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Small RNA-Sequencing for Analysis of Circulating miRNAs: Benchmark Study. J Mol Diagn 2022; 24:386-394. [PMID: 35081459 DOI: 10.1016/j.jmoldx.2021.12.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 11/15/2021] [Accepted: 12/20/2021] [Indexed: 11/22/2022] Open
Abstract
Small RNA-sequencing (RNA-Seq) is being increasingly used for profiling of circulating microRNAs (miRNAs), a new group of promising biomarkers. Unfortunately, small RNA-Seq protocols are prone to biases limiting quantification accuracy, which motivated development of several novel methods. Here, we present comparison of all small RNA-Seq library preparation approaches that are commercially available for quantification of miRNAs in biofluids. Using synthetic and human plasma samples, we compared performance of traditional two-adaptor ligation protocols (Lexogen, Norgen), as well as methods using randomized adaptors (NEXTflex), polyadenylation (SMARTer), circularization (RealSeq), capture probes (EdgeSeq), or unique molecular identifiers (QIAseq). There was no single protocol outperforming others across all metrics. Limited overlap of measured miRNA profiles was documented between methods largely owing to protocol-specific biases. Methods designed to minimize bias largely differ in their performance, and contributing factors were identified. Usage of unique molecular identifiers has rather negligible effect and, if designed incorrectly, can even introduce spurious results. Together, these results identify strengths and weaknesses of all current methods and provide guidelines for applications of small RNA-Seq in biomarker research.
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Mueller RC, Ellström P, Howe K, Uliano-Silva M, Kuo RI, Miedzinska K, Warr A, Fedrigo O, Haase B, Mountcastle J, Chow W, Torrance J, Wood JMD, Järhult JD, Naguib MM, Olsen B, Jarvis ED, Smith J, Eöry L, Kraus RHS. A high-quality genome and comparison of short- versus long-read transcriptome of the palaearctic duck Aythya fuligula (tufted duck). Gigascience 2021; 10:giab081. [PMID: 34927191 PMCID: PMC8685854 DOI: 10.1093/gigascience/giab081] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 07/15/2021] [Accepted: 11/22/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The tufted duck is a non-model organism that experiences high mortality in highly pathogenic avian influenza outbreaks. It belongs to the same bird family (Anatidae) as the mallard, one of the best-studied natural hosts of low-pathogenic avian influenza viruses. Studies in non-model bird species are crucial to disentangle the role of the host response in avian influenza virus infection in the natural reservoir. Such endeavour requires a high-quality genome assembly and transcriptome. FINDINGS This study presents the first high-quality, chromosome-level reference genome assembly of the tufted duck using the Vertebrate Genomes Project pipeline. We sequenced RNA (complementary DNA) from brain, ileum, lung, ovary, spleen, and testis using Illumina short-read and Pacific Biosciences long-read sequencing platforms, which were used for annotation. We found 34 autosomes plus Z and W sex chromosomes in the curated genome assembly, with 99.6% of the sequence assigned to chromosomes. Functional annotation revealed 14,099 protein-coding genes that generate 111,934 transcripts, which implies a mean of 7.9 isoforms per gene. We also identified 246 small RNA families. CONCLUSIONS This annotated genome contributes to continuing research into the host response in avian influenza virus infections in a natural reservoir. Our findings from a comparison between short-read and long-read reference transcriptomics contribute to a deeper understanding of these competing options. In this study, both technologies complemented each other. We expect this annotation to be a foundation for further comparative and evolutionary genomic studies, including many waterfowl relatives with differing susceptibilities to avian influenza viruses.
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Affiliation(s)
- Ralf C Mueller
- Department of Migration, Max Planck Institute of Animal Behavior, Radolfzell, 78315, Germany
- Department of Biology, University of Konstanz, Konstanz, 78457, Germany
| | - Patrik Ellström
- Department of Medical Sciences, Zoonosis Science Center, Uppsala University, Uppsala, SE-75185, Sweden
| | - Kerstin Howe
- Tree of Life, Wellcome Sanger Institute, Cambridge CB10 1SA, UK
| | | | - Richard I Kuo
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK
| | - Katarzyna Miedzinska
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK
| | - Amanda Warr
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK
| | - Olivier Fedrigo
- Vertebrate Genome Laboratory, The Rockefeller University, New York, 10065, NY
| | - Bettina Haase
- Vertebrate Genome Laboratory, The Rockefeller University, New York, 10065, NY
| | | | - William Chow
- Tree of Life, Wellcome Sanger Institute, Cambridge CB10 1SA, UK
| | - James Torrance
- Tree of Life, Wellcome Sanger Institute, Cambridge CB10 1SA, UK
| | | | - Josef D Järhult
- Department of Medical Sciences, Zoonosis Science Center, Uppsala University, Uppsala, SE-75185, Sweden
| | - Mahmoud M Naguib
- Department of Medical Biochemistry and Microbiology, Zoonosis Science Center, Uppsala University, Uppsala, 75237, Sweden
| | - Björn Olsen
- Department of Medical Sciences, Zoonosis Science Center, Uppsala University, Uppsala, SE-75185, Sweden
| | - Erich D Jarvis
- Vertebrate Genome Laboratory and HHMI, The Rockefeller University, New York, 10065, NY
| | - Jacqueline Smith
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK
| | - Lél Eöry
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK
| | - Robert H S Kraus
- Department of Migration, Max Planck Institute of Animal Behavior, Radolfzell, 78315, Germany
- Department of Biology, University of Konstanz, Konstanz, 78457, Germany
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Methyltransferase-directed orthogonal tagging and sequencing of miRNAs and bacterial small RNAs. BMC Biol 2021; 19:129. [PMID: 34158037 PMCID: PMC8220740 DOI: 10.1186/s12915-021-01053-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 05/24/2021] [Indexed: 12/13/2022] Open
Abstract
Background Targeted installation of designer chemical moieties on biopolymers provides an orthogonal means for their visualisation, manipulation and sequence analysis. Although high-throughput RNA sequencing is a widely used method for transcriptome analysis, certain steps, such as 3′ adapter ligation in strand-specific RNA sequencing, remain challenging due to structure- and sequence-related biases introduced by RNA ligases, leading to misrepresentation of particular RNA species. Here, we remedy this limitation by adapting two RNA 2′-O-methyltransferases from the Hen1 family for orthogonal chemo-enzymatic click tethering of a 3′ sequencing adapter that supports cDNA production by reverse transcription of the tagged RNA. Results We showed that the ssRNA-specific DmHen1 and dsRNA-specific AtHEN1 can be used to efficiently append an oligonucleotide adapter to the 3′ end of target RNA for sequencing library preparation. Using this new chemo-enzymatic approach, we identified miRNAs and prokaryotic small non-coding sRNAs in probiotic Lactobacillus casei BL23. We found that compared to a reference conventional RNA library preparation, methyltransferase-Directed Orthogonal Tagging and RNA sequencing, mDOT-seq, avoids misdetection of unspecific highly-structured RNA species, thus providing better accuracy in identifying the groups of transcripts analysed. Our results suggest that mDOT-seq has the potential to advance analysis of eukaryotic and prokaryotic ssRNAs. Conclusions Our findings provide a valuable resource for studies of the RNA-centred regulatory networks in Lactobacilli and pave the way to developing novel transcriptome and epitranscriptome profiling approaches in vitro and inside living cells. As RNA methyltransferases share the structure of the AdoMet-binding domain and several specific cofactor binding features, the basic principles of our approach could be easily translated to other AdoMet-dependent enzymes for the development of modification-specific RNA-seq techniques. Supplementary Information The online version contains supplementary material available at 10.1186/s12915-021-01053-w.
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Benesova S, Kubista M, Valihrach L. Small RNA-Sequencing: Approaches and Considerations for miRNA Analysis. Diagnostics (Basel) 2021; 11:964. [PMID: 34071824 PMCID: PMC8229417 DOI: 10.3390/diagnostics11060964] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/21/2021] [Accepted: 05/24/2021] [Indexed: 01/15/2023] Open
Abstract
MicroRNAs (miRNAs) are a class of small RNA molecules that have an important regulatory role in multiple physiological and pathological processes. Their disease-specific profiles and presence in biofluids are properties that enable miRNAs to be employed as non-invasive biomarkers. In the past decades, several methods have been developed for miRNA analysis, including small RNA sequencing (RNA-seq). Small RNA-seq enables genome-wide profiling and analysis of known, as well as novel, miRNA variants. Moreover, its high sensitivity allows for profiling of low input samples such as liquid biopsies, which have now found applications in diagnostics and prognostics. Still, due to technical bias and the limited ability to capture the true miRNA representation, its potential remains unfulfilled. The introduction of many new small RNA-seq approaches that tried to minimize this bias, has led to the existence of the many small RNA-seq protocols seen today. Here, we review all current approaches to cDNA library construction used during the small RNA-seq workflow, with particular focus on their implementation in commercially available protocols. We provide an overview of each protocol and discuss their applicability. We also review recent benchmarking studies comparing each protocol's performance and summarize the major conclusions that can be gathered from their usage. The result documents variable performance of the protocols and highlights their different applications in miRNA research. Taken together, our review provides a comprehensive overview of all the current small RNA-seq approaches, summarizes their strengths and weaknesses, and provides guidelines for their applications in miRNA research.
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Affiliation(s)
- Sarka Benesova
- Laboratory of Gene Expression, Institute of Biotechnology, CAS, BIOCEV, 252 50 Vestec, Czech Republic; (S.B.); (M.K.)
- Laboratory of Informatics and Chemistry, Faculty of Chemical Technology, University of Chemistry and Technology, 166 28 Prague, Czech Republic
| | - Mikael Kubista
- Laboratory of Gene Expression, Institute of Biotechnology, CAS, BIOCEV, 252 50 Vestec, Czech Republic; (S.B.); (M.K.)
- TATAA Biocenter AB, 411 03 Gothenburg, Sweden
| | - Lukas Valihrach
- Laboratory of Gene Expression, Institute of Biotechnology, CAS, BIOCEV, 252 50 Vestec, Czech Republic; (S.B.); (M.K.)
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Li Y, Fehlmann T, Borcherding A, Drmanac S, Liu S, Groeger L, Xu C, Callow M, Villarosa C, Jorjorian A, Kern F, Grammes N, Meese E, Jiang H, Drmanac R, Ludwig N, Keller A. CoolMPS: evaluation of antibody labeling based massively parallel non-coding RNA sequencing. Nucleic Acids Res 2021; 49:e10. [PMID: 33290507 PMCID: PMC7826284 DOI: 10.1093/nar/gkaa1122] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 10/02/2020] [Accepted: 11/26/2020] [Indexed: 12/16/2022] Open
Abstract
Results of massive parallel sequencing-by-synthesis vary depending on the sequencing approach. CoolMPS™ is a new sequencing chemistry that incorporates bases by labeled antibodies. To evaluate the performance, we sequenced 240 human non-coding RNA samples (dementia patients and controls) with and without CoolMPS. The Q30 value as indicator of the per base sequencing quality increased from 91.8 to 94%. The higher quality was reached across the whole read length. Likewise, the percentage of reads mapping to the human genome increased from 84.9 to 86.2%. For both technologies, we computed similar distributions between different RNA classes (miRNA, piRNA, tRNA, snoRNA and yRNA) and within the classes. While standard sequencing-by-synthesis allowed to recover more annotated miRNAs, CoolMPS yielded more novel miRNAs. The correlation between the two methods was 0.97. Evaluating the diagnostic performance, we observed lower minimal P-values for CoolMPS (adjusted P-value of 0.0006 versus 0.0004) and larger effect sizes (Cohen's d of 0.878 versus 0.9). Validating 19 miRNAs resulted in a correlation of 0.852 between CoolMPS and reverse transcriptase-quantitative polymerase chain reaction. Comparison to data generated with Illumina technology confirmed a known shift in the overall RNA composition. With CoolMPS we evaluated a novel sequencing-by-synthesis technology showing high performance for the analysis of non-coding RNAs.
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Affiliation(s)
- Yongping Li
- Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany
- MGI, BGI-Shenzhen, Shenzhen 518083, China
| | - Tobias Fehlmann
- Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany
| | | | | | - Sophie Liu
- Complete Genomics Incorporated, San Jose, CA 95134, USA
| | - Laura Groeger
- Department of Human Genetics, Saarland University, 66421 Homburg, Germany
| | - Chongjun Xu
- MGI, BGI-Shenzhen, Shenzhen 518083, China
- Complete Genomics Incorporated, San Jose, CA 95134, USA
- BGI-Shenzhen, Shenzhen 518083, China
- China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | | | | | | | - Fabian Kern
- Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany
| | - Nadja Grammes
- Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany
| | - Eckart Meese
- Department of Human Genetics, Saarland University, 66421 Homburg, Germany
| | - Hui Jiang
- MGI, BGI-Shenzhen, Shenzhen 518083, China
| | - Radoje Drmanac
- MGI, BGI-Shenzhen, Shenzhen 518083, China
- Complete Genomics Incorporated, San Jose, CA 95134, USA
- BGI-Shenzhen, Shenzhen 518083, China
- China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Nicole Ludwig
- Department of Human Genetics, Saarland University, 66421 Homburg, Germany
| | - Andreas Keller
- Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany
- Department of Neurology and Neurological Sciences, Stanford UniversitySchool of Medicine, Stanford, CA 94304, USA
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Valihrach L, Androvic P, Kubista M. Circulating miRNA analysis for cancer diagnostics and therapy. Mol Aspects Med 2020; 72:100825. [DOI: 10.1016/j.mam.2019.10.002] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 10/01/2019] [Accepted: 10/07/2019] [Indexed: 12/12/2022]
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