Environmental DNA Metabarcoding Deiner, Kristy
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Efficient Discretization Approaches for Machine Learning Techniques To
Advances in Science, Technology and Engineering Systems Journal Vol. 5, No. 3, 547-556 (2020) ASTES Journal www.astesj.com ISSN: 2415-6698 Special Issue on Multidisciplinary Innovation in Engineering Science & Technology Efficient Discretization Approaches for Machine Learning Techniques to Improve Disease Classification on Gut Microbiome Composition Data Hai Thanh Nguyen*;1, Nhi Yen Kim Phan1, Huong Hoang Luong2 , Trung Phuoc Le2, Nghi Cong Tran3 1College of Information and Communication Technology, Can Tho University, Can Tho city, 900100, Vietnam. 2Department of Information Technology, FPT University, Can Tho city, 900000, Vietnam. 3National Central University, Taoyuan, 320317, Taiwan, R.O.C. ARTICLEINFOABSTRACT Article history: The human gut environment can contain hundreds to thousands bacterial species which Received: 10 May, 2020 are proven that they are associated with various diseases. Although Machine learning has Accepted: 18 June, 2020 been supporting and developing metagenomic researches to obtain great achievements in Online: 28 June, 2020 personalized medicine approaches to improve human health, we still face overfitting issues in Bioinformatics tasks related to metagenomic data classification where the performance in Keywords: the training phase is rather high while we get low performance in testing. In this study, we Personalized medicine present discretization methods on metagenomic data which include Microbial Compositions Bacterial composition to obtain better results in disease prediction tasks. Data types used in the experiments consist Classic machine learning of species abundance and read counts on various taxonomic ranks such as Genus, Family, Discretization Order, etc. The proposed data discretization approaches for metagenomic data in this work Species abundance are unsupervised binning approaches including binning with equal width bins, considering Read counts the frequency of values and data distribution. -
Metagenomics Approaches for the Detection and Surveillance of Emerging and Recurrent Plant Pathogens
microorganisms Review Metagenomics Approaches for the Detection and Surveillance of Emerging and Recurrent Plant Pathogens Edoardo Piombo 1,2 , Ahmed Abdelfattah 3,4 , Samir Droby 5, Michael Wisniewski 6,7, Davide Spadaro 1,8,* and Leonardo Schena 9 1 Department of Agricultural, Forest and Food Sciences (DISAFA), University of Torino, 10095 Grugliasco, Italy; [email protected] 2 Department of Forest Mycology and Plant Pathology, Uppsala Biocenter, Swedish University of Agricultural Sciences, P.O. Box 7026, 75007 Uppsala, Sweden 3 Institute of Environmental Biotechnology, Graz University of Technology, Petersgasse 12, 8010 Graz, Austria; [email protected] 4 Department of Ecology, Environment and Plant Sciences, University of Stockholm, Svante Arrhenius väg 20A, 11418 Stockholm, Sweden 5 Department of Postharvest Science, Agricultural Research Organization (ARO), The Volcani Center, Rishon LeZion 7505101, Israel; [email protected] 6 U.S. Department of Agriculture—Agricultural Research Service (USDA-ARS), Kearneysville, WV 25430, USA; [email protected] 7 Department of Biological Sciences, Virginia Technical University, Blacksburg, VA 24061, USA 8 AGROINNOVA—Centre of Competence for the Innovation in the Agroenvironmental Sector, University of Torino, 10095 Grugliasco, Italy 9 Department of Agriculture, Università Mediterranea, 89122 Reggio Calabria, Italy; [email protected] * Correspondence: [email protected]; Tel.: +39-0116708942 Abstract: Globalization has a dramatic effect on the trade and movement of seeds, fruits and vegeta- bles, with a corresponding increase in economic losses caused by the introduction of transboundary Citation: Piombo, E.; Abdelfattah, A.; plant pathogens. Current diagnostic techniques provide a useful and precise tool to enact surveillance Droby, S.; Wisniewski, M.; Spadaro, protocols regarding specific organisms, but this approach is strictly targeted, while metabarcoding D.; Schena, L. -
Studies on Authentication of True Source of Honey Using Pollen DNA
Journal of Entomology and Zoology Studies 2018; 6(3): 255-261 E-ISSN: 2320-7078 P-ISSN: 2349-6800 Studies on authentication of true source of honey JEZS 2018; 6(3): 255-261 © 2018 JEZS using pollen DNA barcoding Received: 09-03-2018 Accepted: 10-04-2018 Praghadeesh Manivanan Praghadeesh Manivanan, Srinivasan Madapuji Rajagopalan and Department of Plant Mohankumar Subbarayalu Biotechnology, Centre for Plant Molecular Biology& Biotechnology, Tamil Nadu Abstract Agricultural University, Plant pollen DNA comprising unique barcode signatures– serve as a highly resilient biomarker to Coimbatore, Tamil Nadu, India establish its true biological origin. Over a decade, DNA barcoding of plants has evolved as an effective tool to identify its origin down to species level that promptedits practical applications in various fields of Srinivasan Madapuji Rajagopalan applied biology. Premium unifloral honey, due to its economic value as a medicinal product is vulnerable Department of Agricultural to intentional mislabelling and adulteration to fetch higher price. Melissopalynological and Entomology, Tamil Nadu physiochemical based approaches to ascertain the true source of honey is not yet available on commercial Agricultural University, scale. DNA barcoding of pollen trapped in honey can be effectively used to identify the true source of Coimbatore, Tamil Nadu, India honey with high feasibility across labs at cheaper price. The current study was carried out to standardise Mohankumar Subbarayalu an efficient pollen DNA isolation protocol and to assess the efficiency of two barcode (rbcL and matK Professor and Head, Department gene) combinations in identifying the botanical origin of pollen and to ascertain its true source. Six honey of Plant Biotechnology, Centre samples with diverse characteristics were used in the study. -
Using RNA-Seq to Characterize Pollen–Stigma Interactions for Pollination
www.nature.com/scientificreports OPEN Using RNA‑seq to characterize pollen–stigma interactions for pollination studies Juan Lobaton1,3*, Rose Andrew1, Jorge Duitama2, Lindsey Kirkland1, Sarina Macfadyen3 & Romina Rader1 Insects are essential for the reproduction of pollinator‑dependent crops and contribute to the pollination of 87% of wild plants and 75% of the world’s food crops. Understanding pollen fow dynamics between plants and pollinators is thus essential to manage and conserve wild plants and ensure yields are maximized in food crops. However, the determination of pollen transfer in the feld is complex and laborious. We developed a feld experiment in a pollinator‑dependent crop and used high throughput RNA sequencing (RNA‑seq) to quantify pollen fow by measuring changes in gene expression between pollination treatments across diferent apple (Malus domestica Borkh.) cultivars. We tested three potential molecular indicators of successful pollination and validated these results with feld data by observing single and multiple visits by honey bees (Apis mellifera) to apple fowers and measured fruit set in a commercial apple orchard. The frst indicator of successful outcrossing was revealed via diferential gene expression in the cross‑pollination treatments after 6 h. The second indicator of successful outcrossing was revealed by the expression of specifc genes related to pollen tube formation and defense response at three diferent time intervals in the stigma and the style following cross‑pollination (i.e. after 6, 24, and 48 h). Finally, genotyping variants specifc to donor pollen could be detected in cross‑pollination treatments, providing a third indicator of successful outcrossing. Field data indicated that one or fve fower visits by honey bees were insufcient and at least 10 honey bee fower visits were required to achieve a 25% probability of fruit set under orchard conditions. -
Nitritation/Anammox System by an Iterative Hybrid Assembly Method
Liu et al. Microbiome (2020) 8:155 https://doi.org/10.1186/s40168-020-00937-3 RESEARCH Open Access High-quality bacterial genomes of a partial- nitritation/anammox system by an iterative hybrid assembly method Lei Liu1,2,3, Yulin Wang1, You Che1, Yiqiang Chen1, Yu Xia1,2,3, Ruibang Luo4, Suk Hang Cheng5, Chunmiao Zheng2,3* and Tong Zhang1,3* Abstract Background: Genome-centric approaches are widely used to investigate microbial compositions, dynamics, ecology, and interactions within various environmental systems. Hundreds or even thousands of genomes could be retrieved in a single study contributed by the cost-effective short-read sequencing and developed assembly/ binning pipelines. However, conventional binning methods usually yield highly fragmented draft genomes that limit our ability to comprehensively understand these microbial communities. Thus, to leverage advantage of both the long and short reads to retrieve more complete genomes from environmental samples is a must-do task to move this direction forward. Results: Here, we used an iterative hybrid assembly (IHA) approach to reconstruct 49 metagenome-assembled genomes (MAGs), including 27 high-quality (HQ) and high-contiguity (HC) genomes with contig number ≤ 5, eight of which were circular finished genomes from a partial-nitritation anammox (PNA) reactor. These 49 recovered MAGs (43 MAGs encoding full-length rRNA, average N50 of 2.2 Mbp), represented the majority (92.3%) of the bacterial community. Moreover, the workflow retrieved HQ and HC MAGs even with an extremely low coverage (relative abundance < 0.1%). Among them, 34 MAGs could not be assigned to the genus level, indicating the novelty of the genomes retrieved using the IHA method proposed in this study. -
Metabcc-LR: Metagenomics Binning by Coverage and Composition for Long Reads Anuradha Wickramarachchi 1,∗, Vijini Mallawaarachchi 1, Vaibhav Rajan 2 and Yu Lin 1,∗
✐ ✐ “output” — 2020/5/25 — 7:49 — page 1 — #1 ✐ ✐ Bioinformatics doi.10.1093/bioinformatics/xxxxxx Advance Access Publication Date: Day Month Year Manuscript Category Subject Section MetaBCC-LR: Metagenomics Binning by Coverage and Composition for Long Reads Anuradha Wickramarachchi 1,∗, Vijini Mallawaarachchi 1, Vaibhav Rajan 2 and Yu Lin 1,∗ 1Research School of Computer Science, Australian National University, Canberra, ACT 0200, Australia and 2Department of Information Systems and Analytics, School of Computing, National University of Singapore, Singapore 117417. ∗To whom correspondence should be addressed. Associate Editor: XXXXXXX Received on XXXXX; revised on XXXXX; accepted on XXXXX Abstract Motivation: Metagenomics studies have provided key insights into the composition and structure of microbial communities found in different environments. Among the techniques used to analyse metagenomic data, binning is considered a crucial step to characterise the different species of microorganisms present. The use of short-read data in most binning tools poses several limitations, such as insufficient species-specific signal, and the emergence of long-read sequencing technologies offers us opportunities to surmount them. However, most current metagenomic binning tools have been developed for short reads. The few tools that can process long reads either do not scale with increasing input size or require a database with reference genomes that are often unknown. In this paper, we present MetaBCC- LR, a scalable reference-free binning method which clusters long reads directly based on their k -mer coverage histograms and oligonucleotide composition. Results: We evaluate MetaBCC-LR on multiple simulated and real metagenomic long-read datasets with varying coverages and error rates. Our experiments demonstrate that MetaBCC-LR substantially outperforms state-of-the-art reference-free binning tools, achieving ∼13% improvement in F1-score and ∼30% improvement in ARI compared to the best previous tools. -
Fungal Genomes Tell a Story of Ecological Adaptations
Folia Biologica et Oecologica 10: 9–17 (2014) Acta Universitatis Lodziensis Fungal genomes tell a story of ecological adaptations ANNA MUSZEWSKA Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Pawinskiego 5A, 02-106 Warsaw, Poland E-mail: [email protected] ABSTRACT One genome enables a fungus to have various lifestyles and strategies depending on environmental conditions and in the presence of specific counterparts. The nature of their interactions with other living and abiotic elements is a consequence of their osmotrophism. The ability to degrade complex compounds and especially plant biomass makes them a key component of the global carbon circulation cycle. Since the first fungal genomic sequence was published in 1996 mycology has benefited from the technolgical progress. The available data create an unprecedented opportunity to perform massive comparative studies with complex study design variants targeted at all cellular processes. KEY WORDS: fungal genomics, osmotroph, pathogenic fungi, mycorrhiza, symbiotic fungi, HGT Fungal ecology is a consequence of osmotrophy Fungi play a pivotal role both in encountered as leaf endosymbionts industry and human health (Fisher et al. (Spatafora et al. 2007). Since fungi are 2012). They are involved in biomass involved in complex relationships with degradation, plant and animal infections, other organisms, their ecological fermentation and chemical industry etc. repertoire is reflected in their genomes. They can be present in the form of The nature of their interactions with other resting spores, motile spores, amebae (in organisms and environment is defined by Cryptomycota, Blastocladiomycota, their osmotrophic lifestyle. Nutrient Chytrydiomycota), hyphae or fruiting acquisition and communication with bodies. The same fungal species symbionts and hosts are mediated by depending on environmental conditions secreted molecules. -
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Rotimi et al. BMC Bioinformatics (2018) 19:309 https://doi.org/10.1186/s12859-018-2320-1 SOFTWARE Open Access Selection of marker genes for genetic barcoding of microorganisms and binning of metagenomic reads by Barcoder software tools Adeola M. Rotimi1 , Rian Pierneef1,2 and Oleg N. Reva1* Abstract Background: Metagenomic approaches have revealed the complexity of environmental microbiomes with the advancement in whole genome sequencing displaying a significant level of genetic heterogeneity on the species level. It has become apparent that patterns of superior bioactivity of bacteria applicable in biotechnology as well as the enhanced virulence of pathogens often requires distinguishing between closely related species or sub-species. Current methods for binning of metagenomic reads usually do not allow for identification below the genus level and generally stops at the family level. Results: In this work, an attempt was made to improve metagenomic binning resolution by creating genome specific barcodes based on the core and accessory genomes. This protocol was implemented in novel software tools available for use and download from http://bargene.bi.up.ac.za/. The most abundant barcode genes from the core genomes were found to encode for ribosomal proteins, certain central metabolic genes and ABC transporters. Performance of metabarcode sequences created by this package was evaluated using artificially generated and publically available metagenomic datasets. Furthermore, a program (Barcoding 2.0) was developed to align reads against barcode sequences and thereafter calculate various parameters to score the alignments and the individual barcodes. Taxonomic units were identified in metagenomic samples by comparison of the calculated barcode scores to set cut-off values. -
1 Molecular Analysis of Honey Bee Foraging Ecology Dissertation
Molecular analysis of honey bee foraging ecology Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Rodney Trey Richardson Graduate Program in Entomology The Ohio State University 2018 Dissertation Committee Professor Reed Johnson, Advisor Professor Mary Gardiner Professor John Christman Professor Roman Lanno 1 Copyrighted by Rodney Trey Richardson 2018 2 Abstract While numerous factors currently impact the health of honey bees and other pollinating Hymenoptera, poor floral resource availability due to habitat loss and land conversion is thought to be important. This issue is particularly salient in the upper Midwest, a location which harbors approximately 60 percent of the US honey bee colonies each summer for honey production. This region has experienced a dramatic expansion in the area devoted to crop production over the past decade. Consequently, understanding how changes to landscape composition affect the diversity, quality and quantity of available floral resources has become an important research goal. Here, I developed molecular methods for the identification of bee-collected pollen by adapting and improving upon the existing amplicon sequencing infrastructure used for microbial community ecology. In thoroughly benchmarking our procedures, I show that a simple and cost-effective three-step PCR-based library preparation protocol in combination with Metaxa2-based hierarchical classification yields an accurate and highly quantitative pollen metabarcoding approach when applied across multiple plant markers. In Chapter 1, I conducted one of the first ever proof-of-concept studies applying amplicon sequencing, or metabarcoding, to the identification of bee-collected pollen. -
Experimental Quantification of Pollen with DNA Metabarcoding Using
www.nature.com/scientificreports OPEN Experimental quantifcation of pollen with DNA metabarcoding using ITS1 and trnL Sandra Baksay 1*, André Pornon1, Monique Burrus1, Jérôme Mariette2, Christophe Andalo1 & Nathalie Escaravage1 Although the use of metabarcoding to identify taxa in DNA mixtures is widely approved, its reliability in quantifying taxon abundance is still the subject of debate. In this study we investigated the relationships between the amount of pollen grains in mock solutions and the abundance of high- throughput sequence reads and how the relationship was afected by the pollen counting methodology, the number of PCR cycles, the type of markers and plant species whose pollen grains have diferent characteristics. We found a signifcant positive relationship between the number of DNA sequences and the number of pollen grains in the mock solutions. However, better relationships were obtained with light microscopy as a pollen grain counting method compared with fow cytometry, with the chloroplastic trnL marker compared with ribosomal ITS1 and with 30 when compared with 25 or 35 PCR cycles. We provide a list of recommendations to improve pollen quantifcation. Environmental DNA metabarcoding is a molecular method that consists of investigating environmental DNA samples made of complex mixtures of genomes from numerous organisms1. Due to new sequencing technologies and bioinformatics tools, metabarcoding has been increasingly used to identify taxa in environmental samples1 to monitor biodiversity2–4, to investigate ecosystem functioning5 and interaction networks6–8, in both aquatic and terrestrial ecosystems. Nevertheless, its reliability in quantitative approaches, which depend on the match between counts of high-throughput sequence reads and the amount of sampled biological material2, is still the subject of debate9,10. -
Pollen DNA Barcoding: Current Applications and Future Prospects
Page 1 of 43 Pollen DNA barcoding: current applications and future prospects Authors: Karen L. Bell 1, Natasha de Vere 2, Alexander Keller 3, Rodney T. Richardson 4, Annemarie Gous 5,6 , Kevin S. Burgess 7, Berry J. Brosi 1 1Emory University, School of Environmental Sciences, Atlanta, GA, USA 2National Botanic Garden of Wales, Llanarthne, United Kingdom 3Department of Animal Ecology and Tropical Biology, University of Würzburg, Würzburg, Germany 4Department of Entomology, The Ohio State University, Columbus, OH, USA 5Biotechnology Platform , Agricultural Research Council , Pretoria, South Africa 6School of Life Science, University of KwaZulu-Natal, Pietermaritzburg, South Africa 7Columbus State University, Columbus, GA, USA Keywords (3-6): DNA metabarcoding; metagenomics; pollen; palynology; high-throughput sequencing; next-generation sequencing Genome Downloaded from www.nrcresearchpress.com by MICHIGAN STATE UNIV on 04/18/16 1 For personal use only. This Just-IN manuscript is the accepted prior to copy editing and page composition. It may differ from final official version of record. Page 2 of 43 ABSTRACT (<200 words) Identification of the species origin of pollen has many applications, including assessment of plant-pollinator networks, reconstruction of ancient plant communities, product authentication, allergen monitoring, and forensics. Such applications, however, have previously been limited by microscopy-based identification of pollen, which is slow, has low taxonomic resolution, and few expert practitioners. One alternative is pollen DNA barcoding, which could overcome these issues. Recent studies demonstrate that both chloroplast and nuclear barcoding markers can be amplified from pollen. These recent validations of pollen metabarcoding indicate that now is the time for researchers in various fields to consider applying these methods to their research programs. -
Applying Pollen DNA Metabarcoding to the Study of Plant-Pollinator Interactions Karen L
Applying Pollen DNA Metabarcoding to the Study of Plant-Pollinator Interactions Karen L. Bell, Emory University Julie Fowler, Emory University Kevin S. Burgess, The University of Western Australia Emily K. Dobbs, Emory University David Gruenewald, Emory University Brice Lawley, Emory University Connor Morozumi, Emory University Berry Brosi, Emory University Journal Title: Applications in Plant Sciences Volume: Volume 5, Number 6 Publisher: Botanical Society of America: APPS | 2017-06-01 Type of Work: Article | Final Publisher PDF Publisher DOI: 10.3732/apps.1600124 Permanent URL: https://pid.emory.edu/ark:/25593/s3w2z Final published version: http://dx.doi.org/10.3732/apps.1600124 Copyright information: © 2017 Bell et al. Published by the Botanical Society of America This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (http://creativecommons.org/licenses/by-nc-sa/4.0/). Accessed September 26, 2021 6:17 AM EDT Applying Pollen DNA Metabarcoding to the Study of Plant–Pollinator Interactions Author(s): Karen L. Bell, Julie Fowler, Kevin S. Burgess, Emily K. Dobbs, David Gruenewald, Brice Lawley, Connor Morozumi, and Berry J. Brosi Source: Applications in Plant Sciences, 5(6) Published By: Botanical Society of America https://doi.org/10.3732/apps.1600124 URL: http://www.bioone.org/doi/full/10.3732/apps.1600124 BioOne (www.bioone.org) is a nonprofit, online aggregation of core research in the biological, ecological, and environmental sciences. BioOne provides a sustainable online platform for over 170 journals and books published by nonprofit societies, associations, museums, institutions, and presses. Your use of this PDF, the BioOne Web site, and all posted and associated content indicates your acceptance of BioOne’s Terms of Use, available at www.bioone.org/page/terms_of_use.