UMI Small RNA-seq

UMI small RNA sequencing (RNA-seq) is a unique molecular identifier (UMI)-based technology for accurate qualitative and quantitative analysis of multiple small RNAs in cells. PCR amplification bias can be removed by adding UMI into each cDNA segment, achieving accurate and unbiased quantification. UMI small RNA-seq can accurately identify SNP, quantify low-abundance transcripts, and reveal comprehensive transcriptome information. We provide UMI small RNA-seq to help you analyze microRNA (miRNA), small interfering RNA (siRNA), piwi-interacting RNA (piRNA) at one time.


UMI is a short sequence of 8-10nt, often with degenerate bases. It incorporates a unique barcode onto each cDNA fragments before library amplification, which can exclude quantitative deviations introduced by PCR amplification preference and sequencing preference and increase the sensitivity of variant detection. UMI small RNA-seq is a high-throughput sequencing-based technique that introduces UMI during library construction to deliver accurate, affordable and high-quality information on cell-specific or tissue-specific small RNA profiles in a given state. UMI small RNA-seq enables the identification of small RNA sequences, target gene analysis and functional analysis, and satisfies research needs of various classes of small RNA including miRNA, siRNA, piRNA. UMI Small RNA-seq has been applied to many fields, ranging from scientific research to clinical applications. It accurately profiles and quantitates small RNA fragments, which can provide comprehensive insights into plant/animal growth and development, plant disease resistance, biological characters and regulatory mechanism of genes. In the aspect of disease research, it can be applied to studies of disease mechanisms, screening of biomarkers, and development of targeted drugs.


UMI TechnologyApplicationsRich ExperienceBioinformatics Service
Remove PCR amplification bias, achieve accurate and unbiased transcriptome quantification.Detect low-frequency transcripts, transcript variants, and differential expression.Rich experience in experimental operations, even with low starting amounts.Provide standard and customized bioinformatics analyses, which are reflected in the report.

Project Workflow

Sample Preparation

1. Sample Preparation

A variety of sample types; quality assessment and quantification; rRNA removal; size selection.

Library Preparation

2. Library Preparation

Add a UMI to each cDNA fragment; construction of strand-specific libraries.


3. Sequencing

Illumina HiSeq;
20 million clean reads per sample.

Data Analysis

4. Data Analysis

Perform custom bioinformatics analyses and provide professional data report.

Bioinformatics Analysis Pipeline

Bioinformatics Analysis Pipeline

In-depth data analysis:

  • Classification of small RNA
  • Identification of rRNAs, tRNAs, snRNAs, snoRNAs, etc.
  • Length distribution of small RNA
  • quantitative analysis of small RNA
  • Differential expression analysis of small RNA
  • Predict novel small RNA
  • GO annotation and KEGG pathway analysis
  • Transcription factor annotation
  • GSEA analysis
  • Interactive network analysis

Sample Requirements

Total RNA sample (concentration ≥ 50 ng/uL, quantity ≥ 1 ug)
Plant/fungi: RIN ≥ 7.5, 28S:18S ≥1.3;
Animals/prokaryotes: RIN ≥ 8.0, 28S:18S ≥ 1.5.
Please make sure that the RNA is not significantly degraded.

Sample storage: RNA can be dissolved in ethanol or RNA-free ultra-pure water and stored at -80°C. RNA should avoid repeated freezing and thawing.

Deliverable: FastQ, BAM, coverage summary, QC report, custom bioinformatics analysis.


  1. Macosko E Z, Basu A, Satija R, et al. Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. Cell, 2015, 161: 1202-1214.
  2. Smith, T, Heger, A, Sudbery, I. UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy. Genome Res, 2017, 27, 491-499.
  3. Parekh S, Ziegenhain C, Vieth B, et al. zUMIs-a fast and flexible pipeline to process RNA sequencing data with UMIs. Gigascience, 2018, 7, giy059.
  4. MacConaill L E, Burns R T, Nag A, et al. Unique, dual-indexed sequencing adapters with UMIs effectively eliminate index cross-talk and significantly improve sensitivity of massively parallel sequencing. BMC genomics, 2018, 19(1): 30.
* For Research Use Only. Not for use in diagnostic procedures.

Research Areas
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