
Real-time quantitative reverse-transcription-PCR (qRT-PCR)
To verify the accuracy and repeatability of the transcription sequencing results, 10
differentially expressed genes were randomly selected to be detected using qRT-PCR. Designed by
Primer3 (http://fokker.wi.mit.edu/primer3/input.htm), the primer sequences were shown in
S1 File. The housekeeping gene GAPDH was used to correct the mRNA levels of differentially
expressed genes. qRT-PCR was carried out in triplicate with the LightCycler 1 480 SYBR
Green I Master Kit (Roche Applied Science, Penzberg, Germany), in a 15 μ L reaction on a
LightCycler480 (Roche), using the following program: 95ÊC for 8 min, 45 cycles of 95ÊC for 10
s, 60ÊC for 15 s, 72ÊC for 10 s, and 72ÊC for 10 min.
Antioxidant enzyme activities of embryos
Antioxidant enzyme activities of SOD, GSH-Px and POD were detected in the incubation
period. As shown in Fig 1A, the activity of SOD in the liver was higher than that in the heart
tissue during incubation at different time points. In addition, there was a slight increase in
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Fig 1. Effect of incubation day on SOD and GSH-PX activity in embryonic liver and heart. Note: The SOD activity (A) and GSH-PX (B) of
heart and liver tissues were determined at days 14 to 20. The value of each fraction was the mean± standard deviation (n = 3), different letters
(a, b) above columns indicate significant differences (p<0.05) in liver tissues, different letters (A, B) above columns indicate significant
differences (p<0.05) in heart tissues.
SOD activity in the liver, while it decreased in the heart with the increase in the incubation
period. Fig 1A showed that SOD activity in the liver had a significant change from days 14 to
20 (25.86% increase, P<0.05) while Fig 1B showed that GSH-PX activity in the heart had an
extremely significant change from days 14 to 20 (43.75% increase, P<0.01). Overall, the
activity of GSH-PX in the liver tissue was significantly higher than in that in the heart. Meanwhile,
the activity of POD in the heart and liver is shown in Fig 2. The results showed that POD
activity in the liver increased initially and then decreased, and its activity had a significant change
from days 14 to 20 (28.69% decrease, P<0.05). In the heart, the activity of POD increased
steadily. According to the antioxidant activities, liver tissues at day 16 and 20 were used for
Sequencing and mapping of the liver transcriptome
In total, we obtained 51,868,410±58,937,096 paired-end reads per sample. After removing the
sequencing adaptors and poor quality reads, we acquired a total of 336,724,356 clean reads,
and the total read length was 50.5 gigabases (GB) for six samples (Table 1). The data sets
analyzed are available in the NCBI GenBank (https://www.ncbi.nlm.nih.gov/genbank) and the
BioProject ID is PRJNA416967 (SRP123539). In this study, the Pearson correlation method
was used for the calculation of the correlation coefficient (R2). The result showed that R2of
biologically repeated samples was higher than 0.92, indicating that the similarity of the three
biological replicates within each group was sufficiently high.
Different gene expression between high and low groups for SOD activity
Using the DEseq R package, the differential gene expression profile between liver tissues in
chicken embryo at day 16 and day 20 was examined. In total, 18,837 genes were plotted.
Meanwhile, 1,154 (571 down and 583 up) differentially expressed genes were identified (DEGs) at
an FDR (false discovery rate) adjusted p-value <0.05, and absolute value of fold change 1 in
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Fig 2. Effect of incubation day on POD activity in embryonic liver and heart. Note: The POD activity of heart and
liver tissues was determined at days 14 to 20. The value of each fraction was the mean± standard deviation (n = 3),
different letters (a, b) above columns indicate significant differences (p<0.05) in liver tissues, different letters (A, B)
above columns indicate significant differences (p<0.05) in heart tissues.
two samples. Volcano plots of the two comparison groups that are differentially expressed
illustrate the distinct transcriptional profiles, displayed in Fig 3. The details of all DEGs are
shown in S2 File.
GO and pathway analysis of the DGEs
To further evaluate the function of differentially expressed genes, GO classification analysis
was used to annotate all genes identified from liver tissues, and formed into three categories:
cellular components, biological processes, and molecular functions. These 1154 differential
expressed genes were analyzed by GO enrichment, and 7731 GO terms were obtained. Of
these, 1069 GO terms (13.83%) were significantly enriched (p<0.05) (S3 File). GO terms with
P-value less than 0.05 were considered significantly enriched by DEGs. Among these GO
terms, there are some GO terms related with cell cycle process, regulation of cell cycle and
response to stress etc. In addition, there are 10 GO terms significantly related with antioxidant
enzyme activity (P<0.01), such as glutathione transferase activity, a response to reactive
oxygen species (Table 2). Meanwhile, we conducted metabolic pathway analysis using KOBAS
software; the details of the significant pathway in the two-comparison group are shown in S4
File. The results of the KEGG analysis showed that several important pathways, such as
ªglyoxylate and dicarboxylate metabolismº, ªcarbon metabolismº, and the ªp53 signaling pathwayº
Real-time quantitative PCR
Ten genes (PAPSS1, CCNB3, DYNLL1, GGT5, CLGN, ULK2, SPP1, VAV2, CEP170B, and
SARS) were analyzed to confirm expression profiles and validate the transcriptome analysis
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Note: Day 20 means the liver tissues in chicken embryo at day 20 and Day 20±1, Day 20±2, Day 20±3 mean the three biological replicate liver tissues in Day20 group, the
rest of groups share the same name rules. Q20, the proportion of bases with a phred base quality score greater than 20; i.e., the proportion of read bases whose error rate
is less than 1%.Q30, the proportion of bases with a phred base quality score greater than 30; i.e., the proportion of read bases whose error rate is less than 0.1%.
results (Fig 4). The results showed that the gene expression levels were all consistent with
mRNA-Seq results, which confirmed that the results obtained from the transcriptome
sequencing platform were accurate.
According to the GO database, within significantly enriched biological processes, 8 biological
processes were related to reactive oxygen species and antioxidant enzyme activities. Among
these processes, the most significant one was ªresponse to reactive oxygen speciesº. Integrated
analysis of DEGs, GO and pathway results, and gene function allow us to suggest GSTA2,
Fig 3. Volcano plot displaying DEGs within two different comparison groups. Note: the y-axis shows the mean
expression value of log10(q-value), and the x-axis displays the log2fold change value. The blue dots represent the transcripts
that did not reach statistical significance (q > 0.05); the red (up-regulated) and green dots (down-regulated) represent those
whose expression levels were significantly different (q < 0.05); the blue dots represent the transcripts did not reach statistical
significance (q > 0.05).
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Note: GO ID indicates the label information in the Gene Ontology database, GO term refers to the description information of Gene Ontology function, P<0.05 means
the function is an enriched item
MGST1, GSTA4, GPX3 and HAO2 (Table 3) as the 5 promising candidate genes for affecting
the activity of antioxidant enzymes during chicken embryo development.
RNA-Seq has been applicated in many fields in chickens. Monson [
] established the liver
library of domesticated turkey and wild turkey with AFB1 treatment by RNA-Seq and
Fig 4. Validation of the gene expression profile by real-time PCR. Note: The x-axis represents the gene name, the
yaxis represents the log2Ratio (Day20/Day16), different color columns represent data from RT-PCR or RNA-Seq.
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obtained 89.2Gb of sequence. Sporer [
] utilized the microarray to detect the key genes in
turkey skeletal muscle development and identified DEGs between two genetic lines of turkeys.
] revealed the differences of gene expression in the abdominal fat with high and low
feed efficiency commercial broiler chickens. RNA-Seq was first used for analysis of early
embryonic development in cattle and provided a method for further study mammalian
embryonic development [
]. Based on those studies, we evaluated the whole genome transcriptome
profile of chicken embryo liver tissues on different incubation days using RNA-Seq, with the
aim of determining key genes that regulate the activity of antioxidant enzymes in this study.
Compared with mammals, chicken embryonic development is carried out in a semi-closed
system, and these natural antioxidants (SOD, GSH-PX and CAT) have been suggested to play
a central role at hatching [
]. Therefore, the aim of this study is to detect the differentially
expressed genes associated with the activities of antioxidant enzymes during chick embryonic
development. In the present study, the activity of SOD and GSH-PX was significantly higher
in the liver than in the heart. In the heart, GSH-PX activity value was half of that in the liver,
which was consistent with results shown by Surai [
]. Additionally, CAT in the liver might be
less important in ROS defense. Thus, the results of antioxidant enzyme activity revealed
that the liver was an important source of antioxidants. The different activities of antioxidant
enzymes in the liver may be caused by different regulation of gene expression. According to
the antioxidant enzyme activity detected in this study, the cDNA library was established by the
liver. The transcript was deeply sequenced and the package of DESeq and Cuffdiff was used for
analyses. We obtained 1,154 differentially expressed genes, while some of the genes have a
known function, e.g., GSTA, GGT, GPX3, studies have also reported that these genes are
associated with antioxidant enzyme activity [28±30]. Of these, DEGs, APOA4, LTC4S, GSTA2,
MGST1, GSTA4, GPX3, and PEX11A were suggested to be the promising candidate genes for
affecting the mechanisms of the defense system in response to ROS during chicken embryo
Apolipoprotein (apo) A-IV (APOA4) was detected in the processes of ªresponse to reactive
oxygen speciesº, ªresponse to oxidative stressº, ªresponse to lipid hydroperoxideº, ªcellular
response to oxidative stressº, and ªresponse to hydroperoxideº. APOA4 is a 46 kDa
glycoprotein and encodes a protein consisting of 396 amino acid residues. Kumar et al. [
that APOA4 is an important mediator of lipid metabolism and has antioxidant activity. Studies
have shown that the antioxidant effect of APOA4 is mediated by its ability to bind to the
surface of the abundant lipoprotein lipase within atherosclerotic plaques [
]. Ostoa et al [
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suggested that APOA4 and APOA1 accumulate in diseased artery walls to help protect against
As a member of the MAPEG (Membrane Associated Proteins in Eicosanoid and
Glutathione metabolism) family of transmembrane proteins, leukotrieneC4 synthase (LTC4S) was
down-regulated in this study. LTC4S encodes an enzyme that catalyzes the first step in
biosynthesis of cysteinyl leukotrienes (LT), which possess important functions in inflammation [
Zhang et al. [
] showed that LTC4S and Orai3 can promote vascular smooth muscle cell
migration and neointima formation by changing Akt signaling.
Glutathione S-transferase alpha 2 (GSTA2) is a member of a family of glutathione
S-transferases (GSTs), located in a cluster of similar genes and pseudogenes on chromosome 6.
GSTA2 plays a role in detoxification by adding glutathione to target electrophilic compounds.
Located in a cluster mapped to chromosome 6, GSTA2 is the most abundantly expressed
glutathione S-transferase in the liver [36±37]. Additionally, GSTA2 has glutathione peroxidase
activity, thereby protecting the cells from reactive oxygen species and the products of
peroxidation. Tetlow [
] suggested that GSTA2 is a majorline of defense against oxidative stress.
Glutathione S-transferase alpha4 (GSTA4) encodes a glutathione S-transferase belonging to
the alpha class. The alpha class genes are highly related and encoded enzymes with glutathione
peroxidase activity, that have a function in the detoxification of lipid peroxidation products
]. Shearn [
] suggested that GSTA4 is a phase 2 detoxifying enzymes, and that its
expression increases in response to oxidative stress.
The microsomal glutathione S-transferase 1 (MGST1) gene encodes a protein that catalyzes
the combination of glutathione to electrophiles and the reduction of lipid hydroperoxides. In
addition, it scavenges reactive intermediates through its glutathione dependent transferase and
peroxidase activities [
]. Glutathione peroxidase 3 (GPX3) belongs to the glutathione
peroxidase family, which catalyzes the reduction of organic hydroperoxides and hydrogen peroxide
by glutathione, and protects cells against oxidative damage [
]. Olson et al. [
that GPX3 was the only known selenocysteine-containing extracellular form of glutathione
peroxidase. Barrett et al. [
] reported that knockdown of GPX3 in the human colon cancer
cell line Caco2 caused an increase in ROS production. In addition, Xu et al.[
] suggested that
vitamin E improves the antioxidant defense mechanisms, and enriches the GPX3 mRNA and
protein expression levels, thereby enhancing the testicular antioxidant capacity. Peroxisomal
biogenesis factor 11 alpha (PEX11A) is the richest ingredient of the peroxisomal membrane,
and essential for proliferation of peroxisomes [
]. RodrÂõguez-Serrano et al [
] reported that
in Arabidopsis, PEX11A lines exhibited higher levels of lipid peroxidation content and lower
expression of genes involved in antioxidative defense and signaling. Weng et al. [
that the deficiency of PEX11A is related to peroxisome abundance reduction.
KEGG metabolic pathway was used to analyze the function of differentially expressed
genes, and 16 out of 139pathway terms was significantly enriched. Of these, ªGlutathione
metabolismº and ªGlyoxylate and dicarboxylate metabolismº were pathway terms related to
ROS defense. As a low molecular weight tripeptide, glutathione (GSH) is only present in a
small quantity in the oxidation process[
]. Reduced GSH reduces the peroxide toH2O, and
free radical reactions in vivo can be maintained. ªGlutathione metabolismº pathway involved
9 differentially expressed genes, which were all down-regulated. Presumably, the mechanism is
that the up-regulation of GPX3 (188.8.131.52) promotes the conversion of GSH to GSSG, and
glutathione reductase (GSR) (184.108.40.206) catalyzes the reduction of GSSG to GSH with NADPH as an
H donor. Meanwhile, changes in the differentially expressed genes indicate that the
glutathione metabolism in the liver is accelerated during the later stage of hatching. Additionally,
hydroxyacid oxidase 2 (HAO2) was up-regulated in the conversion process of Glycolate to
H2O2. The up-regulation of HAO2 indicated that it can catalyze more glycolate and generate
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more H2O2. Mattu et al. [
] also revealed that the increased expression of HAO2 caused
increased ROS production and lipid peroxidation.
SOD, GSH-PX, and POD together play a role in the fight against ROS together in the
embryo; the SOD activity is decreased with the generation of H2O2, when scavenging O2-.
While adding CAT and GSH, H2O2can be decomposed. In this study, most genes in the
ªglutathione metabolismº pathway were down-regulated, indicating more GSH involved in
scavenging H2O2, thereby protecting SOD activity. PEX11a down-regulated revealed the decrease in
POD activity, and more POD participating in ROS defense with GSH.
In this comprehensive analysis of GO enrichment and the KEGG pathway, we discovered
that some different gene expression not only exists in significantly enriched GO terms, but
also participates significantly in the KEGG pathway; these genes were MGST1, GSTA2, GSTA4,
GPX3, HAO2. This result revealed that these 5 genes may be key genes affecting ROS defense
and antioxidant enzymes. These genes were associated with glutathione metabolism, and thus
affected enzyme activity. This discovery also confirmed that GSH-PX played a primary role in
antioxidant defense in the liver. Further research is required to understand the molecular
mechanisms of these candidate genes on ROS defense and antioxidant enzyme in chickens.
Chicken embryo liver tissues at day 16 and day 20 were used as the follow-up study materials.
In this study, we provided a comprehensive analysis of the complexity of the liver tissue
transcriptome, and identified 1,154 differentially expressed genes between different incubation
periods, with high and low antioxidant enzyme activity. GO enrichment and pathway analysis
revealed 5 key genes affecting ROS defense and antioxidant enzymes, including MGST1,
GSTA2, GSTA4, GPX3 and HAO2.
S1 File. PCR primers for qRT-PCR validation of 10 DEGs between the two different comparison groups.
S2 File. List of DEGs in liver tissues within two different comparison groups.
S3 File. GO enrichment list of DEGs between high and low antioxidant enzyme activity in biological processes.
S4 File. List of significant KEGG pathway categories for DEGs.
Conceptualization: Shaohua Yang, Guoqing Liu.
Data curation: Shaohua Yang, Lu Lu Wang, Wei Wang.
Formal analysis: Lu Lu Wang, Wei Wang, Xue Chen.
Funding acquisition: Shaohua Yang, Wei Wang, Guoqing Liu.
Investigation: Xue Chen, Guoqing Liu.
Methodology: Xiaoqian Ou, Xue Chen.
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Project administration: Shaohua Yang, Guoqing Liu.
Resources: Lu Lu Wang, Zhaoyuan Shi.
Software: Lu Lu Wang, Zhaoyuan Shi, Xiaoqian Ou.
Supervision: Shaohua Yang, Guoqing Liu.
Validation: Zhaoyuan Shi.
Visualization: Zhaoyuan Shi, Xiaoqian Ou.
Writing ± original draft: Lu Lu Wang.
Writing ± review & editing: Shaohua Yang, Guoqing Liu.
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