Parsing the microRNA genetics basis regulating skeletal muscle fiber types and meat quality traits in pigs

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.

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Mitochondrial Dynamics Is a Distinguishing Feature of Skeletal Muscle Fiber Types and Regulates Organellar Compartmentalization

Cell Metabolism ◽

10.1016/j.cmet.2015.09.027 ◽

2015 ◽

Vol 22 (6) ◽

pp. 1033-1044 ◽

Cited By ~ 90

Author(s):

Prashant Mishra ◽

Grigor Varuzhanyan ◽

Anh H. Pham ◽

David C. Chan

Keyword(s):

Skeletal Muscle ◽

Muscle Fiber ◽

Mitochondrial Dynamics ◽

Skeletal Muscle Fiber ◽

Muscle Fiber Types ◽

Fiber Types

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Blood flow to different skeletal muscle fiber types during contraction

AJP Heart and Circulatory Physiology ◽

10.1152/ajpheart.1983.245.2.h265 ◽

1983 ◽

Vol 245 (2) ◽

pp. H265-H275 ◽

Cited By ~ 30

Author(s):

B. G. Mackie ◽

R. L. Terjung

Keyword(s):

Skeletal Muscle ◽

Blood Flow ◽

Muscle Fiber ◽

Fiber Type ◽

Oxidative Capacity ◽

Skeletal Muscle Fiber ◽

Muscle Fiber Types ◽

Fiber Types ◽

Blood Flows ◽

Fast Twitch

Blood flow to fast-twitch red (FTR), fast-twitch white (FTW), and slow-twitch red (STR) muscle fiber sections of the gastrocnemius-plantaris-soleus muscle group was determined using 15 +/- 3-microns microspheres during in situ stimulation in pentobarbital-anesthetized rats. Steady-state blood flows were assessed during the 10th min of contraction using twitch (0.1, 0.5, 1, 3, and 5 Hz) and tetanic (7.5, 15, 30, 60, and 120/min) stimulation conditions. In addition, an earlier blood flow determination was begun at 3 min (twitch series) or at 30 s (tetanic series) of stimulation. Blood flow was highest in the FTR (220-240 ml X min-1 X 100 g-1), intermediate in the STR (140), and lowest in the FTW (70-80) section during tetanic contraction conditions estimated to coincide with the peak aerobic function of each fiber type. These blood flows are fairly proportional to the differences in oxidative capacity among fiber types. Further, their absolute values are similar to those predicted from the relationship between blood flow and oxidative capacity found by others for dog and cat muscles. During low-frequency contraction conditions, initial blood flow to the FTR and STR sections were excessively high and not dependent on contraction frequency. However, blood flows subsequently decreased to values in keeping with the relative energy demands. In contrast, FTW muscle did not exhibit this time-dependent relative hyperemia. Thus, besides the obvious quantitative differences between skeletal muscle fiber types, there are qualitative differences in blood flow response during contractions. Our findings establish that, based on fiber type composition, a heterogeneity in blood flow distribution can occur within a whole muscle during contraction.

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Human Skeletal Muscle Fiber Types: Delineation, Development, and Distribution

Canadian Journal of Applied Physiology ◽

10.1139/h97-020 ◽

1997 ◽

Vol 22 (4) ◽

pp. 307-327 ◽

Cited By ~ 87

Author(s):

Robert S. Staron

Keyword(s):

Skeletal Muscle ◽

Muscle Fiber ◽

Human Skeletal Muscle ◽

Fiber Type ◽

Skeletal Muscle Fiber ◽

Muscle Fiber Types ◽

Fiber Types ◽

Key Words Aging ◽

Fiber Number ◽

Human Limb

This brief review attempts to summarize a number of studies on the delineation, development, and distribution of human skeletal muscle fiber types. A total of seven fiber types can be identified in human limb and trunk musculature based on the pH stability/ability of myofibrillar adenosine triphosphatase (mATPase). For most human muscles, mATPase-based fiber types correlate with the myosin heavy chain (MHC) content. Thus, each histochemically identified fiber has a specific MHC profile. Although this categorization is useful, it must be realized that muscle fibers are highly adaptable and that innumerable fiber type transients exist. Also, some muscles contain specific MHC isoforms and/or combinations that do not permit routine mATPase-based fiber typing. Although the major populations of fast and slow are, for the most part, established shortly after birth, subtle alterations take place throughout life. These changes appear to relate to alterations in activity and/or hormonal levels, and perhaps later in life, total fiber number. Because large variations in fiber type distribution can be found within a muscle and between individuals, interpretation of data gathered from human muscle is often difficult. Key words: aging, myosin heavy chains, myogenesis, myofibrillar adenosine triphosphate

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PROPERTIES O F SKELETAL MUSCLE FIBER TYPES

BIOS Instant Notes in Human Physiology ◽

10.4324/9780203002650-60 ◽

2013 ◽

pp. 295-295

Keyword(s):

Skeletal Muscle ◽

Muscle Fiber ◽

Skeletal Muscle Fiber ◽

Muscle Fiber Types ◽

Fiber Types

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Identification of Differentially Expressed Genes in Different Types of Broiler Skeletal Muscle Fibers Using the RNA-seq Technique

BioMed Research International ◽

10.1155/2020/9478949 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Han Wang ◽

Zhonghao Shen ◽

Xiaolong Zhou ◽

Songbai Yang ◽

Feifei Yan ◽

...

Keyword(s):

Skeletal Muscle ◽

Differentially Expressed Genes ◽

Muscle Fiber ◽

Muscle Development ◽

Skeletal Muscle Fiber ◽

Differentially Expressed ◽

Muscle Fiber Types ◽

Type I ◽

Fiber Types ◽

Rna Seq

The difference in muscle fiber types is very important to the muscle development and meat quality of broilers. At present, the molecular regulation mechanisms of skeletal muscle fiber-type transformation in broilers are still unclear. In this study, differentially expressed genes between breast and leg muscles in broilers were analyzed using RNA-seq. A total of 767 DEGs were identified. Compared with leg muscle, there were 429 upregulated genes and 338 downregulated genes in breast muscle. Gene Ontology (GO) enrichment indicated that these DEGs were mainly involved in cellular processes, single organism processes, cells, and cellular components, as well as binding and catalytic activity. KEGG analysis shows that a total of 230 DEGs were mapped to 126 KEGG pathways and significantly enriched in the four pathways of glycolysis/gluconeogenesis, starch and sucrose metabolism, insulin signalling pathways, and the biosynthesis of amino acids. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) was used to verify the differential expression of 7 selected DEGs, and the results were consistent with RNA-seq data. In addition, the expression profile of MyHC isoforms in chicken skeletal muscle cells showed that with the extension of differentiation time, the expression of fast fiber subunits (types IIA and IIB) gradually increased, while slow muscle fiber subunits (type I) showed a downward trend after 4 days of differentiation. The differential genes screened in this study will provide some new ideas for further understanding the molecular mechanism of skeletal muscle fiber transformation in broilers.

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