Search
Author
Title
Vol.
Issue
Year
1st Page

Journal of Animal Science - Article

 

 

This article in

  1. Vol. 87 No. 1, p. 119-130
     
    Received: Apr 02, 2008
    Published: December 5, 2014


    2 Corresponding author(s): yonghong.wang@csiro.au
 View
 Download
 Share

doi:10.2527/jas.2008-1082

Gene expression patterns during intramuscular fat development in cattle1

  1. Y. H. Wang*†2,
  2. N. I. Bower*†3,
  3. A. Reverter*†,
  4. S. H. Tan*†4,
  5. N. De Jager*‡,
  6. R. Wang*5,
  7. S. M. McWilliam*,
  8. L. M. Cafe†§,
  9. P. L. Greenwood†§ and
  10. S. A. Lehnert*†
  1. Commonwealth Scientific and Industrial Research Organisation (CSIRO) Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Rd., St. Lucia, Queensland 4067, Australia;
    Cooperative Research Centre (CRC) for Cattle and Beef Quality, Armidale, New South Wales, Australia;
    School of Biological and Chemical Sciences, University of Queensland, Queensland 4072, Australia; and
    Beef Industry Centre of Excellence, New South Wales Department of Primary Industries, JSF Barker Building, University of New England, Armidale, New South Wales 2351, Australia

Abstract

Deposition of intramuscular fat, or “marbling,” in beef cattle contributes significantly to meat quality variables, including juiciness, flavor, and tenderness. The accumulation of intramuscular fat is largely influenced by the genetic background of cattle, as well as their age and nutrition. To identify genes that can be used as early biomarkers for the prediction of marbling capacity, we studied the muscle transcriptome of 2 cattle crossbreeds with contrasting intramuscular fat content. The transcriptomes of marbling LM tissue of heifers from Wagyu × Hereford (W×H; n = 6) and Piedmontese × Hereford (P×H; n = 7) crosses were profiled by using a combination of complementary DNA microarray and quantitative reverse transcription-PCR. Five biopsies of LM were taken from each animal at approximately 3, 7, 12, 20, and 25 mo from birth. Tissue was also collected from the LM of each animal at slaughter (approximately 30 mo). Microarray experiments, conducted on the first 3 biopsies of 2 animals from each crossbreed, identified 97 differentially expressed genes. The gene expression results indicated that the LM transcriptome of animals with high marbling potential (W×H) could be reliably distinguished from less marbled animals (P×H) when the animals were as young as 7 mo of age. At this early age, one cannot reliably determine meaningful differences in intramuscular fat deposition. We observed greater expression of a set of adipogenesis- and lipogenesis-related genes in the LM of young W×H animals compared with their P×H contemporaries. In contrast, genes highly expressed in P×H animals were associated with mitochondrial oxidative activity. Further quantitative reverse transcription-PCR experiments revealed that the messenger RNA of 6 of the lipogenesis-related genes also peaked at the age of 20 to 25 mo in W×H animals. The messenger RNA expression of ADIPOQ, SCD, and THRSP was highly correlated with intramuscular fat content of an individual in W×H animals. Our study provides clear evidence of early molecular changes associated with marbling and also identifies specific time frames when intramuscular fat development in cattle muscle can be detected by using gene expression. This information could be used by animal scientists to design optimal nutrition for high marbling potential. In addition, the genes found to be highly expressed during development of marbling could be used to develop genetic markers or biomarkers to assist with beef production strategies.


INTRODUCTION

Intramuscular fat content, or “marbling,” of cattle muscle is an important component of traits that influence eating quality, such as meat tenderness, juiciness, and taste (Hovenier et al., 1993). The accumulation of intramuscular fat is associated with the genetic background, development, and nutrition of an animal. The potential for cellular development of adipocytes is believed to be fixed relatively early in life and to change thereafter in either the size or number of cells that occur in proportion to the initial cell number and lipogenic proteins (Kirkland and Dobson, 1997; Caserta et al., 2001; Pethick et al., 2004). The importance of early life on intramuscular fat development suggests that it may be possible to predict adult intramuscular fat content by using biochemical measurements on muscle tissue in early life (Pethick et al., 2007).

A gene expression study of LM from Wagyu compared with Holstein animals at 11 mo of age found significantly greater adipogenesis- and lipogenesis-related gene expression in Wagyu cattle (Wang et al., 2005). However, when gene expression in the LM of newborn Wagyu × Hereford (W×H) calves was compared with the LM of newborn Piedmontese × Hereford (P×H), very few of the genes associated with adipogenesis were found to be significantly elevated (Lehnert et al., 2007). This suggests that the onset of marbling in animals occurs between birth and the early postweaning phase. However, the exact timing and development of marbling in cattle with a genetic disposition for this trait are still unknown.

To further address these issues, this study used a combination of microarray and quantitative reverse transcription-PCR (qRT-PCR) to measure the transcriptome of LM tissue of W×H and P×H cattle with contrasting amounts of intramuscular fat development at 6 consecutive time points between birth and 30 mo of age. This study demonstrated that the molecular changes associated with the processes of adipogenesis and lipogenesis set the 2 crossbreeds apart as early as 7 mo of age.

MATERIALS AND METHODS

Use of animals and the procedures performed in this study were approved by the North Coast Animal Care and Ethics Committee.

Animals and RNA Samples

Thirteen female progeny of 5 Wagyu (W; n = 6 progeny) sires and 5 Piedmontese (P; n = 7 progeny) sires and Hereford (H) dams were weaned at 7 to 8 mo of age and fed on improved temperate perennial pastures until feedlot entry at approximately 26 mo of age (Table 1). The animals were a subset of those well-nourished animals from the studies published by Cafe et al. (2006) and Greenwood et al. (2006). Animals were slaughtered at approximately 30 mo, when BW reached approximately 600 kg. The intramuscular fat percentage (IMF%; determined by near-infrared spectrophotometry) was determined as described by Perry et al. (2001). Five consecutive biopsy samples (approximately 5 g) were taken from the midlumbar region of the LM under local anesthetic when animals were aged 3 (T3), 7 (T7; weaning), 12 (T12), 20 (T20), and 25 (T25; feedlot entry) mo. These muscle biopsies were taken from alternate sides of the body of the animal to avoid previously biopsied sites. At slaughter (T30), approximately 20 g of LM tissue from each animal was also collected from the lumbar region of the LM, adjacent to the quartering site between the 12th and 13th ribs. Further details regarding the age and phenotype of experimental animals are listed in Table 1.

Total RNA was prepared by using Trizol reagent (Invitrogen, Carlsbad, CA), according to the instructions of the manufacturer. The RNA samples were treated with Turbo DNase I (Ambion, Austin TX), followed by a second DNase I treatment using RNAeasy Mini Kit columns (Qiagen, Valencia, CA). All purified total RNA samples were stored at −80°C for microarray experiments and qRT-PCR assays.

Microarray Experiment

The RNA samples from 3 consecutive biopsy samples (T3, T7, and T12) of 4 animals were selected for the microarray experiment. Two W×H (animal identification no. 179 and 235) and 2 P×H (animal identification no. 130 and 285) crossbreeds were included in the study. These animals, identified with an asterisk (*) in Table 1, were selected because their extreme intramuscular fat performance within their breed contemporaries was expected to maximize the chances of identifying differentially expressed genes.

Total RNA (2 μg) was used for antisense RNA amplification according to the instructions of the manufacturer (MessageAmp kit, Ambion). Fluorescent labeling was performed on 5 μg of antisense RNA by using the indirect labeling method (Lehnert et al., 2004).

Twenty-one spotted complementary DNA (cDNA) microarray hybridizations containing 9,600 probes from muscle and fat tissue-derived cattle cDNA libraries on CMT GAPS II (Corning Inc., Lowell, MA) slides (Lehnert et al., 2004) were used for this experiment (Figure 1). The experimental layout was designed to allow a focus on the developmental aspect of the study, but also to permit a breed comparison to be carried out. It comprised a series of 12 hybridizations arranged in a multiple dye-swap to address the within-time, across-breed comparisons. Eight further hybridizations were arranged in an alternate dye sampling design layout to address the within-breed, across-time comparisons. Finally, a self-hybridization was performed and incorporated into the analysis as a measure of the pure error component. Fluorescently labeled cDNA were mixed in 50 μL of hybridization solution and hybridized under standard conditions (Lehnert et al., 2004). Microarray slides were scanned with the GenePix 4000A scanner (Molecular Devices, Sunnyvale, CA) at a resolution of 10 μm. The photomultiplier tube voltage was adjusted so the histograms of green (Cy3) and red (Cy5) channels overlapped. The intensity values for the Cy3 and Cy5 channels for each spot were acquired by GenePix-Pro 3.0 (Molecular Devices).

Microarray Data Analysis

Gene expression intensity signals were subjected to a series of data acquisition criteria based on the signal-to-noise ratio and the mean-to-median correlation and as detailed in Tan et al. (2006). In brief, we used the following 2 editing criteria for data acquisition. First, we required that the signal-to-noise ratio (computed by dividing the background-corrected intensity by the SD of the background pixels) be greater than unity; second, we required that the correlation between the mean and the median signal intensities (computed by dividing the smaller of the mean or median by the larger) to be greater than 0.85. Tran et al. (2002) suggested not only that a correlation of 0.85 or greater retains more data than other methods, but also that the retained data are more accurate than traditional thresholds or common spot-flagging algorithms. However, these criteria were applied separately for the Cy5 and Cy3 intensity channels so that a different number of observations for each channel were obtained. These resulted in a total of 690,124 gene expression intensity readings (343,180 red and 346,944 green) on 8,129 genes (or probes or clones) that were background-corrected and base-2 log-transformed. The arithmetic mean and SD (in parentheses) for the red and green intensities were 11.10 (2.02) and 11.19 (1.97), respectively.

Data normalization was carried out by using a linear mixed ANOVA model and differentially expressed genes identified by model-based clustering via mixtures of distributions on the normalized expression of each gene at each breed and time point, as detailed in Reverter et al. (2004, 2005). In brief, the following linear mixed-effect model was fitted to the data:

where Yijktmn represents the nth background-adjusted, normalized base-2 log intensity from the mth gene (probe) at the tth treatment (animal age and breed sample) from the ith array, jth printing block, and kth dye channel; C represents a comparison group fixed effect (2,016 levels), defined as those intensity measurements from the same array slide, printing block, and dye channel; G represent the random gene (probe) effects with 8,129 levels; AG, DG, and TG are the random interaction effects of array × gene, dye × gene, and treatment × gene, respectively; and ε is the random error term.

Variance components for random effects were estimated by using REML, and differentially expressed genes were identified after processing the appropriate linear combination of the BLUP of TG via model-based clustering, addressing the age as well as the breed comparison contrasts of interest.

A total of 5 contrasts were considered in the identification of differentially expressed genes. These included the 2 within-breed, across-time contrasts and the 3 within-time, across-breed contrasts. For each contrast, a 2-component normal mixture model was fitted, and posterior probabilities of belonging to the nonnull component, used to identify differentially expressed genes for an estimated experiment-wise false discovery rate of <1%, were computed as described by McLachlan et al. (2006).

qRT-PCR Assays

To validate the microarray hybridization results, 11 genes were selected from the differentially expressed gene list for qRT-PCR assays. In addition, 5 adipogenesis-related genes were analyzed in the RNA samples by qRT-PCR. Primer sequences of these genes are listed in Table 2. The samples used in qRT-PCR assays were total RNA of all 6 time points from 13 animals (Table 1).

Single-stranded cDNA synthesis from 2 μg of total RNA, qRT-PCR assay, and data collection were performed as described previously (Wang et al., 2005). Sequence Detection Software (version 2.0; Applied Bio-systems, Foster City, CA) results were exported as tab-delimited text files and imported into Microsoft Excel (Microsoft Corp., Redmond, WA) and Q-gene (Muller et al., 2002) for further analysis. The PCR efficiency for each primer pair was calculated by using the Lin-RegPCR program (Ramakers et al., 2003). The average amplification efficiency for each gene across all samples was used in Q-gene for all qRT-PCR analyses.

Four commonly used internal reference housekeeping (HK) genes, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), β-actin (ACTB), 18S ribosomal RNA, and ribosomal protein large P0 (RPLP0) were tested for their suitability in this experiment; each gene was tested in a subset of samples (24 RNA samples from 2 W×H and 2 P×H at 6 time points) and analyzed by using GeNorm software (http://medgen31.ugent.be/jvdesomp/genorm/). The gene expression stability measure (M) is the average pair-wise variation for that gene with all other tested genes. The M values for all 4 HK genes were <0.5, which met the stability requirement to be an HK gene. The RPLP0 gene showed the lowest M value and was therefore selected as the internal HK gene for data normalization (Vandesompele et al., 2002).

Correlation and Regression Analyses

Importantly, qRT-PCR was performed on the 11 candidate genes not only to validate the differential expression observed in the microarray experiment, but also to evaluate the extent to which the expression of each gene was related to the intramuscular fat performance of the 13 cattle at each of the 6 time points. To this end, correlation analyses were performed to ascertain whether the expression of any of the individual genes was significantly related to the performance measures. Finally, the qRT-PCR mean normalized expression of individual genes was further analyzed by fitting an ANOVA model that contained the main effects of breed and age and the covariate (regression) effect of IMF% nested within the breed × age interaction. These analyses were performed by using the procedures CORR and GLM (SAS Inst. Inc., Cary, NC).

RESULTS

Detection of Differentially Expressed Genes by Microarray

Ninety-seven genes, including 4 unannotated expression sequence tags, were identified as differentially expressed genes over 3 time points in the LM muscle of W×H compared with P×H (Table 3). They were classified into 9 categories according to their biological functions: adipogenesis and lipogenesis, energy metabolism, carbohydrate metabolism, oxidation, myogenesis and muscle development, extracellular structure, immune and stress responses, signaling, and transcription and translation. A further set of 31 differentially expressed genes were not associated with any of the above categories and were classified as “others.” Figure 2 shows the number of differentially expressed genes in each category in W×H and P×H. Genes highly expressed in W×H animals were in the categories of adipogenesis and lipogenesis, extracellular structure, and signaling, whereas genes highly expressed in P×H animals dominated the categories of energy metabolism and oxidation.

Microarray Data Validation by qRT-PCR Assays

Eleven differentially expressed genes from the microarray analysis were selected for qRT-PCR validation assays. Seven genes with likely roles in adipogenesis and lipogenesis and 4 genes coding for extracellular matrix components were chosen for validation by qRT-PCR. The assays were performed on biopsy samples of all 13 experimental animals at T3, T7, and T12. The variations between technical replicates were very small, whereas the variations between the biological replicates (animals) were large (data not shown). Overall, qRT-PCR expression profiles (as indicated by ratios of averaged expression in LM of W×H over P×H) for each selected gene closely mirrored those obtained from microarray assays (Table 4).

qRT-PCR Assays for 17 Selected Genes

Eleven differentially expressed genes (Table 2) from microarray analysis and an additional 6 adipogenesis- and lipogenesis-related genes (THRSP, FAS, LPL, CEBPB, PPARG, and SFRP5) were measured for their mRNA expression in all 13 animals and across all 6 time points. At T7, significant differences were detected between W×H and P×H in 10 out of 17 genes (Figure 3). These genes include 2 adipose differentiation-associated genes (CEBPB and PPARG), 3 genes involved with fatty acid synthesis and metabolism (ADIPOQ, FABP4, and FAS), one gene from the wingless signal transduction pathway (SFRP5), and 4 connective tissue structure genes (COL1A1, COL1A2, COL3A1, and FN1). In addition, several genes were significantly different between the 2 crossbreeds at T25 and T30. In general, the adipogenesis- and lipogenesis-related genes were preferentially expressed in W×H animals at T7 and T25.

The mRNA expression for CEBPB were relatively greater at early time points, whereas PPARG displayed a slightly different expression profile, with a peak of expression occurring at T25 and T30 for W×H animals. This expression peak was not observed in P×H animals.

The WNT10B mRNA began with greater expression in P×H animals at T3 and reached its peak at T25 (Figure 3). In contrast, SFRP5 showed decreased expression in both breeds until T30, when SFRP5 reached its peak expression in W×H animals only.

Coordinated gene expression changes were observed for 4 connective tissue-related genes, COL1A1, COL1A2, COL3A1, and FN1. The mRNA abundance was generally greater in W×H animals, for which peaks of expression occurred at T7 and T25. The expression profiles closely mirrored those of the lipid metabolism genes (Figure 3).

Correlation Between mRNA of Adipogenic- and Lipogenic-Related Genes and Intramuscular Fat Content

Strong positive correlations were observed between mRNA expression of several adipogenic- and lipogenic-related genes and IMF% in W×H animals (Table 5). The ADIPOQ, SCD, THRSP, and FAS genes showed particularly strong correlations with IMF% at both T20 and T25. In contrast, the correlations between gene expression and IMF% in P×H animals were not as strong as in W×H animals, except at T3, when strong correlations were seen for SCD and FAS. Figure 4 illustrates the correlation, at T20 and T25, between ADIPOQ mRNA expression and IMF%, with R2 = 0.94 and 0.85 in W×H animals compared with R2 = 0.09 and 0.01 in P×H animals. The ANOVA model for ADIPOQ containing the main effects of breed and age and the covariate (regression) effect of IMF% nested within the breed × age interaction explained 55.7% of the variation in ADIPO. Importantly, the only regression coefficients of ADIPOQ on IMF% found to be significantly different from zero (P < 0.001) were for the W×H cross at the later ages of T20 (with regression estimated at 0.019 ± 0.006), T25 (estimated at 0.018 ± 0.006), and T30 (estimated at 0.027 ± 0.006). No strong correlations were observed between gene expression of adipogenesis- and lipogenesis-related genes and rump fat in both W×H and P×H animals (data not shown).

DISCUSSION

Experimental Design and Analysis Considerations

To maximize the chances of identifying differentially expressed genes in the microarray component of this study, the 2 cattle with the most extreme performance, in terms of intramuscular fat deposition, within each sire breed group were selected. In the qRT-PCR validation of the study, RNA samples from all 13 cattle and across all 6 time points were used to obtain an unbiased estimate of the expression of candidate genes. To allow us to distinguish expression changes within and across sire genotype, sire breed was fitted in the statistical models for the analysis of both the microarray and the qRT-PCR data. Statistical inference was performed at the level of both between and within breeds. The resulting normalized mean expression of each gene within each breed was used for building the between-breed contrast W vs. P in the differential expression analyses for microarray and RT-PCR, respectively, as well as for assessing the strength of the relationship between the expression of a gene and intramuscular fat deposition within breed.

Early Development of Intramuscular Fat in W×H Animals

Intramuscular fat deposition is associated with genetic background, as well as the development and nutrition of an animal (Pethick et al., 2004). Wagyu animals, such as Japanese Black, are genetically predisposed to deposit intramuscular fat. Previous microarray studies indicated a time frame during which the development of adipogenesis and lipogenesis may occur in W animals (Wang et al., 2005; Lehnert et al., 2007). In the present study, gene expression profiling of LM from W×H and P×H crossbreeds was carried out retrospectively, in biopsies that had been collected before substantial intramuscular fat deposition took place. Examination of the amounts of gene transcripts at these early stages provides an opportunity to observe the window of time during muscle development when transcriptional activation occurs.

One transcription factor involved in the preadipocyte differentiation process, CEBPB, was seen as differentially expressed between the 2 crossbreeds as early as T7. This may indicate that the predisposition of the animal to develop fat and activate one of the core early transcription factors is well developed by that time for W×H animals. It is interesting to note, however, that CEBPB and PPARG showed opposite expression patterns in W×H animals: CEBPB was expressed at relatively greater abundance at earlier time points, whereas PPARG expression increased only at the last 2 time points, during the accumulation of fat deposits. This gene expression pattern is consistent with the established model of adipogenesis, in which CEBPB is required for subsequent induction of PPARG expression (Wu et al., 1995; Clarke et al., 1997). Although PPARG was found to be elevated only in the later time points, the mRNA expression of several adipogenic- and lipogenic-related genes, ADIPOQ, FABP4, and FAS, was markedly elevated in W×H animals at T7, when animals were close to weaning. This early separation between the 2 cross-breeds provides molecular evidence for the early cellular development of adipocytes in animals with marbling potential. This evidence points to a time frame during which early invention is possible to maximize intramuscular fat in later life.

Peak Expression for Lipogenic Genes in W×H Animals at T25

A peak of expression for many of the adipogenesis- and lipogenesis-associated genes was detected by using qRT-PCR assays at T25, before the animals entered the feedlot. This expression pattern confirms findings from a previous study (Wang et al., 2005). It is a commonly held view that intramuscular fat is an adipose tissue depot that is laid down only in the mature animal (Pethick et al., 2004). Our data support the contention that at 25 mo of age, W×H animals had reached this stage of maturity and were depositing or beginning to deposit substantial amounts of intramuscular fat. In contrast, by 30 mo, P×H animals were not depositing substantial amounts of intramuscular fat. However, our data were unable to exclude the possibility that intramuscular fat accumulation in the P×H crossbreed may have commenced at a later stage in the life of the animal.

The mRNA expression of adipogenic- and lipogenic-related genes in LM at T25 had strong positive correlations with IMF% measured after slaughter. This evidence indicated that a snapshot of mRNA abundance at T25 could be used to predict the development of intramuscular fat during the subsequent feedlot phase. Hence, it offers a potential application of using gene expression data to predict the marbling trait.

Expression of Mitochondrial Genes

There is evidence of coordinate gene expression differences between W×H and P×H animals. Mitochondrial genes, such as MTCYB, COX7A2, MTND4, and MTND4L, are more highly expressed in P×H animals. These genes are the subunits of the respiratory complexes that are involved in mitochondrial oxidative phosphorylation. Because mitochondrial oxidative phosphorylation is involved in the generation of energy, such as ATP, these findings indicate that compared with the W×H, the P×H animals may use more energy to support more rapid growth of muscle during the period to weaning, when fractional rates of muscle growth are increased, as we have discussed previously (Lehnert et al., 2007). In this regard, it has also been shown that animals sired by increased muscle growth genotypes have greater oxidative enzyme activity in muscles, including LM, than those sired by decreased muscle growth genotypes during early postnatal life, despite a shift toward more glycolytic myofiber types in the offspring of sire genotypes with greater muscle growth (Gardner et al., 2007; Greenwood et al., 2007; Warner et al., 2007). Animals with an increased basal energy requirement may also be expected to store less triacylglycerol in adipose tissue.

Expression of Connective Tissue Structure Genes

It is interesting to note that, in the highly marbling W×H animals, the expression of several extracellular protein genes loosely mirrored that of adipogenic-related genes. Four connective tissue protein genes (COL1A1, COL1A2, CIL3A1, and FN1) and 2 genes that influence the synthesis and interaction with the extracellular matrix (SPARC and FMOD) showed this pattern. Intramuscular fat has been shown to develop within the perimysium connective tissue alongside myofibers (Moody and Cassens, 1968). Perimysium is a major connective tissue in muscle and contains collagen fibers, as well as other minor components. This perhaps suggests that the expansion of the extracellular matrix may be a prerequisite for intramuscular fat development. This conclusion is further strengthened by previous reports showing that intramuscular connective tissue undergoes structural changes during the fattening of Japanese Black cattle (Nishimura et al., 1999) and that type XII collagen isoforms are expressed during bovine adipogenesis (Tahara et al., 2004).

Wingless Signaling Pathway and Marbling Development

In a previous study (Tan et al., 2006), we showed that the wingless signaling pathway may play a role during bovine adipogenesis. The WNT10B gene is a molecular switch that governs 3T3-L1 adipogenesis and maintains preadipocytes in an undifferentiated state. Interruption of WNT10B expression in preadipocyte cells will lead to adipogenic differentiation (Ross et al., 2000). When the expression pattern of WNT10B and the gene coding for its binding partner, SFRP5, are examined in LM samples, it becomes apparent that when the expression of WNT10B decreases, SFRP5 increases. These results strengthen the argument that adipogenesis and intramuscular fat deposition in cattle may be regulated in part by the wingless signaling pathway, and that tissue-specific manipulation of this pathway could potentially be used to increase intramuscular fat deposition.

In conclusion, we have provided molecular evidence of early intramuscular adipogenesis. The coordinate expression pattern of a set of adipogenesis- and lipogenesis-related genes and their strong positive correlation with intramuscular fat content at slaughter provide potential for the development of markers for predicting marbling. Gene expression profiling provides an effective tool to discover gene expression changes associated with production traits and to discover genes contributing to quantitative variation between breeds of farm animals.


View Full Table | Close Full ViewTable 1.

The identification (ID), genetic background, age (d) at each biopsy sampling time, and LM intramuscular fat percentage (IMF%) after slaughter for each experimental animal

 
58 P 1 H 96 234 375 634 797 928 674 6.32
112 P 1 H 85 223 364 623 786 917 542 4.25
130* P 2 H 81 219 360 619 782 913 722 3.43
201 P 3 H 67 205 346 605 768 899 614 6.05
224 P 1 H 61 199 340 599 762 893 634 5.39
273 P 4 H 47 185 326 585 748 880 708 8.16
285* P 5 H 44 182 323 582 745 877 712 3.42
Mean 69 207 348 607 770 901 658 5.29
SD 19 19 19 19 19 19 65.5 1.73
99 W 1 H 84 222 363 622 785 918 672 8.11
169 W 1 H 75 213 354 613 776 907 698 8.38
179* W 2 H 70 208 349 608 771 902 638 14.58
212 W 3 H 63 201 342 601 764 895 708 8.00
235* W 4 H 60 198 339 598 761 892 656 18.44
245 W 5 H 56 194 335 594 757 888 690 6.80
Mean 68 206 347 606 769 900 677 10.72
SD 10 10 10 10 10 11 26.7 4.68

View Full Table | Close Full ViewTable 2.

Primer sequences used in quantitative reverse transcription-PCR assays

 
Differentially expressed genes from microarray analysis
    ADIPOQ Adiponectin, C1Q and collagen domain containing tcacaatggggtctatgcag tgatgttcagaatcccctca
    FABP4 Adipocyte-type fatty acid binding protein cgtgggctttgctaccag tggttgattttccatcccag
    SCD Stearoyl-CoA desaturase ccagaggaggtactacaaacctg agccaggtgacgttgagc
    DLK Delta-like 1 homolog gcgtggtgaatggctcg ggctgcaggtcttgtcca
    ANKRD1 Ankyrin repeat domain 1 (cardiac muscle) gacagaacctgtggatgtgc acgattgccaaatgtccttc
    FN1 Fibronectin attgatgcaccatccaacct cctggttccagaccagtgat
    COL1A1 Collagen type I α I tggtgacaagggtgagacag gggagaccattgagtccatc
    COL1A2 Collagen type I α 2 ggtcgaagtggagagacagg aggttcacccacagatccag
    COL3A1 Collagen type 3 α I
    GAPDH Glyceraldehyde-3-phosphate dehydrogenase cctggagaaacctgccaagt agccgtattcattgtcatacca
    WNT10B Wingless-type MMTV integration site family, member 10B ctgtaaccatgacatggacttcg aggttttcagttaccacctgacg
Additional adipogenesis-related genes
    CEBPB CCAAT/enhancer binding protein β cgacagttgctccaccttct ctcgcaggtcaagagcaag
    PPARG Peroxisome proliferator-activated receptor gamma aaagcgtcagggttccacta cccaaacctgatggcattat
    LPL Lipoprotein lipase taccctgcctgaagtttccac cccagtttcagccagactttc
    FAS Fatty acid synthesis ggtgtggacatggtgacaga acaatggcctcgtaggtgac
    THRSP Thyroid hormone responsive SPOT14 aagaggctgaggaggagagc ggactgccttctatcatgtgg
    SFRP5 Secreted frizzled-related protein 5 cctccagtgaccaagatctgtg ttcttcatgtgcagcacgag
Housekeeping gene
    RPLP0 Acetic ribosomal protein large P0 caaccctgaagtgcttgacat aggcagatggatcagcca

View Full Table | Close Full ViewTable 3.

Microarray identification of genes differentially expressed in LM of Wagyu × Hereford (W×H) compared with Piedmontese × Hereford (P×H) animals in at least 1 time point

 
Genes related to adipogenesis and lipogenesis
    CF613470 32 FABP4 Fatty acid-binding protein, adipocyte 1.20 2.33 1.53
    CO729188 23 SCD Stearoyl-CoA desaturase (delta-9-desaturase) 1.11 2.16 0.78
    CO729221 8 AdipQ Adipocyte, C1Q and collagen domain containing 1.09 2.36 1.21
    CF613982 2 CLU Clusterin 0.94 1.28 0.92
    BF773913 1 ACSM1 Acyl-CoA synthetase medium-chain family member 1 0.87 1.32 0.92
    DW521722 1 APOE Apolipoprotein E 0.59 0.53 0.50
    CF615136 1 SCARF1 Scavenger receptor class F, member 1 isoform 1 precursor 0.55 1.64 1.10
Genes related to energy metabolism
    CF615488 1 PPP1R3C Protein phosphatase 1, regulatory (inhibitor) subunit 3C 2.46 0.68 0.89
    DW521731 2 ATP5J ATP synthase F0 subunit 6 1.85 0.59 0.38
    CF614094 1 PDK4 Pyruvate dehydrogenase kinase, isoenzyme 4 1.06 2.71 1.96
    CF615087 2 PFKFB3 6-Phosphofructo-2-kinase/fructose-2, 6-biphosphatase 3 0.87 2.72 1.31
    CF614549 1 CKM Creatine kinase, muscle 0.83 0.66 0.57
Gene related to carbohydrate metabolism
    GAPDH_5′ 2 GAPDH Glyceraldehyde-3-phosphate dehydrogenase 0.48 0.87 1.12
    CF614691 1 ALDOA Aldolase A, fructose-bisphosphate 0.41 0.52 0.59
Genes related to oxidative metabolism
    CF615544 1 UQCRB ubiquinol-cytochrome c reductase binding protein 1.73 0.80 1.07
    CF613649 5 MTND3 NADH dehydrogenase subunit 3 1.32 0.81 0.76
    CF613892 4 MTCYB Cytochrome b 1.16 0.64 0.59
    DW521756 3 MTND5 mitochondrion NADH dehydrogenase subunit 5 0.75 0.82 0.94
    CF615553 3 MTND4 NADH dehydrogenase subunit 4 0.67 0.81 0.61
    CF615047 35 MTCO1 Mitochondrially encoded cytochrome c oxidase I 0.64 0.93 0.85
    DW521765 4 MTND4L NADH dehydrogenase subunit 4L 0.57 0.80 0.57
    DW521773 1 COX7A2 Cytochrome c oxidase subunit VIIa polypeptide 2 0.53 0.72 0.61
    DW521845 1 LDHA LDH-A mRNA for lactate dehydrogenase-A isozyme 0.52 0.61 0.60
Genes related to myogenesis and muscle development
    CF614343 8 CSRP3 Cysteine and glycine-rich protein 3 (cardiac LIM protein) 2.05 0.89 1.37
    CF614523 8 CRYAB Crystallin, α B 1.83 1.07 1.29
    CF615135 1 TPM2 tropomyosin 2 (β) (TPM2), transcript variant 1 1.79 0.20 0.30
    CF614815 1 MYH1 Myosin, heavy polypeptide 1, skeletal muscle 0.74 0.97 0.62
    CF615306 8 ATP2A1 ATPase, Ca++ transporting, cardiac muscle, fast twitch 1 0.56 0.78 0.59
    CES014390 2 ACTB β-Actin_5′ 0.52 1.04 0.85
    CF614690 1 TNN12 Troponin I, skeletal, fast 0.42 0.93 0.63
    CF614924 1 ACTN3 Actinin, α 3 0.40 0.54 0.68
    CF614495 5 ACTN1 Actin, α 1, skeletal muscle 0.36 0.53 0.54
Genes related to extra cellular structure
    CO729170 4 FN1 Fibronectin 1 (FN1), transcript variant 1 1.30 2.04 1.76
    CF613798 12 COL3A1 Collagen, type III, α 1 1.17 1.32 1.77
    CF614144 2 MGP Matrix Gla protein 1.09 1.93 1.55
    CF613952 28 COL1A1 Collagen, type I, α 1 1.02 2.14 1.37
    DW521763 1 FMOD Fibromodulin 0.90 1.66 0.71
    CF613956 10 COL1A2 Collagen, type I, α 2 0.85 1.73 1.32
    DW521813 1 LAMA4 Laminin α-4 chain precursor 0.61 0.99 0.96
Genes related to immune and stress responses
    CF614108 5 HLA-A Major histocompatibility complex, class I, A precursor 1.60 1.35 1.36
    DW521819 1 EPC1 Enhancer of polycomb 1 1.39 1.16 1.73
    CF614214 4 HLA-B Major histocompatibility complex, class I, B 1.29 1.04 1.33
    CF615362 2 HLA-C Major histocompatibility complex, class I, C 1.26 1.23 1.45
    DW521838 1 PSMB5 Proteasome (prosome, macropain) subunit, β type 5 1.19 1.31 1.32
    DW521638 5 TXNIP Thioredoxin interacting protein 1.10 1.54 1.18
    DW521770 1 HLA-DQB1 Major histocompatibility complex, class II, DQ β 1 0.88 0.70 0.50
    DW521762 1 RTN4 Reticulon 4, transcript variant 3 0.84 0.60 0.49
    CES014034 1 CCL2 Chemokine (C-C motif) ligand 2 0.69 0.82 0.84
Genes related to signaling
    DW521754 1 ASB5 Ankyrin repeat and SOCS box-containing 5 2.75 1.25 0.92
    CF614403 6 ANKRD1 Ankyrin repeat domain 1 (cardiac muscle) 2.16 0.90 0.68
    CF614646 1 TRIM54 Tripartite motif-containing 54 (TRIM54), transcript variant 2 2.03 0.72 0.77
    BF707278 1 ADRB2 β-2 adrenergic receptor 1.72 1.03 0.80
    DW521766 1 SH3BP4 SH3-domain binding protein 4 1.46 1.99 1.47
    CF614111 5 IGFBP5 Insulin-like growth factor binding protein 5 1.31 0.81 0.59
    CF614035 2 SPARC Secreted protein, acidic, cysteine-rich (osteonectin) 1.21 1.41 1.27
    CF614138 1 IGFBP5 Insulin-like growth factor-binding protein 5 1.11 0.64 0.40
    DW521760 1 RGS2 Regulator of G-protein signaling 2, 24kDa 0.94 1.32 1.18
    BE683284 1 WNT10B Wingless type 10b (wnt10b) homolog 0.86 1.23 2.04
    AW289395 1 STAT1 Signal transducer and activator of transcription 1 0.43 1.08 0.82
Genes related to transcription and translation
    CO729196 1 HSPB1 Heat shock 27kDa protein 1 2.16 0.93 1.49
    CF613588 1 FOS v-fos FBJ murine osteosarcoma viral oncogene homolog 2.06 1.51 2.66
    DW521833 1 UBA52 Ubiquitin A-52 residue ribosomal protein fusion product 1 1.53 0.95 1.53
    DW521761 1 MEF2C Myocyte enhancer factor 2C 1.41 0.86 0.66
    CF613993 1 RPL14 Ribosomal protein L14 1.32 2.27 1.01
    CF615612 7 ATF4 Activating transcription factor 4 0.56 0.81 0.76
Others
    CF615310 4 HSPA1A Heat shock 70kDa protein 1A 2.33 0.94 1.23
    DW521842 1 SETBP1 SET binding protein 1 2.11 0.91 0.86
    CO729198 3 KBTBD5 Kelch repeat and BTB (POZ) domain containing 5 2.03 0.83 0.83
    DW521700 4 MUSTN1 Musculoskeletal, embryonic nuclear protein 1 1.97 1.12 1.26
    CO729185 1 HSPB8 Heat shock 22kDa protein 8 1.82 1.15 1.17
    BF606016 2 DLK Delta-like 1 homolog 1.77 1.23 0.90
    CO729222 1 MAP1A Microtubule-associated protein 1A 1.62 0.85 0.88
    DW521839 1 TOMM22 Translocase of outer mitochondrial membrane 22 homolog(yeast) 1.60 1.14 1.25
    DW521758 1 EST Similar to Schistosoma japonicum SJCHGC09300 protein 1.27 0.85 1.61
    DW521830 1 CSTB Cystatin B (stefin B) 1.01 1.49 0.70
    CF615380 1 DDIT4 DNA-damage-inducible transcript 4 0.97 0.91 1.74
    DW521843 1 SYNE2 Spectrin repeat containing, nuclear envelope 2 0.97 0.66 0.56
    CO729200 1 SQSTM1 Sequestosome 1 0.93 2.17 0.84
    DW521834 1 EST Bos taurus hypothetical protein LOC784639 0.85 1.46 0.90
    DW521768 1 LARP5 La ribonucleoprotein domain family, member 5 0.78 1.83 1.49
    DW521822 1 EST Bos taurus hypothetical protein LOC783730 0.78 1.08 1.66
    DW521764 1 PDZRN3 PDZ domain containing RING finger 3 0.73 0.69 0.70
    CF614142 3 MTRNR1 Mitochondrially encoded 12S RNA 0.72 0.46 1.31
    CF615327 1 GSTM3 Glutathione S-transferase M3 (brain) 0.69 0.51 0.53
    DW521769 1 FNTB Farnesyltransferase, CAAX box, β 0.68 0.79 0.49
    DW521846 1 UBC Polyubiquitin, transcript variant 27 0.67 0.61 0.59
    DW521759 2 FHL1 Four and a half LIM domains 1 0.58 1.01 0.94
    DW521831 1 tRNA-Pro Mitochondrion tRNA-Pro 0.57 0.62 0.62
    DW521836 1 CA3 Carbonic anhydrase III 0.55 0.72 0.66
    DW521757 1 MLF1 Myeloid leukemia factor 1 0.55 0.68 0.92
    CF614734 1 CCNG1 Cyclin G1 (CCNG1), transcript variant 1 0.51 0.69 0.50
    DW521837 1 EST Bos taurus hypothetical LOC518370 0.49 0.60 0.43
    DW521829 1 AHNAK Nucleoprotein isoform 1 0.44 0.61 0.66
    CF614846 1 C11orf39 Chromosome 11 open reading frame 39 0.26 0.53 0.63
    DW521840 1 H3F3A H3 histone, family 3A 0.26 0.33 0.16
    DW521835 1 CTDSP1 CTD (carboxy-terminal domain, RNA polymerase II, polypeptide A) small phosphatase 1 0.21 0.46 0.25

View Full Table | Close Full ViewTable 4.

Comparison of gene expression measurements by microarray and quantitative reverse transcription PCR (qRT-PCR) at T3, T7, and T121

 
ADIPOQ 1.09 0.98 2.36 3.69 1.21 0.74
FABP4 1.20 1.01 2.33 2.68 1.53 0.63
SCD 1.11 1.03 2.16 2.08 0.78 0.53
DLK 1.77 1.34 1.23 1.99 0.90 1.30
GAPDH 0.48 0.86 0.87 0.95 1.12 0.99
WNT10B 0.86 0.52 1.23 0.79 2.04 1.70
ANKRD1 2.16 1.44 0.90 0.61 0.68 0.89
FN1 1.30 0.69 2.04 1.87 1.76 1.68
COL1A1 1.02 1.47 2.14 1.73 1.37 1.76
COL1A2 0.85 0.89 1.73 1.42 1.32 0.94
COL3A1 1.17 1.60 1.32 1.34 1.77 1.64
Correlation4 0.511 0.511 0.807** 0.807** 0.634* 0.634*

View Full Table | Close Full ViewTable 5.

Correlations between gene expression and intramuscular fat percentage in LM samples at 6 time points1

 
ADIPOQ W×H −0.50 0.13 0.65 0.97*** 0.92** 0.66
P×H −0.06 0.44 0.10 0.30 0.11 −0.07
FABP4 W×H −0.29 −0.09 0.20 0.95 0.83* 0.63
P×H 0.04 −0.13 0.17 0.21 0.14 −0.57
SCD W×H −0.43 −0.03 −0.34 0.77 0.92** 0.54
P×H 0.84* −0.01 0.19 0.25 −0.01 0.26
THRSP W×H −0.17 0.08 −0.35 0.94** 0.10 0.22
P×H −0.26 0.46 −0.25 −0.07 0.59 −0.57
FAS W×H −0.73 0.23 −0.29 0.94** 0.83* 0.55
P×H 0.92** 0.60 0.35 0.34 0.18 0.71
LPL W×H −0.55 −0.20 −0.28 0.30 0.53 0.61
P×H 0.25 −0.30 0.03 0.25 −0.09 −0.36
Figure 1.
Figure 1.

Microarray experimental design of LM transcription profiles. The experiment contained 21 slides and compared the expression profile in muscle tissue between 2 crossbreeds: Wagyu × Hereford and Piedmontese × Hereford, with 2 animals from each crossbreed, at 3 time points. The direction of the arrows indicates the labeling with either red or green dyes.

 
Figure 2.
Figure 2.

A number of differentially expressed genes highly expressed in Wagyu × Hereford (W×H) animals (unfilled boxes) and highly expressed in Piedmontese × Hereford (P×H) animals (filled boxes) were classified into 10 categories according to their biological functions: (1) adipogenesis and lipogenesis; (2) energy metabolism; (3) carbohydrate metabolism; (4) oxidation; (5) myogenesis and muscle development; (6) extracellular structure; (7) immune and stress; (8) signaling; (9) transcription and translation; and (10) others. Biopsy time points are referred to as T3, T7, and T12, corresponding to 3, 7, and 12 mo of age.

 
Figure 3.
Figure 3.

Mean normalized expression (MNE) of 17 genes (identified in Table 2) in LM of Wagyu × Hereford (W×H; n = 6, solid line) and Piedmontese × Hereford (P×H; n = 7, dashed line) at 6 time points. The MNE expression values were established by quantitative reverse transcription-PCR assays normalized to ribosomal protein large P0 (RPLP0) expression measured at the same time. The statistical significance at any given time point between the 2 crossbreeds was analyzed by unpaired t-test (*P < 0.05; **P < 0.001; ***P < 0.0001).

 
Figure 4.
Figure 4.

Correlations between mean normalized expression (MNE) of adiponectin, C1Q, and collagen domain-containing (ADIPOQ) gene expression at (A) T20 (biopsy time point corresponding to 20 mo of age) and (B) T25 (biopsy time point corresponding to 25 mo of age) and intramuscular fat (IMF) percentage in LM tissue of Wagyu × Hereford (n = 6, solid line) and Piedmontese × Hereford (n = 7, dashed line).

 

 

References

Footnotes