Associations between two novel rSNPs in 5'-flanking region of the bovine casein gene cluster and milk performance traits

Ten evolutionary conservative sequences with high identity level to homological sequences in other mammal species were revealed in 5'-flanking region of casein's genes cluster. Five novel SNPs located inside of the evolutionary conservative regions were identified. The binding sites were revealed to be present in one allelic variant of four detected SNPs. So these SNPs were considered as rSNPs. Significant differences of allelic frequencies were revealed between beef cow's group and dairy cow's group in two rSNPs (NCE4, NCE7, p<0.001). Different alleles of those two rSNPs were shown to be associated with some milk performance traits in Black-and-White Holstein dairy cows. Significant difference of protein percentage has been found between cows with G/G and A/A genotypes (P<0.05) and A/G and A/A genotypes (P<0.05) for NCE4 polymorphism. The groups of animals with genotypes G/G and A/G for NCE7 polymorphism were significantly different in milk yield at the first lactation (kg) (P<0.01), milk fat yield (kg) (P<0.05) and milk protein yield (kg) (P<0.01). For the last trait the difference was significant also between cows with genotypes G/G and A/A for rSNP NCE7 (P<0.05).     

Chemical and physical stimuli induce cardiomyocyte differentiation from stem cells

In this study we investigated cardiomyocyte differentiation of rat bone marrow-mesenchymal stem cells (BM-MSCs) by treating the stem cells with conditions mimicking that of myocardial infarction. The extract from infarcted rat myocardium contained the biochemical factors arising after infarction. The cardiac contraction and relaxation were simulated by applying 4% strain at 1 Hz to the stem cells. We found that the extract from infarcted myocardium or 4% strain each alone could induce cardiomyocyte differentiation of BM-MSCs, as shown by expression of cardiomyocyte-specific genes including α-actin, connexin 43, Nkx2.5, MEF2c, GATA4, α-MHC, and Troponin I. Furthermore, a combination of the extract and 4% strain had stronger effects on cardiomyocyte differentiation than what either treatment alone had. Our results suggest that this in vitro model system simulates the local cardiac environment cues after infarction and may be useful in identifying the biochemical and physical factors involved in cardiomyocyte differentiation.     

The Adiponectin variants contribute to the genetic background of type 2 diabetes in Turkish population

Adiponectin, an adipose tissue specific protein encoded by the Adiponectin gene, modulates insulin sensitivity and plays an important role in regulating energy homeostasis. Many studies have shown that single nucleotide polymorphisms (SNPs) in the Adiponectin gene are associated with low plasma Adiponectin levels, insulin resistance and an increased risk of type 2 diabetes mellitus. The aim of the present study was to evaluate the contribution of the Adiponectin gene polymorphisms in genetic background of type 2 diabetes in a Turkish population. In total, 169 unrelated and non-obese diabetic patients and 119 age- and BMI-matched non-diabetic individuals with no family history of diabetes were enrolled in this study. We detected a significant association between type 2 diabetes and two SNPs: SNP − 11391G > A, which is located in the promoter region of the Adiponectin gene, and SNP + 276G > T, which is found in intron 2 of the gene (P < 0.05). The silence SNP G15G (+ 45T > G) in exon 1 and SNP + 349A > G in intron 2 also showed a weak association with type 2 diabetes (P = 0.06 and P = 0.07, respectively), while SNPs − 3971A > G in intron 1 and Y111H, R112C and H241P in exon 3 showed no association (P > 0.05). In conclusion, these findings suggest that Adiponectin gene polymorphisms might be effective on susceptibility for type 2 diabetes development which emerged from the interactions between multiple genes, variants and environmental factors.     

Gene expression signature of human HepG2 cell line

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and is associated with various clinico-pathological characteristics such as genetic mutations and viral infections. Therefore, numerous laboratories look out for identifying always new putative markers for the improvement of HCC diagnosis/prognosis. Many molecular profiling studies investigated gene expression changes related to HCC. HepG2 represents a pure cell line of human liver carcinoma, often used as HCC model due to the absence of viral infection. In this study we compare gene expression profiles associated with HepG2 (as HCC model) and normal hepatocyte cells by microarray technology. Hierarchical cluster analysis of genes evidenced that 2646 genes significantly down-regulated in HepG2 cells compared to hepatocytes whereas a further 3586 genes significantly up-regulated. By using the Ingenuity Pathway Analysis (IPA) program, we have classified the genes that were differently expressed and studied the functional networks correlating these genes in the complete human interactome. Moreover, to confirm the differentially expressed genes as well as the reliability of our microarray data, we performed a quantitative Real time RT-PCR analysis on 9 up-regulated and 11 down-regulated genes, respectively. In conclusion this work i) provides a gene signature of human hepatoma cells showing genes that change their expression as a consequence of liver cancer in the absence of any genetic mutations or viral infection, ii) evidences new differently expressed genes found in our signature compared to previous published studies and iii) suggests some genes on which to focus future studies to understand if they can be used to improve the HCC prognosis/diagnosis.