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. 2018 May 12;96(6):2226–2237. doi: 10.1093/jas/skx016

Comparative transcriptome analysis of rumen papillae in suckling and weaned Japanese Black calves using RNA sequencing

Koki Nishihara 1,#, Daichi Kato 1,#, Yutaka Suzuki 2, Dahye Kim 1, Misato Nakano 1, Yu Yajima 1, Satoshi Haga 3, Miwa Nakano 3, Hiroshi Ishizaki 3, Ryouka Kawahara-Miki 4,5, Tomohiro Kono 4,5, Kazuo Katoh 1, Sang-gun Roh 1,✉
PMCID: PMC6095377  PMID: 29762736

Abstract

The length and density of rumen papillae starts to increase during weaning and growth of ruminants. This significant development increases the intraruminal surface area and the efficiency of VFA (acetate, propionate, butyrate, etc.) uptake. Thus, it is important to investigate the factors controlling the growth and development of rumen papillae during weaning. This study aimed to compare the transcriptomes of rumen papillae in suckling and weaned calves. Total RNA was extracted from the rumen papillae of 10 male Japanese Black calves (5 suckling calves, 5 wk old; 5 weaned calves, 15 wk old) and used in RNA-sequencing. Transcript abundance was estimated and differentially expressed genes were identified and these data were then used in Ingenuity Pathway Analysis (IPA) to predict the major canonical pathways and upstream regulators. Among the 871 differentially expressed genes screened by IPA, 466 genes were upregulated and 405 were downregulated in the weaned group. Canonical pathway analysis showed that “atherosclerosis” was the most significant pathway, and “tretinoin,” a derivative of vitamin A, was predicted as the most active upstream regulator during weaning. Analyses also predicted IgG, lipopolysaccharides, and tumor-necrosis factor-α as regulators of the microbe-epithelium interaction that activates rumen-related immune responses. The functional category and the up-regulators found in this study provide a valuable resource for studying new candidate genes related to the proliferation and development of rumen papillae from suckling to weaning Japanese Black calves.

Keywords: atherosclerosis pathway, Japanese Black calves, RNA sequencing, rumen papillae, transcriptome, tretinoin

INTRODUCTION

The rumen has physiologically essential functions such as nutrient uptake, transportation, and metabolism (Roh et al., 2007; Roh et al., 2016). Therefore, this organ is crucial for ruminant life, body maintenance, and growth (Warner et al., 1956; Tamate et al., 1962). A dramatic morphological development of rumen papillae occurs when feed is converted to roughage or concentrated from milk. Highly concentrated diets induce significant increases in rumen papillae density and length, as VFA (acetate, propionate, butyrate, among others) and lactate derive from intraruminal fermentation (Stobo et al., 1966). In neonatal Holstein calves, diets based on grain and on orchard-grass hay significantly increased the length and density of rumen papillae, whereas a milk-based diet had little effect on the development of these structures (Connor et al., 2013). Feeding VFA, particularly butyrate, significantly induced morphological development and promoted an increase in the length and density of the rumen epithelium (Sakata and Tamate, 1978; Shen et al., 2004; Gorka et al., 2011; Kato et al., 2011). Although many studies have been conducted on rumen development, only a few reported gene expression variations, regulatory factors, and gene networks in the rumen epithelium of calves fed different diets. Transcription factors, such as CREBBP (cAMP response element binding protein-binding protein) and TTF2 (transcription termination factor 2), were found to control several regulatory networks in the rumen epithelium by butyrate infusion using RNA-sequencing (RNA-seq) and Gene Ontology (GO) (Baldwin et al., 2012). Connor et al. (2013) reported that lipid metabolism, cell morphology and death, cellular growth and proliferation, molecular transport, and the cell cycle were predicted by GO analysis using Ingenuity Pathway Analysis (IPA) on microarray data obtained from the rumen epithelium of Holstein calves fed on a milk replacer and solid feed. Using digital differential display (DDD), Kato et al. (2015) identified candidate genes related to rumen development in suckling and weaned Japanese Black cattle (Kato et al., 2015). The present study reports the first application of RNA-seq to comprehensively investigate the transcriptomes of rumen papillae in suckling and weaned Japanese Black calves, aiming to identify differentially expressed genes (DEG) related to the development of rumen papillae.

MATERIALS AND METHODS

This study was conducted in accordance with the “Guidelines for the National Agriculture and Food Research Organization (NARO) Institute of Livestock and Grassland Science” and was approved by the Animal Care Committee of the NARO Institute of Livestock and Grassland Science.

Animals

Ten Japanese Black male calves were used in the experiment. Information on sires, dams, natural dams, and calves used in this study is presented in Supplementary Tables 1 and 2. All calves were bred at the Grassland Management Research Division, NARO Institute of Livestock and Grassland Science. Feed and management practices were as described previously (Kato et al., 2015; Suzuki et al., 2016). Japanese Black male calves born from March 2013 to May 2014 were assigned sequentially to the suckling and weaned groups. Finally, 5 calves in each group were used for this experiment. All calves were raised by natural suckling, and although none were creep fed, all had free access to dams’ feed. Calves in the suckling group were slaughtered at 5 wk of age, and their average body weight at slaughter was 51 ± 2 kg. Calves in the weaned group were separated from their dams at 12 wk of age and then raised by group feeding. All weaned calves were slaughtered at 15 to 16 wk of age, and their average body weight was 126 ± 8 kg. From 12 to 15–16 wk, weaned calves were only fed grower feed and timothy hay at 09:00 and 16:00 h to reach an average daily gain of about 0.6 kg, following the Japanese Feeding Standard for Beef Cattle (Agriculture, Forestry and Fisheries Research Council Secretariat, 2000). Grower feed components (CP 19.1% dry matter basis) were 39% grain (corn, milo, and wheat), 36% chaff and bran (bran, corn gluten meal, corn distiller’s dried grains with solubles, and draff), 11% vegetable oil cake (soybean and rapeseed), and 14% others (alfalfa, alfalfa meal, molasses, and minerals) in raw matter basis. Calves were allowed ad libitum access to water and mineral blocks. The blood hormones and metabolites of suckling and weaned calves were reported in our previous study (Suzuki et al., 2016).

Tissue Collection

After slaughter, rumen papillae tissues (approximately 1 × 1 cm) were collected from the ventral cranial sac. Excised rumen papillae tissues of suckling and weaned calves are shown in Figure 1. The papillae layer was manually separated from the muscular layer using surgical scissors and rinsed with PBS to remove residual feed particles. All tissue samples were frozen immediately in liquid nitrogen and stored at −80 °C until total RNA extraction was performed.

Figure 1.

Figure 1.

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Rumen papillae in suckling (A) and weaned (B) calves of Japanese Black cattle. Calves in the suckling group were slaughtered at 5 wk of age. Weaned calves were separated from their dams at 12 wk of age, and, after weaning, they were raised by group feeding. All weaned calves were slaughtered at 15 to 16 wk of age. The bar represents the scale (mm).

Total RNA Purification

Tissues were soaked in 200 μL RNAiso Plus (TAKARA Bio Inc., Shiga, Japan) in liquid nitrogen and homogenized using a Multibeads shocker (YASUIKIKAI Inc., Osaka, Japan), as indicated by the manufacturer. Homogenization was carried out twice at 2,000 rpm for 10 to 15 s, and 300 μL RNAiso was then added at 25 °C. The homogenate was collected in 1.5-mL tubes, 100-μL chloroform was added to the homogenate, and the solution was thoroughly mixed. After settling for 3 min at room temperature, the solution was centrifuged at 12,000 × g for 15 min at 4 °C, and the supernatant was collected. The supernatant was then mixed with 700 μL 70% ethanol. Total RNA was further purified and gDNA was removed using NucleoSpin RNA columns (MACHEREY-NAGEL, Düren, Germany), following the manufacturer’s instructions. Purified total RNA was quantified in a NanoDrop ND-1000 Spectrophotometer V3.7.1 (THERMO FISHER SCIENTIFIC, Waltham, MA, USA) at wavelengths of 230, 260, and 280 nm. The purity of total RNA was determined as the A260/A280 ratio, with expected values over 1.8, and was verified by running samples on 1.0% agarose gels. All samples were stored at −80 °C.

RNA-sequencing

The RNA Integrity Number (RIN) was confirmed in a Bioanalyzer 2100 using RNA nano kit (AGILENT, Palo Alto, CA, USA) to check if the purified total RNA could be used in RNA-seq. The average RIN in suckling and weaned groups was 7.1 (5.9 to 7.9) and 8.0 (7.5 to 8.4), respectively. Quality check of total RNA, library preparation, and RNA-seq were conducted at the NODAI Genome Research Center, Tokyo University of Agriculture. Single 50-bp reads were performed on a HiSeq 2500 platform (ILLUMINA, San Diego, CA, USA) using the TruSeq RNA Sample Preparation Kit v2 (ILLUMINA). Analysis of high-quality sequences was performed as in a previous report (Endo et al., 2013). Sequences were retained as high quality when passing the Illumina quality-filtering pipeline GERALD under default settings with the following conditions: only contain reads that passed filtering based on cluster intensities and noise estimates; demultiplexing; adapter masking; and ignore the first and last bases. These sequences were then aligned to the bovine reference genome (bosTau6) and to the exon–exon splice junction database downloaded from the University of California Santa Cruz (UCSC) sequence and annotation database (http://hgdownload.cse.ucsc.edu/downloads.html#cow). Alignment was performed in CLC Genomics Workbench (Qiagen, Valencia, CA, USA) using the defaults parameters. The EM estimation algorithm was used to iteratively estimate the abundance of transcripts and to assign reads to transcripts according to their abundances (Cappe and Moulines, 2009; Li and Dewey, 2011). Raw and normalized (i.e., Reads Per Kilobase of transcript per Million mapped reads [RPKM]) read counts (Mortazavi et al., 2008) were also calculated in CLC Genomics Workbench. After data normalization and fold change computation based on the estimated relative abundances of reads, the statistical significance of each pairwise comparison (suckling vs. weaned groups) was determined using the digital gene expression (DGE) empirical analysis tool incorporated in the EdgeR Bioconductor package (Robinson et al., 2010) and in the CLC Genomics Workbench. The DGE tool implements an “exact test” for two group comparisons, which is similar to Fisher’s exact test. The test is applicable to count data only and is designed for the analyses of differentially expressed RNA-seq data. In addition to P-values, FDR-corrected P-values were also calculated (Benjamini et al., 2001). Differentially expressed genes (fold change ≥ 2 and FDR-corrected P-value < 0.05) were analyzed regarding their biological processes and functions, and assigned to canonical pathways using IPA with the default parameters in General Settings, Networks, Data sources, Confidence, Species, Tissues & Cell Lines, and Mutation (Qiagen, www.qiagen.com/ingenuity). Fisher’s exact test was used in the analysis of gene set enrichment in the functional categories.

RESULTS

The Sequencing Results and the Dataset of Analyzed Genes

Sequencing of total RNA from rumen papillae in two lanes yielded, on average, 1067.4 and 1011.8 Mb and 21,353,595 and 20,238,186 sequence reads for suckling and weaned groups, respectively. The numbers of raw reads and mapped reads per sample are shown in Supplementary Table 3. Sequence data from RNA-seq were deposited in Sequence Read Archive (DRA) of DNA Data Bank of Japan (DDBJ). The accession number is DRA005801. After sequence alignment, 82% to 86% of the reads within each sample were mapped to the reference genome (Supplementary Table 3). Gene expression levels were then compared between groups based on these data, using the CLC Genomic Workbench. Overall, 17,001 of the 24,616 genes in the UCSC annotation were expressed, and 871 of these genes were differentially expressed, with fold change ≥ 2 and FDR < 0.05. Compared with the suckling group, weaning calves presented 466 upregulated and 405 downregulated genes (Supplementary Table 4). However, it should be noted that 43 of the 871 DEGs showed low expression level (RPKM < 1), which might have affected the large fold change detected.

Canonical Pathway Analysis

The seven major canonical pathways (P < 0.05) of DEGs found through IPA are displayed in Figure 2. Seventeen DEGs were found in the top canonical pathway “Atherosclerosis Signaling” (Figure 3, Table 1).

Figure 2.

Figure 2.

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Canonical pathway analysis generated by Ingenuity Pathway Analysis (IPA). The P-values and ratios of the 7 major pathways in suckling and weaned groups are displayed. Pathways were considered as most important at P < 0.05.

Figure 3.

Figure 3.

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The atherosclerosis-signaling pathway in rumen papillae. The Ingenuity Pathway Analysis (IPA) indicated that 17 genes were related to this pathway, and 12 of them functioned in the rumen papillae as demonstrated in this figure.

Table 1.

Genes integrating the atherosclerosis pathway

Symbol Entrez gene name Fold change1 FDR2 Location Type(s)
RBP4 Retinol binding protein 4, plasma 6.461 1.13E-09 Extracellular space Transporter
PLA2G4D Phospholipase A2, group IVD (cytosolic) 6.146 2.98E-03 Cytoplasm Enzyme
CMA1 Chymase 1, mast cell 5.912 7.36E-04 Extracellular space Peptidase
CCR2 Chemokine (C-C motif) receptor 2 3.998 1.45E-03 Plasma membrane G-protein coupled receptor
IL33 Interleukin 33 2.655 2.40E-05 Extracellular space Cytokine
PLA2G4F Phospholipase A2, group IVF 2.533 3.50E-02 Cytoplasm Enzyme
APOA2 Apolipoprotein A-II 2.389 7.94E-06 Extracellular space Transporter
ITGB2 Integrin, beta 2 (complement component 3 receptor 3 and 4 subunit) 2.253 3.60E-04 Plasma membrane Transmembrane receptor
PON1 Paraoxonase 1 2.232 1.48E-02 Extracellular space Phosphatase
PLA2G16 Phospholipase A2, group XVI 2.21 9.76E-04 Nucleus Enzyme
MSR1 Macrophage scavenger receptor 1 2.181 2.17E-02 Plasma membrane Transmembrane receptor
CXCR4 Chemokine (C-X-C motif) receptor 4 2.09 9.76E-03 Plasma membrane G-protein coupled receptor
PDGFA Platelet-derived growth factor alpha polypeptide −2.225 3.31E-04 Extracellular space Growth factor
PLA2G3 Phospholipase A2, group III −2.448 3.23E-03 Extracellular space Enzyme
APOA1 Apolipoprotein A-I −2.681 1.01E-02 Extracellular space Transporter
F3 Coagulation factor III (thromboplastin, tissue factor) −2.96 1.87E-04 Plasma membrane Transmembrane receptor
ALOX12B Arachidonate 12-lipoxygenase, 12R type −5.499 1.67E-02 Cytoplasm Enzyme
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1Fold change: Values indicate the relative gene expression. Positive values indicate higher expression in weaned than in suckling calves, and negative values indicate the opposite.

2FDR = false discovery rate.

Upstream Regulators

Based on the differentially increased or decreased expression of genes in the dataset, IPA revealed the upstream regulators that were activated or inhibited within each group. Tables 2 and 3 show the top 5 upstream regulators with P < 0.05 and z-scores, respectively. Tretinoin was predicted as the most significant regulator (Table 2); the P-value of 112 target molecules downstream of tretinoin also changed (Table 4). Seventy target molecules were upregulated during weaning, whereas 42 were downregulated (Table 4). Seven molecules were predicted by IPA as the most activated (z-score > 2.000), whereas “estrogen receptor” was inhibited (z-score < −2.000) (Table 3).

Table 2.

The 5 major upstream regulators generated by ingenuity pathway analysis (IPA)

Upstream regulator Fold change1 Predicted activation state Activation z-score2 P-value of overlap3 Mechanistic network4
Tretinoin 1.918 2.19E-16 301 (20)
TGFβ15 −1.073 1.089 1.15E-14 285 (17)
Phorbol myristate acetate 0.371 1.24E-14 253 (17)
PPARA6 1.364 Activated 2.155 3.17E-14 207 (16)
Lipopolysaccharide Activated 2.516 2.35E-13 283 (16)
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1Fold change: Values indicate the relative gene expression. Positive values indicate higher expression in weaned than in suckling calves, and negative values indicate the opposite.

2 z-Score: Values indicate a statistically significant pattern match between up- and down-regulation patterns.

3 P-value of overlap: Values indicate a statistically significant enrichment of the network-regulated genes in the database.

4Mechanistic network: The number of molecules that are downstream of the regulators and the number of regulators involved in that particular network in parentheses.

5TGFβ1: tumor growth factor beta-1.

6PPARA: Peroxisome proliferator-activated receptor alpha.

Table 3.

Upstream regulators activated (z-score > 2.00) and inhibited (z-score < -2.00) in the rumen of Japanese Black cattle during weaning

Upstream regulator Molecule type P-value of overlap1 Predicted activation state Activation z-score2
IgG Complex 1.38E-09 Activated 3.039
Lipopolysaccharide Chemical drug 2.35E-13 Activated 2.516
Alitretinoin Chemical drug 7.57E-06 Activated 2.241
PPARδ3 Ligand-dependent nuclear receptor 3.40E-07 Activated 2.232
PPARα4 Ligand-dependent nuclear receptor 3.17E-14 Activated 2.155
Pirinixic acid Chemical toxicant 2.34E-08 Activated 2.075
TNF5 Cytokine 6.08E-12 Activated 2.007
Estrogen receptor Group 1.97E-07 Inhibited −2.232
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1P-value of overlap: Values indicate a statistically significant encrichment of the network-regulated genes in the database.

2 z-Score: Values indicate a statistically significant match between up- and down-regulation patterns.

3PPARδ = peroxisome proliferator-activated receptor delta.

4PPARα = peroxisome proliferator-activated receptor alpha.

5TNF = tumor necrosis factor.

Table 4.

Genes regulated by tretinoin in rumen papillae tissue

Symbol Entrez gene name Fold change1 FDR2 Location Type(s)
SFTPC Surfactant protein C 15.731 6.95E-05 Extracellular space Other
CDKN2A Cyclin-dependent kinase inhibitor 2A 14.833 3.44E-04 Nucleus Transcription regulator
MSLN Mesothelin 14.337 5.37E-03 Extracellular space Other
CYP4F2 Cytochrome P450, family 4, subfamily F, polypeptide 2 14.255 5.63E-17 Cytoplasm Enzyme
NEU4 Sialidase 4 7.214 1.56E-03 Cytoplasm Enzyme
SLC27A2 Solute carrier family 27 (fatty acid transporter), member 2 7.161 2.84E-15 Cytoplasm Transporter
SIX1 SIX homeobox 1 6.675 1.69E-04 Nucleus Transcription regulator
TNC Tenascin C 6.034 8.28E-04 Extracellular space Other
CES1 Carboxylesterase 1 5.812 3.44E-04 Cytoplasm Enzyme
CYP1A1 Cytochrome P450, family 1, subfamily A, polypeptide 1 5.111 4.60E-03 Cytoplasm Enzyme
SLA Src-like-adaptor 3.589 9.81E-05 Plasma membrane Other
AREG Amphiregulin 3.566 1.95E-03 Extracellular space Growth factor
A2M α-2-macroglobulin 3.543 5.08E-03 Extracellular space Transporter
DUSP4 Dual specificity phosphatase 4 3.494 4.82E-03 Nucleus Phosphatase
EBI3 Epstein-Barr virus induced 3 3.48 6.85E-04 Extracellular space Cytokine
BMP6 Bone morphogenetic protein 6 3.453 6.37E-05 Extracellular space Growth factor
ALDH1A2 Aldehyde dehydrogenase 1 family, member A2 3.445 7.74E-03 Cytoplasm Enzyme
CCR1 Chemokine (C-C motif) receptor 1 3.425 1.12E-03 Plasma membrane G-protein coupled receptor
ALDH1A3 Aldehyde dehydrogenase 1 family, member A3 3.274 2.77E-03 Cytoplasm Enzyme
PLEK Pleckstrin 3.273 1.37E-02 Cytoplasm Other
ALPL Alkaline phosphatase, liver/bone/kidney 3.185 8.35E-05 Plasma membrane Phosphatase
CCR5 Chemokine (C-C motif) receptor 5 (gene/pseudogene) 3.121 7.27E-03 Plasma membrane G-protein coupled receptor
CTGF Connective tissue growth factor 3.116 1.03E-02 Extracellular space Growth factor
TLR5 Toll-like receptor 5 3.1 2.96E-03 Plasma membrane Transmembrane receptor
PTPN22 Protein tyrosine phosphatase, non-receptor type 22 (lymphoid) 2.883 1.53E-02 Cytoplasm Phosphatase
THBS1 Thrombospondin 1 2.851 1.03E-02 Extracellular space Other
NOV Nephroblastoma overexpressed 2.818 4.67E-02 Extracellular space Growth factor
ANPEP Alanyl (membrane) aminopeptidase 2.817 2.10E-02 Plasma membrane Peptidase
SCML1 Sex comb on midleg-like 1 (Drosophila) 2.814 5.60E-03 Nucleus Transcription regulator
SOAT1 Sterol O-acyltransferase 1 2.774 1.47E-07 Cytoplasm Enzyme
MMP28 Matrix metallopeptidase 28 2.76 1.13E-09 Extracellular space Peptidase
CTSL Cathepsin L 2.678 2.61E-02 Cytoplasm Peptidase
C1QA Complement component 1, q subcomponent, A chain 2.625 7.58E-03 Extracellular space Other
VSIG4 V-set and immunoglobulin domain containing 4 2.623 2.56E-02 Plasma membrane Other
AMICA1 Adhesion molecule, interacts with CXADR antigen 1 2.523 7.94E-06 Plasma membrane Other
CD52 CD52 molecule 2.522 5.02E-03 Plasma membrane Other
CD101 CD101 molecule 2.504 4.32E-03 Plasma membrane Other
FABP4 Fatty acid binding protein 4, adipocyte 2.496 3.53E-03 Cytoplasm Transporter
HMGCS2 3-Hydroxy-3-methylglutaryl-CoA synthase 2 (mitochondrial) 2.491 4.20E-05 Cytoplasm Enzyme
IGFBP5 Insulin-like growth factor binding protein 5 2.452 9.78E-04 Extracellular space Other
CD86 CD86 molecule 2.404 5.74E-03 Plasma membrane Transmembrane receptor
RBP2 Retinol binding protein 2, cellular 2.401 2.18E-03 Cytoplasm Transporter
APOA2 Apolipoprotein A-II 2.389 7.94E-06 Extracellular space Transporter
SEMA7A Semaphorin 7A, GPI membrane anchor (John Milton Hagen blood group) 2.374 1.44E-02 Plasma membrane Transmembrane receptor
BAMBI BMP and activin membrane-bound inhibitor 2.374 2.89E-03 Plasma membrane Other
GGT1 γ-Glutamyltransferase 1 2.365 2.67E-02 Plasma membrane Enzyme
POMC Proopiomelanocortin 2.343 1.19E-04 Extracellular space Other
CD68 CD68 molecule 2.337 4.21E-03 Plasma membrane Other
CD38 CD38 molecule 2.332 3.81E-02 Plasma membrane Enzyme
SLAMF7 SLAM family member 7 2.316 2.30E-02 Plasma membrane Other
CYP4F3 Cytochrome P450, family 4, subfamily F, polypeptide 3 2.302 1.12E-03 Cytoplasm Enzyme
ECI2 Enoyl-CoA delta isomerase 2 2.289 2.31E-05 Cytoplasm Enzyme
TYROBP TYRO protein tyrosine kinase binding protein 2.288 2.73E-03 Plasma membrane Transmembrane receptor
RGS5 Regulator of G-protein signaling 5 2.276 4.61E-02 Plasma membrane Other
ITGB2 Integrin, β 2 (complement component 3 receptor 3 and 4 subunit) 2.253 3.60E-04 Plasma membrane Transmembrane receptor
ITGAM Integrin, α M (complement component 3 receptor 3 subunit) 2.245 2.53E-02 Plasma membrane Transmembrane receptor
MGST3 Microsomal glutathione S-transferase 3 2.237 2.79E-05 Cytoplasm Enzyme
BNIP3L BCL2/adenovirus E1B 19kDa interacting protein 3-like 2.231 2.39E-06 Cytoplasm Other
HLA-DMB Major histocompatibility complex, class II, DM beta 2.207 1.58E-04 Plasma membrane Transmembrane receptor
FOLR2 Folate receptor 2 (fetal) 2.206 1.12E-02 Plasma membrane Transporter
MFNG MFNG O-fucosylpeptide 3-beta-N-acetylglucosaminyltransferase 2.177 1.38E-02 Cytoplasm Enzyme
SPI1 Spi-1 proto-oncogene 2.172 4.23E-03 Nucleus Transcription regulator
IKZF1 IKAROS family zinc finger 1 (Ikaros) 2.165 8.46E-03 Nucleus Transcription regulator
CFP Complement factor properdin 2.165 7.82E-03 Extracellular space Other
CXCR4 Chemokine (C-X-C motif) receptor 4 2.09 9.76E-03 Plasma membrane G-protein coupled receptor
CIDEA Cell death-inducing DFFA-like effector a 2.085 3.59E-02 Cytoplasm Other
RPL6 Ribosomal protein L6 2.055 1.27E-02 Cytoplasm Other
COL4A1 Collagen, type IV, alpha 1 2.024 1.40E-03 Extracellular space Other
TNFRSF1B Tumor necrosis factor receptor superfamily, member 1B 2.009 3.27E-04 Plasma membrane Transmembrane receptor
MAOB Monoamine oxidase B 2.002 7.89E-03 Cytoplasm Enzyme
KLF9 Kruppel-like factor 9 −2.011 1.35E-04 Nucleus Transcription regulator
BTC betacellulin −2.042 2.68E-02 Extracellular space Growth factor
MYBL2 v-myb avian myeloblastosis viral oncogene homolog- like 2 −2.109 2.85E-02 Nucleus Transcription regulator
TSC22D3 TSC22 domain family, member 3 −2.116 1.31E-04 Nucleus Transcription regulator
SOX6 SRY (sex determining region Y)-box 6 −2.129 2.14E-02 Nucleus Transcription regulator
DLL1 δ-Like 1 (Drosophila) −2.154 1.79E-03 Plasma membrane Enzyme
KRT15 Keratin 15 −2.166 1.11E-03 Cytoplasm Other
HES1 Hes family bHLH transcription factor 1 −2.169 6.79E-03 Nucleus Transcription regulator
CEACAM1 Carcinoembryonic antigen-related cell adhesion molecule 1 (biliary glycoprotein) −2.172 1.12E-02 Plasma membrane Other
KIF23 Kinesin family member 23 −2.181 2.57E-03 Cytoplasm Other
HOXD4 Homeobox D4 −2.212 1.81E-02 Nucleus Transcription regulator
HEY1 Hes-related family bHLH transcription factor with YRPW motif 1 −2.22 1.12E-02 Nucleus Transcription regulator
DUSP1 Dual specificity phosphatase 1 −2.259 3.10E-02 Nucleus Phosphatase
MYB v-myb avian myeloblastosis viral oncogene homolog −2.285 1.84E-02 Nucleus Transcription regulator
PTCH1 Patched 1 −2.319 3.84E-03 Plasma membrane Transmembrane receptor
IGFBP3 Insulin-like growth factor binding protein 3 −2.437 7.34E-03 Extracellular space Other
IGF2 Insulin-like growth factor 2 −2.472 3.57E-05 Extracellular space Growth factor
FGF2 Fibroblast growth factor 2 (basic) −2.476 2.82E-02 Extracellular space Growth factor
COL4A5 Collagen, type IV, alpha 5 −2.481 4.70E-03 Extracellular space Other
ITGA2 Integrin, alpha 2 (CD49B, alpha 2 subunit of VLA-2 receptor) −2.507 6.26E-05 Plasma membrane Transmembrane receptor
GJB5 Gap junction protein, beta 5, 31.1kDa −2.615 7.49E-03 Plasma membrane Transporter
IGFBP2 Insulin-like growth factor binding protein 2, 36kDa −2.711 1.65E-03 Extracellular space Other
IGFBP6 Insulin-like growth factor binding protein 6 −2.797 1.94E-03 Extracellular space Other
STC1 Stanniocalcin 1 −2.923 5.90E-03 Extracellular space Kinase
F3 Coagulation factor III (thromboplastin, tissue factor) −2.96 1.87E-04 Plasma membrane Transmembrane receptor
HS3ST1 Heparan sulfate (glucosamine) 3-O-sulfotransferase 1 −3.044 6.26E-05 Cytoplasm Enzyme
RNASE1 Ribonuclease, RNase A family, 1 (pancreatic) −3.056 2.31E-02 Extracellular space Enzyme
GATA6 GATA binding protein 6 −3.173 1.12E-02 Nucleus Transcription regulator
TERT Telomerase reverse transcriptase −3.239 3.14E-03 Nucleus Enzyme
GHR Growth hormone receptor −3.268 2.20E-05 Plasma membrane Transmembrane receptor
CHL1 Cell adhesion molecule L1-like −3.721 1.88E-02 Plasma membrane Other
SYCP3 Synaptonemal complex protein 3 −4.417 2.38E-05 Nucleus Other
SLC12A2 Solute carrier family 12 (sodium/potassium/chloride transporter), member 2 −4.847 3.85E-07 Plasma membrane Transporter
CFTR Cystic fibrosis transmembrane conductance regulator (ATP-binding cassette sub-family C, member 7) −4.953 1.01E-06 Plasma membrane Ion channel
OAS2 2ʹ-5ʹ-Oligoadenylate synthetase 2, 69/71kDa −5.376 7.18E-05 Cytoplasm Enzyme
BMPR1B Bone morphogenetic protein receptor, type IB −6.669 2.95E-03 Plasma membrane Kinase
PITX2 Paired-like homeodomain 2 −7.073 3.43E-02 Nucleus Transcription regulator
RXRG Retinoid X receptor, gamma −7.723 2.15E-02 Nucleus Ligand-dependent nuclear receptor
NTRK2 Neurotrophic tyrosine kinase, receptor, type 2 −8.077 1.09E-09 Plasma membrane Kinase
HOXB9 Homeobox B9 −8.378 4.76E-02 Nucleus Transcription regulator
DSG1 Desmoglein 1 −9.067 3.88E-09 Plasma membrane Other
EYA2 EYA transcriptional coactivator and phosphatase 2 −19.365 2.07E-05 Nucleus Phosphatase
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1Fold change: Values indicate the relative gene expression. Positive values indicate higher expression in weaned than in suckling calves, and negative values indicate the opposite.

2FDR = false discovery rate.

DISCUSSION

This study comprises the first application of RNA-seq to investigate the transcriptional changes and to predict the genes underlying the physiological and morphological modifications accompanying the transition from suckling to weaning in the rumen papillae of Japanese Black calves. In our previous study, HMGCS2, AKR1C1, and FABP3 were identified as candidate up-regulated genes in the rumen epithelium after weaning and growth (Kato et al., 2015). However, based on RNA-seq analysis, only the expression of HMGCS2 increased in weaned calves compared with suckling calves. These results reflected the limited dataset in the EST library in silico. However, the present results from RNA-seq analysis revealed several possible pathways and upregulators by analyzing global expression profiles during the weaning, growth, and development of rumen papillae.

The IPA data used in the present study were based on human, rat, and mouse and therefore had limitations for bovine pathway analysis. However, analysis revealed that 7 pathways significantly changed (FDR < 0.05) from suckling to weaned calves, especially “Atherosclerosis signaling.” Atherosclerosis is a subsequent, nonadaptive response of blood vessels to damage, induced by chronic inflammation. So far, there are no direct evidences of a relationship between rumen epithelial cells and atherosclerosis-related genes. The main factors regulating atherosclerosis are thought to be high-cholesterol levels (in particular low-density lipoprotein [LDL] cholesterol), hypertension, and blood fat (Levine et al., 1995; Glasser et al., 1996). During the atherogenesis, circulating monocytes are recruited and differentiated, and tissue macrophages capture cholesterol and oxidize LDL in order to form lipid-foam cells (Moreno and Mitjavila, 2003). Intraruminal VFA are thought to be the substrate of cholesterol, and the in vivo synthesis of cholesterol may become active by increasing VFA levels through feeding concentrate or high-grain diets (Sakata and Tamate, 1978). Holstein cattle fed grain-based feed presented changes in the expression level of genes related to cholesterol synthesis and homeostasis, and the synthesis of cholesterol was regulated via intracellular sterol regulatory element-binding protein (SREBP) (Steele et al., 2011). In the present study, 12 of the 17 DEGs in the atherosclerosis pathway were upregulated during weaning, whereas 5 genes were downregulated (Table 1). In monogastric animals, all these genes, except APOA1, may act as regulators or initiators of atherosclerosis (Miller-Kasprzak et al., 2004; Takahashi et al., 2005; Sato et al., 2008; Meisel et al., 2011). Thus, cholesterol synthesis might be promoted by grain-based feeds during weaning, and atherosclerosis might advance. Decreasing the expression of the genes related to cholesterol synthesis may help relieve the inflammation caused by atherosclerosis, at least partly. This suggests that cholesterol homeostasis and inflammation might have been activated in the rumen epithelium during weaning, by feeding starter and roughage.

Among the upstream regulators indicated by IPA, tretinoin was predicted as the most active molecule in the rumen papillae of Japanese Black cattle during weaning (P = 2.19E-16; Table 2). However, tretinoin was not yet reported as an upregulating factor in the rumen epithelium. Other important factors controlling the differentiation of rumen epithelium at weaned are TGFB1 and PPARA (Connor et al., 2014). Tretinoin is also known as “All-trans retinoic acid (ATRA),” which is a derivative of vitamin A. Alitretionin, a form of vitamin A, is predicted to play a role on rumen development (Table 3). There are some reports that vitamin A or its derivatives are related to epithelium functioning. For example, vitamin A was related to the maintenance of lung epithelial cells in rat (Takahashi et al., 1993). In addition, vitamin A and its derivatives, including retinol, retinal, and retinoic acid, function as effective inhibitors of mammary epithelial cell proliferation in cattle, and it is possible that retinoid, an analogue of vitamin A, can regulate mammary growth and development (Purup et al., 2001). The expression of SLC26A3, downregulated in adenoma (Makela et al., 2002), is increased by ATRA in intestinal epithelial cells (Priyamvada et al., 2015). Only a few studies have reported the effects of vitamin A in rumen papillae. Although the effects of vitamin A differ according to gastrointestinal track sites, villus height in the ileum and jejunum was enhanced by the supplementation of vitamin A in newborn calves (Schottstedt et al., 2005). The present study suggests that tretinoin (probably also retinol or retinoic acid) might be an important factor mediating the development of the rumen epithelium during the transition period from suckling to weaned.

The IPA analysis also indicated that IgG, lipopolysaccharides (LPS), and tumor-necrosis factor-α (TNFα) are activated in the rumen papillae of weaned calves. These upstream regulators are involved in immune responses and inflammation. Because IgG is vital to provide adequate immunological protection and resistance to disease (Conneely et al., 2014), in rumen papillae it is needed to induce adequate immunity and protection against pathogenic organisms. Changes in LPS, which are produced from dead bacteria, are caused by the alteration of bacterial diversity during weaning. Grain-induced subacute ruminal acidosis and the increment of a grain-based diet in lactating dairy cows increased the free ruminal LPS (Gozho et al., 2007). The concentration of ruminal LPS increased in steers fed grain-based diets and caused a variety of metabolic and immunologic alterations in the host (Andersen et al., 1994; Gozho et al., 2005). Moreover, the mucosal epithelium becomes more permeable and susceptible to apoptosis by the presence and increment of endotoxins (Chin et al., 2006). In addition, TNFα may be produced in the rumen epithelium by increasing the LPS released from rumen microbes in weaned calves (Pfeffer et al., 1993; Pasparakis et al., 1996; Raabe et al., 1998). Because TNFα is paracrine and endocrine, it may only act on the inflammation of rumen epithelium after weaning. The presence of IgG, LPS, and TNFα in rumen papillae contributes to microbe-epithelium interactions that activate rumen-related immune responses.

The IPA analysis also revealed that PPARα, PPARδ, and pirinixic acid might activate the growth and proliferation of rumen papillae (Table 3). Both PPARα and PPARδ are nuclear-receptor stimulating genes involved in fatty acid intake and metabolism, ketogenesis, and epidermal proliferation (Schoonjans et al., 1996; Burdick et al., 2006; Takahashi et al., 2006; Badman et al., 2007; Laarman et al., 2012; Naeem et al., 2012; Connor et al., 2013; Benesch et al., 2014). These PPARs might be increased to adapt to fatty acid metabolism, ketogenesis, and development of rumen papillae in weaned calves. Both PPARα and PPARδ heterodimerize with retinoid X receptor (RXR) (Klemm et al., 2001). The FXR/RXR-, LXR/RXR-, and LPS/IL-1-mediated inhibition of the RXR function, and the VDR/RXR activation obtained in the canonical pathway analysis suggest the importance of RXR (Figure 1). Tretinoin was identified as the most important upregulator (Table 2), and alitretinoin (9-cis retinoic acid) has been identified as a ligand of RXR (Heyman et al., 1992), whereas pirinixic acid (Wy-14,643) is a ligand of PPARα (Schaefer et al., 2008). Because Wy-14,643 increased the gene expression of monocarboxylate transporters (MCT)1, but not the MCT4 of VFA, in cultured ovine rumen epithelial cells (Benesch et al., 2014), pirinixic acid and PPARα/δ activation of RXR by alitretinoin might be important to adapt to VFA absorption and, therefore, are related to the growth and development of the rumen epithelium during the weaning period. However, estrogen receptors were inhibited in rumen papilla of weaned calves. There are 2 types of estrogen receptors: estrogen receptor 1 (ESR1) and estrogen receptor 2 (ESR2). In the present study, the expression of ESR2, not ESR1, was lower in the rumen papillae of weaned calves, and this molecule is known to have an antiproliferative role in the epithelium of immature uterus (Weihua et al., 2000). Thus, ESR2 might be downregulated in the rumen papillae after weaning to block antiproliferative effects. The upstream regulators predicted in this study need to be further validated.

In conclusion, the RNA-seq analysis of the rumen papillae of suckling and weaned calves provided a comprehensive view of the relative abundance and differential expression of several protein-coding genes. This information provides a valuable resource for studying atherosclerosis signaling, as candidate networks were found, including the activation of PPAR/RXR, which act as upregulators of the proliferation and development of rumen papillae in the transition from suckling to weaning in Japanese Black calves.

SUPPLEMENTARY DATA

Supplementary data are available at Journal of Animal Science online.

Supplementary Table
Click here for additional data file. (94.3KB, xlsx)

This work was partly supported by JSPS KAKENHI (grant 15K14839) and the Cooperative Research Grant of the Genome Research for BioResource, NODAI Genome Research Center, Tokyo University of Agriculture. We are grateful to the staff of the Grassland Research Support Center, Institute of Livestock and Grassland Science, NARO, for animal supplies and management.

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