Exploring the lncRNAs Related to Skeletal Muscle Fiber Types and Meat Quality Traits in Pigs.

Rongyang Li,Aiwen Jiang,Liming Hou,Wangjun Wu,Xiying Zhang,Honglin Liu,Kee-Hong Kim,Yan Cao,Bojiang Li,Zengkai Zhang

doi:10.3390/genes11080883

Abstract

The alteration in skeletal muscle fiber is a critical factor affecting livestock meat quality traits and human metabolic diseases. Long non-coding RNAs (lncRNAs) are a diverse class of non-coding RNAs with a length of more than 200 nucleotides. However, the mechanisms underlying the regulation of lncRNAs in skeletal muscle fibers remain elusive. To understand the genetic basis of lncRNA-regulated skeletal muscle fiber development, we performed a transcriptome analysis to identify the key lncRNAs affecting skeletal muscle fiber and meat quality traits on a pig model. We generated the lncRNA expression profiles of fast-twitch Biceps femoris (Bf) and slow-twitch Soleus (Sol) muscles and identified the differentially expressed (DE) lncRNAs using RNA-seq and performed bioinformatics analyses. This allowed us to identify 4581 lncRNA genes among six RNA libraries and 92 DE lncRNAs between Bf and Sol which are the key candidates for the conversion of skeletal muscle fiber types. Moreover, we detected the expression patterns of lncRNA MSTRG.42019 in different tissues and skeletal muscles of various development stages. In addition, we performed a correlation analyses between the expression of DE lncRNA MSTRG.42019 and meat quality traits. Notably, we found that DE lncRNA MSTRG.42019 was highly expressed in skeletal muscle and its expression was significantly higher in Sol than in Bf, with a positive correlation with the expression of Myosin heavy chain 7 (MYH7) (r = 0.6597, p = 0.0016) and a negative correlation with meat quality traits glycolytic potential (r = −0.5447, p = 0.0130), as well as drip loss (r = −0.5085, p = 0.0221). Moreover, we constructed the lncRNA MSTRG.42019–mRNAs regulatory network for a better understanding of a possible mechanism regulating skeletal muscle fiber formation. Our data provide the groundwork for studying the lncRNA regulatory mechanisms of skeletal muscle fiber conversion, and given the importance of skeletal muscle fiber types in muscle-related diseases, our data may provide insight into the treatment of muscular diseases in humans.

Highlights

Skeletal muscle is the major component of body mass accounting for approximately 50% of body mass in a mammal, and its growth and development are critical for maintaining skeletal muscle function
Expression Patterns of LncRNA MSTRG.42019. Among these differentially expressed (DE) Long non-coding RNAs (lncRNAs), we found that lncRNA MSTRG.42019 was a promising DE lncRNA
Our results showed that expression levels of lncRNA MSTRG.42019 were positively correlated with the mRNA expression level of Myosin heavy chain 7 (MYH7) (r = 0.659, p = 0.0016) (Figure 5A), with no correlation with the expression levels of MyoB and Myosin heavy chain 4 (MYH4) (Additional File 4: Figure S4A,B)

Summary

Introduction

Skeletal muscle is the major component of body mass accounting for approximately 50% of body mass in a mammal, and its growth and development are critical for maintaining skeletal muscle function. Skeletal muscle is composed of various muscle fibers that exhibit different physiological and metabolic properties, such as glycolysis, oxidative metabolism, and contraction [1]. Genes 2020, 11, 883 dysfunctions of skeletal muscle fiber types are known to many human diseases, such as muscular dystrophy, cardiomyopathic disease, and type 2 diabetes [2,3,4,5]. The differences in skeletal muscle fiber types directly affect meat quality postmortem in livestock, such as pH, meat color, and drip loss [6]. Elucidating the underlying mechanisms of skeletal muscle growth and development and skeletal muscle fibers formation will be useful for the treatment of human muscle diseases and the improvement of production traits of livestock. Myogenesis is a complex process that is controlled by a series of factors, such as myogenic regulatory factors (MRFs) [7,8] and non-coding small molecule RNA microRNAs (miRNAs) [9,10]

Methods

Results

Conclusion