Biomarker discovery: quantification of microRNAs and other small non-coding RNAs using next generation sequencing.

BACKGROUND: Small ncRNAs (sncRNAs) offer great hope as biomarkers of disease and response to treatment. This has been highlighted in the context of several medical conditions such as cancer, liver disease, cardiovascular disease, and central nervous system disorders, among many others. Here we assessed several steps involved in the development of an ncRNA biomarker discovery pipeline, ranging from sample preparation to bioinformatic processing of small RNA sequencing data. METHODS: A total of 45 biological samples were included in the present study. All libraries were prepared using the Illumina TruSeq Small RNA protocol and sequenced using the HiSeq2500 or MiSeq Illumina sequencers. Small RNA sequencing data was validated using qRT-PCR. At each stage, we evaluated the pros and cons of different techniques that may be suitable for different experimental designs. Evaluation methods included quality of data output in relation to hands-on laboratory time, cost, and efficiency of processing. RESULTS: Our results show that good quality sequencing libraries can be prepared from small amounts of total RNA and that varying degradation levels in the samples do not have a significant effect on the overall quantification of sncRNAs via NGS. In addition, we describe the strengths and limitations of three commercially available library preparation methods: (1) Novex TBE PAGE gel; (2) Pippin Prep automated gel system; and (3) AMPure XP beads. We describe our bioinformatics pipeline, provide recommendations for sequencing coverage, and describe in detail the expression and distribution of all sncRNAs in four human tissues: whole-blood, brain, heart and liver. CONCLUSIONS: Ultimately this study provides tools and outcome metrics that will aid researchers and clinicians in choosing an appropriate and effective high-throughput sequencing quantification method for various study designs, and overall generating valuable information that can contribute to our understanding of small ncRNAs as potential biomarkers and mediators of biological functions and disease.

Common polymorphisms in the promoter of the visfatin gene (PBEF1) influence plasma insulin levels in a French-Canadian population.

The adipokine visfatin (PBEF1) exhibits insulin-mimetic effects and correlates strongly with visceral adiposity. We sequenced visfatin gene exons and 1,480 bp of the promoter in 23 individuals, including 18 individuals from the Quebec Family Study (QFS) with varying degrees of abdominal visceral fat, assessed by computed tomography, and 5 individuals from the Saguenay-Lac-Saint-Jean region of Québec. We identified a synonymous polymorphism in exon 7 (SER301SER) but no nonsynonymous mutations. We observed an additional 10 polymorphisms, including 5 intronic, 4 within the promoter, and 1 within the 3' untranslated region. Further promoter sequencing (816 bp) identified five additional single nucleotide polymorphisms (SNPs) in the QFS population. To investigate the role of visfatin gene variants in obesity-related phenotypes, we genotyped a total of 13 SNPs in the promoter region of the gene. From these, we analyzed the seven common SNPs in the QFS sample (918 participants from 208 families). A significant association was found between two SNPs (rs9770242 and rs1319501), in perfect linkage disequilibrium, and fasting insulin levels (P = 0.002). These SNPs were also associated with fasting glucose (P