Navigating the labyrinth: a guide to sequence-based, community ecology of arbuscular mycorrhizal fungi.
Identifieur interne : 001528 ( Main/Curation ); précédent : 001527; suivant : 001529Navigating the labyrinth: a guide to sequence-based, community ecology of arbuscular mycorrhizal fungi.
Auteurs : Miranda M. Hart [Canada] ; Kristin Aleklett [Canada] ; Pierre-Luc Chagnon [Canada] ; Cameron Egan [Canada] ; Stefano Ghignone [Italie] ; Thorunn Helgason [Royaume-Uni] ; Ylva Lekberg [États-Unis] ; Maarja Öpik [Estonie] ; Brian J. Pickles [Canada] ; Lauren Waller [États-Unis]Source :
- The New phytologist [ 1469-8137 ] ; 2015.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- chemical , genetics : DNA, Fungal.
- genetics : Biota, Mycorrhizae.
- methods : High-Throughput Nucleotide Sequencing.
- Computational Biology, Databases, Nucleic Acid, Models, Biological, Specimen Handling.
Abstract
Data generated from next generation sequencing (NGS) will soon comprise the majority of information about arbuscular mycorrhizal fungal (AMF) communities. Although these approaches give deeper insight, analysing NGS data involves decisions that can significantly affect results and conclusions. This is particularly true for AMF community studies, because much remains to be known about their basic biology and genetics. During a workshop in 2013, representatives from seven research groups using NGS for AMF community ecology gathered to discuss common challenges and directions for future research. Our goal was to improve the quality and accessibility of NGS data for the AMF research community. Discussions spanned sampling design, sample preservation, sequencing, bioinformatics and data archiving. With concrete examples we demonstrated how different approaches can significantly alter analysis outcomes. Failure to consider the consequences of these decisions may compound bias introduced at each step along the workflow. The products of these discussions have been summarized in this paper in order to serve as a guide for any researcher undertaking NGS sequencing of AMF communities.
DOI: 10.1111/nph.13340
PubMed: 25737096
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<front><div type="abstract" xml:lang="en">Data generated from next generation sequencing (NGS) will soon comprise the majority of information about arbuscular mycorrhizal fungal (AMF) communities. Although these approaches give deeper insight, analysing NGS data involves decisions that can significantly affect results and conclusions. This is particularly true for AMF community studies, because much remains to be known about their basic biology and genetics. During a workshop in 2013, representatives from seven research groups using NGS for AMF community ecology gathered to discuss common challenges and directions for future research. Our goal was to improve the quality and accessibility of NGS data for the AMF research community. Discussions spanned sampling design, sample preservation, sequencing, bioinformatics and data archiving. With concrete examples we demonstrated how different approaches can significantly alter analysis outcomes. Failure to consider the consequences of these decisions may compound bias introduced at each step along the workflow. The products of these discussions have been summarized in this paper in order to serve as a guide for any researcher undertaking NGS sequencing of AMF communities. </div>
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<Abstract><AbstractText>Data generated from next generation sequencing (NGS) will soon comprise the majority of information about arbuscular mycorrhizal fungal (AMF) communities. Although these approaches give deeper insight, analysing NGS data involves decisions that can significantly affect results and conclusions. This is particularly true for AMF community studies, because much remains to be known about their basic biology and genetics. During a workshop in 2013, representatives from seven research groups using NGS for AMF community ecology gathered to discuss common challenges and directions for future research. Our goal was to improve the quality and accessibility of NGS data for the AMF research community. Discussions spanned sampling design, sample preservation, sequencing, bioinformatics and data archiving. With concrete examples we demonstrated how different approaches can significantly alter analysis outcomes. Failure to consider the consequences of these decisions may compound bias introduced at each step along the workflow. The products of these discussions have been summarized in this paper in order to serve as a guide for any researcher undertaking NGS sequencing of AMF communities. </AbstractText>
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