A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling Article Swipe
Melanie K. Hess
,
Suzanne J. Rowe
,
Tracey C. van Stijn
,
Hannah Henry
,
S. M. Hickey
,
Rüdiger Bräuning
,
Alan McCulloch
,
Andrew S. Hess
,
Michelle R. Kirk
,
Sandra Kittelmann
,
Graham R. Wood
,
Peter H. Janssen
,
John C. McEwan
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1101/694133
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1101/694133
Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock, however, these profiles can be difficult and expensive to obtain for thousands of samples. The objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeK I or Pst I, and two bioinformatic pipelines (reference-based and reference-free) were compared to 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n=236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to sequencing. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of host genetics, laboratory and analytical method, and the genetic and phenotypic correlations with methane production. The results suggested that the best method was Pst I RE-RRS analyzed with the reference-free approach via a correspondence analysis, with estimates for repeatability of 0.62±0.06, heritability 0.31±0.29, and genetic and phenotypic correlation with methane emissions of 0.88±0.25 and 0.64±0.05 respectively for the first component of correspondence analysis. The reference-free approach assigned 62.0±5.7% of reads to common 65 bp tags, much higher than the reference-based approach of 6.8±1.8% of reads assigned. Sensitivity studies suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, therefore the current work of 118 samples/lane and future proposed 384 samples/lane are well within that threshold. Our approach is now being used to investigate host factors affecting the rumen and its association with a variety of production and environmental traits. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/694133
- https://www.biorxiv.org/content/biorxiv/early/2019/07/05/694133.full.pdf
- OA Status
- green
- Cited By
- 2
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2954025836
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2954025836Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/694133Digital Object Identifier
- Title
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A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profilingWork title
- Type
-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-07-05Full publication date if available
- Authors
-
Melanie K. Hess, Suzanne J. Rowe, Tracey C. van Stijn, Hannah Henry, S. M. Hickey, Rüdiger Bräuning, Alan McCulloch, Andrew S. Hess, Michelle R. Kirk, Sandra Kittelmann, Graham R. Wood, Peter H. Janssen, John C. McEwanList of authors in order
- Landing page
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https://doi.org/10.1101/694133Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2019/07/05/694133.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2019/07/05/694133.full.pdfDirect OA link when available
- Concepts
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Rumen, Repeatability, Biology, Heritability, Metagenomics, Computational biology, DNA sequencing, Genetic diversity, Biotechnology, Genetics, Food science, Gene, Chemistry, Chromatography, Population, Demography, Fermentation, SociologyTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2022: 1, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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30Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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