The whole-transcriptome analysis is of growing importance in understanding how altered expression of genetic variants contributes to complex diseases such as cancer, diabetes, and heart disease. Analysis of genome-wide differential RNA expression provides researchers with greater insights into biological pathways and molecular mechanisms that regulate cell fate, development, and disease progression. We offer an extensive range of transcriptomic analysis tools: RNA-seq, Microarrays, and RT-qPCR. Core scientists help in every step of the analysis, from RNA purification to bioinformatics analysis of the results.
RNA seq analysis
RNA-seq or RNA sequencing is the transcriptome analysis approach based on parallel (Next-generation) sequencing of entire RNA molecules.
The FGC supports a variety of RNA-seq applications, to help researchers from the University of South Carolina and other institutions of Transcriptome analysis. We are helping with common applications and will help to work with scientists to establish custom applications to fulfill your needs. The FGC supports bulk and single-cell RNA-seq.
3' Tag-Seq (Quant-Seq)
In contrast to other, traditional RNA-seq protocols, 3'-Tag-seq is based on sequencing only one single molecule or “tag” per transcript. complementary to 3' end of the sequences. The advantages of the protocol for differential expression analysis are:
Less sensitive to RNA sample quality/integrity variations (compared to poly-A enrichment protocols)
Requires significantly lower numbers of sequencing reads.
Whole transcript or Poly A mRNA-seq
The sequencing of polyadenylated RNAs, The libraries are prepared from the polyadenylated RNAs purified by Oligo(dT) magnetic beads. Contrary to 3' Tag seq, library-originated fragments cover whole RNA transcript. The advantages of the protocol are:
Less biased to 3' fragments
Determines differential expression of splice isoforms
rRNA depletion or Total RNA-seq.
The sequencing of the entire pool of RNAs starting from ~ 200 bp. Since ribosomal RNAs compiles up to 95% - 99% of total cellular RNAs, the ribosomal RNAs are depleted from the RNA pool by Ribo-Zero or similar procedure. The total RNA-seq of rRNA depleted samples allows us to identify the majority of coding and non-coding RNAs from eukaryotes and bacterias Advantages of rRNA depletion protocol are:
Applicable or transcriptome profiling of eucaryotes, bacterias and the mixtures of bacteria and eukaryotic cells
Determine all coding and noncoding RNAs, including lncRNAs, circular RNAs and eRNAs
less sensitive to RNA sample quality/integrity variations
Small RNA seq
The sequencing of small non-coding RNAs, ~ 12 - 40 bases: miRNAs, piRNAs, snRNAs, and others.
RNA immunoprecipitation sequencing. The sequencing of RNAs co-precipitated with RNA binding proteins.
RNA input - We accept samples with standard (from 100 ng) and low (from 1 pg) amount of RNAs. Low input samples are processed with special library preparation kits.
RNA quality - RNA samples should score a RIN of ≥ 7 on a scale from 1 (highly degraded) to 10 (highest integrity,) Samples with low RIN may not be accepted or require adjustment of RNA-seq protocol. Processing of low RIN samples may incur additional charges
Bioinformatics analysis - We provide bioinformatics support for all the applications.
Basic Bioinformatics: Analysis includes: QC, alignment to the reference genome, differential expression analysis.
Advanced Bioinformatics: Analysis includes: Cluster analysis, functional enrichment analysis, Gene set enrichment analysis and additional analysis requested by scientists
Preparation results for publication: Help with preparation of publication-quality figures and submission of the data to NCBI
For price estimation please look at the Project Price Calculator.
Expression array or microarrays is the transcriptome analysis approach based on hybridization of RNA molecules converted to cDNAs with designed oligonucleotides printed on the solid surface. The results transcriptome analysis with expression arrays is comparable with RNA-seq ones. However, Background hybridization and probe saturation interfere with low-level and high-level detection. Microarrays detect only known sequences, so they can’t be used for the discovery of new variants and transcriptomics analysis of non-model organisms. In spite of limitations, microarrays are reliable tools for transcriptome analysis. The microarray analysis pipeline is significantly shorter than RNA-seq one. The above gives the advantage to the microarray approach for pilot projects and a small number of samples.
The FGC provides the analysis with Affymetrix (currently ThermoFisher Scientific) and Agilent expression arrays.
Affymetrix Arrays - The Core offers analysis with modern Clarion family of expression arrays as well as with previous generations of the arrays. The Clarion family includes Clarion S arrays, allows measuring gene-level expression from >20,000 well-annotated genes and Clarion D, to detect genes, exons, and alternative splicing events that give rise to coding RNA and lncRNA isoforms. The Clarion D arrays designed to detect more than 540,000 different transcripts. Both Clarion D and Clarion S series are available for Human, Mouse and Rat genomes. The expression profiles can be generated from as little as 100 pg of total RNA.
The Core offers microRNA expression analysis with Affymetrix GeneChip miRNA 4.0 Arrays. The analysis required >150 ng of total RNA.
Agilent Arrays - FGC offers analysis with large selection of Gene Expression & Exon Microarrays. This includes whole transcriptome gene expression for almost 30 different species, Exon microarrays to analyze splicing variants and gene expression microarrays with comprehensive content, including full LNCipedia databases to provide full coverage of the transcriptome in a single experiment.
Expression analysis - The core provides access to Affymetrix and Agilent analysis software.
RT-qPCR - Quantitative reverse transcription PCR (RT-qPCR) is used when the starting material is RNA. In this method, RNA is first transcribed into complementary DNA (cDNA) by reverse transcriptase from total RNA or messenger RNA (mRNA). The cDNA is then used as the template for the qPCR reaction. RT-qPCR is used in a variety of applications including gene expression analysis, knockouts, and knockdowns validation, RNA-seq, and microarray validation. FGC offers two major modifications of RT-qPCR: SYBR Green and an internal probe (aka Taq-man) based.
SYBR Green I - is a commonly used fluorescent dye that binds double-stranded DNA molecules by intercalating between the DNA bases. It is used in quantitative PCR because the fluorescence can be measured at the end of each amplification cycle to determine, relatively or absolutely, how much DNA has been amplified. The SYBR green-based assays require two standard PCR primers.
Internal Probe (TaqMan) - Probe-based QPCR relies on the sequence-specific detection of the desired PCR product. Unlike SYBR based QPCR methods that detect all double-stranded DNA, probe-based QPCR utilizes a fluorescent–labeled target-specific probe internal probe. The probe is an additional oligonucleotide hybridized with an amplified fragment. The probe is constructed containing a reporter fluorescent dye on the 5´ end and a quencher dye on the 3´ end. While the probe is intact, the proximity of the quencher dye greatly reduces the fluorescence emitted by the reporter dye by fluorescence resonance energy transfer (FRET) through space. If the target sequence is present, the probe anneals downstream from one of the primer sites and is cleaved by the 5´ nuclease activity of Taq DNA polymerase as this primer is extended, separating the fluorescent dye from the quencher.
The FGC equipped with Bio-RAD CFX384 qPCR systems to perform both SYBR GREEN and TaqMan based assays. We will provide access to the systems, training and assays development and full service, which includes primers selection and validation, Reverse transcription and qPCR, and data analysis.