TRANSCRIPTOMICS
Expression at Every Resolution
At Nucleome, we decode the dynamic landscape of gene expression to reveal how genomes function in real biological systems. Our transcriptomics solutions provide high-resolution insights into RNA expression, regulation, and cellular heterogeneity, enabling a deeper understanding of biological processes, disease mechanisms, and therapeutic responses.
From full-length transcript discovery to single-cell and spatial profiling, we transform complex transcriptomic data into precise, biologically meaningful interpretations bridging expression data with functional insight and clinical relevance.
Partner with Nucleome to explore the transcriptome with precision, depth, and biological context from single molecules to complex tissues.
Why Transcriptomics Matters
While the genome defines potential, the transcriptome reflects real-time biological activity. Transcriptomics enables:
- Quantification of gene expression changes across conditions and treatments.
- Discovery of novel transcripts, splice variants, and isoforms.
- Identification of regulatory RNAs including miRNA and lncRNA.
- Understanding of cell-type-specific expression and heterogeneity.
- Insights into disease pathways, biomarkers, and therapeutic targets.
At Nucleome, we move beyond expression profiling to deliver context-driven insights that connect transcriptional dynamics with functional biology.
Next-Generation Transcriptomics Ecosystem
At Nucleome, our transcriptomics ecosystem integrates advanced <b/.short-read, long-read, and single-cell RNA sequencing approaches to capture the full spectrum of transcriptional complexity across biological systems. We enable both quantitative and qualitative transcriptome profiling, from high-throughput gene expression analysis to full-length isoform resolution without assembly bias.
Our workflows combine deep RNA-Seq for sensitive detection of gene expression changes, full-length transcript sequencing for accurate isoform and splice variant characterization, and single-cell and spatial transcriptomics to resolve cellular heterogeneity and tissue-level organization.
This multi-dimensional approach allows precise identification of differentially expressed genes, alternative splicing events, gene fusions, and regulatory non-coding RNAs, providing a comprehensive view of transcriptional regulation.
Transcriptomics Bioinformatics & Data Analysis
At Nucleome, we apply robust and scalable bioinformatics pipelines to transform raw RNA sequencing data into high-resolution, biologically meaningful insights. Our workflows encompass stringent quality control, alignment or pseudo-alignment, transcript assembly, and accurate quantification of gene and isoform expression across diverse experimental designs.
We perform comprehensive downstream analyses including differential gene expression (DGE), isoform-level analysis, alternative splicing detection, and gene fusion identification, supported by advanced statistical frameworks to ensure reproducibility and sensitivity.
Functional interpretation is enabled through pathway enrichment, gene ontology (GO) analysis, and regulatory network modelling, providing context to transcriptional changes.
By combining transcriptomic data with other omics layers and clinical metadata, we deliver multi-dimensional insights into gene regulation, disease mechanisms, and biomarker discovery, supporting both research and translational applications.
Our Key Solutions
mRNA Sequencing (Bulk RNA-Seq)
Nucleome’s mRNA sequencing service enables high-resolution profiling of protein-coding gene expression across diverse biological conditions. Designed for transcriptome-wide analysis, this service supports applications ranging from differential expression studies to biomarker discovery and disease mechanism exploration.
Why it should be done:Enables accurate quantification of gene expression changes, identification of disease-associated genes, and discovery of functional pathways and biomarkers.
Small RNA Sequencing
Dedicated profiling of small regulatory RNAs, including miRNA, siRNA, and piRNA, critical for post-transcriptional gene regulation.
Why it should be done:
Essential for understanding gene silencing mechanisms, regulatory networks, and disease-associated miRNA signatures.
Whole Transcriptome Sequencing
Comprehensive sequencing of all RNA species, including coding and non-coding transcripts, providing a global view of transcriptomic activity.
Why it should be done:
Captures the complete transcriptional landscape, enabling deeper insights into gene regulation and system-wide expression dynamics.
Single-Cell RNA Sequencing
High-resolution transcriptomic profiling at the single-cell level, enabling analysis of cellular heterogeneity and rare cell populations.
Why it should be done:Critical for identifying cell subtypes, lineage trajectories, and tumor heterogeneity in complex tissues.
Circular RNA (circRNA) Sequencing
Targeted sequencing of circular RNAs, a class of stable non-coding RNAs involved in gene regulation and disease processes.
Why it should be done: Enables discovery of novel regulatory molecules and potential biomarkers, particularly in cancer and neurological disorders.
DrSeq GEScore Biostimulants Testing
A specialized transcriptomics-based assay to evaluate gene expression changes in response to biostimulants, particularly in agricultural systems.
Why it should be done: Supports functional validation of biostimulants, enabling data-driven decisions for crop performance, stress response, and yield optimization.