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Pacific Biosciences third generation long-read sequencing
16S rRNA amplicon <t>sequencing</t> diversity analyses between commercial DNA extraction kits. A Species-level alpha diversity of the samples from each DNA extraction kit (following rarefaction) across the dataset, represented by observed Shannon, Simpson, and Chao1 indices. Analysis between groups shown using paired t-test with Benjamini–Hochberg multiple testing correction (after testing for normality using a Shapiro-Wilks test). B Species-level principal coordinate analysis (PCoA) of the samples from each DNA extraction kit across the dataset. C Relative abundance of expected 16S rRNA gene within the ZMC for each genus, and the 16S rRNA gene amplicon relative abundances achieved using each DNA extraction kit. The genus abundance was ascertained through the use of 16S rRNA gene amplicon sequencing using the LSK112 kit
Third Generation Long Read Sequencing, supplied by Pacific Biosciences, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/third-generation+long-read+sequencing/long+read+sequencing+platforms/pmc12054170-29-5-14
Average 90 stars, based on 1 article reviews
third generation long-read sequencing - by Bioz Stars, 2026-10
90/100 stars

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1) Product Images from "Impact of microbiological molecular methodologies on adaptive sampling using nanopore sequencing in metagenomic studies"

Article Title: Impact of microbiological molecular methodologies on adaptive sampling using nanopore sequencing in metagenomic studies

Journal: Environmental Microbiome

doi: 10.1186/s40793-025-00704-7

16S rRNA amplicon sequencing diversity analyses between commercial DNA extraction kits. A Species-level alpha diversity of the samples from each DNA extraction kit (following rarefaction) across the dataset, represented by observed Shannon, Simpson, and Chao1 indices. Analysis between groups shown using paired t-test with Benjamini–Hochberg multiple testing correction (after testing for normality using a Shapiro-Wilks test). B Species-level principal coordinate analysis (PCoA) of the samples from each DNA extraction kit across the dataset. C Relative abundance of expected 16S rRNA gene within the ZMC for each genus, and the 16S rRNA gene amplicon relative abundances achieved using each DNA extraction kit. The genus abundance was ascertained through the use of 16S rRNA gene amplicon sequencing using the LSK112 kit
Figure Legend Snippet: 16S rRNA amplicon sequencing diversity analyses between commercial DNA extraction kits. A Species-level alpha diversity of the samples from each DNA extraction kit (following rarefaction) across the dataset, represented by observed Shannon, Simpson, and Chao1 indices. Analysis between groups shown using paired t-test with Benjamini–Hochberg multiple testing correction (after testing for normality using a Shapiro-Wilks test). B Species-level principal coordinate analysis (PCoA) of the samples from each DNA extraction kit across the dataset. C Relative abundance of expected 16S rRNA gene within the ZMC for each genus, and the 16S rRNA gene amplicon relative abundances achieved using each DNA extraction kit. The genus abundance was ascertained through the use of 16S rRNA gene amplicon sequencing using the LSK112 kit

Techniques Used: Amplification, Sequencing, DNA Extraction

Metagenomic comparison between ONT sequencing chemistries. Relative abundance of the number of reads mapped to each expected organism within the ZMC, from DNA extracted using the BM kit and sequenced using both the LSK109 and Q20 + LSK112 chemistries. Results are shown for whole metagenomic sequencing. Left panel shows expected genomic composition (estimated genome copy number) of each organism within the ZMC Standard
Figure Legend Snippet: Metagenomic comparison between ONT sequencing chemistries. Relative abundance of the number of reads mapped to each expected organism within the ZMC, from DNA extracted using the BM kit and sequenced using both the LSK109 and Q20 + LSK112 chemistries. Results are shown for whole metagenomic sequencing. Left panel shows expected genomic composition (estimated genome copy number) of each organism within the ZMC Standard

Techniques Used: Comparison, Sequencing

Metagenomic assembly statistics comparison between ONT sequencing chemistries. Comparison of whole genome de novo assemblies from metagenomic sequencing of the ZMC. Genome quality is assessed based on metrics obtained using Quast and Samtools, and alignments to the Zymo Research Corporation reference genomes. A Length of aligned assemblies against respective reference assemblies (line of best fit to the data shown in black and x = y line shown as a dotted grey line). B Total length of assemblies against respective reference assemblies (line of best fit to the data shown in black and x = y line shown as a dotted grey line). C GC content (%) of the largest contig of the assemblies against that of the reference genomes (line of best fit to the data shown in black and x = y line shown as a dotted grey line). D Genome fraction (%) of the assemblies to the references. E ) N50 values of each ZMC assembly (Mb). F Number of insertions and deletions (indels) for each ZMC assembly per Mb. G Largest contig within each ZMC assembly (Mb). H ) Number of contigs within each ZMC assembly. I Base mismatches within each ZMC assembly per Mb. J Coverage of reads (percentage of bases covered) to each ZMC assembly (%). K Depth of reads (mean depth of coverage) for each ZMC assembly. Comparison between chemistries is based on a paired Wilcoxon Signed rank sum test with Benjamini–Hochberg multiple testing correction (* = < 0.05). L ) Dotplots of the assembled genomes of each expected bacterial species within the ZMC. Genomes assembled from LSK109 and LSK112 reads, aligned by divergence (dv; approximate per-base difference) between the query (reference genome) and target (genome assembled within study)
Figure Legend Snippet: Metagenomic assembly statistics comparison between ONT sequencing chemistries. Comparison of whole genome de novo assemblies from metagenomic sequencing of the ZMC. Genome quality is assessed based on metrics obtained using Quast and Samtools, and alignments to the Zymo Research Corporation reference genomes. A Length of aligned assemblies against respective reference assemblies (line of best fit to the data shown in black and x = y line shown as a dotted grey line). B Total length of assemblies against respective reference assemblies (line of best fit to the data shown in black and x = y line shown as a dotted grey line). C GC content (%) of the largest contig of the assemblies against that of the reference genomes (line of best fit to the data shown in black and x = y line shown as a dotted grey line). D Genome fraction (%) of the assemblies to the references. E ) N50 values of each ZMC assembly (Mb). F Number of insertions and deletions (indels) for each ZMC assembly per Mb. G Largest contig within each ZMC assembly (Mb). H ) Number of contigs within each ZMC assembly. I Base mismatches within each ZMC assembly per Mb. J Coverage of reads (percentage of bases covered) to each ZMC assembly (%). K Depth of reads (mean depth of coverage) for each ZMC assembly. Comparison between chemistries is based on a paired Wilcoxon Signed rank sum test with Benjamini–Hochberg multiple testing correction (* = < 0.05). L ) Dotplots of the assembled genomes of each expected bacterial species within the ZMC. Genomes assembled from LSK109 and LSK112 reads, aligned by divergence (dv; approximate per-base difference) between the query (reference genome) and target (genome assembled within study)

Techniques Used: Comparison, Sequencing

Genome completeness for adaptive sampling enriched S. cerevisiae . Circos plot showing the mapping of reads enriched for S. cerevisiae using adaptive sampling against the reference genome to assess differences in coverage between the LSK109 and LSK112 library preparation methods. Outer track shows the reference assembly of S. cerevisiae (Accession No.: GCF_000146045.2), with the inner track showing a heatmap of GC content score calculated using bedtools nuc, and the next two inner tracks in green, the depth of reads covering each region using LSK109 or LSK112 sequencing chemistry
Figure Legend Snippet: Genome completeness for adaptive sampling enriched S. cerevisiae . Circos plot showing the mapping of reads enriched for S. cerevisiae using adaptive sampling against the reference genome to assess differences in coverage between the LSK109 and LSK112 library preparation methods. Outer track shows the reference assembly of S. cerevisiae (Accession No.: GCF_000146045.2), with the inner track showing a heatmap of GC content score calculated using bedtools nuc, and the next two inner tracks in green, the depth of reads covering each region using LSK109 or LSK112 sequencing chemistry

Techniques Used: Sampling, Sequencing

Related Articles

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Article Title: Vertirhodins A–F, C-Linked Pyrrolidine-Iminosugar-Containing Pyranonaphthoquinones from Streptomyces sp. B15-008
Article Snippet: Six novel pyranonaphthoquinones, vertirhodins A−F (1−6), were discovered from a soil-derived Streptomyces sp. B15-008.. Their chemical structures and absolute configurations were determined using nuclear magnetic resonance and comparison of experimental and theoretical electronic circular dichroism spectra.. The vertirhodins feature an unusual C-8 N-methyl-2-pyrrolidinemethanol moiety, a 5,14epoxide rarely seen in streptomyces-derived natural products, and a C-13 hydroxyl group that forms the semiquinone.

Article Title: Vertirhodins A–F, C-Linked Pyrrolidine-Iminosugar-Containing Pyranonaphthoquinones from Streptomyces sp. B15–008
Article Snippet: The Streptomyces sp. B15–008 genome was subjected to third-generation long-read sequencing (Pacific Biosciences and Oxford Nanopore), and BGCs encoding secondary metabolites were identified by AntiSMASH 21 ( ).

Article Title: The Notable Achievements and the Prospects of Bacterial Pathogen Genomics
Article Snippet: Over the last decade, third-generation long-read sequencing technologies have emerged to address the limitations referred to above, most notably from Pacific Biosciences (PacBio) [ ] and Oxford Nanopore Technologies (ONT) [ ].



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Image Search Results


16S rRNA amplicon sequencing diversity analyses between commercial DNA extraction kits. A Species-level alpha diversity of the samples from each DNA extraction kit (following rarefaction) across the dataset, represented by observed Shannon, Simpson, and Chao1 indices. Analysis between groups shown using paired t-test with Benjamini–Hochberg multiple testing correction (after testing for normality using a Shapiro-Wilks test). B Species-level principal coordinate analysis (PCoA) of the samples from each DNA extraction kit across the dataset. C Relative abundance of expected 16S rRNA gene within the ZMC for each genus, and the 16S rRNA gene amplicon relative abundances achieved using each DNA extraction kit. The genus abundance was ascertained through the use of 16S rRNA gene amplicon sequencing using the LSK112 kit

Journal: Environmental Microbiome

Article Title: Impact of microbiological molecular methodologies on adaptive sampling using nanopore sequencing in metagenomic studies

doi: 10.1186/s40793-025-00704-7

Figure Lengend Snippet: 16S rRNA amplicon sequencing diversity analyses between commercial DNA extraction kits. A Species-level alpha diversity of the samples from each DNA extraction kit (following rarefaction) across the dataset, represented by observed Shannon, Simpson, and Chao1 indices. Analysis between groups shown using paired t-test with Benjamini–Hochberg multiple testing correction (after testing for normality using a Shapiro-Wilks test). B Species-level principal coordinate analysis (PCoA) of the samples from each DNA extraction kit across the dataset. C Relative abundance of expected 16S rRNA gene within the ZMC for each genus, and the 16S rRNA gene amplicon relative abundances achieved using each DNA extraction kit. The genus abundance was ascertained through the use of 16S rRNA gene amplicon sequencing using the LSK112 kit

Article Snippet: More recently, third generation long-read sequencing technologies have been developed, most notably those from Pacific BioSciences and Oxford Nanopore Technologies (ONT).

Techniques: Amplification, Sequencing, DNA Extraction

Metagenomic comparison between ONT sequencing chemistries. Relative abundance of the number of reads mapped to each expected organism within the ZMC, from DNA extracted using the BM kit and sequenced using both the LSK109 and Q20 + LSK112 chemistries. Results are shown for whole metagenomic sequencing. Left panel shows expected genomic composition (estimated genome copy number) of each organism within the ZMC Standard

Journal: Environmental Microbiome

Article Title: Impact of microbiological molecular methodologies on adaptive sampling using nanopore sequencing in metagenomic studies

doi: 10.1186/s40793-025-00704-7

Figure Lengend Snippet: Metagenomic comparison between ONT sequencing chemistries. Relative abundance of the number of reads mapped to each expected organism within the ZMC, from DNA extracted using the BM kit and sequenced using both the LSK109 and Q20 + LSK112 chemistries. Results are shown for whole metagenomic sequencing. Left panel shows expected genomic composition (estimated genome copy number) of each organism within the ZMC Standard

Article Snippet: More recently, third generation long-read sequencing technologies have been developed, most notably those from Pacific BioSciences and Oxford Nanopore Technologies (ONT).

Techniques: Comparison, Sequencing

Metagenomic assembly statistics comparison between ONT sequencing chemistries. Comparison of whole genome de novo assemblies from metagenomic sequencing of the ZMC. Genome quality is assessed based on metrics obtained using Quast and Samtools, and alignments to the Zymo Research Corporation reference genomes. A Length of aligned assemblies against respective reference assemblies (line of best fit to the data shown in black and x = y line shown as a dotted grey line). B Total length of assemblies against respective reference assemblies (line of best fit to the data shown in black and x = y line shown as a dotted grey line). C GC content (%) of the largest contig of the assemblies against that of the reference genomes (line of best fit to the data shown in black and x = y line shown as a dotted grey line). D Genome fraction (%) of the assemblies to the references. E ) N50 values of each ZMC assembly (Mb). F Number of insertions and deletions (indels) for each ZMC assembly per Mb. G Largest contig within each ZMC assembly (Mb). H ) Number of contigs within each ZMC assembly. I Base mismatches within each ZMC assembly per Mb. J Coverage of reads (percentage of bases covered) to each ZMC assembly (%). K Depth of reads (mean depth of coverage) for each ZMC assembly. Comparison between chemistries is based on a paired Wilcoxon Signed rank sum test with Benjamini–Hochberg multiple testing correction (* = < 0.05). L ) Dotplots of the assembled genomes of each expected bacterial species within the ZMC. Genomes assembled from LSK109 and LSK112 reads, aligned by divergence (dv; approximate per-base difference) between the query (reference genome) and target (genome assembled within study)

Journal: Environmental Microbiome

Article Title: Impact of microbiological molecular methodologies on adaptive sampling using nanopore sequencing in metagenomic studies

doi: 10.1186/s40793-025-00704-7

Figure Lengend Snippet: Metagenomic assembly statistics comparison between ONT sequencing chemistries. Comparison of whole genome de novo assemblies from metagenomic sequencing of the ZMC. Genome quality is assessed based on metrics obtained using Quast and Samtools, and alignments to the Zymo Research Corporation reference genomes. A Length of aligned assemblies against respective reference assemblies (line of best fit to the data shown in black and x = y line shown as a dotted grey line). B Total length of assemblies against respective reference assemblies (line of best fit to the data shown in black and x = y line shown as a dotted grey line). C GC content (%) of the largest contig of the assemblies against that of the reference genomes (line of best fit to the data shown in black and x = y line shown as a dotted grey line). D Genome fraction (%) of the assemblies to the references. E ) N50 values of each ZMC assembly (Mb). F Number of insertions and deletions (indels) for each ZMC assembly per Mb. G Largest contig within each ZMC assembly (Mb). H ) Number of contigs within each ZMC assembly. I Base mismatches within each ZMC assembly per Mb. J Coverage of reads (percentage of bases covered) to each ZMC assembly (%). K Depth of reads (mean depth of coverage) for each ZMC assembly. Comparison between chemistries is based on a paired Wilcoxon Signed rank sum test with Benjamini–Hochberg multiple testing correction (* = < 0.05). L ) Dotplots of the assembled genomes of each expected bacterial species within the ZMC. Genomes assembled from LSK109 and LSK112 reads, aligned by divergence (dv; approximate per-base difference) between the query (reference genome) and target (genome assembled within study)

Article Snippet: More recently, third generation long-read sequencing technologies have been developed, most notably those from Pacific BioSciences and Oxford Nanopore Technologies (ONT).

Techniques: Comparison, Sequencing

Genome completeness for adaptive sampling enriched S. cerevisiae . Circos plot showing the mapping of reads enriched for S. cerevisiae using adaptive sampling against the reference genome to assess differences in coverage between the LSK109 and LSK112 library preparation methods. Outer track shows the reference assembly of S. cerevisiae (Accession No.: GCF_000146045.2), with the inner track showing a heatmap of GC content score calculated using bedtools nuc, and the next two inner tracks in green, the depth of reads covering each region using LSK109 or LSK112 sequencing chemistry

Journal: Environmental Microbiome

Article Title: Impact of microbiological molecular methodologies on adaptive sampling using nanopore sequencing in metagenomic studies

doi: 10.1186/s40793-025-00704-7

Figure Lengend Snippet: Genome completeness for adaptive sampling enriched S. cerevisiae . Circos plot showing the mapping of reads enriched for S. cerevisiae using adaptive sampling against the reference genome to assess differences in coverage between the LSK109 and LSK112 library preparation methods. Outer track shows the reference assembly of S. cerevisiae (Accession No.: GCF_000146045.2), with the inner track showing a heatmap of GC content score calculated using bedtools nuc, and the next two inner tracks in green, the depth of reads covering each region using LSK109 or LSK112 sequencing chemistry

Article Snippet: More recently, third generation long-read sequencing technologies have been developed, most notably those from Pacific BioSciences and Oxford Nanopore Technologies (ONT).

Techniques: Sampling, Sequencing

PacBio single-molecule real-time  sequencing  results of ABO gene conducted in this study.

Journal: Frontiers in Immunology

Article Title: Characterization of a novel AEL allele harboring a c.28 + 5G>A mutation on the ABO*A2.01 background: a study utilizing PacBio third-generation sequencing and functional assays

doi: 10.3389/fimmu.2024.1396426

Figure Lengend Snippet: PacBio single-molecule real-time sequencing results of ABO gene conducted in this study.

Article Snippet: Third-generation long-read single-molecule real-time sequencing technology, as provided by Pacific BioSciences (PacBio), holds significant potential for the comprehensive assembly of haplotype sequences of blood group gene alleles ( ).

Techniques: Sequencing, Mutagenesis

Advantages and limitations of current methylation  sequencing  methods

Journal: Nature methods

Article Title: Profiling the epigenetic landscape of the antigen receptor repertoire: the missing epi-immunogenomics data

doi: 10.1038/s41592-022-01723-9

Figure Lengend Snippet: Advantages and limitations of current methylation sequencing methods

Article Snippet: An advantage of these alternative methods is potential compatibility with long-read third-generation sequencing platforms such as Oxford Nanopore 36 and PacBio single-molecule real-time (SMRT) 37 sequencing.

Techniques: Methylation, Sequencing, Binding Assay, Amplification, Next-Generation Sequencing, Control