top of page
This site was designed with the
.com
website builder. Create your website today.Start Now

Transcriptome Sequencing

Discover gene transcription, expression and regulation

Gene Expression Analysis Overview

Gene Expression or Transcriptome has became a cornerstone of modern biomedical research. RNA sequencing or RNA-Seq is the NGS approach to precisely sequence all RNA molecules in an organism. RNA-Seq data is compared to a reference genome in order to calculate the expression level of all RNA transcripts along with a wealth of additional information. This approach is useful for research applications in physiology, cell biology, biomarker discovery, pathology, drug screening, and other fields. We have extensive experience in RNA-Seq and our services include library generation, transcript sequencing and complete data analysis according to your custom requirements.

Advantages

  • Digitized signals -directly determine each RNA fragment sequence at single nucleotide resolution without crosstalk and background clutter common in traditional microarray hybridization

  • Precise gene expression levels are calculated by the RPKM method.

  • High throughput - more than 10 millions reads can be acquired in a single-experiment

  • RNA-seq appraoches offer good reproducility across experiments.

Applications

  • Identify an organism's entire transcriptome

  • identify differentially expressed genes following treatment

  • identify mechanism of pathogenicity

 

Bioinformatics

  • Data QC & Filtering

  • Gene Expression Analysis

  • Differential Gene Expression Analysis

  • Gene Ontology Enrichment Analysis of DEGs

  • Pathway Enrichment Analysis of DEGs

  • PCA Analysis

Small RNA Analysis Overview

Small RNAs include microRNA (miRNA), small interfering RNA (siRNA) and piwi-interacting RNA (piRNA). These small RNAs are about 19-30 nt in length and are involved in the regulation of gene expresiion. Our small RNA sequencing services include total RNA preparation, isolation of small RNAs, Library preparation, sequencing and data analysis. Data analysis can include novel miRNA prediction, miRNA expression analysis, target gene prediction and functional annotation of gene targets.

​

Advantages

  • High throughput: suitable for analysis of multiple samples.

  • High resolution: single base resolution

  • Novel miRNAs can be discovered

Bioinformatics

  • Data QC & Filtering

  • Length distribution of small RNA

  • Explore small RNA distribution across selected genome

  • Identify rRNAs, tRNAs, snRNAs, etc

  • Identify known miRNAs

  • Annotate small RNAs

  • Analyze the expression pattern of known miRNSs

  • Target gene prdiction of novel and known miRNA

  • Target genes prediction of differential miRNA

  • GO and KEGG pathway analysis of known and novel miRNA Target genes

  • GO and KEGG pathway analysis of differential miRNA Target genes

  • Differential expression analysis and cluster analysis of known miRNA

  • Differential expression analysis and cluster analysis of novel miRNA

Transcriptome de novo Assembly Overview

Transcriptome de novo assembly is designed to generate sequence data of your samples under different conditions, including the transcripts of coding and non-coding RNAs. This approach allows for a gene expression analysis as discussed previously, but it also facilities the discovery of novel transcripts, detection of alternative splice variants, and detection of low-expressing transcripts. SNP detection is also available if you are working with a species that has a reference genome sequence. Transcriptome assembly is possible wit rare cell populations, stem cells, circulating tumor cells (CTCs) ancient DNA samples and samples that require difficult RNA extraction methods.

Advantages

  • Complete coverage sequences all RNA transcripts in your sample

  • Wide range of detection: detects both rare transcripts and highly expressed transcripts

  • High resolution: detects alternative splice variants of a gene homologous sequences within a gene family

Applications

  • Transcription assembly for non-model organisms

  • Detection of alternative splice variants

  • Novel transcript variants underlying cancer

  • Non-coding RNA analysis

 

Bioinformatics

  • Data QC & Filtering

  • Transcriptome de novo assembly

  • Unigene annotation (COG and GO classification)

  • Unigene pathway analysis

  • Protein coding region (CDS) prediction

  • Unigene differential expression analysis

  • Gene ontology classification of differentially expressed unigene

  • SNP analysis

IncRNA Analysis Overview

Long non-coding RNAs (IncRNA) are RNA molecules greater than 200 nt that do not code for a protein. IncRNAs are involved in X chromosome inactivation, genomic imprinting, chromatin modification and transcriptional regulation, yet IncRNA research is only in its infancy. NGS promises to accelerate IncRNA discovery and allow for studies looking at IncRNA expression levels during treatment.

​

By reducing ribosomal RNAs first and then using strand-specific primers during library preparation, our NGS pipeline is targeted to IncRNA molecules and we can provide directional information in the final data analysis. Our Final Reports will also include IncRNA expression levels, differential expression during treatment and novel IncRNA discovery.

Advantages

  • High reproducibility: repeated testing of the same sample shows Pearson correlation greater than 0.993

  • A single NGS experiment can reveal nearly all IncRNA information in your sample

  • Data are not limited to known IncRNA, novel IncRNA prediction is also available

  • lncRNA analysis of non-model organisms is also available - we can collaborate with you on all your custom research needs

Applications

  • Biomarker identification

  • Mechanism of gene regulation

 

Bioinformatics

  • Data QC & Filtering

  • Transcripts assembly

  • Known and novel transcript identification

  • Novel lncRNA prediction

  • Quantification and differential expression analysis of lncRNA

  • Up/Down stream lncRNA of a gene

  • Pre-miRNA prediction

bottom of page