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Overcome the Challenges of Small RNA Profiling


Small RNAs include miRNAs, pre-miRNAs, tsRNAs, tRNAs and snoRNAs. Even though RNA-seq has been used for profiling small RNAs, we need to overcome several major challenges unique to these small RNA classes in order to accurately profile their whole spectrum, especially for samples at limited amount.


• Interference from RNA Modifications

Small RNA modifications (e.g. m1A, m3C and m1G, particularly heavily in tRNAs and tsRNAs) block reverse transcription, causing failures in constructing full length unskewed representation of the sequencing library.

• Library Amplification Biases

RNA G/C content, sequence contexts, secondary structures, RNA lengths, priming, and reaction conditions can lead to biases and distortions in the PCR amplification of the sequencing library [1].

• Distortions in Small RNA-seq Data Analysis using TPM

TPM, a commonly used measure in small RNA-seq data analysis, is dependent on the composition of the RNA population in a sample [2,3](Fig 1).

• Sample Amounts Required

For small RNA-sequencing of tRNA and tsRNA, 5ug or even 100ug total RNA is required for target RNA isolation and pretreatments [5], which precludes research projects with limited sample amount availability.


Fig 1. A few very highly expressed genes can skew the distribution of TPM expression values [4].


Our Solution

Arraystar Small RNA Array.is designed to overcome these challenges to profile the full spectrum of small RNAs at high sensitivity and accuracy, yet requiring much less sample RNA amounts. It combines direct end-labeling and smart probe design microarray technologies to detect and quantify miRNAs, pre-miRNAs, tsRNAs, tRNAs and snoRNAs simultaneously on the same array, opening up more opportunities for exploring their biomarker potentials.



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References
[1]  Dabney J. and Meyer M. (2012) Biotechniques [PMID:22313406]
[2]  Zhao, Y., et al. (2021) J Transl Med [PMID: 34158060]
[3]  Zhao, S., et al. (2020) RNA [PMID: 32284352]
[4]  Witwer, K. W. and Halushka, M. K. (2016) RNA Biol [PMID: 27645402]
[5]  Junchao S., et al. (2021) Nat Cell Biol [PMID: 33927371]



Selected Publications

• Epitranscriptomic Array
   [PMID: 38355624] Xiong YW, et al.
   (2024) Nature Communications

• Small RNA Modification Array
   [PMID: 38747146] Zhang J, et al.
   (2024) Circulation Research

• Circular RNA Array
   [PMID: 39695693] Hu Y, et al.
   (2024) Molecular Cancer

• tRNA Sequencing
   [PMID: 38519786] Wu X, et al.
   (2024) Nature Cancer

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CircRNA Array Service
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Valid 06/01/2025 - 08/31/2025

 
 
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