Genome-Wide Profiling of MicroRNAs significance was calculated using student’s t-test. * p,0.05 ; **p,0.01 C: For the diet induced obesity model, miRNA expression in epididymal fat pads from chow or high fat diet fed wild-type as well as from PPARc DN (P465L) mice was determined by real-time PCR. Five mice were analyzed for each condition. Data were normalized to SNORA73A expression and plotted as relative expression levels compared to wild-type normally fed mice. Anova tests revealed significantly regulated miRNAs * p,0.05 ; **p,0.01 and influence of genome (a), diet (b) or interaction of both (c). doi:10.1371/journal.pone.0021305.g005 t-test revealed significant changes (p,0.05) for 12 of the regulated miRNAs and highly significant changes (p,0.01) for 8 miRNAs (Fig. 5B). Interestingly, we found that the majority of those miRNAs (17/20) that were upregulated in differentiating adipo- cytes were downregulated in the fat pads of obese mice and vice versa. Only three miRNAs were consistently regulated in both model systems with miR-155 being upregulated both in differen- tiating adipocytes and in obese mice and miR-466a-3p as well as miR-467 that were downregulated in both adipocytes and obese mice. Additionally, we investigated the influence of high fat diet and PPARc activity on microRNA expression either separately or in combination. For this purpose, animals with a mixed genetic background harboring either the PPARc wild type gene (WT) or a dominant-negative PPARc mutation (P465L DN) were fed either a high fat diet or a chow diet. The levels of the 66 miRNAs being differentially expressed during in vitro adipocyte development, were also determined in epididymal fat pads of the four in vivo conditions (wt+chow, wt+HFD, P465L+chow, P465L+HFD). Compared to wt chow fed animals that served as a reference 21 miRNAs were differentially expressed in at least one of the other three conditions (fold change .1.5 or ,0.66; p,0.05). Using 2- way ANOVA, the influence of the genotype (a), diet (b) or an interaction of both factors (c) on the miRNA expression was assessed (compare Fig. 5C). For eleven of these regulated miRNAs, the diet was the only factor responsible for altered expression levels (‘‘b’’ in Fig. 5C). In all these cases, the miRNA expression was induced after high fat diet in both the wild-type as well as PPARc mutant animals. The high fat diet induced up-regulation of miR- 421, miR-702 and miR-703, in these mouse models was not reflected in the mesenchymal stem cell model of adipogenesis as these miRNAs were down-regulated during in vitro adipocyte differentiation. The expression of miR-146b that was induced both early after induction of mesenchymal stem cell differentiation as well as after reaching a growth arrest in NIH/3T3 fibroblasts, was also significantly up-regulated upon HFD-treatment in wild-type mice as well as mutant animals. The expression of four miRNAs was only dependent on the PPARc expression status of the animals; miR-199, miR-455 and miR-1192 were upregulated in mice with dominant-negative PPARc irrespective of the diet given to the animals, the fourth, miR-592, was reduced in mutant animals (‘‘a’’ in Fig. 5C). An interaction between genotype and diet on miRNA expression was found in three cases: miR-7b, miR- 27a and miR-34a were up-regulated in wt animals receiving high fat diet but not upregulated in P465L DN mice receiving HFD (‘‘c’’ in Fig. 5C). Discussion Experimental strategy for miRNA profiling In the present study, we have analyzed the expression pattern of 583 mouse miRNAs during the adipogenic differentiation of murine mesenchymal stem cells. The expression profile has been performed by qRT-PCR employing a pooling strategy. Using this new approach, we were able to analyze the expression of every single mouse miRNA (miRBase v.12) at different time points during the differentiation process of murine mesenchymal stem cells into terminally differentiated adipocytes. The pooling of samples significantly reduces work load while the sensitivity of a real-time PCR based approach significantly exceeds other alternative methods like Northern blot or even miRNA expression microarrays. Using such a pooling approach we showed that complex PCR-based miRNA screening projects could be handled in a reasonable time, even by laboratories devoid of extensive lab automation. This strategy could also be employed as a primary screen profiling microRNA expression in different animal tissues (e.g samples from a variety of brain regions). After the identification of miRNAs that are expressed in any of the pooled samples, the tissue-specific expression of these ‘‘primary hits’’ can be determined by qRT-PCR analysis of the individual samples. In such a study design, the primary screening serves only for the qualitative detection, whereas for the quantitative analysis of microRNA expression, each sample needs to be tested individu- ally. Using pooled samples results in the dilution of each individual sample within the pool, with the consequence of reduced sensitivity during quantitative PCR analysis. The theoretical loss of sensitivity can be calculated as follows: given an ideal amplification efficiency of 100% (E = 100%) with a doubling of the PCR product with each amplification cycle, the slope of a dilution curve (S) could be calculated as 23.322 using the following equation: E = (10e(21/S)21)6100. This means that a ten-fold reduction of template-DNA would result in a 3.322 higher CT value. By pooling five cDNA samples, as we did in the present study, the copy number for a specific target cDNA from one sample is diluted 5-times in the resulting pooled cDNA. Therefore, the loss of sensitivity for each individual sample in the pool is small, as the CT value of transcripts present in only one of the five pooled samples would be 2.322 CT higher than in the individually analyzed sample. Statistically, an average CT value of 35 means, that there are about five copies of the miRNA transcript detected in the PCR reaction [20]. That is why there is no biological relevance of transcripts detected with CT values .35. According to that, the limit of detection in pools of 5 samples is lowered to a CT of 32.7. A big advantage of the SYBR Green-based miRNA PCR assays used in this study is the possibility to quickly verify the specificity of the amplified sequences by studying the melting curves of the miRNA-specific PCR products. These largely uniform amplicons should all display very similar Tms of 75uC. In the rare case that PCR-products with significantly higher melting temperatures were produced these have been proven to be not specific using agarose gel-based fragment size determination. There may be a theoretical risc for cross reactivity between closely related microRNA isoforms, such as from the let-7 family, not distinguishable by melting curve analysis alone. Nevertheless, a recent study has provided evidence for the relatively high specificity of the miRNA PCR assays employed in our present study [21]. For several members of the let-7 family, Kumar et al. could demonstrate that the amplification of related miRNAs was much less efficient than that of the actually analyzed miRNA. Therefore, these unspecific amplicons contribute only to a lesser part to the overall signal. Technically, the pooling of samples for RT-PCR analysis -besides economical aspects- has several benefits compared to gene chip technology platforms usually employed for such screening approaches. Since microarray platforms are less sensitive in the PLoS ONE | www.plosone.org 9 June 2011 | Volume 6 | Issue 6 | e21305