Denovo and Reference-Based RNASeq

At Landmark Research Insights (LRI), we specialise in pioneering RNA sequencing services, equipping researchers to navigate the intricate realm of RNA with precision and depth. Our Denovo and Reference-Based RNASeq services are meticulously crafted to unveil the treasure trove of knowledge concealed within RNA transcripts, whether in model or non-model organisms.

Denovo and Reference-Based RNASeq: Illuminating the Transcriptome

Understanding RNA-Seq: 

RNA-Seq has emerged as a powerful method for exploring the complete spectrum of RNA transcripts, encompassing mRNA, rRNA, tRNA, and other non-coding RNA. It excels at capturing gene expression by sequencing cDNA libraries derived from mRNA. Unlike the stable genome, the transcriptome is dynamically changing. Whole transcriptome analysis allows for discovering rare genes, mRNA profiling, gene expression analysis, splice junctions, gene fusions, pathway elucidation, and the detection of novel transcripts. 

Our Comprehensive RNASeq Services:

• Bacterial/Fungus/Animal/Plant Denovo RNASeq: Excelling in non-model organism research, utilizing De-novo transcriptome assembly techniques to efficiently analyze short Illumina reads.

• Reference-Based RNASeq: Our preferred approach for model organisms, where reads are mapped to a reference genome to extract valuable insights.

Sequencing Technology: 

Sequencing will be carried out on the state-of-the-art Illumina Novaseq platform with 2x150 for RNA v2 chemistry, ensuring high-quality data and reliable results.

Pricing:

• Experimental Design Consulting: 250 euros per project

• Data Analysis Pipeline Creation: 550 euros per project

Our Workflow and Deliverables:

Workflow:

a. Quality Check of Raw Reads:

• Rigorous quality filtration and adapter trimming.

• Removal of primer sequences, poly(A) tails, and reads originating from ribosomal DNA templates.

• Utilization of high-quality data for downstream analysis.

b. Denovo Assembly:

• Expert De-novo transcriptome assembly using optimized parameters.

• Assembly evaluation based on transcriptome length, transcript N50, and length distribution of transcripts.

• Clustering of non-redundant transcripts into unigenes.

c. Coding Sequence (CDS) Prediction:

• Utilization of TransDecoder to predict coding sequences from unigenes.

d. Functional Annotation:

• Annotation of predicted CDS against NCBI non-redundant protein database (Nr), Swissprot, Kyoto Encyclopedia of Genes and Genomes (KEGG), Cluster of Orthologous Group (COG) databases using Basic Local Alignment Search Tool (BlastX).

e. Functional Annotation of KEGG Pathway:

• Mapping of CDS to reference canonical pathways in KEGG.

• Classification of CDS into Metabolism, Cellular processes, Genetic information processing, and Environmental information processing categories.

f. Functional Annotation of Gene Ontology Analysis:

• Identification of abundant GO terms related to biological processes, Molecular function, and Cellular components.

• GO term assignment for functional categorization.

g. Transcription Factor Analysis:

• Search for transcription factors (TFs) among predicted CDS using plant transcription factor databases.

h. Simple Sequence Repeat (SSR) Identification:

• Detection of SSRs in assembled unigenes, crucial for various genetic applications.

i. Differential Gene Expression Analysis:

• Differential expression analysis based on FPKM values.

• Identification of significantly expressed transcripts between experimental and control conditions using DESeq.

• Visualization through Heat Maps, Volcano Plots, and Scatter Plots.

Deliverables:

Denovo-based RNASeq:

• Quality-filtered reads

• Denovo assembly generating transcript/unigene

• Summary statistics

• CDS prediction

• Functional annotation

• KEGG pathway analysis

• Gene ontology analysis

• SSR Identification

• Differential gene expression analysis

• Comprehensive report with publication-standard methodology, graphs, and tables.

Reference-based RNASeq:

• Quality-filtered reads

• Mapping on the reference genome

• Alignment summary statistics

• Differential gene expression analysis based on RPKM/FPKM

• Functional annotation of differentially expressed genes

• List of upregulated and downregulated genes

• Statistical significant genes

• Heat Maps, Volcano Plots, Scatter Plots

• Pathway analysis

• SNP analysis

• SSR Identification

• .bam file for visualization of alignment

• Comprehensive report with publication-standard methodology.

LRI - Pioneering Precision in RNA Exploration!

For specific cases or custom requirements not covered by our standard packages, please email us at info@landmarkresearchinsights.com