Identification of genes related to skeletal muscle growth and development by integrated analysis of transcriptome and proteome in myostatin-edited Meishan pigs.

来自 PUBMED

作者:

Li XXie SQian LCai CBi HCui W

展开

摘要:

Embryonic development of skeletal muscle is a complex process that is important to the growth of skeletal muscle after birth. However, the mechanisms by which skeletal muscle growth and development in embryonic phase remain unclear. We have previously produced myostatin-knockout (MKO) Meishan pigs with double-muscle (DM) phenotype via zinc finger nucleases (ZFN) technology. To further investigate the molecular mechanisms involved in skeletal muscle growth and development, in this study, we performed an integrated analysis of transcriptome and proteome in longissimus dorsi muscle from myostatin wild type (MWT) and MKO pigs on 65 days post coitus. Results showed that, compared with MWT group, there were 438 differentially expressed genes (DEGs) and 66 differentially expressed proteins (DEPs) in MKO group. These DEGs and DEPs were mainly enriched in signaling pathways that are involved in skeletal muscle growth and development, glucose metabolism and apoptosis. Furthermore, we identified two key genes, Troponin T 1 (TNNT1) and Myosin regulatory light chain 9 (MYL9), which showed significant changes in both mRNA and protein levels with the similar changing trends in MKO group. It is thus speculated that TNNT1 and MYL9 may play an important role in skeletal muscle growth and development. SIGNIFICANCE: Our study analyzed some important regulatory genes and proteins during skeletal muscle growth and development, our results provided (1) a new insight to further understanding of the molecular mechanisms by which growth and development are regulated in porcine skeletal muscle, and (2) some possible molecular makers for improvement of meat quality in the animal husbandry and diagnosis of human muscle diseases in medicine.

收起

展开

DOI:

10.1016/j.jprot.2019.103628

被引量:

12

年份:

1970

SCI-Hub (全网免费下载) 发表链接

通过 文献互助 平台发起求助,成功后即可免费获取论文全文。

查看求助

求助方法1:

知识发现用户

每天可免费求助50篇

求助

求助方法1:

关注微信公众号

每天可免费求助2篇

求助方法2:

求助需要支付5个财富值

您现在财富值不足

您可以通过 应助全文 获取财富值

求助方法2:

完成求助需要支付5财富值

您目前有 1000 财富值

求助

我们已与文献出版商建立了直接购买合作。

你可以通过身份认证进行实名认证,认证成功后本次下载的费用将由您所在的图书馆支付

您可以直接购买此文献,1~5分钟即可下载全文,部分资源由于网络原因可能需要更长时间,请您耐心等待哦~

身份认证 全文购买

相似文献(133)

参考文献(0)

引证文献(12)

来源期刊

-

影响因子:暂无数据

JCR分区: 暂无

中科院分区:暂无

研究点推荐

关于我们

zlive学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们不忘初心,砥砺前行。

友情链接

联系我们

合作与服务

©2024 zlive学术声明使用前必读