Dataset Information

Identification of transcriptional biomarkers by RNA-sequencing for improved detection of ?2-agonists abuse in goat skeletal muscle.

ABSTRACT: In this paper, high-throughput RNA-sequencing (RNA-seq) was used to search for transcriptional biomarkers for ?2-agonists. In combination with drug mechanisms, a smaller group of genes with higher detection accuracy was screened out. Unknown samples were first predicted by this group of genes, and liquid chromatograph tandem mass spectrometer (LC-MS/MS) was applied to positive samples to validate the biomarkers. The results of principal component analysis (PCA), hierarchical cluster analysis (HCA) and discriminant analysis (DA) indicated that the eight genes screened by high-throughput RNA-seq were able to distinguish samples in the experimental group and control group. Compared with the nine genes selected from an earlier literature, 17 genes including these nine genes were proven to have a more satisfactory effect, which validated the accuracy of gene selection by RNA-seq. Then, six key genes were selected from the 17 genes according to the variable importance in projection (VIP) value of greater than 1. The test results using the six genes and 17 genes were similar, revealing that the six genes were critical genes. By using the six genes, three positive samples possibly treated with drugs were screened out from 25 unknown samples through DA and partial least squares discriminant analysis (PLS-DA). Then, the three samples were verified by a standard method, and mapenterol was detected in a sample. Therefore, the six genes can be used as biomarkers to detect ?2-agonists. Compared with the previous study, accurate detection of ?2-agonists abuse using six key genes is an improvement method, which show great significance in the monitoring of ?2-agonists abuse in animal husbandry.

SUBMITTER: Zhao L

PROVIDER: S-EPMC5528896 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Identification of transcriptional biomarkers by RNA-sequencing for improved detection of β2-agonists abuse in goat skeletal muscle.

Zhao Luyao L Yang Shuming S Cheng Yongyou Y Hou Can C You Xinyong X Zhao Jie J Zhang Ying Y He Wenjing W

PloS one 20170726 7

In this paper, high-throughput RNA-sequencing (RNA-seq) was used to search for transcriptional biomarkers for β2-agonists. In combination with drug mechanisms, a smaller group of genes with higher detection accuracy was screened out. Unknown samples were first predicted by this group of genes, and liquid chromatograph tandem mass spectrometer (LC-MS/MS) was applied to positive samples to validate the biomarkers. The results of principal component analysis (PCA), hierarchical cluster analysis (HC ...[more]

PMID: 28746361

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Project description:Skeletal muscle is a complex heterogeneous tissue and characterizing its cellular heterogeneity and transcriptional and epigenetic signatures are important for understanding the details of its ontogeny. In our study, we applied scRNA-seq and scATAC-seq to investigate the cell types, molecular features, transcriptional and epigenetic regulation, and patterns of developing bovine skeletal muscle from gestational, lactational and adult stages. Detailed molecular analyses were used to dissect cellular heterogeneity, and we deduced the differentiation trajectory of myogenic cells and uncovered their dynamic gene expression profiles. SCENIC analysis was performed to demonstrate key regulons during cell fate decisions. We explored the future expression states of these heterogeneous cells by RNA velocity analysis and found extensive networks of intercellular communication using the toolkit CellChat. Moreover, the transcriptomic and chromatin accessibility modalities were confirmed to be highly concordant, and integrative analysis of chromatin accessibility and gene expression revealed key transcriptional regulators acting during myogenesis. In bovine skeletal muscle, by scRNA-seq and scATAC-seq analysis, different cell types such as adipocytes, endothelial cells, fibroblasts, lymphocytes, monocytes, pericyte cells and eight skeletal myogenic subpopulations were identified at the three developmental stages. The pseudotime trajectory exhibited a distinct sequential ordering for these myogenic subpopulations and eight distinct gene clusters were observed according to their expression pattern. Moreover, specifically expressed TFs (such as MSC, MYF5, MYOD1, FOXP3, ESRRA, BACH1, SIX2 and ATF4) associated with muscle development were predicted, and likely future transcriptional states of individual cells and the developmental dynamics of differentiation among neighbouring cells were predicted. CellChat analysis on the scRNA-seq data set then classified many ligand-receptor pairs among these cell clusters, which were further categorized into significant signalling pathways, including BMP, IGF, WNT, MSTN, ANGPTL, TGFB, TNF, VEGF and FGF. Finally, scRNA-seq and scATAC-seq results were successfully integrated to reveal a series of specifically expressed TFs that are likely to be candidates for the promotion of cell fate transition during bovine skeletal muscle development. Overall, our results outline a single-cell dynamic chromatin/transcriptional landscape for normal bovine skeletal muscle development; these provide an important resource for understanding the structure and function of mammalian skeletal muscle, which will promote research into its biology.

Project description:BACKGROUND:Circular RNA (circRNA) is produced during the splicing of mRNA (in addition to linear splicing) and is part of the gene regulatory network. The temporal expression patterns the different developmental stages were inseparable from these molecules' function. RESULTS:Skeletal muscles of Anhui white goat (AWG) across seven fetal to postnatal development stages were sequenced and 21 RNA sequencing libraries were constructed. We thereby identified 9090 circRNAs and analyzed their molecular properties, temporal expression patterns, and potential functions at the different stages. CircRNAs showed complexities and diversity of formation as the same host gene produces multiple isoforms of these nucleic acids with different expression profiles. The differential expression of 2881 circRNAs (DECs, P < 0.05) was identified and four were randomly selected and validated by qPCR. Moreover, 1118 DECs under strict selected (SDECs, |log2FC| > 2 and P-adj value < 0.01) showed 4 expression trends (Clusters 0, 19, 16 and 18). Cluster 0 molecules had increasing expression at all stages with effects on muscle through metabolism, regulation of enzyme activity, and biosynthesis. Cluster 16 circRNAs had high expression in the early and late stages and are involved in "Wnt signaling pathway", "AMPK signaling pathway" and others. Cluster 18 molecules were mainly expressed at F120 and participate in "cytoskeletal protein binding", "Notch signaling pathway" and so on. Cluster 19 circRNAs were down-regulated at all stages and related to muscle structure and development. Lastly, the SDECs divided the period of skeletal muscle development into three transitional stages: stage 1 (F45 to F90), which related to muscle satellite cell proliferation and muscle fiber structure; stage 2 (F90 to B1), in which the attachment of the cytoplasmic surface to the actin cytoskeleton initiates; and stage 3, which involved the "cGMP-PKG signaling pathway". Moreover, the paraffin sections messages also validated that there are three transitional stages of skeletal muscle development. CONCLUSION:Our current study provides a catalog of goat muscle-related circRNAs that can stratify skeletal muscle development fetus 45 days to newborn 90 days into three developmental stages. These findings better our understanding of functional transitions during mammalian muscle development.

Dataset Information

Identification of transcriptional biomarkers by RNA-sequencing for improved detection of ?2-agonists abuse in goat skeletal muscle.

Publications

Identification of transcriptional biomarkers by RNA-sequencing for improved detection of β2-agonists abuse in goat skeletal muscle.

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