scholarly journals Taxon appearance from extraction and amplification steps demonstrates the value of multiple controls in tick microbiota analysis

2019 ◽  
Author(s):  
Emilie Lejal ◽  
Agustín Estrada-Peña ◽  
Maud Marsot ◽  
Jean-François Cosson ◽  
Olivier Rué ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Dna Extraction ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Dna Amplification ◽  
Community Diversity ◽  
Analytical Process ◽  
Sequencing Technologies ◽  
And Gender ◽  
The Impact

AbstractBackgroundThe development of high throughput sequencing technologies has substantially improved analysis of bacterial community diversity, composition, and functions. Over the last decade, high throughput sequencing has been used extensively to identify the diversity and composition of tick microbial communities. However, a growing number of studies are warning about the impact of contamination brought along the different steps of the analytical process, from DNA extraction to amplification. In low biomass samples, e.g. individual tick samples, these contaminants may represent a large part of the obtained sequences, and thus generate considerable errors in downstream analyses and in the interpretation of results. Most studies of tick microbiota either do not mention the inclusion of controls during the DNA extraction or amplification steps, or consider the lack of an electrophoresis signal as an absence of contamination. In this context, we aimed to assess the proportion of contaminant sequences resulting from these steps. We analyzed the microbiota of individual Ixodes ricinus ticks by including several categories of controls throughout the analytical process: crushing, DNA extraction, and DNA amplification.ResultsControls yielded a significant number of sequences (1,126 to 13,198 mean sequences, depending on the control category). Some operational taxonomic units (OTUs) detected in these controls belong to genera reported in previous tick microbiota studies. In this study, these OTUs accounted for 50.9% of the total number of sequences in our samples, and were considered contaminants. Contamination levels (i.e. the percentage of sequences belonging to OTUs identified as contaminants) varied with tick stage and gender: 76.3% of nymphs and 75% of males demonstrated contamination over 50%, while most females (65.7%) had rates lower than 20%. Contamination mainly corresponded to OTUs detected in crushing and DNA extraction controls, highlighting the importance of carefully controlling these steps.ConclusionHere, we showed that contaminant OTUs from extraction and amplification steps can represent more than half the total sequence yield in sequencing runs, and lead to unreliable results when characterizing tick microbial communities. We thus strongly advise the routine use of negative controls in tick microbiota studies, and more generally in studies involving low biomass samples.

scholarly journals Impact of human gene annotations on RNA-seq differential expression analysis

2021 ◽  
Author(s):  
Yu Hamaguchi ◽  
Chao Zeng ◽  
Michiaki Hamada
Keyword(s):  
Differential Expression ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Human Gene ◽  
Gene Annotation ◽  
Differential Expression Analysis ◽  
Rna Seq ◽  
Gene Annotations ◽  
Sequencing Technologies ◽  
The Impact

Abstract Background: Differential expression (DE) analysis of RNA-seq data typically depends on gene annotations. Different sets of gene annotations are available for the human genome and are continually updated–a process complicated with the development and application of high-throughput sequencing technologies. However, the impact of the complexity of gene annotations on DE analysis remains unclear.Results: Using “mappability”, a metric of the complexity of gene annotation, we compared three distinct human gene annotations, GENCODE, RefSeq, and NONCODE, and evaluated how mappability affected DE analysis. We found that mappability was significantly different among the human gene annotations. We also found that increasing mappability improved the performance of DE analysis, and the impact of mappability mainly evident in the quantification step and propagated downstream of DE analysis systematically.Conclusions: We assessed how the complexity of gene annotations affects DE analysis using mappability. Our findings indicate that the growth and complexity of gene annotations negatively impact the performance of DE analysis, suggesting that an approach that excludes unnecessary gene models from gene annotations improves the performance of DE analysis.

scholarly journals High Throughput Sequencing Technologies as a New Toolbox for Deep Analysis, Characterization and Potentially Authentication of Protection Designation of Origin Cheeses?

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Elena Kamilari ◽  
Marios Tomazou ◽  
Athos Antoniades ◽  
Dimitrios Tsaltas
Keyword(s):  
Microbial Communities ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
The European Union ◽  
Ripening Process ◽  
Additional Tool ◽  
Sequencing Technologies ◽  
Protected Designation Of Origin ◽  
The Matrix ◽  
Dynamic Community

Protected Designation of Origin (PDO) labeling of cheeses has been established by the European Union (EU) as a quality policy that assures the authenticity of a cheese produced in a specific region by applying traditional production methods. However, currently used scientific methods for differentiating and establishing PDO are limited in terms of time, cost, accuracy and their ability to identify through quantifiable methods PDO fraud. Cheese microbiome is a dynamic community that progressively changes throughout ripening, contributing via its metabolism to unique qualitative and sensorial characteristics that differentiate each cheese. High Throughput Sequencing (HTS) methodologies have enabled the more precise identification of the microbial communities developed in fermented cheeses, characterization of their population dynamics during the cheese ripening process, as well as their contribution to the development of specific organoleptic and physio-chemical characteristics. Therefore, their application may provide an additional tool to identify the key microbial species that contribute to PDO cheeses unique sensorial characteristics and to assist to define their typicityin order to distinguish them from various fraudulent products. Additionally, they may assist the cheese-makers to better evaluate the quality, as well as the safety of their products. In this structured literature review indications are provided on the potential for defining PDO enabling differentiating factors based on distinguishable microbial communities shaped throughout the ripening procedures associated to cheese sensorial characteristics, as revealed through metagenomic and metatranscriptomic studies. Conclusively, HTS applications, even though still underexploited, have the potential to demonstrate how the cheese microbiome can affect the ripening process and sensorial characteristics formation via the catabolism of the available nutrients and interplay with other compounds of the matrix and/or production of microbial origin metabolites and thus their further quality enhancement.

scholarly journals In Silico Estimation of the Abundance and Phylogenetic Significance of the Composite Oct4-Sox2 Binding Motifs within a Wide Range of Species

Data ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 111
Author(s):  
Arman Kulyyassov ◽  
Ruslan Kalendar
Keyword(s):  
High Throughput ◽  
Dna Sequences ◽  
High Throughput Sequencing ◽  
Regulatory Elements ◽  
Scoring Method ◽  
Sequencing Technologies ◽  
Wide Range ◽  
Multiple Species ◽  
Eukaryotic Organisms ◽  
The Impact

High-throughput sequencing technologies have greatly accelerated the progress of genomics, transcriptomics, and metagenomics. Currently, a large amount of genomic data from various organisms is being generated, the volume of which is increasing every year. Therefore, the development of methods that allow the rapid search and analysis of DNA sequences is urgent. Here, we present a novel motif-based high-throughput sequence scoring method that generates genome information. We found and identified Utf1-like, Fgf4-like, and Hoxb1-like motifs, which are cis-regulatory elements for the pluripotency transcription factors Sox2 and Oct4 within the genomes of different eukaryotic organisms. The genome-wide analysis of these motifs was performed to understand the impact of their diversification on mammalian genome evolution. Utf1-like, Fgf4-like, and Hoxb1-like motif diversity was evaluated across genomes from multiple species.

scholarly journals Impact of human gene annotations on RNA-seq differential expression analysis

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yu Hamaguchi ◽  
Chao Zeng ◽  
Michiaki Hamada
Keyword(s):  
Differential Expression ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Human Gene ◽  
Gene Annotation ◽  
Differential Expression Analysis ◽  
Rna Seq ◽  
Gene Annotations ◽  
Sequencing Technologies ◽  
The Impact

Abstract Background Differential expression (DE) analysis of RNA-seq data typically depends on gene annotations. Different sets of gene annotations are available for the human genome and are continually updated–a process complicated with the development and application of high-throughput sequencing technologies. However, the impact of the complexity of gene annotations on DE analysis remains unclear. Results Using “mappability”, a metric of the complexity of gene annotation, we compared three distinct human gene annotations, GENCODE, RefSeq, and NONCODE, and evaluated how mappability affected DE analysis. We found that mappability was significantly different among the human gene annotations. We also found that increasing mappability improved the performance of DE analysis, and the impact of mappability mainly evident in the quantification step and propagated downstream of DE analysis systematically. Conclusions We assessed how the complexity of gene annotations affects DE analysis using mappability. Our findings indicate that the growth and complexity of gene annotations negatively impact the performance of DE analysis, suggesting that an approach that excludes unnecessary gene models from gene annotations improves the performance of DE analysis.

scholarly journals Extremely Halophilic Biohydrogen Producing Microbial Communities from High-Salinity Soil and Salt Evaporation Pond

Fuels ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 241-252
Author(s):  
Dyah Asri Handayani Taroepratjeka ◽  
Tsuyoshi Imai ◽  
Prapaipid Chairattanamanokorn ◽  
Alissara Reungsang
Keyword(s):  
Microbial Communities ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
High Salinity ◽  
Amplicon Sequencing ◽  
Spatial Proximity ◽  
Lignocellulosic Waste ◽  
Evaporation Pond ◽  
Operational Taxonomic Units ◽  
Determining Factor

Extreme halophiles offer the advantage to save on the costs of sterilization and water for biohydrogen production from lignocellulosic waste after the pretreatment process with their ability to withstand extreme salt concentrations. This study identifies the dominant hydrogen-producing genera and species among the acclimatized, extremely halotolerant microbial communities taken from two salt-damaged soil locations in Khon Kaen and one location from the salt evaporation pond in Samut Sakhon, Thailand. The microbial communities’ V3–V4 regions of 16srRNA were analyzed using high-throughput amplicon sequencing. A total of 345 operational taxonomic units were obtained and the high-throughput sequencing confirmed that Firmicutes was the dominant phyla of the three communities. Halanaerobium fermentans and Halanaerobacter lacunarum were the dominant hydrogen-producing species of the communities. Spatial proximity was not found to be a determining factor for similarities between these extremely halophilic microbial communities. Through the study of the microbial communities, strategies can be developed to increase biohydrogen molar yield.

scholarly journals Assessing genotyping errors in mammalian museum study skins using high-throughput genotyping-by-sequencing

2021 ◽  
Author(s):  
Stella C. Yuan ◽  
Eric Malekos ◽  
Melissa T. R. Hawkins
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Massively Parallel Sequencing ◽  
Massively Parallel ◽  
Museum Specimens ◽  
Museum Specimen ◽  
Genotyping Errors ◽  
Allelic Dropout ◽  
Parallel Sequencing ◽  
Sequencing Technologies

AbstractThe use of museum specimens held in natural history repositories for population and conservation genetic research is increasing in tandem with the use of massively parallel sequencing technologies. Short Tandem Repeats (STRs), or microsatellite loci, are commonly used genetic markers in wildlife and population genetic studies. However, they traditionally suffered from a host of issues including length homoplasy, high costs, low throughput, and difficulties in reproducibility across laboratories. Massively parallel sequencing technologies can address these problems, but the incorporation of museum specimen derived DNA suffers from significant fragmentation and exogenous DNA contamination. Combatting these issues requires extra measures of stringency in the lab and during data analysis, yet there have not been any high-throughput sequencing studies evaluating microsatellite allelic dropout from museum specimen extracted DNA. In this study, we evaluate genotyping errors derived from mammalian museum skin DNA extracts for previously characterized microsatellites across PCR replicates utilizing high-throughput sequencing. We found it useful to classify samples based on DNA concentration, which determined the rate by which genotypes were accurately recovered. Longer microsatellites performed worse in all museum specimens. Allelic dropout rates across loci were dependent on sample quantity, with high concentration museum specimens performing as well and recovering quality metrics nearly as high as the frozen tissue sample. Based on our results, we provide a set of best practices for quality assurance and incorporation of reliable genotypes from museum specimens.

scholarly journals Profiling soil microbial communities with next-generation sequencing: the influence of DNA kit selection and technician technical expertise

2017 ◽  
Author(s):  
Taha Soliman ◽  
Sung-Yin Yang ◽  
Tomoko Yamazaki ◽  
Holger Jenke-Kodama
Keyword(s):  
Next Generation Sequencing ◽  
Microbial Communities ◽  
Dna Extraction ◽  
Dna Isolation ◽  
Soil Microbial Communities ◽  
Next Generation ◽  
Microbial Composition ◽  
Okinawa Island ◽  
The Impact ◽  
Generation Sequencing

Structure and diversity of microbial communities are an important research topic in biology, since microbes play essential roles in the ecology of various environments. Different DNA isolation protocols can lead to data bias and can affect results of next-generation sequencing. To evaluate the impact of protocols for DNA isolation from soil samples and also the influence of individual handling of samples, we compared results obtained by two researchers (R and T) using two different DNA extraction kits: (1) MO BIO PowerSoil® DNA Isolation kit (MO_R and MO_T) and (2) NucleoSpin® Soil kit (MN_R and MN_T). Samples were collected from six different sites on Okinawa Island, Japan. For all sites, differences in the results of microbial composition analyses (bacteria, archaea, fungi, and other eukaryotes), obtained by the two researchers using the two kits, were analyzed. For both researchers, the MN kit gave significantly higher yields of genomic DNA at all sites compared to the MO kit (ANOVA; P <0.006). In addition, operational taxonomic units for some phyla and classes were missed in some cases: Micrarchaea were detected only in the MN_T and MO_R analyses; the bacterial phylum Armatimonadetes was detected only in MO_R and MO_T; and WIM5 of the phylum Amoebozoa of eukaryotes was found only in the MO_T analysis. Our results suggest the possibility of handling bias; therefore, it is crucial that replicated DNA extraction be performed by at least two technicians for thorough microbial analyses and to obtain accurate estimates of microbial diversity.

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