The following description is a generic project plan for performing RNA-Seq experiment, from the management of the sample to the analyses of RNA-Seq data. Such experiment may comprise samples from a setting such as healty vs disease, treated vs placebo, genetically modified organism vs. wild type, or different tissues or time points. The aim of this project is to study transcriptome-wide differences between the samples on the level of genes and pathways.
Pre-analytical management of your sample are critical for the best output of the experiment. At PAREAN biotechnologies, we work in just-in-time model to perform cell biology on fresh sample. After receiving your samples, our team carefully identified and prepares them for cell sorting experiment to manage them in the minimum of time. If you are working with froozen cell, your samples will be biobanked in our facilities.
We create a single-cell suspension and with FACS BD melody, we sort the cell of interest from your samples. Cells are then washed and lysed. Then, RNA are perfectly conserved at -80°C in lysis buffer before RNA extraction.
The protocol begins with RNA purification. You can send us isolated RNA, or sort your cells in preservation reagents before sending them to us. We perform RNA purification in our lab for sorted cells in different preservation reagents. Please, ask us for details.
Quality control of RNA quality and quantity are performed by automated micro-electrophoresis. According to RNA integrity, we choose the right method to amplify your sample and create cDNA library ready to sequence.
For an exhaustive analysis of the transcriptome, we create a library with all the RNA quality control and the cDNA quality and quantity are also performed by automated electrophoresis to ensure the good outcome of the sequencing. Once all these steps are performed, we complete the NGS library preparation and send the sample out for sequencing.
While NGS data analysis provides a lot of information, it simultaneously produces more bioinformatics challenges. The finished NGS libraries are sequenced by one of our partners on the Illumina device. We choose the device function of the sequencing length and depth for a cost-effective sequencing.
When we’ve received the raw sequencing data, we process and control the data to ensure that it is of sufficient quality for the planned analyses. Quality control is a critical step to improve the reproducibility of your biological results. We compute a multi-perspective strategy to remove low-quality data that would interfere with downstream analyses.
Normalization of the data is a critical step that corrects for sample-to-sample or cell-to-cell differences in capture efficiency, sequencing depth, and other technical confounders. This ensures that downstream comparisons of relative expression between cells are valid.
Transcriptome analysis of gene expression help understanding the regulation of biological systems. The first step of analysis is the differential gene expression based on RNA sequencing, single-cell RNA sequencing or microRNA sequencing measurements, that can be combined with other data in a multi-omics integration process.
Although gene expression analysis is the gold standard of RNA sequencing data analysis, there are numerous other transcriptomic markers, such as alternative splicing, allele-specific expression, long non-coding RNA expression, transposable element expression, genetic variants, post-transcriptional events…