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Comparing Sanger sequencing and high-throughput metabarcoding for inferring photobiont diversity in lichens
The implementation of HTS (high-throughput sequencing) approaches is rapidly changing our understanding of the lichen symbiosis, by uncovering high bacterial and fungal diversity, which is often host-specific. Recently, HTS methods revealed the presence of multiple photobionts inside a single thallu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988838/ https://www.ncbi.nlm.nih.gov/pubmed/29872090 http://dx.doi.org/10.1038/s41598-018-26947-8 |
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author | Paul, Fiona Otte, Jürgen Schmitt, Imke Dal Grande, Francesco |
author_facet | Paul, Fiona Otte, Jürgen Schmitt, Imke Dal Grande, Francesco |
author_sort | Paul, Fiona |
collection | PubMed |
description | The implementation of HTS (high-throughput sequencing) approaches is rapidly changing our understanding of the lichen symbiosis, by uncovering high bacterial and fungal diversity, which is often host-specific. Recently, HTS methods revealed the presence of multiple photobionts inside a single thallus in several lichen species. This differs from Sanger technology, which typically yields a single, unambiguous algal sequence per individual. Here we compared HTS and Sanger methods for estimating the diversity of green algal symbionts within lichen thalli using 240 lichen individuals belonging to two species of lichen-forming fungi. According to HTS data, Sanger technology consistently yielded the most abundant photobiont sequence in the sample. However, if the second most abundant photobiont exceeded 30% of the total HTS reads in a sample, Sanger sequencing generally failed. Our results suggest that most lichen individuals in the two analyzed species, Lasallia hispanica and L. pustulata, indeed contain a single, predominant green algal photobiont. We conclude that Sanger sequencing is a valid approach to detect the dominant photobionts in lichen individuals and populations. We discuss which research areas in lichen ecology and evolution will continue to benefit from Sanger sequencing, and which areas will profit from HTS approaches to assessing symbiont diversity. |
format | Online Article Text |
id | pubmed-5988838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-59888382018-06-20 Comparing Sanger sequencing and high-throughput metabarcoding for inferring photobiont diversity in lichens Paul, Fiona Otte, Jürgen Schmitt, Imke Dal Grande, Francesco Sci Rep Article The implementation of HTS (high-throughput sequencing) approaches is rapidly changing our understanding of the lichen symbiosis, by uncovering high bacterial and fungal diversity, which is often host-specific. Recently, HTS methods revealed the presence of multiple photobionts inside a single thallus in several lichen species. This differs from Sanger technology, which typically yields a single, unambiguous algal sequence per individual. Here we compared HTS and Sanger methods for estimating the diversity of green algal symbionts within lichen thalli using 240 lichen individuals belonging to two species of lichen-forming fungi. According to HTS data, Sanger technology consistently yielded the most abundant photobiont sequence in the sample. However, if the second most abundant photobiont exceeded 30% of the total HTS reads in a sample, Sanger sequencing generally failed. Our results suggest that most lichen individuals in the two analyzed species, Lasallia hispanica and L. pustulata, indeed contain a single, predominant green algal photobiont. We conclude that Sanger sequencing is a valid approach to detect the dominant photobionts in lichen individuals and populations. We discuss which research areas in lichen ecology and evolution will continue to benefit from Sanger sequencing, and which areas will profit from HTS approaches to assessing symbiont diversity. Nature Publishing Group UK 2018-06-05 /pmc/articles/PMC5988838/ /pubmed/29872090 http://dx.doi.org/10.1038/s41598-018-26947-8 Text en © The Author(s) 2018 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Paul, Fiona Otte, Jürgen Schmitt, Imke Dal Grande, Francesco Comparing Sanger sequencing and high-throughput metabarcoding for inferring photobiont diversity in lichens |
title | Comparing Sanger sequencing and high-throughput metabarcoding for inferring photobiont diversity in lichens |
title_full | Comparing Sanger sequencing and high-throughput metabarcoding for inferring photobiont diversity in lichens |
title_fullStr | Comparing Sanger sequencing and high-throughput metabarcoding for inferring photobiont diversity in lichens |
title_full_unstemmed | Comparing Sanger sequencing and high-throughput metabarcoding for inferring photobiont diversity in lichens |
title_short | Comparing Sanger sequencing and high-throughput metabarcoding for inferring photobiont diversity in lichens |
title_sort | comparing sanger sequencing and high-throughput metabarcoding for inferring photobiont diversity in lichens |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988838/ https://www.ncbi.nlm.nih.gov/pubmed/29872090 http://dx.doi.org/10.1038/s41598-018-26947-8 |
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