Literature DB >> 29292539

Scaling up: A guide to high-throughput genomic approaches for biodiversity analysis.

Teresita M Porter1,2, Mehrdad Hajibabaei1.   

Abstract

The purpose of this review is to present the most common and emerging DNA-based methods used to generate data for biodiversity and biomonitoring studies. As environmental assessment and monitoring programmes may require biodiversity information at multiple levels, we pay particular attention to the DNA metabarcoding method and discuss a number of bioinformatic tools and considerations for producing DNA-based indicators using operational taxonomic units (OTUs), taxa at a variety of ranks and community composition. By developing the capacity to harness the advantages provided by the newest technologies, investigators can "scale up" by increasing the number of samples and replicates processed, the frequency of sampling over time and space, and even the depth of sampling such as by sequencing more reads per sample or more markers per sample. The ability to scale up is made possible by the reduced hands-on time and cost per sample provided by the newest kits, platforms and software tools. Results gleaned from broad-scale monitoring will provide opportunities to address key scientific questions linked to biodiversity and its dynamics across time and space as well as being more relevant for policymakers, enabling science-based decision-making, and provide a greater socio-economic impact. As genomic approaches are continually evolving, we provide this guide to methods used in biodiversity genomics.
© 2018 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Keywords:  DNA barcode; biodiversity; bioinformatics; biomonitoring; environment; high-throughput sequencing; metabarcoding; metagenomics

Mesh:

Substances:

Year:  2018        PMID: 29292539     DOI: 10.1111/mec.14478

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  44 in total

1.  Status and trends of terrestrial arthropod abundance and diversity in the North Atlantic region of the Arctic.

Authors:  Mark A K Gillespie; Matthias Alfredsson; Isabel C Barrio; Joseph J Bowden; Peter Convey; Lauren E Culler; Stephen J Coulson; Paul Henning Krogh; Amanda M Koltz; Seppo Koponen; Sarah Loboda; Yuri Marusik; Jonas P Sandström; Derek S Sikes; Toke T Høye
Journal:  Ambio       Date:  2019-03-16       Impact factor: 5.129

Review 2.  Circumpolar terrestrial arthropod monitoring: A review of ongoing activities, opportunities and challenges, with a focus on spiders.

Authors:  Mark A K Gillespie; Matthias Alfredsson; Isabel C Barrio; Joe Bowden; Peter Convey; Stephen J Coulson; Lauren E Culler; Martin T Dahl; Kathryn M Daly; Seppo Koponen; Sarah Loboda; Yuri Marusik; Jonas P Sandström; Derek S Sikes; Jozef Slowik; Toke T Høye
Journal:  Ambio       Date:  2019-04-27       Impact factor: 5.129

3.  Early Life Stages of a Common Broadcast Spawning Coral Associate with Specific Bacterial Communities Despite Lack of Internalized Bacteria.

Authors:  Katarina Damjanovic; Patricia Menéndez; Linda L Blackall; Madeleine J H van Oppen
Journal:  Microb Ecol       Date:  2019-08-21       Impact factor: 4.552

4.  Changes in bovine milk bacterial microbiome from healthy and subclinical mastitis affected animals of the Girolando, Gyr, Guzera, and Holstein breeds.

Authors:  Raphael S Steinberg; Lilian C Silva E Silva; Marcelo R de Souza; Ronaldo B Reis; Patrícia C L da Silva; Gustavo A Lacorte; Jacques R Nicoli; Elisabeth Neumann; Álvaro C Nunes
Journal:  Int Microbiol       Date:  2022-07-15       Impact factor: 3.097

5.  Metagenomic Insights into the Gut Microbiota of Eudrilus eugeniae (Kinberg) and Its Potential Roles in Agroecosystem.

Authors:  Samrendra Singh Thakur; Azhar Rashid Lone; Sailu Yellaboina; Subodh Tambat; Ajar Nath Yadav; Subodh Kumar Jain; Shweta Yadav
Journal:  Curr Microbiol       Date:  2022-08-22       Impact factor: 2.343

6.  Toward global integration of biodiversity big data: a harmonized metabarcode data generation module for terrestrial arthropods.

Authors:  Paula Arribas; Carmelo Andújar; Kristine Bohmann; Jeremy R deWaard; Evan P Economo; Vasco Elbrecht; Stefan Geisen; Marta Goberna; Henrik Krehenwinkel; Vojtech Novotny; Lucie Zinger; Thomas J Creedy; Emmanouil Meramveliotakis; Víctor Noguerales; Isaac Overcast; Hélène Morlon; Anna Papadopoulou; Alfried P Vogler; Brent C Emerson
Journal:  Gigascience       Date:  2022-07-19       Impact factor: 7.658

Review 7.  Potential of Meta-Omics to Provide Modern Microbial Indicators for Monitoring Soil Quality and Securing Food Production.

Authors:  Christophe Djemiel; Samuel Dequiedt; Battle Karimi; Aurélien Cottin; Walid Horrigue; Arthur Bailly; Ali Boutaleb; Sophie Sadet-Bourgeteau; Pierre-Alain Maron; Nicolas Chemidlin Prévost-Bouré; Lionel Ranjard; Sébastien Terrat
Journal:  Front Microbiol       Date:  2022-06-30       Impact factor: 6.064

8.  Comparison of traditional and DNA metabarcoding samples for monitoring tropical soil arthropods (Formicidae, Collembola and Isoptera).

Authors:  Yves Basset; Mehrdad Hajibabaei; Michael T G Wright; Anakena M Castillo; David A Donoso; Simon T Segar; Daniel Souto-Vilarós; Dina Y Soliman; Tomas Roslin; M Alex Smith; Greg P A Lamarre; Luis F De León; Thibaud Decaëns; José G Palacios-Vargas; Gabriela Castaño-Meneses; Rudolf H Scheffrahn; Marleny Rivera; Filonila Perez; Ricardo Bobadilla; Yacksecari Lopez; José Alejandro Ramirez Silva; Maira Montejo Cruz; Angela Arango Galván; Héctor Barrios
Journal:  Sci Rep       Date:  2022-06-24       Impact factor: 4.996

9.  Automated high throughput animal CO1 metabarcode classification.

Authors:  Teresita M Porter; Mehrdad Hajibabaei
Journal:  Sci Rep       Date:  2018-03-09       Impact factor: 4.379

10.  Shotgun sequencing of honey DNA can describe honey bee derived environmental signatures and the honey bee hologenome complexity.

Authors:  Samuele Bovo; Valerio Joe Utzeri; Anisa Ribani; Riccardo Cabbri; Luca Fontanesi
Journal:  Sci Rep       Date:  2020-06-09       Impact factor: 4.379

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