Developmental Changes in Myofibers and Expression Profiles of Potential Regulatory Genes in Slow- and Fast- Growing Chickens

Jia Liu1, Zhen Wang1, Zifan Ning1, Ali Mujtaba Shah2,3, Qing Zhu1, Yan Wang1, Huadong Yin1, Zhichao Zhang1, Lu Zhang1, Yaofu Tian1, Diyan Li1, Gang Shu2,4, Lin Ye1 and Xiaoling Zhao1,*

1College of Animal Science and Technology, Sichuan Agricultural University, ,611130 Chengdu, China

2Department of Livestock Production, Shaheed Benazir Bhutto University of Veterinary and Animal Science, Sakrand 67210, Sindh, Pakistan

3Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu, Sichuan 611130, China

4Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural

University, ,611130 Chengdu, China

Jia Liu and Zhen Wang made equal contributions to this study.

ABSTRACT

There are weight and size differences in skeletal muscles of fast- (FG), and slow- growing (SG) chickens, however, the underlying molecular mechanisms responsible for the differences in post-hatch muscle development are unclear. Here, we report on the identification of several candidate genes that may modulate myofiber growth and thus explain some of the differences in the skeletal muscle phenotype of FG and SG chickens. We collected pectoralis major (PM) and gastrocnemius muscles (GM) on d 1, 7, 28, 49, and 70 post-hatch, and measured the weights of the muscles, diameter and, a density of myofibers, and the expression abundances of MyoD, MyoG, IGF-1, and Pax7. The body weight of FG was heavier than SG from d 7 to 70. Their muscle weights and myofiber diameters of FG were also greater than SG (P < 0.05). The expression of MyoG was affected by chicken population, age, and muscle-type. It was the heaviest in PM for FG on d 28, compared with other combinations. The expression of Pax7 mRNA paralleled changed in myofiber density, whereas the expression profiles of MyoG and MyoD were similar to the developmental changes in myofiber diameter. Overall, body weight and muscle expansion of SG chickens were less than FG chickens. MyoG was the possible gene controlling myofiber development as its expression abundances were associated with the muscle development profiles in the SG and FG chickens, respectively.

Article Information

Received 08 April 2019

Revised 29 June 2019

Accepted 09 July 2019

Available online 08 March 2021

(early access)

Published 10 December 2021

Authors’ Contribution

XZ designed the study. ZW, GS, LY and LZ raised the chickens and performed the experiments. QZ, YW, HZ, ZZ and DL helped in experimental work. JL analyzed the data and wrote the article. AMS, ZN and YT helped in preparation of manuscript.

Key words

Broiler, Myofiber development, Myoblast determining factors, Myogenin, Expression abundance

DOI: https://dx.doi.org/10.17582/journal.pjz/20190408030436

* Corresponding author: [email protected]

0030-9923/2022/0001-0295 $ 9.00/0

Copyright 2022 Zoological Society of Pakistan

INTRODUCTION

Development of skeletal muscle is an economically-important trait in poultry production. It is well known that the myofiber number in chickens is established before hatching. So, any increase in muscle weight post-hatching depends on the increase in length and diameter of the myofibers (Chen et al., 2007). Myofiber growth is affected by interactions of heredity, age, nutrition, exercise, type of management and environmental conditions (Hu et al., 2013; Michalczuk et al., 2016). In China, local meat-type chickens have a slower growth rate and smaller myofiber diameters than commercial strains (Sheng et al., 2013). Consumer acceptance of meat depends on its quality, which is influenced by a series of factors ranging from the physical and chemical to the histological properties and processing procedure of meat. Tenderness has been noted as the most important factor in consumer perception of quality of meat products. Papa (1988) had demonstrated that myofiber diameters influenced the tenderness of meat products (Papa and Fletcher, 1988). Studies have identified multiple genes that contribute to the growth and development of skeletal muscle fibers in mammals, such as myoblast determining factors (MyoD), myogenin (MyoG), insulin like growth factor 1 (IGF-1), and paired box 7 (Pax7) (Grochowska et al., 2017; Stupka et al., 2014; Wang et al., 2015). Their functions in the development of SG and FG chickens’ skeletal muscle are unclear. This experiment thus focused on the skeletal myofiber characteristics and gene expression profiles of potential regulatory factors in the slow- growing genetic line HS1 (SG) and fast-growing genetic line Cobb (FG). The HS1 is a Chinese dual-purpose chicken line selected for five generations by Sichuan Agricultural University in China. It originated from a local breed that grows slowly during the starter and grower periods and has good meat quality. Cobb is a typical commercial population that was successfully bred in Britain to meet the demands of the fast-growing bird market (Taschetto et al., 2012).

MATERIALS AND METHODS

All procedures for raising and slaughtering chickens were approved by the Institutional Animal Care and Use Committee of Sichuan Agricultural University. The methods were conducted according to approved guidelines.

Sampling

A total of 180 one-day-old males (90 birds from each population) were raised for this study, with three replicate groups (30 chicks per group) in each population. All the chicks were raised in batteries with wire mesh floor from d 1 to d 70.The diets consisted of 21.4% CP and 3,015 Kcal of ME/kg to d 28, followed by 19.9% CP and 3,100 kcal of ME/kg from d 29 to 42, and 18% CP and 3,180 kcal of ME/kg from d 43 to 70. Water and feed were available ad libitum. We weighted the birds at the first day and the end of each week from d 1 to 70, and randomly sampled six birds from each group on d 1, 7, 28, 49, and 70, respectively. The whole right breast muscle (pectoralis major [PM] and minor) and leg muscles (drum and thigh) of each chicken were isolated and weighed. Breast muscle weight (BW) and leg muscle weight (LW) are shown as doubled right breast muscle weight and leg muscle weight, respectively. About two cm3 of right PM and gastrocnemius muscle (GM) were excised along the muscle fibers and fixed in formalin for paraffin embedding and sectioning. Samples for RNA extractions were collected from the left PM and GM, snap-frozen in liquid nitrogen, and stored at -80°C.

Morphological analysis of skeletal muscles

PM and GM tissues were fixed with 10% neutral-buffered formalin and then dehydrated in a dilution series of ethanol and treated with xylene. Samples were embedded into paraffin blocks, trimmed, and cut at 5 μm thickness using a Microm HM315 (Germany), sections were mounted onto slides. Dewaxed after section flattening, slices were stained with hematoxylin and eosin (Saverino et al., 2014). We observed a section under the microscope with a magnification of 10×20x, randomly selected 5-10 fields on the image, and captured the photomicrographs. The diameter and density of myofibers were measured with Image-Pro Plus 5.0 software (Media Cybernetics Bethesda, MD, USA).

Total RNA extraction and cDNA synthesis

Total RNA was isolated from PM and GM using Trizol (Invitrogen, USA) according to the manufacturer’s instructions. The integrity and concentration/quality of RNA were verified by gel electrophoresis and spectrophotometry, respectively. The cDNA was synthesized via reverse transcription with a PrimeScript® RT reagent Kit (TaKaRa Biotech Co., Ltd.).

Real time PCR

A SYBR Prime Script RT-PCR Kit (TaKaRa, Japan) was used for real time PCR. β-Actin was the housekeeping gene. The reaction contained 2 μL of cDNA template, 12.5 μL SYBR® Premix Ex Taq™II, 8.5 μL ddH2O, and 1 μL of each gene-specific primer (Table I). The reaction mixture was predenatured for 2 min at 95 °C, followed by 40 cycles at 95 °C for 5 s, 65 °C for 2 s, and a full extension cycle at 95 °C for 5 s. Reactions were performed in triplicate. Primer sequences are displayed in Table I.

Data analysis

The model for other traits including myofiber diameter and density, breast muscle and leg muscle weights were as follows.

Yijk = µ + Pi + Tj +Ak+ (PT)ij +(PA)ik+(TA)jk+(PTA)ijk+ eijk

where Yijk = the performance of chicken in population i of tissue j on age k, µ = the general mean, Pi = the effect of population i (i = 1 and 2; FG and SG), Tj = the effect of tissue j (j = 1 and 2; breast muscle and leg muscle), Ak = the effect of age k (k = 1, 2, 3, 4, and 5; d1, 7, 28, 49, and 70) ; (PT)ij = the interaction effect of population i × tissue j, (PA)ik = the interaction effect of population i × age k, (TA)jk = the interaction effect of tissue j × age k, (PTA)ijk = the interaction effect of population i × tissue j × age k, eijk= the random residual effect.

All data were analyzed using the GLM procedure of JMP Pro v.10 (SAS Institute). Tukey’s test was used for multiple comparison analysis, and statistical significance was set at P < 0.05. Live weights at the end of each week were analyzed via student’s t-test.

RESULTS

The body weights of the two populations from d 1 to 70 were shown in Fig 1. Student’s t-test results indicated that the body weight of the chickens did not differ between FG and SG at hatch, whereas FG was heavier than SG from d 7 to 70 (P < 0.05).

 

Table I.- Primers used for real time PCR.

Gene1	Primer sequence2 (5′–3′)	Product length (bp)	Annealing temperature (°C)	GenBank accession number
β-Actin	F:TGTGCTGTCCCTGTATGCCTC R: GGAGGGCGTAGCCTTCATAGA	101	60	NM_205518.1
IGF-1	F:GTGGTGCTGAGCTGGTTGATG R: AGCATTCATCCACTATTCCCTTG	126	58	NM_001004384.2
MyoD	F:GCTACTACACGGAATCACCAAATG R: CATGTGGAGTTGTCTGTGGAAATC	112	58	NM_204214.2
MyoG	F:GCGGAGGCTGAAGAAGGTGA R: CGCTCGATGTACTGGATGGC	120	57	NM_204184.1
Pax7	F:CCACGGGAATGCCAACTCT R: ATGGTGGATGGTGGCAAGG	121	57	NM_205065.1

 

1 IGF-1, insulin-like growth factor 1; MyoD, myogenic differentiation antigen; MyoG, myogenin; Pax7, paired-box 7.

2 F, forward primer; R, reverse primer.

 

Effects of Interaction of population, age, and tissue on myofiber histological characteristics

Results for the histology analysis were summarized in Table II. The results showed that the effect of age on all traits was significant. The muscle weight of the breast and leg and myofiber diameter of PM and GM for males increased with age, whereas their myofiber density decreased (Table II; P < 0.001). Meanwhile, the muscle weight and myofiber diameter of FG were greater than SG (P < 0.01). The myofiber diameter of PM was greater than GM (P < 0.001).

Effects of Interaction of population with age on muscle fiber characteristics

There was an interaction of population and age on muscle fiber characteristics (Fig. 2). The muscle weight (Fig. 2a) and myofiber diameter (Fig. 2b) of FG and SG were the highest on d 70 in comparison with the other combinations, and the muscle weights of FG were greater than SG from d 28 to 70 (P < 0.05) (Fig. 2a). The myofiber diameters of FG were thicker than SG from d 1 to 70 (P < 0.05) (Fig. 2b). While, myofiber density (Fig. 2c) decreased from d 1 to 7 and did not significantly differ between the two populations at the same time point (P > 0.05).

 

Table II.- Muscle fiber characteristics of chickens on d 1, 7, 28, 49, and 70.

Effects		n	Diameter1 (μm)	Density1 (N/mm2)	Weight1 (g)
Population	FG	30	37.07a	5514.27	98.55a
	SG	30	25.39b	5618.44	38.17b
	SEM		0.85	916.60	16.10
	P-value		< 0.001	0.95	0.01
Age	d1	12	7.08e	22695.11a	0.57c
	d7	12	14.84d	5413.36b	2.56c
	d28	12	26.26c	2102.66bc	28.96c
	d49	12	61.91b	403.02c	111.79b
	d70	12	76.15a	225.04c	194.14a
	SEM		0.65	855.83	0.70
	P-value		< 0.001	< 0.001	< 0.001
Tissue	Pectoralis major muscle	60	27.79b	7852.10	58.79
	Gastrocnemius muscle	60	37.05a	4800.10	78.64
	SEM		0.89	1044.05	12.03
	P-value		< 0.001	0.15	0.41
			P-value
Interaction2	P×A		< 0.001	< 0.001	< 0.001
	P×T		< 0.001	0.23	0.07
	A×T		< 0.001	< 0.001	< 0.001
	P×A×T		< 0.001	< 0.001	< 0.001

 

1Means in a column within an effect without a common superscript letter differ significantly (P < 0.05).

2P, A, and T represent effects of population, age, and tissue, respectively.

 

Effect of Interaction of population and tissue on muscle fiber diameter

There was an interaction of population and tissue on muscle fiber traits as shown in Figure 3. The GM fiber diameter of FG was thicker than SG, and the fiber diameter in PM was less than GM for FG (P < 0.05). No differences were observed between the tissues of SG (P > 0.05).

Effects of Interaction of tissue and age on muscle fiber characteristics

Figure 4 shows the interaction of tissue and age on muscle fiber characteristics. No significant differences were observed between BW and LW (P > 0.05) (Fig. 4a). The fiber diameter in PM was greater than GM on d 28 (P < 0.05) (Fig. 4b). However, the opposite pattern was observed from d 49 to onward. In addition, myofiber density declined with time, and the myofiber density of PM was greater than GM on the first day (P < 0.05) (Fig. 4c).

Effects of Interaction of population, age, and tissue on myofiber characteristics

The three-way interaction is displayed in Figure 5. From d 28 to 70, muscle weights of FG were heavier than SG, and the leg of SG was heavier than the breast of SG on d 70 (P < 0.05) (Fig. 5a). The PM fibers of FG were thicker

 

 

than SG from d 7, and the GM fiber diameters of FG were greater than SG from d 28 (P < 0.05) (Fig. 5b). In the first week, the GM fiber diameter was greater than PM’s in SG (P < 0.05) (Fig. 5b). On d 28, the PM fiber was thicker than GM’s in FG (P < 0.05) (Fig. 5b). In general, the myofiber diameters of FG were greater than SG for all growth points (P < 0.05) (Fig. 5b). The myofiber densities for both SG and FG were the greatest on the first day compared with other growth points. From d 1 to 28, the PM fiber density of SG was greater than FG. The fiber density in GM of FG was greater than GM of SG on day 1, but fiber density in GM of SG exceeded that in GM of FG on d 28 (P < 0.05) (Fig. 5c). The fiber density in PM was greater than GM for FG during the first week. The fiber density of PM was greater than GM for FG on d 1, and its GM fiber density exceeded that of PM on d 7 (P < 0.05) (Fig. 5c).

In general, muscle weight and myofiber diameter in chickens were increased with time while myofiber density was decreased with time. Moreover, the muscle weights and myofiber diameters in fast-growing Cobbs were greater than slow-growing chicken line HS1 from d 28 (P < 0.05).

Effects of population, age, and tissue on mRNA

In Table III we summarized the expression of genes MyoD, MyoG, IGF-1, and Pax7, including the main effects of population, age, tissue, and their interactions. The effect of age was significant in this study. The expression profiles of MyoG and IGF-1 increased initially, then decreased, and reached its peak on d 7. Pax7 expression decreased with time (P < 0.05). In addition, MyoG and Pax7 mRNA abundances were greater in the PM than the GM (P < 0.05).

 

Table III.- Effects of population, age, and tissue and their interactions on gene expression abundances in skeletal muscles.

Effects		n	Relative difference in mRNA
			MyoD1	MyoG1	IGF-11	Pax71
Population	FG	30	1.02	1.07	0.79	1.07
	SG	30	0.95	0.82	0.73	1.17
	SEM		0.11	0.09	0.06	0.19
	P-value		0.74	0.15	0.64	0.80
Age	d1	12	1.31	0.52b	0.71b	2.07a
	d7	12	0.80	1.27a	1.24a	0.94ab
	d28	12	1.39	1.10ab	0.68b	1.59ab
	d49	12	0.63	1.36a	0.71b	0.57ab
	d70	12	0.69	0.50b	0.54b	0.28b
	SEM		0.22	0.16	0.12	0.38
	P-value		0.042	< 0.001	0.005	0.01
Tissue	Pectoralis major muscle	60	1.06	1.15a	0.71	1.53a
	Gastrocnemius muscle	60	0.90	0.73b	0.82	0.71b
	SEM		0.11	0.08	0.06	0.19
	P-value		0.45	0.01	0.37	0.03
			P-value
Interaction2	P×A		0.19	0.004	0.08	0.18
	P×T		0.87	0.005	0.22	0.16
	A×T		0.05	< 0.001	0.03	0.002
	P×A×T		0.04	< 0.001	0.04	0.20

 

1Means in a column within a variation without a common letter differ significantly (P < 0.05).

2P, A, and T represent effects of population, age, and tissue, respectively.

Interaction of population and tissue with population with age on MyoG mRNA

The differences between the two populations in MyoG for all time points were not significant (P > 0.05; Fig. 6). As shown in Figure 7, the expression of MyoG was the greatest in FGP, compared with other combinations (P < 0.05), and no significant differences were observed among the other combinations (P > 0.05).

Interaction of tissue and age on gene expression

There was an interaction of tissue and age on the expression of the four genes in PM and GM (Fig. 8). No significant differences were observed between the two tissues at any time point for the expression of MyoG, IGF-1, and Pax7 (P > 0.05). MyoG expression in PM was greater on d 49 than days 1 and 70 (P < 0.05) (Fig. 8a). The expression of Pax7 in PM on d 1 was greater than on d 70 (P < 0.05) (Fig. 8c).

 

Interaction of population, age, and tissue on mRNA

No significant differences were observed between the tissues at the same time point for MyoD (Fig. 9a). On d 28, the expression of MyoD (Fig. 9a) and MyoG (Fig. 9b) in PM of FG peaked with respect to the other ages. Expression of MyoG in PM was greater than GM for FG on d 28 (P <0.05) (Fig. 9b). The expression of MyoG (Fig. 9b) and MyoD (Fig. 9a) in PM of FG initially increased, then decreased, and was greatest on d 28.

Other interaction effects on myofiber traits and gene expression were not significant.

DISCUSSION

The physiological characteristics of skeletal muscle, such as myofiber density and diameter, are important in chicken breeding and production (Chen et al., 2013). The development of myofibers in poultry is artificially divided into two stages: incubation and post-hatch periods. During the incubation period, the myofiber precursor cells proliferate, then fuse into myotubes, and finally differentiate into myofibers (Picard et al., 2002). In general, the total number of muscle fibers are constant during the post-hatch period (Baryshnikova et al., 2007). Meanwhile, hypertrophy and the extension of myofibers decrease myofiber density during muscle development post-hatch (Wang et al., 2017).

 

 

 

Our results showed that muscle weight and myofiber diameter increased with time in PM and GM for FG and SG, while myofiber density was mostly unchanged, showing that myofiber density peaked initially and then was relatively stable until the end of the study, consistent with another chicken experiment (Chen et al., 2007).

Skeletal muscle fiber characteristics are affected by genetics. Several studies reported differences in carcass characteristics and meat quality between slow- and fast-growing breeds (Cassandro et al., 2016; Verdiglione and Cassandro, 2013). Cobb broilers are fast-growing, have large breast meat yields, and reach the market weight on d 40 (Eldeeb et al., 2006). However, HS1, like other breeds of Chinese meat-type chickens, are slow-growing and reaches market at 12 weeks or later. In the current study, the weights and fiber diameters of the skeletal muscle of Cobb increased at a greater rate than HS1 from d 28 to onward, which demonstrates that FG muscle develops faster. The myofiber diameter of fast- growing broiler is higher than slow-growing chickens due to the greater number of giant fibers. This fast growth rate may negatively impact on meat quality. Meat tenderness is negatively correlated with myofiber density; thus, the myofiber density of chickens should be considered in evaluating meat tenderness (An et al., 2010). Our results revealed that the myofibers of FG were thicker than SG, thus the meat of FG may be considered to be tougher than SG.

The developmental profiles of different skeletal muscle tissues differed greatly (Ying et al., 2016). A previous study reported that the leg muscle yield of quality chickens are greater than breast muscle yield (Sabbioni et al., 2006). We found that the leg of SG was heavier than their breast on d 70. From d 1 to 7, the fiber density in PM was greater than that in GM in SG. When the density was stable, muscle growth depended on myofiber hypertrophy. The weights of the breast and leg of FG were similar. The fiber diameter in PM was larger than that in GM for FG on d 28. However, after d 49, the increasing tendencies in fiber diameter in PM and GM of FG was not different which indicates that the growth rate of PM was greater than GM in FG during the early post-hatch period. This is consistent with a previous study, which found that the muscle growth rate of breast was greater than leg in Cobbs (Abdulla et al., 2017).

The GM fiber diameter of FG was thicker than PM and greater than GM in SG. Age is an essential factor affecting the development of skeletal muscle. When the effect of age was removed, myofiber diameter poorly described skeletal muscle development (Baéza et al., 2012). The interaction effects of tissue and age indicated that the increase of myofiber diameter in chickens were different between the two muscle tissues for all ages.

Several studies (Pallafacchina et al., 2013; Sacco et al., 2008) reported that skeletal muscle satellite cells affected the development of muscle fiber dimension. The activation, proliferation, and differentiation of stem cells induce myofiber hypertrophy. When the myofiber matures, the satellite cells are in a relatively static state, which maintains the relative constancy of the histological characteristics of the myofiber, also, the development of satellite cells are affected by factors such as MyoD and myogenin (Pallafacchina et al., 2010).

The expression of genes evaluated in this study always showed spatiotemporal change. Pax7 plays a critical role during activation, proliferation, and differentiation. Increasing the expression of Pax7 promotes satellite cell self-renewal (Craig et al., 2008). In other words, a high expression of Pax7 is always accompanied by growth of myofiber density. In the present study, the expression of Pax7 in PM was time-dependent. Pax7 expression in PM decreased with time and was accompanied by decreased PM fiber density. Moreover, no significant differences were observed between the PM and GM in terms of Pax7 expression abundance and myofiber density.

Expression of IGF-1, MyoG, and MyoD were increased myofiber diameter and resulted in hypertrophy. MyoD function is also involved in myofiber-type transformation (Lee et al., 2016; Sharma et al., 2016; Wang et al., 2013). In the current study, the expression of MyoG and MyoD in PM of FG were peaked on d 28, thereby suggesting that the age of 28 days is vital for skeletal muscle development. MyoG mRNA was peaked in PM on d 49. In different tissues of FG, the expression of MyoG was contrary to the increase of myofiber diameter. In conclusion, tissue was a significant factor influencing MyoG expression. IGF-1 plays an essential role in heart and skeletal muscle development, which regulates the cell cycle, promoting cell fusion and protein synthesis (Clemmons, 2009), and increasing myofiber diameter and the rates of protein synthesis (Latres et al., 2005). However, no prominent difference was observed between the fast- and slow- growing genetic chickens and between PM and GM muscle tissues. A previous study on broilers suggested that IGF-1 mRNA is down-regulated with age in the breast, but the expression profile of IGF-1 did not significantly change after d 7 (Saneyasu et al., 2016). Moreover, the polymorphism of IGF-1 is not associated with body weight in fast-growing chickens (Paswan et al., 2013). Thus, we did not consider IGF-1 to be a major gene affecting skeletal muscle in FG and SG.

CONCLUSION

Our results indicated that body weights and muscle expansion of slow- growing chickens were less than fast- growing chickens. The expression abundance of MyoG was affected by genetics, age, tissues, and their interactions. The expression profiles of Pax7 were consistent with the growth trend of myofiber density, whereas MyoG and MyoD were associated with myofiber diameter changes. Overall, we revealed that body weight and muscle expansion of slow- growing chickens were less than fast- growing chickens. MyoG was a gene that contributes to phenotypic differences between the slow- and fast- growing chickens.

ACKNOWLEDGMENTS

We thank Elizabeth R. Gilbert from Virginia Polytechnic Institute and State University for her professional comments on this manuscript, which greatly improved its quality. The work was supported by the National Natural Science Foundation of China (grant Number 31872347), the Enterprise Innovation Ability Cultivation Project of Sichuan Province (grant Number 2018NZ0017) and Transformation of Agricultural Scientific and Technological Achievements of Sichuan Province (Grant Number 2018NZZJ003).

Statement of conflict of interest

The authors declare no conflict of interest.

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