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Analysis and Interpretation of metagenomics data: an approach
Advances in next-generation sequencing technologies have accelerated the momentum of metagenomic studies, which is increasing yearly. The metagenomics field is one of the versatile applications in microbiology, where any interaction in the environment involving microorganisms can be the topic of stu...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9675974/ https://www.ncbi.nlm.nih.gov/pubmed/36402995 http://dx.doi.org/10.1186/s12575-022-00179-7 |
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author | Navgire, Gauri S. Goel, Neha Sawhney, Gifty Sharma, Mohit Kaushik, Prashant Mohanta, Yugal Kishore Mohanta, Tapan Kumar Al-Harrasi, Ahmed |
author_facet | Navgire, Gauri S. Goel, Neha Sawhney, Gifty Sharma, Mohit Kaushik, Prashant Mohanta, Yugal Kishore Mohanta, Tapan Kumar Al-Harrasi, Ahmed |
author_sort | Navgire, Gauri S. |
collection | PubMed |
description | Advances in next-generation sequencing technologies have accelerated the momentum of metagenomic studies, which is increasing yearly. The metagenomics field is one of the versatile applications in microbiology, where any interaction in the environment involving microorganisms can be the topic of study. Due to this versatility, the number of applications of this omics technology reached its horizons. Agriculture is a crucial sector involving crop plants and microorganisms interacting together. Hence, studying these interactions through the lenses of metagenomics would completely disclose a new meaning to crop health and development. The rhizosphere is an essential reservoir of the microbial community for agricultural soil. Hence, we focus on the R&D of metagenomic studies on the rhizosphere of crops such as rice, wheat, legumes, chickpea, and sorghum. These recent developments are impossible without the continuous advancement seen in the next-generation sequencing platforms; thus, a brief introduction and analysis of the available sequencing platforms are presented here to have a clear picture of the workflow. Concluding the topic is the discussion about different pipelines applied to analyze data produced by sequencing techniques and have a significant role in interpreting the outcome of a particular experiment. A plethora of different software and tools are incorporated in the automated pipelines or individually available to perform manual metagenomic analysis. Here we describe 8–10 advanced, efficient pipelines used for analysis that explain their respective workflows to simplify the whole analysis process. |
format | Online Article Text |
id | pubmed-9675974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96759742022-11-21 Analysis and Interpretation of metagenomics data: an approach Navgire, Gauri S. Goel, Neha Sawhney, Gifty Sharma, Mohit Kaushik, Prashant Mohanta, Yugal Kishore Mohanta, Tapan Kumar Al-Harrasi, Ahmed Biol Proced Online Review Advances in next-generation sequencing technologies have accelerated the momentum of metagenomic studies, which is increasing yearly. The metagenomics field is one of the versatile applications in microbiology, where any interaction in the environment involving microorganisms can be the topic of study. Due to this versatility, the number of applications of this omics technology reached its horizons. Agriculture is a crucial sector involving crop plants and microorganisms interacting together. Hence, studying these interactions through the lenses of metagenomics would completely disclose a new meaning to crop health and development. The rhizosphere is an essential reservoir of the microbial community for agricultural soil. Hence, we focus on the R&D of metagenomic studies on the rhizosphere of crops such as rice, wheat, legumes, chickpea, and sorghum. These recent developments are impossible without the continuous advancement seen in the next-generation sequencing platforms; thus, a brief introduction and analysis of the available sequencing platforms are presented here to have a clear picture of the workflow. Concluding the topic is the discussion about different pipelines applied to analyze data produced by sequencing techniques and have a significant role in interpreting the outcome of a particular experiment. A plethora of different software and tools are incorporated in the automated pipelines or individually available to perform manual metagenomic analysis. Here we describe 8–10 advanced, efficient pipelines used for analysis that explain their respective workflows to simplify the whole analysis process. BioMed Central 2022-11-19 /pmc/articles/PMC9675974/ /pubmed/36402995 http://dx.doi.org/10.1186/s12575-022-00179-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Review Navgire, Gauri S. Goel, Neha Sawhney, Gifty Sharma, Mohit Kaushik, Prashant Mohanta, Yugal Kishore Mohanta, Tapan Kumar Al-Harrasi, Ahmed Analysis and Interpretation of metagenomics data: an approach |
title | Analysis and Interpretation of metagenomics data: an approach |
title_full | Analysis and Interpretation of metagenomics data: an approach |
title_fullStr | Analysis and Interpretation of metagenomics data: an approach |
title_full_unstemmed | Analysis and Interpretation of metagenomics data: an approach |
title_short | Analysis and Interpretation of metagenomics data: an approach |
title_sort | analysis and interpretation of metagenomics data: an approach |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9675974/ https://www.ncbi.nlm.nih.gov/pubmed/36402995 http://dx.doi.org/10.1186/s12575-022-00179-7 |
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