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16 results for “16S amplicon sequencing”

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edi44/100

Inventory of soil prokaryotic and fungal microbiome (via 16S rRNA gene amplicons and ITS sequencing) from Shark River Slough and Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, February 2019 - October 2020

Global sea-level rise is transforming coastal ecosystems, especially freshwater wetlands, in part due to increased saltwater exposure, leading to change in soil microbial communities and many important biogeochemical processes. Given the high spatial and temporal heterogeneity in coastal wetlands, especially in tropical or subtropical climates characterized by seasonal temperature, precipitation, and tidal fluctuations, it remains unclear which environmental factors influence the compositions of soil microbial communities in wetlands affected by varying degrees of sea-water intrusion. To address this, a two-year survey was conducted on microbial community structure in submerged surface soils from 14 wetland sites across the Florida Everglades, representing three major ecosystem types, i.e. freshwater marshes, mangrove forests, and seagrass meadows. Bulk surface soil samples of each site were collected from February 2019 to October 2020 to cover dry and wet seasons. In addition to bulk soil samples, soil cores were collected from each site in August 2020 to assess vertical gradients of microbial communities. The dataset contains amplicon sequencing data of 16S rRNA gene (both bulk soil and soil cores) and ITS gene (only the bulk soil). The 2019 to 2020 data are published in Zhao et al. 2023. A detailed list of sequence data and their accession numbers in GenBank is provided, and data collection is complete. This data package is an inventory of sequence read archive (SRA) entries available through GenBank BioProject PRJNA804243 (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA804243), PRJNA804246 (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA804246), and PRJNA804228 (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA804228). This data package is associated with the following publication: Zhao, J., Chakrabarti, S., Chambers, R., Weisenhorn, P., Travieso, R., Stumpf, S., Standen, E., Briceno, H., Troxler, T., Gaiser, E., Kominoski, J., Dhillon, B., & Martens-H

openCC (other)Feb 2024View details →
zenodo36/100

Raw Fast5 data for "Microbiota profiling with long amplicons using Nanopore sequencing: full-length 16S rRNA gene and the 16S-ITS-23S of the rrn operon" - PART I

<p>Raw Fast5 data for &quot;Microbiota profiling with long amplicons using Nanopore sequencing: full-length 16S rRNA gene and the 16S-ITS-23S of the rrn operon&quot;. See Supplementary Table 2 for associating each sample to its barcode.</p> <p>- FC1_1 includes data for the HM mock community from BEI resources and skin microbiome of the chin in dogs.</p> <p>- FC1_2 includes data for the dorsal skin samples</p> <p>- FC2 includes data for the Zymobiomics mock community&nbsp;and Staphylococcus pseudintermedius isolate</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Feb 2020View details →
dryad36/100

Shallow shotgun sequencing of the microbiome recapitulates 16S amplicon results and provides functional insights

<p>Prevailing 16S rRNA gene-amplicon methods for characterizing the bacterial microbiome of wildlife are economical, but result in coarse taxonomic classifications, are subject to primer and 16S copy number biases, and do not allow for direct estimation of microbiome functional potential. While deep shotgun metagenomic sequencing can overcome many of these limitations, it is prohibitively expensive for large sample sets. We evaluated the ability of shallow shotgun metagenomic sequencing to characterize taxonomic and functional patterns in the fecal microbiome of a model population of feral horses (Sable Island, Canada). Since 2007, this unmanaged population has been the subject of an individual-based, long-term ecological study. Using deep shotgun metagenomic sequencing, we determined the sequencing depth required to accurately characterize the horse microbiome. In comparing conventional versus high-throughput shotgun metagenomic library preparation techniques, we validate the use of more cost-effective lab methods. Finally, we characterize similarities between 16S amplicon and shallow shotgun characterization of the microbiome and demonstrate that the latter recapitulates biological patterns first described in a published amplicon dataset. Unlike amplicon data, we further demonstrate how shallow shotgun metagenomic data provide useful insights about microbiome functional potential which support previously hypothesized diet effects in this study system.</p>

opencc-zeroSep 2022View details →
dryad36/100

Shallow shotgun sequencing of the microbiome recapitulates 16S amplicon results and provides functional insights

Open the record for dataset details and reuse information.

publicNov 2024View details →
dryad32/100

Data from: 16S rRNA amplicon sequencing for epidemiological surveys of bacteria in wildlife

The human impact on natural habitats is increasing the complexity of human-wildlife interactions and leading to the emergence of infectious diseases worldwide. Highly successful synanthropic wildlife species, such as rodents, will undoubtedly play an increasingly important role in transmitting zoonotic diseases. We investigated the potential for recent developments in 16S rRNA amplicon sequencing to facilitate the multiplexing of the large numbers of samples needed to improve our understanding of the risk of zoonotic disease transmission posed by urban rodents in West Africa. In addition to listing pathogenic bacteria in wild populations, as in other high-throughput sequencing (HTS) studies, our approach can estimate essential parameters for studies of zoonotic risk, such as prevalence and patterns of coinfection within individual hosts. However, the estimation of these parameters requires cleaning of the raw data to mitigate the biases generated by HTS methods. We present here an extensive review of these biases and of their consequences, and we propose a comprehensive trimming strategy for managing these biases. We demonstrated the application of this strategy using 711 commensal rodents, including 208 Mus musculus domesticus, 189 Rattus rattus, 93 Mastomys natalensis, and 221 Mastomys erythroleucus, collected from 24 villages in Senegal. Seven major genera of pathogenic bacteria were detected in their spleens: Borrelia, Bartonella, Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia. Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia have never before been detected in West African rodents. Bacterial prevalence ranged from 0% to 90% of individuals per site, depending on the bacterial taxon, rodent species, and site considered, and 26% of rodents displayed coinfection. The 16S rRNA amplicon sequencing strategy presented here has the advantage over other molecular surveillance tools of dealing with a large spectrum of bacterial pathogens without requiring assumptions about their presence in the samples. This approach is therefore particularly suitable to continuous pathogen surveillance in the context of disease-monitoring programs.

opencc-zeroDec 2015View details →
zenodo32/100

16S Amplicon sequence variants (ASVs) data of NEREA Augmented Observatory

<p><strong>Metabarcoding - 16S ASV generation and taxonomic assignment</strong>. Raw 16S paired-end sequences were subjected to a data quality control step and subsequently imported into the QIIME2 pipeline v.2022.2.0. Leftover primers and adapter sequences were removed through cutadapt. The amplicon sequence variants (ASV) table, which represent true biological sequences within each sample, was generated using the denoised-paired method including truncation, denoising, dereplication, merging, and chimera filtering of the DADA2 (Divisive Amplicon Denoising Algorithm 2) plugin inside QIIME2. Default parameters were used with the exception of the forward and reverse sequence length (--p-trunc-len-f and --p-trunc-len-r), that were set to 220 and 180, respectively. Processed reads that passed all these filters were used for taxonomy classification. The V4-V5 regions were extracted from the pre-formatted reference sequences and taxonomy file built on the SILVA 138 99% OTUs database and the vsearch v.2.6.2 global alignment implemented in QIIME2 was used.</p>

opencc-by-4.0Jul 2024View details →
zenodo32/100

16s rRNA sequences, R code used for amplicon analysis and example code for NMGS analysis

<p>This submission contains the following data presented in: &quot;Selection processes of Arctic seasonal glacier snowpack bacterial communities&quot; by Keuschnig et al.</p> <p>the R code used to analyze the 16S rRNA amplicon data</p> <p>the script used for NMGS analysis</p> <p>the sequences obtained from snow samples</p>

opencc-by-4.0Dec 2021View details →
dryad32/100

Data from: 16S rRNA amplicon sequencing for epidemiological surveys of bacteria in wildlife

Open the record for dataset details and reuse information.

publicApr 2017View details →
dryad28/100

Data from: Assessment of a 16S rRNA amplicon Illumina sequencing procedure for studying the microbiome of a symbiont-rich aphid genus

The bacterial communities inhabiting arthropods are generally dominated by a few endosymbionts that play an important role in the ecology of their hosts. Rather than comparing bacterial species richness across samples, ecological studies on arthropod endosymbionts often seek to identify the main bacterial strains associated with each specimen studied. The filtering out of contaminants from the results and the accurate taxonomic assignment of sequences are therefore crucial in arthropod microbiome studies. We aimed here to validate an Illumina 16S rRNA gene sequencing protocol and analytical pipeline for investigating endosymbiotic bacteria associated with aphids. Using replicate DNA samples from 12 species (Aphididae: Lachninae, Cinara) and several controls, we removed individual sequences not meeting a minimum threshold number of reads in each sample and carried out taxonomic assignment for the remaining sequences. With this approach, we show that: i) contaminants accounted for a negligible proportion of the bacteria identified in our samples; ii) the taxonomic composition of our samples and the relative abundance of reads assigned to a taxon were very similar across PCR and DNA replicates for each aphid sample; in particular, bacterial DNA concentration had no impact on the results. Furthermore, by analysing the distribution of unique sequences across samples rather than aggregating them into operational taxonomic units (OTUs), we gained insight into the specificity of endosymbionts for their hosts. Our results confirm that Serratia symbiotica is often present in Cinara species, in addition to the primary symbiont, Buchnera aphidicola. Furthermore, our findings reveal new symbiotic associations with Erwinia and Sodalis-related bacteria. We conclude with suggestions for generating and analysing 16S rRNA gene sequences for arthropod endosymbiont studies.

opencc-zeroDec 2014View details →
dryad28/100

Data from: Assessment of a 16S rRNA amplicon Illumina sequencing procedure for studying the microbiome of a symbiont-rich aphid genus

Open the record for dataset details and reuse information.

publicOct 2015View details →
zenodo24/100

16S rRNA gene and ITS2 region amplicon sequencing of GBP5 KO mice and WT littermates

<p>16S rRNA gene (v4) and ITS2 region amplicon sequencing of fecal microbiota of GBP5 KO mice and their littermate WT mice.</p>

opencc-by-4.0Nov 2023View details →
ClinicalTrials.gov24/100

Association of Intestinal Microbiota and the Onset of Perianal Abscess Based on 16S RDNA Amplicon Sequencing

ClinicalTrials.gov study NCT05862129. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
geo20/100

16S rDNA Amplicon Sequencing Analysis of Polystyrene Microplastic Exposed Zebrafish Intestine

GEO Series GSE136108. Danio rerio. 12 samples. Type: Other.

openGEO-OpenOct 2019View details →
zenodo16/100

16S Amplicon sequence variants (ASVs) data of NEREA Augmented Observatory

<p>Cleaned raw 16S paired-end sequences were imported into the QIIME2 pipeline v. 2022.2.0. Leftover primers and adapters&rsquo; sequences were removed through cutadapt. The amplicon sequence variants (ASV) table, which represent true biological sequences within each sample, was generated using the denoised-paired method including truncation, denoising, dereplication, and chimera filtering of the DADA2 (Divisive Amplicon Denoising Algorithm 2) plugin inside QIIME2. Default parameters were used with the exception of the forward and reverse sequence length (--p-trunc-len-f and --p-trunc-len-r), that were set to 220 and 180, respectively. For taxonomy classification, the V4-V5 region were extracted from the pre-formatted reference sequences and taxonomy file build on the SILVA 138 99% OTUS database and the vsearch v. 2.6.2 global alignment implemented in QIIME2 was used.</p>

restrictedcc-by-4.0Jul 2024View details →
zenodo12/100

Example datasets from 16S rRNA amplicon Illumina paired end sequencing

<p>Six example datasets from 16S rRNA amplicon Illumina paired-end sequencing.&nbsp;</p>

restrictedNov 2021View details →
zenodo8/100

The molecular raw data of microbial communities associated with fish gut - in vitro model system using 16S rRNA Illumina amplicon sequencing approach.

<p>This data on the microbial communities and its diversity&nbsp;associated with fish gut. The&nbsp;samples were obtained from fish gut - in vitro model system&nbsp;using 16S rRNA Illumina amplicon sequencing approach.</p>

restrictedMay 2023View details →

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