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

被引:9
|
作者
Wang, Han [1 ]
Shen, Zhonghao [1 ]
Zhou, Xiaolong [1 ]
Yang, Songbai [1 ]
Yan, Feifei [1 ]
He, Ke [1 ]
Zhao, Ayong [1 ]
机构
[1] Zhejiang A&F Univ, Coll Vet Med, Coll Anim Sci & Technol, Linan 311300, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
MYOSIN HEAVY-CHAIN; POSTMORTEM GLYCOLYTIC RATE; MEAT QUALITY; MESSENGER-RNA; CHICKEN BREAST; INSULIN; SLOW; RAT; ISOFORMS; RECEPTOR;
D O I
10.1155/2020/9478949
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] DEsubs: an R package for flexible identification of differentially expressed subpathways using RNA-seq experiments
    Vrahatis, Aristidis G.
    Balomenos, Panos
    Tsakalidis, Athanasios K.
    Bezerianos, Anastasios
    BIOINFORMATICS, 2016, 32 (24) : 3844 - 3846
  • [42] Bayesian identification of differentially expressed isoforms using a novel joint model of RNA-seq data
    Shi, Xu
    Wang, Xiao
    Jin, Lu
    Halakivi-Clarke, Leena
    Clarke, Robert
    Neuwald, Andrew F.
    Xuan, Jianhua
    PLOS COMPUTATIONAL BIOLOGY, 2025, 21 (01)
  • [43] Comparison of differentially expressed genes in longissimus dorsi muscle of Diannan small ears, Wujin and landrace pigs using RNA-seq
    Li, Qiuyan
    Hao, Meilin
    Zhu, Junhong
    Yi, Lanlan
    Cheng, Wenjie
    Xie, Yuxiao
    Zhao, Sumei
    FRONTIERS IN VETERINARY SCIENCE, 2024, 10
  • [44] Identification of key differentially expressed genes in SARS-CoV-2 using RNA-seq analysis with a systems biology approach
    Safarzadeh, Arash
    Hussen, Bashdar Mahmud
    Taheri, Mohammad
    Ghafouri-Fard, Soudeh
    Hajiesmaeili, Mohammadreza
    CYTOKINE, 2023, 166
  • [45] Identification of genes differentially expressed between prostrate shoots and erect shoots in the lycophyte Selaginella nipponica using an RNA-seq approach
    Sun, Jun
    Li, Gui-Sheng
    AOB PLANTS, 2022, 14 (03):
  • [46] Identification of differentially expressed genes based on antennae RNA-seq analyses in Culex quinquefasciatus and Culex pipiens molestus
    Heting Gao
    Zhenyu Gu
    Dan Xing
    Qiaojiang Yang
    Jianhang Li
    Xinyu Zhou
    Teng Zhao
    Chunxiao Li
    Parasites & Vectors, 15
  • [47] Identification of differentially expressed genes based on antennae RNA-seq analyses in Culex quinquefasciatus and Culex pipiens molestus
    Gao, Heting
    Gu, Zhenyu
    Xing, Dan
    Yang, Qiaojiang
    Li, Jianhang
    Zhou, Xinyu
    Zhao, Teng
    Li, Chunxiao
    PARASITES & VECTORS, 2022, 15 (01)
  • [48] Exploring differentially expressed genes in the ovaries of uniparous and multiparous goats using the RNA-Seq (Quantification) method
    Ling, Ying-Hui
    Xiang, Hao
    Li, Yun-Sheng
    Liu, Ya
    Zhang, Yun-Hai
    Zhang, Zi-Juan
    Ding, Jian-Ping
    Zhang, Xiao-Rong
    GENE, 2014, 550 (01) : 148 - 153
  • [49] DEGnet: Identifying Differentially Expressed Genes Using Deep Neural Network from RNA-Seq Datasets
    Kakati, Tulika
    Bhattacharyya, Dhruba K.
    Kalita, Jugal K.
    PATTERN RECOGNITION AND MACHINE INTELLIGENCE, PREMI 2019, PT II, 2019, 11942 : 130 - 138
  • [50] Modeling and cleaning RNA-seq data significantly improve detection of differentially expressed genes
    Deyneko, Igor, V
    Mustafaev, Orkhan N.
    Tyurin, Alexander A.
    Zhukova, Ksenya, V
    Varzari, Alexander
    Goldenkova-Pavlova, Irina, V
    BMC BIOINFORMATICS, 2022, 23 (01)