scholarly journals DNA Barcoding of fogged caterpillars in Peru: A novel approach for unveiling host-plant relationships of tropical moths (Insecta, Lepidoptera)

2019 ◽  
Author(s):  
Axel Hausmann ◽  
Juliane Diller ◽  
Jerome Moriniere ◽  
Amelie Höcherl ◽  
Andreas Floren ◽  
...  
Keyword(s):  
Host Plant ◽  
Dna Barcoding ◽  
High Throughput Sequencing ◽  
Reference Database ◽  
Gut Content ◽  
Molecular Gut Content Analysis ◽  
Novel Approach ◽  
Lepidopteran Larvae ◽  
Potential Alternative ◽  
Alternative Feeding

AbstractA total of 130 lepidopteran larvae were selected from 37 fogging samples at the Panguana station, district Yuyapichis, province Puerto Inca, department Huánuco, Peru. Target trees were pre-identified and subsequently submitted to molecular confirmation of identity with three markers (rbcL, psbA and trnL-F). Identification of 119 lepidopteran larvae (92 species) was successful through DNA barcoding: Comparison of COI barcodes with the reference database of adult moths resulted in 65 (55%) matches at species level, 32 (27%) at genus level and 19 (16%) at subfamily or family level. Three larvae could not be assigned to a family. For these larvae the fogged target tree now suggests a potential host-plant relationship. Molecular gut content analysis, based on High-Throughput-Sequencing was successfully tested for ten larvae corroborating feeding on the target plant in some cases but elucidating several other cases of potential ‘alternative feeding’. We propose a larger-scale approach using this rapid and efficient method including molecular gut-content analyses for comprehensively testing the ratio of ‘alternative feeders’ and pitfalls caused by collateral fogging of larvae from neighboring trees.

scholarly journals DNA barcoding of fogged caterpillars in Peru: A novel approach for unveiling host-plant relationships of tropical moths (Insecta, Lepidoptera)

PLoS ONE ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. e0224188 ◽  
Author(s):  
Axel Hausmann ◽  
Juliane Diller ◽  
Jerome Moriniere ◽  
Amelie Höcherl ◽  
Andreas Floren ◽  
...  
Keyword(s):  
Host Plant ◽  
Dna Barcoding ◽  
Novel Approach ◽  
Host Plant Relationships

scholarly journals Predation on Drosophila suzukii within Hedges in the Agricultural Landscape

Insects ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 305
Author(s):  
Alexandra Siffert ◽  
Fabian Cahenzli ◽  
Patrik Kehrli ◽  
Claudia Daniel ◽  
Virginie Dekumbis ◽  
...  
Keyword(s):  
Agricultural Landscape ◽  
Vital Role ◽  
Agricultural Landscapes ◽  
Gut Content ◽  
Drosophila Suzukii ◽  
Natural Habitats ◽  
Host Fruit ◽  
Molecular Gut Content Analysis ◽  
Wild Fruits ◽  
Diverse Community

The invasive Drosophila suzukii feeds and reproduces on various cultivated and wild fruits and moves between agricultural and semi-natural habitats. Hedges in agricultural landscapes play a vital role in the population development of D. suzukii, but also harbor a diverse community of natural enemies. We investigated predation by repeatedly exposing cohorts of D. suzukii pupae between June and October in dry and humid hedges at five different locations in Switzerland. We sampled predator communities and analyzed their gut content for the presence of D. suzukii DNA based on the COI marker. On average, 44% of the exposed pupae were predated. Predation was higher in dry than humid hedges, but did not differ significantly between pupae exposed on the ground or on branches and among sampling periods. Earwigs, spiders, and ants were the dominant predators. Predator communities did not vary significantly between hedge types or sampling periods. DNA of D. suzukii was detected in 3.4% of the earwigs, 1.8% of the spiders, and in one predatory bug (1.6%). While the molecular gut content analysis detected only a small proportion of predators that had fed on D. suzukii, overall predation seemed sufficient to reduce D. suzukii populations, in particular in hedges that provide few host fruit resources.

scholarly journals Bioconductor workflow for microbiome data analysis: from raw reads to community analyses

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 1492 ◽  
Author(s):  
Ben J. Callahan ◽  
Kris Sankaran ◽  
Julia A. Fukuyama ◽  
Paul J. McMurdie ◽  
Susan P. Holmes
Keyword(s):  
High Throughput Sequencing ◽  
Linear Models ◽  
Reference Database ◽  
Rrna Gene ◽  
Microbial Composition ◽  
Nonparametric Testing ◽  
Abundance Estimates ◽  
Taxonomic Markers ◽  
Microbiome Data ◽  
Microbiome Data Analysis

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level of analysis of complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or microbial composition of communities in different conditions. The sequencing reads have to be denoised and assigned to the closest taxa from a reference database. Common approaches use a notion of 97% similarity and normalize the data by subsampling to equalize library sizes. In this paper, we show that statistical models allow more accurate abundance estimates. By providing a complete workflow in R, we enable the user to do sophisticated downstream statistical analyses, including both parameteric and nonparametric methods. We provide examples of using the R packages dada2, phyloseq, DESeq2, ggplot2 and vegan to filter, visualize and test microbiome data. We also provide examples of supervised analyses using random forests, partial least squares and linear models as well as nonparametric testing using community networks and the ggnetwork package.

scholarly journals DISMIR: a deep learning-based cancer-detection method by integrating DNA sequence and methylation information of individual cell-free DNA reads

2021 ◽  
Author(s):  
Jiaqi Li ◽  
Lei Wei ◽  
Xianglin Zhang ◽  
Wei Zhang ◽  
Haochen Wang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Dna Sequence ◽  
Cancer Detection ◽  
High Throughput Sequencing ◽  
Detection Method ◽  
Low Cost ◽  
Sequencing Data ◽  
Cell Free Dna ◽  
Free Dna ◽  
Novel Approach

ABSTRACTDetecting cancer signals in cell-free DNA (cfDNA) high-throughput sequencing data is emerging as a novel non-invasive cancer detection method. Due to the high cost of sequencing, it is crucial to make robust and precise prediction with low-depth cfDNA sequencing data. Here we propose a novel approach named DISMIR, which can provide ultrasensitive and robust cancer detection by integrating DNA sequence and methylation information in plasma cfDNA whole genome bisulfite sequencing (WGBS) data. DISMIR introduces a new feature termed as “switching region” to define cancer-specific differentially methylated regions, which can enrich the cancer-related signal at read-resolution. DISMIR applies a deep learning model to predict the source of every single read based on its DNA sequence and methylation state, and then predicts the risk that the plasma donor is suffering from cancer. DISMIR exhibited high accuracy and robustness on hepatocellular carcinoma detection by plasma cfDNA WGBS data even at ultra-low sequencing depths. Analysis showed that DISMIR tends to be insensitive to alterations of single CpG sites’ methylation states, which suggests DISMIR could resist to technical noise of WGBS. All these results showed DISMIR with the potential to be a precise and robust method for low-cost early cancer detection.

scholarly journals Novel Approach to Study the Diversity of Soil Microbial Communities in Qatar

2020 ◽  
Author(s):  
Jane Oja ◽  
Sakeenah Adenan ◽  
Abdel-Fattah Talaat ◽  
Juha Alatalo
Keyword(s):  
Microbial Communities ◽  
High Throughput ◽  
Mycorrhizal Fungi ◽  
High Throughput Sequencing ◽  
Soil Microbial Communities ◽  
Arbuscular Mycorrhizal ◽  
Soil Microbial ◽  
Fungal Abundance ◽  
Novel Approach ◽  
Soil Climate

A broad diversity of microorganisms can be found in soil, where they are essential for nutrient cycling and energy transfer. Recent high-throughput sequencing methods have greatly advanced our knowledge about how soil, climate and vegetation variables structure the composition of microbial communities in many world regions. However, we are lacking information from several regions in the world, e.g. Middle-East. We have collected soil from 19 different habitat types for studying the diversity and composition of soil microbial communities (both fungi and bacteria) in Qatar and determining which edaphic parameters exert the strongest influences on these communities. Preliminary results indicate that in overall bacteria are more abundant in soil than fungi and few sites have notably higher abundance of these microbes. In addition, we have detected some soil patameters, which tend to have reduced the overall fungal abundance and enhanced the presence of arbuscular mycorrhizal fungi and N-fixing bacteria. More detailed information on the diversity and composition of soil microbial communities is expected from the high-throughput sequenced data.

scholarly journals An 18S V4 rDNA metabarcoding dataset of protist diversity in the Atlantic inflow to the Arctic Ocean, through the year and down to 1000 m depth

2021 ◽  
Author(s):  
Elianne Egge ◽  
Stephanie Elferink ◽  
Daniel Vaulot ◽  
Uwe John ◽  
Gunnar Bratbak ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
High Throughput Sequencing ◽  
Sea Water ◽  
Size Fraction ◽  
The Arctic ◽  
Reference Database ◽  
Rrna Gene ◽  
Svalbard Archipelago ◽  
The Arctic Ocean ◽  
Epipelagic Zone

AbstractArctic marine protist communities have been understudied due to challenging sampling conditions, in particular during winter and in deep waters. The aim of this study was to improve our knowledge on Arctic protist diversity through the year, both in the epipelagic (< 200 m depth) and mesopelagic zones (200-1000 m depth). Sampling campaigns were performed in 2014, during five different months, to capture the various phases of the Arctic primary production: January (winter), March (pre-bloom), May (spring bloom), August (post-bloom) and November (early winter). The cruises were undertaken west and north of the Svalbard archipelago, where warmer Atlantic waters from the West Spitsbergen Current meets cold Arctic waters from the Arctic Ocean. From each cruise, station, and depth, 50 L of sea water were collected and the plankton was size-fractionated by serial filtration into four size fractions between 0.45-200 µm, representing the picoplankton, nanoplankton and microplankton. In addition vertical net hauls were taken from 50 m depth to the surface at selected stations. From the plankton samples DNA was extracted, the V4 region of the 18S rRNA-gene was amplified by PCR with universal eukaryote primers and the amplicons were sequenced by Illumina high-throughput sequencing. Sequences were clustered into Amplicon Sequence Variants (ASVs), representing protist genotypes, with the dada2 pipeline. Taxonomic classification was made against the curated Protist Ribosomal Reference database (PR2). Altogether 6,536 protist ASVs were obtained (including 54 fungal ASVs). Both ASV richness and taxonomic composition were strongly dependent on size-fraction, season, and depth. ASV richness was generally higher in the smaller fractions, and higher in winter and the mesopelagic samples than in samples from the well-lit epipelagic zone during summer. During spring and summer, the phytoplankton groups diatoms, chlorophytes and haptophytes dominated in the epipelagic zone. Parasitic and heterotrophic groups such as Syndiniales and certain dinoflagel-lates dominated in the mesopelagic zone all year, as well as in the epipelagic zone during the winter. The dataset is available at https://doi.org/10.17882/79823, (Egge et al., 2014).

scholarly journals Host plant identification in the generalist xylem feeder Philaenus spumarius through gut content analysis

2020 ◽  
Vol 168 (12) ◽  
pp. 890-899
Author(s):  
Elena Gonella ◽  
Luca Picciau ◽  
Liam Pippinato ◽  
Beniamino Cavagna ◽  
Alberto Alma
Keyword(s):  
Content Analysis ◽  
Host Plant ◽  
Gut Content Analysis ◽  
Gut Content ◽  
Plant Identification ◽  
Philaenus Spumarius

scholarly journals Studying 3D genome evolution using genomic sequence

2019 ◽  
Author(s):  
Raphaël Mourad
Keyword(s):  
Genome Evolution ◽  
High Throughput Sequencing ◽  
Genomic Sequence ◽  
Regulation Of Gene Expression ◽  
Replication Timing ◽  
Three Dimensions ◽  
Supplementary Information ◽  
3D Genome ◽  
Chromatin Looping ◽  
Novel Approach

Abstract Motivation The three dimensions (3D) genome is essential to numerous key processes such as the regulation of gene expression and the replication-timing program. In vertebrates, chromatin looping is often mediated by CTCF, and marked by CTCF motif pairs in convergent orientation. Comparative high-throughput sequencing technique (Hi-C) recently revealed that chromatin looping evolves across species. However, Hi-C experiments are complex and costly, which currently limits their use for evolutionary studies over a large number of species. Results Here, we propose a novel approach to study the 3D genome evolution in vertebrates using the genomic sequence only, e.g. without the need for Hi-C data. The approach is simple and relies on comparing the distances between convergent and divergent CTCF motifs by computing a ratio we named the 3D ratio or ‘3DR’. We show that 3DR is a powerful statistic to detect CTCF looping encoded in the human genome sequence, thus reflecting strong evolutionary constraints encoded in DNA and associated with the 3D genome. When comparing vertebrate genomes, our results reveal that 3DR which underlies CTCF looping and topologically associating domain organization evolves over time and suggest that ancestral character reconstruction can be used to infer 3DR in ancestral genomes. Availability and implementation The R code is available at https://github.com/morphos30/PhyloCTCFLooping. Supplementary information Supplementary data are available at Bioinformatics online.

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