scholarly journals Expression levels of candidate genes for intramuscular fat deposition in two Banna mini-pig inbred lines divergently selected for fatness traits

2012 ◽  
Vol 35 (4) ◽  
pp. 783-789 ◽  
Author(s):  
Su-Mei Zhao ◽  
Wei-Zhen Li ◽  
Hong-Bin Pan ◽  
Ying Huang ◽  
Ming-Hua Yang ◽  
...  
2021 ◽  
Author(s):  
Pan Zhang ◽  
Qinggang Li ◽  
Yijing Wu ◽  
Yawen Zhang ◽  
Bo Zhang ◽  
...  

Abstract Subcutaneous fat and intramuscular fat (IMF) deposition are closely related to meat production and pork quality. Dingyuan pig, as a native pig breed in China, low selection leads to obvious genetic and phenotypic differences in the population. Individuals with extreme fat content in the population are ideal models for studying the mechanism of fat deposition. In this study, we used RNA-Seq and tandem mass tags-based (TMT) proteomics to analyze the key pathways and genes that specifically regulate subcutaneous fat and IMF deposition in Dingyuan pigs. We identified 191 differentially expressed genes (DEGs) and 61 differentially abundant proteins (DAPs) in the high and low back fat thickness (HBF, LBF) groups, 85 DEGs and 12 DAPs were obtained in the high and low intramuscular fat (HIMF, LIMF) groups. The functional analysis showed that the DEGs and DAPs in the backfat groups were mainly involved in carbohydrates, amino acids, and fatty acids, whereas the IMF groups were involved in the insulin pathway, longevity, and some disease-related pathways. we found 33 candidate genes that might tissue-specifically lipids deposition for subcutaneous and intramuscular fat. Our research provides theoretical reference materials for the improvement of fat deposition traits of local pig breeds in my country.


2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Huimin Kang ◽  
Di Zhao ◽  
Hai Xiang ◽  
Jing Li ◽  
Guiping Zhao ◽  
...  

Abstract Background In broiler production, breast muscle weight and intramuscular fat (IMF) content are important economic traits. Understanding the genetic mechanisms that underlie these traits is essential to implement effective genetic improvement programs. To date, genome-wide association studies (GWAS) and gene expression analyses have been performed to identify candidate genes for these traits. However, GWAS mainly detect associations at the DNA level, while differential expression analyses usually have low power because they are typically based on small sample sizes. To detect candidate genes for breast muscle weight and IMF contents (intramuscular fat percentage and relative content of triglycerides, cholesterol, and phospholipids), we performed association analyses based on breast muscle transcriptomic data on approximately 400 Tiannong partridge chickens at slaughter age. Results First, by performing an extensive simulation study, we evaluated the statistical properties of association analyses of gene expression levels and traits based on the linear mixed model (LMM) and three regularized linear regression models, i.e., least absolute shrinkage and selection operator (LASSO), ridge regression (RR), and elastic net (EN). The results show that LMM, LASSO and EN with tuning parameters that are determined based on the one standard error rule exhibited the lowest type I error rates. Using results from all three models, we detected 43 candidate genes with expression levels that were associated with breast muscle weight. In addition, candidate genes were detected for intramuscular fat percentage (1), triglyceride content (2), cholesterol content (1), and phospholipid content (1). Many of the identified genes have been demonstrated to play roles in the development and metabolism of skeletal muscle or adipocyte. Moreover, weighted gene co-expression network analyses revealed that many candidate genes were harbored by gene co-expression modules, which were also significantly correlated with the traits of interest. The results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that these modules are involved in muscle development and contraction, and in lipid metabolism. Conclusions Our study provides valuable insight into the transcriptomic bases of breast muscle weight and IMF contents in Chinese indigenous yellow broilers. Our findings could be useful for the genetic improvement of these traits in broiler chickens.


2021 ◽  
Author(s):  
Pan Zhang ◽  
Qinggang Li ◽  
Yijing Wu ◽  
Yawen Zhang ◽  
Bo Zhang ◽  
...  

Abstract Background: Subcutaneous fat and intramuscular fat (IMF) deposition are closely related to meat production and pork quality. The Dingyuan pig is a local pig breed in Anhui Province, China, that has great potential for fat deposition. Individuals with extreme subcutaneous fat and intramuscular fat content can be found in this breed, which provides a good study system for investigating the molecular mechanisms regulating these two types of fat deposit.Results: In this study, we used RNA-Seq and tandem mass tags-based proteomics to analyze the key pathways and genes that specifically regulate subcutaneous fat and intramuscular fat deposition in Dingyuan pigs. We identified 191 differentially expressed genes (DEGs) and 61 differentially abundant proteins (DAPs) in the high backfat thickness (HBF) and low backfat thickness (LBF) groups. In the high intramuscular fat and low intramuscular fat groups, we found 85 DEGs and 12 DAPs. The gene ontology and KEGG pathway enrichment analysis showed that the DEGs and DAPs in the backfat groups were mainly involved in various metabolic pathways, such as those related to carbohydrates, amino acids, esters, and fatty acids, whereas the DEGs and DAPs of the IMF groups were involved in a wide range of signaling pathways, including metabolic pathways, the insulin pathway, ketone body synthesis and degradation, longevity, and some disease-related pathways. Among the genes related to the metabolic pathways of carbohydrates, amino acids, esters, and fatty acids, we found 26 candidate genes that specifically regulate subcutaneous fat deposition and 7 genes that specifically regulate IMF deposition in Dingyuan pigs.Conclusion: Our data show that subcutaneous fat deposition and IMF deposition are regulated by the same genes, but there are also genes that specifically regulate these two fat depositions. Our data provide insights into the mechanisms of pig fat deposition.


2021 ◽  
Author(s):  
Pan Zhang ◽  
Qinggang Li ◽  
Yijing Wu ◽  
Yawen Zhang ◽  
Hao Zhang ◽  
...  

Abstract Background: Subcutaneous fat and intramuscular fat (IMF) deposition are closely related to meat production and pork quality. The Dingyuan pig is a local pig breed in Anhui Province, China, that has great potential for fat deposition. Individuals with extreme subcutaneous fat and intramuscular fat content can be found in this breed, which provides a good study system for investigating the molecular mechanisms regulating these two types of fat deposit.Results: In this study, we used RNA-Seq and tandem mass tags-based proteomics to analyze the key pathways and genes that specifically regulate subcutaneous fat and intramuscular fat deposition in Dingyuan pigs. We identified 191 differentially expressed genes (DEGs) and 61 differentially abundant proteins (DAPs) in the high backfat thickness (HBF) and low backfat thickness (LBF) groups. In the high intramuscular fat and low intramuscular fat groups, we found 85 DEGs and 12 DAPs. The gene ontology and KEGG pathway enrichment analysis showed that the DEGs and DAPs in the backfat groups were mainly involved in various metabolic pathways, such as those related to carbohydrates, amino acids, esters, and fatty acids, whereas the DEGs and DAPs of the IMF groups were involved in a wide range of signaling pathways, including metabolic pathways, the insulin pathway, ketone body synthesis and degradation, longevity, and some disease-related pathways. Among the genes related to the metabolic pathways of carbohydrates, amino acids, esters, and fatty acids, we found 26 candidate genes that specifically regulate subcutaneous fat deposition and 7 genes that specifically regulate IMF deposition in Dingyuan pigs.Conclusion: Our data show that subcutaneous fat deposition and IMF deposition are regulated by the same genes, but there are also genes that specifically regulate these two fat depositions. Our data provide insights into the mechanisms of pig fat deposition.


2021 ◽  
Vol 11 (2) ◽  
pp. 126
Author(s):  
Noshad Peyravian ◽  
Stefania Nobili ◽  
Zahra Pezeshkian ◽  
Meysam Olfatifar ◽  
Afshin Moradi ◽  
...  

This study aimed at building a prognostic signature based on a candidate gene panel whose expression may be associated with lymph node metastasis (LNM), thus potentially able to predict colorectal cancer (CRC) progression and patient survival. The mRNA expression levels of 20 candidate genes were evaluated by RT-qPCR in cancer and normal mucosa formalin-fixed paraffin-embedded (FFPE) tissues of CRC patients. Receiver operating characteristic curves were used to evaluate the prognosis performance of our model by calculating the area under the curve (AUC) values corresponding to stage and metastasis. A total of 100 FFPE primary tumor tissues from stage I–IV CRC patients were collected and analyzed. Among the 20 candidate genes we studied, only the expression levels of VANGL1 significantly varied between patients with and without LNMs (p = 0.02). Additionally, the AUC value of the 20-gene panel was found to have the highest predictive performance (i.e., AUC = 79.84%) for LNMs compared with that of two subpanels including 5 and 10 genes. According to our results, VANGL1 gene expression levels are able to estimate LNMs in different stages of CRC. After a proper validation in a wider case series, the evaluation of VANGL1 gene expression and that of the 20-gene panel signature could help in the future in the prediction of CRC progression.


2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110180
Author(s):  
Xiao Lin ◽  
Meng Zhou ◽  
Zehong Xu ◽  
Yusheng Chen ◽  
Fan Lin

In this study, we aimed to screen out genes associated with a high risk of postoperative recurrence of lung adenocarcinoma and investigate the possible mechanisms of the involvement of these genes in the recurrence of lung adenocarcinoma. We identify Hub genes and verify the expression levels and prognostic roles of these genes. Datasets of GSE40791, GSE31210, and GSE30219 were obtained from the Gene Expression Omnibus database. Enrichment analysis of gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed for the screened candidate genes using the DAVID database. Then, we performed protein–protein interaction (PPI) network analysis through the database STRING. Hub genes were screened out using Cytoscape software, and their expression levels were determined by the GEPIA database. Finally, we assessed the relationships of Hub genes expression levels and the time of survival. Forty-five candidate genes related to a high-risk of lung adenocarcinoma recurrence were screened out. Gene ontology analysis showed that these genes were enriched in the mitotic spindle assembly checkpoint, mitotic sister chromosome segregation, G2/M-phase transition of the mitotic cell cycle, and ATP binding, etc. KEGG analysis showed that these genes were involved predominantly in the cell cycle, p53 signaling pathway, and oocyte meiosis. We screened out the top ten Hub genes related to high expression of lung adenocarcinoma from the PPI network. The high expression levels of eight genes (TOP2A, HMMR, MELK, MAD2L1, BUB1B, BUB1, RRM2, and CCNA2) were related to short recurrence-free survival and they can be used as biomarkers for high risk of lung adenocarcinoma recurrence. This study screened out eight genes associated with a high risk of lung adenocarcinoma recurrence, which might provide novel insights into researching the recurrence mechanisms of lung adenocarcinoma as well as into the selection of targets in the treatment of the disease.


2013 ◽  
Vol 42 (3) ◽  
pp. 161-164 ◽  
Author(s):  
Morteza Roodgar ◽  
Andrew Lackner ◽  
Deepak Kaushal ◽  
Sumathi Sankaran ◽  
Satya Dandekar ◽  
...  

2014 ◽  
Vol 13 (1) ◽  
pp. 363-370
Author(s):  
L.R. Alves ◽  
R.C. Antunes ◽  
R.B. Andrade ◽  
A.A. Storti ◽  
S.L.B. Reis ◽  
...  

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