Dataset Information

Application of third-generation sequencing to herbal genomics.

ABSTRACT: There is a long history of traditional medicine use. However, little genetic information is available for the plants used in traditional medicine, which limits the exploitation of these natural resources. Third-generation sequencing (TGS) techniques have made it possible to gather invaluable genetic information and develop herbal genomics. In this review, we introduce two main TGS techniques, PacBio SMRT technology and Oxford Nanopore technology, and compare the two techniques against Illumina, the predominant next-generation sequencing technique. In addition, we summarize the nuclear and organelle genome assemblies of commonly used medicinal plants, choose several examples from genomics, transcriptomics, and molecular identification studies to dissect the specific processes and summarize the advantages and disadvantages of the two TGS techniques when applied to medicinal organisms. Finally, we describe how we expect that TGS techniques will be widely utilized to assemble telomere-to-telomere (T2T) genomes and in epigenomics research involving medicinal plants.

SUBMITTER: Gao L

PROVIDER: S-EPMC10027759 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Application of third-generation sequencing to herbal genomics.

Gao Longlong L Xu Wenjie W Xin Tianyi T Song Jingyuan J

Frontiers in plant science 20230307

There is a long history of traditional medicine use. However, little genetic information is available for the plants used in traditional medicine, which limits the exploitation of these natural resources. Third-generation sequencing (TGS) techniques have made it possible to gather invaluable genetic information and develop herbal genomics. In this review, we introduce two main TGS techniques, PacBio SMRT technology and Oxford Nanopore technology, and compare the two techniques against Illumina, ...[more]

PMID: 36959935

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Project description:BackgroundDNA-based testing has been gaining acceptance as a tool for authentication of a wide range of food products; however, its applicability for testing of herbal supplements remains contentious.MethodsWe utilized Sanger and Next-Generation Sequencing (NGS) for taxonomic authentication of fifteen herbal supplements representing three different producers from five medicinal plants: Echinacea purpurea, Valeriana officinalis, Ginkgo biloba, Hypericum perforatum and Trigonella foenum-graecum. Experimental design included three modifications of DNA extraction, two lysate dilutions, Internal Amplification Control, and multiple negative controls to exclude background contamination. Ginkgo supplements were also analyzed using HPLC-MS for the presence of active medicinal components.ResultsAll supplements yielded DNA from multiple species, rendering Sanger sequencing results for rbcL and ITS2 regions either uninterpretable or non-reproducible between the experimental replicates. Overall, DNA from the manufacturer-listed medicinal plants was successfully detected in seven out of eight dry herb form supplements; however, low or poor DNA recovery due to degradation was observed in most plant extracts (none detected by Sanger; three out of seven-by NGS). NGS also revealed a diverse community of fungi, known to be associated with live plant material and/or the fermentation process used in the production of plant extracts. HPLC-MS testing demonstrated that Ginkgo supplements with degraded DNA contained ten key medicinal components.ConclusionQuality control of herbal supplements should utilize a synergetic approach targeting both DNA and bioactive components, especially for standardized extracts with degraded DNA. The NGS workflow developed in this study enables reliable detection of plant and fungal DNA and can be utilized by manufacturers for quality assurance of raw plant materials, contamination control during the production process, and the final product. Interpretation of results should involve an interdisciplinary approach taking into account the processes involved in production of herbal supplements, as well as biocomplexity of plant-plant and plant-fungal biological interactions.

Project description:BackgroundThird-generation sequencing offers some advantages over next-generation sequencing predecessors, but with the caveat of harboring a much higher error rate. Clustering-related sequences is an essential task in modern biology. To accurately cluster sequences rich in errors, error type and frequency need to be accounted for. Levenshtein distance is a well-established mathematical algorithm for measuring the edit distance between words and can specifically weight insertions, deletions and substitutions. However, there are drawbacks to using Levenshtein distance in a biological context and hence has rarely been used for this purpose. We present novel modifications to the Levenshtein distance algorithm to optimize it for clustering error-rich biological sequencing data.ResultsWe successfully introduced a bidirectional frameshift allowance with end-user determined accommodation caps combined with weighted error discrimination. Furthermore, our modifications dramatically improved the computational speed of Levenstein distance. For simulated ONT MinION and PacBio Sequel datasets, the average clustering sensitivity for 3GOLD was 41.45% (S.D. 10.39) higher than Sequence-Levenstein distance, 52.14% (S.D. 9.43) higher than Levenshtein distance, 55.93% (S.D. 8.67) higher than Starcode, 42.68% (S.D. 8.09) higher than CD-HIT-EST and 61.49% (S.D. 7.81) higher than DNACLUST. For biological ONT MinION data, 3GOLD clustering sensitivity was 27.99% higher than Sequence-Levenstein distance, 52.76% higher than Levenshtein distance, 56.39% higher than Starcode, 48% higher than CD-HIT-EST and 70.4% higher than DNACLUST.ConclusionOur modifications to Levenshtein distance have improved its speed and accuracy compared to the classic Levenshtein distance, Sequence-Levenshtein distance and other commonly used clustering approaches on simulated and biological third-generation sequenced datasets. Our clustering approach is appropriate for datasets of unknown cluster centroids, such as those generated with unique molecular identifiers as well as known centroids such as barcoded datasets. A strength of our approach is high accuracy in resolving small clusters and mitigating the number of singletons.

Dataset Information

Application of third-generation sequencing to herbal genomics.

Publications

Application of third-generation sequencing to herbal genomics.

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