Using gene expression information obtained by quantitative real-time PCR to evaluate Angus bulls divergently selected for feed efficiency

2012 ◽  
Vol 52 (11) ◽  
pp. 1058 ◽  
Author(s):  
Y. Chen ◽  
P. F. Arthur ◽  
I. M. Barchia ◽  
K. Quinn ◽  
P. F. Parnell ◽  
...  

Residual feed intake (RFI) is a measure of feed efficiency in beef cattle. Young Angus bulls from lines of cattle divergently selected for RFI were used in a gene expression profiling study of the liver. Quantitative real-time PCR (qPCR) assay was used to quantify the differentially expressed genes and the information was used to examine the relationships between the genes and RFI and to classify the bulls into their respective RFI group. Gene expression of 21 genes in liver biopsies from 22 low RFI and 22 high RFI bulls were measured by qPCR. Gene expressions of 14 of the 21 genes were significantly correlated with RFI. The expression of the genes was used in a principal component analysis from which five components were extracted. The five principal components explained 70% of the variation in the dependency structure. The first component was highly correlated (correlation coefficient of 0.69) with RFI. The genes of the glutathione S-transferase Mu family (GSTM1, GSTM2, GSTM4), protocadherin 19 (PCDH19), ATP-binding cassette transporter C4 (ABCC4) and superoxide dismutase 3 (SOD3) are in the xenobiotic pathway and were the key factors in the first principal component. This highlights the important relationship between this pathway and variation in RFI. The second and third principal components were also correlated with RFI, with correlation coefficients of –0.28 and –0.20, respectively. Two of the four important genes of the second principal component work coordinately in the signalling pathways that inhibit the insulin-stimulated insulin receptor and regulate energy metabolism. This is consistent with the observation that a positive genetic correlation exists between RFI and fatness. The important genes in the third principal component are related to the extracellular matrix activity, with low RFI bulls showing high extracellular matrix activity.

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Ana Érika Inácio Gomes ◽  
Leonardo Prado Stuchi ◽  
Nathália Maria Gonçalves Siqueira ◽  
João Batista Henrique ◽  
Renato Vicentini ◽  
...  

Genome ◽  
2018 ◽  
Vol 61 (5) ◽  
pp. 349-358 ◽  
Author(s):  
Yanchun You ◽  
Miao Xie ◽  
Liette Vasseur ◽  
Minsheng You

Gene expression analysis provides important clues regarding gene functions, and quantitative real-time PCR (qRT-PCR) is a widely used method in gene expression studies. Reference genes are essential for normalizing and accurately assessing gene expression. In the present study, 16 candidate reference genes (ACTB, CyPA, EF1-α, GAPDH, HSP90, NDPk, RPL13a, RPL18, RPL19, RPL32, RPL4, RPL8, RPS13, RPS4, α-TUB, and β-TUB) from Plutella xylostella were selected to evaluate gene expression stability across different experimental conditions using five statistical algorithms (geNorm, NormFinder, Delta Ct, BestKeeper, and RefFinder). The results suggest that different reference genes or combinations of reference genes are suitable for normalization in gene expression studies of P. xylostella according to the different developmental stages, strains, tissues, and insecticide treatments. Based on the given experimental sets, the most stable reference genes were RPS4 across different developmental stages, RPL8 across different strains and tissues, and EF1-α across different insecticide treatments. A comprehensive and systematic assessment of potential reference genes for gene expression normalization is essential for post-genomic functional research in P. xylostella, a notorious pest with worldwide distribution and a high capacity to adapt and develop resistance to insecticides.


2020 ◽  
Vol 14 (2) ◽  
pp. 109-118 ◽  
Author(s):  
Qiuling Ma ◽  
Yong Shao ◽  
Wei Chen ◽  
Cheng Quan ◽  
Yanhui Zhu ◽  
...  

Aim: To investigate whether cervical cancer (CC) and cervical intraepithelial neoplasia (CIN) can be screened by analyzing gene expression profiling of peripheral blood. Methods: RNA-sequencing analysis of blood was performed on 11 CC patients, 21 CIN patients and 19 healthy controls (H). Fifty-nine genes were validated by quantitative real-time PCR using blood samples from 46 H, 83 CC and 32 CIN patients. Results: There were significant differences in the expression levels of six genes between CC and H, five genes between CIN and H and four genes between CC and CIN (p < 0.05). Four genes discriminated cervical lesions from H with a sensitivity of 82.61%, a specificity of 87.83% and an area under the curve of 0.8981. Three genes discriminated CC from CIN with a sensitivity of 53.13%, a specificity of 96.39% and an area under the curve of 0.7786. Conclusion: Our findings provided a promising noninvasive quantitative real-time PCR diagnostic assay of CC and CIN.


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