Accepted Manuscript Title: High-Throughput Sequencing Reveals Differing Immune Responses in the Intestinal Mucosa of Two Inbred Lines Afflicted with Necrotic Enteritis Author: Anh Duc Truong Yeong Ho Hong Hyun S. Lillehoj PII: DOI: Reference:
S0165-2427(15)00134-8 http://dx.doi.org/doi:10.1016/j.vetimm.2015.06.008 VETIMM 9356
To appear in:
VETIMM
Received date: Revised date: Accepted date:
26-12-2014 18-3-2015 20-6-2015
Please cite this article as: Truong, A.D., Hong, Y.H., Lillehoj, H.S.,High-Throughput Sequencing Reveals Differing Immune Responses in the Intestinal Mucosa of Two Inbred Lines Afflicted with Necrotic Enteritis, Veterinary Immunology and Immunopathology (2015), http://dx.doi.org/10.1016/j.vetimm.2015.06.008 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1 2
High-Throughput Sequencing Reveals Differing Immune Responses in the Intestinal Mucosa of Two Inbred Lines Afflicted with Necrotic Enteritis
3
Anh Duc Truong1, Yeong Ho Hong1* and Hyun S. Lillehoj2 1
5 6
Department of Animal Science and Technology
ip t
4
Chung-Ang University, Anseong 456-756, Republic of Korea 2
Animal Biosciences and Biotechnology Laboratory,
cr
7
Agricultural Research Services, United States Department of Agriculture
9
Beltsville, MD 20705, USA
an
us
8
M
10 11
14 15 16
Ac ce pt e
13
d
12
17
*Address correspondence:
18
Yeong Ho Hong, Ph.D.
19
Department of Animal Science and Technology
20
Chung-Ang University, Anseong 456-756,
21 22 23
Republic of Korea Tel: +82-31-670-3025, Fax: +82-31-671-3025 E-mail: [email protected]
24
1/24 Page 1 of 31
1
Abstract We investigated the necrotic enteritis (NE)-induced transcripts of immune-related genes
3
in the intestinal mucosa of two highly inbred White Leghorn chicken lines, line 6.3 and line
4
7.2, which share the same MHC haplotype and show different levels of NE susceptibility using
5
high-throughput RNA sequencing (RNA-Seq) technology. NE was induced by the previously
6
described co-infection model using E. maxima and C. perfringens. The RNA-Seq generated over 38
7
million sequence reads for Marek’s disease (MD)-resistant line 6.3 and over 40 million reads for
8
the MD-susceptible line 7.2. Alignment of these sequences with the Gallus gallus genome database
9
revealed the expression of over 29,900 gene transcripts induced by NE in these two lines, among
10
which 7,841 genes were significantly upregulated and 2,919 genes were downregulated in line 6.3
11
chickens and 6,043 genes were significantly upregulated and 2,764 genes were downregulated in
12
NE-induced line 7.2 compared with their uninfected controls. Analysis of 560 differentially
13
expressed genes (DEGs) using the gene ontology database revealed annotations for 246 biological
14
processes, 215 molecular functions, and 81 cellular components. Among the 53 cytokines and 96
15
cytokine receptors, 15 cytokines and 29 cytokine receptors were highly expressed in line 6.3,
16
whereas the expression of 15 cytokines and 15 cytokine receptors was higher in line 7.2 than in line
17
6.3 (fold change ≥ 2, p < 0.01). In a hierarchical cluster analysis of novel mRNAs, the novel
18
mRNA transcriptome showed higher expression in line 6.3 than in line 7.2, which is consistent with
19
the expression profile of immune-related target genes.
Ac ce pt e
d
M
an
us
cr
ip t
2
20
In qRT-PCR and RNA-Seq analysis, all the genes examined showed similar responses to NE
21
(correlation coefficient R= 0.85 to 0.89, p < 0.01) in both lines 6.3 and 7.2. This study is the first
22
report describing NE-induced DEGs and novel transcriptomes using RNA-seq data from two inbred
23
chicken lines showing different levels of NE susceptibility. These findings provide important
24
insights into our current knowledge of host-pathogen interaction and the nature of host genes that
25
can serve as NE resistance markers for molecular breeding.
26
Keywords: RNA-seq, Necrotic Enteritis, Chicken, E. maxima, C. perfringens
27
2/24 Page 2 of 31
1
1. Introduction
2
Necrotic enteritis (NE) is an acute or chronic enterotoxemia caused by Clostridium perfringens
4
(C. perfringens) where a prior infection with Eimeria maxima (E. maxima) is a primary risk factor
5
in chickens, turkeys, and ducks (Bannam et al., 2011, Savva et al., 2012 and Mot et al., 2013). With
6
the regulatory ban of antibiotic growth promoters, NE which is caused by netB toxin-producing C.
7
perfringens type A and to a lesser extent by type C strains (Songer, 1996 and Yan et al., 2013), is
8
becoming an important enteric disease in chicken worldwide (Bannam et al., 2011, Savva et al.,
9
2012 and Mot et al., 2013) and has been estimated to cost the world poultry industry approximately
10
$2 billion annually (McReynolds et al., 2004). However, the molecular mechanisms underlying the
11
pathology of NE remain to be determined. High-throughput RNA sequencing (RNA-Seq) is a
12
recently developed approach that uses a massively parallel sequencing strategy to generate
13
transcriptome profiles (Wang et al., 2013) and is considered a revolutionary tool for
14
transcriptomics, as it can absolutely quantify millions of unknown transcripts. It has also shown
15
great analytical power for the identification of transcripts that are differentially expressed in
16
response to different conditions (Wang et al., 2011 and Xia et al., 2013).
Ac ce pt e
d
M
an
us
cr
ip t
3
17
In a dual infection model of NE, E. maxima facilitates the replication and toxin production of
18
C. perfringens and is thus used in conjunction with C. perfringens for the development of
19
experimental NE disease models (Lee et al., 2011). To date, many studies have used RNA-seq
20
technology for transcriptome analysis in mammals. However, this is the first time this technology
21
has been used to study host pathogen interaction in NE in the intestinal mucosa using two inbred
22
White Leghorn chickens differing NE susceptibility. In this study, we experimentally induced NE
23
using E. maxima and C. perfringens to identify differentially expressed mRNA in intestinal mucosa
24
of the chicken lines 6.3 and 7.2 which have been selected for their disparate susceptibility to
25
Marek’s Disease (Briles et al., 1977). Our new findings provide further insights into the molecular
26
mechanisms that underline posttranscriptional regulation by mRNA of mucosal tissue in NE-
27
afflicted chickens that will facilitate the development of novel strategies to control NE and the new 3/24 Page 3 of 31
1
genes identified in this study will be useful molecular markers for selecting NE resistance in
2
commercial chickens.
3 4
2. Materials and Methods
5
2.1. Experimental animals The two White Leghorn chicken lines, namely, the MD-resistant line 6.3 and MD-susceptible
7
line 7.2, were obtained from the Avian Disease and Oncology Laboratory (East Lansing, MI, USA)
8
of the Agricultural Research Service of the United States Department of Agriculture (USDA).
9
Chickens were raised in Petersime starter brooder units, provided ad libitum access to water, and
10
maintained under uniform standard management conditions. Experimental and control groups were
11
kept in separate rooms, preventing cross-contamination throughout the course of the experiment.
an
us
cr
ip t
6
13
2.2. Experimental NE disease model
M
12
The method used to produce NE was previously described (Jang et al., 2012). Chickens were
15
infected with E. maxima (1.0 104 oocysts/bird) by oral gavage on day 14, which was followed by
16
oral gavage with a field strain of C. perfringens strain Del-1(1.0 109 colony forming units
17
[CFU]/bird) after 4 days. For development of NE, the birds were fed a non-medicated commercial
18
basal ration of 17% crude protein from 1 to 18 days of age, and at 18–20 days of age, the feed was
19
replaced with commercial non-medicated feed containing 24% crude protein. All protocols were
20
approved by the Beltsville Area Institutional Animal Care and Use Committee.
22
Ac ce pt e
21
d
14
2.3. Total RNA preparation
23
The small intestines from five chickens per group were cut longitudinally and briefly washed 3
24
times with ice-cold Hanks’ balanced salt solution (HBSS) containing 100 U/mL penicillin and 100
25
mg/mL streptomycin (Sigma, St. Louis, MO, USA). The mucosal layer was carefully removed
26
using a cell scraper (Nunc, Thermo Scientific Inc., Waltham, MA, USA). The samples were placed 4/24 Page 4 of 31
on ice immediately and maintained on ice until the total RNA extraction. Total RNA was isolated
2
using TRizol reagent (Invitrogen, Carlsbad, CA, USA) as described (Hong et al., 2012). RNA
3
concentrations were quantified using a NanoDrop spectrophotometer (NanoDrop Technologies,
4
USA), and the 260/280 nm ratio was confirmed to be between 1.7 and 2.0. The integrity of the total
5
RNA samples was evaluated using the Agilent 2100 (Agilent Technologies, Inc., Santa Clara, CA,
6
USA) and Tecan F2000 (Tecan Group Ltd., Männedorf, Switzerland) devices, and only samples
7
with an RNA integrity number (RIN) > 7.0 and high-quality RNA (28S/18S > 1) were used for the
8
subsequent experiments.
cr
ip t
1
10
us
9
2.4. mRNA sequencing and analysis
Reverse transcription was performed and cDNA was synthesized using 5’ adaptor forward and
12
3’ adaptor reverse primers. Libraries for Illumina sequencing were constructed from cDNA as
13
described (Trapnell et al., 2010). High-throughput RNA sequencing was performed by Theragen
14
Bio Institute (Suwon, Korea) on an Illumina HiSeq 2000 high-throughput sequencer (Illumina, Inc.
15
San Diego, CA, USA) according to the manufacturer’s specifications. RNA-Seq data were
16
analyzed according to the method described (Trapnell et al., 2012). Briefly, reads were mapped to
17
the Gallus gallus reference genome (v.4.0) obtained from the University of California, Santa Cruz
18
(UCSC)
19
(http://tophat.cbcb.umd.edu/), and Bowtie v.0.12.8 (http://bowtie-bio.sourceforge.net/index.shtml)
20
from Illumina iGenomes (http://support.illumina.com/). Gene expression values were measured for
21
each gene from the Ensembl database by fragments per kilobase of exon per million mapped reads
22
(FPKM) calculated using Cufflinks v2.0.1 (http://cufflinks.cbcb.umd.edu/) (Mortazavi et al., 2008).
23
Differentially expressed genes were considered in a given library when 1) the p-value was less than
24
0.01 and 2) a greater-than-or-equal to 2-fold change in expression across libraries was observed and
25
used to identify the genes differentially expressed between two chicken lines. Subsequently, the
26
differential expression pattern analysis of known mRNA and prediction of novel mRNA were
Ac ce pt e
d
M
an
11
database
(UCSC:
http://genome.ucsc.edu/)
using
TopHat
v.2.0.3
5/24 Page 5 of 31
performed using unannotated sRNAs. Gene ontology (GO) terms and annotations were matched on
2
GO terms in the database (http://www.geneontology.org/), and the functional enrichment analysis
3
was performed using Blast2GO (v.2.7.1) (http://www.blast2go.org/). Further, significantly differed
4
genes from the corresponding library were searched against the Kyoto Encyclopedia of Genes and
5
Genomes (KEGG) database to determine the pathways using DAVID Bioinformatics Resources
6
version 6.7, NIAID/NIH (http://david.abcc.ncifcrf.gov/tools.jsp) with p < 0.01.
ip t
1
7
cr
9
2.5. Hierarchical cluster analysis for mRNA
Hierarchical cluster analysis was performed for mRNAs using Cluster version 4.49 software
us
8
10
http://www.bram.org/serf/Clusters.php
11
(http://sourceforge.net/projects/jtreeview/files/). Intestinal samples of lines 6.3 and 7.2 were
12
compared as treatment and control samples, respectively. Cluster map analysis of genes was
13
performed using the Euclidean distance. The p values were calculated using the right-tailed Fisher’s
14
exact test.
Treeview
software
d
M
an
Java
Ac ce pt e
15 16
and
2.5. cDNA synthesis
17
For analysis of mRNA gene expression levels, 5 µg of total RNA was treated with 1.0 unit of
18
DNase I and 1.0 μL of 10 reaction buffer (Thermo Scientific, Waltham, MA, USA), and
19
incubated for 30 min at 37°C. Subsequently, to inactivate DNase I, 1.0 μL of 50 mM EDTA was
20
added and the mixture was heated to 65°C for 10 min. RNA was reverse-transcribed using the
21
Maxima First Strand cDNA Synthesis Kit (Thermo Scientific, Waltham, MA, USA) according to
22
the manufacturer's recommendations. Briefly, 5.0 μg of RNA was combined with 0.2 μg of oligo
23
(dT)18 primer and RNase-free water to give a total volume of 12.0 μL. Then, 4.0 μl of 5 X reaction
24
buffer, 20 units of Ribolock RNase Inhibitor, 10 mM dNTP mix, and 200 units of RevertAcid M-
25
MuLV reverse transcriptase were added. The mixture was incubated at 42°C for 60 min and heated
6/24 Page 6 of 31
1
at 70°C for 5 min to terminate the reaction. After cDNA synthesis, the gene expression profile was
2
determined using an equivalent amount of cDNA.
3 4
2.6. Quantitative real-time PCR (qRT-PCR) All real-time PCR primers used in this study for cytokine genes were designed using
6
Lasergene software (DNASTAR Inc. Madison, WI, USA) and synthesized by Genotech Corp.
7
(Daejeon, South Korea). Details for the primers are given in supplementary Table S1. Cytokine
8
gene expression was quantified using standard curves that were generated using log10 diluted
9
cDNA from individual total RNA samples as described (Hong et al., 2012). cDNA (100 ng) was
10
added into a reaction mix including 10 μL of 2 Power SYBR Green Master Mix (Roche,
11
Indianapolis, USA), 0.5 μL of each primer, and RNase-free water to a total volume of 20 μL. Real-
12
time PCR was performed using a LightCycler 96 system (Roche, IN, USA) with the following
13
standard cycling program: pre-incubation at 95ºC for 10 min, followed by 45 cycles of 95ºC for 10
14
sec, 52ºC for 30 sec, and 72ºC for 30 sec.
d Ac ce pt e
15 16
M
an
us
cr
ip t
5
2.7. Statistical analysis
17
Statistical analyses were performed using IBM SPSS software (SPSS 20.0 for Windows,
18
Chicago, IL, USA). The data are expressed as the mean values ± SD for each group (N = 5) and
19
were compared between groups using Student’s t-test. Statistical significance was defined as p
S0165-2427(15)00134-8 http://dx.doi.org/doi:10.1016/j.vetimm.2015.06.008 VETIMM 9356
To appear in:
VETIMM
Received date: Revised date: Accepted date:
26-12-2014 18-3-2015 20-6-2015
Please cite this article as: Truong, A.D., Hong, Y.H., Lillehoj, H.S.,High-Throughput Sequencing Reveals Differing Immune Responses in the Intestinal Mucosa of Two Inbred Lines Afflicted with Necrotic Enteritis, Veterinary Immunology and Immunopathology (2015), http://dx.doi.org/10.1016/j.vetimm.2015.06.008 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1 2
High-Throughput Sequencing Reveals Differing Immune Responses in the Intestinal Mucosa of Two Inbred Lines Afflicted with Necrotic Enteritis
3
Anh Duc Truong1, Yeong Ho Hong1* and Hyun S. Lillehoj2 1
5 6
Department of Animal Science and Technology
ip t
4
Chung-Ang University, Anseong 456-756, Republic of Korea 2
Animal Biosciences and Biotechnology Laboratory,
cr
7
Agricultural Research Services, United States Department of Agriculture
9
Beltsville, MD 20705, USA
an
us
8
M
10 11
14 15 16
Ac ce pt e
13
d
12
17
*Address correspondence:
18
Yeong Ho Hong, Ph.D.
19
Department of Animal Science and Technology
20
Chung-Ang University, Anseong 456-756,
21 22 23
Republic of Korea Tel: +82-31-670-3025, Fax: +82-31-671-3025 E-mail: [email protected]
24
1/24 Page 1 of 31
1
Abstract We investigated the necrotic enteritis (NE)-induced transcripts of immune-related genes
3
in the intestinal mucosa of two highly inbred White Leghorn chicken lines, line 6.3 and line
4
7.2, which share the same MHC haplotype and show different levels of NE susceptibility using
5
high-throughput RNA sequencing (RNA-Seq) technology. NE was induced by the previously
6
described co-infection model using E. maxima and C. perfringens. The RNA-Seq generated over 38
7
million sequence reads for Marek’s disease (MD)-resistant line 6.3 and over 40 million reads for
8
the MD-susceptible line 7.2. Alignment of these sequences with the Gallus gallus genome database
9
revealed the expression of over 29,900 gene transcripts induced by NE in these two lines, among
10
which 7,841 genes were significantly upregulated and 2,919 genes were downregulated in line 6.3
11
chickens and 6,043 genes were significantly upregulated and 2,764 genes were downregulated in
12
NE-induced line 7.2 compared with their uninfected controls. Analysis of 560 differentially
13
expressed genes (DEGs) using the gene ontology database revealed annotations for 246 biological
14
processes, 215 molecular functions, and 81 cellular components. Among the 53 cytokines and 96
15
cytokine receptors, 15 cytokines and 29 cytokine receptors were highly expressed in line 6.3,
16
whereas the expression of 15 cytokines and 15 cytokine receptors was higher in line 7.2 than in line
17
6.3 (fold change ≥ 2, p < 0.01). In a hierarchical cluster analysis of novel mRNAs, the novel
18
mRNA transcriptome showed higher expression in line 6.3 than in line 7.2, which is consistent with
19
the expression profile of immune-related target genes.
Ac ce pt e
d
M
an
us
cr
ip t
2
20
In qRT-PCR and RNA-Seq analysis, all the genes examined showed similar responses to NE
21
(correlation coefficient R= 0.85 to 0.89, p < 0.01) in both lines 6.3 and 7.2. This study is the first
22
report describing NE-induced DEGs and novel transcriptomes using RNA-seq data from two inbred
23
chicken lines showing different levels of NE susceptibility. These findings provide important
24
insights into our current knowledge of host-pathogen interaction and the nature of host genes that
25
can serve as NE resistance markers for molecular breeding.
26
Keywords: RNA-seq, Necrotic Enteritis, Chicken, E. maxima, C. perfringens
27
2/24 Page 2 of 31
1
1. Introduction
2
Necrotic enteritis (NE) is an acute or chronic enterotoxemia caused by Clostridium perfringens
4
(C. perfringens) where a prior infection with Eimeria maxima (E. maxima) is a primary risk factor
5
in chickens, turkeys, and ducks (Bannam et al., 2011, Savva et al., 2012 and Mot et al., 2013). With
6
the regulatory ban of antibiotic growth promoters, NE which is caused by netB toxin-producing C.
7
perfringens type A and to a lesser extent by type C strains (Songer, 1996 and Yan et al., 2013), is
8
becoming an important enteric disease in chicken worldwide (Bannam et al., 2011, Savva et al.,
9
2012 and Mot et al., 2013) and has been estimated to cost the world poultry industry approximately
10
$2 billion annually (McReynolds et al., 2004). However, the molecular mechanisms underlying the
11
pathology of NE remain to be determined. High-throughput RNA sequencing (RNA-Seq) is a
12
recently developed approach that uses a massively parallel sequencing strategy to generate
13
transcriptome profiles (Wang et al., 2013) and is considered a revolutionary tool for
14
transcriptomics, as it can absolutely quantify millions of unknown transcripts. It has also shown
15
great analytical power for the identification of transcripts that are differentially expressed in
16
response to different conditions (Wang et al., 2011 and Xia et al., 2013).
Ac ce pt e
d
M
an
us
cr
ip t
3
17
In a dual infection model of NE, E. maxima facilitates the replication and toxin production of
18
C. perfringens and is thus used in conjunction with C. perfringens for the development of
19
experimental NE disease models (Lee et al., 2011). To date, many studies have used RNA-seq
20
technology for transcriptome analysis in mammals. However, this is the first time this technology
21
has been used to study host pathogen interaction in NE in the intestinal mucosa using two inbred
22
White Leghorn chickens differing NE susceptibility. In this study, we experimentally induced NE
23
using E. maxima and C. perfringens to identify differentially expressed mRNA in intestinal mucosa
24
of the chicken lines 6.3 and 7.2 which have been selected for their disparate susceptibility to
25
Marek’s Disease (Briles et al., 1977). Our new findings provide further insights into the molecular
26
mechanisms that underline posttranscriptional regulation by mRNA of mucosal tissue in NE-
27
afflicted chickens that will facilitate the development of novel strategies to control NE and the new 3/24 Page 3 of 31
1
genes identified in this study will be useful molecular markers for selecting NE resistance in
2
commercial chickens.
3 4
2. Materials and Methods
5
2.1. Experimental animals The two White Leghorn chicken lines, namely, the MD-resistant line 6.3 and MD-susceptible
7
line 7.2, were obtained from the Avian Disease and Oncology Laboratory (East Lansing, MI, USA)
8
of the Agricultural Research Service of the United States Department of Agriculture (USDA).
9
Chickens were raised in Petersime starter brooder units, provided ad libitum access to water, and
10
maintained under uniform standard management conditions. Experimental and control groups were
11
kept in separate rooms, preventing cross-contamination throughout the course of the experiment.
an
us
cr
ip t
6
13
2.2. Experimental NE disease model
M
12
The method used to produce NE was previously described (Jang et al., 2012). Chickens were
15
infected with E. maxima (1.0 104 oocysts/bird) by oral gavage on day 14, which was followed by
16
oral gavage with a field strain of C. perfringens strain Del-1(1.0 109 colony forming units
17
[CFU]/bird) after 4 days. For development of NE, the birds were fed a non-medicated commercial
18
basal ration of 17% crude protein from 1 to 18 days of age, and at 18–20 days of age, the feed was
19
replaced with commercial non-medicated feed containing 24% crude protein. All protocols were
20
approved by the Beltsville Area Institutional Animal Care and Use Committee.
22
Ac ce pt e
21
d
14
2.3. Total RNA preparation
23
The small intestines from five chickens per group were cut longitudinally and briefly washed 3
24
times with ice-cold Hanks’ balanced salt solution (HBSS) containing 100 U/mL penicillin and 100
25
mg/mL streptomycin (Sigma, St. Louis, MO, USA). The mucosal layer was carefully removed
26
using a cell scraper (Nunc, Thermo Scientific Inc., Waltham, MA, USA). The samples were placed 4/24 Page 4 of 31
on ice immediately and maintained on ice until the total RNA extraction. Total RNA was isolated
2
using TRizol reagent (Invitrogen, Carlsbad, CA, USA) as described (Hong et al., 2012). RNA
3
concentrations were quantified using a NanoDrop spectrophotometer (NanoDrop Technologies,
4
USA), and the 260/280 nm ratio was confirmed to be between 1.7 and 2.0. The integrity of the total
5
RNA samples was evaluated using the Agilent 2100 (Agilent Technologies, Inc., Santa Clara, CA,
6
USA) and Tecan F2000 (Tecan Group Ltd., Männedorf, Switzerland) devices, and only samples
7
with an RNA integrity number (RIN) > 7.0 and high-quality RNA (28S/18S > 1) were used for the
8
subsequent experiments.
cr
ip t
1
10
us
9
2.4. mRNA sequencing and analysis
Reverse transcription was performed and cDNA was synthesized using 5’ adaptor forward and
12
3’ adaptor reverse primers. Libraries for Illumina sequencing were constructed from cDNA as
13
described (Trapnell et al., 2010). High-throughput RNA sequencing was performed by Theragen
14
Bio Institute (Suwon, Korea) on an Illumina HiSeq 2000 high-throughput sequencer (Illumina, Inc.
15
San Diego, CA, USA) according to the manufacturer’s specifications. RNA-Seq data were
16
analyzed according to the method described (Trapnell et al., 2012). Briefly, reads were mapped to
17
the Gallus gallus reference genome (v.4.0) obtained from the University of California, Santa Cruz
18
(UCSC)
19
(http://tophat.cbcb.umd.edu/), and Bowtie v.0.12.8 (http://bowtie-bio.sourceforge.net/index.shtml)
20
from Illumina iGenomes (http://support.illumina.com/). Gene expression values were measured for
21
each gene from the Ensembl database by fragments per kilobase of exon per million mapped reads
22
(FPKM) calculated using Cufflinks v2.0.1 (http://cufflinks.cbcb.umd.edu/) (Mortazavi et al., 2008).
23
Differentially expressed genes were considered in a given library when 1) the p-value was less than
24
0.01 and 2) a greater-than-or-equal to 2-fold change in expression across libraries was observed and
25
used to identify the genes differentially expressed between two chicken lines. Subsequently, the
26
differential expression pattern analysis of known mRNA and prediction of novel mRNA were
Ac ce pt e
d
M
an
11
database
(UCSC:
http://genome.ucsc.edu/)
using
TopHat
v.2.0.3
5/24 Page 5 of 31
performed using unannotated sRNAs. Gene ontology (GO) terms and annotations were matched on
2
GO terms in the database (http://www.geneontology.org/), and the functional enrichment analysis
3
was performed using Blast2GO (v.2.7.1) (http://www.blast2go.org/). Further, significantly differed
4
genes from the corresponding library were searched against the Kyoto Encyclopedia of Genes and
5
Genomes (KEGG) database to determine the pathways using DAVID Bioinformatics Resources
6
version 6.7, NIAID/NIH (http://david.abcc.ncifcrf.gov/tools.jsp) with p < 0.01.
ip t
1
7
cr
9
2.5. Hierarchical cluster analysis for mRNA
Hierarchical cluster analysis was performed for mRNAs using Cluster version 4.49 software
us
8
10
http://www.bram.org/serf/Clusters.php
11
(http://sourceforge.net/projects/jtreeview/files/). Intestinal samples of lines 6.3 and 7.2 were
12
compared as treatment and control samples, respectively. Cluster map analysis of genes was
13
performed using the Euclidean distance. The p values were calculated using the right-tailed Fisher’s
14
exact test.
Treeview
software
d
M
an
Java
Ac ce pt e
15 16
and
2.5. cDNA synthesis
17
For analysis of mRNA gene expression levels, 5 µg of total RNA was treated with 1.0 unit of
18
DNase I and 1.0 μL of 10 reaction buffer (Thermo Scientific, Waltham, MA, USA), and
19
incubated for 30 min at 37°C. Subsequently, to inactivate DNase I, 1.0 μL of 50 mM EDTA was
20
added and the mixture was heated to 65°C for 10 min. RNA was reverse-transcribed using the
21
Maxima First Strand cDNA Synthesis Kit (Thermo Scientific, Waltham, MA, USA) according to
22
the manufacturer's recommendations. Briefly, 5.0 μg of RNA was combined with 0.2 μg of oligo
23
(dT)18 primer and RNase-free water to give a total volume of 12.0 μL. Then, 4.0 μl of 5 X reaction
24
buffer, 20 units of Ribolock RNase Inhibitor, 10 mM dNTP mix, and 200 units of RevertAcid M-
25
MuLV reverse transcriptase were added. The mixture was incubated at 42°C for 60 min and heated
6/24 Page 6 of 31
1
at 70°C for 5 min to terminate the reaction. After cDNA synthesis, the gene expression profile was
2
determined using an equivalent amount of cDNA.
3 4
2.6. Quantitative real-time PCR (qRT-PCR) All real-time PCR primers used in this study for cytokine genes were designed using
6
Lasergene software (DNASTAR Inc. Madison, WI, USA) and synthesized by Genotech Corp.
7
(Daejeon, South Korea). Details for the primers are given in supplementary Table S1. Cytokine
8
gene expression was quantified using standard curves that were generated using log10 diluted
9
cDNA from individual total RNA samples as described (Hong et al., 2012). cDNA (100 ng) was
10
added into a reaction mix including 10 μL of 2 Power SYBR Green Master Mix (Roche,
11
Indianapolis, USA), 0.5 μL of each primer, and RNase-free water to a total volume of 20 μL. Real-
12
time PCR was performed using a LightCycler 96 system (Roche, IN, USA) with the following
13
standard cycling program: pre-incubation at 95ºC for 10 min, followed by 45 cycles of 95ºC for 10
14
sec, 52ºC for 30 sec, and 72ºC for 30 sec.
d Ac ce pt e
15 16
M
an
us
cr
ip t
5
2.7. Statistical analysis
17
Statistical analyses were performed using IBM SPSS software (SPSS 20.0 for Windows,
18
Chicago, IL, USA). The data are expressed as the mean values ± SD for each group (N = 5) and
19
were compared between groups using Student’s t-test. Statistical significance was defined as p
