RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated with the Illumina platform, and to perform a cross-platform comparison based on the results obtained through Affymetrix microarray. As a case study for our work we, used the Saccharomyces cerevisiae strain CEN.PK 113-7D, grown under two different conditions (batch and chemostat). Here, we asses the influence of genetic variation on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and TopHat) on S288c genome, the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and NOISeq) and we explored the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays) for gene expression analysis and addresses the contribution of the different steps involved in the analysis of RNA-seq data.

OBJECTIVE -To assess the 24-h glucose levels in a group of nondiabetic, nonobese pregnant women and to verify the presence of correlations between maternal glucose levels and sonographic parameters of fetal growth. RESEARCH DESIGN AND METHODS -A total of 66Caucasian nonobese pregnant women with normal glucose challenge tests (GCT) enrolled in the study; from this population, we selected 51 women who delivered term (from 37 to 42 weeks completed) live-born infants without evidence of congenital malformations. The women were requested to have three main meals and to perform daily glucose profiles fortnightly from 28 -38 weeks without modifying their lifestyle or following any dietary restriction. All subjects were taught how to monitor their blood glucose by using a reflectance meter. Fetal biometry was evaluated by ultrasound scan according to standard methodology at 22, 28, 32, and 36 weeks of pregnancy.RESULTS -The overall daily mean glucose level during the third trimester was 74.7 Ϯ 5.2 mg/dl. Daily mean glucose values increased between 28 (71.9 Ϯ 5.7 mg/dl) and 38 (78.3 Ϯ 5.4 mg/dl) weeks of pregnancy. We found a significant positive correlation at 28 weeks between 1-h postprandial glucose values and fetal abdominal circumference (AC). At 32 weeks, we documented positive correlations between fetal AC and maternal blood glucose levels 1 h after breakfast, 1 and 2 h after lunch, and 1 and 2 h after dinner. At 36 weeks, there was a positive correlation between fetal AC and 1-and 2-h postprandial blood glucose levels. In addition, there was a negative correlation between head-abdominal circumference ratio and 1-h postprandial blood glucose values.CONCLUSIONS -This longitudinal study first provides a contribution toward the definition of normoglycemia in nondiabetic, nonobese pregnant women; moreover, it reveals significant correlations of postprandial blood glucose levels with the growth of insulin-sensitive fetal tissues and, in particular, between 1-h postprandial blood glucose values and fetal AC. Diabetes Care 24:1319 -1323, 2001T he complex phenomenon of fetal growth has been thoroughly investigated over past decades (1) but still remains to be fully understood. We know that maternal glucose is one of the most important factors of influence (1,2), and Reece et al. (3) showed that normoglycemia in pregnancy is associated with normal levels of other nutrients, such as amino acids and lipids. For this reason, glycemia is the single maternal metabolic parameter routinely assessed in diabetic pregnancies. Indeed, the criteria for metabolic control and therapeutic strategies of diabetes in pregnancy are based almost exclusively on maternal glucose levels (2). Although there is overwhelming evidence that good perinatal outcomes can be achieved in diabetic pregnancies only with the normalization of maternal glucose values (4 -6), there is no clear definition of normoglycemia in nondiabetic pregnancies. In fact, a very limited number of studies have been performed thus far in the attempt to define maternal glucose l...

BackgroundScheffersomyces stipitis is a Crabtree negative yeast, commonly known for its capacity to ferment pentose sugars. Differently from Crabtree positive yeasts such as Saccharomyces cerevisiae, the onset of fermentation in S. stipitis is not dependent on the sugar concentration, but is regulated by a decrease in oxygen levels. Even though S. stipitis has been extensively studied due to its potential application in pentoses fermentation, a limited amount of information is available about its metabolism during aerobic growth on glucose. Here, we provide a systems biology based comparison between the two yeasts, uncovering the metabolism of S. stipitis during aerobic growth on glucose under batch and chemostat cultivations.ResultsStarting from the analysis of physiological data, we confirmed through 13C-based flux analysis the fully respiratory metabolism of S. stipitis when growing both under glucose limited or glucose excess conditions. The patterns observed showed similarity to the fully respiratory metabolism observed for S. cerevisiae under chemostat cultivations however, intracellular metabolome analysis uncovered the presence of several differences in metabolite patterns. To describe gene expression levels under the two conditions, we performed RNA sequencing and the results were used to quantify transcript abundances of genes from the central carbon metabolism and compared with those obtained with S. cerevisiae. Interestingly, genes involved in central pathways showed different patterns of expression, suggesting different regulatory networks between the two yeasts. Efforts were focused on identifying shared and unique families of transcription factors between the two yeasts through in silico transcription factors analysis, suggesting a different regulation of glycolytic and glucoenogenic pathways.ConclusionsThe work presented addresses the impact of high-throughput methods in describing and comparing the physiology of Crabtree positive and Crabtree negative yeasts. Based on physiological data and flux analysis we identified the presence of one metabolic condition for S. stipitis under aerobic batch and chemostat cultivations, which shows similarities to the oxidative metabolism observed for S. cerevisiae under chemostat cultivations. Through metabolome analysis and genome-wide transcriptomic analysis several differences were identified. Interestingly, in silico analysis of transciption factors was useful to address a different regulation of mRNAs of genes involved in the central carbon metabolism. To our knowledge, this is the first time that the metabolism of S. stiptis is investigated in details and is compared to S. cerevisiae. Our study provides useful results and allows for the possibility to incorporate these data into recently developed genome-scaled metabolic, thus contributing to improve future industrial applications of S. stipitis as cell factory.