The MACE-Seq kit for accurate and fast 3’mRNA Sequencing with UMIs and UDIs


Transcriptomics from 0.05 ng of totalRNA

Our highly successful MACE-Seq service is now also available as a kit. It contains all ingredients to perform MACE-Seq. In contrast to other “3’mRNA Seq”  or “Tag-Seq” approaches the MACE-Seq Kit includes our patented TrueQuant method (molecular barcodes; Unique Molecular Identifiers, UMIs) to avoid PCR-bias, for the generation of qualitative and quantitative accurate data on any Illumina sequencing machine. MACE-Seq allows for accurate and cost efficient high-resolution gene expression profiling, genotyping in transcripts, allele frequency determination and the analysis of alternative polyadenylation. Up to 386 samples can be processed in parallel.

The low input requirements make it ideal for the analyses of exosomal / EV-cargo or from laser capture microdissected material (LCM). The kit works also very well with low amounts of FFPE-derived RNA.


The MACE-seq kit comes with optional bioinformatics-vouchers for a convenient analysis of the data on our servers.  As MACE data have some specificities, we have developed an optimized analysis pipeline that you can access using the vouchers. Simply upload your data using the provided voucher-codes to our servers. We provide complete result tables compatible with Excel, as well as plots of your data and Gene Ontology enrichment analyses. The raw and the refined data is accessible via our easily understandable web interface at

Further bioinformatics analyses are possible e.g. SNP-analysis, alternative polyadenylation or allele frequency determination (see Bioinformatics).

Therefore you do not need bioinformatians nor special hardware for the detailed analysis of the complex data.

MACE-Seq construct with Unique Dual Indices (UDI)

The latest version of our kit uses unique-dual-indexing to avoid read-misassignment due to “index-hopping” during the illumina sequencing

Our kit uses UMIs and UDIs in its standard version and optional  highly standardized and peer-reviewed published Bioinformatics. 

Technical Variance

the pearson correllation between three technical replicates using MACE-seq from 5 ng of total RNA is shown below. Values of >0,996 demonstrate very high technical reliability.

5 ng – 1 5 ng – 2 5 ng – 3
5 ng – 1 1
5 ng – 2 0,996987 1
5 ng – 3 0,996446 0,99798 1

Sensitivity and reliability for low input

MACE-seq requires only 0,05 ng of total RNA as input while maintaining consistent transcript quantification. As shown in the table below, the pearson correlation between MACE-seq transcription profiles from 100 ng and 1 ng of total RNA input is 0,96 and 0,87 between data from 100 ng and 0,05 ng total RNA. The lower pearson correlation in the later comparison is due to a reduced number of low-level transcripts in the 0.05 ng sample.

total RNA 0.05 ng 0.1 ng 0.5 ng 1 ng 5 ng 25 ng 100 ng
0.05 ng 1
0.1 ng 0,830518 1
0.5 ng 0,881877 0,923032 1
1 ng 0,864297 0,896227 0,939137 1
5 ng 0,864884 0,898313 0,940447 0,995379 1
25 ng 0,871146 0,89844 0,943703 0,978482 0,986371 1
100 ng 0,867123 0,888887 0,936261 0,959999 0,969597 0,995612 1

Sequence your MACE -Seq libraries with other NGS-libraries

Because MACE-Sequencing does not require any specific sequencing primers but uses the standard primers for Illumina machines, you can easily sequence your MACE-Seq projects with other projects simultanteously.

Kit sizes and parameters

our kit is available fo 6, 24 and 96 reactions. Required starting material is 0.05 ng-200 ng of totalRNA.  Library preparation requires 4-6 hours. Please request manual at


Please use our quotation and ordering page send us an e-mail at or give us a call at: +49 69 95739710


Please contact us for a trial kit at

Customers in Japan: please contact FUNAKOSHI.


We also offer MACE-Seq as a service including optional RNA extraction and bioinformatics.


Our kit received five Stars from “BIOZ

Tushev G, Glock C, Heumüller M, Biever A, Jovanovic M, Schuman EM.Alternative 3′ UTRs Modify the Localization, Regulatory Potential, Stability, and Plasticity of mRNAs in Neuronal Compartments.Neuron. 2018 May 2;98(3):495-511

Tosches MA, Yamawaki TM, Naumann RK, Jacobi AA, Tushev G, Laurent G. Evolution of pallium, hippocampus, and cortical cell types revealed by single-cell transcriptomics in reptiles. Science. 2018 May 25;360(6391):881-888.

Agarwal R, Cao Y, Hoffmeier K, Krezdorn N, Jost L, Meisel AR, Jüngling R, Dituri F, Mancarella S, Rotter B, Winter P, Giannelli G.Precision medicine for hepatocelluar carcinoma using molecular pattern diagnostics: results from a preclinical pilot study. Cell Death Dis. 2017 Jun 8;8(6):e2867.

Casado-Díaz A, Anter J, Müller S, Winter P, Quesada-Gómez JM, Dorado G. Transcriptomic Analyses of Adipocyte Differentiation From Human Mesenchymal Stromal-Cells (MSC). J Cell Physiol. 2016 Jun 28

Hofer TP, Zawada AM, Frankenberger M, Skokann K, Satzl AA, Gesierich W,
Schuberth M, Levin J, Danek A, Rotter B, Heine GH, Ziegler-Heitbrock L. slan-defined subsets of CD16-positive monocytes:Characterization of subsets of the CD16-positive monocytes: impact of granulomatous inflammation and M-CSF-receptor mutation. Blood. 2015 Oct 6. pii: blood-2015-06-651331.

Nold-Petry CA, Lo CY, Rudloff I, Elgass KD, Li S, Gantier MP, Lotz-Havla AS, Gersting SW, Cho SX, Lao JC, Ellisdon AM, Rotter B, Azam T, Mangan NE, Rossello FJ, Whisstock JC, Bufler P, Garlanda C, Mantovani A, Dinarello CA, Nold MF. IL-37 requires the receptors IL-18Ra and IL-1R8 (SIGIRR) to carry out its multifaceted anti-inflammatory program upon innate signal transduction.Nat Immunol. 2015 Mar 2

More references at: 


The MACE-kit is for research use only.

For orders or quotation requests, please use our web-tool

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