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Comprehensive assessment of multiple biases in small RNA sequencing reveals significant differences in the performance of widely used methods
by
Cross, Alan J.
, Williams, Courtney
, Brandon, Nicholas J.
, Collado-Torres, Leonardo
, Kimos, Martha
, Burke, Emily E.
, Jaffe, Andrew E.
, Shin, Joo Heon
, Rajpurohit, Anandita
, Wright, Carrie
, Weinberger, Daniel R.
in
Analysis
/ Animal Genetics and Genomics
/ Bias (Statistics)
/ Biomedical and Life Sciences
/ Health aspects
/ Identification and classification
/ isomiRs
/ Library preparation
/ Life Sciences
/ Methodology
/ Methodology Article
/ Methods
/ Microarrays
/ Microbial Genetics and Genomics
/ MicroRNA
/ Plant Genetics and Genomics
/ Proteomics
/ RNA
/ RNA sequencing
/ Small RNA sequencing
/ Transcriptomic methods
/ Unique molecular identifiers
2019
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Comprehensive assessment of multiple biases in small RNA sequencing reveals significant differences in the performance of widely used methods
by
Cross, Alan J.
, Williams, Courtney
, Brandon, Nicholas J.
, Collado-Torres, Leonardo
, Kimos, Martha
, Burke, Emily E.
, Jaffe, Andrew E.
, Shin, Joo Heon
, Rajpurohit, Anandita
, Wright, Carrie
, Weinberger, Daniel R.
in
Analysis
/ Animal Genetics and Genomics
/ Bias (Statistics)
/ Biomedical and Life Sciences
/ Health aspects
/ Identification and classification
/ isomiRs
/ Library preparation
/ Life Sciences
/ Methodology
/ Methodology Article
/ Methods
/ Microarrays
/ Microbial Genetics and Genomics
/ MicroRNA
/ Plant Genetics and Genomics
/ Proteomics
/ RNA
/ RNA sequencing
/ Small RNA sequencing
/ Transcriptomic methods
/ Unique molecular identifiers
2019
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Comprehensive assessment of multiple biases in small RNA sequencing reveals significant differences in the performance of widely used methods
by
Cross, Alan J.
, Williams, Courtney
, Brandon, Nicholas J.
, Collado-Torres, Leonardo
, Kimos, Martha
, Burke, Emily E.
, Jaffe, Andrew E.
, Shin, Joo Heon
, Rajpurohit, Anandita
, Wright, Carrie
, Weinberger, Daniel R.
in
Analysis
/ Animal Genetics and Genomics
/ Bias (Statistics)
/ Biomedical and Life Sciences
/ Health aspects
/ Identification and classification
/ isomiRs
/ Library preparation
/ Life Sciences
/ Methodology
/ Methodology Article
/ Methods
/ Microarrays
/ Microbial Genetics and Genomics
/ MicroRNA
/ Plant Genetics and Genomics
/ Proteomics
/ RNA
/ RNA sequencing
/ Small RNA sequencing
/ Transcriptomic methods
/ Unique molecular identifiers
2019
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Comprehensive assessment of multiple biases in small RNA sequencing reveals significant differences in the performance of widely used methods
Journal Article
Comprehensive assessment of multiple biases in small RNA sequencing reveals significant differences in the performance of widely used methods
2019
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Overview
Background
RNA sequencing offers advantages over other quantification methods for microRNA (miRNA), yet numerous biases make reliable quantification challenging. Previous evaluations of these biases have focused on adapter ligation bias with limited evaluation of reverse transcription bias or amplification bias. Furthermore, evaluations of the quantification of isomiRs (miRNA isoforms) or the influence of starting amount on performance have been very limited. No study had yet evaluated the quantification of isomiRs of altered length or compared the consistency of results derived from multiple moderate starting inputs. We therefore evaluated quantifications of miRNA and isomiRs using four library preparation kits, with various starting amounts, as well as quantifications following removal of duplicate reads using unique molecular identifiers (UMIs) to mitigate reverse transcription and amplification biases.
Results
All methods resulted in false isomiR detection; however, the adapter-free method tested was especially prone to false isomiR detection. We demonstrate that using UMIs improves accuracy and we provide a guide for input amounts to improve consistency.
Conclusions
Our data show differences and limitations of current methods, thus raising concerns about the validity of quantification of miRNA and isomiRs across studies. We advocate for the use of UMIs to improve accuracy and reliability of miRNA quantifications.
Publisher
BioMed Central,BioMed Central Ltd,BMC
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